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E-Service Quality Expectations: A Case Study

  • Marketing & Supply Chain Management

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  • 10.1080/1478336032000047255

T1 - E-Service Quality Expectations: A Case Study

AU - van Riel, A.C.R.

AU - Semeijn, J.

AU - Janssen, W.

PY - 2003/1/1

Y1 - 2003/1/1

N2 - The paper is based on an empirical investigation of the effects of customer disposition on two levels of expectations regarding e-service quality: adequate and desired quality. Previous research indicates that customers have distinct levels of expectations with respect to the quality they desire and the quality they will find adequate in a service. The difference between these two levels is known as the "zone of tolerance'. To investigate quality expectations concerning online service offerings, a recent study on the effect of the disposition of a customer towards traditional services and the zone of tolerance was replicated in an online context. Results indicate that online customers have the smallest zone of tolerance for the two quality dimensions they find most important: security and reliability. Furthermore, positively predisposed online customers appear to be more demanding with respect to service quality. Implications for online service providers are formulated.

AB - The paper is based on an empirical investigation of the effects of customer disposition on two levels of expectations regarding e-service quality: adequate and desired quality. Previous research indicates that customers have distinct levels of expectations with respect to the quality they desire and the quality they will find adequate in a service. The difference between these two levels is known as the "zone of tolerance'. To investigate quality expectations concerning online service offerings, a recent study on the effect of the disposition of a customer towards traditional services and the zone of tolerance was replicated in an online context. Results indicate that online customers have the smallest zone of tolerance for the two quality dimensions they find most important: security and reliability. Furthermore, positively predisposed online customers appear to be more demanding with respect to service quality. Implications for online service providers are formulated.

U2 - 10.1080/1478336032000047255

DO - 10.1080/1478336032000047255

M3 - Article

SN - 0954-4127

JO - Total Quality Management

JF - Total Quality Management

To read this content please select one of the options below:

Please note you do not have access to teaching notes, total quality management from theory to practice: a case study.

International Journal of Quality & Reliability Management

ISSN : 0265-671X

Article publication date: 1 May 1993

Most quality professionals recommend a core set of attributes as the nucleus of any quality improvement process. These attributes include: (1) clarifying job expectations; (2) setting quality standards; (3) measuring quality improvement; (4) effective super‐vision; (5) listening by management; (6) feedback by management; and (7) effective training. Based on a survey of employees at a medium‐sized manufacturing firm in the United States, it was found that management philosophy and actions can undermine even a proven total quality management (TQM) programme. For the many firms which hire outside consultants to set up a TQM programme, makes recommendations to management to ensure its successful implementation.

  • MANAGEMENT PHILOSOPHY
  • QUALITY ASSURANCE
  • QUALITY MANAGEMENT

Longenecker, C.O. and Scazzero, J.A. (1993), "Total Quality Management from Theory to Practice: A Case Study", International Journal of Quality & Reliability Management , Vol. 10 No. 5. https://doi.org/10.1108/02656719310040114

Copyright © 1993, MCB UP Limited

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CUSTOMERS QUALITY EXPECTATIONS AND ACCEPTANCE CRITERIA  

  December 27, 2020

By   Dave Litten

Customers Quality Expectations and Acceptance Criteria

The customer’s quality expectations.

It is normally not an easy task to extract the Quality Expectations of a product from a client and the answers you get can be very vague, but this must be done and must be done as early as possible in the project so they can be listed in detail in the Project Product Description.

Some companies may be in a rush to get the product out or they may have budgetary issues so they think they can save on Quality.

Customers Quality Expectations And Acceptance Criteria

I have even seen projects where there funds were scarce at the start of the project, but once the product is out and customers are having issues, then lots of funds are available to start fixing. This approach is always a lot more expensive.

Let us look at some good questions to ask to get the customer focused on Quality:

  • What % of features should work when product is launched, and what is the budget for critical issues, fixes, recalls etc.?
  • What will be the cost to the company if the product cannot be used as expected at the end of the project (e.g., fines, keeping old product in service, etc.)?

As you can imagine, this should help the customer to see the importance of Quality.

Some good questions to ask to uncover the Quality Expectations are:

  • What are the key requirements for the Project Product (Project Product refers to the main product that will be produced)?
  • What standards need to be applied to achieve the Quality requirements? (Note: For the building, there could be building code standards.)
  • What are the measurements that can be used to assess whether the products meet the Quality requirements? For example, with the apartment block a building surveyor can check the structure, and another specialist can be used to check heat-loss and insulation.

As you can expect, the higher Quality requirements will have an effect on the time and cost of the project.

For example, the client may want a high-standard and low-energy apartment block. This will require triple-glazed windows, thicker insulation, and all fittings with a guarantee of 20 years.

Important things to remember on Customer’s Quality Expectations:

  • They must be listed in detail and with tolerance levels
  • They should be prioritized, starting with what the client finds most important
  • It is good Project Management to review the customer’s Quality Expectations to make sure the project can meet them.

Prioritize technique: MoSCoW

It stands for

  • M ust have ,
  • S hould have,
  • C ould have,
  • W on’t have for now

You can also use: High, Medium, Low or Not Required but MoSCoW is better

Acceptance Criteria

The Acceptance Criteria is a prioritized list of attributes that the Project Product should have when complete. This is first agreed between the Customer and Supplier in the very first process, the Starting Up a Project process.

Once the Acceptance Criteria list is complete, it will become part of the Project Brief.

The Project Product Description is written around the same time as the Acceptance Criteria and both can be updated during the Initiating a Project process.

This Acceptance Criteria will be baselined with the rest of the Project Initiation Documentation and can only be changed with approval from the Project Board.

As mentioned, the Acceptance Criteria should also be prioritized and the MoSCoW technique can be used to do this by separating requirements into

  • Should have,
  • Could have &
  • Won’t have for now.

Toward the end of the project, the customer will check that all the Acceptance Criteria have been met before the project can be closed. It is therefore a good idea to have agreed in advance on the acceptance methods that will be used.

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David spent 25 years as a senior project manager for USA multinationals, and has deep experience in project management. He now develops a wide range of Project Management Masterclasses, under the Projex Academy brand name. In addition, David runs project management training seminars across the world, and is a prolific writer on the many topics of project management.

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AI is becoming deeper ingrained in our industry, and innovative technologies and processes, driven by LLMs and GenAI, are being announced left and right. It can be hard to navigate between the oneirisms and the applications with actual transformative power. When it comes to quality estimation, the advancements over the past year are significant. Significant enough to analyze the real-world impact it has on companies who have successfully integrated a quality estimation step into their workflows. In this blog, we’ll take a closer look at the various real-world use cases and benefits of quality estimation.

Quality Estimation in Content Workflows

Global communication and access to information in our native language are paramount in our interconnected world, making the accuracy of translated content foundational for success. As the volume of content grows, so does the need for translation in an expanding variety of languages. The result is an abundance of content that exceeds human capacities. While machine translation addresses the initial translation step, quality estimation can play a pivotal role in the subsequent steps of reviewing and post-editing the translations. The use cases are clear: from risk management to minimizing human review, to evaluating and choosing the best performing MT engines. However, let’s take a closer look at the concrete benefits that quality estimation has for active users of the TAUS Estimate API.

1. Mitigating risk in global chat communication

Global technology companies that manage thousands of chat messages, being sent between users and agents, turn to machine translation to get the message across faster. But how do they ensure the correctness of the information and the quality of the translation? Here’s where quality estimation can make a serious difference. By integrating TAUS Estimate API into their workflows, a leading technology company experienced a significant improvement in the accuracy and reliability of their machine-generated translations. Using language data from the TAUS Data Repository, synthetic data created with LLMs and a sample of data form the client, TAUS trained a custom model that reflects the client’s unique content and quality expectations. Now, processing millions of characters through the API per day, the company is achieving increased operational efficiency, reduced post-editing efforts and substantial cost savings. Concrete benefits: an impressive 85% accuracy rate and rolling out content 3 times faster. 

Read the full case study here.

2. Minimizing post-editing in MT workflows

Global technology and language providers have now widely adopted machine translation, but are still struggling with the amount of time it takes to review all of the MT before it gets sent out to the client (or published). Integrating a quality estimation step into this workflow gives insights into the quality of the MT and thus helps companies focus human effort only where needed. Through implementing TAUS Estimate API, a global technology solutions provider witnessed a substantial improvement in the efficiency of their MT processes. TAUS quality estimation capabilities proved instrumental in predicting the MT quality, reducing the need for extensive post-editing for almost 30% of their content. This not only led to significant time savings, but also increased productivity, ultimately resulting in improved translation output and cost-savings. 

Transforming potential into reality

While our content workflows and the technologies we use keep evolving, quality estimation is turning potential into reality. Analyzing these real-world applications of the TAUS Estimate API and the benefits it has brought to these companies, it’s evident that accurate quality estimation is not just a theoretical concept; it's a recipe for success. 

With a generic model that is available in 100+ languages and the ability to train custom models tailored to your unique content and quality expectations, the TAUS Estimate API has become an indispensable tool for a productive and efficient content workflow. Get in touch now to get a complementary custom model with your first credit bundle purchase.

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Anne-Maj van der Meer is a marketing professional with over 10 years of experience in event organization and management. She has a BA in English Language and Culture from the University of Amsterdam and a specialization in Creative Writing from Harvard University. Before her position at TAUS, she was a teacher at primary schools in regular as well as special needs education. Anne-Maj started her career at TAUS in 2009 as the first TAUS employee where she became a jack of all trades, taking care of bookkeeping and accounting as well as creating and managing the website and customer services. For the past 5 years, she works in the capacity of Events Director, chief content editor and designer of publications. Anne-Maj has helped in the organization of more than 35 LocWorld conferences, where she takes care of the program for the TAUS track and hosts and moderates these sessions.

quality expectations case study

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  • v.70(2); 2016 Apr

Patients’ Expectations and Perceptions of Service Quality in the Selected Hospitals

Aliasghar nadi.

1 Health Sciences Research Center, Faculty of Health, Mazandaran University of Medical Sciences, Sari, Iran

Jalil Shojaee

Ghassem abedi.

2 Faculty of Health, Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran

Hasan Siamian

3 Health Information Technology Department, School of Allied Medical Sciences, Mazandaran University of Medical Sciences Sari, Mazandaran, Iran

Ehsan Abedini

Farideh rostami, background:.

Hospital’s success depends on patients’ expectations, perceptions, and judgment on the quality of services provided by hospitals. This study was conducted to assess the patients’ perceptions and expectations from the quality of inpatient health care in Vali-Asr hospital, Ghaemshahr, and Imam Khomeini and Shafa Hospitals, Sari.

Materials and Methods:

This study is applied regarding the objective of the study. Considering the research methodology, it is a descriptive – analytical study. The sample of this study consists of 600 patients with at least 24 hours of being hospitalized in internal, surgery, women, and children sectors of Vali-Asr, Ghaemshahr, Imam Khomeini, and Shafa Hospitals. Using random sampling method, the classifications relevant to the size of each class were selected. The data required was collected through the standard SERVQUAL questionnaire and then it was analyzed using the SPSS software.

The overall mean value and standard deviation of expectations were equal to 10.4 and 28, respectively. The mean value for the field of perception was 69.2 and the relevant standard deviation was 26. In terms of patients and hospital visits in concrete cases, the highest priority is related to empathy. The second priority is related to physical appearance, the third priority is related to responsiveness, the fourth priority is related to assurance, and the lowest priority is related to the reliability of the SERVQUAL approach. Examining the gap between patients’ perceptions and expectations, the widest gap was observed in the Vali-Asr Hospital with the mean and SD (-92.0±39.0) and the lowest gap was observed in Shafa Hospital with the mean value of (-39.9±44.0). According to The Kruskal–Wallis test, the difference observed in these three hospitals were significant.

Conclusion:

The results showed that patients’ expectations had not been met in any of the examined dimensions and their consent has not been achieved. It seemed that necessary for managers and relevant authorities to plan and pay special attention to this important issue.

1. INTRODUCTION

The main mission of hospitals is to provide quality care services for patients and to meet their needs and expectations. Fulfilling this important mission requires the quality institutionalization in hospitals ( 1 ). Accordingly, in 1983, the America National Health Service passed law that all health care centers in America should use the recipients’ comments in setting their plans and consider these comments in the evaluation of training programs designed for the staff. Despite the increased number of hospitals and hospital activities, the improved quality of health care services has become a priority concern for patients ( 2 ). The quality of health services in many countries, especially developing and Third World countries has become a pressing issue. In our country, patients are always looking for a hospital with better quality of health care services. Therefore, better service qualities can be considered as a means to achieve more support, competitive advantage, and long-term profitability ( 3 ). Today, quality is defined by customers’ demand & customer’s perceptions and expectations are considered as the most fundamental determinant factors of quality ( 4 ). Providing sufficient information on the grounds of the customer’s perception of the service quality can help organizations to identify the dimensions that affect the organization’s competitive advantage. On the other hand, it can prevent the wasting of resources ( 5 ). In order to determine the gap of the service quality in hospitals and health care centers, the SERVQUAL approach has been used in many studies. This service conceptual model was introduced in 1985 by Parasuraman et al. This tool measures the patients’ perceptions and expectations of services in 5 different dimensions, including physical or concrete dimensions, reliability, responsiveness, assurance, and empathy. The difference between customer’s expectations and perceptions of service provided is called the service quality gap ( 6 ). Successful organizations are trying to meet the environmental demands and needs and this is not made possible unless organizations understand the need to move towards being customer-centered. In fact, customer-centered organizations set their activities based on the expectations and preferences of their customers and are to satisfy the needs and expectations of customers and considering their expectations as service quality standards is of essence ( 7 ). Hospitals are the most important element of the health care system and in terms of resources, about half of health care costs is allocated to them account since the largest and most expensive operational units are health care systems attracting a majority of capital, financial, and human resources ( 8 - 11 ).

Considering that patients compare the quality of services in health systems with their expectations, in order to assess the gap between the expectations and perceptions of service quality, patients’ expectations and perceptions of service quality in Mazandaran University of Medical Sciences was evaluated in 2014. Determining the gap of quality services provided by the health centers, this study was to provide the proper grounds for the development of programs and projects by authorities and service suppliers to increase patients’ satisfaction with services.

2. MATERIALS AND METHODS

This study is applied regarding the objective of the study. Considering the research methodology, it is a descriptive – analytical study. In terms of data collection, it is regarded as a survey. Two methods were used to gather information: library method and the standard SERVQUAL questionnaire. This questionnaire consists of general questions (age, sex, marital status, education, hospitalization records of Imam Khomeini Hospital, the number of hospitalizations in this Hospital, length of hospitalization) as well as 22 questions in the areas of concrete cases (questions 1 to 4), reliability (questions 5 to 9), responsiveness (questions 10 to 13), assurance (questions 14 and 17), and empathy (questions 18 and 22) in a5-pointLikert scale (strongly disagree, disagree, indifferent, agree and strongly agree), respectively. To calculate the validity of the questionnaire, content validity was used in the way that, considering the questionnaire being standard, professors of this field were also consulted with and the content validity was approved.

To test the reliability, internal consistency (Cronbach’s alpha) was used and the values of Cronbach’s alpha were equal to .88 for service quality dimension, .83 for concrete cases, .87 for reliability, .90 for responsiveness, .91 for assurance, and .80 for empathy. The study population included those patients with at least 24 hours of being hospitalized in internal, surgery, women, and children sectors of Vali-Asr, Ghaemshahr, Imam Khomeini, and Shafa Hospitals. According to the statistics of 2013, there were 10,000 people. Groups of samples (subjects) were selected using stratified random sampling method in which the hospital sector is regarded as a class and the sample size in each class was also selected proportional to the size of the class. Moreover, the sample size was determined to be 622 subjects by using Cochran formula (with Type I error of .01, estimation error of 5%, and p-value of .5). In order to make comparison between the current and desired status of the test and to determine the priority of services provided, paired sample t-test and Friedman’s rank test were used, respectively.

The gender distribution of respondents in the study showed that they consists of 161 men (26.8%) and 439 women (2/73 percent). Regarding the marital status of respondents, 64 persons were single (10.7%) and 536 persons were married (3/89 percent). Regarding respondents’ age, table of descriptive statistics in this study showed that the average age, median, mode, standard deviation, minimum, and maximum were 39.94, 38, 37, 10.99, 5, and 70, respectively. With regard to patients’ level of education, it was observed that there were 36 illiterate persons (6%), 79 below-diploma persons (13.2 percent), 161 persons diploma persons (26.8 percent), 34 persons AA holders (7.5 per cent), 242 persons BA holders (3/40 percent), and 48 persons MA or PHD holder (8%). Descriptive statistics of the distribution of patients in hospital sectors showed that there were 180 persons in the interior section (almost 30%), 150 persons in general surgery sector (25 percent), 168 persons in women sector (28 percent), 102 persons in children sector (17%). Finally, in the case of hospitals’ descriptive statistics, results showed that there were 290 persons hospitalized in Sari Imam Khomeini Hospital (3/48 percent), 170 persons in Sari Shafa hospital (28.4%) and 140 persons in Ghaemshahr Vali-Asr hospital (23.3 percent).

After collecting data on study variables and running Kolmogorov-Smirnov test, the results showed that all variables in both areas of perceptions and expectations are abnormal. Then, Binomial test was used to check the status of the variables examined. As it is observed, since the 5-point Likert-scaled questionnaire was used, we have to check the status of perception and its dimensions by the Binomial test. In this test, the cut-off point is regarded 3. The ratio of people with scores less than 3 is compared with the ratio of people with scores greater than 3. If the sig . value is less than .05, the equality hypothesis of these two categories is rejected and is determined if it is appropriate or inappropriate. Regarding the scores in perceptions, all 600 participants obtained a score greater than 3. It means that 100 percent of participants in the study obtained the perception scores greater than 3, which is a satisfactory score. Overall, it can be said that the perception score in the hospitals under consideration is greater than average. On the other hand, according to the above table, the perception dimension scores have the same condition and are higher than the average. To check the gap between perception and expectation scores, paired Wilcoxon test was used. As it is observed in Table 2 , the total mean value for expectation is 4.06 and the standard deviation is equal to 0.45. The mean and standard deviation of perception is equal to 0.4 and 0.33, respectively. According to Wilcoxon Z value of -19.77 and the sig. value which is less than 0.05, the hypothesis of mean equality for expectations and perceptions is rejected. This means that there is a significant difference between the visitors and patients’ expectations and perceptions in Sari Imam Khomeini Hospital, Ghaemshahr Vali-Asr Hospital, and Sari Shafa Hospital. The mean and standard deviation of concretes in the field of expectation are 4.62 and 0.47, respectively. The mean and standard deviation of concretes in the field of perception are 4.62 and 0.47, respectively. Regarding the t -value of -19.45 and sig . value being less than 0.05, the equality hypothesis for concrete mean scores in both fields of expectation and perception is rejected. The mean and standard deviation of reliability in the field of expectation are 4.62 and 0.47, respectively. The mean and standard deviation of reliability in the field of perception are 4.31 and 0.36, respectively. Regarding the z -value of -13.12 and sig . value being less than 0.05, the equality hypothesis of reliability mean scores in both fields of expectation and perception is rejected. The mean and standard deviation of responsiveness in the field of expectation are 4.61 and 0.47, respectively. The mean and standard deviation of responsiveness in the field of perception are 3.89 and 0.46, respectively. Regarding the z -value of -19.27 and sig . value being less than .05, the equality hypothesis of responsiveness mean scores in both fields of expectation and perception is rejected. The mean and standard deviation of assurance in the field of expectation are 4.61 and 0.46, respectively. The mean and standard deviation of assurance in the field of perception are 3.82 and 0.48, respectively. Regarding the z -value of -26.30 and sig . value being less than 0.05, there is a significant difference between the visitors and patients’ expectations and perceptions with regard to assurance dimension in Sari Imam Khomeini Hospital. Finally, the mean and standard deviation of empathy in the field of expectation are 4.60 and 0.47, respectively. The mean and standard deviation of empathy in the field of perception are 3.97 and .34, respectively. Regarding the z -value of -38.18 and sig . value being less than 0.05, the equality hypothesis of empathy mean scores in both fields of expectation and perception is rejected. As a result, there is a significant difference between the visitors and patients’ expectations and their perception in all dimensions examined in Sari Imam Khomeini Hospital and the patients’ satisfactions in these fields have not been met. In this part, we are to explain in which field the gap between the perceptions and expectations is more. To this end, Friedman test is used. As it is observed in Table 3 , the greatest gap is for assurance with the mean of -0.78, standard deviation of .52, and rank mean of 2.27. The smallest gap is related to reliability with the mean and SD (0.52±4.83) With regard to Friedman statistics of 664.34 and the sig . value being less than 0.05, the equality hypothesis is rejected and the result is that the difference between the gaps in the different areas is unequal.

Reviewing the current status of the variables of perceptions based on Binomial test

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Paired Wilcoxon test to examine the differences between the perceptions and expectations

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Examining the gap in the field of perceptions and expectations using Friedman Test names of average rating

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EExamining the gap differences and its dimensions using the Kruskal-Wallis test

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As it can be observed in the above table, the results of Kruskal-Wallis test show that, the greatest gap of the three hospitals was related to Sari Shafa Hospital with the mean of -0.92 and standard deviation of .39. The lowest gap was in Vali-Asr Hospital with the mean of -0.39 and the standard deviation of 0.44. Moreover, the amount of gap in Sari Imam Khomeini Hospital was -0.35with the standard deviation of 0.04. According to the Kruskal-Wallis statistics and the sig . value being less than .05, the difference observed among the three hospitals was significant.

4. DISCUSSION

The results showed that the greatest gap of the three hospitals with regard to the dimensions of concretes, reliability, responsiveness, assurance, and empathy was related to Sari Shafa Hospital and the lowest gap for the dimensions discussed was observed in Ghaemshahr Vali-Asr Hospital. According to the statistics and the sig . value which is less than .05, a significant difference was observed among these three hospitals. Examining the gap in perceptions and expectations, the greatest gap was related to the dimensions of assurance and the lowest gap was relevant to reliability and the difference between the gaps in the different areas is unequal. In none of the surveyed dimensions, patients’ expectations have not been met and their consent has not been obtained. The results of a study conducted by Tabibi, et al. showed that there is a significant difference among the patients’ perceptions and expectations regarding 5 dimensions of service quality in these hospitals. Patients visiting the clinics ranked assurance with the score of 4.41 and personnel’s responsiveness with the score of 2.21 as the most important and the least important dimensions ( 11 ). However, the findings of the Havasbeigi’s study also showed significant differences among the patients’ perceptions and expectations regarding five dimensions of service quality in the hospitals. Patients visiting the clinics ranked concreteness with the score of 3.47 and assurance with the score of 2.06 as the most important and the least important dimensions ( 12 ). Hekmatpour’s et al. study examined the quality of health care in Arak hospitals and showed there are significant differences among all dimensions of patients’ expectations and perceptions from service quality and patients’ perception of quality in none of the dimensions was consistent with their expectations. It means that all hospitals failed to meet patients’ expectations in any of the quality dimensions. Moreover, the overall rate of perceived service quality does not correspond to patients’ average expectations. However, in Hekmatpour’ study, the greatest quality gap was related to access to health care dimension and the lowest gap was relevant to service assurance. This is not compatible with the current study ( 13 ). Also, in all of domains of services in Caha study, patients’ expectations of the services provided were higher than their perceptions and the gaps between patients’ perceptions and their expectations were negative. The highest negative gap was in responsiveness dimension and the lowest negative gap was in assurance dimension. The negative gaps indicate that patients’ expectations of the services provided are higher than their perceptions ( 14 ). In a study by Sabahi et al., to evaluate the hospitals’ service quality from the perspective of patients being hospitalized, the results showed that the mean score was significant for all dimensions in hospitals and the highest and lowest quality scores were relevant to empathy and concreteness, respectively ( 15 ). It was observed from the results of Abedi study, in perception part; there was a significant difference in all groups except for responding and behavior, while, in expectation level, no significance in the age of the dimensions except for access. Also, the satisfaction status of patients in Imam Hospital clinic in Sari was good ( 16 ). Several factors can create a gap between the patients’ expectations and perceptions. In Ranjbar et al. paying attention to the health care of the patient’s room, removing patients’ problems during hospitalization, a commitment to providing quality service, and providing the appropriate, clean, and beautiful physical environment are the most important problematic factors. Moreover, using proper equipment, prioritizing tasks in rush hours, having clean clothes while providing services are the most critical factors in Yazd Afshar Hospital ( 17 ). The results revealed that there is a gap between the expected and perceived quality of hospital patients. Patients’ expectations are beyond their understanding of the current situation and none of the aspects of the service is met in their expectations. However, patients’ expectations in both concretes and responsiveness of service quality and received service qualities are more than other dimensions and service quality has been downloaded more than other aspects. And these two dimensions had the greatest impact on service quality gap. In Mahdizadeh’ study, these factors and cooperation in evaluating the quality of health care and hospitalized patients’ satisfaction using newly developed SERVQUAL method in physical environment and facilities showed that the patients’ expectation score in all aspects was higher than their perception score and the most gap was related to concretes and the lowest gaps was observed in responsiveness ( 18 ). The problem of service quality is mostly related to those organizations which do not focus on understanding and meeting customers’ needs and demands. The service organization should put themselves in their customers’ boat and lay their own policies on the basis of their views. Lack of direct relationship with customers leads the customers’ expectations not to meet. As a result, there would be a controversy among customers regarding the service quality provided and security factors ( 19 ). This study and other studies conducted in hospitals and other health care centers show that patients’ expectations are not met in none of the aspects and they are not satisfied. The negative gap (expectations more than perceptions) in all dimensions of quality showed that it is necessary to improve service quality in all dimensions. In order to lessen the gap of all five dimensions of quality and provide desired services, it is recommended that hospital managers by planning and their optimal management take the patients’ needs into account ( 20 ). This necessitates managers and the relevant authorities, special attention to planning. In addition, the proper use of tools such as SERVQUAL seems necessary in evaluating hospitals’ service quality and in enabling managers and experts to identify the grievances. And since the difference between customers’ expectations and their received services increases over time regardless of the new approaches or actions, hospital authorities should implement expectation management through which they become aware of the source or sources of the customers’ expectation formation and become sure of their customers’ logical needs, their own abilities and their organization’s capabilities in meeting the patients’ needs.

Acknowledgment

The authors gratefully acknowledge the study team. The study was supported by a grant from the Health Sciences Research Center, Mazandaran University of Medical Sciences.

• Author’s contribution: all authors were included in all phases of preparing this article, including final proof reading.

• Conflict of interest: none declared.

  • Open access
  • Published: 19 February 2024

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  • Hannah M. Bailey 1 ,
  • Lauren M. Sippel 6 , 7 ,
  • Kendra Weaver 8 &
  • Christopher J. Miller 1 , 2  

Implementation Science volume  19 , Article number:  16 ( 2024 ) Cite this article

Metrics details

Sustaining evidence-based practices (EBPs) is crucial to ensuring care quality and addressing health disparities. Approaches to identifying factors related to sustainability are critically needed. One such approach is Matrixed Multiple Case Study (MMCS), which identifies factors and their combinations that influence implementation. We applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM) at nine Department of Veterans Affairs (VA) outpatient mental health clinics, 3–4 years after implementation support had concluded.

We conducted a directed content analysis of 30 provider interviews, using 6 CCM elements and 4 Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) domains as codes. Based on CCM code summaries, we designated each site as high/medium/low sustainability. We used i-PARIHS code summaries to identify relevant factors for each site, the extent of their presence, and the type of influence they had on sustainability (enabling/neutral/hindering/unclear). We organized these data into a sortable matrix and assessed sustainability-related cross-site trends.

CCM sustainability status was distributed among the sites, with three sites each being high, medium, and low. Twenty-five factors were identified from the i-PARIHS code summaries, of which 3 exhibited strong trends by sustainability status (relevant i-PARIHS domain in square brackets): “Collaborativeness/Teamwork [Recipients],” “Staff/Leadership turnover [Recipients],” and “Having a consistent/strong internal facilitator [Facilitation]” during and after active implementation. At most high-sustainability sites only, (i) “Having a knowledgeable/helpful external facilitator [Facilitation]” was variably present and enabled sustainability when present, while (ii) “Clarity about what CCM comprises [Innovation],” “Interdisciplinary coordination [Recipients],” and “Adequate clinic space for CCM team members [Context]” were somewhat or less present with mixed influences on sustainability.

Conclusions

MMCS revealed that CCM sustainability in VA outpatient mental health clinics may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators. These findings have informed a subsequent CCM implementation trial that prospectively examines whether enhancing the above-mentioned factors within implementation facilitation improves sustainability. MMCS is a systematic approach to multi-site examination that can be used to investigate sustainability-related factors applicable to other EBPs and across multiple contexts.

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Contributions to the literature

We examined the ways in which the sustainability of the evidence-based Collaborative Chronic Care Model differed across nine outpatient mental health clinics where it was implemented.

This work demonstrates a unique application of the Matrixed Multiple Case Study (MMCS) method, originally developed to identify factors and their combinations that influence implementation, to investigate the long-term sustainability of a previously implemented evidence-based practice.

Contextual influences on sustainability identified through this work, as well as the systematic approach to multi-site examination offered by MMCS, can inform future efforts to sustainably implement and methodically evaluate an evidence-based practice’s uptake and continued use in routine care.

The sustainability of evidence-based practices (EBPs) over time is crucial to maximize the public health impact of EBPs implemented into routine care. Implementation evaluators focus on sustainability as a central implementation outcome, and funders of implementation efforts seek sustained long-term returns on their investment. Furthermore, practitioners and leadership at implementation sites face the task of sustaining an EBP’s usage even after implementation funding, support, and associated evaluation efforts conclude. The circumstances and influences contributing to EBP sustainability are therefore of high interest to the field of implementation science.

Sustainability depends on the specific EBP being implemented, the individuals undergoing the implementation, the contexts in which the implementation takes place, and the facilitation of (i.e., support for) the implementation. Hence, universal conditions that invariably lead to sustainability are challenging to establish. Even if a set of conditions could be identified as being associated with high sustainability “on average,” its usefulness is questionable when most real-world implementation contexts may deviate from “average” on key implementation-relevant metrics.

Thus, when seeking a better understanding of EBP sustainability, there is a critical need for methods that examine the ways in which sustainability varies in diverse contexts. One such method is Matrixed Multiple Case Study (MMCS) [ 1 ], which is beginning to be applied in implementation research to identify factors related to implementation [ 2 , 3 , 4 , 5 ]. MMCS capitalizes on the many contextual variations and heterogeneous outcomes that are expected when an EBP is implemented across multiple sites. Specifically, MMCS provides a formalized sequence of steps for cross-site analysis by arranging data into an array of matrices, which are sorted and filtered to test for expected factors and identify less expected factors influencing an implementation outcome of interest.

Although the MMCS represents a promising method for systematically exploring the “black box” of the ways in which implementation is more or less successful, it has not yet been applied to investigate the long-term sustainability of implemented EBPs. Therefore, we applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM), previously implemented using implementation facilitation [ 6 , 7 , 8 ], at nine VA medical centers’ outpatient general mental health clinics. An earlier interview-based investigation of CCM provider perspectives had identified key determinants of CCM sustainability at the sites, yet characteristics related to the ways in which CCM sustainability differed at the sites are still not well understood. For this reason, our objective was to apply MMCS to examine the interview data to determine factors associated with CCM sustainability at each site.

Clinical and implementation contexts

CCM-based care aims to ensure that patients are treated in a coordinated, patient-centered, and anticipatory manner. This project’s nine outpatient general mental health clinics had participated in a hybrid CCM effectiveness-implementation trial 3 to 4 years prior, which had resulted in improved clinical outcomes that were not universally maintained post-implementation (i.e., after implementation funding and associated evaluation efforts concluded) [ 7 , 9 ]. This lack of aggregate sustainability across the nine clinics is what prompted the earlier interview-based investigation of CCM provider perspectives that identified key determinants of CCM sustainability at the trial sites [ 10 ].

These prior works were conducted in VA outpatient mental health teams, known as Behavioral Health Interdisciplinary Program (BHIP) teams. While there was variability in the exact composition of each BHIP team, all teams consisted of a multidisciplinary set of frontline clinicians (e.g., psychiatrists, psychologists, social workers, nurses) and support staff, serving a panel of about 1000 patients each.

This current project applied MMCS to examine the data from the earlier interviews [ 10 ] for the ways in which CCM sustainability differed at the sites and the factors related to sustainability. The project was determined to be non-research by the VA Boston Research and Development Service, and therefore did not require oversight by the Institutional Review Board (IRB). Details regarding the procedures undertaken for the completed hybrid CCM effectiveness-implementation trial, which serves as the context for this project, have been previously published [ 6 , 7 ]. Similarly, details regarding data collection for the follow-up provider interviews have also been previously published [ 10 ]. We provide a brief overview of the steps that we took for data collection and describe the steps that we took for applying MMCS to analyze the interview data. Additional file  1 outlines our use of the Consolidated Criteria for Reporting Qualitative Research (COREQ) Checklist [ 11 ].

Data collection

We recruited 30 outpatient mental health providers across the nine sites that had participated in the CCM implementation trial, including a multidisciplinary mix of mental health leaders and frontline staff. We recruited participants via email, and we obtained verbal informed consent from all participants. Each interview lasted between 30 and 60 min and focused on the degree to which the participant perceived care processes to have remained aligned to the CCM’s six core elements: work role redesign, patient self-management support, provider decision support, clinical information systems, linkages to community resources, and organizational/leadership support [ 12 , 13 , 14 ]. Interview questions also inquired about the participant’s perceived barriers and enablers influencing CCM sustainability, as well as about the latest status of CCM-based care practices. Interviews were digitally recorded and professionally transcribed. Additional details regarding data collection have been previously published [ 10 ].

Data analysis

We applied MMCS’ nine analytical steps [ 1 ] to the interview data. Each step described below was led by one designated member of the project team, with subsequent review by all project team members to reach a consensus on the examination conducted for each step.

We established the evaluation goal (step 1) to identify the ways in which sustainability differed across the sites and the factors related to sustainability, defining sustainability (step 2) as the continued existence of CCM-aligned care practices—namely, that care processes remained aligned with the six core CCM elements. Table  1 shows examples of care processes that align with each CCM element. As our prior works directly leading up to this project (i.e., design and evaluation of the CCM implementation trial that involved the very sites included in this project [ 6 , 15 , 16 ]) were guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework [ 17 ] and i-PARIHS positions facilitation (the implementation strategy that our trial was testing) as the core ingredient that drives implementation [ 17 ], we selected i-PARIHS’ four domains—innovation, recipients, context, and facilitation—as relevant domains under which to examine factors influencing sustainability (step 3). i-PARIHS posits that the successful implementation of an innovation and its sustained use by recipients in a context is enabled by facilitation (both the individuals doing the facilitation and the process used for facilitation). We examined the data on both sustainability and potentially relevant i-PARIHS domains (step 4) by conducting directed content analysis [ 18 ] of the recorded and professionally transcribed interview data. We used the six CCM elements and the four i-PARIHS domains as a priori codes.

Additional file  2 provides an overview of data input, tasks performed, and analysis output for MMCS steps 5 through 9 described below. We assessed sustainability per site (step 5) by generating CCM code summaries per site, and reached a consensus on whether each site exhibited high, medium, or low sustainability relative to other sites based on the summary data. We assigned a higher sustainability level for sites that exhibited more CCM-aligned care processes, had more participants consistently mention those processes, and considered those processes more as “just the way things are done” at the site. Namely, (i) high sustainability sites had concrete examples of CCM-aligned care processes (such as the ones shown in Table  1 ) for many of the six CCM elements, which multiple participants mentioned as central to how they deliver care, (ii) low sustainability sites had only a few concrete examples of CCM-aligned care processes, mentioned by only a small subset of participants and/or inconsistently practiced, and (iii) medium sustainability sites matched neither of the high nor low sustainability cases, having several concrete examples of CCM-aligned care process for some of the CCM elements, varying in whether they are mentioned by multiple participants or how consistently they are a part of delivering care. For the CCM code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. Each summary and relevant exemplar quotes were then reviewed by and refined with input from all six project team members during recurring team meetings to finalize the high, medium, or low sustainability designation to use in the subsequent MMCS steps. Reviewing and refining the summaries for the nine sites took approximately four 60-min meetings of the six project team members, with each site’s CCM code summary taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of specific examples of how the six core CCM elements were operationalized in our CCM implementation trial [ 19 , 20 ]. Refinements occurred mostly around familiarizing the newer members of the project team (i.e., those who had not participated in our prior CCM-related work) with the examples and definitions. We aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ]. Recognizing the common challenge faced by such discussions in adequately accounting for everyone’s interpretations of the data [ 22 ], we drew on Bens’ meeting facilitation techniques [ 23 ] that include setting ground rules, ensuring balanced participation from all project team members, and accurately recording decisions and action items.

We then identified influencing factors per site (step 6), by generating i-PARIHS code summaries per site and identifying distinct factors under each domain of i-PARIHS (e.g., Collaborativeness and teamwork as a factor under the Recipients domain). For the i-PARIHS code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. They elaborated on each i-PARIHS domain-specific summary by noting distinct factors that they deemed relevant to the summary, proposing descriptive wording to refer to each factor (e.g., “team members share a commitment to their patients” under the Recipients domain). Each summary, associated factor descriptions, and relevant exemplar quotes were then reviewed and refined with input from all six project team members during recurring team meetings to finalize the relevant factors to use in the subsequent MMCS steps. Finalizing the factors included deciding which similar proposed factor descriptions from different sites to consolidate into one factor and which wording to use to refer to the consolidated factor (e.g., “team members share a commitment to their patients,” “team members collaborate well,” and “team members know each other’s styles and what to expect” were consolidated into the Collaborativeness and teamwork factor under the Recipients domain). It took approximately four 60-min meetings of the six project team members to review and refine the summaries and factors for the nine sites, with each site’s i-PARIHS code summary and factors taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of explicit definitions of i-PARIHS constructs that our team members had previously developed and published [ 16 , 24 ]. We once again aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ], drawing on Bens’ meeting facilitation techniques [ 23 ] to adequately account for everyone’s interpretations of the data [ 22 ].

We organized the examined data (i.e., the assessed sustainability and identified factors per site) into a sortable matrix (step 7) using Microsoft Excel [ 25 ], laid out by influencing factor (row), sustainability (column), and site (sheet). We conducted within-site analysis of the matrixed data (step 8), examining the data on each influencing factor and designating whether the factor (i) was present, somewhat present, or minimally present [based on aggregate reports from the site’s participants; used “minimally present” when, considering all available data from a site regarding a factor, the factor was predominantly weak (e.g., predominantly weak Ability to continue patient care during COVID at a medium sustainability site); used “somewhat present” when, considering all available data from a site regarding a factor, the factor was neither predominantly strong nor predominantly weak (e.g., neither predominantly strong nor predominantly weak Collaborativeness and teamwork at a low sustainability site)], and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability (designated as “neutral” when, considering all available data from a site regarding a factor, the factor had neither a predominantly enabling nor a predominantly hindering influence on sustainability). These designations of factors’ presence and influence are conceptually representative of what is commonly referred to as magnitude and valence, respectively, by other efforts that construct scoring for qualitative data (e.g., [ 26 , 27 ]). Like the team-based consensus approach of earlier MMCS steps, factors’ presence and type of influence per site were initially proposed by one project team member after reviewing the matrix’s site-specific data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions.

We then conducted a cross-site analysis of the matrixed data (step 9), assessing whether factors and their combinations were (i) present across multiple sites, (ii) consistently associated with higher or lower sustainability, and (iii) emphasized at some sites more than others. We noted that any factor may have not come up during interviews with a site because either it is not pertinent or it is pertinent but still did not come up, although we asked an open-ended question at the end of each interview about whether there was anything else that the participant wanted to share regarding sustainability. To adequately account for these possibilities, we decided as a team to regard a factor or a combination of factors as being associated with high/medium/low sustainability if it was identified at a majority (i.e., even if not all) of the sites designated as high/medium/low sustainability (e.g., if the Collaborativeness and teamwork factor is identified at a majority, even if not all, of the high sustainability sites, we would find it to be associated with high sustainability). Like the team-based consensus approach of earlier MMCS steps, cross-site patterns were initially proposed by one project team member after reviewing the matrix’s cross-site data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions. We acknowledged the potential existence of additional factors influencing sustainability that may not have emerged during our interviews and also may vary substantially between sites. For example, adaptation of the CCM, characteristics of the patient population, and availability of continued funding, which are factors that extant literature reports as being relevant to sustainability [ 28 , 29 ], were not seen in our interview data. To maintain our analytic focus on the factors seen in our data, we did not add these factors to our analysis.

For the nine sites included in this project, we found the degree of CCM sustainability to be split evenly across the sites—three high-, three medium-, and three low-sustainability. Twenty-five total influencing factors were identified under the i-PARIHS domains of Innovation (6), Recipients (6), Context (8), and Facilitation (5). Table  2 shows these identified influencing factors by domain. Figure  1 shows 11 influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites—e.g., the factor “consistent and strong internal facilitator” is shown as being present at high sustainability sites with an enabling influence on sustainability, because it was identified as such at two or more of the high sustainability sites. Of these 11 influencing factors, four were identified only for sites with high CCM sustainability and two were identified only for sites with medium or low CCM sustainability.

figure 1

Influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites

Key trends in influencing factors associated with high, medium, and/or low CCM sustainability

Three factors across two i-PARIHS domains exhibited strong trends by sustainability status. They were the Collaborativeness and teamwork and Turnover of clinic staff and leadership factors under the Recipients domain, and the Having a consistent and strong internal facilitator factor under the Facilitation domain.

Recipients-related factors

Collaborativeness and teamwork was present with an enabling influence on CCM sustainability at most high and medium sustainability sites, while it was only somewhat present with a neutral influence on CCM sustainability at most low sustainability sites. When asked what had made their BHIP team work well, a participant from a high sustainability site said,

“Just a collaborative spirit.” (Participant 604)

A participant from a medium sustainability site said,

“We joke that [the BHIP teams] are even family, that the teams really do function pretty tightly and they each have their own personality.” (Participant 201)

At the low sustainability sites, willingness to work as a team varied across team members; a participant from a low sustainability site said,

“… I think it has to be the commitment of the people who are on the team. So those that are regularly attending, we get a lot more out of it than those that probably don't ever come [to team meetings].” (Participant 904)

Collaborativeness and teamwork of BHIP team members were often perceived as the highlight of pursuing interdisciplinary care.

Turnover of clinic staff and leadership was present with a hindering influence on CCM sustainability at most high, medium, and low sustainability sites.

“We’ve lost a lot of really, really good providers here in the time I’ve been here …,” (Participant 102)

said a participant from a low-sustainability site that had to reconfigure its BHIP teams due to clinic staff shortages. Turnover of mental health clinic leadership made it difficult to maintain CCM practices, especially beyond the teams that participated in the original CCM implementation trial. A participant from a medium sustainability site said,

“Probably about 90 percent of the things that we came up with have fallen by the wayside. Within our team, many of those remain but again, that hand off towards the other teams that I think partly is due to the turnover rate with program managers, supervisors, didn’t get fully implemented.” (Participant 703)

Although turnover was an issue for high sustainability sites as well, there was also indication of the situation improving in recent years; a participant from a high sustainability site said,

“… our attrition rollover rate has dropped quite a bit and I would really attribute that to [the CCM being] more functional and more sustainable and tolerable for the providers.” (Participant 502)

As such, staff and leadership turnover was deemed a major challenge for CCM sustainability for all sites regardless of the overall level of sustainability.

Facilitation-related factor

Having a consistent and strong internal facilitator was present with an enabling influence on CCM sustainability at high sustainability sites, not identified as an influencing factor at most of the medium sustainability sites, and variably present with a hindering, neutral, or unclear influence on CCM sustainability at low sustainability sites. Participants from a high sustainability site perceived that it was important for the internal facilitator to understand different BHIP team members’ personalities and know the clinic’s history. A participant from another high sustainability site shared that, as an internal facilitator themselves, they focused on recognizing and reinforcing the progress of team members:

“… I'm often the person who kind of [starts] off with, ‘Hey, look at what we've done in this location,’ ‘Hey look at what the team's done this month.’” (Participant 402)

A participant from a low sustainability site had also served as an internal facilitator and recounted the difficulty and importance of readying the BHIP team to function in the long run without their assistance:

“I should have been able to get out sooner, I think, to get it to have them running this themselves. And that was just a really difficult process.” (Participant 301)

Participants, especially from the high and low sustainability sites, attributed their BHIP teams’ successes and challenges to the skills of the internal facilitator.

Influencing factors identified only for sites with high CCM sustainability

Four factors across four i-PARIHS domains were identified for high sustainability sites and not for medium or low sustainability sites. They were the factors Details about the CCM being well understood (Innovation domain), Interdisciplinary coordination (Recipients domain), Having adequate clinic space for CCM team members (Context domain), and Having a knowledgeable and helpful external facilitator (Facilitation domain).

Innovation-related factor

Details about the CCM being well understood was minimal to somewhat present with an unclear influence on CCM sustainability.

“We’ve … been trying to help our providers see the benefit of team-based care and the episodes-of-care idea, and I would say that is something our folks really have continued to struggle with as well,” (Participant 401)

said a participant from a high sustainability site. “What is considered CCM-based care?” continued to be a question on providers’ minds. A participant from a high sustainability site asked during the interview,

“Is there kind of a clearing house of some of the best practices for [CCM] that you guys have … or some other collection of resources that we could draw from?” (Participant 601)

Although such references are indeed accessible online organization-wide, participants were not always aware of those resources or what exactly CCM entails.

Recipients-related factor

Interdisciplinary coordination was somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. Coordination between psychotherapy and psychiatry providers was deemed difficult by participants from high-sustainability sites. A participant said,

“We were initially kind of top heavy on the psychiatry so just making sure we have … therapy staff balancing that out [has been important].” (Participant 501)

Another participant perceived that BHIP teams were helpful in managing.

… ‘sibling rivalry’ between different disciplines … because [CCM] puts us all in one team and we communicate.” (Participant 505)

Interdisciplinary coordination was understood by the participants as being necessary for effective CCM-based care yet difficult to achieve.

Context-related factor

Having adequate clinic space for CCM team members was minimal to somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. COVID-19 led to changes in how clinic space was used/assigned. A participant from a high sustainability site remarked,

“Pre-COVID everything was in a room instead of online. And now all our meetings are online and so it's actually really easy for the supervisors to be able to rotate through them and then, you know, they can answer programmatic questions ….” (Participant 402)

Participants from another high sustainability site found that issues regarding limited clinic space were both exacerbated and alleviated by COVID, with the mental health service losing space to vaccine clinics but more mental health clinicians teleworking and in less need of clinic space. Virtual connections were seen to alleviate some physical workspace-related concerns.

Having a knowledgeable and helpful external facilitator was variably present; when present, it had an enabling influence on CCM sustainability. Participants from a high sustainability site noted how many of the external facilitator’s efforts to change the BHIP team’s work processes very much remained over time. An example of a change was to have team meetings be structured to meet evolving patient needs. Team members came to meetings with the shared knowledge and expectation that,

“… we need to touch on folks who are coming out of the hospital, we need to touch on folks with higher acuity needs.” (Participant 402)

Implementation support that sites received from their external facilitator mostly occurred during the time period of the original CCM implementation trial; correspondence with the external facilitator after that trial time period was not common for sites. Participants still largely found the external facilitator to provide helpful guidance and advice on delivering CCM-based care.

Influencing factors identified only for sites with medium or low CCM sustainability

Two factors were identified for medium or low sustainability sites and not for high sustainability sites. They were the factors Ability to continue patient care during COVID and Adequate resources/capacity for care delivery . These factors were both under i-PARIHS’ Context domain, unlike the influencing factors above that were identified only for high sustainability sites, which spanned all four i-PARIHS domains.

Context-related factors

Ability to continue patient care during COVID had a hindering influence on CCM sustainability when minimally present. Participants felt that their CCM work was challenged when delivering care through telehealth was made difficult—e.g., at a medium sustainability site, site policies during the pandemic required a higher number of in-person services than the BHIP team providers expected or desired to deliver. On the other hand, this factor had an enabling influence on CCM sustainability when present. A participant at a low sustainability site mentioned the effect of telehealth on being able to follow up more easily with patients who did not show up for their appointments:

“… my no-show rate has dropped dramatically because if people don’t log on after a couple minutes, I call them. They're like ‘oh, I forgot, let me pop right on,’ whereas, you know, in the face-to-face space, you know, you wait 15 minutes, you call them, it’s too late for them to come in so then they're no shows.” (Participant 102)

The advantages of virtual care delivery, as well as the challenges of getting approvals to pursue it to varying extents, were well recognized by the participants.

Adequate resources/capacity for care delivery was minimally present at medium sustainability sites with a hindering influence on CCM sustainability. At a medium sustainability site, although leadership was supportive of CCM, resources were being used to keep clinics operational (especially during COVID) rather than investing in building new CCM-based care delivery processes.

“I think that if my boss came to me, [and asked] what could I do for [the clinics] … I would say even more staff,” (Participant 202)

said a participant from a medium sustainability site. At the same time, the participant, as many others we interviewed, understood and emphasized the need for BHIP teams to proceed with care delivery even when resources were limited:

“… when you’re already dealing with a very busy clinic, short staff and then you’re hit with a pandemic you handle it the best that you can.” (Participant 202)

Participants felt the need for basic resource requirements to be met in order for CCM-based care to be feasible.

In this project, we examined factors influencing the sustainability of CCM-aligned care practices at general mental health clinics within nine VA medical centers that previously participated in a CCM implementation trial. Guided by the core CCM elements and i-PARIHS domains, we conducted and analyzed CCM provider interviews. Using MMCS, we found CCM sustainability to be split evenly across the nine sites (three high, three medium, and three low), and that sustainability may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators.

In comparison to most high sustainability sites, participants from most medium or low sustainability sites did not mention a knowledgeable and helpful external facilitator who enabled sustainability. Participants at the high sustainability sites also emphasized the need for clarity about what CCM-based care comprises, interdisciplinary coordination in delivering CCM-aligned care, and adequate clinic space for BHIP team members to connect and collaborate. In contrast, in comparison to participants at most high sustainability sites, participants at most medium or low sustainability sites emphasized the need for better continuity of patient-facing activities during the COVID-19 pandemic and more resources/capacity for care delivery. A notable difference between these two groups of influencing factors is that the ones emphasized at most high sustainability sites are more CCM-specific (e.g., external facilitator with CCM expertise, knowledge, and structures to support delivery of CCM-aligned care), while the ones emphasized at most medium or low sustainability sites are factors that certainly relate to CCM sustainability but are focused on care delivery operations beyond CCM-aligned care (e.g., COVID’s widespread impacts, limited staff availability). In short, an emphasis on immediate, short-term clinical needs in the face of the COVID-19 pandemic and staffing challenges appeared to sap sites’ enthusiasm for sustaining more collaborative, CCM-consistent care processes.

Our previous qualitative analysis of these interview data suggested that in order to achieve sustainability, it is important to establish appropriate infrastructure, organizational readiness, and mental health service- or department-wide coordination for CCM implementation [ 10 ]. The findings from the current project augment these previous findings by highlighting the specific factors associated with higher and lower CCM sustainability across the project sites. This additional knowledge provides two important insights into what CCM implementation efforts should prioritize with regard to the previously recommended appropriate infrastructure, readiness, and coordination. First, for knowledge retention and coordination during personnel changes (including any changes in internal facilitators through and following implementation), care processes and their specific procedures should be established and documented in order to bring new personnel up to speed on those care processes. Management sciences, as applied to health care and other fields, suggest that such organizational knowledge retention can be maximized when there are (i) structures set up to formally recognize/praise staff when they share key knowledge, (ii) succession plans to be applied in the event of staff turnover, (iii) opportunities for mentoring and shadowing, and (iv) after action reviews of conducted care processes, which allow staff to learn about and shape the processes themselves [ 30 , 31 , 32 , 33 ]. Future CCM implementation efforts may thus benefit from enacting these suggestions alongside establishing and documenting CCM-based care processes and associated procedures.

Second, efforts to implement CCM-aligned practices into routine care should account for the extent to which sites’ more fundamental operational needs are met or being addressed. That information can be used to appropriately scope the plan, expectations, and timeline for implementation. For instance, ongoing critical staffing shortages or high turnover [ 34 ] at a site are unlikely to be resolved through a few months of CCM implementation. In fact, in that situation, it is possible that CCM implementation efforts could lead to reduced team effectiveness in the short term, given the effort required to establish more collaborative and coordinated care processes [ 35 ]. Should CCM implementation move forward at a given site, implementation goals ought to be set on making progress in realms that are within the implementation effort’s control (e.g., designing CCM-aligned practices that take staffing challenges into consideration) [ 36 , 37 ] rather than on factors outside of the effort’s control (e.g., staffing shortages). As healthcare systems determine how to deploy support (e.g., facilitators) to sites for CCM implementation, they would benefit from considering whether it is primarily CCM expertise that the site needs at the moment, or more foundational organizational resources (e.g., mental health staffing, clinical space, leadership enhancement) [ 38 ] to first reach an operational state that can most benefit from CCM implementation efforts at a later point in time. There is growing consensus across the field that the readiness of a healthcare organization to innovate is a prerequisite to successful innovation (e.g., CCM implementation) regardless of the specific innovation [ 39 , 40 ]. Several promising strategies specifically target these organizational considerations for implementing evidence-based practices (e.g., [ 41 , 42 ]). Further, recent works have begun to more clearly delineate leadership-related, climate-related, and other contextual factors that contribute to organizations’ innovation readiness [ 43 ], which can inform healthcare systems’ future decisions regarding preparatory work leading to, and timing of, CCM implementation at their sites.

These considerations informed by MMCS may have useful implications for implementation strategy selection and tailoring for future CCM implementation efforts, especially in delineating the target level (e.g., system, organizational, clinic, individual) and timeline of implementation strategies to be deployed. For instance, of the three factors found to most notably trend with CCM sustainability, Collaborativeness and teamwork may be strengthened through shorter-term team-building interventions at the organizational and/or clinic levels [ 38 ], Turnover of clinic staff and leadership may be mitigated by aiming for longer-term culture/climate change at the system and/or organizational levels [ 44 , 45 , 46 ], and Having a consistent and strong internal facilitator may be ensured more immediately by selecting an individual with fitting expertise/characteristics to serve in the role [ 15 ] and imparting innovation/facilitation knowledge to them [ 47 ]. Which of these factors to focus on, and through what specific strategies, can be decided in partnership with an implementation site—for instance, candidate strategies can be identified based on ones that literature points to for addressing these factors [ 48 ], systematic selection of the strategies to move forward can happen with close input from site personnel [ 49 ], and explicit further specification of those strategies [ 50 ] can also happen in collaboration with site personnel to amply account for site-specific contexts [ 51 ].

As is common for implementation projects, the findings of this project are highly context-dependent. It involves the implementation of a specific evidence-based practice (the CCM) using a specific implementation strategy (implementation facilitation) at specific sites (BHIP teams within general mental health clinics at nine VA medical centers). For such context-dependent findings to be transferable [ 52 , 53 ] to meaningfully inform future implementation efforts, sources of variation in the findings and how the findings were reached must be documented and traceable. This means being explicit about each step and decision that led up to cross-site analysis, as MMCS encourages, so that future implementation efforts can accurately view and consider why and how findings might be transferable to their own work. For instance, beyond the finding that Turnover of clinic staff and leadership was a factor present at most of the examined sites, MMCS’ traceable documentation of qualitative data associated with this factor at high sustainability sites also allowed highlighting the perception that CCM implementation is contributing to mitigating turnover of providers in the clinic over time, which may be a crucial piece of information that fuels future CCM implementation efforts.

Furthermore, to compare findings and interpretations across projects, consistent procedures for setting up and conducting these multi-site investigations are indispensable [ 54 , 55 , 56 ]. Although many projects involve multiple sites and assess variations across the sites, it is less common to have clearly delineated protocols for conducting such assessments. MMCS is meant to target this very gap, by offering a formalized sequence of steps that prompt specification of analytical procedures and decisions that are often interpretive and left less specified. MMCS uses a concrete data structure (the matrix) to traceably organize information and knowledge gained from a project, and the matrix can accommodate various data sources and conceptual groundings (e.g., guiding theories, models, and frameworks) that may differ from project to project – for instance, although our application of MMCS aligned to i-PARIHS, other projects applying MMCS [ 2 , 5 ] use different conceptual guides (e.g., Consolidated Framework for Implementation Research [ 57 ], Theoretical Domains Framework [ 58 ]). Therefore, as more projects align to the MMCS steps [ 1 ] to identify factors related to implementation and sustainability, better comparisons, consolidations, and transfers of knowledge between projects may become possible.

This project has several limitations. First, the high, medium, and low sustainability assigned to the sites were based on the sites’ CCM sustainability relative to one another, rather than based on an external metric of sustainability. As measures of sustainability such as the Program Sustainability Assessment Tool [ 59 , 60 ] and the Sustainment Measurement System Scale [ 61 ] become increasingly developed and tested, future projects may consider the feasibility of incorporating such measures to assess each site’s sustainability. In our case, we worked on addressing this limitation by using a consensus approach within our project team to assign sustainability levels to sites, as well as by confirming that the sites that we designated as high sustainability exhibited CCM elements that we had previously observed at the end of their participation in the original CCM implementation trial [ 19 ]. Second, we did not assign strict thresholds above/below which the counts or proportions of data regarding a factor would automatically indicate whether the factor (i) was present, somewhat present, or minimally present and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability. This follows widely accepted qualitative analytical guidance that discourages characterizing findings solely based on the frequency with which a notion is mentioned by participants [ 62 , 63 , 64 ], in order to prevent unsubstantiated inferences or conclusions. We sought to address this limitation in two ways: We carefully documented the project team’s rationale for each consensus reached, and we reviewed all consensuses reached in their entirety to ensure that any two factors with the same designation (e.g., “minimally present”) do not have associated rationale that conflict across those factors. These endeavors we undertook closely adhere to established case study research methods [ 65 ], which MMCS builds on, that emphasize strengthening the validity and reliability of findings through documenting a detailed analytic protocol, as well as reviewing data to ensure that patterns match across analytic units (e.g., factors, interviewees, sites). Third, our findings are based on three sites each for high/medium/low sustainability, and although we identified single factors associated with sustainability, we found no specific combinations of factors’ presence and influence that were repeatedly existent at a majority of the sites designated as high/medium/low sustainability. Examining additional sites on the factors identified through this work (as we will for our subsequent CCM implementation trial described below) will allow more opportunities for repeated combinations and other factors to emerge, making possible firmer conclusions regarding the extent to which the currently identified factors and absence of identified combinations are applicable beyond the sites included in this study. Fourth, the identified influencing factor “leadership support for CCM” (under the Context domain of the i-PARIHS framework) substantially overlaps in concept with the core “organizational/leadership support” element of the CCM. To avoid circular reasoning, we used leadership support-related data to inform our assignment of sites’ high, medium, or low CCM sustainability, rather than as a reason for the sites’ CCM sustainability. In reality, strong leadership support may both result from and contribute to implementation and sustainability [ 16 , 66 ], and thus causal relationships between the i-PARIHS-aligned influencing factors and the CCM elements (possibly with feedback loops) warrant further examination to most appropriately use leadership support-related data in future analyses of CCM sustainability. Fifth, findings may be subject to both social desirability bias in participants providing more positive than negative evidence of sustainability (especially participants who are responsible for implementing and sustaining CCM-aligned care at their site) and the project team members’ bias in interpreting the findings to align to their expectations of further effort being necessary to sustainably implement the CCM. To help mitigate this challenge, the project interviewers strove to elicit from participants both positive and negative perceptions and experiences related to CCM-based care delivery, both of which were present in the examined interview data.

Future work stemming from this project is twofold. Regarding CCM implementation, we will conduct a subsequent CCM implementation trial involving eight new sites to prospectively examine how implementation facilitation with an enhanced focus on these findings affects CCM sustainability. We started planning for sustainability prior to implementation, looking to this work for indicators of specific modifications needed to the previous way in which we used implementation facilitation to promote the uptake of CCM-based care [ 67 ]. Findings from this work suggest that sustainability may be related most strongly to (i) provider collaboration, (ii) knowledge retention during staff/leadership transitions, and (iii) availability of skilled internal facilitators. Hence, we will accordingly prioritize developing procedures for (i) regular CCM-related information exchange amongst BHIP team members, as well as between the BHIP team and clinic leadership, (ii) both translating knowledge to and keeping knowledge documented at the site, and (iii) supporting the sites’ own personnel to take the lead in driving CCM implementation.

Regarding MMCS, we will continuously refine and improve the method by learning from other projects applying, testing, and critiquing MMCS. Outside of our CCM-related projects, examinations of implementation data using MMCS are actively underway for various implementation efforts including that of a data dashboard for decision support on transitioning psychiatrically stable patients from specialty mental health to primary care [ 2 ], a peer-led healthy lifestyle intervention for individuals with serious mental illness [ 3 ], screening programs for intimate partner violence [ 4 ], and a policy- and organization-based health system strengthening intervention to improve health systems in sub-Saharan Africa [ 5 ]. As MMCS is used by more projects that differ from one another in their specific outcome of interest, and especially in light of our MMCS application that examines factors related to sustainability, we are curious whether certain proximal to distal outcomes are more subject to heterogeneity in influencing factors than other outcomes. For instance, sustainability outcomes, which are tracked following a longer passage of time than some other outcomes, may be subject to more contextual variations that occur over time and thus could particularly benefit from being examined using MMCS. We will also explore MMCS’ complementarity with coincidence analysis and other configurational analytical approaches [ 68 ] for examining implementation phenomena. We are excited about both the step-by-step traceability that MMCS can bring to such methods and those methods’ computational algorithms that can be beneficial to incorporate into MMCS for projects with larger numbers of sites. For example, Salvati and colleagues [ 69 ] described both the inspiration that MMCS provided in structuring their data as well as how they addressed MMCS’ visualization shortcomings through their innovative data matrix heat mapping, which led to their selection of specific factors to include in their subsequent coincidence analysis. Coincidence analysis is an enhancement to qualitative comparative analysis and other configurational analytical methods, in that it is formulated specifically for causal inference [ 70 ]. Thus, in considering improved reformulations of MMCS’ steps to better characterize examined factors as explicit causes to the outcomes of interest, we are inspired by and can draw on coincidence analysis’ approach to building and evaluating causal chains that link factors to outcomes. Relatedly, we have begun to actively consider the potential contribution that MMCS can make to hypothesis generation and theory development for implementation science. As efforts to understand the mechanisms through which implementation strategies work are gaining momentum [ 71 , 72 , 73 ], there is an increased need for methods that help decompose our understanding of factors that influence the mechanistic pathways from strategies to outcomes [ 74 ]. Implementation science is facing the need to develop theories, beyond frameworks, which delineate hypotheses for observed implementation phenomena that can be subsequently tested [ 75 ]. The methodical approach that MMCS offers can aid this important endeavor, by enabling data curation and examination of pertinent factors in a consistent way that allows meaningful synthesis of findings across sites and studies. We see these future directions as concrete steps toward elucidating the factors related to sustainable implementation of EBPs, especially leveraging data from projects where the number of sites is much smaller than the number of factors that may matter—which is indeed the case for most implementation projects.

Using MMCS, we found that provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators may be most strongly related to CCM sustainability in VA outpatient mental health clinics. Informed by these findings, we have a subsequent CCM implementation trial underway to prospectively test whether increasing the aforementioned factors within implementation facilitation enhances sustainability. The MMCS steps used here for systematic multi-site examination can also be applied to determining sustainability-related factors relevant to various other EBPs and implementation contexts.

Availability of data and materials

The data analyzed during the current project are not publicly available because participant privacy could be compromised.

Abbreviations

Behavioral Health Interdisciplinary Program

Collaborative Chronic Care Model

Consolidated Criteria for Reporting Qualitative Research

coronavirus disease

evidence-based practice

Institutional Review Board

Integrated Promoting Action on Research Implementation in Health Services

Matrixed Multiple Case Study

United States Department of Veterans Affairs

Kim B, Sullivan JL, Ritchie MJ, Connolly SL, Drummond KL, Miller CJ, et al. Comparing variations in implementation processes and influences across multiple sites: What works, for whom, and how? Psychiatry Res. 2020;283:112520.

Article   PubMed   Google Scholar  

Hundt NE, Yusuf ZI, Amspoker AB, Nagamoto HT, Kim B, Boykin DM, et al. Improving the transition of patients with mental health disorders back to primary care: A protocol for a partnered, mixed-methods, stepped-wedge implementation trial. Contemp Clin Trials. 2021;105:106398.

Tuda D, Bochicchio L, Stefancic A, Hawes M, Chen J-H, Powell BJ, et al. Using the matrixed multiple case study methodology to understand site differences in the outcomes of a Hybrid Type 1 trial of a peer-led healthy lifestyle intervention for people with serious mental illness. Transl Behav Med. 2023;13(12):919–27.

Adjognon OL, Brady JE, Iverson KM, Stolzmann K, Dichter ME, Lew RA, et al. Using the Matrixed Multiple Case Study approach to identify factors affecting the uptake of IPV screening programs following the use of implementation facilitation. Implement Sci Commun. 2023;4(1):145.

Article   PubMed   PubMed Central   Google Scholar  

Seward N, Murdoch J, Hanlon C, Araya R, Gao W, Harding R, et al. Implementation science protocol for a participatory, theory-informed implementation research programme in the context of health system strengthening in sub-Saharan Africa (ASSET-ImplementER). BMJ Open. 2021;11(7):e048742.

Bauer MS, Miller C, Kim B, Lew R, Weaver K, Coldwell C, et al. Partnering with health system operations leadership to develop a controlled implementation trial. Implement Sci. 2016;11:22.

Bauer MS, Miller CJ, Kim B, Lew R, Stolzmann K, Sullivan J, et al. Effectiveness of implementing a Collaborative Chronic Care Model for clinician teams on patient outcomes and health status in mental health: a randomized clinical trial. JAMA Netw Open. 2019;2(3):e190230.

Ritchie MJ, Dollar KM, Miller CJ, Smith JL, Oliver KA, Kim B, et al. Using Implementation Facilitation to Improve Healthcare (Version 3): Veterans Health Administration, Behavioral Health Quality Enhancement Research Initiative (QUERI). 2020.

Google Scholar  

Bauer MS, Stolzmann K, Miller CJ, Kim B, Connolly SL, Lew R. Implementing the Collaborative Chronic Care Model in mental health clinics: achieving and sustaining clinical effects. Psychiatr Serv. 2021;72(5):586–9.

Miller CJ, Kim B, Connolly SL, Spitzer EG, Brown M, Bailey HM, et al. Sustainability of the Collaborative Chronic Care Model in outpatient mental health teams three years post-implementation: a qualitative analysis. Adm Policy Ment Health. 2023;50(1):151–9.

Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349–57.

Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness. Ann Intern Med. 1997;127(12):1097–102.

Article   Google Scholar  

Wagner EH, Austin BT, Von Korff M. Organizing care for patients with chronic illness. Milbank Q. 1996;74(4):511–44.

Article   CAS   PubMed   Google Scholar  

Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the chronic care model in the new millennium. Health Aff (Millwood). 2009;28(1):75–85.

Connolly SL, Sullivan JL, Ritchie MJ, Kim B, Miller CJ, Bauer MS. External facilitators’ perceptions of internal facilitation skills during implementation of collaborative care for mental health teams: a qualitative analysis informed by the i-PARIHS framework. BMC Health Serv Res. 2020;20(1):165.

Kim B, Sullivan JL, Drummond KL, Connolly SL, Miller CJ, Weaver K, et al. Interdisciplinary behavioral health provider perceptions of implementing the Collaborative Chronic Care Model: an i-PARIHS-guided qualitative study. Implement Sci Commun. 2023;4(1):35.

Harvey G, Kitson A. PARIHS revisited: from heuristic to integrated framework for the successful implementation of knowledge into practice. Implement Sci. 2016;11:33.

Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.

Sullivan JL, Kim B, Miller CJ, Elwy AR, Drummond KL, Connolly SL, et al. Collaborative Chronic Care Model implementation within outpatient behavioral health care teams: qualitative results from a multisite trial using implementation facilitation. Implement Sci Commun. 2021;2(1):33.

Miller CJ, Sullivan JL, Kim B, Elwy AR, Drummond KL, Connolly S, et al. Assessing collaborative care in mental health teams: qualitative analysis to guide future implementation. Adm Policy Ment Health. 2019;46(2):154–66.

Miles MB, Huberman AM. Qualitative data analysis: an expanded sourcebook: sage. 1994.

Jones J, Hunter D. Consensus methods for medical and health services research. BMJ. 1995;311(7001):376–80.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Bens I. Facilitating with Ease!: core skills for facilitators, team leaders and members, managers, consultants, and trainers. Hoboken: John Wiley & Sons; 2017.

Ritchie MJ, Drummond KL, Smith BN, Sullivan JL, Landes SJ. Development of a qualitative data analysis codebook informed by the i-PARIHS framework. Implement Sci Commun. 2022;3(1):98.

Excel: Microsoft. Available from: https://www.microsoft.com/en-us/microsoft-365/excel . Accessed 15 Feb 2024.

Madrigal L, Manders OC, Kegler M, Haardörfer R, Piper S, Blais LM, et al. Inner and outer setting factors that influence the implementation of the National Diabetes Prevention Program (National DPP) using the Consolidated Framework for Implementation Research (CFIR): a qualitative study. Implement Sci Commun. 2022;3(1):104.

Wilson HK, Wieler C, Bell DL, Bhattarai AP, Castillo-Hernandez IM, Williams ER, et al. Implementation of the Diabetes Prevention Program in Georgia Cooperative Extension According to RE-AIM and the Consolidated Framework for Implementation Research. Prev Sci. 2023;Epub ahead of print.

Proctor E, Luke D, Calhoun A, McMillen C, Brownson R, McCrary S, et al. Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support. Implement Sci. 2015;10:88.

Fathi LI, Walker J, Dix CF, Cartwright JR, Joubert S, Carmichael KA, et al. Applying the Integrated Sustainability Framework to explore the long-term sustainability of nutrition education programmes in schools: a systematic review. Public Health Nutr. 2023;26(10):2165–79.

Guptill J. Knowledge management in health care. J Health Care Finance. 2005;31(3):10–4.

PubMed   Google Scholar  

Gammelgaard J. Why not use incentives to encourage knowledge sharing. J Knowledge Manage Pract. 2007;8(1):115–23.

Liebowitz J. Knowledge retention: strategies and solutions. Boca Raton: CRC Press; 2008.

Ensslin L, CarneiroMussi C, RolimEnsslin S, Dutra A, Pereira Bez Fontana L. Organizational knowledge retention management using a constructivist multi-criteria model. J Knowledge Manage. 2020;24(5):985–1004.

Peterson AE, Bond GR, Drake RE, McHugo GJ, Jones AM, Williams JR. Predicting the long-term sustainability of evidence-based practices in mental health care: an 8-year longitudinal analysis. J Behav Health Serv Res. 2014;41(3):337–46.

Miller CJ, Griffith KN, Stolzmann K, Kim B, Connolly SL, Bauer MS. An economic analysis of the implementation of team-based collaborative care in outpatient general mental health clinics. Med Care. 2020;58(10):874–80.

Silver SA, Harel Z, McQuillan R, Weizman AV, Thomas A, Chertow GM, et al. How to begin a quality improvement project. Clin J Am Soc Nephrol. 2016;11(5):893–900.

Dixon-Woods M. How to improve healthcare improvement-an essay by Mary Dixon-Woods. BMJ. 2019;367:l5514.

Miller CJ, Kim B, Silverman A, Bauer MS. A systematic review of team-building interventions in non-acute healthcare settings. BMC Health Serv Res. 2018;18(1):146.

Robert G, Greenhalgh T, MacFarlane F, Peacock R. Organisational factors influencing technology adoption and assimilation in the NHS: a systematic literature review. Report for the National Institute for Health Research Service Delivery and Organisation programme. London; 2009.

Kelly CJ, Young AJ. Promoting innovation in healthcare. Future Healthc J. 2017;4(2):121–5.

PubMed   PubMed Central   Google Scholar  

Aarons GA, Ehrhart MG, Farahnak LR, Hurlburt MS. Leadership and organizational change for implementation (LOCI): a randomized mixed method pilot study of a leadership and organization development intervention for evidence-based practice implementation. Implement Sci. 2015;10:11.

Ritchie MJ, Parker LE, Kirchner JE. Facilitating implementation of primary care mental health over time and across organizational contexts: a qualitative study of role and process. BMC Health Serv Res. 2023;23(1):565.

van den Hoed MW, Backhaus R, de Vries E, Hamers JPH, Daniëls R. Factors contributing to innovation readiness in health care organizations: a scoping review. BMC Health Serv Res. 2022;22(1):997.

Melnyk BM, Hsieh AP, Messinger J, Thomas B, Connor L, Gallagher-Ford L. Budgetary investment in evidence-based practice by chief nurses and stronger EBP cultures are associated with less turnover and better patient outcomes. Worldviews Evid Based Nurs. 2023;20(2):162–71.

Jacob RR, Parks RG, Allen P, Mazzucca S, Yan Y, Kang S, et al. How to “start small and just keep moving forward”: mixed methods results from a stepped-wedge trial to support evidence-based processes in local health departments. Front Public Health. 2022;10:853791.

Aarons GA, Conover KL, Ehrhart MG, Torres EM, Reeder K. Leader-member exchange and organizational climate effects on clinician turnover intentions. J Health Organ Manag. 2020;35(1):68–87.

Kirchner JE, Ritchie MJ, Pitcock JA, Parker LE, Curran GM, Fortney JC. Outcomes of a partnered facilitation strategy to implement primary care-mental health. J Gen Intern Med. 2014;29 Suppl 4(Suppl 4):904–12.

Strategy Design: CFIR research team-center for clinical management research. Available from: https://cfirguide.org/choosing-strategies/ . Accessed 15 Feb 2024.

Kim B, Wilson SM, Mosher TM, Breland JY. Systematic decision-making for using technological strategies to implement evidence-based interventions: an illustrated case study. Front Psychiatry. 2021;12:640240.

Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8:139.

Lewis CC, Scott K, Marriott BR. A methodology for generating a tailored implementation blueprint: an exemplar from a youth residential setting. Implement Sci. 2018;13(1):68.

Maher C, Hadfield M, Hutchings M, de Eyto A. Ensuring rigor in qualitative data analysis: a design research approach to coding combining NVivo with traditional material methods. Int J Qual Methods. 2018;17(1):1609406918786362.

Holloway I. A-Z of qualitative research in healthcare. 2nd ed. Oxford: Wiley-Blackwell; 2008.

Reproducibility and Replicability in Research: National Academies. Available from: https://www.nationalacademies.org/news/2019/09/reproducibility-and-replicability-in-research . Accessed 15 Feb 2024.

Chinman M, Acosta J, Ebener P, Shearer A. “What we have here, is a failure to [Replicate]”: ways to solve a replication crisis in implementation science. Prev Sci. 2022;23(5):739–50.

Vicente-Saez R, Martinez-Fuentes C. Open Science now: a systematic literature review for an integrated definition. J Bus Res. 2018;88:428–36.

Consolidated Framework for Implementation Research: CFIR Research Team-Center for Clinical Management Research. Available from: https://cfirguide.org/ . Accessed 15 Feb 2024.

Atkins L, Francis J, Islam R, O’Connor D, Patey A, Ivers N, et al. A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems. Implement Sci. 2017;12(1):77.

Luke DA, Calhoun A, Robichaux CB, Elliott MB, Moreland-Russell S. The Program Sustainability Assessment Tool: a new instrument for public health programs. Prev Chronic Dis. 2014;11:130184.

Calhoun A, Mainor A, Moreland-Russell S, Maier RC, Brossart L, Luke DA. Using the Program Sustainability Assessment Tool to assess and plan for sustainability. Prev Chronic Dis. 2014;11:130185.

Palinkas LA, Chou CP, Spear SE, Mendon SJ, Villamar J, Brown CH. Measurement of sustainment of prevention programs and initiatives: the sustainment measurement system scale. Implement Sci. 2020;15(1):71.

Sandelowski M. Real qualitative researchers do not count: the use of numbers in qualitative research. Res Nurs Health. 2001;24(3):230–40.

Wood M, Christy R. Sampling for Possibilities. Qual Quant. 1999;33(2):185–202.

Chang Y, Voils CI, Sandelowski M, Hasselblad V, Crandell JL. Transforming verbal counts in reports of qualitative descriptive studies into numbers. West J Nurs Res. 2009;31(7):837–52.

Yin RK. Case study research and applications. Los Angeles: Sage; 2018.

Bauer MS, Weaver K, Kim B, Miller C, Lew R, Stolzmann K, et al. The Collaborative Chronic Care Model for mental health conditions: from evidence synthesis to policy impact to scale-up and spread. Med Care. 2019;57 Suppl 10 Suppl 3(10 Suppl 3):S221-s7.

Miller CJ, Sullivan JL, Connolly SL, Richardson EJ, Stolzmann K, Brown ME, et al. Adaptation for sustainability in an implementation trial of team-based collaborative care. Implement Res Pract. 2024;5:26334895231226197.

Curran GM, Smith JD, Landsverk J, Vermeer W, Miech EJ, Kim B, et al. Design and analysis in dissemination and implementation research. In: Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and Implementation Research in Health: Translating Science to Practice. 3 ed. New York: Oxford University Press; In press.

Salvati ZM, Rahm AK, Williams MS, Ladd I, Schlieder V, Atondo J, et al. A picture is worth a thousand words: advancing the use of visualization tools in implementation science through process mapping and matrix heat mapping. Implement Sci Commun. 2023;4(1):43.

Whitaker RG, Sperber N, Baumgartner M, Thiem A, Cragun D, Damschroder L, et al. Coincidence analysis: a new method for causal inference in implementation science. Implement Sci. 2020;15(1):108.

Lewis CC, Powell BJ, Brewer SK, Nguyen AM, Schriger SH, Vejnoska SF, et al. Advancing mechanisms of implementation to accelerate sustainable evidence-based practice integration: protocol for generating a research agenda. BMJ Open. 2021;11(10):e053474.

Kilbourne AM, Geng E, Eshun-Wilson I, Sweeney S, Shelley D, Cohen DJ, et al. How does facilitation in healthcare work? Using mechanism mapping to illuminate the black box of a meta-implementation strategy. Implement Sci Commun. 2023;4(1):53.

Kim B, Cruden G, Crable EL, Quanbeck A, Mittman BS, Wagner AD. A structured approach to applying systems analysis methods for examining implementation mechanisms. Implementation Sci Commun. 2023;4(1):127.

Geng EH, Baumann AA, Powell BJ. Mechanism mapping to advance research on implementation strategies. PLoS Med. 2022;19(2):e1003918.

Luke DA, Powell BJ, Paniagua-Avila A. Bridges and mechanisms: integrating systems science thinking into implementation research. Annu Rev Public Health. In press.

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Acknowledgements

The authors sincerely thank the project participants for their time, as well as the project team members for their guidance and support. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

This project was funded by VA grant QUE 20–026 and was designed and conducted in partnership with the VA Office of Mental Health and Suicide Prevention.

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COREQ (COnsolidated criteria for REporting Qualitative research) Checklist.

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Data input, tasks performed, and analysis output for MMCS Steps 5 through 9.

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Kim, B., Sullivan, J.L., Brown, M.E. et al. Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study. Implementation Sci 19 , 16 (2024). https://doi.org/10.1186/s13012-024-01342-2

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Case Study: Quality Management System at Coca Cola Company

Coca Cola’s history can be traced back to a man called Asa Candler, who bought a specific formula from a pharmacist named Smith Pemberton. Two years later, Asa founded his business and started production of soft drinks based on the formula he had bought. From then, the company grew to become the biggest producers of soft drinks with more than five hundred brands sold and consumed in more than two hundred nations worldwide.

Although the company is said to be the biggest bottler of soft drinks, they do not bottle much. Instead, Coca Cola Company manufactures a syrup concentrate, which is bought by bottlers all over the world. This distribution system ensures the soft drink is bottled by these smaller firms according to the company’s standards and guidelines. Although this franchised method of distribution is the primary method of distribution, the mother company has a key bottler in America, Coca Cola Refreshments.

In addition to soft drinks, which are Coca Cola’s main products, the company also produces diet soft drinks. These are variations of the original soft drinks with improvements in nutritional value, and reductions in sugar content. Saccharin replaced industrial sugar in 1963 so that the drinks could appeal to health-conscious consumers. A major cause for concern was the inter product competition which saw some sales dwindle in some products in favor of others.

Coca Cola started diversifying its products during the First World War when ‘Fanta’ was introduced. During World War 1, the heads of Coca Cola in Nazi Germany decided to establish a new soft drink into the market. During the ongoing war, America’s promotion in Germany was not acceptable. Therefore, he decided to use a new name and ‘Fanta’ was born. The creation was successful and production continued even after the war. ‘Sprite’ followed soon after.

In the 1990’s, health concerns among consumers of soft drinks forced their manufactures to consider altering the energy content of these products. ‘Minute Maid’ Juices, ‘PowerAde’ sports drinks, and a few flavored teas variants were Coca Cola’s initial reactions to this new interest. Although most of these new products were well received, some did not perform as well. An example of such was Coca Cola classic, dubbed C2.

Coca Cola Company has been a successful company for more than a century. This can be attributed partly to the nature of its products since soft drinks will always appeal to people. In addition to this, Coca Cola has one of the best commercial and public relations programs in the world. The company’s products can be found on adverts in virtually every corner of the globe. This success has led to its support for a wide range of sporting activities. Soccer, baseball, ice hockey, athletics and basketball are some of these sports, where Coca Cola is involved

Quality Management System at Coca Cola Company

The Quality Management System at Coca Cola

It is very important that each product that Coca Cola produces is of a high quality standard to ensure that each product is exactly the same. This is important as the company wants to meet with customer requirements and expectations. With the brand having such a global presence, it is vital that these checks are continually consistent. The standardized bottle of Coca Cola has elements that need to be checked whilst on the production line to make sure that a high quality is being met. The most common checks include ingredients, packaging and distribution. Much of the testing being taken place is during the production process, as machines and a small team of employees monitor progress. It is the responsibility of all of Coca Colas staff to check quality from hygiene operators to product and packaging quality. This shows that these constant checks require staff to be on the lookout for problems and take responsibility for this, to ensure maintained quality.

Coca-cola uses inspection throughout its production process, especially in the testing of the Coca-Cola formula to ensure that each product meets specific requirements. Inspection is normally referred to as the sampling of a product after production in order to take corrective action to maintain the quality of products. Coca-Cola has incorporated this method into their organisational structure as it has the ability of eliminating mistakes and maintaining high quality standards, thus reducing the chance of product recall. It is also easy to implement and is cost effective.

Coca-cola uses both Quality Control (QC) and Quality Assurance (QA) throughout its production process. QC mainly focuses on the production line itself, whereas QA focuses on its entire operations process and related functions, addressing potential problems very quickly. In QC and QA, state of the art computers check all aspects of the production process, maintaining consistency and quality by checking the consistency of the formula, the creation of the bottle (blowing), fill levels of each bottle, labeling of each bottle, overall increasing the speed of production and quality checks, which ensures that product demands are met. QC and QA helps reduce the risk of defective products reaching a customer; problems are found and resolved in the production process, for example, bottles that are considered to be defective are placed in a waiting area for inspection. QA also focuses on the quality of supplied goods to Coca-cola, for example sugar, which is supplied by Tate and Lyle. Coca-cola informs that they have never had a problem with their suppliers. QA can also involve the training of staff ensuring that employees understand how to operate machinery. Coca-Cola ensures that all members of staff receive training prior to their employment, so that employees can operate machinery efficiently. Machinery is also under constant maintenance, which requires highly skilled engineers to fix problems, and help Coca-cola maintain high outputs.

Every bottle is also checked that it is at the correct fill level and has the correct label. This is done by a computer which every bottle passes through during the production process. Any faulty products are taken off the main production line. Should the quality control measures find any errors, the production line is frozen up to the last good check that was made. The Coca Cola bottling plant also checks the utilization level of each production line using a scorecard system. This shows the percentage of the line that is being utilized and allows managers to increase the production levels of a line if necessary.

Coca-Cola also uses Total Quality Management (TQM) , which involves the management of quality at every level of the organisation , including; suppliers, production, customers etc. This allows Coca-cola to retain/regain competitiveness to achieve increased customer satisfaction . Coca-cola uses this method to continuously improve the quality of their products. Teamwork is very important and Coca-cola ensures that every member of staff is involved in the production process, meaning that each employee understands their job/roles, thus improving morale and motivation , overall increasing productivity. TQM practices can also increase customer involvement as many organisations, including Coca-Cola relish the opportunity to receive feedback and information from their consumers. Overall, reducing waste and costs, provides Coca-cola with a competitive advantage .

The Production Process

Before production starts on the line cleaning quality tasks are performed to rinse internal pipelines, machines and equipment. This is often performed during a switch over of lines for example, changing Coke to Diet Coke to ensure that the taste is the same. This quality check is performed for both hygiene purposes and product quality. When these checks are performed the production process can begin.

Coca Cola uses a database system called Questar which enables them to perform checks on the line. For example, all materials are coded and each line is issued with a bill of materials before the process starts. This ensures that the correct materials are put on the line. This is a check that is designed to eliminate problems on the production line and is audited regularly. Without this system, product quality wouldn’t be assessed at this high level. Other quality checks on the line include packaging and carbonation which is monitored by an operator who notes down the values to ensure they are meeting standards.

To test product quality further lab technicians carry out over 2000 spot checks a day to ensure quality and consistency. This process can be prior to production or during production which can involve taking a sample of bottles off the production line. Quality tests include, the CO2 and sugar values, micro testing, packaging quality and cap tightness. These tests are designed so that total quality management ideas can be put forward. For example, one way in which Coca Cola has improved their production process is during the wrapping stage at the end of the line. The machine performed revolutions around the products wrapping it in plastic until the contents were secure. One initiative they adopted meant that one less revolution was needed. This idea however, did not impact on the quality of the packaging or the actual product therefore saving large amounts of money on packaging costs. This change has been beneficial to the organisation. Continuous improvement can also be used to adhere to environmental and social principles which the company has the responsibility to abide by. Continuous Improvement methods are sometimes easy to identify but could lead to a big changes within the organisation. The idea of continuous improvement is to reveal opportunities which could change the way something is performed. Any sources of waste, scrap or rework are potential projects which can be improved.

The successfulness of this system can be measured by assessing the consistency of the product quality. Coca Cola say that ‘Our Company’s Global Product Quality Index rating has consistently reached averages near 94 since 2007, with a 94.3 in 2010, while our Company Global Package Quality Index has steadily increased since 2007 to a 92.6 rating in 2010, our highest value to date’. This is an obvious indication this quality system is working well throughout the organisation. This increase of the index shows that the consistency of the products is being recognized by consumers.

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McDonald’s Business Studies Case Study

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Resource Description

role of operations management ● strategic role of operations management – cost leadership, good/service differentiation

Operations → business processes that involve transformation/production – Production = conversion of inputs into outputs

Customer focus → minimising waste, fair value for labour, low cost, reflect changes in consumerism Profit centres → aspects of the business that derive revenue and profits Cost centres → areas which cost is attributed

Cost Leadership → aiming to have the lowest cost & be most price-competitive

CASE STUDY: McDonald’s → Mcdonald’s invested in a global training program (Hamburger University) to ensure efficiency and reduce overall costs

goods and/or services in different industries

Goods/Services Differentiation

Standardisation → making products that are all the same

Product Differentiation → distinguishing products

Differentiating Goods Differentiating Services

– Product features – Product quality – Augmented features (add-ons or benefits) – Time spent on a service – Level of expertise – Qualifications and expertise of the service provider – Quality of the materials/technology used in service delivery

Goods Differentiation Perishable goods → short lead times, distributed fast

Non-perishable goods → operations similar in all industries, more durable goods

Self-service → encouraging customers to take initiative

● interdependence with other key business functions

Interdependence → mutual dependency on one another

Interdependence with… Marketing → producing goods based on market needs, marketing based on cost, product design affects transformation

Finance → cost of production, labour costs

Human Resources → staff needed for production, technology changing operations, outsourcing specialists influences

● globalisation, technology, quality expectations, cost-based competition, government policies, legal regulation, environmental sustainability

Globalisation → removal of trade barriers between nations, operating on an international scale & develop international influence

CASE STUDY: McDonald’s → McDonalds has 37,000 restaurants in 120 countries → in 2018, McDonald’s ranked 11th on Forbes list of most valuable brands → 2017 report showed US$91billion in sales, showing success in maintaining competitive advantage by adapting to global conditions

Supply chain management → managing the flows of goods and services, including transformation. – Businesses need a reliable supply chain that is responsive to changes

Technology → the design, construction and application of innovation devices, methods and machinery in the operations process.

– Administrative level → organisation, planning, decision making – Processing level → manufacturing, logistics, quality management, inventory management

CASE STUDY: McDonald’s → digital menu boards, automatic drink dispensers, online ordering apps

Quality → how well designed, made and functionable goods are. – Expectations that people have of business determines the way products are designed, created and delivered.

CASE STUDY: McDonald’s → after complaints of coffee quality, McDonalds made a promise in 2011 that coffee would be barista made. → in 2018, Mcdonalds started using fresh (not frozen) beef patties, despite taking longer to cook, quality was improved

Cost-based Competition → derived from the breakeven point Fixed costs = costs that do not change regardless of business activity Variable costs = costs that vary in relation to business activity/level of production

CASE STUDY: McDonald’s → in 2015, Mcdonalds dominated western Europe, other businesses attempted to compete by lowering their prices → close focus on cost, helps them to maximise profits Government policies & Legal Regulation → Work Health and Safety Act 2011, Fair Work Act 2009, Superannuation Guarantee Act 1992, Racial Discrimination Act 1975, Taxation Act 1953 → influence business operations

CASE STUDY: McDonald’s → McDonalds is bound by obligations in relation to marketing, advertising, product safety and quality guarantees (Australian Consumer Law 2010) → they must ensure conscionable conduct at a local, state and federal level Environmental Sustainability → business operations shaped around sustainable practices

CASE STUDY: McDonald’s → in 2012, McDonalds opened the Australia’s first Green star accredited restaurant in VIC

● corporate social responsibility CSR → doing more than just complying with the law, but having higher respect for people, community and environment Triple Bottom Line → financial profitability, social impact and environmental impact of a business.

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Service Quality -Expectations, perceptions and satisfaction about Service Quality at Destination Gotland -A case study

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Tourist behavior has become more multifaceted and difficult regarding the selection of tourist attraction and services. The main focus of this paper is to understand the relationship of service quality and customer satisfaction in tourism industry. From the previous studies, it was established that that there is a positive association amid customer satisfaction and service quality which attracts tourists to visit the destinations. This paper discussed the dimensions of service quality and customer satisfaction from the previous researchers' viewpoint. In addition, authors also discussed the importance of SERVQUAL Model and highlight its criticism also. The paper is based majorly on secondary data collected from different published research articles, book chapters, reports etc. This paper also discussed the future implication with some management strategies to improve service quality for tourists

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This research attempts to find the impact of service quality on customer satisfaction and retention in Maldives tourism industry. To measure the variables used in the research, a 5-point Likert type questionnaire for performance-only-measure was developed, as in SERVPERF model. A total of 30 questions, including the 22 questions in original SERVQUAL scale, along with additional questions to measure the dependant variables, Customer Satisfaction was included. The independent variables used were, Responsiveness, Assurance, Tangibles, Empathy and Reliability. A descriptive and explanatory research design was selected for this study. A total of 120 samples from different types of tourist establishments, such as Resorts, Guest Houses and Safari Boats were taken using random probability sampling. The data collected was analysed using SPSS 21.0 software, performing descriptive, regression and correlation analysis. The results of this study confirmed three aspects of service quality, Responsiveness, Tangibles and reliability to have positive and significant impact on customer satisfaction. According to the analysis done, Assurance and Empathy does not show an impact on customer satisfaction and retention. As this study was done across all types of tourist establishments in Maldives, a general view is portrayed, and t o determine the exact impact of a dimension on a particular tourist establishment, future study is anticipated.

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Information Technology Services

Office of Internal Audit relies on ITS Managed Desktop Services

By Louise Flinn

Dean Weber chief audit officer in the office of internal audit

The Office of Internal Audit (OIA) at UNC-Chapel Hill is a service unit that assists University management in providing the highest quality education and services to students and the people of North Carolina. Dean Weber, Chief Audit Officer, said that OIA’s underlying premise is that “the University must function at the highest level possible.” The OIA supports this objective by providing independent and proactive analyses of operations, financial activities and systems of internal control. Weber said these analyses evaluate whether resources are used in keeping with State requirements and the University’s mission, goals and objectives.

The Office of Internal Audit has been an ITS Managed Desktop Support (MDS) customer since June 2019. MDS provides IT support to faculty, staff and administrators at UNC-Chapel Hill. The group supplies “fixers” for technical support as well as consultative services, with a focus on security and reliability. It supports 15 different campus departments.

In this customer case study, Weber answered a few questions about the “terrific” partnership between OIA and MDS.

Tell us a little about the Office of Internal Audit.

The University established an internal audit function in 1961 with an internal auditor position in the Division of Business and Finance. Fast forward to 2024, the Office of Internal Audit (OIA) operates as an independent department with the chief audit officer administratively reporting to the University’s chancellor and functionally to the Board of Trustees, Audit, Compliance and Risk Management Committee.

Why did you enlist ITS Managed Desktop Services?

We turned to MDS to aid in supporting the technology administration of our department. As a smaller unit of eight FTE administratively housed under the Chancellor’s Office, we realized our department lacked the professional expertise necessary to maintain our administrative technology needs. Specifically, we needed to ensure our technology was properly managed, administered, secured and understood by our department’s users. MDS was the solution to meet our needs in providing professional, efficient, knowledgeable and user-friendly staffing to support our desktop computing needs.

What services does MDS provide to your department?

MDS provides support and direction guiding desktop computing needs for our department. This encompasses addressing departmental staff’s immediate technology questions, as well as our technology hardware and software application planning needs. MDS quickly and efficiently responds to our requests to prepare laptops for our team members, comprising wiping and refreshing equipment when changes in staffing occur. They readily respond to user inquiries regarding technology access, software application questions and technology procurement needs.

How does partnering with MDS benefit OIA?

Partnering with MDS as the provider for our department’s administrative desktop hardware and software computing needs has been terrific! As a department focused on cost-effectiveness, the OIA recognizes substantial value in this partnership, both from a financial standpoint and in terms of the knowledge-based expertise offered in technology administration. The utilization of this shared University resource adds significant value to our unit, given that the costs incurred are minimal compared to the alternative of hiring an in-house professional to support our computing needs. This strategic approach allows us to benefit from specialized support while maintaining a prudent fiscal approach.

What about MDS’ support or service has exceeded your expectations?

I am consistently impressed by the professionalism and expertise demonstrated by every member of the Managed Desktop Services Team with whom I interact. Their responsiveness in addressing our inquiries, fulfilling requests and addressing concerns is prompt and delivered in a friendly manner. Our designated representative is readily accessible through various communication channels, including text, email, phone and Teams, making the process of reaching out to MDS remarkably convenient.

The utilization of Teams chat and remote screen sharing between MDS and our staff has proven to be an invaluable resource. This collaborative approach facilitates swift and effective solutions, enabling the resolution of technology concerns or problems in real time. This efficient process allows us to promptly return to our work, supporting our audit activities with minimal disruption.

What would you tell other schools or departments that are considering hiring MDS?

I would tell them that based on my experience, this is certainly a value-added opportunity to successfully meet the desktop computing needs of their team. MDS personnel are extremely professional, knowledgeable, responsive and customer focused. They are a valuable resource possessing the expertise necessary to support and solve your team’s desktop computing issues.

Anything else you would like to say?

In the decentralized University operating environment, leveraging Managed Desktop Services (MDS) offers a steadfast and dependable solution for meeting desktop computing requirements. MDS services stand out as an efficient and cost-effective option, equipped with the expertise to offer guidance and direction in addressing user technology needs. This includes providing swift and effective solutions, along with expert advice on the optimal methods for addressing software and hardware requirements.

MDS and the OIA IT Systems Auditor are collaborating to explore IT audit services that will provide MDS management insight. The audit tool Nessus Professional will be used to assist MDS with evaluating settings in the baseline images for computers they configure. The OIA will provide recommendations from the Center for Internet Security (CIS) benchmarks. This collaboration supports our common goals to strengthen controls and add value to the University of North Carolina at Chapel Hill.

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Computer Science > Machine Learning

Title: differential private federated transfer learning for mental health monitoring in everyday settings: a case study on stress detection.

Abstract: Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to mitigate their adverse impacts on life quality. The surge in data-driven methodologies for mental health monitoring has underscored the importance of privacy-preserving techniques in handling sensitive health data. Despite strides in federated learning for mental health monitoring, existing approaches struggle with vulnerabilities to certain cyber-attacks and data insufficiency in real-world applications. In this paper, we introduce a differential private federated transfer learning framework for mental health monitoring to enhance data privacy and enrich data sufficiency. To accomplish this, we integrate federated learning with two pivotal elements: (1) differential privacy, achieved by introducing noise into the updates, and (2) transfer learning, employing a pre-trained universal model to adeptly address issues of data imbalance and insufficiency. We evaluate the framework by a case study on stress detection, employing a dataset of physiological and contextual data from a longitudinal study. Our finding show that the proposed approach can attain a 10% boost in accuracy and a 21% enhancement in recall, while ensuring privacy protection.

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The clinical and neuroimaging differences between vascular parkinsonism and Parkinson's disease: a case-control study

Affiliations.

  • 1 Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • 2 Department of Radiology, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • 3 Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt. [email protected].
  • PMID: 38321372
  • PMCID: PMC10845551
  • DOI: 10.1186/s12883-024-03556-9

Background: Parkinson's disease (PD) and vascular parkinsonism (VaP) have highly overlapping phenotypes, and different prognosis. This study comprehensively investigated the clinical, brain MRI and transcranial sonography differences between VaP and PD.

Methods: Forty-eight patients with PD, 27 patients with VaP, and 29 healthy controls were compared. All patients were assessed using the MDS-UPDRS, Berg Balance Scale (BBS), Ten-Meter Walking Test (10-MWT), Time Up and Go Test, and Non-Motor Symptoms Scale. Beck Depression Inventory, PD questionnaire- 39, international urine incontinence scale, cognitive assessment scales, MRI brain and transcranial colour-coded doppler. The study was registered on clinical-Trial.gov ( NCT04308135 ) on 03/12/2020.

Results: VaP patients showed significantly older age of onset, shorter disease duration, lower drug doses and levodopa responsiveness, higher On and Off axial scores, On and Off BBS, higher On scores for PIGD, rigidity, bradykinesia and total motor MDS-UPDRS, lower On and Off tremor, lower-half predominance, lower asymmetrical presentation and symmetric index than PD patients. VaP patients had worse non-motor symptoms Scale (NMSS) than controls except for perceptual problems/hallucinations but better symptoms than PD patients except for urinary dysfunction. Quality of life (QoL) was impaired in VaP patients and was correlated with motor function and NMSs. The VaP group had significantly higher white matter lesions and brain atrophy, with lower hyperechogenicity of the substantia nigra and more impaired cerebral vascular resistance and vasoreactivity than the PD group.

Conclusions: VaP has a characteristic motor and non-motor profile, with impaired QoL, white matter, and transcranial sonography abnormalities that differentiate it from PD. Further studies are warranted to explore the role of vascular lesions in the pathogenesis of VaP.

Trial registration: The registered identifier NCT04308135 on clinical-Trial.gov. Registered on 03/12/2020.

Keywords: Brain MRI; Non-motor; Parkinson’s disease; Quality of life; TCCD; Vascular parkinsonism.

© 2024. The Author(s).

  • Case-Control Studies
  • Parkinson Disease*
  • Postural Balance
  • Quality of Life / psychology
  • Time and Motion Studies
  • Ultrasonography, Doppler, Transcranial

Associated data

  • ClinicalTrials.gov/NCT04308135

College of Nursing

Driving change: a case study of a dnp leader in residence program in a gerontological center of excellence.

View as pdf A later version of this article appeared in Nurse Leader , Volume 21, Issue 6 , December 2023 . 

The American Association of Colleges of Nursing (AACN) published the Essentials of Doctoral Education for Advanced Practice Nursing in 2004 identifying the essential curriculum needed for preparing advanced practice nurse leaders to effectively assess organizations, identify systemic issues, and facilitate organizational changes. 1 In 2021, AACN updated the curriculum by issuing The Essentials: Core Competencies for Professional Nursing Education to guide the development of competency-based education for nursing students. 1 In addition to AACN’s competency-based approach to curriculum, in 2015 the American Organization of Nurse Leaders (AONL) released Nurse Leader Core Competencies (updated in 2023) to help provide a competency based model to follow in developing nurse leaders. 2

Despite AACN and AONL competency-based curriculum and model, it is still common for nurse leaders to be promoted to management positions based solely on their work experience or exceptional clinical skills, rather than demonstration of management and leadership competencies. 3 The importance of identifying, training, and assessing executive leaders through formal leadership development programs, within supportive organizational cultures has been discussed by national leaders. As well as the need for nurturing emerging leaders through fostering interprofessional collaboration, mentorship, and continuous development of leadership skills has been identified. 4 As Doctor of Nursing Practice (DNP) nurse leaders assume executive roles within healthcare organizations, they play a vital role within complex systems. Demonstration of leadership competence and participation in formal leadership development programs has become imperative for their success. However, models of competency-based executive leadership development programs can be hard to find, particularly programs outside of health care systems.

The implementation of a DNP Leader in Residence program, such as the one designed for The Barbara and Richard Csomay Center for Gerontological Excellence, addresses many of the challenges facing new DNP leaders and ensures mastery of executive leadership competencies and readiness to practice through exposure to varied experiences and close mentoring. The Csomay Center , based at The University of Iowa, was established in 2000 as one of the five original Hartford Centers of Geriatric Nursing Excellence in the country. Later funding by the Csomay family established an endowment that supports the Center's ongoing work. The current Csomay Center strategic plan and mission aims to develop future healthcare leaders while promoting optimal aging and quality of life for older adults. The Csomay Center Director created the innovative DNP Leader in Residence program to foster the growth of future nurse leaders in non-healthcare systems. The purpose of this paper is to present a case study of the development and implementation of the Leader in Residence program, followed by suggested evaluation strategies, and discussion of future innovation of leadership opportunities in non-traditional health care settings.

Development of the DNP Leader in Residence Program

The Plan-Do-Study-Act (PDSA) cycle has garnered substantial recognition as a valuable tool for fostering development and driving improvement initiatives. 5 The PDSA cycle can function as an independent methodology and as an integral component of broader quality enhancement approaches with notable efficacy in its ability to facilitate the rapid creation, testing, and evaluation of transformative interventions within healthcare. 6 Consequently, the PDSA cycle model was deemed fitting to guide the development and implementation of the DNP Leader in Residence Program at the Csomay Center.

PDSA Cycle: Plan

Existing resources. The DNP Health Systems: Administration/Executive Leadership Program offered by the University of Iowa is comprised of comprehensive nursing administration and leadership curriculum, led by distinguished faculty composed of national leaders in the realms of innovation, health policy, leadership, clinical education, and evidence-based practice. The curriculum is designed to cultivate the next generation of nursing executive leaders, with emphasis on personalized career planning and tailored practicum placements. The DNP Health Systems: Administration/Executive Leadership curriculum includes a range of courses focused on leadership and management with diverse topics such as policy an law, infrastructure and informatics, finance and economics, marketing and communication, quality and safety, evidence-based practice, and social determinants of health. The curriculum is complemented by an extensive practicum component and culminates in a DNP project with additional hours of practicum.

New program. The DNP Leader in Residence program at the Csomay Center is designed to encompass communication and relationship building, systems thinking, change management, transformation and innovation, knowledge of clinical principles in the community, professionalism, and business skills including financial, strategic, and human resource management. The program fully immerses students in the objectives of the DNP Health Systems: Administration/Executive Leadership curriculum and enables them to progressively demonstrate competencies outlined by AONL. The Leader in Residence program also includes career development coaching, reflective practice, and personal and professional accountability. The program is integrated throughout the entire duration of the Leader in Residence’s coursework, fulfilling the required practicum hours for both the DNP coursework and DNP project.

The DNP Leader in Residence program begins with the first semester of practicum being focused on completing an onboarding process to the Center including understanding the center's strategic plan, mission, vision, and history. Onboarding for the Leader in Residence provides access to all relevant Center information and resources and integration into the leadership team, community partnerships, and other University of Iowa College of Nursing Centers associated with the Csomay Center. During this first semester, observation and identification of the Csomay Center Director's various roles including being a leader, manager, innovator, socializer, and mentor is facilitated. In collaboration with the Center Director (a faculty position) and Center Coordinator (a staff position), specific competencies to be measured and mastered along with learning opportunities desired throughout the program are established to ensure a well-planned and thorough immersion experience.

Following the initial semester of practicum, the Leader in Residence has weekly check-ins with the Center Director and Center Coordinator to continue to identify learning opportunities and progression through executive leadership competencies to enrich the experience. The Leader in Residence also undertakes an administrative project for the Center this semester, while concurrently continuing observations of the Center Director's activities in local, regional, and national executive leadership settings. The student has ongoing participation and advancement in executive leadership roles and activities throughout the practicum, creating a well-prepared future nurse executive leader.

After completing practicum hours related to the Health Systems: Administration/Executive Leadership coursework, the Leader in Residence engages in dedicated residency hours to continue to experience domains within nursing leadership competencies like communication, professionalism, and relationship building. During residency hours, time is spent with the completion of a small quality improvement project for the Csomay Center, along with any other administrative projects identified by the Center Director and Center Coordinator. The Leader in Residence is fully integrated into the Csomay Center's Leadership Team during this phase, assisting the Center Coordinator in creating agendas and leading meetings. Additional participation includes active involvement in community engagement activities and presenting at or attending a national conference as a representative of the Csomay Center. The Leader in Residence must mentor a master’s in nursing student during the final year of the DNP Residency.

Implementation of the DNP Leader in Residence Program

PDSA Cycle: Do

Immersive experience. In this case study, the DNP Leader in Residence was fully immersed in a wide range of center activities, providing valuable opportunities to engage in administrative projects and observe executive leadership roles and skills during practicum hours spent at the Csomay Center. Throughout the program, the Leader in Residence observed and learned from multidisciplinary leaders at the national, regional, and university levels who engaged with the Center. By shadowing the Csomay Center Director, the Leader in Residence had the opportunity to observe executive leadership objectives such as fostering innovation, facilitating multidisciplinary collaboration, and nurturing meaningful relationships. The immersive experience within the center’s activities also allowed the Leader in Residence to gain a deep understanding of crucial facets such as philanthropy and community engagement. Active involvement in administrative processes such as strategic planning, budgeting, human resources management, and the development of standard operating procedures provided valuable exposure to strategies that are needed to be an effective nurse leader in the future.

Active participation. The DNP Leader in Residence also played a key role in advancing specific actions outlined in the center's strategic plan during the program including: 1) the creation of a membership structure for the Csomay Center and 2) successfully completing a state Board of Regents application for official recognition as a distinguished center. The Csomay Center sponsored membership for the Leader in Residence in the Midwest Nurse Research Society (MNRS), which opened doors to attend the annual MNRS conference and engage with regional nursing leadership, while fostering socialization, promotion of the Csomay Center and Leader in Residence program, and observation of current nursing research. Furthermore, the Leader in Residence participated in the strategic planning committee and engagement subcommittee for MNRS, collaborating directly with the MNRS president. Additional active participation by the Leader in Residence included attendance in planning sessions and completion of the annual report for GeriatricPain.org , an initiative falling under the umbrella of the Csomay Center. Finally, the Leader in Residence was involved in archiving research and curriculum for distinguished nursing leader and researcher, Dr. Kitty Buckwalter, for the Benjamin Rose Institute on Aging, the University of Pennsylvania Barbara Bates Center for the Study of the History of Nursing, and the University of Iowa library archives.

Suggested Evaluation Strategies of the DNP Leader in Residence Program

PDSA Cycle: Study

Assessment and benchmarking. To effectively assess the outcomes and success of the DNP Leader in Residence Program, a comprehensive evaluation framework should be used throughout the program. Key measures should include the collection and review of executive leadership opportunities experienced, leadership roles observed, and competencies mastered. The Leader in Residence is responsible for maintaining detailed logs of their participation in center activities and initiatives on a semester basis. These logs serve to track the progression of mastery of AONL competencies by benchmarking activities and identifying areas for future growth for the Leader in Residence.

Evaluation. In addition to assessment and benchmarking, evaluations need to be completed by Csomay Center stakeholders (leadership, staff, and community partners involved) and the individual Leader in Residence both during and upon completion of the program. Feedback from stakeholders will identify the contributions made by the Leader in Residence and provide valuable insights into their growth. Self-reflection on experiences by the individual Leader in Residence throughout the program will serve as an important measure of personal successes and identify gaps in the program. Factors such as career advancement during the program, application of curriculum objectives in the workplace, and prospects for future career progression for the Leader in Residence should be considered as additional indicators of the success of the program.

The evaluation should also encompass a thorough review of the opportunities experienced during the residency, with the aim of identifying areas for potential expansion and enrichment of the DNP Leader in Residence program. By carefully examining the logs, reflecting on the acquired executive leadership competencies, and studying stakeholder evaluations, additional experiences and opportunities can be identified to further enhance the program's efficacy. The evaluation process should be utilized to identify specific executive leadership competencies that require further immersion and exploration throughout the program.

Future Innovation of DNP Leader in Residence Programs in Non-traditional Healthcare Settings

PDSA Cycle: Act

As subsequent residents complete the program and their experiences are thoroughly evaluated, it is essential to identify new opportunities for DNP Leader in Residence programs to be implemented in other non-health care system settings. When feasible, expansion into clinical healthcare settings, including long-term care and acute care environments, should be pursued. By leveraging the insights gained from previous Leaders in Residence and their respective experiences, the program can be refined to better align with desired outcomes and competencies. These expansions will broaden the scope and impact of the program and provide a wider array of experiences and challenges for future Leaders in Residency to navigate, enriching their development as dynamic nurse executive leaders within diverse healthcare landscapes.

This case study presented a comprehensive overview of the development and implementation of the DNP Leader in Residence program developed by the Barbara and Richard Csomay Center for Gerontological Excellence. The Leader in Residence program provided a transformative experience by integrating key curriculum objectives, competency-based learning, and mentorship by esteemed nursing leaders and researchers through successful integration into the Center. With ongoing innovation and application of the PDSA cycle, the DNP Leader in Residence program presented in this case study holds immense potential to help better prepare 21 st century nurse leaders capable of driving positive change within complex healthcare systems.

Acknowledgements

         The author would like to express gratitude to the Barbara and Richard Csomay Center for Gerontological Excellence for the fostering environment to provide an immersion experience and the ongoing support for development of the DNP Leader in Residence program. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

  • American Association of Colleges of Nursing. The essentials: core competencies for professional nursing education. https://www.aacnnursing.org/Portals/42/AcademicNursing/pdf/Essentials-2021.pdf . Accessed June 26, 2023.
  • American Organization for Nursing Leadership. Nurse leader core competencies. https://www.aonl.org/resources/nurse-leader-competencies . Accessed July 10, 2023.
  • Warshawsky, N, Cramer, E. Describing nurse manager role preparation and competency: findings from a national study. J Nurs Adm . 2019;49(5):249-255. DOI:  10.1097/NNA.0000000000000746
  • Van Diggel, C, Burgess, A, Roberts, C, Mellis, C. Leadership in healthcare education. BMC Med. Educ . 2020;20(465). doi: 10.1186/s12909-020-02288-x
  • Institute for Healthcare Improvement. Plan-do-study-act (PDSA) worksheet. https://www.ihi.org/resources/Pages/Tools/PlanDoStudyActWorksheet.aspx . Accessed July 4, 2023.
  • Taylor, M, McNicolas, C, Nicolay, C, Darzi, A, Bell, D, Reed, J. Systemic review of the application of the plan-do-study-act method to improve quality in healthcare. BMJ Quality & Safety. 2014:23:290-298. doi: 10.1136/bmjqs-2013-002703

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