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Patient perceptions and experiences may explain discrepancies between guideline recommendations and real-world utilization and adherence to cardiorenal protective GLP-1 RAs and SGLT-2is for type 2 diabetes (T2D) . We identified 60,912 posts from public T2D Facebook groups (N=15 from 20to 2021 and extracted all narratives mentioning cardioprotective GLP-1 RAs and SGLT-2is by name (N=250) . We used open coding to categorize all mentions of risks/harms and benefits of these drugs as defined by the 2021 ADA Standards of Care (SOC) vs. described by individuals but not mentioned in the SOC. Individuals reported 41 risks and 6 benefits not in the SOC. Posts rarely ( People with T2D have a range of concerns and perceptions of the benefits/harms of to GLP-1RAs and SGLT2is. Cardiorenal protection appears to be of lower priority than other tangible benefits/harms. While these data are not representative of all people with T2D (i.e., those underrepresented in social media groups) , they underscore the importance of proactively engaging patients in conversation, eliciting and addressing questions/concerns, and providing evidence-based information on T2D treatment options. Disclosure N.Lambert: Consultant; Hugo Health, Research Support; Optum Labs. C.Clark: Employee; UnitedHealth Group, Stock/Shareholder; UnitedHealth Group. R.G.Mccoy: Consultant; Emmi. A.Wong: Employee; UnitedHealth Group. D.J.Cook: None.

People with diabetes have been profoundly impacted by the COVID-pandemic. Diabetes and its comorbidities are strong risk factors for severe, including fatal, COVID-disease. People with diabetes may also have limited or delayed routine and non-emergent medical services, potentially increasing their risk of death from causes unrelated to COVID-19. Granular population-level data on rates, causes, and places (i.e. home vs. hospital) of death among people with diabetes during the COVID-pandemic is scarce. We examined Minnesota death certificates from 2020 (COVID-year) and 2018-20 (comparator years) among people with diabetes to compare changes in population-adjusted rates of diabetes-specific mortality (diabetes as a primary cause of death) , and all-cause and other disease-specific mortality (other primary causes with diabetes as a contributing cause of death) . We also assessed COVID-mortality (COVID-as a primary cause and diabetes as a contributing cause) . Analyses were adjusted for multiple comparisons using the false discovery rate correction. COVID-accounted for 246 deaths per 100,000 people with diabetes. There was no significant change in diabetes-specific mortality from 2018-20to 2020 (328 to 353 per 100,000; 2020 vs. 2018-20IRR 1.[95% CI 1.01-1.15]; p=0.08) . All-cause mortality among people with diabetes increased from 1,484 to 1,922 per 100,000 (IRR 1.30 [95% CI 1.26-1.33]; p Disclosure R.G.Mccoy: Consultant; Emmi. A.F.Mullan: None. M.M.Jeffery: Stock/Shareholder; Goodness Growth Holdings. C.M.Bucks: None. C.M.Clements: Consultant; Vail Scientific LLC. R.Campbell: Consultant; Bryn Pharma. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K23DK114497)

Severe hypoglycemia and hyperglycemia (ketoacidosis, hyperglycemic hyperosmolar state) are common yet potentially preventable acute complications of diabetes. Our objectives were to use national data from OptumLabs® Data Warehouse, 2011-2020, to 1) characterize trends in all-cause mortality among adults with type 1 diabetes (T1D) and type 2 diabetes (T2D) experiencing emergency department visits or hospitalizations for hypoglycemia and hyperglycemia;2) extend analyses through 2020 to assess the impact of the COVID-pandemic; and3) examine racial/ethnic and gender disparities in subsequent mortality adjusted for relevant patient characteristics. Among 4,164 adults with T1DM experiencing hypoglycemia, 30-day and 1-year mortality increased from 0.5% to 0.9% and 4.7% to 6.1%. Among 49,931 adults with T2DM experiencing hypoglycemia, 30-day and 1-year mortality were stable at 2.1-2.0% and 16.2-16.1%. Among 4,698 adults with T1DM experiencing hyperglycemia, 30-day and 1-year mortality increased from 0.4% to 1.0% and 2.7% to 5.9%, respectively. Among 17,123 adults with T2DM experiencing hyperglycemia, 30-day and 1-year mortality increased from 2.5% to 3.0% and 11.5% to 13.1%. Table shows differences in mortality rates by age, race/ethnicity, gender. These results call for proactive engagement of high risk individuals experiencing severe hypoglycemia and hyperglycemia to reduce their risk of death. Disclosure R.G.Mccoy: Consultant; Emmi. J.Herrin: Consultant; Johnson & Johnson Medical Devices Companies. K.Swarna: None. R.J.Galindo: Advisory Panel; Sanofi, WW International, Inc., Research Support; Dexcom, Inc., Eli Lilly and Company, Novo Nordisk. G.E.Umpierrez: Research Support; AstraZeneca, Dexcom, Inc., Novo Nordisk. S.Golden: Advisory Panel; Abbott Diabetes, Medtronic. P.J.O'connor: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases grant number K23DK114497

Purpose: An enhanced primary care diabetes model (EPCD) was implemented to provide proactive longitudinal care to adult patients with diabetes, grounded in close partnership between primary care providers (PCP) , registered nurses (RN) , and Medication Management Services (MMS) pharmacists. In this model, care team RNs could request pharmacist support through chart review for comprehensive diabetes management. The purpose of this study is to evaluate the impact of the MMS pharmacist in the EPCD model for patients with diabetes. Methods: All adults with diabetes paneled to a PCP in six primary care clinics in the Midwest U.S. were eligible for the EPCD model. We compared the change in diabetes care quality between patients who received pharmacist chart review and care recommendations to matched patients who did not. The index date was defined as the date of MMS pharmacist review after referral from the care team RN or date of RN review and no subsequent pharmacist consult. The primary outcome was the change in the proportion of patients meeting the composite of four diabetes treatment goals (D4) , including hemoglobin A1c control (HbA1c less than 8%) , blood pressure control (less than 140/90 mmHg) , aspirin use if indicated, and statin use if indicated at six months from the index date. Secondary outcomes were each of the four indicators individually. Results: The proportion of patients meeting the D4 after 6 months increased with pharmacist chart reviews (N=85) compared to matched patients with no review (N=170) (27% vs. 7%, p Conclusions: Pharmacist engagement in the EPCD model improved diabetes care quality. This supports the inclusion and utilization of pharmacists in multidisciplinary efforts to improve diabetes care. Disclosure D.Hess: None. R.G.Mccoy: Consultant; Emmi. J.Matulis: None. M.Kessler: None. K.Mara: None. J.Herges: None.

High deductible health plans (HDHPs) have become increasingly common as a means of increasing access to health insurance while curbing total utilization. However, high out-of-pocket (OOP) expenditures faced by HDHP enrollees may disincentivize high value care, particularly for people with chronic but costly health conditions like diabetes. Glucose-lowering drugs are a large part of direct costs of diabetes management and contribute to cost-related non-adherence, burden of treatment, and poor health outcomes. We examined the changes in OOP expenses for a 30-day supply of each class of glucose-lowering drugs among 43,900 adults with diabetes included in OptumLabs® Data Warehouse between 20 and 2018 who switched from non-HDHPs to HDHPs, compared to 333,803 adults who did not switch. The mean OOP expenses, standardized to 20$US, were higher for HDHP beneficiaries (Table) . Switching to a HDHP significantly increased OOP expenditures for all glucose-lowering classes, ranging from 5% increase (sulfonylurea) to 48% increase (glitazone) . This increased expense for patients may hinder adherence and adversely impact glycemic management and health outcomes among HDHP enrollees. Clinicians should be aware that HDHP enrollees may be more sensitive to OOP costs when choosing medications, and policy makers should exempt evidence-based prescription drugs from high deductibles. Disclosure D.H.Jiang: None. J.Herrin: Consultant; Johnson & Johnson Medical Devices Companies. H.Van houten: None. R.G.Mccoy: Consultant; Emmi. Funding National Institute of Diabetes and Digestive and Kidney Diseases grant number K23DK114497

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

IntroductionThe public health crisis of escalating mental health, behavioural and substance-related emergencies has revealed the need to approach these complex events from a health perspective, rather than the traditional criminal justice standpoint. Despite law enforcement officers often being the first responders to emergency calls concerning self or bystander harm, they are not optimally equipped to manage these crises holistically or to connect affected individuals to necessary medical treatment and social support. Paramedics and other emergency medical services (EMS) providers are well positioned to deliver comprehensive medicosocial care during and in the immediate aftermath of these emergencies, moving beyond their traditional role in emergency evaluation, stabilisation and transport to a higher level of care. The role of EMS in bridging this gap and helping shift emphasis to mental and physical health needs in crisis situations has not been examined in prior reviews.Methods and analysisIn this protocol, we delineate our approach to describing existing EMS programmes that focus specifically on supporting individuals and communities experiencing mental, behavioural and substance-related health crises. The databases to be searched are EBSCO CINAHL, Ovid Cochrane Central Register of Controlled Trials, Ovid Embase, Ovid Medline, Ovid PsycINFO and Web of Science Core Collection, with search date limits being from database inception to 14 July 2022. A narrative synthesis will be completed to characterise populations and situations targeted by the programmes, describe programme staffing and composition, detail the interventions and identify collected outcomes.Ethics and disseminationAll data in the review will be publicly accessible and published previously, so approval by a research ethics board is not needed. Our findings will be published in a peer-reviewed journal and shared with the public.Trial registration numberhttps://doi.org/10.17605/OSF.IO/UYV4R

OBJECTIVESTo emulate the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) trial using real-world data prior to its publication. GRADE is the first comparative effectiveness study to directly compare second-line glucose-lowering medications with respect to their ability to lower hemoglobin A1c (HbA1c).DESIGN AND SETTINGIn this observational cohort study, we applied GRADE trial criteria to claims and laboratory data from OptumLabs® Data Warehouse (OLDW), a U.S. nationwide claims database, between 1/25/2010 and 6/30/2019.PARTICIAPNTSAdults with type 2 diabetes with hemoglobin A1c (HbA1c) 6.8-8.5% on metformin monotherapy, identified according to GRADE trial specifications.INTERVENTIONSGlimepiride, liraglutide, sitagliptin, and insulin glargine.MAIN OUTCOME MEASURESThe primary outcome was time to HbA1c ≥7.0% and secondary outcomes were other metabolic, microvascular, macrovascular, and safety outcomes specified by GRADE. Propensity scores were estimated using the gradient boosting machine method and inverse propensity score weighting was used to emulate randomization of the treatment groups, which were then compared using Cox proportional hazards regression.RESULTSWe identified 8252 patients (19.7% of adults starting the study drugs in OLDW) meeting GRADE eligibility criteria (glimepiride arm=4318, liraglutide arm=690, sitagliptin arm=2993, glargine arm=251). The glargine arm was excluded from analyses due to small sample size. Median times to HbA1c ≥7.0% were 442 (95% CI, 394-480) days for glimepiride, 764 (95% CI, 741-NA) days for liraglutide, and 427 (95% CI, 380-483) days for sitagliptin. Liraglutide was associated with lower risk of reaching HbA1c ≥7.0% compared to glimepiride (HR 0.57 [95% CI, 0.43-0.75]) and sitagliptin (HR 0.55 [95% CI, 0.41-0.73]). Results were consistent for the secondary outcome of time to HbA1c >7.5%. There were no significant differences among treatment groups for the remaining secondary outcomes.CONCLUSIONSIn this emulation of the GRADE trial, liraglutide was significantly more effective at maintaining glycemic control than glimepiride or sitagliptin when added to metformin monotherapy. There is value in generating timely evidence on medical treatments using real-world data as a complement to prospective trials.SUMMARY BOXESWhat is already known about this topic?Real-world data is an important source of information about clinical practice, comparative effectiveness and safety, and health outcomes and has the potential to generate timely, pragmatic evidence on medical treatments as a complement to prospective clinical trials.Multiple classes of second-line glucose-lowering medications have been approved for the management of type 2 diabetes, with limited evidence of their comparative effectiveness with respect to glycemic control.What this study adds?We emulated the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE) randomized clinical trial using data from a U.S. nationwide administrative claims database to identify the strengths and limitations of using real-world data to emulate prospective comparative effectiveness trials, particularly when examining medications in contexts that may not be the standard of care.Liraglutide is more effective than glimepiride and sitagliptin at lowering HbA1c, supporting its preferential use when substantial glycemic reduction is needed.Advanced causal inference analytic methods applied to observational data can be used to efficiently and effectively emulate clinical trials.

ObjectiveWe examined the association between stay-at-home order implementation and the incidence of COVID-19 infections and deaths in rural versus urban counties of the United States.DesignWe used an interrupted time-series analysis using a mixed effects zero-inflated Poisson model with random intercept by county and standardised by population to examine the associations between stay-at-home orders and county-level counts of daily new COVID-19 cases and deaths in rural versus urban counties between 22 January 2020 and 10 June 2020. We secondarily examined the association between stay-at-home orders and mobility in rural versus urban counties using Google Community Mobility Reports.InterventionsIssuance of stay-at-home orders.Primary and secondary outcome measuresCo-primary outcomes were COVID-19 daily incidence of cases (14-day lagged) and mortality (26-day lagged). Secondary outcome was mobility.ResultsStay-at-home orders were implemented later (median 30 March 2020 vs 28 March 2020) and were shorter in duration (median 35 vs 54 days) in rural compared with urban counties. Indoor mobility was, on average, 2.6%–6.9% higher in rural than urban counties both during and after stay-at-home orders. Compared with the baseline (pre-stay-at-home) period, the number of new COVID-19 cases increased under stay-at-home by incidence risk ratio (IRR) 1.60 (95% CI, 1.57 to 1.64) in rural and 1.36 (95% CI, 1.30 to 1.42) in urban counties, while the number of new COVID-19 deaths increased by IRR 14.21 (95% CI, 11.02 to 18.34) in rural and IRR 2.93 in urban counties (95% CI, 1.82 to 4.73). For each day under stay-at-home orders, the number of new cases changed by a factor of 0.982 (95% CI, 0.981 to 0.982) in rural and 0.952 (95% CI, 0.951 to 0.953) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.977 (95% CI, 0.976 to 0.977) in rural counties and 0.935 (95% CI, 0.933 to 0.936) in urban counties. Each day after stay-at-home orders expired, the number of new cases changed by a factor of 0.995 (95% CI, 0.994 to 0.995) in rural and 0.997 (95% CI, 0.995 to 0.999) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.969 (95% CI, 0.968 to 0.970) in rural counties and 0.928 (95% CI, 0.926 to 0.929) in urban counties.ConclusionStay-at-home orders decreased mobility, slowed the spread of COVID-19 and mitigated COVID-19 mortality, but did so less effectively in rural than in urban counties. This necessitates a critical re-evaluation of how stay-at-home orders are designed, communicated and implemented in rural areas.

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.

PURPOSE: Primary care practices manage most patients with diabetes and face considerable operational, regulatory, and reimbursement pressures to improve the quality of this care. The Enhanced Primary Care Diabetes (EPCD) model was developed to leverage the expertise of care team nurses and pharmacists to improve diabetes care. METHODS: Using a retrospective, interrupted-time series design, we evaluated the EPCD model’s impact on D5, a publicly reported composite quality measure of diabetes care: glycemic control, blood pressure control, low-density lipoprotein control, tobacco abstinence, and aspirin use. We examined 32 primary care practices in an integrated health care system that cares for adults with diabetes; practices were categorized as staff clinician practices (having physicians and advanced practice providers) with access to EPCD (5,761 patients); resident physician practices with access to EPCD (1,887 patients); or staff clinician practices without access to EPCD (10,079 patients). The primary outcome was the percentage of patients meeting the D5 measure, compared between a 7-month preimplementation period and a 10-month postimplementation period. RESULTS: After EPCD implementation, staff clinician practices had a significant improvement in the percentage of patients meeting the D5 composite quality indicator (change in incident rate ratio from 0.995 to 1.005; P = .01). Trends in D5 attainment did not change significantly among the resident physician practices with access to EPCD (P = .14) and worsened among the staff clinician practices without access to EPCD (change in incident rate ratio from 1.001 to 0.994; P = .05). CONCLUSIONS: Implementation of the EPCD team model was associated with an improvement in diabetes care quality in the staff clinician group having access to this model. Further study of proactive, multidisciplinary chronic disease management led by care team nurses and integrating clinical pharmacists is warranted.

Background An enhanced primary care team model was implemented to provide proactive, longitudinal care to patients with diabetes, grounded in close partnership between primary care providers (PCPs), nurses, and Medication Management Services (MMS) pharmacists. The purpose of this study is to evaluate the impact of the MMS pharmacist involvement in the enhanced primary care model for patients with diabetes. Methods This retrospective cohort study compared the quality of diabetes care between patients referred to a pharmacist and propensity score matched controls who were not. Eligible patients were adults (age 18 to 75 years) enrolled in the enhanced primary care team process who did not meet at least one of four diabetes quality indicators at 13 Mayo Clinic Rochester primary care practice locations. The intervention examined was asynchronous e-consults by pharmacists affiliated with the primary care practice. Main measures The primary outcome was change in the proportion of patients meeting the composite of four diabetes treatment goals (D4), including hemoglobin A1c (HbA1c) control, blood pressure control, aspirin use, and statin use at six months from enrollment among patients who received pharmacist intervention compared to matched patients who did not. Secondary outcomes were each of the D4 goal individually. Results The proportion of patients meeting the D4 increased with pharmacist e-consults (N = 85) compared to matched controls with no review (N = 170) (27% vs 7.0%, p Conclusions Pharmacist engagement in the enhanced primary care team improved diabetes management. This supports the inclusion and utilization of pharmacists in multidisciplinary efforts to improve diabetes care.

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.

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

PURPOSE OF REVIEW: Present the value of a person-centered approach in diabetes management and review current evidence supporting its practice. RECENT FINDINGS: Early evidence from glycemic control trials in diabetes resulted in most practice guidelines adopting a glucose-centric intensive approach for management of the disease, consistently relying on HbA1c as a marker of metabolic control and success. This paradigm has been recently dispelled by new evidence that shows that intensive glycemic control does not provide a significant benefit regarding patient-important microvascular and macrovascular hard outcomes when compared to moderate glycemic targets. SUMMARY: The goals of diabetes therapy are to reduce the risks of acute and chronic complications and increase quality of life while incurring least burden of treatment and disruption to the patient’s life. A person-centered approach to diabetes management is achieved through shared decision making, integration of evidence-based care and patient’s needs, values and preferences, and minimally disruptive approaches to diabetes care and at the same time offer practical guidance to clinicians and patients on achieving this type of care.

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.

Background Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with high morbidity and limited treatment options. Type 2 diabetes mellitus (T2DM) is a common comorbid illness among patients with IPF and is often treated with metformin, the first-line agent in the management of T2DM. There is growing evidence demonstrating metformin’s anti-fibrotic properties; however, there is little real-world clinical data regarding its potential effectiveness in IPF. This study aims to evaluate the clinical benefit of metformin in patients with IPF and T2DM. Methods This nationwide cohort study used de-identified administrative claims data from OptumLabs® Data Warehouse to identify 3599 adults with IPF and concomitant T2DM between January 1, 2014 and June 30, 2019. Two cohorts were created: a cohort treated with metformin (n = 1377) and a cohort not treated with metformin (n = 2222). A final 1:1 propensity score-matched cohort compared 1100 patients with IPF and T2DM receiving metformin to those with both diagnoses but not receiving metformin; matching accounted for age, sex, race/ethnicity, residence region, year, medications, oxygen use, smoking status, healthcare use, and comorbidities. Outcomes were all-cause mortality (primary) and hospitalizations (secondary). Results Among 2200 patients with IPF and T2DM included in this matched analysis, metformin therapy was associated with a reduction in all-cause mortality (hazard ratio [HR], 0.46; 95% confidence interval [CI], 0.36–0.58; p p = 0.003) compared to patients not receiving metformin. Conclusions Among patients with IPF and T2DM, metformin therapy may be associated with improved clinical outcomes. However, further investigation with randomized clinical trials is necessary prior to metformin’s broad implementation in the clinical management of IPF.

Acute kidney injury (AKI) survivors are at heightened risk for poor short- and long-term health outcomes. Even among those who recover after an AKI episode, the risk for chronic kidney disease is 4- to 6-fold higher than in patients without AKI, underscoring the importance of identifying methods to improve AKI survivorship.The purpose of this report was to describe the development and feasibility of a novel multidisciplinary approach to caring for AKI survivors at care transitions (ACT).Observational process improvement initiative.Single academic medical center in the United States.The studied population was adults with stage 3 AKI not discharging on dialysis who were established with a primary care provider (PCP) at our institution.An electronic health record tool was developed prior to implementation to identify AKI survivors. The ACT program encompassed engaging patients in the hospital, delivering education by nephrology-trained nurses before discharge, completing recommended laboratory testing after discharge, and conducting structured kidney-focused follow-up with a pharmacist and a PCP within 7 to 14 days after discharge. Patients could be referred for nephrology evaluation at the discretion of the PCP.Preliminary data demonstrated that most AKI survivors of interest could be identified, educated, and followed up with this model. This strategy appeared feasible, scalable, and maximized the unique expertise of each member of the multidisciplinary team.Small sample size, future assessment of process, clinical, and patient-reported outcomes needed.The multidisciplinary ACT workflow supported by clinical decision support was feasible and addressed gaps in existing care transition models. Team-based care delivery in primary care appears to be a mechanism to extend the capacity for kidney health monitoring for AKI survivors.Les patients qui survivent à un épisode d’insuffisance rénale aiguë (IRA) courent un risque plus élevé de mauvais résultats cliniques à court et à long terme. Même chez les patients qui se rétablissent, le risque de progression vers l’insuffisance rénale chronique (IRC) demeure de quatre à six fois plus élevé que chez les patients n’ayant jamais eu d’épisode d’IRA. Il est donc essentiel d’identifier des méthodes permettant d’améliorer la survie à un épisode d’IRA.L’objectif de cette étude était de décrire l’élaboration et la faisabilité d’une nouvelle approche multidisciplinaire pour la prise en charge des survivants d’un épisode d’IRA en transition de soins (Approche multidisciplinaire en Transition de Soins—AmTS).Initiative d’amélioration des processus menée par observation.Un seul centre médical universitaire aux États-Unis.La population étudiée était constituée d’adultes atteints d’IRA de stade 3 sans traitements de dialyse à leur sortie et qui avaient été mis en contact avec un fournisseur de soins primaires (FSP) dans l’établissement.Avant la mise en œuvre de l’intervention, un outil de dossier de santé électronique a été développé pour identifier les survivants à un épisode d’IRA. Le programme de l’AmTS comprenait la participation des patients pendant leur séjour à l’hôpital, une formation donnée par des infirmières formées en néphrologie avant le congé, les tests de laboratoire recommandés après la sortie de l’hôpital et un suivi structuré axé sur la santé rénale avec un pharmacien et un FSP dans les 7 à 14 jours suivant la sortie de l’hôpital. Il a été laissé à la discrétion des FSP d’aiguiller ou non leurs patients pour une évaluation en néphrologie.Des données préliminaires ont démontré qu’il était possible d’identifier, d’informer et d’assurer le suivi de la plupart des sujets d’intérêt (des survivants à un épisode d’IRA) avec ce modèle. Cette stratégie a semblé réalisable, évolutive et apte à optimiser l’expertise individuelle des membres de l’équipe multidisciplinaire.Faible taille de l’échantillon; une évaluation future du processus, des résultats cliniques et des résultats rapportés par les patients est nécessaire.Le processus de cette AmTS soutenue par une aide à la prise de décision clinique s’est avéré réalisable et a permis de combler les lacunes des modèles de transition des soins existants. Dans le contexte des soins primaires, la prestation de soins en équipe semble être un mécanisme permettant d’étendre la capacité de surveillance de la santé rénale des survivants à un épisode d’IRA.

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.

OBJECTIVE To examine factors associated with emergency department (ED) transport after hypoglycemia treated by emergency medical services (EMS) and assess the impact of ED transport on severe hypoglycemia recurrence. RESEARCH DESIGN AND METHODS We retrospectively analyzed electronic health records of a multistate advanced life support EMS provider and an integrated healthcare delivery system serving an overlapping geographic area in the upper Midwest. For adults with diabetes treated by EMS for hypoglycemia between 2013 and 2019, we examined rates of ED transport, factors associated with it, and its impact on rates of recurrent hypoglycemia requiring EMS, ED, or hospital care within 3, 7, and 30 days. RESULTS We identified 1,977 hypoglycemia-related EMS encounters among 1,028 adults with diabetes (mean age 63.5 years [SD 17.7], 55.2% male, 87.4% non-Hispanic White, 42.4% rural residents, and 25.6% with type 1 diabetes), of which 46.4% resulted in ED transport (31.1% of calls by patients with type 1 diabetes and 58.0% of calls by patients with type 2 diabetes). Odds of ED transport were lower in patients with type 1 diabetes (odds ratio [OR] 0.44 [95% CI 0.31–0.62] vs. type 2 diabetes) and higher in patients with prior ED visits (OR 1.38 [95% CI 1.03–1.85]). Within 3, 7, and 30 days, transported patients experienced recurrent severe hypoglycemia 2.8, 5.2, and 10.6% of the time, respectively, compared with 7.4, 11.2, and 22.8% of the time among nontransported patients (all P < 0.001). This corresponds to OR 0.58 (95% CI 0.42–0.80) for recurrent severe hypoglycemia within 30 days for transported versus nontransported patients. When subset by diabetes type, odds of recurrent severe hypoglycemia among transported patients were 0.64 (95% CI 0.43–0.96) and 0.42 (95% CI 0.24–0.75) in type 1 and type 2 diabetes, respectively. CONCLUSIONS Transported patients experienced recurrent hypoglycemia requiring medical attention approximately half as often as nontransported patients, reinforcing the importance of engaging patients in follow-up to prevent recurrent events.

Background To meet increasing demand, healthcare systems may leverage shorter appointment lengths to compensate for a limited supply of primary care providers (PCPs). Limiting the time spent with patients when evaluating acute health needs may adversely affect quality of care and increase subsequent healthcare utilization; however, the impact of brief duration appointments on healthcare utilization in the United States has not been examined. This study aimed to assess for potential inferiority of shorter (15-min) primary care appointments compare to longer (≥ 30-min appointments) with respect to downstream healthcare utilization within 7 days of the initial appointment. Methods We performed a retrospective cohort study using electronic health record (EHR), billing, and administrative scheduling data from five primary care practices in Midwest United States. Adult patients seen for acute Evaluation & Management visits between 10/1/2015 and 9/30/2017 were included. Patients scheduled for 15-min appointments were propensity score matched to those scheduled for ≥ 30-min. Multivariate regression models examined the effects of appointment length on repeat primary care visits, emergency department (ED) visits, hospitalizations, and diagnostic services within 7 days following the visit. Models were adjusted for baseline patient, visit, and provider characteristics. A non-inferiority approach was employed. Results We identified 173,758 total index visits (6.5% 15-min, 93.5% ≥ 30-min). 11,222 15-min appointments were matched to a comparable ≥ 30-min visit. Longer appointments were more frequent among trainee physicians, patients with limited English proficiency, and patients with more comorbidities. There was no significant effect of scheduled appointment length on the incidence of repeat primary care visits (OR = 0.983, CI: 0.873, 1.106) or ED visits (OR = 0.856, CI: 0.700, 1.047). Shorter appointments were associated with lower rates of subsequent hospitalizations (OR = 0.689, CI: 0.504, 0.941), laboratory services (OR = 0.682, CI: 0.643, 0.724), and diagnostic imaging services (OR = 0.499, CI: 0.466, 0.534). None of the non-inferiority thresholds were exceeded. Conclusions For select indications and select low risk patients, shorter duration appointments may be a non-inferior option for scheduling of patient care that will not result in greater downstream healthcare utilization. These findings can help inform healthcare delivery models and triage processes as health systems and payers re-examine how to best deliver care to growing patient populations.

BackgroundThroughout the spring of 2020, stay-at-home orders were imposed to curb the spread of COVID-19. There is limited data on the effectiveness of stay-at-home orders, particularly in rural as compared to urban areas.ObjectiveTo examine the association between stay-at-home order implementation and the incidence of COVID-19 in rural vs. urban counties.DesignInterrupted time series analysis using a mixed effects zero-inflated Poisson model.Participants3,142 U.S. counties.InterventionsStay-at-home orders.Main MeasuresCOVID-19 daily incidence (primary) and mobility (secondary and intermediate measure of stay-at-home effectiveness)Key ResultsStay-at-home orders were implemented later (median March 30 vs. March 28) and were shorter (median 35 vs. 54 days) in rural than urban counties. Indoor mobility was, on average, 2.6-6.9% higher in rural than urban counties both during and after stay-at-home orders. Compared to the baseline (pre-stay-at-home) period, the number of new COVID-19 cases increased under stay-at-home by IRR 1.60 (95% CI, 1.57-1.64) in rural and 1.36 (95% CI, 1.30-1.42) in urban counties. For each day under stay-at-home orders, the number of new cases changed by a factor of 0.982 (95% CI 0.981-0.982) in rural and 0.952 (95% CI, 0.951-0.953) in urban counties compared to prior to stay-at-home. Each day after stay-at-home orders expired, the number of new cases changed by a factor of 0.995 (95% CI, 0.994-0.995) in rural and 0.997 (95% CI, 0.995-0.999) in urban counties compared to prior to stay-at-home.ConclusionStay-at-home orders decreased mobility and slowed the spread of COVID-19, but less effectively in rural than in urban counties. This necessitates a critical reevaluation of how stay-at-home orders are designed, communicated, and implemented in rural areas.

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.

Examine the efficacy of metformin compared to placebo or other glucose-lowering medications on microvascular outcomes in patients with Type 2 Diabetes Mellitus (T2DM).MEDLINE, EMBASE, Web of Science, and Scopus were searched from database inception to March 2020. We included randomized clinical trials of patients with T2DM receiving metformin compared with another active glucose-lowering treatment or placebo in which a microvascular outcome was assessed. The risk of bias was assessed using the Cochrane Risk of Bias tool. Microvascular complications included kidney-related outcomes, retinopathy, and peripheral neuropathy. An inverse-weighted variance random-effect meta-analysis was performed to estimate drugs effect over microvascular disease. PROSPERO (CRD42019120365).Nineteen RCTs (n = 18,181) were included. Metformin increased estimated glomerular filtration rate (eGFR) by a mean difference (MD) of 1.08 (95% CI 0.84 to 1.33 ml/min/1.73 mThere is no evidence of clinically significant beneficial effect of metformin therapy as compared to other glucose-lowering medications or placebo on the examined microvascular complications.

IntroductionDiabetes is one of the most common serious chronic health conditions in the USA. People living with diabetes face multiple barriers to optimal diabetes care, including gaps in access to medical care and self-management education, diabetes distress, and high burden of treatment. Community paramedics (CPs) are uniquely positioned to support multidisciplinary care for patients with diabetes by delivering focused diabetes self-management education and support and bridging the gaps between patients and the clinical and community resources they need to live well with their disease.Methods and analysisWe will conduct a pragmatic single-arm prospective trial of a CP-led Diabetes Rescue, Engagement and Management (D-REM) programme that seeks to reduce diabetes distress. We will enrol 70 adults (≥18 years) with diabetes who have haemoglobin A1c (HbA1c)≥9.0%, experienced an emergency department (ED) visit or hospitalisation for any cause within the prior 6 months, and reside in areas with available CP support in Southeast Minnesota (Olmsted, Freeborn and Mower counties) and Northwest Wisconsin (Barron, Rusk and Dunn counties). Participants will be identified using Mayo Clinic electronic health records, contacted for consent and enrolled into the D-REM programme. Visit frequency will be individualised for each patient, but will be an average of four CP visits over the course of approximately 1 month. Outcomes will be change in diabetes distress (primary outcome), confidence in diabetes self-management, health-related quality of life, self-reported hypoglycaemia and hyperglycaemia, HbA1c, ED visits and hospitalisations. Outcomes will be assessed on enrolment, programme completion and 3 months after programme completion.Ethics and disseminationThe study was approved by Mayo Clinic Institutional Review Board. Findings will be disseminated through peer-reviewed publications and presentations. If demonstrated to be successful, this model of care can be implemented across diverse settings and populations to support patients living with diabetes.Trial registration numberNCT04385758.

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.