State-level metabolic comorbidity prevalence and control among adults age 50-plus with diabetes: estimates from electronic health records and survey data in five states.

BACKGROUND: Although treatment and control of diabetes can prevent complications and reduce morbidity, few data sources exist at the state level for surveillance of diabetes comorbidities and control. Surveys and electronic health records (EHRs) offer different strengths and weaknesses for surveillance of diabetes and major metabolic comorbidities. Data from self-report surveys suffer from cognitive and recall biases, and generally cannot be used for surveillance of undiagnosed cases. EHR data are becoming more readily available, but pose particular challenges for population estimation since patients are not randomly selected, not everyone has the relevant biomarker measurements, and those included tend to cluster geographically. METHODS: We analyzed data from the National Health and Nutritional Examination Survey, the Health and Retirement Study, and EHR data from the DARTNet Institute to create state-level adjusted estimates of the prevalence and control of diabetes, and the prevalence and control of hypertension and high cholesterol in the diabetes population, age 50 and over for five states: Alabama, California, Florida, Louisiana, and Massachusetts. RESULTS: The estimates from the two surveys generally aligned well. The EHR data were consistent with the surveys for many measures, but yielded consistently lower estimates of undiagnosed diabetes prevalence, and identified somewhat fewer comorbidities in most states. CONCLUSIONS: Despite these limitations, EHRs may be a promising source for diabetes surveillance and assessment of control as the datasets are large and created during the routine delivery of health care. TRIAL REGISTRATION: Not applicable.

Use and Impact of Type 2 Diabetes Prevention Interventions.

INTRODUCTION: RCTs have found that type 2 diabetes can be prevented among high-risk individuals by metformin medication and evidence-based lifestyle change programs. The purpose of this study is to estimate the use of interventions to prevent type 2 diabetes in real-world clinical practice settings and determine the impact on diabetes-related clinical outcomes. METHODS: The analysis performed in 2020 used 2010‒2018 electronic health record data from 69,434 patients aged ≥18 years at high risk for type 2 diabetes in 2 health systems. The use and impact of prescribed metformin, lifestyle change program, bariatric surgery, and combinations of the 3 were examined. A subanalysis was performed to examine uptake and retention among patients referred to the National Diabetes Prevention Program. RESULTS: Mean HbA1c values declined from before to after intervention for patients who were prescribed metformin (-0.067%; p<0.001) or had bariatric surgery (-0.318%; p<0.001). Among patients referred to the National Diabetes Prevention Program lifestyle change program, the type 2 diabetes postintervention incidence proportion was 14.0% for nonattendees, 12.8% for some attendance, and 7.5% for those who attended ≥4 sessions (p<0.001). Among referred patients to the National Diabetes Prevention Program lifestyle change program, uptake was low (13% for 1‒3 sessions, 15% for ≥4 sessions), especially among males and Hispanic patients. CONCLUSIONS: Findings suggest that metformin and bariatric surgery may improve HbA1c levels and that participation in the National Diabetes Prevention Program may reduce type 2 diabetes incidence. Efforts to increase the use of these interventions may have positive impacts on diabetes-related health outcomes.

Patient-Centered Approaches to Transitional Care Research and Implementation: Overview and Insights From Patient-Centered Outcomes Research Institute's Transitional Care Portfolio.

BACKGROUND: This Special Issue, Future Directions in Transitional Care Research, focuses on the approaches used and lessons learned by researchers conducting care transitions studies funded by the Patient-Centered Outcomes Research Institute (PCORI). PCORI's approach to transitional care research augments prior research by encouraging researchers to focus on head-to-head comparisons of interventions, the use of patient-centered outcomes, and the engagement of stakeholders throughout the research process. OBJECTIVES: This paper introduces the themes and topics addressed by the articles that follow, which are focused on opportunities and challenges involved in conducting patient-centered clinical comparative effectiveness research in transitional care. It provides an overview of the state of the care transitions field, a description of PCORI's programmatic objectives, highlights of the patient and stakeholder engagement activities that have taken place during the course of these studies, and a brief overview of PCORI's Transitional Care Evidence to Action Network, a learning community designed to foster collaboration between investigators and their research teams and enhance the collective impact of this body of work. CONCLUSIONS: The papers in this Special Issue articulate challenges, lessons learned, and new directions for measurement, stakeholder engagement, implementation, and methodological and design approaches that reflect the complexity of transitional care comparative effectiveness research and seek to move the field toward a more holistic understanding of transitional care that integrates social needs and lifespan development into our approaches to improving care transitions.

Development and psychometric properties of surveys to assess provider perspectives on the barriers and facilitators of effective care transitions.

BACKGROUND: The quality of the discharge process and effective care transitions between settings of care are critical to minimize gaps in patient care and reduce hospital readmissions. Few studies have explored which care transition components and strategies are most valuable to patients and providers. This study describes the development, pilot testing, and psychometric analysis of surveys designed to gain providers' perspectives on current practices in delivering transitional care services. METHODS: We underwent a comprehensive process to develop items measuring unique aspects of care transitions from the perspectives of the three types of providers (downstream, ambulatory, and hospital providers). The process involved 1) an environmental scan, 2) provider interviews, 3) survey cognitive testing, 4) pilot testing, 5) a Stakeholder Advisory Group, 6) a Scientific Advisory Council, and 7) a collaborative Project ACHIEVE (Achieving Patient-Centered Care and Optimized Health in Care Transitions by Evaluating the Value of Evidence) research team. Three surveys were developed and fielded to providers affiliated with 43 hospitals participating in Project ACHIEVE. Web-based survey administration resulted in 948 provider respondents. We assessed response variability and response missingness. To evaluate the composites' psychometric properties, we examined intercorrelations of survey items, item factor loadings, model fit indices, internal consistency reliability, and intercorrelations between the composite measures and overall rating items. RESULTS: Results from psychometric analyses of the three surveys provided support for five composite measures: 1) Effort in Coordinating Patient Care, 2) Quality of Patient Information Received, 3) Organizational Support for Transitional Care, 4) Access to Community Resources, and 5) Strength of Relationships Among Community Providers. All factor loadings and reliability estimates were acceptable (loadings ≥ 0.40, α ≥ 0.70), and the fit indices showed a good model fit. All composite measures positively and significantly correlated with the overall ratings (0.13 ≤ r ≤ 0.71). CONCLUSIONS: We determined that the items and composite measures assessing the barriers and facilitators to care transitions within this survey are reliable and demonstrate satisfactory psychometric properties. The instruments may be useful to healthcare organizations and researchers to assess the quality of care transitions and target areas of improvement across different provider settings.

The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR): Unique 1.4 M patient Electronic Health Record cohort.

BACKGROUND: The Longitudinal Epidemiologic Assessment of Diabetes Risk (LEADR) study uses a novel Electronic Health Record (EHR) data approach as a tool to assess the epidemiology of known and new risk factors for type 2 diabetes mellitus (T2DM) and study how prevention interventions affect progression to and onset of T2DM. We created an electronic cohort of 1.4 million patients having had at least 4 encounters with a healthcare organization for at least 24-months; were aged ≥18 years in 2010; and had no diabetes (i.e., T1DM or T2DM) at cohort entry or in the 12 months following entry. EHR data came from patients at nine healthcare organizations across the U.S. between January 1, 2010-December 31, 2016. RESULTS: Approximately 5.9% of the LEADR cohort (82,922 patients) developed T2DM, providing opportunities to explore longitudinal clinical care, medication use, risk factor trajectories, and diagnoses for these patients, compared with patients similarly matched prior to disease onset. CONCLUSIONS: LEADR represents one of the largest EHR databases to have repurposed EHR data to examine patients' T2DM risk. This paper is first in a series demonstrating this novel approach to studying T2DM. IMPLICATIONS: Chronic conditions that often take years to develop can be studied efficiently using EHR data in a retrospective design. LEVEL OF EVIDENCE: While much is already known about T2DM risk, this EHR's cohort's 160 M data points for 1.4 M people over six years, provides opportunities to investigate new unique risk factors and evaluate research hypotheses where results could modify public health practice for preventing T2DM.

Using Learning Communities to Support Adoption of Health Care Innovations.

BACKGROUND: Diffusion of innovations can be a slow process, posing a major challenge to quality improvement in health care. Learning communities can provide a rich, collaborative environment that supports the adoption of health care innovations and motivates organizational change. From 2014-2016, the Agency for Healthcare Research and Quality (AHRQ) Health Care Innovations Exchange established and supported three learning communities focused on adopting innovations in three high-priority areas: (1) advancing the practice of patient- and family-centered care in hospitals, (2) promoting medication therapy management for at-risk populations, and (3) reducing non-urgent emergency services. METHODS: Members of each learning community worked collaboratively in facilitated settings to adapt and implement strategies featured in the Health Care Innovations Exchange, receiving technical assistance from content experts. Project staff conducted a mixed methods evaluation of the initiative, both formative and summative. RESULTS: The activities and outcomes of the three learning communities provided insights about how this approach can support local implementation efforts, and about factors influencing innovation adoption. Using a qualitative synthesis method, lessons were identified related to learning community startup (recruitment and goal setting), learning community operations (engagement, collaborative decision-making, and sustainability), and innovation implementation (changing care delivery processes and/or policies). CONCLUSIONS: Findings from this work indicate that the learning community model of group learning can serve as an effective method to support dissemination and implementation of innovations, and to achieve desired outcomes in local settings.

Novel Methods and Data Sources for Surveillance of State-Level Diabetes and Prediabetes Prevalence.

States bear substantial responsibility for addressing the rising rates of diabetes and prediabetes in the United States. However, accurate state-level estimates of diabetes and prediabetes prevalence that include undiagnosed cases have been impossible to produce with traditional sources of state-level data. Various new and nontraditional sources for estimating state-level prevalence are now available. These include surveys with expanded samples that can support state-level estimation in some states and administrative and clinical data from insurance claims and electronic health records. These sources pose methodologic challenges because they typically cover partial, sometimes nonrandom subpopulations; they do not always use the same measurements for all individuals; and they use different and limited sets of variables for case finding and adjustment. We present an approach for adjusting new and nontraditional data sources for diabetes surveillance that addresses these limitations, and we present the results of our proposed approach for 2 states (Alabama and California) as a proof of concept. The method reweights surveys and other data sources with population undercoverage to make them more representative of state populations, and it adjusts for nonrandom use of laboratory testing in clinically generated data sets. These enhanced diabetes and prediabetes prevalence estimates can be used to better understand the total burden of diabetes and prediabetes at the state level and to guide policies and programs designed to prevent and control these chronic diseases.

Preferential vastus medialis oblique activation achieved as a treatment for knee disorders.

The purpose of this study was to compare the effect of an open-stance cycling protocol (OSCP) with the traditional cycling foot position (TCFP) for preferential vastus medialis oblique (VMO) muscle activation, measured by surface electromyography (SEMG), and preferential VMO activation as defined by achieving significantly increased VMO/VL (vastus lateralis muscle) ratio values. Forty subjects of both sexes participated, 18 symptomatic with patellofemoral pain and 22 control subjects; ages ranged from 18 to 60 years (mean = 28.7 +/- 8 years). The OSCP and TCFP were ridden in randomized order while SEMG recordings were taken of the VMO and VL muscles, collecting the mean of peak amplitudes to calculate VMO/VL ratio values. The SEMG readings were taken 4 times per testing session with randomized resistance and a consistent cycling cadence of 85 rpm. The OSCP displayed preferential VMO activation for all subject groups (F = 40.47, p = 0.0001), and this study revealed a protocol that effectively treats patellofemoral pain.