Barriers and Facilitators in Implementing Non-Face-to-Face Chronic Care Management in an Elderly Population with Diabetes: A Qualitative Study of Physician and Health System Perspectives

Bazzano, Alessandra N.; Wharton, M. Kristina; Monnette, Alisha; Nauman, Elizabeth; Price‐Haywood, Eboni G.; Glover, Cathy; Dominick, Patricia; Malone, Peggy; Hu, Gang; Shi, Lizheng

doi:10.3390/jcm7110451

Cited by 17 publications

(21 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although they were focused only on the high-risk strategy, the implementation of telephone counseling, follow-up, and distance clinical services allowed health teams to become familiar with telemedicine strategies. Cultural and regulatory barriers make their incorporation difficult, as described in the literature [25,26], and we were able to experience it during the piloting. Barriers range from registration of the activities to the performance of the remote service.…”

Section: Discussionmentioning

confidence: 95%

Impact of a high-risk multimorbidity integrated care implemented at the public health system in Chile

et al. 2022

View full text Add to dashboard Cite

During recent years, multimorbidity has taken relevance because of the impact of causes in the system, people, and their families, which has been a priority in the health care plan. Interventions strategies and their implementation are still an emerging topic. In this context, Centro de Innovación en Salud ANCORA UC, together with Servicio de Salud Metropolitano Sur Oriente, implemented as a pilot study High-Risk Multimorbidity Integrated Care strategy. This study aimed to evaluate the impact of this strategy in terms of health services utilization and mortality. A cohort study was conducted with high-risk patients with multimorbidity, stratified by ACG®, intervened between April 2017 and December 2019. The studied population was 3,933 patients who belonged to similar size and location primary care centers. The impact analysis was performed used generalized linear models. Results showed that intervened patients had a significantly lower incidence in mortality (OR 0.56; 95% CI 0.40–0.77), hospital admissions, length of stay, and the number of hospital emergency consultancies. With the proper barriers and facilitators of a real context intervention, the implementation process allowed the systematization and consolidation of the intervention provided in this study. The training for new roles and the constant implementation support from the Centro de Innovación en Salud ANCORA UC team were essential in the progress and success of the intervention. A complete description of the high-risk intervention strategy is provided to contribute to this emerging topic and facilitate its scale-up. We can conclude that this complex intervention was feasible to be implemented in a real context. The Ministry of Health has taken the systematization and consolidation of the conditions for the national scale-up.

show abstract

Section: Discussionmentioning

confidence: 95%

Impact of a high-risk multimorbidity integrated care implemented at the public health system in Chile

et al. 2022

View full text Add to dashboard Cite

show abstract

“…To develop effective interventions to facilitate health behavior, a detailed understanding of the demographic, psychological, and ecological factors is required, as suggested Hardcastle and Hagger [44]. In this sense, technologies offer today new ways for implementing non-face to face care management for elderly population [45]. Finally, we should not ignore the fact that the psychosocial environment also includes the family and the partner, who also seems to be an important predictor to explain health behavior in mature ages [46].…”

Section: Discussionmentioning

confidence: 99%

Health Behavior and Health and Psychosocial Planning for Retirement among Spanish Health Professionals

Hurtado

Topa

2018

JCM

View full text Add to dashboard Cite

The aging of the workforce among health professionals demands attention to the study of their health behavior before retirement. The aim of the present study is to analyze the relationships between health planning and psychosocial planning—on the one hand—and health professionals’ health behavior, on the other. In addition, we will study the mediator role of public protection, self-insurance, and self-protection in the relationship between planning and health behavior. The sample includes 169 healthcare professionals from a public hospital in Spain. A serial mediation model estimating all of the parameters simultaneously was tested. The findings have confirmed the relationship between health planning and health behavior, as well as the serial mediation of the behaviors in this relationship. As the main causes of death in the Western world are not transmittable diseases, but cardiovascular diseases, diabetes, and other diseases that are closely linked to lifestyle factors, our findings strongly support that we are responsible for our long-term health status and well-being.

show abstract

“…This study is a secondary data analysis of EHR data acquired from the Louisiana Experiment Assessing Diabetes cohort study. The LEAD cohort includes electronic health record data which were obtained from the Research Action for Health Network (REACHnet) for the time period between January 1, 2013, and October 31, 2017 [ 19 ]. Clinical data from REACHNet conform to the National Patient-Centered Clinical Research Network (PCORnet) common data model, the specification that defines a standard organization and representation of data for the PCORnet distributed research network [ 20 ].…”

Section: Methodsmentioning

confidence: 99%

Electronic Medical Record Risk Modeling of Cardiovascular Outcomes Among Patients with Type 2 Diabetes

et al. 2021

Self Cite

View full text Add to dashboard Cite

Introduction: Increased utilization of electronic health records (EHR) has enriched databases for creating risk models. We used machine learning techniques to develop an EHR-based risk model locally fitted to patients with type 2 diabetes mellitus (T2DM) for predicting cardiovascular disease. Methods: This retrospective observational study was conducted within Ochsner Health, Louisiana, USA, between 2013-2017. Data analysis included 6245 patients who had two outpatient diagnoses of T2DM recorded on separate days or a diagnosis recorded during an inpatient encounter. Baseline clinical data were limited to 180 days before the index diagnosis. Cardiovascular outcomes were coronary heart disease (CHD), heart failure and stroke. Machine learning approaches were used to select predictor variables into Cox proportional hazards models for each outcome. Locally fit equations were compared to ''generalized'' risk equations (RECODe, AS-CVD, QRISK3) using model discrimination and calibration. Results: Among factors identified in the Ochsner (n = 11), RECODe (n = 14), AS-CVD (n = 15) and QRISK3 (n = 23), only age was common to all four risk equations. The Ochsner model had high internal discrimination for CHD (C-statistics 0.85) and better discrimination than RECODe (C-statistics 0.45), the QRISK3 (C-statistics 0.72) and AS-CVD (Cstatistics 0.54). Conclusions: The Ochsner model overestimated 5-year CHD risk, but had relatively higher calibration than the other models in CHD. Risk equations fitted for local populations improved cardiovascular risk stratification for patients with T2DM. Application of machine learning simplified the models compared to ''generalized'' risk equations.

show abstract

Barriers and Facilitators in Implementing Non-Face-to-Face Chronic Care Management in an Elderly Population with Diabetes: A Qualitative Study of Physician and Health System Perspectives

Cited by 17 publications

References 33 publications

Impact of a high-risk multimorbidity integrated care implemented at the public health system in Chile

Impact of a high-risk multimorbidity integrated care implemented at the public health system in Chile

Health Behavior and Health and Psychosocial Planning for Retirement among Spanish Health Professionals

Electronic Medical Record Risk Modeling of Cardiovascular Outcomes Among Patients with Type 2 Diabetes

Contact Info

Product

Resources

About