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Background Diabetes mellitus is associated with increased rates of mortality in patients with less severe (stage C) heart failure (HF). The prevalence of diabetes and its complications in advanced (stage D) HF and their contributions to mortality risk are unknown. Methods and Results We conducted a retrospective population-based cohort study of all adult residents of Olmsted County, Minnesota, who had advanced HF between 2007 and 2017. Patients with diabetes were identified by using the criteria of the Healthcare Effectiveness Data and Information Set. Diabetes complications were captured by using the Diabetes Complications Severity Index. Of 936 patients with advanced HF, 338 (36.1%) had diabetes. Overall, median survival time after development of advanced HF was 13.1 (3.9–33.1) months; mortality did not vary by diabetes status (aHR 1.06, 95% CI 0.90–1.25; P = 0.45) or by glycated hemoglobin levels in those with diabetes (aHR 1.01 per 1% increase, 95% CI 0.93–1.10; P = 0.82). However, patients with diabetes and 4 (aHR 1.24, 95% CI 0.92–1.67) or 5–7 (aHR 1.49, 95% CI 1.09–2.03) diabetes complications were at increased risk of mortality compared to those with ≤ 3 complications. Conclusions More than one-third of patients with advanced HF have diabetes. In advanced HF, overall prognosis is poor, but we found no evidence that diabetes is associated with a significantly higher mortality risk.

OBJECTIVE To examine whether glucagon-like peptide 1 receptor agonists (GLP-1RA) and sodium–glucose cotransporter 2 inhibitors (SGLT2i) are preferentially initiated among patients with cardiovascular disease, heart failure (HF), or nephropathy, where these drug classes have established benefit, compared with dipeptidyl peptidase 4 inhibitors (DPP-4i), for which corresponding benefits have not been demonstrated. RESEARCH DESIGN AND METHODS We retrospectively analyzed claims of adults with type 2 diabetes included in OptumLabs Data Warehouse, a deidentified database of commercially insured and Medicare Advantage beneficiaries, who first started GLP-1RA, SGLT2i, or DPP-4i therapy between 2016 and 2019. Using multinomial logistic regression, we examined the relative risk ratios (RRR) of starting GLP-1RA and SGLT2i compared with DPP-4i for those with a history of myocardial infarction (MI), cerebrovascular disease, HF, and nephropathy after adjusting for demographic and other clinical factors. RESULTS We identified 75,395 patients who started GLP-1RA, 58,234 who started SGLT2i, and 91,884 who started DPP-4i. Patients with prior MI, cerebrovascular disease, or nephropathy were less likely to start GLP-1RA rather than DPP-4i compared with patients without these conditions (RRR 0.83 [95% CI 0.78–0.88] for MI, RRR 0.77 [0.74–0.81] for cerebrovascular disease, and RRR 0.87 [0.84–0.91] for nephropathy). Patients with HF or nephropathy were less likely to start SGLT2i (RRR 0.83 [0.80–0.87] for HF and RRR 0.57 [0.55–0.60] for nephropathy). Both medication classes were less likely to be started by non-White and older patients. CONCLUSIONS Patients with cardiovascular disease, HF, and nephropathy, for whom evidence suggests a greater likelihood of benefiting from GLP-1RA and/or SGLT2i therapy, were less likely to start these drugs. Addressing this treatment/benefit paradox, which was most pronounced in non-White and older patients, may help reduce the morbidity associated with these conditions.

A 45-year-old woman presented to our clinic in July 2019 for evaluation of intermittent fever, rigors, diaphoresis, malaise, and urinary symptoms of frequency and urgency of 5 days’ duration. Her history was notable for Graves disease after total thyroidectomy 8 months previously after failed medical management, with no neck swelling or pain at present; an incidentally discovered and resected papillary thyroid microcarcinoma; and hypertension. A reconciled medication list included levothyroxine (125 μg/d), sertraline (100 mg/d), amphetamine-dextroamphetamine (20 mg/d), propranolol (40 mg twice daily), selenium (200 μg/d), and biotin (10 mg/d). She reported no relevant family history or sick contacts, but she may have had tick exposure. Physical examination revealed a temperature of 39.4 °C, heart rate of 64 beats/min, blood pressure of 98/56 mm Hg, weight of 85 kg, exophthalmos and lagophthalmos, and healed Kocher incision with no neck masses or tenderness. Abdominal examination revealed mild suprapubic tenderness. The differential diagnosis included infection (urinary tract infection [UTI], viral syndrome, tick-borne illness) and hyperthyroidism in the setting of ongoing levothyroxine therapy and her history of Graves disease. Subsequent laboratory studies revealed the following (reference ranges provided parenthetically): hemoglobin, 10.7 g/dL (11.6 to 15.0 g/dL); white blood cell count, 16.7 × 10(9)/L (3.4 to 9.6 × 10(9)/L); creatinine, 0.91 mg/dL (0.59 to 1.04 mg/dL); 2 sets of blood cultures with negative results; urine culture growing Escherichia coli, greater than 100,000 colony-forming units per milliliter; and negative results on a tick-borne pathogen panel including Lyme disease serology. Chest radiography revealed no abnormalities. Thyroid function testing (TFT) revealed the following: thyrotropin, 0.01 mIU/L (0.3 to 4.2 mIU/L); free thyroxine (fT4), 1.3 ng/dL (0.9 to 1.7 ng/dL); and free triiodothyronine (fT3) 2.4 pg/mL (2.8 to 4.4 pg/mL). Antimicrobial therapy was initiated for a UTI.

Objectives Older patients discharged to skilled nursing facilities (SNFs) for post-acute care are at high risk for hospital readmission. Yet, as in the community setting, some readmissions may be preventable with optimal transitional care. This study examined the proportion of 30-day hospital readmissions from SNFs that could be considered potentially preventable readmissions (PPRs) and evaluated the reasons for these readmissions. Design Retrospective cohort study. Setting and Participants Post-acute practice of an integrated health care delivery system serving 11 SNFs in the US Midwest. Patients discharged from the hospital to an SNF and subsequently readmitted to the hospital within 30 days from January 1, 2009, through November 31, 2016. Methods A computerized algorithm evaluated the relationship between initial and repeat hospitalizations to determine whether the repeat hospitalization was a PPR. We assessed for changes in PPR rates across the system over the study period and evaluated the readmission categories to identify the most prevalent PPR categories. Results Of 11,976 discharges to SNFs for post-acute care among 8041 patients over the study period, 16.6% resulted in rehospitalization within 30 days, and 64.8% of these rehospitalizations were considered PPRs. Annual proportion of PPRs ranged from 58.2% to 66.4% [mean (standard deviation) 0.65 (0.03); 95% confidence interval CI 0.63-0.67; P = .36], with no discernable trend. Nearly one-half (46.2%) of all 30-day readmissions were classified as potentially preventable medical readmissions related to recurrence or continuation of the reason for initial admission or to complications from the initial hospitalization. Conclusions and Implications For this cohort of patients discharged to SNFs, a computerized algorithm categorized a large proportion of 30-day hospital readmissions as potentially preventable, with nearly one-half of those linked to the reason for the initial hospitalization. These findings indicate the importance of improvement in postdischarge transitional care for patients discharged to SNFs.

We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical decision support tool enables early diagnosis of low ejection fraction (EF), a condition that is underdiagnosed but treatable. In this trial ( NCT04000087 ), 120 primary care teams from 45 clinics or hospitals were cluster-randomized to either the intervention arm (access to AI results; 181 clinicians) or the control arm (usual care; 177 clinicians). ECGs were obtained as part of routine care from a total of 22,641 adults (N = 11,573 intervention; N = 11,068 control) without prior heart failure. The primary outcome was a new diagnosis of low EF (≤50%) within 90 days of the ECG. The trial met the prespecified primary endpoint, demonstrating that the intervention increased the diagnosis of low EF in the overall cohort (1.6% in the control arm versus 2.1% in the intervention arm, odds ratio (OR) 1.32 (1.01–1.61), P = 0.007) and among those who were identified as having a high likelihood of low EF (that is, positive AI-ECG, 6% of the overall cohort) (14.5% in the control arm versus 19.5% in the intervention arm, OR 1.43 (1.08–1.91), P = 0.01). In the overall cohort, echocardiogram utilization was similar between the two arms (18.2% control versus 19.2% intervention, P = 0.17); for patients with positive AI-ECGs, more echocardiograms were obtained in the intervention compared to the control arm (38.1% control versus 49.6% intervention, P

When making an appointment, patients are generally unaware of how much clinician time is available to address their concerns. Similarly, the primary care clinician is often unaware of what the patient expects to accomplish during the visit, leading to uncertainty about how much time they can allot to each sequentially appearing concern, and whether they can reasonably expect to address necessary preventive services and chronic disease management. Neither patient nor clinician expectations can be adequately managed through standardized scheduling templates, which assign a fixed appointment length based on a single stated reason for the visit. As such, standardized appointment scheduling may contribute to inefficient use of valuable face-to-face time, patient and clinician dissatisfaction, and low-value care. Herein, we suggest several potential mechanisms for improving the scheduling process, including (1) entrusting scheduling to the primary care team; (2) advance visit planning; (3) pro-active engagement of ancillary team members including behavioral health, nursing, social work, and pharmacy; and (4) application of innovative, technologically advanced solutions such as telehealth and artificial intelligence to the scheduling process. These changes have the potential to improve efficiency, patient and clinician satisfaction, and health outcomes, while decreasing low-value testing and return visits for unaddressed concerns.

As the COVID-19 pandemic continues to unfold, payers across the USA have stepped up to alleviate patients’ financial burden by waiving cost-sharing for COVID-19 testing and treatment. However, there has been no substantive discussion of potential long-term effects of COVID-19 on patient health or their financial and policy implications. After recovery, patients remain at risk for lung disease, heart disease, frailty, and mental health disorders. There may also be long-term sequelae of adverse events that develop in the course of COVID-19 and its treatment. These complications are likely to place additional medical, psychological, and economic burdens on all patients, with lower-income individuals, the uninsured and underinsured, and individuals experiencing homelessness being most vulnerable. Thus, there needs to be a comprehensive plan for preventing and managing post-COVID-19 complications to quell their clinical, economic, and public health consequences and to support patients experiencing delayed morbidity and disability as a result.

Background A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead electrocardiogram (ECG) has recently been developed and validated. The algorithm was incorporated into the electronic health record (EHR) to automatically screen for low EF, encouraging clinicians to obtain a confirmatory transthoracic echocardiogram (TTE) for previously undiagnosed patients, thereby facilitating early diagnosis and treatment. Objectives To prospectively evaluate a novel artificial intelligence (AI) screening tool for detecting low EF in primary care practices. Design The EAGLE trial is a pragmatic two-arm cluster randomized trial ( NCT04000087 ) that will randomize >100 clinical teams (i.e., clusters) to either intervention (access to the new AI screening tool) or control (usual care) at 48 primary care practices across Minnesota and Wisconsin. The trial is expected to involve approximately 400 clinicians and 20,000 patients. The primary endpoint is newly discovered EF ≤50%. Eligible patients will include adults who undergo ECG for any reason and have not been previously diagnosed with low EF. Data will be pulled from the EHR, and no contact will be made with patients. A positive deviance qualitative study and a post-implementation survey will be conducted among select clinicians to identify facilitators and barriers to using the new screening report. Summary This trial will examine the effectiveness of the AI-enabled ECG for detection of asymptomatic low EF in routine primary care practices and will be among the first to prospectively evaluate the value of AI in real-world practice. Its findings will inform future implementation strategies for the translation of other AI-enabled algorithms.

Objective It is difficult to assess self-management behaviors (SMBs) and incorporate them into a personalized self-care plan. We aimed to develop and apply SMB phenotyping algorithms from data collected by diabetes devices and a mobile health (mHealth) application to create patient-specific SMBs reports to guide individualized interventions. Follow-up interventions aimed to understand patient's reasoning behind discovered SMB choices. Methods This study deals with adults on continuous subcutaneous insulin infusion using a continuous glucose monitor (CGM) who self-tracked SMBs with an mHealth application for 1 month. Patient-generated data were quantified and an SMB report was designed and populated for each participant. A diabetes educator used the report to conduct personalized, data-driven educational interventions. Thematic analysis of the intervention was conducted. Results Twenty-two participants recorded 118 alcohol, 251 exercise, 2,661 meal events, and 1,900 photos. A patient-specific SMB report was created from this data and used to conduct the educational intervention. High variability of SMB was observed between patients. There was variability in the percentage of alcohol events accompanied by a blood glucose check, median 79% (38–100% range), and frequency of changing the bolus waveform, median 11 (7–95 range). Interventions confirmed variability of SMBs. Main emerging themes from thematic analysis were: challenges and barriers, motivators, current SMB techniques, and future plans to improve glycemic control. Conclusion The ability to quantify SMBs and understand patients' rationale may help improve diabetes self-care and related outcomes. This study describes our first steps in piloting a patient-specific diabetes educational intervention, as opposed to the current “one size fits all” approach.

People with chronic kidney disease (CKD) are at risk for adverse events and/or CKD progression with use of renally eliminated or nephrotoxic medications. To examine the prevalence of potentially inappropriate medication (PIM) use by U.S. adults by CKD stage and self-reported CKD awareness. Cross-sectional analysis of National Health and Nutrition Examination Surveys, 2011–2016 Non-pregnant adults with stages 3a (eGFR 45–59 mL/min/1.73 m2), 3b (eGFR 30–44), or 4–5 (eGFR < 30) CKD, stratified as CKD-aware/unaware. PIMs were identified on the basis of KDIGO guidelines, label information, and literature review. We calculated proportions using any and individual PIMs, assessing for differences over CKD awareness within each CKD stage. Analyses were adjusted for age, sex, race/ethnicity, education, comorbidities, and insurance type. Adjusted proportions of U.S. adults taking any PIM(s) exceeded 50% for all CKD stages and awareness categories, and were highest among CKD-unaware patients with stages 4–5 CKD: 66.6% (95% CI, 55.5–77.8). Proton pump inhibitors, opioids, metformin, sulfonylureas, and non-steroidal anti-inflammatory drugs (NSAIDs) were all used frequently across CKD stages. NSAIDs were used less frequently when CKD-aware by patients with stage 3a CKD (2.2% [95% CI, − 0.3 to 4.7] vs. 10.7% [95% CI, 7.6 to 13.8]) and stages 4–5 CKD (0.8% [95% CI, − 0.9 to 2.5] vs. 16.5% [95% CI, 4.0 to 29.0]). Metformin was used less frequently when CKD-aware by patients with stage 3b CKD (8.1% [95% CI, 0.3–15.9] vs. 26.5% [95% CI, 17.4–35.7]) and stages 4–5 CKD (none vs. 20.8% [95% CI, 1.8–39.8]). The impact of CKD awareness was statistically significant after correction for multiple comparisons only for NSAIDs in stage 3a CKD. PIMs are frequently used by people with CKD, with some impact of CKD awareness on NSAID and metformin use. This may lead to adverse outcomes or hasten CKD progression, reinforcing the need for improved medication management among people with CKD.

Background: High-quality diabetes care is evidence-based, timely, and equitable. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are the most recently approved class of glucose-lowering medications with additional cardio- and renal-protective benefits and low risk of hypoglycemia. Cardiovascular and kidney disease are among the most common chronic diabetes complications, whereas hypoglycemia is the most prevalent adverse effect of glucose-lowering therapy. We examine the sociodemographic and clinical factors associated with early SGLT2i initiation and appropriateness of use based on contemporaneous scientific evidence. Materials and Methods: Retrospective analysis of medical and pharmacy claims data from OptumLabs(®) Data Warehouse for commercially insured and Medicare Advantage adult beneficiaries with diabetes types 1 and 2, who filled any glucose-lowering medication between January 1, 2013 and December 31, 2016. Demographic (age, sex, race, income), clinical (comorbidities), and insurance-related factors affecting first prescription for a SGLT2i were examined using multivariable logistic regression. Results: Among 1,054,727 adults with pharmacologically treated diabetes, 7.2% (n = 75,500) initiated a SGLT2i. Patients with prior myocardial infarction (MI) (odds ratio [OR]: 0.94, 95% confidence interval [CI]: 0.91–0.96), heart failure (HF) (OR: 0.93, 95% CI: 0.91–0.94), kidney disease (OR: 0.80, 95% CI: 0.78–0.81), and severe hypoglycemia (OR: 0.96, 95% CI: 0.94–0.98) were all less likely to start a SGLT2i; P

In times of crisis, rapid deployment of clinical resources to under-served areas/populations is needed, particularly in the absence of an established health care infrastructure. The COVID-19 pandemic exposed profound gaps in care for people experiencing homelessness.1-3 A Mobile COVID-19 Unit was

OBJECTIVE We characterized annual trends of severe hypoglycemic and hyperglycemic crises (diabetic ketoacidosis/hyperglycemic hyperosmolar state) in patients with diabetes and end-stage kidney disease (ESKD). RESEARCH DESIGN AND METHODS This was a nationwide, retrospective study of adults (≥18 years old) with diabetes/ESKD, from the United States Renal Data System registry, between 2013 and 2017. Primary outcome was annual rates of emergency department visits or hospitalizations for hypoglycemic and hyperglycemic crises, reported as number of events/1,000 person-years. Event rates and risk factors were adjusted for patient age, sex, race/ethnicity, dialysis modality, comorbidities, treatment regimen, and U.S. region. RESULTS Among 521,789 adults with diabetes/ESKD (median age 65 years [interquartile range 57–73], 56.1% male, and 46% White), overall adjusted rates of hypoglycemic and hyperglycemic crises were 53.64 and 18.24 per 1,000 person-years, respectively. For both hypoglycemia and hyperglycemia crises, respectively, the risks decreased with age and were lowest in older patients (≥75 vs. 18–44 years old: incidence rate ratio 0.35, 95% CI 0.33–0.37, and 0.03, 0.02–0.03), women (1.09, 1.06–1.12, and 1.44, 1.35–1.54), and those with smoking (1.36, 1.28–1.43, and 1.71, 1.53–1.91), substance abuse (1.27, 1.15–1.42, and 1.53, 1.23–1.9), retinopathy (1.10, 1.06–1.15, and 1.36, 1.26–1.47), and insulin therapy (vs. no therapy; 0.60, 0.59–0.63, and 0.44, 0.39–0.48). For hypoglycemia, specifically, additional risk was conferred by Black race (1.11, 1.08–1.15) and amputation history (1.20, 1.13–1.27). CONCLUSIONS In this nationwide study of patients with diabetes/ESKD, hypoglycemic crises were threefold more common than hyperglycemic crises, greatly exceeding national reports in nondialysis patients with chronic kidney disease. Young, Black, and female patients were disproportionately affected.

More than one in 10 Americans today are living with diabetes (1). To prevent acute and chronic complications of diabetes, including death, patients with diabetes often require multiple medications and medication management supplies to enable effective, safe, and evidence-based control of hyperglycemia. These include insulin and noninsulin medications, technologies for glucose monitoring, and equipment for administration of injectable medications (both insulin and noninsulin injectables). Management of hyperglycemia is increasingly expensive for patients and the health care system, having increased 240% from the period 2005–2007 to 2015–2017, from $16.9 billion to $57.6 billion annually (2). Although the majority of these costs are borne by public and private payers (2), patients and caregivers increasingly report cost-related distress, nonadherence, and adverse health outcomes stemming from the costs of managing their disease (3–5). It is therefore vital for primary care clinicians, who care for the majority of people with diabetes (6), to be cognizant of the financial impact of diabetes management on their patients and to reduce it as much as possible. Insulin is just one component of comprehensive diabetes care, but it is the most critical for people who require it to live (i.e., people with type 1 diabetes and some with longstanding type 2 diabetes). In 2018, 18.6% of U.S. adults with diabetes were treated with insulin alone, and an additional 15.1% were treated with insulin and noninsulin glucose-lowering medications (7). The average list price of insulin in the United States rose by 15–17% each year between 2012 and 2016 (8). The greatest increase in insulin-related costs stems from greater use, and higher per-unit costs, of analog insulins (2). New insulin products such as ultra-long-acting or ultra-rapid-acting insulins offer important clinical and safety advantages to certain patients; however, these formulations are among the most expensive to obtain. Between the …

Key Points Question Can real-world data regarding the use of degarelix and leuprolide be used to emulate the forthcoming PRONOUNCE trial, a phase 3b trial comparing the cardiovascular safety of degarelix vs leuprolide among patients with prostate cancer and cardiovascular disease? Findings In this cohort study of 2226 propensity score–matched men with prostate cancer taking degarelix or leuprolide, no significant difference was observed in the risk of a major adverse cardiovascular event. Meaning These findings suggest that real-world data are increasingly available and useful for medical product evaluation, including for emulating clinical trials to understand products’ use in clinical practice and the associated benefits and harms of treatment., This cohort study uses electronic health record and administrative claims data to emulate the ongoing PRONOUNCE trial, which compares the cardiovascular safety of degarelix and leuprolide in men with cardiovascular disease and advanced prostate cancer., Importance With a growing interest in the use of real-world evidence for regulatory decision-making, it is important to understand whether real-world data can be used to emulate the results of randomized clinical trials. Objective To use electronic health record and administrative claims data to emulate the ongoing PRONOUNCE trial (A Trial Comparing Cardiovascular Safety of Degarelix Versus Leuprolide in Patients With Advanced Prostate Cancer and Cardiovascular Disease). Design, Setting, and Participants This retrospective, propensity-matched cohort study included adult men with a diagnosis of prostate cancer and cardiovascular disease who initiated either degarelix or leuprolide between December 24, 2008, and June 30, 2019. Participants were commercially insured individuals and Medicare Advantage beneficiaries included in a large US administrative claims database. Exposures Degarelix or leuprolide. Main Outcomes and Measures The primary end point was time to first occurrence of a major adverse cardiovascular event (MACE), defined as death due to any cause, myocardial infarction, or stroke, analogous to the PRONOUNCE trial. Secondary end points were time to death due to any cause, myocardial infarction, stroke, and angina. Cox proportional hazards regression was used to evaluate primary and secondary end points. Results A total of 32 172 men initiated degarelix or leuprolide for prostate cancer; of them, 9490 (29.5%) had cardiovascular disease, and 7800 (24.2%) met the PRONOUNCE trial eligibility criteria and were included in this study. Overall, 165 participants (2.1%) were Asian, 1390 (17.8%) were Black, 663 (8.5%) were Hispanic, and 5258 (67.4%) were White. The mean (SD) age was 74.4 (7.4) years. Among 2226 propensity score–matched patients, no significant difference was observed in the risk of MACE for patients taking degarelix vs those taking leuprolide (10.18 vs 8.60 events per 100 person-years; hazard ratio [HR], 1.18; 95% CI, 0.86-1.61). Degarelix was associated with a higher risk of death from any cause (HR, 1.48; 95% CI, 1.01-2.18) but not of myocardial infarction (HR, 1.16; 95% CI, 0.60-2.25), stroke (HR, 0.92; 95% CI, 0.45-1.85), or angina (HR, 1.36; 95% CI, 0.43-4.27). Conclusions and Relevance In this emulation of a clinical trial of men with cardiovascular disease undergoing treatment for prostate cancer, degarelix was not associated with a lower risk of cardiovascular events than leuprolide. Comparison of these data with PRONOUNCE trial results, when published, will help enhance our understanding of the appropriate role of using real-world data to emulate clinical trials.

Key Points Question What factors are associated with the occurrence of hyperglycemic crises (diabetic ketoacidosis and hyperglycemic hyperosmolar state) among adults with diabetes? Findings In this cohort study of 816 538 adults with diabetes in the US (20 156 adults with type 1 diabetes and 796 382 with type 2 diabetes), younger age, low income, Black race/ethnicity, high hemoglobin A1c level, prior hyperglycemic crises, severe hypoglycemia, depression, neuropathy, and nephropathy were associated with increased risk of hyperglycemic crises in both groups. Meaning The findings suggest that multidisciplinary interventions focusing on groups at high risk of hyperglycemic crises are needed to decrease the incidence and impact of these potentially preventable complications of diabetes., Importance Hyperglycemic crises (ie, diabetic ketoacidosis [DKA] and hyperglycemic hyperosmolar state [HHS]) are life-threatening acute complications of diabetes. Efforts to prevent these events at the population level have been hindered by scarce granular data and difficulty in identifying individuals at highest risk. Objective To assess sociodemographic, clinical, and treatment-related factors associated with hyperglycemic crises in adults with type 1 or type 2 diabetes in the US from 2014 to 2020. Design, Setting, and Participants This retrospective cohort study analyzed administrative claims and laboratory results for adults (aged ≥18 years) with type 1 or type 2 diabetes from the OptumLabs Data Warehouse from January 1, 2014, through December 31, 2020. Main Outcomes and Measures Rates of emergency department or hospital visits with a primary diagnosis of DKA or HHS (adjusted for age, sex, race/ethnicity, and region, and for year when calculating annualized rates) were calculated separately for patients with type 1 diabetes and type 2 diabetes. The associations of sociodemographic factors (age, sex, race/ethnicity, region, and income), clinical factors (comorbidities), and treatment factors (glucose-lowering medications, hemoglobin A1c) with DKA or HHS in patients with type 1 or type 2 diabetes were assessed using negative binomial regression. Results Among 20 156 adults with type 1 diabetes (mean [SD] age, 46.6 [16.5] years; 51.2% male; 72.6% White race/ethnicity) and 796 382 with type 2 diabetes (mean [SD] age, 65.6 [11.8] years; 50.3% female; 54.4% White race/ethnicity), adjusted rates of hyperglycemic crises were 52.69 per 1000 person-years (95% CI, 48.26-57.12 per 1000 person-years) for type 1 diabetes and 4.04 per 1000 person-years (95% CI, 3.88-4.21 per 1000 person-years) for type 2 diabetes. In both groups, factors associated with the greatest hyperglycemic crisis risk were low income (≥$200 000 vs, This cohort study uses administrative claims and laboratory results from a nationwide database to assess the sociodemographic, clinical, and treatment-related factors associated with diabetic ketoacidosis and hyperglycemic hyperosmolar states among adults with type 1 or type 2 diabetes in the US from 2014 to 2020.

Visual Abstract, The vast majority of patients (>99%) with severe acute respiratory syndrome coronavirus 2 survive immediate infection but remain at risk for persistent and/or delayed multisystem. This review of published reports through May 31, 2021, found that manifestations of postacute sequelae of severe acute respiratory syndrome coronavirus 2 infection (PASC) affect between 33% and 98% of coronavirus disease 2019 survivors and comprise a wide range of symptoms and complications in the pulmonary, cardiovascular, neurologic, psychiatric, gastrointestinal, renal, endocrine, and musculoskeletal systems in both adult and pediatric populations. Additional complications are likely to emerge and be identified over time. Although data on PASC risk factors and vulnerable populations are scarce, evidence points to a disproportionate impact on racial/ethnic minorities, older patients, patients with preexisting conditions, and rural residents. Concerted efforts by researchers, health systems, public health agencies, payers, and governments are urgently needed to better understand and mitigate the long-term effects of PASC on individual and population health.

Severe hypoglycemia and hyperglycemia in diabetes management are dangerous yet potentially preventable. Data on contemporary trends of these events, mortality following their occurrence, and potential racial/ethnic disparities are limited. We used claims data from OptumLabs Data Warehouse to 1) examine rates of hypoglycemic and hyperglycemic emergencies among U.S. adults with diabetes between 2009 and 2018; 2) quantify 30-day and 1-year all-cause mortality after these events adjusted for age, sex, race/ethnicity, and U.S. region; and 3) assess for disparities by race/ethnicity. Among 3,709,936 adults with diabetes (age 60.2 [SD, 13.7] years, 49.2% female, 58.5% White), the adjusted rate of hypoglycemic emergencies per 1000 person-years decreased by 41% from 2009 to 2018, from 16.2 (95% CI, 15.8-16.6) to 9.6 (9.4-9.8). The adjusted rate of hyperglycemic emergencies increased by 24%, from 4.6 (4.5-4.8) to 5.7 (5.6-5.9). Black patients had the highest risk of both events compared to Whites, with RR 1.7 (1.7-1.8) for hypoglycemic and 1.5 (1.4-1.5) for hyperglycemic emergencies. All-cause 30-day and 1-year mortality did not change over time. In 2018, 30-day adjusted mortality was 1.6% (1.4-1.8) and 1.3% (1.1-1.5) after hypoglycemic and hyperglycemic emergencies, respectively, while 1-year mortality was 10.3% (9.8-10.9) and 4.7% (4.2-5.2). The risks of 30-day and 1-year mortality after hypoglycemic emergencies were lower among Black (OR 0.85 [0.76-0.96] and OR 0.91 [0.87-0.96], respectively) and Hispanic (OR 0.81 [0.68-0.97] and OR 0.70 [0.64-0.76]) patients compared to Whites. There was no association between race/ethnicity and 30-day mortality after hyperglycemic emergencies, while the risk of 1-year mortality was lower among Hispanic patients (OR 0.73 [0.63, 0.85]) compared to Whites. New strategies are needed to prevent hypoglycemic and hyperglycemic emergencies among people with diabetes, particularly among racial/ethnic minorities. Disclosure R. G. Mccoy: None. K. Swarna: None. R. J. Galindo: Consultant; Self; Abbott Diabetes, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk, Sanofi US, Valeritas, Inc., Research Support; Self; Dexcom, Inc., Novo Nordisk. H. Van houten: None. P. J. O’connor: None. N. Shah: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K23DK114497)

Hyperglycemic emergencies are life-threatening acute complications of diabetes. Efforts to prevent these events on the population level are hindered by inability to proactively identify those at highest risk. In this retrospective analysis of claims data of adults with type 1 and type 2 diabetes from OptumLabs Data Warehouse between 2014 and 2019, we calculated the adjusted (for age, sex, race/ethnicity, U.S. region) rates of hyperglycemic emergencies and examined their association with sociodemographic (age, sex, race/ethnicity, income), clinical (comorbidities), and treatment (diabetes medications, HbA1c level) factors using negative binomial regression. Among 16,621 adults with type 1 diabetes (age 46.7 [SD, 16.5] years, 48.9% female, 74.6% White) and 615,371 with type 2 diabetes (age 65.5 [SD, 11.9] years, 50.1% female, 56.4% White), adjusted rates of hyperglycemic emergencies were 47.8 (95% CI 43.9-52.0) and 3.7 (95% CI 3.5-3.8) per 1000 person-years, respectively. Table shows model results. Younger age, lower income, higher HbA1c, prior hyperglycemic and hypoglycemic emergencies, and presence of comorbidities (especially in type 2 diabetes) were associated with heightened risk of hyperglycemic emergencies. Event rates in type 2 diabetes increased over time. Proactive engagement of at-risk patients to address hyperglycemia may prevent these dangerous events. Disclosure R. G. Mccoy: None. K. Swarna: None. R. J. Galindo: Consultant; Self; Abbott Diabetes, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Novo Nordisk, Sanofi US, Valeritas, Inc., Research Support; Self; Dexcom, Inc., Novo Nordisk. H. Van houten: None. P. J. O’connor: None. N. Shah: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K23DK114497)

Objective To estimate the contemporary prevalence of intensive glucose-lowering therapy among US adults with diabetes and model the number of hypoglycemia-related emergency department (ED) visits and hospitalizations that are attributable to such intensive treatment. Patients and Methods US adults with diabetes and glycated hemoglobin (HbA1c) levels less than 7.0% who were included in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2014. Participants were categorized as clinically complex if 75 years or older or with 2 or more activities of daily living limitations, end-stage renal disease, or 3 or more chronic conditions. Intensive treatment was defined as any glucose-lowering medications with HbA1c levels of 5.6% or less or 2 or more with HbA1c levels of 5.7% to 6.4%. First, we quantified the proportion of clinically complex and intensively treated individuals in the NHANES population. Then, we modeled the attributable hypoglycemia-related ED visits/hospitalizations over a 2-year period based on published data for event risk. Results Almost half (48.8% [10,719,057 of 21,980,034]) of US adults with diabetes (representing 10.7 million US adults) had HbA1c levels less than 7.0%. Among them, 32.3% (3,466,713 of 10,719,057) were clinically complex, and 21.6% (2,309,556 of 10,719,057) were intensively treated, with no difference by clinical complexity. Over a 2-year period, we estimated 31,511 hospitalizations and 30,954 ED visits for hypoglycemia in this population; of these, 4774 (95% CI, 954-9714) hospitalizations and 4804 (95% CI, 862-9851) ED visits were attributable to intensive treatment. Conclusion Intensive glucose-lowering therapy, particularly among vulnerable clinically complex adults, is strongly discouraged because it may lead to hypoglycemia. However, intensive treatment was equally prevalent among US adults, irrespective of clinical complexity. Over a 2-year period, an estimated 9578 hospitalizations and ED visits for hypoglycemia could be attributed to intensive diabetes treatment, particularly among clinically complex patients. Patients at risk for hypoglycemia may benefit from treatment deintensification to reduce hypoglycemia risk and treatment burden.

Type 2 diabetes mellitus is a risk factor for incident heart failure and increases the risk of morbidity and mortality in patients with established disease. Secular trends in the prevalence of diabetes mellitus and heart failure forecast a growing burden of disease and underscore the need for effective therapeutic strategies. Recent clinical trials have demonstrated the shared pathophysiology between diabetes mellitus and heart failure, the synergistic effect of managing both conditions, and the potential for diabetes mellitus therapies to modulate the risk of heart failure outcomes. This scientific statement on diabetes mellitus and heart failure summarizes the epidemiology, pathophysiology, and impact of diabetes mellitus and its control on outcomes in heart failure; reviews the approach to pharmacological therapy and lifestyle modification in patients with diabetes mellitus and heart failure; highlights the value of multidisciplinary interventions to improve clinical outcomes in this population; and outlines priorities for future research.

Identifying high-value health care delivery for patients with clinically complex and high-cost conditions is important for future reimbursement models.The objective of this study was to assess the Medicare reimbursement savings of an established palliative care homebound program.This is a retrospective cohort study involving 50 participants enrolled in a palliative care homebound program and 95 propensity-matched control patients at Mayo Clinic in Rochester, Minnesota, between September 1, 2012, and March 31, 2013. Total Medicare reimbursement was compared in the year before enrollment with the year after enrollment for participants and controls.No significant differences were observed in demographic characteristics or prognostic indices between the two groups. Total Medicare reimbursement per program participant the year before program enrollment was $16,429 compared with $14,427 per control patient, resulting in $2004 higher charges per program patient. In 12 months after program enrollment, mean annual payment was $5783 per patient among participants and $22,031 per patient among the matched controls. In the second year, the intervention group had a decrease of $10,646 per patient; the control group had an increase of $7604 per patient. The difference between the participant group and control group was statistically significant (P 0.001) and favored the palliative care homebound program enrollees by $18,251 (95% CI, $11,268-$25,234).The Mayo Clinic Palliative Care Homebound Program reduced annual Medicare expenditures by $18,251 per program participant compared with matched control patients. This supports the role of home-based palliative medicine in delivering high-value care to high-risk older adults.

OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients experience primary or secondary therapeutic failure. We developed machine learning models to predict which patients initially prescribed metformin will achieve and maintain control of their blood glucose after one year of therapy. MATERIALS AND METHODS: We performed a retrospective analysis of administrative claims data for 12,147 commercially-insured adults and Medicare Advantage beneficiaries with prediabetes or diabetes. Several machine learning models were trained using variables available at the time of metformin initiation to predict achievement and maintenance of hemoglobin A(1c) (HbA(1c))

ObjectiveDiagnostic error is a key healthcare concern and can result in substantial morbidity and mortality. Yet no study has investigated the relationship between adverse outcomes resulting from diagnostic errors and one potentially large contributor to these errors: deficiencies in diagnostic knowledge. Our objective was to measure that associations between diagnostic knowledge and adverse outcomes after visits to primary care physicians that were at risk for diagnostic errors.Setting/participants1410 US general internists who recently took their American Board of Internal Medicine Maintenance of Certification (ABIM-IM-MOC) exam treating 42 407 Medicare beneficiaries who experienced 48 632 ‘index’ outpatient visits for new problems at risk for diagnostic error because the presenting problem (eg, dizziness) was related to prespecified diagnostic error sensitive conditions (eg, stroke).Outcome measures90-day risk of all-cause death, and, for outcome conditions related to the index visits diagnosis, emergency department (ED) visits and hospitalisations.DesignUsing retrospective cohort study design, we related physician performance on ABIM-IM-MOC diagnostic exam questions to patient outcomes during the 90-day period following an index visit at risk for diagnostic error after controlling for practice characteristics, patient sociodemographic and baseline clinical characteristics.ResultsRates of 90-day adverse outcomes per 1000 index visits were 7 for death, 11 for hospitalisations and 14 for ED visits. Being seen by a physician in the top versus bottom third of diagnostic knowledge during an index visit for a new problem at risk for diagnostic error was associated with 2.9 fewer all-cause deaths (95% CI −5.0 to −0.7, p=0.008), 4.1 fewer hospitalisations (95% CI −6.9 to −1.2, p=0.006) and 4.9 fewer ED visits (95% CI −8.1% to −1.6%, p=0.003) per 1000 visits.ConclusionHigher diagnostic knowledge was associated with lower risk of adverse outcomes after visits for problems at heightened risk for diagnostic error.

Objective To provide a review of the impact of high deductible health plans (HDHPs) on the utilizations of services required for optimal management of diabetes and subsequent health outcomes. Methods Systematic literature review of studies published between January 1, 2000, and May 7, 2021, was conducted that examined the impact of HDHP on diabetes monitoring (eg, recommended laboratory and surveillance testing), routine care (eg, ambulatory appointments), medication management (eg, medication initiation, adherence), and acute health care utilization (eg, emergency department visits, hospitalizations, incident complications). Results Of the 303 reviewed articles, 8 were relevant. These studies demonstrated that HDHPs lower spending at the expense of reduced high-value diabetes monitoring, routine care, and medication adherence, potentially contributing to the observed increases in acute health care utilization. Additionally, patient out-of-pocket costs for recommended screenings doubled, and total health care expenditures increased by 49.4% for HDHP enrollees compared with enrollees in traditional health plans. Reductions in disease monitoring and routine care and increases in acute health care utilization were greatest in lower-income patients. None of the studies examined the impact of HDHPs on access to diabetes self-management education, technology use, or glycemic control. Conclusion Although HDHPs reduce some health care utilization and costs, they appear to do so at the expense of limiting high-value care and medication adherence. Policymakers, providers, and payers should be more cognizant of the potential for negative consequences of HDHPs on patients’ health.

Rational and objectivePrognosis provides critical knowledge for shared decision making between patients and clinicians. While several prognostic indices for mortality in dialysis patients have been developed, their performance among elderly patients initiating dialysis is unknown, despite great need for reliable prognostication in that context. To assess the performance of 6 previously validated prognostic indices to predict 3 and/or 6 months mortality in a cohort of elderly incident dialysis patients.Study designValidation study of prognostic indices using retrospective cohort data. Indices were compared using the concordance (“c”)-statistic, i.e. area under the receiver operating characteristic curve (ROC). Calibration, sensitivity, specificity, positive and negative predictive values were also calculated.Setting & participantsIncident elderly (age ≥75 years; n = 349) dialysis patients at a tertiary referral center.Established predictorsVariables for six validated prognostic indices for short term (3 and 6 month) mortality prediction (Foley, NCI, REIN, updated REIN, Thamer, and Wick) were extracted from the electronic medical record. The indices were individually applied as per each index specifications to predict 3- and/or 6-month mortality.ResultsIn our cohort of 349 patients, mean age was 81.5±4.4 years, 66% were male, and median survival was 351 days. The c-statistic for the risk prediction indices ranged from 0.57 to 0.73. Wick ROC 0.73 (0.68, 0.78) and Foley 0.67 (0.61, 0.73) indices performed best. The Foley index was weakly calibrated with poor overall model fit (p LimitationsSmall sample size, use of secondary data, need for imputation, homogeneous population.ConclusionMost predictive indices for mortality performed moderately in our incident dialysis population. The Wick and Foley indices were the best performing, but had issues with under and over calibration. More accurate indices for predicting survival in older patients with kidney failure are needed.

ObjectivesDespite increasing focus on individualised diabetes management, current diabetes quality measures are based on meeting generic haemoglobin A1c thresholds and do not reflect considerations of clinical complexity, hypoglycaemic susceptibility or treatment burden. Our team observed a multidisciplinary stakeholder panel tasked with informing an appropriate diabetes therapy indicator (ADTI) and analysed their deliberations, seeking to understand what constitutes appropriate diabetes therapy and how it can be captured using an operational quality indicator. We focused specifically on factors the panel valued in an ideal indicator, how they defined appropriateness and how they thought an indicator of appropriateness could be operationalised.DesignQualitative study examining Delphi panel deliberations as it iteratively refined the ADTI.Participants and methodsThe 12-member panel was comprised of clinicians (endocrinology, primary care, geriatrics), pharmacists, nurses, researchers, and representatives of public and private health plans. It met for four teleconference calls and deliberated asynchronously using semi-structured questionnaires following each call to develop the ADTI. These semistructured questionnaires, as well as the meeting minutes, were then analysed using an inductive thematic approach.ResultsWe identified three themes in panellist discussions that represented the core value systems underpinning the indicator and its formation: (1) promoting individualised, evidence-based and equitable care; (2) balancing autonomy and prescriptiveness in clinical decision-making; and (3) ensuring an accurate, reliable and practical indicator. These three principles were operationalised into definitions of treatment intensity and clinical complexity, and yielded an indicator that participants judged both fair and effective.ConclusionsBetter understanding of what multidisciplinary stakeholders perceive as appropriate diabetes management can help develop quality indicators that are patient-centred, evidence-based, equitable and pragmatic across a range of clinical settings.

The American Diabetes Association recommends that all patients at risk for hypoglycemia be prescribed glucagon. Despite this recommendation, there is evidence that prescription rates are lower than expected for patients with type 1 and type 2 diabetes. This study investigated prescription patterns for glucagon among de-identified administrative claims from OptumLabs® Data Warehouse for prescriptions between January 1, 2014 and December 31, 2014 among pharmacologically treated type 1 and 2 diabetes patients. We find that glucagon was rarely filled by patients with type 1 and type 2 diabetes, including fewer than 5% of patients with prior hypoglycemia requiring emergency healthcare utilization. Among patients with type 1 diabetes, glucagon fills were unpredictable and not targeted to highest risk patients.

IntroductionObservational studies constitute an important evidence base for hypoglycemia in diabetes management. This requires consistent and reliable ascertainment and reporting methodology, particularly in studies of type 2 diabetes where hypoglycemia risk is heterogeneous. Therefore, we aimed to examine the definitions of hypoglycemia used by observational studies of patients with type 2 diabetes.Research design and methodsWe conducted a meta-epidemiological review of observational studies reporting on hypoglycemia or evaluating glucose-lowering medications in adults with type 2 diabetes. MEDLINE and Google Scholar were searched from January 1970 to May 2018. The definitions of non-severe, severe and nocturnal hypoglycemia were examined.ResultsWe reviewed 243 studies: 47.7% reported on non-severe hypoglycemia, 77.8% on severe hypoglycemia and 16.9% on nocturnal hypoglycemia; 5.8% did not specify. Among 116 studies reporting non-severe hypoglycemia, 18.1% provided no definition, 23.3% used glucose values, 38.8% relied on patient-reported symptoms, 17.2% accepted either glucose values or patient-reported symptoms and 2.6% relied on International Classification of Disease (ICD) codes. Among 189 studies reporting severe hypoglycemia, 11.1% provided no definition, 53.4% required symptoms needing assistance, 3.7% relied on glucose values, 14.8% relied on ICD codes, 2.6% relied on ICD codes or glucose values and 15.9% required both symptoms needing assistance and glucose values. Overall, 38.2% of non-severe and 67.7% of severe hypoglycemia definitions were consistent with the International Hypoglycemia Study Group.ConclusionsThe marked heterogeneity in how hypoglycemia is defined in observational studies may contribute to the inadequate understanding and correction of hypoglycemia risk factors among patients with type 2 diabetes.

Three new classes of glucose-lowering drugs were introduced into practice over the past 15 years: DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors. These drugs have low hypoglycemia risk, do not cause weight gain, and post-marketing outcomes trials found cardiovascular and renal benefits associated with GLP-1RA and SGLT2i use. Our objective was to determine whether these drugs are being used by patients with type 2 diabetes most likely to benefit from them. Using OptumLabs Data Warehouse, a de-identified dataset of commercially-insured and Medicare Advantage beneficiaries, we identified adults with type 2 diabetes who first started a DPP-4i (n=140,933), GLP-1RA (n=107,331), SGLT2i (n=112,892), or any other diabetes drug (n=1,743,484) between 2013-2018. After adjustment for age, gender, race/ethnicity, insurance type, baseline medications, year, prescriber specialty, and comorbidities, we found that GLP-1RA and SGLT2i, in particular, were less likely to be started by patients most likely to benefit from them. GLP-1RA initiation was less likely among patients with prior hypoglycemia requiring ED/hospital care (OR 0.86 [95% CI 0.79-0.93]), myocardial infarction (MI; OR 0.93 [0.89-0.97], or stroke (OR 0.88 [0.85-0.91]), though more likely with nephropathy (OR 1.20 [1.17-1.23]). SGLT2i initiation was less likely with prior hypoglycemia (OR 0.81 [0.73-0.89]), nephropathy (OR 0.80 [0.78-0.0.82]), or heart failure (HF; OR 0.85 [0.82-0.87]). However, DPP-4i initiation was more likely with prior hypoglycemia (OR 1.49 [1.41-1.57]), MI (OR 1.09 [1.05-1.12]), stroke (OR 1.09 [1.06-1.11), HF (OR 1.12 [1.09-1.14]), and nephropathy (OR 1.40 [1.37-1.43]). Our results do not explain why these drugs are not preferentially used in guideline-recommended contexts, but do highlight missed opportunities to reduce the morbidity and mortality associated with hypoglycemia, cardiovascular disease, and kidney disease in highest risk patients. Disclosure R.G. McCoy: None. H. Van Houten: None. J. Ross: Research Support; Self; Centers for Medicare and Medicaid Services, Janssen Pharmaceuticals, Inc., U.S. Food and Drug Administration. P. Karaca-Mandic: None. V.M. Montori: None. N. Shah: None. Funding National Institutes of Health (K23DK114497); Agency for Healthcare Research and Quality (1U19HS024075, R01HS025164)

Glycemic management in patients with diabetes and end-stage renal disease (ESRD) is challenging. There is limited evidence about the incidence of severe hypoglycemia and hyperglycemia in this population. Here, we examine rates of emergency department visits and hospitalizations for severe hypoglycemia and hyperglycemia (ascertained using validated ICD-9/10 codes) in a national cohort of adults with diabetes and incident ESRD, included in the United States Renal Data System, between 2010-2015. We then examine risk factors for these events using logistic regression. Among 678,376 patients with ESRD, 59.5% (n=403,490) had diabetes (63.6±13.0 years, 56.4% male, 26.8% Black, and 18.0% Hispanic). Rates of severe hypoglycemia and hyperglycemia were 126.2 and 35.5 per 1000 person-years, respectively. Strongest risk factors for hypoglycemia were insulin therapy (OR 4.5 [95% CI, 4.4-4.6] vs. no medications) and non-insulin diabetes medications (OR 3.7 [3.6-3.8]); Black race (OR 1.3 [1.3-1.4] vs. Caucasian); older age: 65-74 years (OR 1.2 [1.1-1.3] and ≥75 years OR 1.1 [1.1-1.1] vs. 18-44 years); and history of amputation (OR 1.4 [1.4-1.5]) or retinopathy (OR 1.2 [1.2-1.3]). Strongest risk factors for hyperglycemia were insulin (OR 7.7 [7.4-8.2]) and non-insulin diabetes medication use (OR 2.8 [2.6-3.1]) and retinopathy (OR 1.5 [1.4-1.5]). Older age was protective for hyperglycemia (OR 0.1 [0.1-0.1] for age ≥75 and 0.2 [0.2-0.2] for age 65-74 vs. 18-44 years). Patients on peritoneal dialysis had a lower risk (OR 0.8 [0.8-0.9]) of hypoglycemia, but no difference in odds of hyperglycemia, compared to patients on hemodialysis. Hypoglycemia requiring ED/hospital care was 3.6-fold more prevalent than severe hyperglycemia, greatly exceeding rates previously reported for older adults and those with non-end stage chronic kidney disease. There is a critical need for proactive interventions to reduce hypoglycemia and related ED/hospital use in this high-risk population. Disclosure R.J. Galindo: Advisory Panel; Self; Lilly Diabetes. Consultant; Self; Valeritas, Inc. Research Support; Self; Novo Nordisk Inc. Other Relationship; Self; UpToDate. M.K. Ali: Research Support; Self; Merck & Co., Inc. N. Shah: None. S. Funni: None. G.E. Umpierrez: None. R.G. McCoy: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (P30DK111024)

Three new classes of glucose-lowering drugs were introduced into practice over the past 15 years. DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors have low hypoglycemia risk, do not cause weight gain, and GLP-1RA and SGLT2i have additional cardiovascular and renal benefits. We previously found low rates of early SGLT2i use by women and black patients, but more recent data and data for other drugs were lacking. Using OptumLabs Data Warehouse, a de-identified dataset of commercially-insured and Medicare Advantage beneficiaries, we identified adults with type 2 diabetes who first started a DPP-4i (n=140,933), GLP-1RA (n=107,331), SGLT2i (n=112,892), or any other diabetes drug (n=1,743,484) between 2013-2018. Odds of starting each medication class were examined in separate logistic regression models for white women (WW), non-white men (NM), and non-white women (NW) compared to white men, adjusting for other factors affecting drug choice (Figure). Results were mixed, as depicted by the Figure. Our study design cannot identify the causes of preferential use of DPP-4i among non-white patients, or the preferential avoidance of SGLT2i among women and NM and of GLP-1RA among NW. Because these drugs have important safety and efficacy benefits, our findings call for closer examination of potential implicit biases surrounding medication prescribing and diabetes management. Disclosure R.G. McCoy: None. H. Van Houten: None. S.M. Dunlay: None. X. Yao: None. T. Dempsey: None. P. Noseworthy: None. L.R. Sangaralingham: None. A.H. Limper: None. N. Shah: None. Funding National Institutes of Health (K23DK114497)

DPP-4 inhibitors, GLP-1 receptor agonists, and SGLT2 inhibitors have low hypoglycemia risk, do not cause weight gain, and post-marketing outcomes trials found cardiovascular and renal benefits with GLP-1RA and SGLT2i use. Using 2013-2016 data, we previously found low and delayed early adoption of SGLT2i among Medicare Advantage (MA) beneficiaries compared to commercial beneficiaries, despite similar formulary coverage. With greater experience using these medications and emerging evidence supporting their preferred use by patients with comorbidities, prescribing patterns may have changed. Using OptumLabs Data Warehouse, a de-identified dataset of commercial and MA beneficiaries, we examined the proportions of pharmacologically-treated adults with type 2 diabetes with commercial vs. MA insurance who filled a DPP-4i, GLP-1RA, or SGLT2i each quarter between 2013-2018. We found significant differences across medications and health plans (Figure). Overall, after adjusting for age, gender, race/ethnicity, baseline medications, year, prescriber specialty, and comorbidities, the odds of DPP-4i, GLP-1RA, and SGLT2i use were significantly lower for MA vs. commercial beneficiaries: OR 0.61 (95% CI 0.60-0.63), 0.45 (95% CI 0.44-0.46), and 0.31 (95% CI 0.30-0.31), respectively. These findings call for better understanding of non-clinical factors contributing to treatment decisions. Disclosure R.G. McCoy: None. H. Van Houten: None. J. Ross: Research Support; Self; Centers for Medicare and Medicaid Services, Janssen Pharmaceuticals, Inc., U.S. Food and Drug Administration. P. Karaca-Mandic: None. V.M. Montori: None. N. Shah: None. Funding National Institutes of Health (K23DK114497); Agency for Healthcare Research and Quality (1U19HS024075, R01HS025164)

The rising cost of managing diabetes is of major concern. To examine trends in expenditures on diabetes drugs, we used OptumLabs Data Warehouse to identify commercially insured and Medicare Advantage enrollees with type 2 diabetes who filled ≥1 diabetes drug between 2006 and 2018. In each year, we examined mean health plan and patient out of pocket (OOP) spending, stratified by health plan (commercial vs. Medicare Advantage), for generic vs. brand, and for insulin vs. non-insulin drugs. We assessed trends using logistic regression. All costs were adjusted to 2018 U.S. dollars. 1,592,663 unique type 2 diabetes patients were included (commercially-insured: 698,725, Medicare Advantage: 893,938). Total mean diabetes drug expenditures increased among all patients (Figure). Among commercially insured patients, OOP spending increased for brand drugs and insulin but decreased for generics (p for trends Disclosure K.J. Lipska: None. R.G. McCoy: None. H. Van Houten: None. X. Yao: None. J. Ross: Research Support; Self; Centers for Medicare and Medicaid Services, Janssen Pharmaceuticals, Inc., U.S. Food and Drug Administration. A.E. Altan: None. N. Shah: None.

Approximately half of all people with diabetes develop diabetic peripheral neuropathy (DPN) and half experience pain. Guidelines recommend pregabalin, gabapentin, and duloxetine (a selective norepinephrine and serotonin reuptake inhibitor [SNRI]) due to their demonstrated efficacy and safety. Topical analgesics, tricyclic anti-depressants (TCA), and anti-convulsants may also be used. Opioids are discouraged due to lack of effectiveness, risk of addiction, and safety concerns. To promote safe evidence-based pain management, we examined pain medication use by adults diagnosed with DPN between 2002-2019 in an integrated healthcare system across 5 states. We identified 13,815 adults with newly diagnosed DPN; mean age 66 (SD, 13) years, 42% female, 93% white, 29% insulin-treated. Overall, 56% received a pain medication from DPN diagnosis (1 month prior or continued from baseline) to 2 years later. Limiting to treatment pathways observed in ≥1% of cases, opioids were the most used 1st line medication, followed by gabapentin and others (Figure). Opioids and gabapentin were also the most prevalent 2nd line drugs. High rates of opioid use by patients with DPN, a life-long pain syndrome, are concerning particularly as safer effective treatment options are available. Further research is needed to identify drivers of opioid use and barriers to evidence-based alternatives, and develop interventions to improve DPN management in clinical practice. Disclosure J. Fan: None. M.M. Jeffery: None. W. Hooten: None. N. Shah: None. R.G. McCoy: None. Funding National Institutes of Health (K23DK114497)

IntroductionGlycemic targets and glucose-lowering regimens should be individualized based on multiple factors, including the presence of comorbidities. We examined contemporary patterns of glycemic control and use of medications known to cause hypoglycemia among adults with diabetes across age and multimorbidity.Research design and methodsWe retrospectively examined glycosylated hemoglobin (HbA1c) levels and rates of insulin/sulfonylurea use as a function of age and multimorbidity using administrative claims and laboratory data for adults with type 2 diabetes included in OptumLabs Data Warehouse, 1 January 2014 to 31 December 2016. Comorbidity burden was assessed by counts of any of 16 comorbidities specified by guidelines as warranting relaxation of HbA1c targets, classified as being diabetes concordant (diabetes complications or risk factors), discordant (unrelated to diabetes), or advanced (life limiting).ResultsAmong 194 157 patients with type 2 diabetes included in the study, 45.2% had only concordant comorbidities, 30.6% concordant and discordant, 2.7% only discordant, and 13.0% had ≥1 advanced comorbidity. Mean HbA1c was 7.7% among 18–44 year-olds versus 6.9% among ≥75 year-olds, and was higher among patients with comorbidities: 7.3% with concordant only, 7.1% with discordant only, 7.1% with concordant and discordant, and 7.0% with advanced comorbidities compared with 7.4% among patients without comorbidities. The odds of insulin use decreased with age (OR 0.51 (95% CI 0.48 to 0.54) for age ≥75 vs 18–44 years) but increased with accumulation of concordant (OR 5.50 (95% CI 5.22 to 5.79) for ≥3 vs none), discordant (OR 1.72 (95% CI 1.60 to 1.86) for ≥3 vs none), and advanced (OR 1.45 (95% CI 1.25 to 1.68) for ≥2 vs none) comorbidities. Conversely, sulfonylurea use increased with age (OR 1.36 (95% CI 1.29 to 1.44) for age ≥75 vs 18–44 years) but decreased with accumulation of concordant (OR 0.76 (95% CI 0.73 to 0.79) for ≥3 vs none), discordant (OR 0.70 (95% CI 0.64 to 0.76) for ≥3 vs none), but not advanced (OR 0.86 (95% CI 0.74 to 1.01) for ≥2 vs none) comorbidities.ConclusionsThe proportion of patients achieving low HbA1c levels was highest among older and multimorbid patients. Older patients and patients with higher comorbidity burden were more likely to be treated with insulin to achieve these HbA1c levels despite potential for hypoglycemia and uncertain long-term benefit.

Background Chronic pain affects more than 20% of adults in the United States and is associated with substantial physical, mental, and social burden. Clinical text contains rich information about chronic pain, but no systematic appraisal has been performed to assess the electronic health record (EHR) narratives for these patients. A formal content analysis of the unstructured EHR data can inform clinical practice and research in chronic pain. Objective We characterized individual episodes of chronic pain by annotating and analyzing EHR notes for a stratified cohort of adults with known chronic pain. Methods We used the Rochester Epidemiology Project infrastructure to screen all residents of Olmsted County, Minnesota, for evidence of chronic pain, between January 1, 2005, and September 30, 2015. Diagnosis codes were used to assemble a cohort of 6586 chronic pain patients; people with cancer were excluded. The records of an age- and sex-stratified random sample of 62 patients from the cohort were annotated using an iteratively developed guideline. The annotated concepts included date, location, severity, causes, effects on quality of life, diagnostic procedures, medications, and other treatment modalities. Results A total of 94 chronic pain episodes from 62 distinct patients were identified by reviewing 3272 clinical notes. Documentation was written by clinicians across a wide spectrum of specialties. Most patients (40/62, 65%) had 1 pain episode during the study period. Interannotator agreement ranged from 0.78 to 1.00 across the annotated concepts. Some pain-related concepts (eg, body location) had 100% (94/94) coverage among all the episodes, while others had moderate coverage (eg, effects on quality of life) (55/94, 59%). Back pain and leg pain were the most common types of chronic pain in the annotated cohort. Musculoskeletal issues like arthritis were annotated as the most common causes. Opioids were the most commonly captured medication, while physical and occupational therapies were the most common nonpharmacological treatments. Conclusions We systematically annotated chronic pain episodes in clinical text. The rich content analysis results revealed complexity of the chronic pain episodes and of their management, as well as the challenges in extracting pertinent information, even for humans. Despite the pilot study nature of the work, the annotation guideline and corpus should be able to serve as informative references for other institutions with shared interest in chronic pain research using EHRs.

Severe hypoglycemia in patients with diabetes is an adverse drug event that is associated with poor outcomes, such as cardiovascular events, falls, high rehospitalization rates, and increased mortality (1,2). Several strategies, including adjustment of glucose-lowering therapy and glycemic targets, have been recommended in patients with severe hypoglycemia (1,3). However, it is not clear how changes in diabetes management are maintained after severe hypoglycemia among patients with type 2 diabetes. We conducted a retrospective analysis of data from the OptumLabs Data Warehouse, a de-identified administrative claims database of over 200 million individuals enrolled in commercial and Medicare Advantage plans across the U.S. (4). Data were accessed in adherence with the Health Insurance Portability and Accountability Act of 1996, and the Yale School of Medicine Human Investigations Committee deemed the study exempt from institutional review board review. We included commercially insured or Medicare Advantage beneficiaries who were aged 18 years or older, had pharmacologically treated type 2 diabetes, and had a severe hypoglycemic event. Severe hypoglycemia was identified as the first event during an observation window of 1 July 2013 through 30 June 2014, based on primary/principal diagnosis codes for hypoglycemia from an emergency department visit, observation stay, or hospital …

The prevalence of nonalcoholic fatty liver disease (NAFLD) is increasing. The health care burden resulting from the multidisciplinary management of this complex disease is unknown. We assessed the total health care cost and resource utilization associated with a new NAFLD diagnosis, compared with controls with similar comorbidities. We used OptumLabs Data Warehouse, a large national administrative claims database with longitudinal health data of over 100 million individuals enrolled in private and Medicare Advantage health plans. We identified 152,064 adults with a first claim for NAFLD between 2010 and 2014, of which 108,420 were matched 1:1 by age, sex, metabolic comorbidities, length of follow-up, year of diagnosis, race, geographic region, and insurance type to non-NAFLD contemporary controls from the OptumLabs Data Warehouse database. Median follow-up time was 2.6 (range 1-6.5) years. The final study cohort consisted of 216,840 people with median age 55 (range 18-86) years, 53% female, 78% white. The total annual cost of care per NAFLD patient with private insurance was $7,804 (interquartile range [IQR] $3,068-$18,688) for a new diagnosis and $3,789 (IQR $1,176-$10,539) for long-term management. These costs are significantly higher than the total annual costs of $2,298 (IQR $681-$6,580) per matched control with similar metabolic comorbidities but without NAFLD. The largest increases in health care utilization that may account for the increased costs in NAFLD compared with controls are represented by liver biopsies (relative risk [RR] = 55.00, 95% confidence interval [CI] 24.48-123.59), imaging (RR = 3.95, 95% CI 3.77-4.15), and hospitalizations (RR = 1.87, 95% CI 1.73-2.02). Conclusion: The costs associated with the care for NAFLD independent of its metabolic comorbidities are very high, especially at first diagnosis. Research efforts shouldfocus on identification of underlying determinants of use, sources of excess cost, and development of cost-effective diagnostic tests.

Collaborative practice models such as the Chronic Care Model are particularly relevant for integrated health care delivery systems, accountable care organizations, and patient-centered medical homes, which focus on improving population health and reducing costs of care.1,2 Our team has developed an

ObjectiveActivin A, an inflammatory mediator implicated in cellular senescence-induced adipose tissue dysfunction and profibrotic kidney injury, may become a new target for the treatment of diabetic kidney disease (DKD) and chronic kidney diseases. We tested the hypothesis that human DKD-related injury leads to upregulation of activin A in blood and urine and in a human kidney cell model. We further hypothesized that circulating activin A parallels kidney injury markers in DKD.Research design and methodsIn two adult diabetes cohorts and controls (Minnesota, USA; Galway, Ireland), the relationships between plasma (or urine) activin A, estimated glomerular filtration rate (eGFR) and DKD injury biomarkers were tested with logistic regression and correlation coefficients. Activin A, inflammatory, epithelial-mesenchymal-transition (EMT) and senescence markers were assayed in human kidney (HK-2) cells incubated in high glucose plus transforming growth factor-β1 or albumin.ResultsPlasma activin A levels were elevated in diabetes (n=206) compared with controls (n=76; 418.1 vs 259.3 pg/mL; ps=−0.61; ps=0.65; pConclusionsCirculating activin A is increased in human DKD and correlates with reduced kidney function and kidney injury markers. DKD-injured human renal tubule cells develop a profibrotic and inflammatory phenotype with activin A upregulation. These findings underscore the role of inflammation and provide a basis for further exploration of activin A as a diagnostic marker and therapeutic target in DKD.

AIMS: Examine 30-day readmissions for recurrent hypoglycemia and hyperglycemia in a national cohort of adults with diabetes. METHODS: Retrospective analysis of data from OptumLabs Data Warehouse for all adults with diabetes hospitalized January 1, 2009 to December 31, 2014 with a principal diagnosis of hypoglycemia or hyperglycemia. We examined the rates and risk factors of 30-day readmissions for hypoglycemia and hyperglycemia. RESULTS: After 6419 index hypoglycemia hospitalizations, 1.2% were readmitted for recurrent hypoglycemia, 0.2% for hyperglycemia, and 8.6% for other causes. Multimorbidity was the strongest predictor of recurrent hypoglycemia. After 6872 index hyperglycemia hospitalizations, 4.0% were readmitted for recurrent hyperglycemia, 0.4% for hypoglycemia, and 5.4% for other causes. Recurrent hyperglycemia was less likely in older patients (OR 0.6, 95% CI 0.5–0.9 for 45–64 vs.

Objectives Most transitional care initiatives to reduce rehospitalization have focused on the transition that occurs between a patient's hospital discharge and return home. However, many patients are discharged from a skilled nursing facility (SNF) to their homes. The goal was to evaluate the effectiveness of the Mayo Clinic Care Transitions (MCCT) program (hereafter called program) among patients discharged from SNFs to their homes. Design Propensity-matched control-intervention trial. Intervention Patients in the intervention group received care management following nursing stay (a home visit and nursing phone calls). Setting and Participants Patients enrolled after discharge from an SNF to home were matched to patients who did not receive intervention because of refusal, program capacity, or distance. Patients were aged ≥60 years, at high risk for hospitalization, and discharged from an SNF. Methods Program enrollees were matched through propensity score to nonenrollees on the basis of age, sex, comorbid health burden, and mortality risk score. Conditional logistic regression analysis examined 30-day hospitalization and emergency department (ED) use; Cox proportional hazards analyses examined 180-day hospital stay and ED use. Results Each group comprised 160 patients [mean (standard deviation) age, 85.4 (7.4) years]. Thirty-day hospitalization and ED rates were 4.4% and 10.0% in the program group and 3.8% and 10.0% in the group with usual care (P = .76 for hospitalization; P > .99 for ED). At 180 days, hospitalization and ED rates were 30.6% and 46.3% for program patients compared with 11.3% and 25.0% in the comparison group (P Conclusions and Implications We found no evidence of reduced hospitalization or ED visits by program patients vs the comparison group. Such findings are crucial because they illustrate how aggressive stabilization care within the SNF may mitigate the program role. Furthermore, we found higher ED and hospitalization rates at 180 days in program patients than the comparison group.

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.

Individualized diabetes management would benefit from prospectively identifying well-controlled patients at risk of losing glycemic control.To identify patterns of hemoglobin A1c (HbA1c) change among patients with stable controlled diabetes.Cohort study using OptumLabs Data Warehouse, 2001-2013. We develop and apply a machine learning framework that uses a Bayesian estimation of the mixture of generalized linear mixed effect models to discover glycemic trajectories, and a random forest feature contribution method to identify patient characteristics predictive of their future glycemic trajectories.The study cohort consisted of 27,005 US adults with type 2 diabetes, age 18 years and older, and stable index HbA1c7.0%.HbA1c values during 24 months of observation.We compared models with k=1, 2, 3, 4, 5 trajectories and baseline variables including patient age, sex, race/ethnicity, comorbidities, medications, and HbA1c. The k=3 model had the best fit, reflecting 3 distinct trajectories of glycemic change: (T1) rapidly deteriorating HbA1c among 302 (1.1%) youngest (mean, 55.2 y) patients with lowest mean baseline HbA1c, 6.05%; (T2) gradually deteriorating HbA1c among 902 (3.3%) patients (mean, 56.5 y) with highest mean baseline HbA1c, 6.53%; and (T3) stable glycemic control among 25,800 (95.5%) oldest (mean, 58.5 y) patients with mean baseline HbA1c 6.21%. After 24 months, HbA1c rose to 8.75% in T1 and 8.40% in T2, but remained stable at 6.56% in T3.Patients with controlled type 2 diabetes follow 3 distinct trajectories of glycemic control. This novel application of advanced analytic methods can facilitate individualized and population diabetes care by proactively identifying high risk patients.

Frail multimorbid elders are at high risk for hospital readmission and can benefit from dedicated care transitions programs. Nonetheless, some patients remain at disproportionately heightened risk. In this retrospective study of 717 frail multimorbid community-dwelling elders (mean age = 83 years) enrolled in a care transitions program, we assessed the effect of specific medications and postdischarge medication changes on 30-day readmission. Patients treated with opioids, anticholinergic agents, or antihistamines and those requiring ≥ 4 medication changes after hospital discharge were at a significantly greater risk. This knowledge provides nurse practitioners an opportunity to individualize and improve the care of this vulnerable population.