Evaluating the Implementation of the Diabetes Self-Management Program in a Rural Population

The evidence-based Diabetes Self-Management Program (DSMP) has been shown to improve a variety of health-related outcomes, but the program has been challenging to implement in rural areas, and rural dissemination has been low. The purpose of this project was to evaluate the effect of implementing the DSMP on self-reported outcomes in a rural region. Through a collaboration with multiple partners, the Living Well program delivered 28 DSMP workshops from 2017 to 2019. Data were collected to determine whether there were post-intervention changes in patient-reported outcomes on measures of diabetes distress, self-management, and patient activation. In addition, secondary analysis of A1C was abstracted from the medical records of participants with type 2 diabetes who completed at least four sessions of a DSMP workshop between 2017 and 2019 and whose medical records had a A1C value in the year before the program and at least one A1C value >3 months after the program. Statistically significant improvements were seen for the Diabetes Distress Scale (P = 0.0017), the Diabetes Self-Management Questionnaire (P <0.0001) and the 10-item Patient Activation Measure (P <0.0001). There was no evidence of change in A1C over time in analyses of all participants (P = 0.5875), but a consistent though nonsignificant (P = 0.1087) decline in A1C was seen for a subset of participants with a baseline A1C ≥8%. This evaluation provides preliminary support for implementing the DSMP as part of a comprehensive treatment and self-management plan for people living with diabetes in rural areas.

Characterization of Symptoms and Symptom Clusters for Type 2 Diabetes Using a Large Nationwide Electronic Health Record Database

OBJECTIVE A variety of symptoms may be associated with type 2 diabetes and its complications. Symptoms in chronic diseases may be described in terms of prevalence, severity, and trajectory and often co-occur in groups, known as symptom clusters, which may be representative of a common etiology. The purpose of this study was to characterize type 2 diabetes–related symptoms using a large nationwide electronic health record (EHR) database. Methods We acquired the Cerner Health Facts, a nationwide EHR database. The type 2 diabetes cohort (n = 1,136,301 patients) was identified using a rule-based phenotype method. A multistep procedure was then used to identify type 2 diabetes–related symptoms based on International Classification of Diseases, 9th and 10th revisions, diagnosis codes. Type 2 diabetes–related symptoms and co-occurring symptom clusters, including their temporal patterns, were characterized based the longitudinal EHR data. Results Patients had a mean age of 61.4 years, 51.2% were female, and 70.0% were White. Among 1,136,301 patients, there were 8,008,276 occurrences of 59 symptoms. The most frequently reported symptoms included pain, heartburn, shortness of breath, fatigue, and swelling, which occurred in 21–60% of the patients. We also observed over-represented type 2 diabetes symptoms, including difficulty speaking, feeling confused, trouble remembering, weakness, and drowsiness/sleepiness. Some of these are rare and difficult to detect by traditional patient-reported outcomes studies. Conclusion To the best of our knowledge, this is the first study to use a nationwide EHR database to characterize type 2 diabetes–related symptoms and their temporal patterns. Fifty-nine symptoms, including both over-represented and rare diabetes-related symptoms, were identified.

The Diabetes Simulation Challenge: Enhancing Patient Perspective-Taking for Medical Students

The Diabetes Simulation Challenge is a unique training tool to foster empathy, a key facet of patient-centered care, for medical students. Thirty-two medical students participated in a 24-hour perspective-taking activity as part of their curriculum, during which they simulated some common experiences of living with a chronic health condition, specifically type 1 diabetes. Students’ written reflections were analyzed using a phenomenological qualitative approach to provide a composite description of the experience. An exhaustive, iterative method of thematic analysis that included manual coding was used to determine whether this activity led to expressions of empathy or thoughts and beliefs consistent with patient-centered health care. Nine unique themes emerged, six of which indicated that students adopted the perspective of an individual with a chronic illness. Most of the students’ reflections illustrated an understanding of the behavioral, social, and emotional challenges related to living with type 1 diabetes, as well as increased empathy toward individuals with the disease. Medical students who aim to provide patient-centered care benefited from this perspective-taking exercise, and training programs should consider using such methods to extend learning beyond traditional didactic education.

Remote Patient Monitoring in Diabetes: How to Acquire, Manage, and Use All of The Data

The ability of patients and health care providers to use various forms of technology for general health has significantly increased in the past several years with the expansion of telehealth, digital applications, personal digital devices, smartphones, and other Internet-connected platforms and devices. For individuals with diabetes, this also includes connected blood glucose meters, continuous glucose monitoring devices, and insulin delivery systems. In this article, the authors outline several steps to facilitate the acquisition, management, and meaningful use of digital diabetes data that can enable successful implementation of both diabetes technology and telehealth services in primary care clinics.

A Conversation on an Effective, Straightforward, Quantitative Approach to the Outpatient Use of Insulin

For primary care providers, using insulin can present challenges that can be met by a straightforward approach using the following principles. Depending on when it is injected, each component of the insulin regimen has a maximal effect on a specific period of the 24-hour cycle (e.g., overnight, morning, afternoon, or evening). The glucose pattern in that period determines whether the dose of that component of the insulin regimen requires adjusting. Regarding which insulin types and insulin regimens to use, human insulin (NPH and regular) is as effective as analog insulins, and a two-injection intensified insulin regimen is as effective as a four-injection regimen.

Risk of Negative Health Outcomes and High Costs for People With Diabetes and Unmet Psychological Needs in the United States

Measuring the population-level relationship between compromised mental health and diabetes care remains an important goal for clinicians and health care decision-makers. We evaluated the impact of self-reported unmet psychological need on health care resource utilization and total health care expenditure in people with type 2 diabetes. Patients who reported unmet psychological needs were more likely than those who did not to incur a higher annual medical expenditure, have greater resource utilization, and have a higher risk of all-cause mortality.

Home Telemonitoring of Patients With Type 2 Diabetes: A Meta-Analysis and Systematic Review

Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (−0.10 mmHg [P = 0.0041], and −0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.