Evaluation of a Care Coordination/Home-Telehealth Program for Veterans with Diabetes

We evaluated a Veterans Health Administration (VHA) care coordination/ hometelehealth (CC/HT) programon the utilization of health care services and health-related quality of life (HRQL) in veterans with diabetes. Administrative records of 445 veterans with diabetes were reviewed to compare health care service utilization in the 1-year period before and 1-year period postenrollment and also examined self-reported HRQL at enrollment and 1 year later. Multivariate analyses indicated a statistically significant reduction in the proportion of patients who were hospitalized (50% reduction), emergency room use (11% reduction), reduction in the average number of bed days of care (decreased an average of 3.0 days), and improvement in the HRQL role-physical functioning, bodily pain, and social functioning. The results need to be interpreted with caution because we used a single-group study design that may be influenced by regression to the mean. Ideally, future research should use a randomized controlled trial design.

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An evaluation of factors affecting the management of COVID-19 in Bangladesh

Journal of Health Research ◽

10.1108/jhr-08-2020-0323 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Syed S.M Sadrul Huda ◽

Afsana Akhtar ◽

Segufta Dilshad ◽

Syeeda Raisa Maliha

Keyword(s):

Health Care ◽

Care Management ◽

Service Providers ◽

Care Service ◽

Health Care Service ◽

Health Care Management ◽

Lessons Learned ◽

Future Research ◽

Content Type ◽

The Social

PurposeThe study aims to gain insights into the management of COVID-19 in Bangladesh to identify the factors that are relevant to managing the pandemic in a developing country.Design/methodology/approachThe study was carried out by pursuing the archival method. The information was collected from credible newspaper reports over the previous months, as well as articles published on the subject of COVID-19.FindingsThe research revealed important and relevant dimensions of the health sector in managing the COVID-19 pandemic. The major factors were doctors, nurses (health service providers), patients, (customers) and society. This is a pioneering paper, which documents the major lessons learned from the management of COVID-19 in Bangladesh concerning three stakeholders of the health-care system, i.e. providers, patients and society. This paper covers the situation regarding the ongoing pandemic from three perspectives – provider, customers and society, and thus, may help to develop future research regarding the development of health-care management models for addressing the pandemic.Research limitations/implicationsThe major limitations of this paper is its over dependence on secondary sources for collecting the information.Practical implicationsThis paper presents the learnings from the pandemic in health-care management in different categories (e.g. social, doctor/nurse, patients), which can help the managers in understanding different dimensions of the health-care sector from different perspectives. The problems as well as the learnings stated in the paper can help the policy makers implement such strategies to ensure better delivery of the medical health-care service during a pandemic.Social implicationsThis paper clearly reveals the social dimensions of the COVID-19 by assessing the social aspects of COVID-19 management. Both social stigma and support are traced out during evaluating the situation. Thus, the social forces will be able to rethink about their role in addressing the social costs of pandemic.Originality/valueThis is a commentary piece.

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The relationship between perceived dissimilarity and feedback avoidance behaviour

International Journal of Conflict Management ◽

10.1108/ijcma-08-2019-0127 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Meng Song ◽

Kubilay Gok ◽

Sherry Moss ◽

Nancy Borkowski

Keyword(s):

Health Care ◽

Service Sector ◽

Care Service ◽

Health Care Service ◽

Avoidance Behaviour ◽

Future Research ◽

Interpersonal Processes ◽

Conflict Task ◽

Content Type ◽

Study Results

Purpose The purpose of this study is to understand the conditions in which subordinates, after making a mistake, are more likely to engage in feedback avoidance behaviour (FAB), a set of behaviours that could ultimately jeopardise patient safety in a health care context. Design/methodology/approach This study used a sample of 183 independent leader-subordinate dyads in the health care service sector. For this study, a multiple mediator model in which three types of conflict (task conflict, relationship conflict and process conflict) were tested and acted as mediating mechanisms that transmitted the effects of perceived dissimilarity to FAB. Findings The results supported the mediating role of two of the three forms of conflict and highlighted the consequences of dissimilarity between supervisors and subordinates in the healthcare setting. Research limitations/implications One of the noteworthy limitations of this study was that this study used cross-sectional time-lagged data. Future research should use a more rigorous longitudinal approach such as a cross-lagged design (Whitman et al., 2012) to explore the dynamic nature of dyadic relationships over time. Practical implications An important implication of our study results suggests that health care leadership development training should provide opportunities to increase awareness of the tendency of leaders to treat subordinates perceived as dissimilar more negatively. Originality/value These results contribute to our understanding of the interpersonal processes between subordinates and their supervisors, which could have a significant impact on organisational outcomes in the health care setting.

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Self- and Other-Dehumanization Processes in Health-Related Contexts: A Critical Review of the Literature

Review of General Psychology ◽

10.1177/1089268019880889 ◽

2019 ◽

Vol 23 (4) ◽

pp. 475-495 ◽

Cited By ~ 3

Author(s):

Eva Diniz ◽

Sónia F. Bernardes ◽

Paula Castro

Keyword(s):

Health Care ◽

Critical Review ◽

Person Perception ◽

Meaning Making ◽

Care Service ◽

Health Care Service ◽

Service Research ◽

Future Research ◽

Self And Other ◽

Health Related

Dehumanization is an everyday, pervasive phenomenon in health contexts. Given its detrimental consequences to health care, much research has been dedicated to understanding and promoting the humanization of health services. However, health care service research has neglected the sociopsychological processes involved in the dehumanization of self and others, in formal but also informal health-related contexts. Drawing upon sociopsychological models of dehumanization, this article will bridge this gap by presenting a critical review of studies on everyday meaning-making and person perception processes of dehumanization in health-related contexts. A database search was conducted in PsycINFO, Web of Science, Scopus, and PubMed, using a combination of keywords on dehumanization and health/illness/body; 3,229 references were screened; 95 full texts were assessed for eligibility; 59 studies were included. Most studies focused on informal contexts, reflecting a decontextualized and one-sided view of dehumanization (i.e., not integrating actors’ and victims’ perspectives). Despite the dominant focus on self-dehumanization, emerging perspectives uncover the role of processes that deny human uniqueness to others, and their individual determinants and consequences for mental health. A few studies bring to light the functions of a variety of dehumanizing body metaphors on self- and other-dehumanization. These trends in the literature leave several gaps, which are here critically analyzed to inform future research.

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Nursing Facility and Health Care Service Use and Costs Under the CMS Financial Alignment Initiative

Innovation in Aging ◽

10.1093/geroni/igab046.1289 ◽

2021 ◽

Vol 5 (Supplement_1) ◽

pp. 334-334

Author(s):

Lauren Palmer ◽

Matt Toth ◽

Joyce Wang ◽

Emily Schneider ◽

Allison Dorneo ◽

...

Keyword(s):

Health Care ◽

Service Utilization ◽

Care Coordination ◽

Care Service ◽

Health Care Service ◽

Nursing Facility ◽

Data Set ◽

Ed Visits ◽

Medicare Costs ◽

The Impact

Abstract The Centers for Medicare & Medicaid Services created the Financial Alignment Initiative (FAI) to test the impact of integrated care and financing models for dually eligible Medicare-Medicaid beneficiaries. Using Medicare claims, the Minimum Data Set 3.0, and state-provided enrollment files, we evaluated demonstration impacts on long-stay nursing facility (NF) use, other health care service utilization, and costs for the overall eligible population in two FAI demonstration States with managed fee-for-service models, Colorado and Washington. We used quasi-experimental, difference-in-differences regression models for the impact analyses. In Colorado, there was a 7.2 percent decrease (p<0.001) in long-stay NF use, relative to the comparison group. Otherwise, the demonstration showed unfavorable service utilization results—increases in preventable emergency department (ED) visits and declines in 30-day follow-up after mental health discharge (MHFU)—and no impact on Medicare costs. In Washington, there was also a decrease in long-stay NF use (12.4 percent, p<0.001) and skilled NF admissions (21.7 percent, p<0.001). However, the demonstration resulted in decreases in physician visits and 30-day MHFU. There was a favorable decrease in Medicare costs. The impact of the FAI demonstrations on NF use was favorable for both States, while the impact on service utilization and Medicare costs was mixed and more favorable in Washington. Washington’s care coordination model was intensive and targeted to high-cost individuals while Colorado provided minimal care coordination. Coordinated care and integrated long-term services and support may help postpone NF institutionalization, but there is no evidence these activities reduced preventable hospitalizations or ED visits.

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Conversational Agents in Health Care: Scoping Review and Conceptual Analysis (Preprint)

10.2196/preprints.17158 ◽

2019 ◽

Author(s):

Lorainne Tudor Car ◽

Dhakshenya Ardhithy Dhinagaran ◽

Bhone Myint Kyaw ◽

Tobias Kowatsch ◽

Shafiq Joty ◽

...

Keyword(s):

Health Care ◽

Scoping Review ◽

Literature Search ◽

Care Service ◽

Health Care Service ◽

Improve Patient Care ◽

Future Research ◽

Free Text ◽

Conversational Agents ◽

Service Support

BACKGROUND Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. OBJECTIVE This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. METHODS We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. RESULTS The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. CONCLUSIONS The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

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The effects of homelessness on Veterans' health care service use: an evaluation of independence from comorbidities

Public Health ◽

10.1016/j.puhe.2014.07.004 ◽

2014 ◽

Vol 128 (11) ◽

pp. 985-992 ◽

Cited By ~ 14

Author(s):

J.P. LePage ◽

L.D. Bradshaw ◽

D.J. Cipher ◽

A.M. Crawford ◽

D. Hoosyhar

Keyword(s):

Health Care ◽

Service Use ◽

Care Service ◽

Health Care Service ◽

Veterans Health ◽

Health Care Service Use

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Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial

JMIR mhealth and uhealth ◽

10.2196/14817 ◽

2020 ◽

Vol 8 (4) ◽

pp. e14817

Author(s):

Meelim Kim ◽

Youngin Kim ◽

Yoonjeong Go ◽

Seokoh Lee ◽

Myeongjin Na ◽

...

Keyword(s):

Health Care ◽

Behavioral Therapy ◽

Care Service ◽

Digital Health ◽

Controlled Trial ◽

Health Care Service ◽

Control Group ◽

Open Label ◽

Randomized Controlled

Background Developing effective, widely useful, weight management programs is a priority in health care because obesity is a major health problem. Objective This study developed and investigated a new, comprehensive, multifactorial, daily, intensive, psychologist coaching program based on cognitive behavioral therapy (CBT) modules. The program was delivered via the digital health care mobile services Noom Coach and InBody. Methods This was an open-label, active-comparator, randomized controlled trial. A total of 70 female participants with BMI scores above 24 kg/m2 and no clinical problems besides obesity were randomized into experimental and control groups. The experimental (ie, digital CBT) group (n=45) was connected with a therapist intervention using a digital health care service that provided daily feedback and assignments for 8 weeks. The control group (n=25) also used the digital health care service, but practiced self-care without therapist intervention. The main outcomes of this study were measured objectively at baseline, 8 weeks, and 24 weeks and included weight (kg) as well as other body compositions. Differences between groups were evaluated using independent t tests and a per-protocol framework. Results Mean weight loss at 8 weeks in the digital CBT group was significantly higher than in the control group (–3.1%, SD 4.5, vs –0.7%, SD 3.4, P=.04). Additionally, the proportion of subjects who attained conventional 5% weight loss from baseline in the digital CBT group was significantly higher than in the control group at 8 weeks (32% [12/38] vs 4% [1/21], P=.02) but not at 24 weeks. Mean fat mass reduction in the digital CBT group at 8 weeks was also significantly greater than in the control group (–6.3%, SD 8.8, vs –0.8%, SD 8.1, P=.02). Mean leptin and insulin resistance in the digital CBT group at 8 weeks was significantly reduced compared to the control group (–15.8%, SD 29.9, vs 7.2%, SD 35.9, P=.01; and –7.1%, SD 35.1, vs 14.4%, SD 41.2, P=.04). Emotional eating behavior (ie, mean score) measured by questionnaire (ie, the Dutch Eating Behavior Questionnaire) at 8 weeks was significantly improved compared to the control group (–2.8%, SD 34.4, vs 21.6%, SD 56.9, P=.048). Mean snack calorie intake in the digital CBT group during the intervention period was significantly lower than in the control group (135.9 kcal, SD 86.4, vs 208.2 kcal, SD 166.3, P=.02). Lastly, baseline depression, anxiety, and self-esteem levels significantly predicted long-term clinical outcomes (24 weeks), while baseline motivation significantly predicted both short-term (8 weeks) and long-term clinical outcomes. Conclusions These findings confirm that technology-based interventions should be multidimensional and are most effective with human feedback and support. This study is innovative in successfully developing and verifying the effects of a new CBT approach with a multidisciplinary team based on digital technologies rather than standalone technology-based interventions. Trial Registration ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306

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Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial (Preprint)

10.2196/preprints.14817 ◽

2019 ◽

Author(s):

Meelim Kim ◽

Youngin Kim ◽

Yoonjeong Go ◽

Seokoh Lee ◽

Myeongjin Na ◽

...

Keyword(s):

Health Care ◽

Behavioral Therapy ◽

Care Service ◽

Digital Health ◽

Controlled Trial ◽

Health Care Service ◽

Control Group ◽

Open Label ◽

Randomized Controlled

BACKGROUND Developing effective, widely useful, weight management programs is a priority in health care because obesity is a major health problem. OBJECTIVE This study developed and investigated a new, comprehensive, multifactorial, daily, intensive, psychologist coaching program based on cognitive behavioral therapy (CBT) modules. The program was delivered via the digital health care mobile services Noom Coach and InBody. METHODS This was an open-label, active-comparator, randomized controlled trial. A total of 70 female participants with BMI scores above 24 kg/m2 and no clinical problems besides obesity were randomized into experimental and control groups. The experimental (ie, digital CBT) group (n=45) was connected with a therapist intervention using a digital health care service that provided daily feedback and assignments for 8 weeks. The control group (n=25) also used the digital health care service, but practiced self-care without therapist intervention. The main outcomes of this study were measured objectively at baseline, 8 weeks, and 24 weeks and included weight (kg) as well as other body compositions. Differences between groups were evaluated using independent t tests and a per-protocol framework. RESULTS Mean weight loss at 8 weeks in the digital CBT group was significantly higher than in the control group (–3.1%, SD 4.5, vs –0.7%, SD 3.4, P=.04). Additionally, the proportion of subjects who attained conventional 5% weight loss from baseline in the digital CBT group was significantly higher than in the control group at 8 weeks (32% [12/38] vs 4% [1/21], P=.02) but not at 24 weeks. Mean fat mass reduction in the digital CBT group at 8 weeks was also significantly greater than in the control group (–6.3%, SD 8.8, vs –0.8%, SD 8.1, P=.02). Mean leptin and insulin resistance in the digital CBT group at 8 weeks was significantly reduced compared to the control group (–15.8%, SD 29.9, vs 7.2%, SD 35.9, P=.01; and –7.1%, SD 35.1, vs 14.4%, SD 41.2, P=.04). Emotional eating behavior (ie, mean score) measured by questionnaire (ie, the Dutch Eating Behavior Questionnaire) at 8 weeks was significantly improved compared to the control group (–2.8%, SD 34.4, vs 21.6%, SD 56.9, P=.048). Mean snack calorie intake in the digital CBT group during the intervention period was significantly lower than in the control group (135.9 kcal, SD 86.4, vs 208.2 kcal, SD 166.3, P=.02). Lastly, baseline depression, anxiety, and self-esteem levels significantly predicted long-term clinical outcomes (24 weeks), while baseline motivation significantly predicted both short-term (8 weeks) and long-term clinical outcomes. CONCLUSIONS These findings confirm that technology-based interventions should be multidimensional and are most effective with human feedback and support. This study is innovative in successfully developing and verifying the effects of a new CBT approach with a multidisciplinary team based on digital technologies rather than standalone technology-based interventions. CLINICALTRIAL ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306

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Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

Journal of Medical Internet Research ◽

10.2196/17158 ◽

2020 ◽

Vol 22 (8) ◽

pp. e17158 ◽

Cited By ~ 2

Author(s):

Lorainne Tudor Car ◽

Dhakshenya Ardhithy Dhinagaran ◽

Bhone Myint Kyaw ◽

Tobias Kowatsch ◽

Shafiq Joty ◽

...

Keyword(s):

Health Care ◽

Scoping Review ◽

Literature Search ◽

Care Service ◽

Health Care Service ◽

Improve Patient Care ◽

Future Research ◽

Free Text ◽

Conversational Agents ◽

Service Support

Background Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care. Objective This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application. Methods We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms “conversational agents,” “conversational AI,” “chatbots,” and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis. Results The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education. Conclusions The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence–driven, and smartphone app–delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents’ formats, focusing on their acceptability, safety, and effectiveness.

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The advanced care coordination program: a protocol for improving transitions of care for dual-use veterans from community emergency departments back to the Veterans Health Administration (VA) primary care

BMC Health Services Research ◽

10.1186/s12913-019-4582-3 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Lindsay B. Miller ◽

Heidi Sjoberg ◽

Ashlea Mayberry ◽

Marina S. McCreight ◽

Roman A. Ayele ◽

...

Keyword(s):

Health Care ◽

Quality Improvement ◽

Social Worker ◽

Care Coordination ◽

Veterans Health Administration ◽

Transitions Of Care ◽

Veterans Health ◽

Health Administration ◽

Dual Use ◽

Effective Care

Abstract Background Veterans who access both the Veterans Health Administration (VA) and non-VA health care systems require effective care coordination to avoid adverse health care outcomes. These dual-use Veterans have diverse and complex needs. Gaps in transitions of care between VA and non-VA systems are common. The Advanced Care Coordination (ACC) quality improvement program aims to address these gaps by implementing a comprehensive longitudinal care coordination intervention with a focus on Veterans’ social determinants of health (SDOH) to facilitate Veterans’ transitions of care back to the Eastern Colorado Health Care System (ECHCS) for follow-up care. Methods The ACC program is an ongoing quality improvement study that will enroll dual-use Veterans after discharge from non-VA emergency department (EDs), and will provide Veterans with social worker-led longitudinal care coordination addressing SDOH and providing linkage to resources. The ACC social worker will complete biopsychosocial assessments to identify Veteran needs, conduct regular in-person and phone visits, and connect Veterans back to their VA care teams. We will identify non-VA EDs in the Denver, Colorado metro area that will provide the most effective partnership based on location and Veteran need. Veterans will be enrolled into the ACC program when they visit one of our selected non-VA EDs without being hospitalized. We will develop a program database to allow for continuous evaluation. Continuing education and outreach including the development of a resource guide, Veteran Care Cards, and program newsletters will generate program buy-in and bridge communication. We will evaluate our program using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework, supported by the Practical, Robust Implementation and Sustainability Model, Theoretical Domains Framework, and process mapping. Discussion The ACC program will improve care coordination for dual-use Veterans by implementing social-work led longitudinal care coordination addressing Veterans’ SDOH. This intervention will provide an essential service for effective care coordination.

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