Multilevel Variation in Diabetes Screening Within an Integrated Health System

Using the Translating Research into Practice framework to develop a diabetes prevention intervention in primary care: a mixed-methods study

BACKGROUND

Pre-diabetes affects one-third of US adults and increases the risk of type 2 diabetes. Effective evidence-based interventions, such as the Diabetes Prevention Program, are available, but a gap remains in effectively translating and increasing uptake of these interventions into routine care.

METHODS

We applied the Translating Research into Practice (TRiP) framework to guide three phases of intervention design and development for diabetes prevention: (1) summarise the evidence, (2) identify local barriers to implementation and (3) measure performance. In phase 1, we conducted a retrospective cohort analysis of linked electronic health record claims data to evaluate current practices in the management of pre-diabetes. In phase 2, we conducted in-depth interviews of 16 primary care physicians, 7 payor leaders and 31 patients to elicit common barriers and facilitators for diabetes prevention. In phase 3, using findings from phases 1 and 2, we developed the core elements of the intervention and performance measures to evaluate intervention uptake.

RESULTS

In phase 1 (retrospective cohort analysis), we found few patients with pre-diabetes received diabetes prevention interventions. In phase 2 (stakeholder engagement), we identified common barriers to include a lack of knowledge about pre-diabetes among patients and about the Diabetes Prevention Program among clinicians. In phase 3 (intervention development), we developed the START Diabetes Prevention Clinical Pathway as a systematic change package to address barriers and facilitators identified in phases 1 and 2, performance measures and a toolkit of resources to support the intervention components.

CONCLUSIONS

The TRiP framework supported the identification of evidence-based care practices for pre-diabetes and the development of a well-fitted, actionable intervention and implementation plan designed to increase treatment uptake for pre-diabetes in primary care settings. Our change package can be adapted and used by other health systems or clinics to target prevention of diabetes or other related chronic conditions.

Improving Diabetes Screening in the Primary Care Clinic

BACKGROUND

In our suburban primary care clinic, the average rate of screening for diabetes among eligible patients was only 51%, similar to national screening data. We conducted a quality improvement project to increase this rate.

METHODS

During the 6-month preintervention phase, we collected baseline data on the percentage of eligible patients screened per week (percentage of patients with hemoglobin A1c checked in the prior 3 years out of patients eligible for screening who completed a visit during the week). We then implemented a two-phase intervention. In phase 1 (approximately 8 months), we generated an electronic health record (EHR) report to identify eligible patients and pended laboratory orders for physicians to sign. In phase 2 (approximately 3 months), we replaced the phase 1 intervention with an EHR clinical decision support tool that automatically identifies eligible patients. We compared screening rates in the preintervention vs. intervention period. For phase 1, we also assessed laboratory completion rates and the laboratory results. We surveyed physicians regarding intervention acceptability and satisfaction at 3, 6, 9, and 12 months during the intervention period.

RESULTS

The weekly percentage of patients screened increased from an average of 51% in the preintervention phase to 65% in the intervention phase (p < 0.001). During phase 1, most patients underwent laboratory blood testing as recommended (83% within 3 months), and results were consistent with prediabetes in 23% and with diabetes in 4%. Overall, most physicians believed that the intervention appropriately identified patients due for screening and was helpful (100% of respondents agreed at 9 months vs. 71% at 3 months).

CONCLUSION

We successfully implemented a systematic screening intervention involving a manual workflow and EHR tool and improved diabetes screening rates in our clinic.

Screening for Prediabetes and Diabetes in a National Network of Federally Qualified Health Centers: An Observational Study

BACKGROUND

In 2021, the U.S. Preventive Services Task Force (USPSTF) recommended screening for prediabetes and diabetes among adults aged 35-70 years with overweight or obesity. Studying dysglycemia screening in federally qualified health centers (FQHCs) that serve vulnerable patient populations is needed to understand health equity implications of this recommendation.

OBJECTIVE

To investigate screening practices among FQHC patients who would be eligible according to the 2021 USPSTF recommendation.

DESIGN

Retrospective cohort study analyzing electronic health records from a national network of 282 FQHC sites.

PARTICIPANTS

We included 183,329 patients without prior evidence of prediabetes or diabetes, who had ≥ 1 office visit from 2018-2020.

MAIN MEASURES

Screening eligibility was based on age and measured body mass index (BMI). The primary outcome, screening completion, was ascertained using hemoglobin A1c or fasting plasma glucose results from 2018-2020.

KEY RESULTS

Among 89,543 patients who would be eligible according to the 2021 USPSTF recommendation, 53,263 (59.5%) were screened. Those who completed screening had higher BMI values than patients who did not (33.0 ± 6.7 kg/m2 vs. 31.9 ± 6.2 kg/m2, p < 0.001). Adults aged 50-64 years had greater odds of screening completion relative to younger patients (OR 1.13, 95% CI: 1.10-1.17). Patients from racial and ethnic minority groups, as well as those without health insurance, were more likely to complete screening than White patients and insured patients, respectively. Clinical risk factors for diabetes were also associated with dysglycemia screening. Among patients who completed screening, 23,588 (44.3%) had values consistent with prediabetes or diabetes.

CONCLUSIONS

Over half of FQHC patients who would be eligible according to the 2021 USPSTF recommendation were screened. Screening completion was higher among middle-aged patients, those with greater BMI values, as well as vulnerable groups with a high risk of developing diabetes. Future research should examine adoption of the 2021 USPSTF screening recommendation and its impact on health equity.

Use of Real-World Data in Population Science to Improve the Prevention and Care of Diabetes-Related Outcomes

The past decade of population research for diabetes has seen a dramatic proliferation of the use of real-world data (RWD) and real-world evidence (RWE) generation from non-research settings, including both health and non-health sources, to influence decisions related to optimal diabetes care. A common attribute of these new data is that they were not collected for research purposes yet have the potential to enrich the information around the characteristics of individuals, risk factors, interventions, and health effects. This has expanded the role of subdisciplines like comparative effectiveness research and precision medicine, new quasi-experimental study designs, new research platforms like distributed data networks, and new analytic approaches for clinical prediction of prognosis or treatment response. The result of these developments is a greater potential to progress diabetes treatment and prevention through the increasing range of populations, interventions, outcomes, and settings that can be efficiently examined. However, this proliferation also carries an increased threat of bias and misleading findings. The level of evidence that may be derived from RWD is ultimately a function of the data quality and the rigorous application of study design and analysis. This report reviews the current landscape and applications of RWD in clinical effectiveness and population health research for diabetes and summarizes opportunities and best practices in the conduct, reporting, and dissemination of RWD to optimize its value and limit its drawbacks.

Assessment of variation in long-term outcomes of integrated care initiatives in Dutch health care

Introduction

The care for many patients with diabetes mellitus type 2 in the Netherlands, is contracted by a local care group. The healthcare providers, who collectively shape a care group, provide protocolled diabetes care. Differences exist between care groups in terms of their organizational and financial arrangements. These differences may result in variation in outcomes. The aim of this study is to assess whether variation in healthcare costs, diabetes complications and related hospital admissions on the level of care groups exist.

Methods

A quantitative cohort study was conducted. Patients who used diabetes medication (more than 180 days of defined daily doses per year) for the first time between the years 2014 and 2019 were included. Data were extracted from health insurance claims between 2014 and 2019. Generalized linear mixed models were used to analyse patient variation in healthcare costs (two and six years follow-up), diabetes-related complications and hospital admission days. Intraclass correlation coefficients were calculated to estimate the amount of variation that was attributable to the care groups.

Results

A large variation in outcome variables was observed between patients and a small variation between care groups. The intraclass correlation coefficient for long-term costs was 0.4%; for short-term costs between 0.1% and 0.3%; for complications 1% and for hospital days 4%.

Discussion

A large variation between patients with diabetes mellitus type 2 exists in terms of their healthcare costs and complications. In our study, care groups accounted minimally for this variation. A generalized linear mixed model in combination with year cohorts is a tool to study variations in the long-term outcomes of integrated care initiatives.

Alternative type 2 diabetes screening tests may reduce the number of U.S. adults with undiagnosed diabetes

AIM

To evaluate the U.S. population-level impact of two alternatives for initial type 2 diabetes screening [opportunistic random plasma glucose (RPG) > 6.7 mmol/l and a 1-h 50-g glucose challenge test (GCT) > 8.9 mmol/l] compared with American Diabetes Association (ADA)-recommended tests.

METHODS

Using a sample (n = 1471) from the National Health and Nutrition Examination Survey (NHANES) 2013-2014 that represented 145 million U.S. adults at high risk for developing type 2 diabetes, we simulated a two-test screening process. We compared ADA-recommended screening tests [fasting plasma glucose (FPG), 2-h 75-g oral glucose tolerance test (OGTT), HbA1c ] vs. initial screening with opportunistic RPG or GCT (followed by FPG, OGTT or HbA1c ). After simulation, participants were entered into an individual-level Monte Carlo-based Markov lifetime outcomes model. Primary outcomes were representative number of U.S. adults correctly identified with type 2 diabetes, societal lifetime costs and quality-adjusted life years (QALYs).

RESULTS

In NHANES 2013-2014, 100 individuals had undiagnosed diabetes [weighted estimate: 8.4 million, standard error (se): 1.1 million]. Among ADA-recommended screening tests, FPG followed by OGTT (FPG-OGTT) was most sensitive, identifying 35 individuals with undiagnosed diabetes (weighted estimate: 3.2 million, se: 0.9 million). Four alternative screening strategies performed superior to FPG-OGTT, with RPG followed by OGTT being the most sensitive overall, identifying 72 individuals with undiagnosed diabetes (weighted estimate: 6.1 million, se: 1.0 million). There was no increase in average lifetime costs and comparable QALYs.

CONCLUSIONS

Initial screening using opportunistic RPG or a GCT may identify more U.S. adults with type 2 diabetes without increasing societal costs.