Food Insecurity and Hypoglycemia among Older Patients with Type 2 Diabetes Treated with Insulin or Sulfonylureas: The Diabetes & Aging Study

BACKGROUND

Severe hypoglycemia is a serious adverse drug event associated with hypoglycemia-prone medications; older patients with diabetes are particularly at high risk. Economic food insecurity (food insecurity due to financial limitations) is a known risk factor for hypoglycemia; however, less is known about physical food insecurity (due to difficulty cooking or shopping for food), which may increase with age, and its association with hypoglycemia.

OBJECTIVE

Study associations between food insecurity and severe hypoglycemia.

DESIGN

Survey based cross-sectional study.

PARTICIPANTS

Survey responses were collected in 2019 from 1,164 older (≥ 65 years) patients with type 2 diabetes treated with insulin or sulfonylureas.

MAIN MEASURES

Risk ratios (RR) for economic and physical food insecurity associated with self-reported severe hypoglycemia (low blood glucose requiring assistance) adjusted for age, financial strain, HbA1c, Charlson comorbidity score and frailty. Self-reported reasons for hypoglycemia endorsed by respondents.

KEY RESULTS

Food insecurity was reported by 12.3% of the respondents; of whom 38.4% reported economic food insecurity only, 21.1% physical food insecurity only and 40.5% both. Economic food insecurity and physical food insecurity were strongly associated with severe hypoglycemia (RR = 4.3; p = 0.02 and RR = 4.4; p = 0.002, respectively). Missed meals ("skipped meals, not eating enough or waiting too long to eat") was the dominant reason (77.5%) given for hypoglycemia.

CONCLUSIONS

Hypoglycemia prevention efforts among older patients with diabetes using hypoglycemia-prone medications should address food insecurity. Standard food insecurity questions, which are used to identify economic food insecurity, will fail to identify patients who have physical food insecurity only.

Associations of U.S. hospital closure (2007-2018) with area socioeconomic disadvantage and racial/ethnic composition

PURPOSE

To examine whether hospital closure is associated with high levels of area socioeconomic disadvantage and racial/ethnic minority composition.

METHODS

Pooled cross-sectional analysis (2007-2018) of 6467 U.S. hospitals from the American Hospital Association's Annual Survey, comparing hospital population characteristics of closed hospitals to all remaining open hospitals. We used multilevel mixed-effects logistic regression models to assess closure as a function of population characteristics, including area deprivation index ([ADI], a composite measure of socioeconomic disadvantage), racial/ethnic composition, and rural classification, nesting hospitals within hospital service areas (HSAs) and hospital referral regions. Secondary analyses examined public or private hospital type.

RESULTS

Overall, 326 (5.0%) of 6467 U.S. hospitals closed during the study period. In multivariable models, hospitals in HSAs with a higher burden of socioeconomic disadvantage (per 10% above median ADI ZIP codes, AOR 1.05; 95% CI, 1.01-1.09) and Black Non-Hispanic composition (highest quartile, AOR 4.03; 95% CI, 2.62-6.21) had higher odds of closure. We did not observe disparities in closure by Hispanic/Latino composition or rurality. Disparities persisted for Black Non-Hispanic communities, even among HSAs with the lowest burden of disadvantage.

CONCLUSIONS

Disproportionate hospital closure in communities with higher socioeconomic disadvantage and Black racial composition raises concerns about unequal loss of healthcare resources in the U.S.

Individualizing Care for Older Adults With Diabetes Amid the Revolution in Pharmacotherapy

This JAMA Network Insights reassesses the approach to caring for older adults with diabetes in the context of newly available pharmacologic agents.

Moderation of associations between weight discrimination and diabetes status by psychosocial factors

Weight discrimination has adverse effects on health that include increasing the risk factors for developing type 2 diabetes. Preliminary evidence suggests a positive association between weight discrimination and diagnosed diabetes; however, it is unknown whether psychosocial resources may buffer this association. In logistic regressions stratified by gender, we examined links between weight discrimination and diabetes among a nationally representative sample of U.S. adults (the National Social Life, Health, and Aging Project; N = 2,794 adults age 50 and older in 2015-16). We also tested the extent to which trait-resilience and social support from a spouse/partner, family, and friends buffered any observed association. We adjusted for known predictors of diabetes (age, race/ethnicity, Body Mass Index) and conducted sensitivity analyses restricted to men and women with obesity. Net of covariates, in the overall sample, weight discrimination was associated with significantly greater odds of having ever had diabetes among women (OR = 2.00, 95% CI [1.15, 3.47]), but not men. Among women with obesity, weight discrimination was only significantly associated with greater odds of diabetes for those with low resilience (OR = 1.84, 95% CI [1.01, 3.35]). Among men overall, weight discrimination was associated with lower odds of diabetes for those with high family support (OR = 0.03, 95% CI [0.003, 0.25]) as well as those with high friend support (OR = 0.34, 95% CI [0.13, 0.91]); similar effects were observed in men with obesity. These novel findings evince a role for psychosocial resources in buffering associations between weight discrimination and diabetes.

Willingness to take less medication for type 2 diabetes among older patients: The Diabetes & Aging Study

BACKGROUND

To examine the willingness of older patients to take less diabetes medication (de-intensify) and to identify characteristics associated with willingness to de-intensify treatment.

METHODS

Survey conducted in 2019 in an age-stratified, random sample of older (65-100 years) adults with diabetes on glucose-lowering medications in the Kaiser Permanente Northern California Diabetes Registry. We classified survey responses to the question: "I would be willing to take less medication for my diabetes" as willing, neutral, or unwilling to de-intensify. Willingness to de-intensify treatment was examined by several clinical characteristics, including American Diabetes Association (ADA) health status categories used for individualizing glycemic targets. Analyses were weighted to account for over-sampling of older individuals.

RESULTS

A total of 1337 older adults on glucose-lowering medication(s) were included (age 74.2 ± 6.0 years, 44% female, 54.4% non-Hispanic white). The proportions of participants willing, neutral, or unwilling to take less medication were 51.2%, 27.3%, and 21.5%, respectively. Proportions of willing to take less medication varied by age (65-74 years: 54.2% vs. 85+ years: 38.5%) and duration of diabetes (0-4 years: 61.0% vs. 15+ years: 44.2%), both p < 0.001. Patients on 1-2 medications were more willing to take less medication(s) compared with patients on 10+ medications (62.1% vs. 46.6%, p = 0.03). Similar proportions of willingness to take less medications were seen across ADA health status, and HbA1c. Willingness to take less medication(s) was similar across survey responses to questions about patient-clinician relationships.

CONCLUSIONS

Clinical guidelines suggest considering treatment de-intensification in older patients with longer duration of diabetes, yet patients with these characteristics are less likely to be willing to take less medication(s).

Impact of 2009 American Recovery and Reinvestment Act (ARRA) health center investments on disadvantaged neighborhoods after recession

BACKGROUND

Federally qualified health centers (FQHCs) are integral to the U.S. healthcare safety net and uniquely situated in disadvantaged neighborhoods. The 2009 American Recovery and Reinvestment Act (ARRA) invested $2 billion in FQHC stimulus during the Great Recession; but it remains unknown whether this investment was associated with extended benefits for disadvantaged neighborhoods.

METHODS

We used a propensity-score matched longitudinal design (2008-2012) to examine whether the 2009 ARRA FQHC investment was associated with local jobs and establishments recovery in FQHC neighborhoods. Job change data were obtained from the Longitudinal Employer-Household Dynamics (LEHD) survey and calculated as an annual rate per 1,000 population. Establishment change data were obtained from the National Neighborhood Data Archive (NaNDA) and calculated as an annual rate per 10,000 population. Establishment data included 4 establishment types: healthcare services, eating/drinking places, retail establishments, and grocery stores. Fixed effects were used to compare annual rates of jobs and establishments recovery between ARRA-funded FQHC census tracts and a matched control group.

RESULTS

Of 50,381 tracts, 2,223 contained ≥ 1 FQHC that received ARRA funding. A higher proportion of FQHC tracts had an extreme poverty designation (11.6% vs. 5.4%), high unemployment rate (45.4% vs. 30.3%), and > 50% minority racial/ethnic composition (48.1% vs. 36.3%). On average, jobs grew at an annual rate of 3.84 jobs per 1,000 population (95% CI: 3.62,4.06). In propensity-score weighted models, jobs in ARRA-funded tracts grew at a higher annual rate of 4.34 per 1,000 (95% CI: 2.56,6.12) relative to those with similar social vulnerability. We observed persistent decline in non-healthcare establishments (-1.35 per 10,000; 95% CI: -1.68,-1.02); but did not observe decline in healthcare establishments.

CONCLUSIONS

Direct funding to HCs may be an effective strategy to support healthcare establishments and some jobs recovery in disadvantaged neighborhoods during recession, reinforcing the important multidimensional roles HCs play in these communities. However, HCs may benefit from additional investments that target upstream determinants of health to mitigate uneven recovery and neighborhood decline.

Costs and Health Care Utilization Analysis of Medical Group Visits for Adults With Type 2 Diabetes in Community Health Centers

OBJECTIVE

We evaluated the economic impact of group visits (GVs) in adults with uncontrolled diabetes in community health centers (CHCs) in the United States.

RESEARCH DESIGN AND METHODS

In this prospective controlled trial, we implemented 6 monthly GV sessions in 5 CHCs and compared intervention patients (n=49) to control patients (n=72) receiving usual care within the same CHCs. We conducted patient chart reviews to obtain health care utilization data for the prior 6 months at baseline, 6 months (during the GV implementation), and 12 months (after the implementation). We also collected monthly logs of CHC expenses and staff time spent on activities related to GVs. Per-patient total costs included CHCs' expenses and costs associated with staff time and patients' health care use. For group comparison, we used the Wilcoxon rank-sum test and the bootstrapping method that was to bootstrap generalized estimating equation models.

RESULTS

The GV group had fewer 6-month hospitalizations (mean: GV: 0.06 vs. control: 0.24, rate: 6.1% vs. 19.4%) ( P ≤ 0.04) and similar emergency department visits at 12 months than the control group. Implementing GV incurred $1770 per-patient. The intervention cost $1597 more than the control at 6 months ($3021 vs. $1424) but saved $1855 at 12 months ($857 vs. $2712) ( P =0.002).

CONCLUSIONS

The diabetes GV care model reduced hospitalizations and had cost savings at 12 months, while it improved patients' diabetes-related quality of life and glucose control. Future studies should assess its lifetime cost-effectiveness through a randomized controlled trial.

Glycemic control and diabetes complications across health status categories in older adults treated with insulin or insulin secretagogues: The Diabetes & Aging Study

BACKGROUND

For older adults with type 2 diabetes (T2D) treated with insulin or sulfonylureas, Endocrine Society guideline recommends HbA1c between 7% to <7.5% for those in good health, 7.5% to <8% for those in intermediate health, and 8% to <8.5% for those in poor health. Our aim was to examine associations between attained HbA1c below, within (reference), or above recommended target range and risk of complication or mortality.

METHODS

Retrospective cohort study of adults ≥65 years old with T2D treated with insulin or sulfonylureas from an integrated healthcare delivery system. Cox proportional hazards models of complications during 2019 were adjusted for sociodemographic and clinical variables. Primary outcome was a combined outcome of any microvascular or macrovascular event, severe hypoglycemia, or mortality during 12-month follow-up.

RESULTS

Among 63,429 patients (mean age: 74.2 years, 46.8% women), 8773 (13.8%) experienced a complication. Complication risk was significantly elevated for patients in good health (n = 16,895) whose HbA1c was above (HR 1.97, 95% CI 1.62-2.41) or below (HR 1.29, 95% CI 1.02-1.63) compared to within recommended range. Among those in intermediate health (n = 30,129), complication risk was increased for those whose HbA1c was above (HR 1.45, 95% CI 1.30-1.60) but not those below the recommended range (HR 0.99, 95% CI 0.89-1.09). Among those in poor health (n = 16,405), complication risk was not significantly different for those whose HbA1c was below (HR 0.98, 95% CI 0.89-1.09) or above (HR 0.96, 95% CI 0.88-1.06) recommended range.

CONCLUSIONS

For older adults with T2D in good health, HbA1c below or above the recommended range was associated with significantly elevated complication risk. However, for those in poor health, achieving specific HbA1c levels may not be helpful in reducing the risk of complications.

Diabetes Life Expectancy Prediction Model Inputs and Results From Patient Surveys Compared With Electronic Health Record Abstraction: Survey Study

Background

Prediction models are being increasingly used in clinical practice, with some requiring patient-reported outcomes (PROs). The optimal approach to collecting the needed inputs is unknown.

Objective

Our objective was to compare mortality prediction model inputs and scores based on electronic health record (EHR) abstraction versus patient survey.

Methods

Older patients aged ≥65 years with type 2 diabetes at an urban primary care practice in Chicago were recruited to participate in a care management trial. All participants completed a survey via an electronic portal that included items on the presence of comorbid conditions and functional status, which are needed to complete a mortality prediction model. We compared the individual data inputs and the overall model performance based on the data gathered from the survey compared to the chart review.

Results

For individual data inputs, we found the largest differences in questions regarding functional status such as pushing/pulling, where 41.4% (31/75) of participants reported difficulties that were not captured in the chart with smaller differences for comorbid conditions. For the overall mortality score, we saw nonsignificant differences (P=.82) when comparing survey and chart-abstracted data. When allocating participants to life expectancy subgroups (<5 years, 5-10 years, >10 years), differences in survey and chart review data resulted in 20% having different subgroup assignments and, therefore, discordant glucose control recommendations.

Conclusions

In this small exploratory study, we found that, despite differences in data inputs regarding functional status, the overall performance of a mortality prediction model was similar when using survey and chart-abstracted data. Larger studies comparing patient survey and chart data are needed to assess whether these findings are reproduceable and clinically important.

CommunityRx, a social care assistance intervention for family and friend caregivers delivered at the point of care: two concurrent blinded randomized controlled trials

BACKGROUND

CommunityRx is an evidence-based social care intervention delivered to family and friend caregivers ("caregivers") at the point of healthcare to address health-related social risks (HRSRs). Two CommunityRx randomized controlled trials (RCTs) are being fielded concurrently on Chicago's South Side, a predominantly African American/Black community. CommunityRx-Hunger is a double-blind RCT enrolling caregivers of hospitalized children. CommunityRx-Dementia is a single-blind RCT enrolling caregivers of community-residing people with dementia. RCTs with caregivers face recruitment barriers, including caregiver burden and lack of systematic strategies to identify caregivers in clinical settings. COVID-19 pandemic-related visitor restrictions exacerbated these barriers and prompted the need for iteration of the protocols from in-person to remote operations. This study describes these protocols and methods used for successful iteration to overcome barriers.

METHODS AND FINDINGS

CommunityRx uses individual-level data to generate personalized, local community resource referrals for basic, health and caregiving needs. In early 2020, two in-person RCT protocols were pre-tested. In March 2020, when pandemic conditions prohibited face-to-face clinical enrollment, both protocols were iterated to efficient, caregiver-centered remote operations. Iterations were enabled in part by the Automated Randomized Controlled Trial Information-Communication System (ARCTICS), a trial management system innovation engineered to integrate the data collection database (REDCap) with community resource referral (NowPow) and SMS texting (Mosio) platforms. Enabled by engaged Community Advisory Boards and ARCTICS, both RCTs quickly adapted to remote operations. To accommodate these adaptations, launch was delayed until November (CommunityRx-Hunger) and December (CommunityRx-Dementia) 2020. Despite the delay, 65% of all planned participants (CommunityRx-Hunger n = 417/640; CommunityRx-Dementia n = 222/344) were enrolled by December 2021, halfway through our projected enrollment timeline. Both trials enrolled 13% more participants in the first 12 months than originally projected for in-person enrollment.

DISCUSSION

Our asset-based, community-engaged approach combined with widely accessible institutional and commercial information technologies facilitated rapid migration of in-person trials to remote operations. Remote or hybrid RCT designs for social care interventions may be a viable, scalable alternative to in-person recruitment and intervention delivery protocols, particularly for caregivers and other groups that are under-represented in traditional health services research.

TRIAL REGISTRATION

ClinicalTrials.gov: CommunityRx-Hunger (NCT04171999, 11/21/2019); CommunityRx for Caregivers (NCT04146545, 10/31/2019).

Severe hypoglycemia and falls in older adults with diabetes: The Diabetes & Aging Study

Objective

To estimate rates of severe hypoglycemia and falls among older adults with diabetes and evaluate their association.

Research Design and Methods

Survey in an age-stratified, random sample adults with diabetes age 65-100 years; respondents were asked about severe hypoglycemia (requiring assistance) and falls in the past 12 months. Prevalence ratios (adjusted for age, sex, race/ethnicity) estimated the increased risk of falls associated with severe hypoglycemia.

Results

Among 2,158 survey respondents, 79 (3.7%) reported severe hypoglycemia, of whom 68 (86.1%) had no ED visit or hospitalization for hypoglycemia. Falls were reported by 847 (39.2%), of whom 745 (88.0%) had no fall documented in outpatient or inpatient records. Severe hypoglycemia was associated with a 70% greater prevalence of falls (adjusted prevalence ratio = 1.7 (95% CI, 1.3-2.2)).

Conclusion

While clinical documentation of events likely reflects severity or care-seeking behavior, severe hypoglycemia and falls are common, under-reported life-threatening events.

Development and Validation of the Life Expectancy Estimator for Older Adults with Diabetes (LEAD): the Diabetes and Aging Study

BACKGROUND

Estimated life expectancy for older patients with diabetes informs decisions about treatment goals, cancer screening, long-term and advanced care, and inclusion in clinical trials. Easily implementable, evidence-based, diabetes-specific approaches for identifying patients with limited life expectancy are needed.

OBJECTIVE

Develop and validate an electronic health record (EHR)-based tool to identify older adults with diabetes who have limited life expectancy.

DESIGN

Predictive modeling based on survival analysis using Cox-Gompertz models in a retrospective cohort.

PARTICIPANTS

Adults with diabetes aged ≥ 65 years from Kaiser Permanente Northern California: a 2015 cohort (N = 121,396) with follow-up through 12/31/2019, randomly split into training (N = 97,085) and test (N = 24,311) sets. Validation was conducted in the test set and two temporally distinct cohorts: a 2010 cohort (n = 89,563; 10-year follow-up through 2019) and a 2019 cohort (n = 152,357; 2-year follow-up through 2020).

MAIN MEASURES

Demographics, diagnoses, utilization and procedures, medications, behaviors and vital signs; mortality.

KEY RESULTS

In the training set (mean age 75 years; 49% women; 48% racial and ethnic minorities), 23% died during 5 years follow-up. A mortality prediction model was developed using 94 candidate variables, distilled into a life expectancy model with 11 input variables, and transformed into a risk-scoring tool, the Life Expectancy Estimator for Older Adults with Diabetes (LEAD). LEAD discriminated well in the test set (C-statistic = 0.78), 2010 cohort (C-statistic = 0.74), and 2019 cohort (C-statistic = 0.81); comparisons of observed and predicted survival curves indicated good calibration.

CONCLUSIONS

LEAD estimates life expectancy in older adults with diabetes based on only 11 patient characteristics widely available in most EHRs and claims data. LEAD is simple and has potential application for shared decision-making, clinical trial inclusion, and resource allocation.

Reply to: Comment on: Data-driven classification of health status of older adults with diabetes: The diabetes and aging study

This letter comments on the letter by Christiaens

The Growing Role of Technology in the Care of Older Adults With Diabetes

The integration of technologies such as continuous glucose monitors, insulin pumps, and smart pens into diabetes management has the potential to support the transformation of health care services that provide a higher quality of diabetes care, lower costs and administrative burdens, and greater empowerment for people with diabetes and their caregivers. Among people with diabetes, older adults are a distinct subpopulation in terms of their clinical heterogeneity, care priorities, and technology integration. The scientific evidence and clinical experience with these technologies among older adults are growing but are still modest. In this review, we describe the current knowledge regarding the impact of technology in older adults with diabetes, identify major barriers to the use of existing and emerging technologies, describe areas of care that could be optimized by technology, and identify areas for future research to fulfill the potential promise of evidence-based technology integrated into care for this important population.

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.

Expected Health Benefits of SGLT-2 Inhibitors and GLP-1 Receptor Agonists in Older Adults

Background. Older and sicker adults with type 2 diabetes (T2D) were underrepresented in randomized trials of glucagon-like peptide 1 receptor-agonist (GLP1RA) and sodium-glucose cotransporter 2 inhibitors (SGLT2I), and thus, health benefits are uncertain in this population. Objective. To assess the impact of age, health status, and life expectancy in older adults with T2D on health benefits of GLP1RA and SGLT2I. Design. We used the United Kingdom Prospective Diabetes Study (UKPDS) model to simulate lifetime health outcomes. We calibrated the UKPDS model to improve mortality prediction in older adults using a common geriatric prognostic index. Participants. National Health and Nutrition Examination Survey 2013-2018 participants 65 y and older with T2D, eligible for GLP1RA or SGLT2I according to American Diabetes Association guidelines. Interventions. GLP1RA or SGLT2I use versus no additional medication. Main Measures. Lifetime complications and weighted life-years (LYs) and quality-adjusted life-years (QALYs) across overall treatment arms and life expectancies. Key Results. The overall older adult population was predicted to experience significant health benefits from GLP1RA (+0.29 LY [95% confidence interval: 0.27, 0.31], +0.15 QALYs [0.14, 0.16]) and SGLT2I (+0.26 LY [0.24, 0.28], +0.13 QALYs [0.12, 0.14]) as compared with no added medication. However, expected benefits declined in subgroups with shorter life expectancies. Participants with <4 y of life expectancy had minimal gains of <0.05 LY and <0.03 QALYs from added medication. Accounting for injection-related disutility, GLP1RA use reduced QALYs (-0.03 QALYs [-0.04, -0.02]). Conclusions. While GLP1RA and SGLT2I have substantial health benefits for many older adults with type 2 diabetes, benefits are not clinically significant in patients with <4 y of life expectancy. Life expectancy and patient preferences are important considerations when prescribing newer diabetes medications.

Highlights

On average, older adults benefit significantly from SGLT2I and GLP1RA use. However, the benefits of these drugs are not clinically significant among older patients with life expectancy less than 4 y.There is potential harm in injectable GLP1RA use in the oldest categories of adults with type 2 diabetes.Heterogeneity in life expectancy and patient preferences for injectable versus oral medications are important to consider when prescribing newer diabetes medications.

Data-driven classification of health status of older adults with diabetes: The diabetes and aging study

BACKGROUND

We set out to identify empirically-derived health status classes of older adults with diabetes based on clusters of comorbid conditions which are associated with future complications.

METHODS

We conducted a cohort study among 105,786 older (≥65 years of age) adults with type 2 diabetes enrolled in an integrated healthcare delivery system. We used latent class analysis of 19 baseline comorbidities to derive health status classes and then compared incident complication rates (events per 100 person-years) by health status class during 5 years of follow-up. Complications included infections, hyperglycemic events, hypoglycemic events, microvascular events, cardiovascular events, and all-cause mortality.

RESULTS

Three health status classes were identified: Class 1 (58% of the cohort) had the lowest prevalence of most baseline comorbidities, Class 2 (22%) had the highest prevalence of obesity, arthritis, and depression, and Class 3 (20%) had the highest prevalence of cardiovascular conditions. The risk for incident complications was highest for Class 3, intermediate for Class 2 and lowest for Class 1. For example, the age, sex and race-adjusted rates for cardiovascular events (per 100 person-years) for Class 3, Class 2 and Class 1 were 6.5, 2.3, and 1.6, respectively; 2.1, 1.2, 0.7 for hypoglycemia; and 8.0, 3.8, and 2.3 for mortality.

CONCLUSIONS

Three health status classes of older adults with diabetes were identified based on prevalent comorbidities and were associated with marked differences in risk of complications. These health status classes can inform population health management and guide the individualization of diabetes care.

Two concurrent randomized controlled trials of CommunityRx, a social care intervention for family and friend caregivers delivered at the point of care

Background

CommunityRx is an evidence-based social care intervention delivered to family and friend caregivers ("caregivers") at the point of healthcare to address health-related social risks (HRSRs). CommunityRx-Hunger is a double-blind randomized controlled trial (RCT) that enrolls caregivers of hospitalized children. CommunityRx-Dementia is a single-blind RCT that enrolls caregivers of community-residing people with dementia. Clinical trials that enroll caregivers face recruitment barriers, including caregiver burden and lack of systematic strategies to identify and track caregivers. COVID-19 pandemic-related visitor restrictions exacerbated these barriers and prompted the need for iteration of the CommunityRx protocols from in-person to remote operations. This study describes the novel methods used to iterate existing RCT protocols and factors contributing to their successful iteration.

Methods

CommunityRx uses individual-level data to generate personalized community resource referrals for basic, health and caregiving needs. Our research program uses an asset-based, community-engaged approach including study-specific community advisory boards (CABs). In early 2020, both RCT protocols were pre-tested in-person. In March 2020, when pandemic conditions prohibited enrollment during clinical encounters, both protocols were iterated to efficient, caregiver-centered remote operations. Iterations were enabled in part by the Automated Randomized Controlled Trial Information-Communication System (ARCTICS), a trial management system innovation engineered to integrate the data collection database (REDCap) with community resource referral (NowPow) and SMS texting (Mosio) platforms.

Results

Enabled by engaged CABs and ARCTICS, both RCTs quickly adapted to remote operations. Designed before the pandemic, we had planned to launch both trials by March 2020 and complete enrollment by December 2021. The pandemic postponed launch until November (CommunityRx-Hunger) and December (CommunityRx-Dementia) 2020. Despite the delay, 65% of all planned participants (CommunityRx-Hunger n = 417/640; CommunityRx-Dementia n = 222/344) were enrolled by December 2021, halfway through our projected enrollment timeline. Both trials enrolled 13% more participants in 12 months than originally projected in-person.

Conclusions

Our asset-based, community-engaged approach combined with widely accessible institutional and commercial information technologies facilitated rapid migration to remote trial operations. Remote or hybrid RCT designs for social care interventions may be a viable, scalable alternative to in-person recruitment and intervention delivery protocols, particularly for caregivers and other groups that are under-represented in traditional health services research.

Trial Status

Both studies are registered on ClinicalTrials.gov: CommunityRx-Hunger (NCT04171999); CommunityRx for Caregivers (NCT04146545); My Diabetes My Community (NCT04970810).

Validation of a Hypoglycemia Risk Stratification Tool Using Data From Continuous Glucose Monitors

This cohort study uses data from continuous glucose monitoring to validate a hypoglycemia risk stratification tool.

Quality of Care for US Adults With Medicaid Insurance and Type 2 Diabetes in Federally Qualified Health Centers Compared With Other Primary Care Settings

OBJECTIVE

The objective of this study was to evaluate indicators of diabetes quality of care for US nonelderly, adult Medicaid enrollees with type 2 diabetes and compare federally qualified health centers (FQHCs) versus non-FQHCs.

RESEARCH DESIGN AND METHODS

We analyzed diabetes process measures and acute health services utilization with 2012 US fee-for-service and managed care Medicaid claims in all 50 states and DC. We compared FQHC (N=121,977) to non-FQHC patients (N=700,401) using propensity scores to balance covariates and generalized estimating equation models.

RESULTS

Overall, laboratory-based process measures occurred more frequently (range, 65.7%-76.6%) than measures requiring specialty referrals (retinal examinations, 33.3%; diabetes education, 3.4%). Compared with non-FQHC patients, FQHC patients had about 3 percentage point lower rates of each process measure, except for higher rates of diabetes education [relative risk=1.09, 95% confidence interval (CI): 1.03-1.16]. FQHC patients had fewer overall [incident rate ratio (IRR)=0.87, 95% CI: 0.86-0.88] and diabetes-related hospitalizations (IRR=0.79, 95% CI: 0.77-0.81), but more overall (IRR=1.06, 95% CI: 1.05-1.07) and diabetes-related emergency department visits (IRR=1.10, 95% CI: 1.08-1.13).

CONCLUSIONS

This national analysis identified opportunities to improve diabetes management among Medicaid enrollees with type 2 diabetes, especially for retinal examinations or diabetes education. Overall, we found slightly lower rates of most diabetes care process measures for FQHC patients versus non-FQHC patients. Despite having higher rates of emergency department visits, FQHC patients were significantly less likely to be hospitalized than non-FQHC patients. These findings emphasize the need to identify innovative, effective approaches to improve diabetes care for Medicaid enrollees, especially in FQHC settings.

Early experience of the quality improvement award program in federally funded health centers

OBJECTIVES

To describe the Health Resources and Services Administration's Quality Improvement Award (QIA) program, award patterns, and early lessons learned.

STUDY SETTING

1413 health centers were eligible for QIA from 2014 to 2018.

STUDY DESIGN

We assessed cumulative QIA funding earned and modified funding excluding payments for per-patient bonuses, electronic health record (EHR) use, patient-centered medical home (PCMH) accreditation, and health information technology. We compared health centers on rural/urban location, PCMH accreditation, EHR reporting, and size.

DATA COLLECTION

Organizational and quality measures are reported in the Uniform Data System, QIA program data.

PRINCIPAL FINDINGS

Average cumulative funding was higher for health centers that were not rural (USD 380,387 [± USD 233,467] vs. USD 303,526 [± USD 164,272]), had PCMH accreditation (USD 401,675 [± USD 218,246] vs. USD 250,784 [± USD 144,404]), used their EHR for quality reporting (USD 374,214 (± USD 222,866) vs. USD 331,150 (± USD 198,689)), and were large (USD 435,473 (± USD 238,193) vs. USD 270,681 (± USD 114,484) an USD 231,917 (± USD 97,847) for small and medium centers, respectively). There were similar patterns, with smaller differences, for average modified payments.

CONCLUSIONS

QIA is an important feasible initiative to introduce value-based payment principles to health centers. Early lessons for program design include announcing award criteria in advance and focusing on a smaller number of priority targets.

Factors associated with federally qualified health center financial performance

OBJECTIVES

To understand factors associated with federally qualified health center (FQHC) financial performance.

STUDY DESIGN

We used multivariate linear regression to identify correlates of health center financial performance. We examined six measures of health center financial performance across four domains: margin (operating margin), liquidity (days cash on hand [DCOH], current ratio), solvency (debt-to-equity ratio), and others (net patient accounts receivable days, personnel-related expenses). We examined potential correlates of financial performance, including characteristics of the patient population, health center organization, and location/geography.

DATA SOURCES

We use 2012-2017 Uniform Data System (UDS) files, financial audit data from Capital link, and publicly available data.

DATA COLLECTION/EXTRACTION METHODS

We focused on health centers in the 50 US states and District of Columbia, which reported information to UDS for at least 1 year between 2012 and 2017 and had Capital link financial audit data.

PRINCIPAL FINDINGS

FQHC financial performance generally improved over the study period, especially from 2015 to 2017. In multivariate regression models, a higher percentage of Medicaid patients was associated with better margins (operating margin: 0.06, p < 0.001), liquidity (DCOH: 0.67, p < 0.001; current ratio: 0.28, p = 0.001), and solvency (debt-to equity ratio: -0.08, p = 0.004). Moreover, a staffing mix comprised of more nonphysician providers was associated with better margin (operating margin: 0.21, p = 0.001) and liquidity (current ratio: 1.12, p < 0.001) measures. Patient-centered medical home (PCMH) recognition was also associated with better liquidity (DCOH: 19.01, p < 0.001; current ratio: 4.68, p = 0.014) and solvency (debt-to-equity ratio: -2.03, p < 0.001).

CONCLUSIONS

The financial health of FQHCs improved with provisions of the Affordable Care Act, which included significant Medicaid expansion and direct funding support for health centers. FQHC financial health was also associated with key staffing and operating characteristics of health centers. Maintaining the financial health of FQHCs is critical to their ability to continuously provide affordable and high-quality care in medically underserved areas.

First-Line Therapy for Type 2 Diabetes With Sodium-Glucose Cotransporter-2 Inhibitors and Glucagon-Like Peptide-1 Receptor Agonists : A Cost-Effectiveness Study

BACKGROUND

Guidelines recommend sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 (GLP1) receptor agonists as second-line therapy for patients with type 2 diabetes. Expanding their use as first-line therapy has been proposed but the clinical benefits may not outweigh their costs.

OBJECTIVE

To evaluate the lifetime cost-effectiveness of a strategy of first-line SGLT2 inhibitors or GLP1 receptor agonists.

DESIGN

Individual-level Monte Carlo-based Markov model.

DATA SOURCES

Randomized trials, Centers for Disease Control and Prevention databases, RED BOOK, and the National Health and Nutrition Examination Survey.

TARGET POPULATION

Drug-naive U.S. patients with type 2 diabetes.

TIME HORIZON

Lifetime.

PERSPECTIVE

Health care sector.

INTERVENTION

First-line SGLT2 inhibitors or GLP1 receptor agonists.

OUTCOME MEASURES

Life expectancy, lifetime costs, incremental cost-effectiveness ratios (ICERs).

RESULTS OF BASE-CASE ANALYSIS

First-line SGLT2 inhibitors and GLP1 receptor agonists had lower lifetime rates of congestive heart failure, ischemic heart disease, myocardial infarction, and stroke compared with metformin. First-line SGLT2 inhibitors cost $43 000 more and added 1.8 quality-adjusted months versus first-line metformin ($478 000 per quality-adjusted life-year [QALY]). First-line injectable GLP1 receptor agonists cost more and reduced QALYs compared with metformin.

RESULTS OF SENSITIVITY ANALYSIS

By removing injection disutility, first-line GLP1 receptor agonists were no longer dominated (ICER, $327 000 per QALY). Oral GLP1 receptor agonists were not cost-effective (ICER, $823 000 per QALY). To be cost-effective at under $150 000 per QALY, costs for SGLT2 inhibitors would need to be under $5 per day and under $6 per day for oral GLP1 receptor agonists.

LIMITATION

U.S. population and costs not generalizable internationally.

CONCLUSION

As first-line agents, SGLT2 inhibitors and GLP1 receptor agonists would improve type 2 diabetes outcomes, but their costs would need to fall by at least 70% to be cost-effective.

PRIMARY FUNDING SOURCE

American Diabetes Association.

Can Alternative Payment Models And Value-Based Insurance Design Alter The Course Of Diabetes In The United States?

Diabetes process and outcome measures are common quality measures in payment reform models, including Alternative Payment Models (APMs) and value-based insurance design (VBID). In this commentary we review evidence from selected research to examine whether these payment models can improve the value of diabetes care. We found that higher-risk APMs yielded greater improvements in diabetes process measures than lower-risk APMs, and that VBID models appeared to improve medication adherence but not other quality measures. We argue that these models are promising first steps in redesigning the payment system to improve diabetes care. However, greater coordination and alignment across models is needed to enhance their impact on providers' behavior, diabetes care processes, and patient health outcomes.

Delayed medical care and its perceived health impact among US older adults during the COVID-19 pandemic

BACKGROUND

Medical care delivery has been substantially disrupted during the coronavirus disease 2019 (COVID-19) pandemic, leading to delays in medical care, particularly among older adults. Less is known about how these delays have affected different segments of this population. Understanding the negative health consequences older adults face from delayed care will provide critical insights into the longer-term population health needs following the pandemic.

METHODS

We used data from a COVID-19 substudy embedded in a nationally representative longitudinal study of older adults, the National Social Life, Health, and Aging Project. Data were collected between September 14, 2020, and January 27, 2021. Two thousand six hundred seventy-two individuals responded to the survey. Using logistic and multinomial logistic regressions, we determined respondent-level characteristics associated with delayed medical care, experiencing a negative impact on physical health from delayed care, and with reporting worsening physical health during the pandemic.

RESULTS

Nearly, one-third (32.8%) of older adults reported delayed medical care during the pandemic. Female sex, higher levels of education, greater concerns about the pandemic, and poorer self-rated physical health were associated with delayed medical care. Blacks and those who are 70 and older were less likely to report delayed care. Among those whose care was delayed, 76.5% reported having already recovered delayed care. Nearly one in five (17.6%) reported that delayed care negatively affected their health. Older adults with worse self-rated physical and mental health or who had not fully recovered delayed care were more likely to report perceived negative health impacts from the delay. Regardless of delayed medical care, 10.2% reported worse physical health during the pandemic.

CONCLUSIONS

One-third of older adults experienced care delays during the pandemic. Despite high rates of care recovery, nearly one in five older adults who experienced delayed care reported being negatively affected. Strategies must be developed to reach these vulnerable patients to increase their healthcare utilization.

Estimating the Impact of Medicaid Expansion and Federal Funding Cuts on FQHC Staffing and Patient Capacity

Policy Points In the preexpansion period, federally qualified health centers (FQHCs) in Medicaid expansion states were significantly different from those in nonexpansion states. This gap widened as revenues in expansion states continued to grow at a faster rate after the expansion. If Medicaid expansion had occurred nationwide, FQHCs' revenue and capacity could have increased substantially. Over time, Medicaid could play a bigger role as it becomes a more stable funding source to allow for capital investments. Section 330 grants appear to have a larger impact on access to care. Given the varying levels of reliance on Medicaid, investing through federal grants might be more effective and equitable.

CONTEXT

The Health Resources and Services Administration's Health Center Program (HCP) plays a critical role as the national ambulatory safety net, delivering services to patients in medically underserved areas, regardless of their ability to pay. As the program has grown, health policy initiatives may have altered access to care for the underserved population. Understanding how federally qualified health centers (FQHCs) have been affected by past policies is important for anticipating the effects of future policies.

METHODS

By analyzing a national data set from the Uniform Data System, we examined, using two sets of random effects regressions, the potential impact of alternative policy actions affecting FQHCs. Our primary equation models the number of full-time equivalent staff, of patients served, and of visits provided in the subsequent year as a function of Medicaid revenues, Section 330 grants, and other revenues. Our secondary equation is a difference-in-differences analysis that models Medicaid revenues as a function of the states' status of Medicaid expansion.

FINDINGS

The expansion of Medicaid in nonexpansion states could have increased Medicaid revenues by 138%, staffing by 25%, and patients' visits by 24% in 2017. Compared to the impact of a "repeal" of Medicaid expansion, the percentage of reductions in staffing would be similar to those predicted by a 50% cut in Medicaid revenues or in Section 330 grants. On a dollar-for-dollar basis, the effects of one dollar of Section 330 grants were more than double that of one dollar of Medicaid revenue.

CONCLUSIONS

Both Medicaid eligibility and Section 330 funding support are important to the HCP, and Section 330 grants are particularly closely related to staffing and the provision of services. States' decisions not to participate in or to repeal Medicaid expansion, to reduce Medicaid payment rates, and federal funding cuts all could have a negative impact on FQHCs, resulting in thousands of low-income patients losing access to primary care.

Defining Minimum Necessary Communication During Care Transitions for Patients on Antihyperglycemic Medication: Consensus of the Care Transitions Task Force of the IPRO Hypoglycemia Coalition

INTRODUCTION

Antihyperglycemic agents are significant contributors to adverse drug events, responsible for emergency department visits, hospitalizations, and death. Nationally, the rate of serious hypoglycemic events associated with these agents remains high despite widespread efforts to improve drug safety. Transitions of care between healthcare settings can lead to communication challenges between care professionals and increase the risk of adverse drug events. System-based improvements are needed to assure the safe transitions for patients with diabetes who are on antihyperglycemic agents. The objective of this study was to develop a consensus list of requisite elements that should be communicated between care settings during transitions of patients who are prescribed antihyperglycemic agents.

METHODS

The Island Peer Review Organization (IPRO) Hypoglycemia Coalition identified suboptimal transitions of care as a barrier to improving patient safety and quality of diabetes care. The Coalition formed a multidisciplinary Task Force with experts in the field of diabetes care. The Task Force created a draft list of requisite communication elements through literature review and deliberation on monthly conference calls. A blinded iterative Delphi process was subsequently performed to generate a consensus list of requisite communication elements that participating experts agreed were necessary to safely and effectively assume the management of patients with diabetes upon care transitions.

RESULTS

The Task Force completed a series of four iterative polls from September 2015 to August 2016, resulting in a final list of 22 requisite communication elements (the Diabetes Management Discharge Communication List), with the elements conceptually categorized into three domains: diagnosis and treatment, factors affecting glycemic control or patient risk, and patient self-management.

CONCLUSIONS

The Diabetes Management Discharge Communication List provides an initial framework for the development of diabetes-specific resources to improve clinical communication between care settings.

Longer-term Benefits and Risks of Sodium-Glucose Cotransporter-2 Inhibitors in Type 2 Diabetes: a Systematic Review and Meta-analysis

BACKGROUND

Sodium-glucose cotransporter-2 inhibitors (SGLT2Is) are a recent class of medication approved for the treatment of type 2 diabetes (T2D). Previous meta-analyses have quantified the benefits and harms of SGLT2Is; however, these analyses have been limited to specific outcomes and comparisons and included trials of short duration. We comprehensively reviewed the longer-term benefits and harms of SGLT2Is compared to placebo or other anti-hyperglycemic medications.

METHODS

We searched PubMed, Scopus, and clinicaltrials.gov from inception to July 2019 for randomized controlled trials of minimum 52 weeks' duration that enrolled adults with T2D, compared an SGLT2I to either placebo or other anti-hyperglycemic medications, and reported at least one outcome of interest including cardiovascular risk factors, microvascular and macrovascular complications, mortality, and adverse events. We conducted random effects meta-analyses to provide summary estimates using weighted mean differences (MD) and pooled relative risks (RR). The study was registered a priori with PROSPERO (CRD42018090506).

RESULTS

Fifty articles describing 39 trials (vs. placebo, n = 28; vs. other anti-hyperglycemic medication, n = 12; vs. both, n = 1) and 112,128 patients were included in our analyses. Compared to placebo, SGLT2Is reduced cardiovascular risk factors (e.g., hemoglobin A1c, MD - 0.55%, 95% CI - 0.62, - 0.49), macrovascular outcomes (e.g., hospitalization for heart failure, RR 0.70, 95% CI 0.62, 0.78), and mortality (RR 0.87, 95% CI 0.80, 0.94). Compared to other anti-hyperglycemic medications, SGLT2Is reduced cardiovascular risk factors, but insufficient data existed for other outcomes. About a fourfold increased risk of genital yeast infections for both genders was observed for comparisons vs. placebo and other anti-hyperglycemic medications.

DISCUSSION

We found that SGLT2Is led to durable reductions in cardiovascular risk factors compared to both placebo and other anti-hyperglycemic medications. Reductions in macrovascular complications and mortality were only observed in comparisons with placebo, although trials comparing SGLT2Is vs. other anti-hyperglycemic medications were not designed to assess longer-term outcomes.

The Longer-Term Benefits and Harms of Glucagon-Like Peptide-1 Receptor Agonists: a Systematic Review and Meta-Analysis

BACKGROUND

Previous meta-analyses of the benefits and harms of glucagon-like peptide-1 receptor agonists (GLP1RAs) have been limited to specific outcomes and comparisons and often included short-term results. We aimed to estimate the longer-term effects of GLP1RAs on cardiovascular risk factors, microvascular and macrovascular complications, mortality, and adverse events in patients with type 2 diabetes, compared to placebo and other anti-hyperglycemic medications.

METHODS

We searched PubMed, Scopus, and clinicaltrials.gov (inception-July 2019) for randomized controlled trials ≥ 52 weeks' duration that compared a GLP1RA to placebo or other anti-hyperglycemic medication and included at least one outcome of interest. Outcomes included cardiovascular risk factors, microvascular and macrovascular complications, all-cause mortality, and treatment-related adverse events. We performed random effects meta-analyses to give summary estimates using weighted mean differences (MD) and pooled relative risks (RR). Risk of bias was assessed using the Cochrane Collaboration risk of bias in randomized trials tool. Quality of evidence was summarized using the Grading of Recommendations, Assessment, Development, and Evaluation approach. The study was registered a priori with PROSPERO (CRD42018090506).

RESULTS

Forty-five trials with a mean duration of 1.7 years comprising 71,517 patients were included. Compared to placebo, GLP1RAs reduced cardiovascular risk factors, microvascular complications (including renal events, RR 0.85, 0.80-0.90), macrovascular complications (including stroke, RR 0.86, 0.78-0.95), and mortality (RR 0.89, 0.84-0.94). Compared to other anti-hyperglycemic medications, GLP1RAs only reduced cardiovascular risk factors. Increased gastrointestinal events causing treatment discontinuation were observed in both comparisons.

DISCUSSION

GLP1RAs reduced cardiovascular risk factors and increased gastrointestinal events compared to placebo and other anti-hyperglycemic medications. GLP1RAs also reduced MACE, stroke, renal events, and mortality in comparisons with placebo; however, analyses were inconclusive for comparisons with other anti-hyperglycemic medications. Given the high costs of GLP1RAs, the lack of long-term evidence comparing GLP1RAs to other anti-hyperglycemic medications has significant policy and clinical practice implications.

2015-2016 Normative Data for the 3-m Usual Walk, Five Repeated Chair Stands, and Static Balance Components of the SPPB Among U.S. Older Adults Across Two Nationally Representative Data Sets: NSHAP and NHATS

OBJECTIVES

Our primary objective was to examine the distribution of 3-m usual walk, five repeated chair stands, and three static balance stance performances among age and gender subgroups of adults at least 65 years in two national data sets. We secondarily determined whether demographic-function associations varied across data sets, birth cohorts, or models incorporating data from those "unable to do" tasks.

METHODS

Two nationally representative data sets were used to generate survey weight-adjusted performance distributions: the 2015-2016 National Social Life Health and Aging Project and the 2016 National Health and Aging Trends Study. We then regressed walk and chair stand performance on age, gender, and race/ethnicity, examining differences across data sets, birth cohorts (1920-1947, 1948-1965), and before/after incorporating the "unable to do" performers.

RESULTS

Findings confirmed the gradual decline in function with age and allowed estimation of "relative" performance within age/gender subgroups. Data set distribution differences were noted, possibly due to recruitment, eligibility, and protocol variations. Demographic associations were similar across data sets but generally weaker among the 1948-1965 cohort and in models including the sizable "unable to do" group.

DISCUSSION

We present the largest, most current Short Physical Performance Battery reference data in U.S. adults aged 65 or older. Findings support standardization of administration protocols in research and clinical care and differentiating absolute from relative performance.

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical "doses" of the HealtheRx shared their information with others ("social doses"). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population ("agents") using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

Variability in Hourly Activity Levels: Statistical Noise or Insight Into Older Adult Frailty?

BACKGROUND

Frailty is associated with lower mean activity; however, hourly activity is highly variable among older individuals. We aimed to relate frailty to hourly activity variance beyond frailty's association with mean activity.

METHOD

Using the 2010-2011 National Social Life, Health and Aging Project wrist accelerometry data (n = 647), we employed a mixed-effects location scale model to simultaneously determine whether an adapted phenotypic frailty scale (0-4) was associated with the log10-mean hourly counts per minute (cpm) and between-and within-subject hourly activity variability, adjusting for demographics, health characteristics, season, day-of-week, and time-of-day. We tested the significance of a Frailty × Time-of-day interaction and whether adjusting for sleep time altered relationships.

RESULTS

Each additional frailty point was associated with a 7.6% (10-0.0343, β = -0.0343; 95% CI: -0.05, -0.02) lower mean hourly cpm in the morning, mid-day, and late afternoon but not evening. Each frailty point was also associated with a 24.5% (e0.219, β = 0.219; 95% CI: 0.09, 0.34) greater between-subject hourly activity variance across the day; a 7% (e0.07, β = 0.07; 95% CI: 0.01¸ 0.13), 6% (e0.06, β = 0.06; 95% CI: 0, 0.12), and 10% (e0.091, β = 0.091; 95% CI: 0.03, 0.15) greater within-subject hourly activity variance in the morning, mid-day, and late afternoon, respectively; and a 6% (e-0.06, β = -0.06; 95% CI: -0.12, -0.003) lower within-subject hourly activity variance in the evening. Adjusting for sleep time did not alter results.

CONCLUSIONS

Frail adults have more variable hourly activity levels than robust adults, a potential novel marker of vulnerability. These findings suggest a need for more precise activity assessment in older adults.

Cost and healthcare utilization analysis of culturally sensitive, shared medical appointment model for Latino children with type 1 diabetes

OBJECTIVE

This study evaluated costs and healthcare utilization associated with a culturally-sensitive, medical and education program for pediatric Latino patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Program participants included Latino children ages 1-20 years old diagnosed with type 1 diabetes (n = 57). Control subjects with type 1 diabetes were matched by age, sex, and zip code to intervention participants from the Colorado All Payer Claims Database. Data included emergency department (ED) visits, hospitalizations, demographic information, and health insurance claims data 180 days prior to program start/index date through 1 year after program start/index date. We tracked program staff time and estimated costs for healthcare utilization using data from the scientific literature. Generalized Estimating Equation (GEE) models with logit link were used to estimate group differences in probabilities of ED visits and hospitalizations over 6-month periods pre/post-study, accounting for correlation of within-subject data across time points. Sensitivity analyses modeled longer-term cost differences under different assumptions.

RESULTS

The intervention group had fewer hospitalizations, 2% versus 12% of controls (p = 0.047,OR = 0.13;95%CI: 0.02-0.97) for 6 months following start date. The intervention group had fewer ED visits, 19% versus 32% in controls (n.s.; p = 0.079,OR = 0.52;95%CI:0.25-1.08) and significantly fewer hospitalizations, 4% versus 15% of controls (p = 0.039,OR = 0.21;95%CI: 0.05-0.93) 6-12 months post-start date. One-year per-patient program costs of $633 and healthcare cost savings of $2710 yielded total per-patient savings of $2077, or a 5-year cost savings of $14,106.

CONCLUSION

This unique type 1 diabetes management program altered health service utilization of program participants, reducing major healthcare cost drivers, ED visits, and hospitalizations.

Analyzing Medical Guideline Dissemination Behaviors Using Culturally Infused Agent Based Modeling Framework

Clinical practice guidelines are a critical medium for the standardization of practices within the overall medical community. However, several studies have shown that, in general, there is a significant delay in the adoption of recommendations in such guidelines. Surveys have identified multiple barriers, including clinical inertia, organizational culture/incentives, access to information and peer influence on guideline dissemination and adoption. Although modeling techniques, especially agent-based models, have shown promise, a rigorous computational model for guideline dissemination that incorporates the intricacies of medical decision making and interactions of healthcare workers, and can identify more effective dissemination strategies, is needed. Similar modeling and simulation issues are also prevalent in many other domains such as opinion diffusion, innovation, and technology adoption. In this paper, we introduce a novel overarching computational modeling and simulation framework called the Culturally Infused Agent Based Modeling (CI-ABM) Framework. CI-ABM is a generalizable framework that provides the capability to model a wide range of real-world complex scenarios. To validate the framework, we focus on modeling and analyzing the dissemination of a Type 2 diabetes guideline that recommends individualizing glycemic (A1C) goals. Using existing cross-sectional surveys from physicians across the US, we demonstrate how our methodology for incorporating various socio-cultural and other related factors in agent based models lead to better posterior probability-based analysis and prediction of guideline dissemination behaviors.

Re-examining the Classification of Older Adults with Diabetes by Comorbidities and Relationship with Frailty, Disability, and 5-year Mortality

BACKGROUND

Limited research has been conducted to risk stratify older adults with diabetes. Our objective was to re-examine the 2005-06 classification systems in participants who are now five years older.

METHODS

We examined a subsample of 884 community-residing older adults with the diagnosis of diabetes from the National Social Life, Health, and Aging Project (NSHAP). The primary objective was to utilize a latent class analysis (LCA) to fit a model to 11 comorbidities, comparing the 2010-11 LCA model to that of 2005-6. The secondary objective was to evaluate the association of the identified classes with frailty, disability, and five-year mortality.

RESULTS

Both 2005-6 LCA and the 2010-11 LCA model fit three similar comorbidity profiles: Class 1 with the lowest rates of nearly all comorbidities, Class 2 had highest rates of obesity, hypertension, arthritis, and incontinence, and Class 3 had the higher rates of myocardial infarctions, congestive heart failure, and stroke. When compared to the healthier Class 1 (class probability=0.67), participants with a comorbidity profile with more prevalent cardiovascular conditions (Class 3; 0.09) were at higher risk of frailty and mortality, but not disability; whereas participants with a comorbidity profile with more prevalent geriatric syndrome conditions (Class 2; 0.24) were at higher risk of frailty and disability, but not mortality.

CONCLUSIONS

We reconfirmed three latent-classes with distinct comorbidity profiles among older adults with diabetes. However, the complex relationships between comorbidity classes with frailty, disability, and mortality will likely require revision of the current rationale for stratified goal setting and treatment selection.

Association of Loneliness With Falls: A Study of Older US Adults Using the National Social Life, Health, and Aging Project

Objectives: Falls represent a significant cause of morbidity and mortality in older adults, and are more common among those living alone. We aimed to determine if there is an association between loneliness and falls. Methods: Participants were surveyed in three waves separated by 5 years. We used the three-item UCLA Loneliness Scale to measure loneliness. Results: Data from 2337 respondents, with both loneliness and fall data in at least two consecutive waves, were included. Over three waves, 51% respondents reported a fall and 23% reported ≥ two falls. In multivariate analysis, the odds of having ≥ one fall 5 years later increased by a factor of 1.11 per one point increase on the loneliness scale (OR = 1.11, 95% CI 1.04, 1.19; p < .01). Discussion: Lonely older adults have increased odds of future falls. Strategies for combating loneliness in older adults may help reduce fall-related morbidity and mortality.

Practice Changes at U.S. Transplant Centers After the New Adult Heart Allocation Policy

BACKGROUND

In October 2018, the U.S. heart allocation system expanded the number of priority "status" tiers from 3 to 6 and added cardiogenic shock requirements for some heart transplant candidates listed with specific types of treatments.

OBJECTIVES

This study sought to determine the impact of the new policy on the treatment practices of transplant centers.

METHODS

Initial listing data on all adult heart candidates listed from December 1, 2017 to April 30, 2019 were collected from the Scientific Registry of Transplant Recipients. The status-qualifying treatments (or exception requests) and hemodynamic values at listing of a post-policy cohort (December 2018 to April 2019) were compared with a seasonally matched pre-policy cohort (December 2017 to April 2018). Candidates in the pre-policy cohort were reclassified into the new priority system statuses by using treatment, diagnosis, and hemodynamics.

RESULTS

Comparing the post-policy cohort (N = 1,567) with the pre-policy cohort (N = 1,606), there were significant increases in listings with extracorporeal membrane oxygenation (+1.2%), intra-aortic balloon pumps (+ 4 %), and exceptions (+ 12%). Listings with low-dose inotropes (-18%) and high-dose inotropes (-3%) significantly decreased. The new priority status distribution had more status 2 (+14%) candidates than expected and fewer status 3 (-5%), status 4 (- 4%) and status 6 (-8%) candidates than expected (p values <0.01 for all comparisons).

CONCLUSIONS

After implementation of the new heart allocation policy, transplant centers listed more candidates with extracorporeal membrane oxygenation, intra-aortic balloon pumps, and exception requests and fewer candidates with inotrope therapy than expected, thus leading to significantly more high-priority status listings than anticipated. If these early trends persist, the new allocation system may not function as intended.

Neighborhood Disadvantage and Hospital Quality Ratings in the Medicare Hospital Compare Program

BACKGROUND

The Centers for Medicare and Medicaid Services provide nationwide hospital ratings that may influence reimbursement. These ratings do not account for the social risk of communities and may inadvertently penalize hospitals that service disadvantaged neighborhoods.

OBJECTIVE

This study examines the relationship between neighborhood social risk factors (SRFs) and hospital ratings in Medicare's Hospital Compare Program.

RESEARCH DESIGN

2017 Medicare Hospital Compare ratings were linked with block group data from the 2015 American Community Survey to assess hospital ratings as a function of neighborhood SRFs.

SUBJECTS

A total of 3608 Medicare-certified hospitals in 50 US states.

MEASURES

Hospital summary scores and 7 quality group scores (100 percentile scale), including effectiveness of care, efficiency of care, hospital readmission, mortality, patient experience, safety of care, and timeliness of care.

RESULTS

Lower hospital summary scores were associated with caring for neighborhoods with higher social risk, including a reduction in hospital score for every 10% of residents who reported dual-eligibility for Medicare/Medicaid [-3.3%; 95% confidence interval (CI), -4.7 to -2.0], no high-school diploma (-0.8%; 95% CI, -1.5 to -0.1), unemployment (-1.2%; 95% CI, -1.9 to -0.4), black race (-1.2%; 95% CI, -1.7 to -0.8), and high travel times to work (-2.5%; 95% CI, -3.3 to -1.6). Associations between neighborhood SRFs and hospital ratings were largest in the timeliness of care, patient experience, and hospital readmission groups; and smallest in the safety, efficiency, and effectiveness of care groups.

CONCLUSIONS

Hospitals serving communities with higher social risk may have lower ratings because of neighborhood factors. Failing to account for neighborhood social risk in hospital rating systems may reinforce hidden disincentives to care for medically underserved areas in the United States.

Impact of a Low-Intensity Resource Referral Intervention on Patients' Knowledge, Beliefs, and Use of Community Resources: Results from the CommunityRx Trial

BACKGROUND

Connecting patients to community-based resources is now a cornerstone of modern healthcare that supports self-management of health. The mechanisms that link resource information to behavior change, however, remain poorly understood.

OBJECTIVE

To evaluate the impact of CommunityRx, an automated, low-intensity resource referral intervention, on patients' knowledge, beliefs, and use of community resources.

DESIGN

Real-world controlled clinical trial at an urban academic medical center in 2015-2016; participants were assigned by alternating week to receive the CommunityRx intervention or usual care. Surveys were administered at baseline, 1 week, 1 month, and 3 months.

PARTICIPANTS

Publicly insured adults, ages 45-74 years.

INTERVENTION

CommunityRx generated an automated, personalized list of resources, known as HealtheRx, near each participant's home using condition-specific, evidence-based algorithms. Algorithms used patient demographic and health characteristics documented in the electronic health record to identify relevant resources from a comprehensive, regularly updated database of health-related resources in the study area.

MAIN MEASURES

Using intent-to-treat analysis, we examined the impact of HealtheRx referrals on (1) knowledge of the most commonly referred resource types, including healthy eating classes, individual counseling, mortgage assistance, smoking cessation, stress management, and weight loss classes or groups, and (2) beliefs about having resources in the community to manage health.

KEY RESULTS

In a real-world controlled trial of 374 adults, intervention recipients improved knowledge (AOR = 2.15; 95% CI, 1.29-3.58) and beliefs (AOR = 1.68; 95% CI, 1.07-2.64) about common resources in the community to manage health, specifically gaining knowledge about smoking cessation (AOR = 2.76; 95% CI, 1.07-7.12) and weight loss resources (AOR = 2.26; 95% CI 1.05-4.84). Positive changes in both knowledge and beliefs about community resources were associated with higher resource use (P = 0.02).

CONCLUSIONS

In a middle-age and older population with high morbidity, a low-intensity health IT intervention to deliver resource referrals promoted behavior change by increasing knowledge and positive beliefs about community resources for self-management of health.

NIH TRIAL REGISTRY

NCT02435511.

Differences in the Receipt of Low-Value Services Between Publicly and Privately Insured Children

BACKGROUND

Children frequently receive low-value services that do not improve health, but it is unknown whether the receipt of these services differs between publicly and privately insured children.

METHODS

We analyzed 2013-2014 Medicaid Analytic eXtract and IBM MarketScan Commercial Claims and Encounters databases. Using 20 measures of low-value care (6 diagnostic testing measures, 5 imaging measures, and 9 prescription drug measures), we compared the proportion of publicly and privately insured children in 12 states who received low-value services at least once or twice in 2014; the proportion of publicly and privately insured children who received low-value diagnostic tests, imaging tests, and prescription drugs at least once; and the proportion of publicly and privately insured children eligible for each measure who received the service at least once.

RESULTS

Among 6 951 556 publicly insured children and 1 647 946 privately insured children, respectively, 11.0% and 8.9% received low-value services at least once, 3.9% and 2.8% received low-value services at least twice, 3.2% and 3.8% received low-value diagnostic tests at least once, 0.4% and 0.4% received low-value imaging tests at least once, and 8.4% and 5.5% received low-value prescription drug services at least once. Differences in the proportion of eligible children receiving each service were typically small (median difference among 20 measures, public minus private: +0.3 percentage points).

CONCLUSIONS

In 2014, 1 in 9 publicly insured and 1 in 11 privately insured children received low-value services. Differences between populations were modest overall, suggesting that wasteful care is not highly associated with payer type. Efforts to reduce this care should target all populations regardless of payer mix.

The Impact of Biomarker Screening and Cascade Genetic Testing on the Cost-Effectiveness of MODY Genetic Testing

OBJECTIVE

In the U.S., genetic testing for maturity-onset diabetes of the young (MODY) is frequently delayed because of difficulty with insurance coverage. Understanding the economic implications of clinical genetic testing is imperative to advance precision medicine for diabetes. The objective of this article is to assess the cost-effectiveness of genetic testing, preceded by biomarker screening and followed by cascade genetic testing of first-degree relatives, for subtypes of MODY in U.S. pediatric patients with diabetes.

RESEARCH DESIGN AND METHODS

We used simulation models of distinct forms of diabetes to forecast the clinical and economic consequences of a systematic genetic testing strategy compared with usual care over a 30-year time horizon. In the genetic testing arm, patients with MODY received treatment changes (sulfonylureas for HNF1A- and HNF4A-MODY associated with a 1.0% reduction in HbA_1c; no treatment for GCK-MODY). Study outcomes included costs, life expectancy (LE), and quality-adjusted life years (QALY).

RESULTS

The strategy of biomarker screening and genetic testing was cost-saving as it increased average quality of life (+0.0052 QALY) and decreased costs (-$191) per simulated patient relative to the control arm. Adding cascade genetic testing increased quality-of-life benefits (+0.0081 QALY) and lowered costs further (-$735).

CONCLUSIONS

A combined strategy of biomarker screening and genetic testing for MODY in the U.S. pediatric diabetes population is cost-saving compared with usual care, and the addition of cascade genetic testing accentuates the strategy's benefits. Widespread implementation of this strategy could improve the lives of patients with MODY while saving the health system money, illustrating the potential population health benefits of personalized medicine.

Use and Discontinuation of Insulin Treatment Among Adults Aged 75 to 79 Years With Type 2 Diabetes

IMPORTANCE

Among older individuals with type 2 diabetes, those with poor health have greater risk and derive less benefit from tight glycemic control with insulin.

OBJECTIVE

To examine whether insulin treatment is used less frequently and discontinued more often among older individuals with poor health compared with those in good health.

DESIGN, SETTING, AND PARTICIPANTS

This longitudinal cohort study included 21 531 individuals with type 2 diabetes followed for up to 4 years starting at age 75 years. Electronic health record data from the Kaiser Permanente Northern California Diabetes Registry was collected to characterize insulin treatment and glycemic control over time. Data were collected from January 1, 2009, through December 31, 2017, and analyzed from February 2, 2018, through June 30, 2019.

EXPOSURES

Health status was defined as good (<2 comorbid conditions or 2 comorbidities but physically active), intermediate (>2 comorbidities or 2 comorbidities and no self-reported weekly exercise), or poor (having end-stage pulmonary, cardiac, or renal disease; diagnosis of dementia; or metastatic cancer).

MAIN OUTCOMES AND MEASURES

Insulin use prevalence at age 75 years and discontinuation among insulin users over the next 4 years (or 6 months prior to death if <4 years).

RESULTS

Of 21 531 patients, 10 396 (48.3%) were women, and the mean (SD) age was 75 (0) years. Nearly one-fifth of 75-year-olds (4076 [18.9%]) used insulin. Prevalence and adjusted risk ratios (aRRs) of insulin use at age 75 years were higher in individuals with poor health (29.4%; aRR, 2.03; 95% CI, 1.87-2.20; P < .01) and intermediate health (27.5%; aRR, 1.85; 95% CI, 1.74-1.97; P < .01) relative to good health (10.5% [reference]). One-third (1335 of 4076 [32.7%]) of insulin users at age 75 years discontinued insulin within 4 years of cohort entry (and at least 6 months prior to death). Likelihood of continued insulin use was higher among individuals in poor health (aRR, 1.47; 95% CI, 1.27-1.67; P < .01) and intermediate health (aRR, 1.16; 95% CI, 1.05-1.30; P < .01) compared with good health (reference). These same prevalence and discontinuation patterns were present in the subset with tight glycemic control (hemoglobin A1c <7.0%).

CONCLUSIONS AND RELEVANCE

In older individuals with type 2 diabetes, insulin use was most prevalent among those in poor health, whereas subsequent insulin discontinuation after age 75 years was most likely in healthier patients. Changes are needed in current practice to better align with guidelines that recommend reducing treatment intensity as health status declines.

National physician survey on glycemic goals and medical decision making for patients with type 2 diabetes

To describe how patient characteristics influence physician decision-making about glycemic goals for Type 2 diabetes.2016 survey of 357 US physicians. The survey included two vignettes, representing a healthy patient and an unhealthy patient, adapted from a past survey of international experts and a factorial design vignette that varied age, heart disease history, and hypoglycemia history. Survey results were weighted to provide national estimates.Over half (57.6%) of physicians recommended a goal HbA1c <7.0% for most of their patients. For the healthy patient vignette, physicians recommended a goal similar to that of international experts (<6.66% (95% Confidence Interval (CI), 6.61-6.71%) vs <6.5% (Interquartile range (IQR), 6.5-6.8%)). For the unhealthy patient, physicians recommended a lower goal than international experts (<7.38% (CI, 7.30-7.46) vs <8.0% (IQR, 7.5-8.0%)). In the factorial vignette, physicians varied HbA1c goals by 0.35%, 0.06%, and 0.28% based on age, heart disease history, and hypoglycemia risk, respectively. The goal HbA1c range between the 55-year-old with no heart disease or hypoglycemic events and the 75-year-old with heart disease and hypoglycemic events was 0.65%.Despite guidelines that recommend HbA1c goals ranging from <6.5% to <8.5%, US physicians seem to be anchored on HbA1c goals around <7.0%.

Association of Transplant Center With Survival Benefit Among Adults Undergoing Heart Transplant in the United States

IMPORTANCE

In the United States, the number of deceased donor hearts available for transplant is limited. As a proxy for medical urgency, the US heart allocation system ranks heart transplant candidates largely according to the supportive therapy prescribed by transplant centers.

OBJECTIVE

To determine if there is a significant association between transplant center and survival benefit in the US heart allocation system.

DESIGN, SETTING, AND PARTICIPANTS

Observational study of 29 199 adult candidates for heart transplant listed on the national transplant registry from January 2006 through December 2015 with follow-up complete through August 2018.

EXPOSURES

Transplant center.

MAIN OUTCOMES AND MEASURES

The survival benefit associated with heart transplant as defined by the difference between survival after heart transplant and waiting list survival without transplant at 5 years. Each transplant center's mean survival benefit was estimated using a mixed-effects proportional hazards model with transplant as a time-dependent covariate, adjusted for year of transplant, donor quality, ischemic time, and candidate status.

RESULTS

Of 29 199 candidates (mean age, 52 years; 26% women) on the transplant waiting list at 113 centers, 19 815 (68%) underwent heart transplant. Among heart transplant recipients, 5389 (27%) died or underwent another transplant operation during the study period. Of the 9384 candidates who did not undergo heart transplant, 5669 (60%) died (2644 while on the waiting list and 3025 after being delisted). Estimated 5-year survival was 77% (interquartile range [IQR], 74% to 80%) among transplant recipients and 33% (IQR, 17% to 51%) among those who did not undergo heart transplant, which is a survival benefit of 44% (IQR, 27% to 59%). Survival benefit ranged from 30% to 55% across centers and 31 centers (27%) had significantly higher survival benefit than the mean and 30 centers (27%) had significantly lower survival benefit than the mean. Compared with low survival benefit centers, high survival benefit centers performed heart transplant for patients with lower estimated expected waiting list survival without transplant (29% at high survival benefit centers vs 39% at low survival benefit centers; survival difference, -10% [95% CI, -12% to -8.1%]), although the adjusted 5-year survival after transplant was not significantly different between high and low survival benefit centers (77.6% vs 77.1%, respectively; survival difference, 0.5% [95% CI, -1.3% to 2.3%]). Overall, for every 10% decrease in estimated transplant candidate waiting list survival at a given center, there was an increase of 6.2% (95% CI, 5.2% to 7.3%) in the 5-year survival benefit associated with heart transplant.

CONCLUSIONS AND RELEVANCE

In this registry-based study of US heart transplant candidates, transplant center was associated with the survival benefit of transplant. Although the adjusted 5-year survival after transplant was not significantly different between high and low survival benefit centers, compared with centers with survival benefit significantly below the mean, centers with survival benefit significantly above the mean performed heart transplant for recipients who had significantly lower estimated expected 5-year waiting list survival without transplant.