Understanding physicians' work via text analytics on EHR inbox messages.

OBJECTIVES: To develop a text analytics methodology to analyze in a refined manner the drivers of primary care physicians' (PCPs') electronic health record (EHR) inbox work. STUDY DESIGN: This study used 1 year (2018) of EHR inbox messages obtained from the Epic system for 184 PCPs from 18 practices. METHODS: An advanced text analytics latent Dirichlet allocation model was trained on physicians' inbox message texts to identify the different work themes managed by physicians and their relative share of workload across physicians and clinics. RESULTS: The text analytics model identified 30 different work themes rolled up into 2 categories of medical and administrative tasks. We found that 50.8% (range across physicians, 34.5%-61.9%) of the messages were concerned with medical issues and 34.1% (range, 23.0%-48.9%) focused on administrative matters. More specifically, 13.6% (range, 7.1%-22.6%) of the messages involved ambiguous diagnosis issues, 13.2% (range, 6.9%-18.8%) involved condition management issues, 6.7% (range, 1.9%-13.4%) involved identified symptoms issues, 9.5% (range, 5.2%-28.9%) involved paperwork issues, and 17.6% (range, 9.3%-27.1%) involved scheduling issues. Additionally, there was significant variability among physicians and practices. CONCLUSIONS: This study demonstrated that advanced text analytics provide a reliable data-driven methodology to understand the individual physician's EHR inbox management work with a significantly greater level of detail than previous approaches. This methodology can inform decision makers on appropriate workflow redesign to eliminate unnecessary workload on PCPs and to improve cost and quality of care, as well as staff work satisfaction.

Understanding Physician Work and Well-being Through Social Network Modeling Using Electronic Health Record Data: a Cohort Study.

BACKGROUND: Understanding association between factors related to clinical work environment and well-being can inform strategies to improve physicians' work experience. OBJECTIVE: To model and quantify what drivers of work composition, team structure, and dynamics are associated with well-being. DESIGN: Utilizing social network modeling, this cohort study of physicians in an academic health center examined inbasket messaging data from 2018 to 2019 to identify work composition, team structure, and dynamics features. Indicators from a survey in 2019 were used as dependent variables to identify factors predictive of well-being. PARTICIPANTS: EHR data available for 188 physicians and their care teams from 18 primary care practices; survey data available for 163/188 physicians. MAIN MEASURES: Area under the receiver operating characteristic curve (AUC) of logistic regression models to predict well-being dependent variables was assessed out-of-sample. KEY RESULTS: The mean AUC of the model for the dependent variables of emotional exhaustion, vigor, and professional fulfillment was, respectively, 0.665 (SD 0.085), 0.700 (SD 0.082), and 0.669 (SD 0.082). Predictors associated with decreased well-being included physician centrality within support team (OR 3.90, 95% CI 1.28-11.97, P=0.01) and share of messages related to scheduling (OR 1.10, 95% CI 1.03-1.17, P=0.003). Predictors associated with increased well-being included higher number of medical assistants within close support team (OR 0.91, 95% CI 0.83-0.99, P=0.05), nurse-centered message writing practices (OR 0.89, 95% CI 0.83-0.95, P=0.001), and share of messages related to ambiguous diagnosis (OR 0.92, 95% CI 0.87-0.98, P=0.01). CONCLUSIONS: Through integration of EHR data with social network modeling, the analysis highlights new characteristics of care team structure and dynamics that are associated with physician well-being. This quantitative methodology can be utilized to assess in a refined data-driven way the impact of organizational changes to improve well-being through optimizing team dynamics and work composition.

Opportunities for Interventions That Address Socioeconomic Barriers to Type 2 Diabetes Management: Patient Perspectives.

PURPOSE: The purpose of the study was to explore patient perspectives on socioeconomic barriers related to diabetes self-management and interventions to address these barriers. METHODS: Focus groups (n = 8) were conducted with a diverse sample of adults with type 2 diabetes (T2D; n = 53). Researchers used a semistructured moderator guide; focus groups were audio recorded and transcribed verbatim. Researchers employed the constant comparison method for qualitative content analysis and utilized Atlas.ti (Version 8.1.1) to digitalize the analytic process. RESULTS: Findings revealed 3 primary themes: (1) Existing food and nutrition resources are insufficient to support healthy eating for diabetes; (2) healthy eating is critical for diabetes management, but socioeconomic circumstances make doing so challenging; and (3) participants supported several broad categories of preferred intervention strategies. First, they endorsed lifestyle intervention informed by socioeconomic status (SES; eg, focusing on food resource management, sensitive health coaching and nutritional counseling). Next, they expressed enthusiasm for group-based learning opportunities, such as cooking classes and support groups with similar SES peers. Finally, they suggested healthy food access resources. CONCLUSIONS: Participant suggestions should be incorporated into intervention development. Ultimately, these interventional strategies should be tested and refined to help improve health for individuals with type 2 diabetes.

Multidisciplinary coordinated care for Type 2 diabetes: A qualitative analysis of patient perspectives.

AIMS: To explore the patient perspective on coordinated multidisciplinary diabetes team care among a socioeconomically diverse group of adults with type 2 diabetes. METHODS: Qualitative research design using 8 focus groups (n=53). We randomly sampled primary care patients with type 2 diabetes and conducted focus groups at their primary care clinic. Discussion prompts queried current perceptions of team care. Each focus group was audio recorded, transcribed verbatim, and independently coded by three reviewers. Coding used an iterative process. Thematic saturation was achieved. Data were analyzed using content analysis. RESULTS: Most participants believed that coordinated multidisciplinary diabetes team care was a good approach, feeling that diabetes was too complicated for any one care team member to manage. Primary care physicians were seen as too busy to manage diabetes alone, and participants were content to be treated by other care team members, especially if there was a single point of contact and the care was coordinated. Participants suggested that an ideal multidisciplinary approach would additionally include support for exercise and managing socioeconomic challenges, components perceived to be missing from the existing approach to diabetes care. CONCLUSIONS: Coordinated, multidisciplinary diabetes team care is understood by and acceptable to patients with type 2 diabetes.

Development and Implementation of a Collaborative Team Care Model for Effective Insulin Use in an Academic Medical Center Primary Care Network.

Improving glycemic control across a primary care diabetes population is challenging. This article describes the development, implementation, and outcomes of the Diabetes Care Collaborative Model (DCCM), a collaborative team care process focused on promoting effective insulin use targeting patients with hyperglycemia in a patient-centered medical home model. After a pilot, the DCCM was implemented in 18 primary care practices affiliated with an academic medical center. Its implementation was associated with improvements in glycemic control and increase in insulin prescription longitudinally and across the entire population, with a >1% reduction in the proportion of glycated hemoglobin >9% at 2 years after the implementation compared with the 2 years prior ( P < .001). Facilitating factors included diverse stakeholder engagement, institutional alignment of priorities, awarding various types of credits for participation and implementation to providers, and a strong theoretical foundation using the principles of the collaborative care model.

Diabetes group visits: integrated medical care and behavioral support to improve diabetes care and outcomes from a primary care perspective.

Of the many innovations in health care delivery proposed in the context of health reform for those with chronic diseases such as diabetes, the group visit model is relatively easy to implement and is effective for improving health outcomes and patient and provider satisfaction, with a neutral to positive effect on health care costs. This article describes the evolution of group visits for those with diabetes, the theory underlying group visits for patients with chronic medical conditions, and the existing evidence for the effectiveness of this model. It also addresses implementation of groups in practice, with an emphasis on the practical aspects of program implementation, integration of behavioral expertise into medical groups, individualization in various practice settings, and reimbursement issues.