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Objective: To estimate the health utility scores associated with type 2 diabetes, its treatments, complications, and comorbidities.Research Design and Methods: We analyzed health-related quality-of-life data, collected at baseline during Translating Research Into Action for Diabetes, a multicenter, prospective, observational study of diabetes care in managed care, for 7,327 individuals with type 2 diabetes. We measured quality-of-life using the EuroQol (EQ)-5D, a standardized instrument for which 1.00 indicates perfect health. We used multivariable regression to estimate the independent impact of demographic characteristics, diabetes treatments, complications, and comorbidities on health-related quality-of-life.Results: The mean EQ-5D-derived health utility score for those individuals with diabetes was 0.80. The modeled utility score for a nonobese, non-insulin-treated, non-Asian, non-Hispanic man with type 2 diabetes, with an annual household income of more than $40,000, and with no diabetes complications, risk factors for cardiovascular disease, or comorbidities, was 0.92. Being a woman, being obese, smoking, and having a lower household income were associated with lower utility scores. Arranging complications from least to most severe according to the reduction in health utility scores resulted in the following order: peripheral vascular disease, other heart diseases, transient ischemic attack, cerebral vascular accident, nonpainful diabetic neuropathy, congestive heart failure, dialysis, hemiplegia, painful neuropathy, and amputation.Conclusions: Major diabetes complications and comorbidities are associated with decreased health-related quality-of-life. Utility estimates from our study can be used to assess the impact of diabetes on quality-of-life and conduct cost-utility analyses. [ABSTRACT FROM AUTHOR]

Background: The Diabetes Prevention Program (DPP) found that an intensive lifestyle intervention can reduce the development of diabetes by more than half in adults with prediabetes, but there is little information about the feasibility of offering such an intervention in community settings. This study evaluated the delivery of a group-based DPP lifestyle intervention in partnership with the YMCA.Methods: This pilot cluster-randomized trial was designed to compare group-based DPP lifestyle intervention delivery by the YMCA to brief counseling alone (control) in adults who attended a diabetes risk-screening event at one of two semi-urban YMCA facilities and who had a BMI>or=24 kg/m2, >or=2 diabetes risk factors, and a random capillary blood glucose of 110-199 mg/dL. Multivariate regression was used to compare between-group differences in changes in body weight, blood pressures, HbA1c, total cholesterol, and HDL-cholesterol after 6 and 12 months.Results: Among 92 participants, controls were more often women (61% vs 50%) and of nonwhite race (29% vs 7%). After 6 months, body weight decreased by 6.0% (95% CI=4.7, 7.3) in intervention participants and 2.0% (95% CI=0.6, 3.3) in controls (p<0.001; difference between groups). Intervention participants also had greater changes in total cholesterol (-22 mg/dL vs +6 mg/dL controls; p<0.001). These differences were sustained after 12 months, and adjustment for differences in race and gender did not alter these findings. With only two matched YMCA sites, it was not possible to adjust for potential clustering by site.Conclusions: The YMCA may be a promising channel for wide-scale dissemination of a low-cost approach to lifestyle diabetes prevention. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To examine racial/ethnic and economic variation in cost-related medication underuse among insured adults with diabetes. RESEARCH DESIGN AND METHODS: We surveyed 5,086 participants from the multicenter Translating Research Into Action for Diabetes Study. Respondents reported whether they used less medication because of cost in the past 12 months. We examined unadjusted and adjusted rates of cost-related medication underuse, using hierarchical regression, to determine whether race/ethnicity differences still existed after accounting for economic, health, and other demographic variables. RESULTS: Participants were 48% white, 14% African American, 14% Latino, 15% Asian/Pacific Islander, and 8% other. Overall, 14% reported cost-related medication underuse. Unadjusted rates were highest for Latinos (23%) and African Americans (17%) compared with whites (13%), Asian/Pacific Islanders (11%), and others (15%). In multivariate analyses, race/ethnicity significantly predicted cost-related medication underuse (P = 0.048). However, adjusted rates were only slightly higher for Latinos (14%) than whites (10%) (P = 0.026) and were not significantly different for African Americans (11%), Asian/Pacific Islanders (7%), and others (11%). Income and out-of-pocket drug costs showed the greatest differences in adjusted rates of cost-related medication underuse (15 vs. 5% for participants with income $50,000 and 24 vs. 7% for participants with out-of-pocket costs >$150 per month vs.

OBJECTIVE: To estimate the cost-effectiveness of screening overweight and obese individuals for pre-diabetes and then modifying their lifestyle based on the Diabetes Prevention Program (DPP). RESEARCH DESIGN AND METHODS: A Markov simulation model was used to estimate disease progression, costs, and quality of life. Cost-effectiveness was evaluated from a health care system perspective. We considered two screening/treatment strategies for pre-diabetes. Strategy 1 included screening overweight subjects and giving them the lifestyle intervention included in the DPP if they were diagnosed with both impaired glucose tolerance (IGT) and impaired fasting glucose (IFG). Strategy 2 included screening followed by lifestyle intervention for subjects diagnosed with either IGT or IFG or both. Each strategy was compared with a program of no screening. RESULTS: Screening for pre-diabetes and treating those identified as having both IGT and IFG with the DPP lifestyle intervention had a cost-effectiveness ratio of $8,181 per quality-adjusted life-year (QALY) relative to no screening. If treatment was also provided to subjects with only IGT or only IFG (strategy 2), the cost-effectiveness ratio increased to $9,511 per QALY. Changes in screening-related parameters had small effects on the cost-effectiveness ratios; the results were more sensitive to changes in intervention-related parameters. CONCLUSIONS: Screening for pre-diabetes in the overweight and obese U.S. population followed by the DPP lifestyle intervention has a relatively attractive cost-effectiveness ratio. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Simple process-of-care indicators are commonly recommended to assess and compare quality of diabetes care across health plans. We sought to determine whether variation in the number of simple diabetes processes of care across provider groups is associated with variation in other quality indicators, including cardiometabolic risk factor levels, patient satisfaction with care, or patient-rated quality of care. RESEARCH DESIGN AND METHODS: We used cross-sectional survey and chart audit data for 8,733 patients with diabetes who received care from 68 provider groups nested in 10 health plans that participated in the Translating Research Into Action for Diabetes study. Analyses using hierarchical regression models assessed associations of the mean number of seven simple process measures with each of the following: HbA(1c) (A1C), systolic blood pressure (SBP), HDL and LDL cholesterol levels, patient satisfaction with care, and patient-rated quality of care. RESULTS: After adjusting for case-mix differences across groups and plans, an average of one additional documented process of care for each patient in a group or plan was associated with significantly lower mean LDL cholesterol levels (-4.51 mg/dl [95% CI 1.46-7.58]) but not with A1C, SBP, or HDL cholesterol levels. The number of care processes documented was associated with patient satisfaction measures and self-rated quality of diabetes care. CONCLUSIONS: Variation in the number of simple process-of-care indicators across provider groups or health plans is associated with differences in patient-centered measures of quality, but assessment of the quality of cardiometabolic risk factor control will require more advanced clinical performance indicators. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to compare the ability of risk stratification models derived from administrative data to classify groups of patients for enrollment in a tailored chronic disease management program.Subjects: This study included 19,548 Medicaid patients with chronic heart failure or diabetes in the Indiana Medicaid data warehouse during 2001 and 2002.Measures: To predict costs (total claims paid) in FY 2002, we considered candidate predictor variables available in FY 2001, including patient characteristics, the number and type of prescription medications, laboratory tests, pharmacy charges, and utilization of primary, specialty, inpatient, emergency department, nursing home, and home health care.Methods: We built prospective models to identify patients with different levels of expenditure. Model fit was assessed using R statistics, whereas discrimination was assessed using the weighted kappa statistic, predictive ratios, and the area under the receiver operating characteristic curve.Results: We found a simple least-squares regression model in which logged total charges in FY 2002 were regressed on the log of total charges in FY 2001, the number of prescriptions filled in FY 2001, and the FY 2001 eligibility category, performed as well as more complex models. This simple 3-parameter model had an R of 0.30 and, in terms in classification efficiency, had a sensitivity of 0.57, a specificity of 0.90, an area under the receiver operator curve of 0.80, and a weighted kappa statistic of 0.51.Conclusion: This simple model based on readily available administrative data stratified Medicaid members according to predicted future utilization as well as more complicated models. [ABSTRACT FROM AUTHOR]

Background: The Diabetes Prevention Program (DPP) demonstrated that interventions can delay or prevent the development of type 2 diabetes.Objective: To estimate the lifetime cost-utility of the DPP interventions.Design: Markov simulation model to estimate progression of disease, costs, and quality of life.Data Sources: The DPP and published reports.Target Population: Members of the DPP cohort 25 years of age or older with impaired glucose tolerance.Time Horizon: Lifetime.Perspectives: Health system and societal.Interventions: Intensive lifestyle, metformin, and placebo interventions as implemented in the DPP.Outcome Measures: Cumulative incidence of diabetes, microvascular and neuropathic complications, cardiovascular complications, survival, direct medical and direct nonmedical costs, quality-adjusted life-years (QALYs), and cost per QALY.Results Of Base-case Analysis: Compared with the placebo intervention, the lifestyle and metformin interventions were estimated to delay the development of type 2 diabetes by 11 and 3 years, respectively, and to reduce the absolute incidence of diabetes by 20% and 8%, respectively. The cumulative incidence of microvascular, neuropathic, and cardiovascular complications were reduced and survival was improved by 0.5 and 0.2 years. Compared with the placebo intervention, the cost per QALY was approximately 1100 dollars for the lifestyle intervention and $31 300 for the metformin intervention. From a societal perspective, the interventions cost approximately 8800 dollars and 29,900 dollars per QALY, respectively. From both perspectives, the lifestyle intervention dominated the metformin intervention.Results Of Sensitivity Analysis: Cost-effectiveness improved when the interventions were implemented as they might be in routine clinical practice. The lifestyle intervention was cost-effective in all age groups. The metformin intervention did not represent good use of resources for persons older than 65 years of age.Limitations: Simulation results depend on the accuracy of the underlying assumptions, including participant adherence.Conclusions: Health policy should promote diabetes prevention in high-risk individuals. [ABSTRACT FROM AUTHOR]

Objective: We evaluated whether participation in a community-based group diabetes prevention program might lead to relative changes in composite 10-year coronary heart disease (CHD) risk for overweight adults with abnormal glucose metabolism.Research Design and Methods: We used the UK Prospective Diabetes Study engine to estimate CHD risk for group-lifestyle and brief counseling (control) groups. Between-group risk changes after 4 and 12 months were compared using ANCOVA.Results: Baseline 10-year risk was similar between treatment groups (P = 0.667). At 4 and 12 months, the intervention group experienced significant decreases in 10-year risk from baseline (-3.28%, P < 0.001; and -2.23%, P = 0.037) compared with control subjects (-0.78%, P = 0.339; and +1.88%, P = 0.073). Between-group differences were statistically significant and increased from the 4- to 12-month visits.Conclusions: Community-based delivery of the Diabetes Prevention Program lifestyle intervention could be a promising strategy to prevent both CHD and type 2 diabetes in adults with pre-diabetes. [ABSTRACT FROM AUTHOR]

Objectives: To assess the use of a co-designed patient-reported outcome (PRO) clinical dashboard and estimate its impact on shared decision-making (SDM) and symptomatology in adults with advanced cancer or chronic kidney disease (CKD)., Materials and Methods: We developed a clinical PRO dashboard within the Northwestern Medicine Patient-Reported Outcomes system, enhanced through co-design involving 20 diverse constituents. Using a single-group, pretest-posttest design, we evaluated the dashboard's use among patients with advanced cancer or CKD between June 2020 and January 2022. Eligible patients had a visit with a participating clinician, completed at least two dashboard-eligible visits, and consented to follow-up surveys. PROs were collected 72 h prior to visits, including measures for chronic condition management self-efficacy, health-related quality of life (PROMIS measures), and SDM (collaboRATE). Responses were integrated into the EHR dashboard and accessible to clinicians and patients., Results: We recruited 157 participants: 66 with advanced cancer and 91 with CKD. There were significant improvements in SDM from baseline, as assessed by collaboRATE scores. The proportion of participants reporting the highest level of SDM on every collaboRATE item increased by 15 percentage points from baseline to 3 months, and 17 points between baseline and 6-month follow-up. Additionally, there was a clinically meaningful decrease in anxiety levels over study period (T-score baseline: 53; 3-month: 52; 6-month: 50; P < .001), with a standardized response mean (SRM) of -0.38 at 6 months., Discussion: PRO clinical dashboards, developed and shared with patients, may enhance SDM and reduce anxiety among patients with advanced cancer and CKD., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Shared decision making (SDM) is the process by which patients and clinicians exchange information and preferences to come to joint healthcare decisions. Clinical dashboards can support SDM by collecting, distilling, and presenting critical information, such as patient-reported outcomes (PROs), to be shared at points of care and in between appointments. We describe the implementation strategies and outcomes of a multistakeholder collaborative process known as "co-design" to develop a PRO-informed clinical dashboard to support SDM for patients with advanced cancer or chronic kidney disease (CKD). Methods: Across 14 sessions, two multidisciplinary teams comprising patients, care partners, clinicians, and other stakeholders iteratively co-designed an SDM dashboard for either advanced cancer (N = 25) or CKD (N = 24). Eligible patients, care partners, and frontline clinicians were identified by six physician champions. The co-design process included four key steps: (1) define "the problem", (2) establish context of use, (3) build a consensus on design, and (4) define and test specifications. We also evaluated our success in implementing the co-design strategy using measures of fidelity, acceptability, adoption, feasibility, and effectiveness which were collected throughout the process. Results: Mean ( M ) scores across implementation measures of the co-design process were high, including observer-rated fidelity and adoption of co-design practices ( M = 19.1 on a 7-21 scale, N = 36 ratings across 9 sessions), as well as acceptability based on the perceived degree of SDM that occurred during the co-design process ( M = 10.4 on a 0 to 12 adapted collaboRATE scale). Capturing the feasibility and adoption of convening multistakeholder co-design teams, min-max normalized scores (ranging from 0 to 1) of stakeholder representation demonstrated that, on average, 95% of stakeholder types were represented for cancer sessions ( M = 0.95) and 85% for CKD sessions ( M = 0.85). The co-design process was rated as either "fully" or "partially" effective by 100% of respondents, in creating a dashboard that met its intended objective. Conclusions: A co-design process was successfully implemented to develop SDM clinical dashboards for advanced cancer and CKD care. We discuss key strategies and learnings from this process that may aid others in the development and uptake of patient-centered healthcare innovations.

Introduction: The rapid development of artificial intelligence (AI) in healthcare has exposed the unmet need for growing a multidisciplinary workforce that can collaborate effectively in the learning health systems. Maximizing the synergy among multiple teams is critical for Collaborative AI in Healthcare., Methods: We have developed a series of data, tools, and educational resources for cultivating the next generation of multidisciplinary workforce for Collaborative AI in Healthcare. We built bulk-natural language processing pipelines to extract structured information from clinical notes and stored them in common data models. We developed multimodal AI/machine learning (ML) tools and tutorials to enrich the toolbox of the multidisciplinary workforce to analyze multimodal healthcare data. We have created a fertile ground to cross-pollinate clinicians and AI scientists and train the next generation of AI health workforce to collaborate effectively., Results: Our work has democratized access to unstructured health information, AI/ML tools and resources for healthcare, and collaborative education resources. From 2017 to 2022, this has enabled studies in multiple clinical specialties resulting in 68 peer-reviewed publications. In 2022, our cross-discipline efforts converged and institutionalized into the Center for Collaborative AI in Healthcare., Conclusions: Our Collaborative AI in Healthcare initiatives has created valuable educational and practical resources. They have enabled more clinicians, scientists, and hospital administrators to successfully apply AI methods in their daily research and practice, develop closer collaborations, and advanced the institution-level learning health system., Competing Interests: This work was supported by the grants from the National Institutes of Health (NIH) Yuan Luo, Kristi Holmes, Luke Rasmussen, Andrew Naidech, Lazaro Sanchez‐Pinto, Richard Wunderink, Jennifer Pacheco, Matthew Carson, Susan Clare. Kristi Holmes is a member of Learning Health Systems Editorial Board. Donald Lloyd‐Jones serves as a board member of the American Heart Association. Michael Markl receives grant support by Siemens and Circle Cardiovascular Imaging; co‐founder and co‐owner of Third Coast Dynamics. Susanna McColley reports grants from the NIH National Center for Advancing Translational Science, the Centers for Disease Control and Prevention, the Cystic Fibrosis Foundation, and the Rosenau Family Research Foundation. She receives compensation as an advisor to Vertex Pharmaceuticals, Inc. Huiping Liu is the scientific co‐founder of ExoMira Medicine. Justin Starren reports grants from the NIH and Greenwall Foundation. Theresa Walunas receives research funding from Gilead Sciences. Kelly Michelson reports grants from the NIH, Greenwall Foundation, and the Patient‐Centered Outcomes Research Institute. Richard D’Aquila reports grants from the NIH, serving on external advisory boards for NIH‐funded projects, serving on the NIAID AIDS Research Advisory Council, and serving on the editorial board of the Journal of Clinical Investigation. Abel Kho is an advisor to Datavant. Sanjiv Shah is supported by grants from the NIH and AHA. Lee Cooper reports grants from the NIH and has invention disclosures registered at the Northwestern Office of Innovation and New Ventures, consults for Tempus, and advises Veracyte and Targeted Bioscience. Feng Yue is supported by grants from NIH and is a co‐founder of Sariant Therapeutics, Inc. Deyu Fang is co‐founder of ExoMira Medicine. Ronald Ackermann is supported by grants from the NIH, CDC, and the UnitedHealth Group., (© 2024 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)

Background: Liver cirrhosis is a chronic disease that is known as a "silent killer" and its true prevalence is difficult to describe. It is imperative to accurately characterize the prevalence of cirrhosis because of its increasing healthcare burden., Methods: In this retrospective cohort study, trends in cirrhosis prevalence were evaluated using administrative data from one of the largest national health insurance providers in the US. (2011-2018). Enrolled adult (≥18-years-old) patients with cirrhosis defined by ICD-9 and ICD-10 were included in the study. The primary outcome measured in the study was the prevalence of cirrhosis 2011-2018., Results: Among the 371,482 patients with cirrhosis, the mean age was 62.2 (±13.7) years; 53.3% had commercial insurance and 46.4% had Medicare Advantage. The most frequent cirrhosis etiologies were alcohol-related (26.0%), NASH (20.9%) and HCV (20.0%). Mean time of follow-up was 725 (±732.3) days. The observed cirrhosis prevalence was 0.71% in 2018, a 2-fold increase from 2012 (0.34%). The highest prevalence observed was among patients with Medicare Advantage insurance (1.67%) in 2018. Prevalence increased in each US. state, with Southern states having the most rapid rise (2.3-fold). The most significant increases were observed in patients with NASH (3.9-fold) and alcohol-related (2-fold) cirrhosis., Conclusion: Between 2012-2018, the prevalence of liver cirrhosis doubled among insured patients. Alcohol-related and NASH cirrhosis were the most significant contributors to this increase. Patients living in the South, and those insured by Medicare Advantage also have disproportionately higher prevalence of cirrhosis. Public health interventions are important to mitigate this concerning trajectory of strain to the health system., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. Lisa VanWagner serves as an advisor for Numares, Novo-Nordisk and Gerson Lehrman Group, receives grant support from W.L. Gore & Associates and provides expert witness services outside the submitted work. Other authors have no competing interests to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials, (Copyright: © 2024 Ladner et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: To describe changes in antidiabetic medication (ADM) use and characteristics associated with changes in ADM use after initiation of noninsulin second-line therapy., Study Design: Retrospective cohort study., Methods: This study analyzed private health plan claims for adults with type 2 diabetes who initiated 1 of 5 index ADM classes: sulfonylureas, dipeptidyl peptidase 4 inhibitors (DPP4is), sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), or thiazolidinediones. Analyses evaluated 3 treatment modification outcomes-discontinuation, switching, and intensification-over 12-month follow-up., Results: Of 82,624 included adults, nearly two-thirds (63.6%) experienced any treatment modification. Discontinuation was the most common modification (38.6%), especially among patients prescribed GLP-1 RAs (50.3%). Switching occurred in 5.2% of patients and intensification in 19.8%. In adjusted analysis, compared with patients prescribed sulfonylureas, discontinuation risk was 7% higher (HR, 1.07; 95% CI, 1.04-1.10) among patients prescribed DPP4is and 28% higher (HR, 1.28; 95% CI, 1.23-1.33) among patients prescribed GLP-1 RAs. Compared with sulfonylureas, all other index ADM classes had higher risks of switching and lower risks of intensification. Younger age group and female sex were both associated with higher risks of all modifications. Compared with index ADM prescription by a family medicine or internal medicine physician, index prescription by an endocrinologist was associated with both lower discontinuation risk and higher intensification risk., Conclusions: Most patients experienced a treatment modification within 1 year. Results highlight the need for new prescribing approaches and patient supports that can maximize medication adherence and reduce health system waste.

Introduction: Menu calorie labeling has been implemented in food service businesses to promote healthy food choices; however, evidence is limited on whether label use is associated with healthier dietary intake. This study examined the association between menu calorie label use and diet quality and whether it varied by weight status., Methods: Adults in the National Health and Nutrition Examination Survey 2017-2018 who visited restaurants were included. Menu calorie label use was categorized as did not notice labels, noticed labels, and used labels. Diet quality was measured using the Healthy Eating Index 2015 (maximum score 100) by two 24-hour diet recalls. The association between menu calorie label use and diet quality was examined using multiple linear regression and tested for effect modification by weight status. Data were collected during 2017-2018 and analyzed during 2022-2023., Results: Of 3,312 participants (representing 195,167,928 U.S. adults), 43% did not notice labels, 30% noticed labels, and 27% used labels. Using labels was associated with 4.0 points (95% CI 2.2, 5.8) higher Healthy Eating Index 2015 scores than not noticing labels. Healthy Eating Index 2015 scores in those using labels were higher for adults with normal BMI (3.4 points; 95% CI=0.2, 6.7), overweight (6.5 points; 95% CI=3.6, 9.5), and obesity (3.0 points; 95% CI=1.0, 5.1) (p-interaction=0.0004) than those who did not notice labels., Conclusions: Using menu calorie labels was associated with modestly healthier diet quality than not noticing labels, regardless of weight status. This suggests that providing caloric information may help some adults with food decisions., (Copyright © 2023 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: In 2021, the U.S. Preventive Services Task Force (USPSTF) recommended screening for prediabetes and diabetes among adults aged 35-70 years with overweight or obesity. Studying dysglycemia screening in federally qualified health centers (FQHCs) that serve vulnerable patient populations is needed to understand health equity implications of this recommendation., Objective: To investigate screening practices among FQHC patients who would be eligible according to the 2021 USPSTF recommendation., Design: Retrospective cohort study analyzing electronic health records from a national network of 282 FQHC sites., Participants: We included 183,329 patients without prior evidence of prediabetes or diabetes, who had ≥ 1 office visit from 2018-2020., Main Measures: Screening eligibility was based on age and measured body mass index (BMI). The primary outcome, screening completion, was ascertained using hemoglobin A1c or fasting plasma glucose results from 2018-2020., Key Results: Among 89,543 patients who would be eligible according to the 2021 USPSTF recommendation, 53,263 (59.5%) were screened. Those who completed screening had higher BMI values than patients who did not (33.0 ± 6.7 kg/m 2 vs. 31.9 ± 6.2 kg/m 2 , p < 0.001). Adults aged 50-64 years had greater odds of screening completion relative to younger patients (OR 1.13, 95% CI: 1.10-1.17). Patients from racial and ethnic minority groups, as well as those without health insurance, were more likely to complete screening than White patients and insured patients, respectively. Clinical risk factors for diabetes were also associated with dysglycemia screening. Among patients who completed screening, 23,588 (44.3%) had values consistent with prediabetes or diabetes., Conclusions: Over half of FQHC patients who would be eligible according to the 2021 USPSTF recommendation were screened. Screening completion was higher among middle-aged patients, those with greater BMI values, as well as vulnerable groups with a high risk of developing diabetes. Future research should examine adoption of the 2021 USPSTF screening recommendation and its impact on health equity., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Introduction: The American Diabetes Association (ADA) recommends screening for prediabetes and diabetes (dysglycemia) starting at age 35, or younger than 35 years among adults with overweight or obesity and other risk factors. Diabetes risk differs by sex, race, and ethnicity, but performance of the recommendation in these sociodemographic subgroups is unknown., Methods: Nationally representative data from the National Health and Nutrition Examination Surveys (2015-March 2020) were analyzed from 5,287 nonpregnant US adults without diagnosed diabetes. Screening eligibility was based on age, measured body mass index, and the presence of diabetes risk factors. Dysglycemia was defined by fasting plasma glucose ≥100mg/dL (≥5.6 mmol/L) or haemoglobin A1c ≥5.7% (≥39mmol/mol). The sensitivity, specificity, and predictive values of the ADA screening criteria were examined by sex, race, and ethnicity., Results: An estimated 83.1% (95% CI=81.2-84.7) of US adults were eligible for screening according to the 2023 ADA recommendation. Overall, ADA's screening criteria exhibited high sensitivity [95.0% (95% CI=92.7-96.6)] and low specificity [27.1% (95% CI=24.5-29.9)], which did not differ by race or ethnicity. Sensitivity was higher among women [97.8% (95% CI=96.6-98.6)] than men [92.4% (95% CI=88.3-95.1)]. Racial and ethnic differences in sensitivity and specificity among men were statistically significant ( P =0.04 and P =0.02, respectively). Among women, guideline performance did not differ by race and ethnicity., Discussion: The ADA screening criteria exhibited high sensitivity for all groups and was marginally higher in women than men. Racial and ethnic differences in guideline performance among men were small and unlikely to have a significant impact on health equity. Future research could examine adoption of this recommendation in practice and examine its effects on treatment and clinical outcomes by sex, race, and ethnicity., Competing Interests: SB has received consultant fees from Lundbeck, Luto, Pfizer, and Sanofi. SB has received research support from Eli Lilly, Gordon and Betty Moore Foundation, Lundbeck, Merk, Pfizer, and Retirement Research Foundation for Aging. RA has received consultant fees from UnitedHealth Group. MA has received advisory panel support from Bayer AG and research support from Merk. All potential financial dualities of interest reported here were unrelated to the current study. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 O’Brien, Zhang, Bailey, Khan, Ackermann, Ali, Bowen, Benoit, Imperatore, Holliday and McKeever Bullard.)

Background: Among 96 million U.S. adults with prediabetes, adoption of evidence-based treatment to prevent diabetes remains low. Primary care represents an essential venue for preventing diabetes, yet providers in this setting have limited time to address prevention. This highlights the need for low-touch interventions that promote diabetes prevention and are not delivered by primary care providers. Text messaging and decision aids displaying disease risk and treatment information have improved outcomes in prior research. However, these approaches have not been definitively studied for managing prediabetes., Methods: The Behavioral Nudges for Diabetes Prevention (BEGIN) trial is a pragmatic, cluster randomized trial testing the effectiveness of text messaging about diabetes prevention and a prediabetes decision aid. These interventions are being studied in 8 primary care clinics using a 2 × 2 factorial design, in which pairs of clinics are randomized in a 1:1:1:1 ratio to receive usual care, text messaging alone, prediabetes decision aid alone, or both interventions. A total of 656 patients are recruited to participate, receive the study interventions, and contribute data at baseline and 12 months. The primary outcome is 12-month weight change, and the secondary outcome is adoption of evidence-based treatment to prevent diabetes. Change in hemoglobin A1c is an exploratory outcome that will be assessed among participants with available values., Conclusion: Findings from the BEGIN trial will provide evidence about the effectiveness of two novel, low-touch interventions focused on diabetes prevention in primary care, where patients are diagnosed with prediabetes and there is little prior research., Trial Registry: NCT04869917., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Ackerman has received consultant fees from UnitedHealth Group unrelated to this study. The other authors have no potential competing financial interests., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Introduction: In 2021, the U.S. Preventive Services Task Force (USPSTF) recommended prediabetes and diabetes screening for asymptomatic adults aged 35-70 years with overweight/obesity, lowering the age from 40 years in its 2015 recommendation. The USPSTF suggested considering earlier screening in racial and ethnic groups with high diabetes risk at younger ages or lower BMI. This study examined the clinical performance of these USPSTF screening recommendations as well as alternative age and BMI cutoffs in the U.S. adult population overall, and separately by race and ethnicity., Methods: Nationally representative data were collected from 3,243 nonpregnant adults without diagnosed diabetes in January 2017-March 2020 and analyzed from 2021 to 2022. Screening eligibility was based on age and measured BMI. Collectively, prediabetes and undiagnosed diabetes were defined by fasting plasma glucose ≥100 mg/dL or hemoglobin A 1c ≥5.7%. The sensitivity, specificity, and predictive values of alternate screening criteria were examined overall, and by race and ethnicity., Results: The 2021 criteria exhibited marginally higher sensitivity (58.6%, 95% CI=55.5, 61.6 vs 52.9%, 95% CI=49.7, 56.0) and lower specificity (69.3%, 95% CI=65.7, 72.2 vs 76.4%, 95% CI=73.3, 79.2) than the 2015 criteria overall, and within each racial and ethnic group. Screening at lower age and BMI thresholds resulted in even greater sensitivity and lower specificity, especially among Hispanic, non-Hispanic Black, and Asian adults. Screening all adults aged 35-70 years regardless of BMI yielded the most equitable performance across all racial and ethnic groups., Conclusions: The 2021 USPSTF screening criteria will identify more adults with prediabetes and diabetes in all racial and ethnic groups than the 2015 criteria. Screening all adults aged 35-70 years exhibited even higher sensitivity and performed most similarly by race and ethnicity, which may further improve early detection of prediabetes and diabetes in diverse populations., (Copyright © 2023 American Journal of Preventive Medicine. All rights reserved.)

Aims: There is limited research using real-world data to evaluate protective cardiovascular effects of glucagon-like peptide-1 (GLP-1) agonists among adults with type 2 diabetes (T2D) early in treatment., Materials and Methods: We conducted a retrospective, active comparator cohort study using 2011-2015 administrative claims data to compare cardiovascular disease (CVD) event rates following initiation of exenatide extended-release (E-ER), exenatide immediate-release (E-IR) or liraglutide in T2D adults who previously received no other antidiabetic medication (ADM) except metformin. The primary outcome was time to first major adverse CVD event (ischaemic heart disease, stroke, congestive heart failure or peripheral arterial disease) after starting GLP-1. Cox proportional hazards regression was used to model the association between index GLP-1 and CVD events, adjusting for baseline patient, prescriber and plan characteristics. Primary analyses included all patients with ≥2 prescription fills for the index GLP-1, regardless of subsequent refill adherence or initiation of other ADM after index date., Results: Compared with liraglutide, neither E-ER nor E-IR was associated with risk of composite major CVD events (hazard ratios [HRs] for E-ER and E-IR: 1.33 [95% C.I. 0.73-2.39] and 1.30 [0.81-2.09]). No associations were observed between event rates for individual CVD components. The HR for an ischaemic event with E-IR relative to liraglutide was 1.85 (95% C.I. 0.97-3.53). Adjusting for time-varying exposure to other ADM and CVD medications after index date produced similar results., Conclusions: Initiating either immediate or extended-release exenatide rather than liraglutide was not associated with significant differences in CVD risk in this observational real-world study., (© 2023 The Authors. Endocrinology, Diabetes & Metabolism published by John Wiley & Sons Ltd.)

Background: Multidisciplinary transitional care services reduce readmissions for high-risk patients, but it is unclear if health system costs to offer these intensive services are offset by avoidance of higher downstream expenditures., Objective: To evaluate net costs for a health system offering transitional care services DESIGN: One-year pragmatic, randomized trial PARTICIPANTS: Adults aged ≥ 18 without a usual source of follow-up care at the time of hospital discharge were enrolled through a high-volume, urban academic medical center in Chicago, IL, USA, from September 2015 through February 2016., Interventions: Eligible patients were silently randomized before discharge by an automated electronic health record algorithm allocating them in a 1:3 ratio to receive routine coordination of post-discharge care (RC) versus being offered intensive, multidisciplinary transitional care (TC) services., Main Measurements: Health system costs were collected from facility administrative systems and transformed to standardized costs using Medicare reference files. Multivariable generalized linear models estimated proportional differences in net costs over one year., Key Results: Study patients (489 TC; 164 RC) had a mean age of 44 years; 34% were uninsured, 55% had public insurance, and 49% self-identified as Black or Latinx. Over 90 days, cost differences between groups were not statistically significant. Over 180 days, the TC group had 41% lower ED/observation costs (adjusted cost ratio [aCR], 0.59; 95% CI, 0.36-0.97), 50% lower inpatient costs (aCR, 0.50; 95% CI, 0.27-0.95), and 41% lower total healthcare costs (aCR, 0.59; 95% CI, 0.36-0.99) than the RC group. Over 365 days, total cost differences remained of similar magnitude but no longer were statistically significant., Conclusions: Offering TC services for vulnerable adults at discharge reduced net health system expenditures over 180 days. The promising economic case for multidisciplinary transitional care interventions warrants further research., Trial Registration: National Clinical Trials Registry (NCT03066492)., (© 2022. The Author(s) under exclusive licence to Society of General Internal Medicine.)

This study tested the preliminary effectiveness of an electronic health record (EHR)-automated population health management (PHM) intervention for smoking cessation among adult patients of a federally qualified health center in Chicago. Participants (N = 190; 64.7% women, 82.1% African American/Black, 8.4% Hispanic/Latino) were self-identified as smokers, as documented in the EHR, who completed the baseline survey of a longitudinal "needs assessment of health behaviors to strengthen health programs and services." Four weeks later, participants were randomly assigned to the PHM intervention (N = 97) or enhanced usual care (EUC; N = 93). PHM participants were mailed a single-page self-determination theory (SDT)-informed letter that encouraged smoking cessation or reduction as an initial step. The letter also addressed low health literacy and low income. PHM participants also received automated text messages on days 1, 5, 8, 11, and 20 after the mailed letter. Two weeks after mailing, participants were called by the Illinois Tobacco Quitline. EUC participants were e-referred following a usual practice. Participants reached by the quitline were offered behavioral counseling and nicotine replacement therapy. Outcome assessments were conducted at weeks 6, 14, and 28 after the mailed letter. Primary outcomes were treatment engagement, utilization, and self-reported smoking cessation. In the PHM arm, 25.8% of participants engaged in treatment, 21.6% used treatment, and 16.3% were abstinent at 28 weeks. This contrasts with no quitline engagement among EUC participants, and a 6.4% abstinence rate. A PHM approach that can reach all patients who smoke and address unique barriers for low-income individuals may be a critical supplement to clinic-based care., (© Society of Behavioral Medicine 2022. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Patient-reported outcomes-symptoms, treatment side effects, and health-related quality of life-are important to consider in chronic illness care. The increasing availability of health IT to collect patient-reported outcomes and integrate results within the electronic health record provides an unprecedented opportunity to support patients' symptom monitoring, shared decision-making, and effective use of the health care system., Objective: The objectives of this study are to co-design a dashboard that displays patient-reported outcomes along with other clinical data (eg, laboratory tests, medications, and appointments) within an electronic health record and conduct a longitudinal demonstration trial to evaluate whether the dashboard is associated with improved shared decision-making and disease management outcomes., Methods: Co-design teams comprising study investigators, patients with advanced cancer or chronic kidney disease, their care partners, and their clinicians will collaborate to develop the dashboard. Investigators will work with clinic staff to implement the co-designed dashboard for clinical testing during a demonstration trial. The primary outcome of the demonstration trial is whether the quality of shared decision-making increases from baseline to the 3-month follow-up. Secondary outcomes include longitudinal changes in satisfaction with care, self-efficacy in managing treatments and symptoms, health-related quality of life, and use of costly and potentially avoidable health care services. Implementation outcomes (ie, fidelity, appropriateness, acceptability, feasibility, reach, adoption, and sustainability) during the co-design process and demonstration trial will also be collected and summarized., Results: The dashboard co-design process was completed in May 2020, and data collection for the demonstration trial is anticipated to be completed by the end of July 2022. The results will be disseminated in at least one manuscript per study objective., Conclusions: This protocol combines stakeholder engagement, health care coproduction frameworks, and health IT to develop a clinically feasible model of person-centered care delivery. The results will inform our current understanding of how best to integrate patient-reported outcome measures into clinical workflows to improve outcomes and reduce the burden of chronic disease on patients and health care systems., International Registered Report Identifier (irrid): DERR1-10.2196/38461., (©Laura M Perry, Victoria Morken, John D Peipert, Betina Yanez, Sofia F Garcia, Cynthia Barnard, Lisa R Hirschhorn, Jeffrey A Linder, Neil Jordan, Ronald T Ackermann, Alexandra Harris, Sheetal Kircher, Nisha Mohindra, Vikram Aggarwal, Rebecca Frazier, Ava Coughlin, Katy Bedjeti, Melissa Weitzel, Eugene C Nelson, Glyn Elwyn, Aricca D Van Citters, Mary O'Connor, David Cella. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 21.09.2022.)

Prediabetes impacts 88 million U.S. adults, yet uptake of evidence-based treatment with intensive lifestyle interventions and metformin remains exceedingly low. After incorporating feedback from 15 primary care providers collected during semi-structured interviews, we developed a novel Prediabetes Clinical Decision Support (PreDM CDS) from August 2019 to February 2020. This tool included order options enabling prediabetes management in a single location within the electronic health record. We conducted a retrospective observational study examining the feasibility of implementing this tool at Erie Family Health Centers, a large community health center, examining its use and related outcomes among patients for whom it was used vs not. Overall, 7,424 eligible patients were seen during the implementation period (February 2020 to August 2021), and the PreDM CDS was used for 108 (1.5 %). Using the PreDM CDS was associated with higher rates of hemoglobin A1c orders (70.4 % vs 22.2 %; p < 0.001), lifestyle counseling (38.0 % vs 7.8 %; p < 0.001), and metformin prescription orders (5.6 % vs 2.6 %; p = 0.06). Exploratory analyses revealed small, nonsignificant weight loss among patients for whom the PreDM CDS was used. This study demonstrates the feasibility of developing and implementing the PreDM CDS in primary care. Its low use was likely related to not imposing an interruptive 'pop-up' alert, as well as major changes in workflows and clinical priorities during the Covid-19 pandemic. Use of the tool was associated with improved process outcomes. Future efforts with the PreDM CDS should follow standard CDS implementation processes that were not possible due to the Covid-19 pandemic., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Author(s).)

Purpose of Review: Diabetes is an ongoing public health issue in the USA, and, despite progress, recent reports suggest acute and chronic diabetes complications are increasing., Recent Findings: The Natural Experiments for Translation in Diabetes 3.0 (NEXT-D3) Network is a 5-year research collaboration involving six academic centers (Harvard University, Northwestern University, Oregon Health & Science University, Tulane University, University of California Los Angeles, and University of California San Francisco) and two funding agencies (Centers for Disease Control and Prevention and National Institutes of Health) to address the gaps leading to persisting diabetes burdens. The network builds on previously funded networks, expanding to include type 2 diabetes (T2D) prevention and an emphasis on health equity. NEXT-D3 researchers use rigorous natural experiment study designs to evaluate impacts of naturally occurring programs and policies, with a focus on diabetes-related outcomes. NEXT-D3 projects address whether and to what extent federal or state legislative policies and health plan innovations affect T2D risk and diabetes treatment and outcomes in the USA; real-world effects of increased access to health insurance under the Affordable Care Act; and the effectiveness of interventions that reduce barriers to medication access (e.g., decreased or eliminated cost sharing for cardiometabolic medications and new medications such as SGLT-2 inhibitors for Medicaid patients). Overarching goals include (1) expanding generalizable knowledge about policies and programs to manage or prevent T2D and educate decision-makers and organizations and (2) generating evidence to guide the development of health equity goals to reduce disparities in T2D-related risk factors, treatment, and complications., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: The benefits of moderate to vigorous physical activity (MVPA) for breast cancer survivors are well established. However, most are insufficiently active. Fit2Thrive used the Multiphase Optimization Strategy methodology to determine the effect of 5 intervention components on MVPA in this population., Methods: Two hundred sixty-nine participants (mean age, 52.5 years; SD, 9.9 years) received a core intervention (the Fit2Thrive self-monitoring app and Fitbit) and were randomly assigned to 5 intervention components set to on/off in a full factorial experiment: support calls, deluxe app, buddy, online gym, and text messages. The intervention was delivered over 12 weeks with a 12-week follow-up. MVPA was measured via accelerometry at the baseline (T1), at 12 weeks (T2), and at 24 weeks (T3). The main effects and interaction effects at each time point were examined for all components., Results: Trial retention was high: 91.8% had valid accelerometer data at T2 or T3. Across all conditions, there were significant increases in MVPA (+53.6 min/wk; P < .001) and in the proportion of survivors meeting MVPA guidelines (+22.3%; P < .001) at T2 that were maintained but attenuated at T3 (MVPA, +24.6 min/wk; P < .001; meeting guidelines, +12.6%; P < .001). No individual components significantly improved MVPA, although increases were greater for the on level versus the off level for support calls, buddy, and text messages at T2 and T3., Conclusions: The Fit2Thrive core intervention (the self-monitoring app and Fitbit) is promising for increasing MVPA in breast cancer survivors, but the components provided no additional increases in MVPA. Future research should evaluate the core intervention in a randomized trial and determine what components optimize MVPA behaviors in breast cancer survivors., (© 2021 American Cancer Society.)

Background: Antidiabetic medications (ADM), especially sulfonylureas (SFU) and basal insulin (BI), are associated with increased risk of hypoglycemia, which is especially concerning among older adults in poor health. The objective of this study was to investigate prescribing patterns of ADM in older adults according to their health status., Methods: This case control study analyzed administrative claims between 2013 and 2017 from a large national payer. The study population was derived from a nationwide database of 84,720 U.S. adults aged ≥65, who were enrolled in Medicare Advantage health insurance plans. Participants had type 2 diabetes on metformin monotherapy, and started a second-line ADM during the study period. The exposure was a binary variable for health status, with poor health defined by end-stage medical conditions, dementia, or residence in a long-term nursing facility. The outcome was a variable identifying which second-line ADM class was started, categorized as SFU, BI, or other (i.e. all other ADM classes combined)., Results: Over half of participants (54%) received SFU as initial second-line ADM, 14% received BI, and 32% received another ADM. In multivariable models, the odds of filling SFU or BI was higher for participants in poor health than those in good or intermediate health [OR 1.13 (95% CI 1.05-1.21) and OR 2.34 (95% CI 2.14-2.55), respectively]. SFU and BI were also more commonly filled by older adults with poor glycemic control., Conclusions: Despite clinical consensus to use caution prescribing SFU and BI among older adults in poor health, these medications remain frequently used in this particularly vulnerable population., (© 2022. The Author(s).)

This pilot trial studied a novel intervention that integrated diabetes technologies into team-based primary care for type 2 diabetes. We found clinically significant reductions in blood pressure, weight, and glucose. The latter two were statistically significant., (Copyright © 2021. Published by Elsevier Ltd.)

Purpose: The purpose of this study was to examine the development and preliminary effectiveness of a novel Prediabetes Decision Aid on adoption of intensive lifestyle interventions (ILIs) and metformin. Little research has focused on increasing uptake of these evidence-based treatments, especially among non-English speakers and those with low educational attainment., Methods: Investigators developed an English and Spanish decision aid displaying information about type 2 diabetes (T2DM) risk and treatments to prevent T2DM and prompting patients to identify next steps for management. This pilot study was a single-arm, pretest-posttest trial of 40 adult patients with prediabetes, obesity, and ≥1 office visit within the prior 12 months. Participants reviewed this tool briefly with a study team member, and data were collected on 3 coprimary outcomes: knowledge about T2DM risk, decisional conflict, and intention to adopt treatment. Exploratory outcomes included subsequent documentation of prediabetes in chart notes and adoption of ILIs or metformin., Results: Almost all participants were women, with nearly half expressing Spanish language preference and low educational attainment. A nonsignificant increase in knowledge was observed across all subgroups. Decisional conflict was significantly reduced from pretest to posttest and was similar between subgroups defined by language preference and educational attainment. While intention to adopt ILIs increased across all subgroups, this change was only significant among Spanish speakers and participants with low educational attainment. At 6 months, 17 participants had subsequent provider documentation of prediabetes, and 12 adopted ILIs or metformin., Conclusions: The decision aid improved patient-reported outcomes and promoted treatment adoption in a diverse patient sample.

Objectives: To examine differences in health care costs associated with choice of second-line antidiabetes medication (ADM) for commercially insured adults with type 2 diabetes., Study Design: Retrospective cohort study with multiple pretests and posttests., Methods: Included patients initiated second-line ADM therapy between 2011 and 2015, with variable follow-up through 2017. The 6 index medication classes were sulfonylureas, dipeptidyl peptidase-4 (DPP-4) inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1 RAs), basal insulin, sodium-glucose cotransporter-2 (SGLT-2) inhibitors, and thiazolidinediones (TZDs). Multivariable regression models compared between-class changes in adjusted quarterly costs after second-line ADM initiation., Results: The study cohort included 34,963 adults. Most were prescribed a sulfonylurea (46.0%) or DPP-4 inhibitor (30.4%). Adjusted quarterly index medication costs were significantly higher for all patients receiving nonsulfonylurea medications, ranging from $108 (95% CI, $99-$118) for TZDs to $742 (95% CI, $720-$765) for GLP-1 RAs. Changes in quarterly total health care costs were significantly higher for all nonsulfonylurea classes. Conversely, changes in quarterly nonpharmacy medical costs were significantly lower for patients receiving DPP-4 inhibitors (-$67; 95% CI, -$92 to -$43), GLP-1 RAs (-$43; 95% CI, -$85 to -$1), and SGLT-2 inhibitors (-$46; 95% CI, -$87 to -$6); changes in all other quarterly costs besides the index medication were significantly lower for patients receiving DPP-4 inhibitors (-$60; 95% CI, -$94 to -$26) and SGLT-2 inhibitors (-$113; 95% CI, -$169 to -$57)., Conclusions: The higher cost of nonsulfonylurea medications was the main driver of relative increases in total costs. Relative decreases in nonpharmacy medical costs among patients receiving newer ADM classes reflect these medications' potential value.

Purpose of Review: Type 2 diabetes is common, burdensome, and preventable. Landmark trials such as the Diabetes Prevention Program (DPP) demonstrated that resource-intensive lifestyle support interventions resulting in modest weight loss via healthy diet changes and physical activity can lower the rate of diabetes development by 58%. We performed a review of efforts to translate and implement DPP-like programs throughout the USA to identify challenges and opportunities for improvement., Recent Findings: For more than a decade, multiple stakeholders have worked to translate evidence-based principles of diabetes prevention to reach 84 million Americans with prediabetes. DPP-like programs have been delivered by over 1500 organizations, reaching almost 300,000 people, but this number represents less than 1% of the target population. Research has uncovered large gaps in efforts to diagnose, raise awareness, and provide access to DPP-like programs for adults with prediabetes, requiring further stakeholder engagement and coordination to resolve. Efforts to address prevailing gaps in diabetes prevention must address distinct and sometimes conflicting priorities and concerns of stakeholders. Our review recommends several areas of further research and action to improve type 2 diabetes prevention on a population scale.

Objective: Lifestyle interventions slow development of type 2 diabetes by half, but the impact of health payer reimbursement for delivery of intervention programs is not well known. We evaluated net commercial health payer expenditures when offering reimbursement for access to YMCA's Diabetes Prevention Program (YDPP) in 42 states., Research Design and Methods: We used a nonequivalent comparison group design to evaluate net health care expenditures for adults with prediabetes who attended one or more YDPP visit between 1 July 2009 and 31 May 2013 ("YDPP users"). Rolling, 1:1 nearest neighbor propensity score (PS) matching was used to identify a comparison group of nonusers. Administrative data provided measures of YDPP attendance, body weight at YDPP visits, and health care expenditures. Random effects, difference-in-difference regression was used to estimate quarterly health care expenditures before and after participants' first visit to YDPP., Results: Worksite screening identified 9.7% of the target population; 39.1% of those identified (19,933 participants through June 2015) became YDPP users. Mean weight loss for YDPP users enrolled before June 2013 ( n = 1,725) was 7.5 lb (3.4%); 29% achieved ≥5% weight loss. Inclusive of added costs to offer YDPP, there were no statistically significant differences in mean per-person net health care expenditures between YDPP users and PS-matched nonusers over 2 years ($0.2 lower [95% CI $56 lower to $56 higher]). Mean reimbursement to the YMCA was $212 per YDPP user, with 92.8% of all expenditures made for those who attended at a high rate (≥9 completed YDPP visits)., Conclusions: Worksite screening was inefficient for identifying the population with prediabetes, but those identified achieved modest YDPP attendance and clinically meaningful weight loss. Over 2 years, added costs to offer the intervention were modest, with neutral effects on net health care costs., (© 2019 by the American Diabetes Association.)

Background: There is limited experimental evidence on transitional care interventions beyond 30 days post-discharge and in vulnerable populations., Objective: Evaluate effects of a transitional care practice (TC) that comprehensively addresses patients' medical and psychosocial needs following hospital discharge., Design: Pragmatic, randomized comparative effectiveness trial., Patients: Adults discharged from an initial emergency, observation, or inpatient hospital encounter with no trusted usual source of care., Interventions: TC intervention included a scheduled post-discharge appointment at the TC practice, where a multidisciplinary team comprehensively assessed patients' medical and psychosocial needs, addressed modifiable barriers, and subsequent linkage to a new primary care source. Routine Care involved assistance scheduling a post-discharge appointment with a primary care provider that often partnered with the hospital where the initial encounter occurred., Main Measures: The primary outcome was a binary indicator of death or additional hospital encounters within 90 days of initial discharge. Secondary outcomes included any additional hospital encounters, and counts of hospital encounters, over 180 days., Key Results: Four hundred ninety patients were randomized to TC intervention and 164 to Routine Care; 34.6% were uninsured, 49.7% had Medicaid, and 57.4% were homeless or lived in a high-poverty area. There was no significant difference between arms in the 90-day probability of death or additional hospital encounters (relative risk [RR] 0.89; 0.91; 95% confidence interval [CI] 0.74-1.13). However, TC patients had 37% and 35% lower probability of any inpatient admission over 90 days (RR 0.63; 95% CI 0.43-0.91) and 180 days (RR 0.65; 95% CI 0.47-0.89), respectively. Over 180 days, TC patients had 42% fewer inpatient admissions (incidence rate ratio 0.58; 95% CI 0.37-0.90)., Conclusions: Among patients randomized to a patient-centered transitional care intervention, there was no significant reduction in 90-day probability of death or additional hospital encounters. However, there were significant decreases in measures of inpatient admissions over 180 days., Trial Registration: clinicaltrials.gov identifier NCT03066492.

Purpose: Despite the benefits of physical activity for breast cancer survivors, the majority remain insufficiently active. Mobile health (mHealth) physical activity interventions may be a more scalable strategy to increase activity among survivors. However, little is known about their preferences for mHealth intervention features. This study explored survivors' preferences for these features., Methods: Survivors (N = 96; M age  = 55.8 (SD = 10.2)) self-reported demographic and disease characteristics, physical activity. A subset (n = 28) completed a semi-structured phone interview. Transcribed interviews were evaluated using a thematic content analysis approach and consensus review. Following interviews, the full sample self-reported interests and preferences for intervention features via online questionnaires. Quantitative data were analyzed using descriptive statistics., Results: Five themes emerged from interview data: (1) importance of relevance to breast cancer survivors; (2) easy to use; (3) integration with wearable activity trackers; (4) provide sense of accomplishment; and (5) variability in desired level of structure and personalization. The highest ranked intervention features were: daily and weekly progress feedback (87.5%), newsfeed (86.6%), activity challenges (81.3%), and scheduling tool (79.2%). Survivors were interested in receiving progress feedback (80.2%) and motivational (78.1%) and reminder (75.0%) messages., Conclusions: Breast cancer survivors are interested in mHealth physical activity promotion interventions, but preferences varied around themes of relevance, ease of use, and enhancing personal motivation., Implications for Cancer Survivors: Engaging survivors in developing and implementing remotely delivered mHealth activity promotion interventions may enhance their effectiveness.

Importance: Understanding cardiovascular outcomes of initiating second-line antidiabetic medications (ADMs) may help inform treatment decisions after metformin alone is not sufficient or not tolerated. To date, no studies have compared the cardiovascular effects of all major second-line ADMs during this early decision point in the pharmacologic management of type 2 diabetes., Objective: To examine the association of second-line ADM classes with major adverse cardiovascular events., Design, Setting, and Participants: Retrospective cohort study among 132 737 insured adults with type 2 diabetes who started therapy with a second-line ADM after taking either metformin alone or no prior ADM. This study used 2011-2015 US nationwide administrative claims data. Data analysis was performed from January 2017 to October 2018., Exposures: Dipeptidyl peptidase 4 (DPP-4) inhibitors, glucagon-like peptide-1 (GLP-1) receptor agonists, sodium-glucose cotransporter 2 (SGLT-2) inhibitors, thiazolidinediones (TZDs), basal insulin, and sulfonylureas or meglitinides (both referred to as sulfonylureas hereafter). The DPP-4 inhibitors served as the comparison group in all analyses., Main Outcomes and Measures: The primary outcome was time to first cardiovascular event after starting the second-line ADM. This composite outcome was based on hospitalization for the following cardiovascular conditions: congestive heart failure, stroke, ischemic heart disease, or peripheral artery disease., Results: Among 132 737 insured adult patients with type 2 diabetes (men, 55%; aged 45-64 years, 58%; white, 63%), there were 3480 incident cardiovascular events during 169 384 person-years of follow-up. Patients were censored after the first cardiovascular event, discontinuation of insurance coverage, transition from International Classification of Diseases, Ninth Revision (ICD-9) to end of ICD-9 coding, or 2 years of follow-up. After adjusting for patient, prescriber, and health plan characteristics, the risk of composite cardiovascular events after starting GLP-1 receptor agonists was lower than DPP-4 inhibitors (hazard ratio [HR], 0.78; 95% CI, 0.63-0.96), but this finding was not significant in all sensitivity analyses. Cardiovascular event rates after starting treatment with SGLT-2 inhibitors (HR, 0.81; 95% CI, 0.57-1.53) and TZDs (HR, 0.92; 95% CI, 0.76-1.11) were not statistically different from DPP-4 inhibitors. The comparative risk of cardiovascular events was higher after starting treatment with sulfonylureas (HR, 1.36; 95% CI, 1.23-1.49) or basal insulin (HR, 2.03; 95% CI, 1.81-2.27) than DPP-4 inhibitors., Conclusions and Relevance: Among insured adult patients with type 2 diabetes initiating second-line ADM therapy, the short-term cardiovascular outcomes of GLP-1 receptor agonists, SGLT-2 inhibitors, and DPP-4 inhibitors were similar. Higher cardiovascular risk was associated with use of sulfonylureas or basal insulin compared with newer ADM classes. Clinicians may consider prescribing GLP-1 receptor agonists, SGLT-2 inhibitors, or DPP-4 inhibitors more routinely after metformin rather than sulfonylureas or basal insulin.

Purpose of Review: To advance our understanding of the impacts of policies and programs aimed at improving detection, engagement, prevention, and clinical diabetes management in the USA, we synthesized findings from a network of studies that used natural experiments to evaluate diabetes health policies and programs., Findings: Studies from the Natural EXperiments for Translation in Diabetes (NEXT-D) network used rigorous longitudinal quasi-experimental study designs (e.g., interrupted time series) and analytical methods (e.g., difference-in-differences) to augment causal inference. Investigators partnered with health system stakeholders to evaluate whether glucose testing rates changed from before-to-after clinic interventions (e.g., integrating electronic screening decision prompts in New York City) or employer programs (e.g., targeted messaging and waiving copayments for at-risk employees). Other studies examined participation and behavior change in low- (e.g., wellness coaching) or high-intensity lifestyle modification programs (e.g., diabetes prevention program-like interventions) offered by payers or employers. Lastly, studies assessed how employer health insurance benefits impacted healthcare utilization, adherence, and outcomes among people with diabetes. NEXT-D demonstrated that low-intensity interventions to facilitate glucose testing and enhance engagement in lifestyle modification were associated with small improvements in weight but large improvements in screening and testing when supported by electronic health record-based decision-support. Regarding high-intensity diabetes prevention program-like lifestyle programs offered by payers or employers, enrollment was modest and led to weight loss and marginally lower short-term health expenditures. Health plans that incentivize patient behaviors were associated with increases in medication adherence. Meanwhile, shifting patients to high-deductible health plans was associated with no change in medication use and preventive screenings, but patients with diabetes delayed accessing healthcare for acute complications (e.g., cellulitis). Findings were more pronounced among lower-income patients, who experienced increased rates and acuity of emergency department visits for diabetes complications and other high-severity conditions. Findings from NEXT-D studies provide informative data that can guide programs and policies to facilitate detection, prevention, and treatment of diabetes in practice.

Purpose of Review: Evidence-based treatments for prediabetes can prevent and delay the development of type 2 diabetes in adults. In this review, we propose a framework for population-based diabetes prevention that links screening and prevention activities across key stakeholders. We also discuss gaps in current practice, while highlighting opportunities to improve diabetes screening and prevention efforts population-wide., Recent Findings: Awareness of diabetes risk is low, and many adults with prediabetes are not identified through existing screening efforts. Accumulating evidence and policies support expansion of the Diabetes Prevention Program (DPP) into clinical and community settings. However, the infrastructure to facilitate referrals and promote data exchange among patients, clinical settings, and community-based DPP programs is lacking. Development of evidence-driven, scalable processes for assessing diabetes risk, screening eligible adults, and delivering preventive treatments are needed to effectively improve the glycemic health of the US adult population.

Background: In 2015, The US Preventive Services Task Force (USPSTF) recommended screening for prediabetes and undiagnosed diabetes (collectively called dysglycemia) among adults aged 40-70 years with overweight or obesity. The recommendation suggests that clinicians consider screening earlier in people who have other diabetes risk factors., Objective: To compare the performance of limited and expanded screening criteria recommended by the USPSTF for detecting dysglycemia among US adults., Design: Cross-sectional analysis of survey and laboratory data collected from nationally representative samples of the civilian, noninstitutionalized US adult population., Participants: A total of 3643 adults without diagnosed diabetes who underwent measurement of hemoglobin A1c (A1c), fasting plasma glucose (FPG), and 2-h plasma glucose (2-h PG)., Main Measures: Screening eligibility according to the limited criteria was based on age 40 to 70 years old and overweight/obesity. Screening eligibility according to the expanded criteria was determined by meeting the limited criteria or having ≥ 1 of the following risk factors: family history of diabetes, history of gestational diabetes or polycystic ovarian syndrome, and non-white race/ethnicity. Dysglycemia was defined by A1c ≥ 5.7%, FPG ≥ 100 mg/dL, and/or 2-h PG ≥ 140 mg/dL., Key Results: Among the US adult population without diagnosed diabetes, 49.7% had dysglycemia. Screening based on the limited criteria demonstrated a sensitivity of 47.3% (95% CI, 44.7-50.0%) and specificity of 71.4% (95% CI, 67.3-75.2%). The expanded criteria yielded higher sensitivity [76.8% (95% CI, 73.5-79.8%)] and lower specificity [33.8% (95% CI, 30.1-37.7%)]. Point estimates for the sensitivity of the limited criteria were lower in all minority groups and significantly different for Asians compared to non-Hispanic whites [29.9% (95% CI, 23.4-37.2%) vs. 49.8% (95% CI, 45.9-53.7%); P < .001]., Conclusions: Diabetes screening that follows the limited USPSTF criteria will identify approximately half of US adults with dysglycemia. Screening other high-risk subgroups defined in the USPSTF recommendation would improve detection of dysglycemia and may reduce associated racial/ethnic disparities.