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ImportanceOptimal diabetes care requires regular monitoring and care to maintain glycemic control. How high-deductible health plans (HDHPs), which reduce overall spending but may impede care by increasing out-of-pocket expenses, are associated with risks of severe hypoglycemia and hyperglycemia is unknown.ObjectiveTo examine the association between an employer-forced switch to HDHP and severe hypoglycemia and hyperglycemia.Design, Setting, and ParticipantsThis retrospective cohort study used deidentified administrative claims data for privately insured adults with diabetes from a single insurance carrier with multiple plans across the US between January 1, 2010, and December 31, 2018. Analyses were conducted between May 15, 2020, and November 3, 2022.ExposuresPatients with 1 baseline year of enrollment in a non-HDHP whose employers subsequently forced a switch to an HDHP were compared with patients who did not switch.Main Outcomes and MeasuresMixed-effects logistic regression models were used to examine the association between switching to an HDHP and the odds of severe hypoglycemia and hyperglycemia (ascertained using diagnosis codes in emergency department [ED] visits and hospitalizations), adjusting for patient age, sex, race and ethnicity, region, income, comorbidities, glucose-lowering medications, baseline ED and hospital visits for hypoglycemia and hyperglycemia, and baseline deductible amount, and applying inverse propensity score weighting to account for potential treatment selection bias.ResultsThe study population was composed of 42 326 patients who switched to an HDHP (mean [SD] age: 52 [10] years, 19 752 [46.7%] women, 7375 [17.4%] Black, 5740 [13.6%] Hispanic, 26 572 [62.8%] non-Hispanic White) and 202 729 patients who did not switch (mean [SD] age, 53 [10] years, 89 828 [44.3%] women, 29 551 [14.6%] Black, 26 689 [13.2%] Hispanic, 130 843 [64.5%] non-Hispanic White). When comparing all study years, switching to an HDHP was not associated with increased odds of experiencing at least 1 hypoglycemia-related ED visit or hospitalization (OR, 1.01 [95% CI, 0.95-1.06]; P = .85), but each year of HDHP enrollment did increase these odds by 2% (OR, 1.02 [95% CI, 1.00-1.04]; P = .04). In contrast, switching to an HDHP did significantly increase the odds of experiencing at least 1 hyperglycemia-related ED visit or hospitalization (OR, 1.25 [95% CI, 1.11-1.42]; P P = .02).Conclusions and RelevanceIn this cohort study, employer-forced switching to an HDHP was associated with increased odds of potentially preventable acute diabetes complications, potentially because of delayed or deferred care. These findings suggest that employers should be more judicious in their health plan offerings, and health plans and policy makers should consider allowing preventive and high-value services to be exempt from deductible requirements.

This cross-sectional study examines the association of socioeconomic, geographic, and behavioral factors with the quality of diabetes management for adults., Key Points Question What is the association between area deprivation index, rurality, and diabetes care quality? Findings In this cross-sectional study of 31 934 adult patients with diabetes receiving care at primary care practices across 3 US states, census block group–level area deprivation index score and zip code–level rurality were significantly associated with diabetes care quality. Meaning Findings from this study showed that adult patients with diabetes who lived in more deprived and rural areas were significantly less likely to attain high-quality diabetes care compared with those in less deprived and urban areas, calling for geographically targeted efforts to improve care quality and health outcomes for disadvantaged populations., Importance Diabetes management operates under a complex interrelationship between behavioral, social, and economic factors that affect a patient's ability to self-manage and access care. Objective To examine the association between 2 complementary area-based metrics, area deprivation index (ADI) score and rurality, and optimal diabetes care. Design, Setting, and Participants This cross-sectional study analyzed the electronic health records of patients who were receiving care at any of the 75 Mayo Clinic or Mayo Clinic Health System primary care practices in Minnesota, Iowa, and Wisconsin in 2019. Participants were adults with diabetes aged 18 to 75 years. All data were abstracted and analyzed between June 1 and November 30, 2020. Main Outcomes and Measures The primary outcome was the attainment of all 5 components of the D5 metric of optimal diabetes care: glycemic control (hemoglobin A1c

Dramatic reductions in outpatient visits and laboratory testing early in the COVID-19 pandemic1,2 raised concerns about gaps in diabetes management and glycemic control.3 We therefore compared weekly rates of diabetes-related outpatient visits, screening tests, medication fills, and patients’ hemoglobin A1c (HbA1c) levels in 2020 vs 2019 in a national cohort of adults with type 2 diabetes.

This cohort study examines the associations of age, cumulative multimorbidity, glycated hemoglobin level, and use of glucose level–lowering medication with hypoglycemia-related emergency department visits and hospitalizations among adults with diabetes., Key Points Question Among adults with diabetes, what is the association of multimorbidity with the risk of severe hypoglycemia in the context of other frequently encountered hypoglycemia risk factors, such as age, diabetes type, prior hypoglycemia, glycemic control, and high-risk medication use? Findings In this cohort study of 201 705 adults with diabetes in the United States, most individuals had additional chronic health conditions. Cumulative multimorbidity was associated with hypoglycemia-related emergency department visits and hospitalizations independent of other factors. Meaning Clinicians may want to consider a broad range of hypoglycemia risk factors, particularly cumulative multimorbidity, when developing a diabetes treatment plan and prioritize prescribing medications with a lower risk for hypoglycemia., Importance Severe hypoglycemia is a serious and potentially preventable complication of diabetes, with some of the most severe episodes requiring emergency department (ED) care or hospitalization. A variety of health conditions increase the risk of hypoglycemia. People with diabetes often have multiple comorbidities, and the association of such multimorbidity with hypoglycemia risk in the context of other risk factors is uncertain. Objective To examine the associations of age, cumulative multimorbidity, glycated hemoglobin (HbA1c) level, and use of glucose level–lowering medication with hypoglycemia-related ED visits and hospitalizations. Design, Setting, and Participants Cohort study of claims and laboratory data from OptumLabs Data Warehouse, an administrative claims database of commercially insured and Medicare Advantage beneficiaries in the United States. Participants were adults (aged ≥18 years) with diabetes who had an available HbA1c level result in 2015. Data from January 1, 2014, to December 31, 2016, were analyzed. Final analyses were conducted from December 2017 to September 2018. Main Outcomes and Measures This study calculated rates of hypoglycemia-related ED visits and hospitalizations during the year after the index HbA1c level was obtained, stratified by patient demographic characteristics, diabetes type, comorbidities (from 16 guideline-specified high-risk conditions), index HbA1c level, and glucose level–lowering medication use. The association of each variable with hypoglycemia-related ED and hospital care was examined using multivariable Poisson regression analysis overall and by diabetes type. Results The study cohort was composed of 201 705 adults with diabetes (mean [SD] age, 65.8 [12.1] years; 102 668 [50.9%] women; 118 804 [58.9%] white; mean [SD] index HbA1c level, 7.2% [1.5%]). Overall, there were 9.06 (95% CI, 8.64-9.47) hypoglycemia-related ED visits and hospitalizations per 1000 persons per year. The risk of hypoglycemia-related ED visits and hospitalizations was increased by age 75 years or older (incidence rate ratio [IRR], 1.56 [95% CI, 1.23-2.02] vs 18-44 years), black race/ethnicity (IRR, 1.30 [95% CI, 1.16-1.46] vs white race/ethnicity), lower annual household income (IRR, 0.63 [95% CI, 0.53-0.74] for ≥$100 000 vs

Key Points Question Are there differences in hospital readmission rates among racial and ethnic minorities with diabetes, and if so, what are the individual-level and hospital-level factors associated with these differences? Findings In this cohort study of 272 758 adults with diabetes, black patients had a significantly higher risk of unplanned all-cause 30-day hospital readmission than members of other racial/ethnic groups. This difference was most pronounced among lower-income patients and patients hospitalized in nonprofit, academic, or large hospitals. Meaning The observed differences in unplanned hospital readmission rates between black patients with diabetes and members of all other racial/ethnic groups reinforce the importance of identifying and addressing gaps in care that may be contributing to racial/ethnic disparities in health care quality and outcomes., This cohort study examines racial/ethnic differences in all-cause readmission among US adults with diabetes and categorizes patient- and system-level factors associated with these differences., Importance Differences in readmission rates among racial and ethnic minorities have been reported, but data among people with diabetes are lacking despite the high burden of diabetes and its complications in these populations. Objectives To examine racial/ethnic differences in all-cause readmission among US adults with diabetes and categorize patient- and system-level factors associated with these differences. Design, Setting, and Participants This retrospective cohort study includes 272 758 adult patients with diabetes, discharged alive from the hospital between January 1, 2009, and December 31, 2014, and stratified by race/ethnicity. An administrative claims data set of commercially insured and Medicare Advantage beneficiaries across the United States was used. Data analysis took place between October 2016 and February 2019. Main Outcomes and Measures Unplanned all-cause readmission within 30 days of discharge and individual-, clinical-, economic-, index hospitalization–, and hospital-level risk factors for readmission. Results A total of 467 324 index hospitalizations among 272 758 adults with diabetes (mean [SD] age, 67.7 [12.7]; 143 498 [52.6%] women) were examined. The rates of 30-day all-cause readmission were 10.2% (33 683 of 329 264) among white individuals, 12.2% (11 014 of 89 989) among black individuals, 10.9% (4151 of 38 137) among Hispanic individuals, and 9.9% (980 of 9934) among Asian individuals (P

Importance Intensive glucose-lowering treatment among patients with non–insulin-requiring type 2 diabetes may increase the risk of hypoglycemia. Objectives To estimate the prevalence of intensive treatment and the association between intensive treatment, clinical complexity, and incidence of severe hypoglycemia among adults with type 2 diabetes who are not using insulin. Design, Setting, and Participants Retrospective analysis of administrative, pharmacy, and laboratory data from the OptumLabs Data Warehouse from January 1, 2001, through December 31, 2013. The study included nonpregnant adults 18 years or older with type 2 diabetes who achieved and maintained a hemoglobin A 1c (HbA 1c ) level less than 7.0% without use of insulin and had no episodes of severe hypoglycemia or hyperglycemia in the prior 12 months. Main Outcomes and Measures Risk-adjusted probability of intensive treatment and incident severe hypoglycemia, stratified by patient clinical complexity. Intensive treatment was defined as use of more glucose-lowering medications than recommended by practice guidelines at specific index HbA 1c levels. Severe hypoglycemia was ascertained by ambulatory, emergency department, and hospital claims for hypoglycemia during the 2 years after the index HbA 1c test. Patients were categorized as having high vs low clinical complexity if they were 75 years or older, had dementia or end-stage renal disease, or had 3 or more serious chronic conditions. Results Of 31 542 eligible patients (median age, 58 years; interquartile range, 51-65 years; 15 483 women [49.1%]; 18 188 white [57.7%]), 3910 (12.4%) had clinical complexity. The risk-adjusted probability of intensive treatment was 25.7% (95% CI, 25.1%-26.2%) in patients with low clinical complexity and 20.8% (95% CI, 19.4%-22.2%) in patients with high clinical complexity. In patients with low clinical complexity, the risk-adjusted probability of severe hypoglycemia during the subsequent 2 years was 1.02% (95% CI, 0.87%-1.17%) with standard treatment and 1.30% (95% CI, 0.98%-1.62%) with intensive treatment (absolute difference, 0.28%; 95% CI, −0.10% to 0.66%). In patients with high clinical complexity, intensive treatment significantly increased the risk-adjusted probability of severe hypoglycemia from 1.74% (95% CI, 1.28%-2.20%) with standard treatment to 3.04% (95% CI, 1.91%-4.18%) with intensive treatment (absolute difference, 1.30%; 95% CI, 0.10%-2.50%). Conclusions and Relevance More than 20% of patients with type 2 diabetes received intensive treatment that may be unnecessary. Among patients with high clinical complexity, intensive treatment nearly doubles the risk of severe hypoglycemia.

For more than 20 years, the American Association of Clinical Endocrinologists (AACE) has been an authoritative source of advocacy and expertise in endocrinology. In line with its mission, the AACE recently introduced an update to their 2009 diabetes mellitus (DM) management algorithm,1 issuing an algorithm (April 2013),2 followed by a consensus statement (July2013).3 Management recommendations can be useful if they are based on evidence, developed through a readily understood process, and respectful of patients’ life circumstances and goals. A process that is easily understood is essential for physicians; other health care providers, such as physician assistants, nurse practitioners, and pharmacists; and patients to adequately judge the validity of management recommendations. Inclusion of patients’ values and preferences is important if the recommendations are to inform patient-centered care. In our view, the AACE’s DM algorithm and consensus statement do not meet these expectations and should not be used to guide clinical care in their current form. Algorithms and clinical guidelines should offer an assessment of the likely benefits and harms of treatments, and evaluate the quality of all of the relevant literature. The Institute of Medicine (IOM) has therefore proposed 8 standards for developing clinical practice guidelines to ensure “scientifically valid, transparent, and reproducible results.”4(p4) Although the AACE’s algorithm and consensus statement were not explicitly labeled as “guidelines,” they were “developed to provide clinicians with a practical guide”3(p3) to the management of type 2 DM, making them subject to the same general principles. The algorithm and consensus statement fall short on several of the 8 IOM standards. We are particularly concerned about the following.