Introductory Overview of the Natural Experiments for Translation in Diabetes 2.0 (NEXT-D2) Network: Examining the Impact of US Health Policies and Practices to Prevent Diabetes and Its Complications

Delivery of miR-15b-5p via magnetic nanoparticle-enhanced bone marrow mesenchymal stem cell-derived extracellular vesicles mitigates diabetic osteoporosis by targeting GFAP

Diabetic osteoporosis (DO) presents significant clinical challenges. This study aimed to investigate the potential of magnetic nanoparticle-enhanced extracellular vesicles (GMNPE-EVs) derived from bone marrow mesenchymal stem cells (BMSCs) to deliver miR-15b-5p, thereby targeting and downregulating glial fibrillary acidic protein (GFAP) expression in rat DO models. Data was sourced from DO-related RNA-seq datasets combined with GEO and GeneCards databases. Rat primary BMSCs, bone marrow-derived macrophages (BMMs), and osteoclasts were isolated and cultured. EVs were separated, and GMNPE targeting EVs were synthesized. Bioinformatic analysis revealed a high GFAP expression in DO-related RNA-seq and GSE26168 datasets for disease models. Experimental results confirmed elevated GFAP in rat DO bone tissues, promoting osteoclast differentiation. miR-15b-5p was identified as a GFAP inhibitor, but was significantly downregulated in DO and enriched in BMSC-derived EVs. In vitro experiments showed that GMNPE-EVs could transfer miR-15b-5p to osteoclasts, downregulating GFAP and inhibiting osteoclast differentiation. In vivo tests confirmed the therapeutic potential of this approach in alleviating rat DO. Collectively, GMNPE-EVs can effectively deliver miR-15b-5p to osteoclasts, downregulating GFAP expression, and hence, offering a therapeutic strategy for rat DO.

Trends and Race/Ethnic Disparities in Diabetes-Related Hospital Use in Medicaid Enrollees: Analyses of Serial Cross-sectional State Data, 2008-2017

BACKGROUND

Race/ethnic disparities in preventable diabetes-specific hospital care may exist among adults with diabetes who have Medicaid coverage.

OBJECTIVE

To examine race/ethnic disparities in utilization of preventable hospital care by adult Medicaid enrollees with diabetes across nine states over time.

DESIGN

Using serial cross-sectional state discharge records for emergency department (ED) visits and inpatient (IP) hospitalizations from the Healthcare Cost and Utilization Project, we quantified race/ethnicity-specific, state-year preventable diabetes-specific hospital utilization.

PARTICIPANTS

Non-Hispanic Black, non-Hispanic White, and Hispanic adult Medicaid enrollees aged 18-64 with a diabetes diagnosis (excluding gestational or secondary diabetes) who were discharged from hospital care in Arizona, Iowa, Kentucky, Florida, Maryland, New Jersey, New York, North Carolina, and Utah for the years 2008, 2011, 2014, and 2017.

MAIN MEASURES

Non-Hispanic Black-over-White and Hispanic-over-White rate ratios constructed using age- standardized state-year, race/ethnicity-specific ED, and IP diabetes-specific utilization rates.

KEY RESULTS

The ratio of Black-over-White ED utilization rates for preventable diabetes-specific hospital care increased across the 9 states in our sample from 1.4 (CI 95, 1.31-1.50) in 2008 to 1.73 (CI 95, 1.68-1.78) in 2017. The cross-year-state average non-Hispanic Black-over-White IP rate ratio was 1.46 (CI 95, 1.42-1.50), reflecting increases in some states and decreases in others. The across-state-year average Hispanic-over-White rate ratio for ED utilization was 0.67 (CI 95, 0.63-0.71). The across-state-year average Hispanic-over-White IP hospitalization rate ratio was 0.72 (CI 95, 0.69-0.75).

CONCLUSIONS

Hospital utilization by non-Hispanic Black Medicaid enrollees with diabetes was consistently greater and often increased relative to utilization by White enrollees within state programs between 2008 and 2017. Hispanic enrollee hospital utilization was either lower or indistinguishable relative to White enrollee hospital utilization in most states, but Hispanic utilization increased faster than White utilization in some states. Among broader patterns, there is heterogeneity in the magnitude of race/ethnic disparities in hospital utilization trends across states.

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.

Evaluating Natural Experiments that Impact the Diabetes Epidemic: an Introduction to the NEXT-D3 Network

PURPOSE OF REVIEW

Diabetes is an ongoing public health issue in the USA, and, despite progress, recent reports suggest acute and chronic diabetes complications are increasing.

RECENT FINDINGS

The Natural Experiments for Translation in Diabetes 3.0 (NEXT-D3) Network is a 5-year research collaboration involving six academic centers (Harvard University, Northwestern University, Oregon Health & Science University, Tulane University, University of California Los Angeles, and University of California San Francisco) and two funding agencies (Centers for Disease Control and Prevention and National Institutes of Health) to address the gaps leading to persisting diabetes burdens. The network builds on previously funded networks, expanding to include type 2 diabetes (T2D) prevention and an emphasis on health equity. NEXT-D3 researchers use rigorous natural experiment study designs to evaluate impacts of naturally occurring programs and policies, with a focus on diabetes-related outcomes. NEXT-D3 projects address whether and to what extent federal or state legislative policies and health plan innovations affect T2D risk and diabetes treatment and outcomes in the USA; real-world effects of increased access to health insurance under the Affordable Care Act; and the effectiveness of interventions that reduce barriers to medication access (e.g., decreased or eliminated cost sharing for cardiometabolic medications and new medications such as SGLT-2 inhibitors for Medicaid patients). Overarching goals include (1) expanding generalizable knowledge about policies and programs to manage or prevent T2D and educate decision-makers and organizations and (2) generating evidence to guide the development of health equity goals to reduce disparities in T2D-related risk factors, treatment, and complications.

Using Electronic Health Records in Longitudinal Studies: Estimating Patient Attrition

BACKGROUND

Electronic health records (EHRs) provide rich data on many domains not routinely available in other data, as such, they are a promising source to study changes in health outcomes using longitudinal study designs (eg, cohort studies, natural experiments, etc.). Yet, patient attrition rates in these data are unknown.

OBJECTIVE

The objective of this study was to estimate overall and among adults with diabetes or hypertension: (1) patient attrition over a 3-year period at community health centers; and (2) the likelihood that patients with Medicaid permanently switched their source of primary care.

RESEARCH DESIGN

A retrospective cohort study of 2012-2017 data from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Data Research Network of community health centers were used to assess EHR data attrition. Oregon Medicaid enrollment and claims data were used to estimate the likelihood of changing the source of primary care.

SUBJECTS

A total of 827,657 patients aged 19-64 with ≥1 ambulatory visit from 76 community health center systems across 20 states. In all, 232,891 Oregon Medicaid enrollees (aged 19-64) with a gap of ≥6 months following a claim for a visit billed to a primary care source.

MEASURES

Percentage of patients not returning within 3 years of their qualifying visit (attrition). The probability that a patient with Medicaid permanently changed their primary care source.

RESULTS

Attrition over the 3 years averaged 33.5%; attrition rates were lower (<25%) among patients with diabetes and/or hypertension. Among Medicaid enrollees, the percentage of provider change after a 6-month gap between visits was 12% for community health center patients compared with 39% for single-provider practice patients. Over 3 years, the likelihood of a patient changing to a new provider increased with length of time since their last visit but remained lowest among community health center patients.

CONCLUSION

This study demonstrates the use of the EHR dataset is a reliable source of data to support longitudinal studies while highlighting variability in attrition by primary care source and chronic conditions.

Network Engagement in Action: Stakeholder Engagement Activities to Enhance Patient-centeredness of Research

BACKGROUND

Stakeholders (ie, patients, policymakers, clinicians, advocacy groups, health system leaders, payers, and others) offer critical input at various stages in the research continuum, and their contributions are increasingly recognized as an important component of effective translational research. Natural experiments, in particular, may benefit from stakeholder feedback in addressing real-world issues and providing insight into future policy decisions, though best practices for the engagement of stakeholders in observational studies are limited in the literature.

METHODS

The Natural Experiments for Translation in Diabetes 2.0 (NEXT-D2) network utilizes rigorous methods to evaluate natural experiments in health policy and program delivery with a focus on diabetes-related outcomes. Each of the 8 partnering institutions incorporates stakeholder engagement throughout multiple study phases to enhance the patient-centeredness of results. NEXT-D2 dedicates a committee to Engagement for resource sharing, enhancing engagement approaches, and advancing network-wide engagement activities. Key stakeholder engagement activities include Study Meetings, Proposal Development, Trainings & Educational Opportunities, Data Analysis, and Results Dissemination. Network-wide patient-centered resources and multimedia have also been developed through the broad expertise of each site's stakeholder group.

CONCLUSIONS

This collaboration has created a continuous feedback loop wherein site-level engagement approaches are informed via the network and network-level engagement efforts are shaped by individual sites. Emerging best practices include: incorporating stakeholders in multiple ways throughout the research, building on previous relationships with stakeholders, enhancing capacity through stakeholder and investigator training, involving stakeholders in refining outcome choices and understanding the meaning of variables, and recognizing the power of stakeholders in maximizing dissemination.

"Not Alone Anymore": The Experiences of Adults With Diabetes in New York's Medicaid Health Home Program

BACKGROUND

New York State Medicaid's Health Home program is an example of a natural experiment that could affect individuals with diabetes. While evaluations of interventions such as the Health Home program are generally based solely on clinical and administrative data and rarely examine patients' experience, patients may add to the understanding of the intervention's implementation and mechanisms of impact.

OBJECTIVE

The objective of this study was to qualitatively examine the health and nonmedical challenges faced by Medicaid-insured patients with diabetes and their experiences with the services provided by New York's Health Homes to address these challenges.

RESEARCH DESIGN

We performed 10 focus groups and 23 individual interviews using a guide developed in collaboration with a stakeholder board. We performed a thematic analysis to identify cross-cutting themes.

SUBJECTS

A total of 63 Medicaid-insured individuals with diabetes, 31 of whom were enrolled in New York's Health Home program.

RESULTS

While participants were not generally familiar with the term "Health Home," they described and appreciated services consistent with Health Home enrollment delivered by care managers. Services addressed challenges in access to care, especially by facilitating and reminding participants about appointments, and nonmedical needs, such as transportation, housing, and help at home. Participants valued their personal relationships with care managers and the psychosocial support they provided.

CONCLUSIONS

From the perspective of its enrollees, the Health Home program primarily addressed access to care, but also addressed material and psychosocial needs. These findings have implications for Health Home entities and for research assessing their impact.

Evaluation of a National Care Coordination Program to Reduce Utilization Among High-cost, High-need Medicaid Beneficiaries With Diabetes

BACKGROUND

Medical, behavioral, and social determinants of health are each associated with high levels of emergency department (ED) visits and hospitalizations.

OBJECTIVE

The objective of this study was to evaluate a care coordination program designed to provide combined "whole-person care," integrating medical, behavioral, and social support for high-cost, high-need Medicaid beneficiaries by targeting access barriers and social determinants.

RESEARCH DESIGN

Individual-level interrupted time series with a comparator group, using person-month as the unit of analysis.

SUBJECTS

A total of 42,214 UnitedHealthcare Medicaid beneficiaries (194,834 person-months) age 21 years or above with diabetes, with Temporary Assistance to Needy Families, Medicaid expansion, Supplemental Security Income without Medicare, or dual Medicaid/Medicare.

MEASURES

Our outcome measures were any hospitalizations and any ED visits in a given month. Covariates of interest included an indicator for intervention versus comparator group and indicator and spline variables measuring changes in an outcome's time trend after program enrollment.

RESULTS

Overall, 6 of the 8 examined comparisons were not statistically significant. Among Supplemental Security Income beneficiaries, we observed a larger projected decrease in ED visit risk among the intervention sample versus the comparator sample at 12 months postenrollment (difference-in-difference: -6.6%; 95% confidence interval: -11.2%, -2.1%). Among expansion beneficiaries, we observed a greater decrease in hospitalization risk among the intervention sample versus the comparator sample at 12 months postenrollment (difference-in-difference: -5.8%; 95% confidence interval: -11.4%, -0.2%).

CONCLUSION

A care coordination program designed to reduce utilization among high-cost, high-need Medicaid beneficiaries was associated with fewer ED visits and hospitalizations for patients with diabetes in selected Medicaid programs but not others.

Trends in Costs of Care and Utilization for Medicaid Patients With Diabetes in Accountable Care Communities

BACKGROUND/OBJECTIVES

Medicaid beneficiaries with diabetes have complex care needs. The Accountable Care Communities (ACC) Program is a practice-level intervention implemented by UnitedHealthcare to improve care for Medicaid beneficiaries. We examined changes in costs and utilization for Medicaid beneficiaries with diabetes assigned to ACC versus usual care practices.

RESEARCH DESIGN

Interrupted time series with concurrent control group analysis, at the person-month level. The ACC was implemented in 14 states, and we selected comparison non-ACC practices from those states to control for state-level variation in Medicaid program. We adjusted the models for age, sex, race/ethnicity, comorbidities, seasonality, and state-by-year fixed effects. We examined the difference between ACC and non-ACC practices in changes in the time trends of expenditures and hospital and emergency room utilization, for the 4 largest categories of Medicaid eligibility [Temporary Assistance to Needy Families, Supplemental Security Income (without Medicare), Expansion, Dual-Eligible].

SUBJECTS/MEASURES

Eligibility and claims data from Medicaid adults with diabetes from 14 states between 2010 and 2016, before and after ACC implementation.

RESULTS

Analyses included 1,200,460 person-months from 66,450 Medicaid patients with diabetes. ACC implementation was not associated with significant changes in outcome time trends, relative to comparators, for all Medicaid categories.

CONCLUSIONS

Medicaid patients assigned to ACC practices had no changes in cost or utilization over 3 years of follow-up, compared with patients assigned to non-ACC practices. The ACC program may not reduce costs or utilization for Medicaid patients with diabetes.

Early Impact of the State Innovation Models Initiative on Diagnosed Diabetes Prevalence Among Adults and Hospitalizations Among Diagnosed Adults

BACKGROUND

The State Innovation Models (SIM) Initiative invested $254 million in 6 states in Round 1 to accelerate delivery system and payment reforms.

OBJECTIVE

The objective of this study was to examine the association of early SIM implementation and diagnosed diabetes prevalence among adults and hospitalization rates among diagnosed adults.

RESEARCH DESIGN

Quasi-experimental design compares diagnosed diabetes prevalence and hospitalization rates before SIM (2010-2013) and during early implementation (2014) in 6 SIM states versus 6 comparison states. County-level, difference-in-differences regression models were estimated.

SUBJECTS

The annual average of 4.5 million adults aged 20+ diagnosed with diabetes with 1.4 million hospitalizations in 583 counties across 12 states.

MEASURES

Diagnosed diabetes prevalence among adults and hospitalization rates per 1000 diagnosed adults.

RESULTS

Compared with the pre-SIM period, diagnosed diabetes prevalence increased in SIM counties by 0.65 percentage points (from 10.22% to 10.87%) versus only 0.10 percentage points (from 9.64% to 9.74%) in comparison counties, a difference-in-differences of 0.55 percentage points. The difference-in-differences regression estimates ranged from 0.49 to 0.53 percentage points (P<0.01). Regression results for ambulatory care-sensitive condition and all-cause hospitalization rates were inconsistent across models with difference-in-differences estimates ranging from -5.34 to -0.37 and from -13.16 to 0.92, respectively.

CONCLUSIONS

SIM Round 1 was associated with higher diagnosed diabetes prevalence among adults after a year of implementation, likely because of SIM's emphasis on detection and care management. SIM was not associated with lower hospitalization rates among adults diagnosed with diabetes, but the SIM's long-term impact on hospitalizations should be assessed.

Premature death and risk of cardiovascular disease in young-onset diabetes: a 23-year follow-up of the Da Qing Diabetes Study

OBJECTIVE

This study aimed to investigate premature mortality and the risk of cardiovascular disease (CVD) in Chinese adults with diabetes diagnosed before the age of 45 years.

METHODS

A total of 519 participants with normal glucose tolerance (NGT) and 630 with newly diagnosed diabetes mellitus (DM) were recruited in 1986 in the Da Qing Diabetes Study. In 2009, the participants were followed up to assess mortality and CVD events. The subjects were stratified into four subgroups according to age and diabetes status: age <45 years with NGT (NGT_<45y), age <45 years with DM (DM_<45y), age ≥45 years with NGT (NGT_≥45y), and age ≥45 years with DM (DM_≥45y). The risk of death and CVD events in patients with young-onset DM and elder subjects with NGT were compared to show the extent of premature death and CVD in the DM participants.

RESULTS

During the 23-year follow-up, 26 (10.40%) participants in NGT_<45y, 72 (34.12%) in DM_<45y, 74 (30.58%) in NGT_≥45y, and 266 (68.73%) in DM_≥45y died, including 13 (5.20%), 36 (17.06%), 24 (9.92%), and 128 (33.07%) death attributed to CVD. The corresponding rates of CVD events were 56 (22.40%), 90 (42.65%), 89 (36.78), and 213 (55.04%). It also showed that the risk of all-cause death (HR 1.23, 95% CI 0.88-1.71) or CVD events (HR 1.25, 95% CI 0.93-1.69) did not differ significantly between the DM_<45y and NGT_≥45y groups after adjusting for sex, smoking, body mass index, systolic blood pressure, total cholesterol and previous history of CVD. Of note, participants in the DM_<45y group had an higher risk of CVD mortality compared with that in the NGT_≥45y group (HR 1.76, 95% CI 1.04-2.98), although the mean age in the former group was 12 years lesser than that in the latter group (39.01 ± 5.00 vs 51.45 ± 5.14).

CONCLUSIONS

Young-onset diabetes is a risk factor for the premature death and cardiovascular disease. Early prevention and intensive treatment are warrented in patients with young-onset diabetes.