Development and Validation of the American Heart Association's PREVENT Equations.

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Estimated Glomerular Filtration Rate, Albuminuria, and Adverse Outcomes: An Individual-Participant Data Meta-Analysis.

Importance: Chronic kidney disease (low estimated glomerular filtration rate [eGFR] or albuminuria) affects approximately 14% of adults in the US. Objective: To evaluate associations of lower eGFR based on creatinine alone, lower eGFR based on creatinine combined with cystatin C, and more severe albuminuria with adverse kidney outcomes, cardiovascular outcomes, and other health outcomes. Design, Setting, and Participants: Individual-participant data meta-analysis of 27 503 140 individuals from 114 global cohorts (eGFR based on creatinine alone) and 720 736 individuals from 20 cohorts (eGFR based on creatinine and cystatin C) and 9 067 753 individuals from 114 cohorts (albuminuria) from 1980 to 2021. Exposures: The Chronic Kidney Disease Epidemiology Collaboration 2021 equations for eGFR based on creatinine alone and eGFR based on creatinine and cystatin C; and albuminuria estimated as urine albumin to creatinine ratio (UACR). Main Outcomes and Measures: The risk of kidney failure requiring replacement therapy, all-cause mortality, cardiovascular mortality, acute kidney injury, any hospitalization, coronary heart disease, stroke, heart failure, atrial fibrillation, and peripheral artery disease. The analyses were performed within each cohort and summarized with random-effects meta-analyses. Results: Within the population using eGFR based on creatinine alone (mean age, 54 years [SD, 17 years]; 51% were women; mean follow-up time, 4.8 years [SD, 3.3 years]), the mean eGFR was 90 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 11 mg/g (IQR, 8-16 mg/g). Within the population using eGFR based on creatinine and cystatin C (mean age, 59 years [SD, 12 years]; 53% were women; mean follow-up time, 10.8 years [SD, 4.1 years]), the mean eGFR was 88 mL/min/1.73 m2 (SD, 22 mL/min/1.73 m2) and the median UACR was 9 mg/g (IQR, 6-18 mg/g). Lower eGFR (whether based on creatinine alone or based on creatinine and cystatin C) and higher UACR were each significantly associated with higher risk for each of the 10 adverse outcomes, including those in the mildest categories of chronic kidney disease. For example, among people with a UACR less than 10 mg/g, an eGFR of 45 to 59 mL/min/1.73 m2 based on creatinine alone was associated with significantly higher hospitalization rates compared with an eGFR of 90 to 104 mL/min/1.73 m2 (adjusted hazard ratio, 1.3 [95% CI, 1.2-1.3]; 161 vs 79 events per 1000 person-years; excess absolute risk, 22 events per 1000 person-years [95% CI, 19-25 events per 1000 person-years]). Conclusions and Relevance: In this retrospective analysis of 114 cohorts, lower eGFR based on creatinine alone, lower eGFR based on creatinine and cystatin C, and more severe UACR were each associated with increased rates of 10 adverse outcomes, including adverse kidney outcomes, cardiovascular diseases, and hospitalizations.

Variation in Initiation, Engagement, and Retention on Medications for Opioid Use Disorder Based on Health Insurance Plan Design.

BACKGROUND: The association between cost-sharing and receipt of medication for opioid use disorder (MOUD) is unknown. METHODS: We constructed a cohort of 10,513 commercially insured individuals with a new diagnosis of opioid use disorder and information on insurance cost-sharing in a large national deidentified claims database. We examined 4 cost-sharing measures: (1) pharmacy deductible; (2) medical service deductible; (3) pharmacy medication copay; and (4) medical office copay. We measured MOUD (naltrexone, buprenorphine, or methadone) initiation (within 14 d of diagnosis), engagement (second receipt within 34 d of first), and 6-month retention (continuous receipt without 14-d gap). We used multivariable logistic regression to assess the association between cost-sharing and MOUD initiation, engagement, and retention. We calculated total out-of-pocket costs in the 30 days following MOUD initiation for each type of MOUD. RESULTS: Of 10,513 individuals with incident opioid use disorder, 1202 (11%) initiated MOUD, 742 (7%) engaged, and 253 (2%) were retained in MOUD at 6 months. A high ($1000+) medical deductible was associated with a lower odds of initiation compared with no deductible (odds ratio: 0.85, 95% confidence interval: 0.74-0.98). We found no significant associations between other cost-sharing measures for initiation, engagement, or retention. Median initial 30-day out-of-pocket costs ranged from $100 for methadone to $710 for extended-release naltrexone. CONCLUSIONS: Among insurance plan cost-sharing measures, only medical services deductible showed an association with decreased MOUD initiation. Policy and benefit design should consider ways to reduce cost barriers to initiation and retention in MOUD.

Application of a Tool to Identify Undiagnosed Hypertension - United States, 2016.

Approximately 11 million U.S. adults with a usual source of health care have undiagnosed hypertension, placing them at increased risk for cardiovascular events (1-3). Using data from the National Health and Nutrition Examination Survey (NHANES), CDC developed the Million Hearts Hypertension Prevalence Estimator Tool, which allows health care delivery organizations (organizations) to predict their patient population's hypertension prevalence based on demographic and comorbidity characteristics (2). Organizations can use this tool to compare predicted prevalence with their observed prevalence to identify potential underdiagnosed hypertension. This study applied the tool using medical billing data alone and in combination with clinical data collected among 8.92 million patients from 25 organizations participating in American Medical Group Association (AMGA) national learning collaborative* to calculate and compare predicted and observed adult hypertension prevalence. Using billing data alone revealed that up to one in eight cases of hypertension might be undiagnosed. However, estimates varied when clinical data were included to identify comorbidities used to predict hypertension prevalence or describe observed hypertension prevalence. These findings demonstrate the tool's potential use in improving identification of hypertension and the likely importance of using both billing and clinical data to establish hypertension and comorbidity prevalence estimates and to support clinical quality improvement efforts.

Improving Blood Pressure Control Using Smart Technology.

BACKGROUND: The authors sought to determine if wireless oscillometric home blood pressure monitoring (HBPM) that integrates with smartphone technology improves blood pressure (BP) control among patients with new or existing uncontrolled hypertension (HTN). METHODS: A prospective observational cohort study monitored BP control before and after an educational intervention and introduction to HBPM. Patients in the intervention group were instructed to track their BP using a smartphone device three to seven times per week. Cases were matched to controls at a 1:3 allocation ratio on several clinical characteristics over the same period and received usual care. The proportion of patients with controlled BP was compared between groups at pre- and postintervention, ∼9 months later. Results and Materials: The total study population included 484 patients with mean age 60 years (range 23-102 years), 47.7% female, and 84.6% Caucasian. Mean preintervention BP was 137.8 mm Hg systolic and 81.4 mm Hg diastolic. Mean BP control rates improved for patients who received HBPM from 42% to 67% compared with matched control patients who improved from 59% to 67% (p < 0.01). CONCLUSION: HBPM with smartphone technology has the potential to improve HTN management among patients with uncontrolled or newly diagnosed HTN. Technology needs to be easy to use and operate and would work best when integrated into local electronic health record systems. In systems without this capability, medical assistants or other personnel may be trained to facilitate the process. Nurse navigator involvement was instrumental in bridging communication between the patients and provider.

Development of a Follow-Up Measure to Ensure Complete Screening for Colorectal Cancer.

Importance: The current quality performance measure for colorectal cancer (CRC) screening is limited to initial screening. Despite low rates, there is no measure for appropriate follow-up with colonoscopy after receipt of an abnormal result of a stool-based screening test (SBT) for CRC. A quality performance measure is needed. Objective: To develop and test a quality performance measure for follow-up colonoscopy within 6 months of an abnormal result of an SBT for CRC. Design, Setting, and Participants: This retrospective quality improvement study examined data from January 1, 2016, to December 31, 2020, with 2018 plus 6 months of follow-up as the primary measurement period to verify performance rates, specify a potential measure, and test for validity, reliability, and feasibility. The Optum Labs Data Warehouse (OLDW), a deidentified database of health care claims and clinical data, was accessed. The OLDW contains longitudinal health information on enrollees and patients, representing a diverse mixture of ages and geographic regions across the US. For the database study, adults from 38 health care organizations (HCOs) aged 50 to 75 years who completed an initial CRC SBT with an abnormal result were observed to determine follow-up colonoscopy rates within 6 months. Rates were stratified by race, ethnicity, sex, insurance, and test modality. Three HCOs participated in the feasibility field testing. Data were analyzed from June 1, 2022, to May 31, 2023. Main Outcome and Measures: The primary outcome consisted of follow-up colonoscopy rates following an abnormal SBT result for CRC. Reliability statistics were also calculated across HCOs, race, ethnicity, and measurement year. Results: Among 20 581 adults (48.6% men and 51.4% women; 307 [1.5%] Asian, 492 [7.2%] Black, 644 [3.1%] Hispanic, and 17 705 [86.0%] White; mean [SD] age, 63.6 [7.1] years) in 38 health systems, 47.9% had a follow-up colonoscopy following an abnormal SBT result for CRC within 6 months. There was significant variation between HCOs. Notably, significantly fewer Black patients (37.1% [95% CI, 34.6%-39.5%]) and patients with Medicare (49.2% [95% CI, 47.7%-50.6%]) or Medicaid (39.2% [95% CI, 36.3%-42.1%]) insurance received a follow-up colonoscopy. A quality performance measure that tracks rates of follow-up within 6 months of an abnormal SBT result was observed to be feasible, valid, and reliable, with a median reliability statistic between HCOs of 94.5% (range, 74.3%-99.7%). Conclusions and Relevance: The findings of this observational study of 20 581 adults suggest that a measure of follow-up colonoscopy within defined periods after an abnormal result of an SBT test for CRC is warranted based on low current performance rates and would be feasible to collect by health systems and produce valid, reliable results.

Prevalence of use and characteristics of users of home-based medical care in Medicare Advantage.

BACKGROUND/OBJECTIVES: Home-based medical care (HBMC) is longitudinal medical care provided by physicians, advanced practice providers, and, often, inter-professional care teams to patients in their homes. Our objective is to determine the prevalence of HBMC among older adults (≥65) insured by a Medicare Advantage (MA) plan and compare characteristics of those who receive HBMC to those who do not. METHODS: Study used de-identified medical claims and enrollment records for MA beneficiaries during calendar years 2017 and 2018 linked with socioeconomic status data in the OptumLabs Data Warehouse. We defined a cohort of MA beneficiaries age ≥65 receiving HBMC for at least 2 months during 2017-2018, described the cohort using demographic, utilization, and comorbidity data and compared it to a 5% random sample of a population of MA beneficiaries age ≥65 not receiving HBMC (No HBMC). RESULTS: Overall, 1.45% of the study cohort age ≥65 received HBMC. Compared to No HBMC (n = 132,147), those receiving HBMC (n = 38,800) were more likely to be: older (46.6% vs. 11.9% age 85+); female (70.8% vs. 58.5%); Black (12.3% vs. 11.3%); urban (90.3% vs. 81.3%); experience hospitalization (38.0% vs. 13.3%), emergency department visit (58.3% vs. 26.9%), ambulance trip (44.1% vs. 9.6%), skilled nursing facility (37.6% vs. 6.4%), or hospice care admission (21.1% vs. 3.5%). They also were more likely to experience a wide range of chronic conditions including dementia (58.1% vs. 5.2%), morbidity burden (Charlson score 3.4 vs. 1.8), and serious illness (77.1% vs. 29.5%). All comparisons p < 0.0001. CONCLUSIONS: MA beneficiaries who received HBMC are older, experience greater chronic and serious illness burden, and higher levels of facility-based care than those who did not receive HBMC. MA plans need strategies to identify patients that would benefit from HBMC and develop approaches to deliver such care to this impactful, often invisible population.

Rates of Follow-up Colonoscopy After a Positive Stool-Based Screening Test Result for Colorectal Cancer Among Health Care Organizations in the US, 2017-2020.

Importance: Noninvasive stool-based screening tests (SBTs) are effective alternatives to colonoscopy. However, a positive SBT result requires timely follow-up colonoscopy (FU-CY) to complete the colorectal cancer screening paradigm. Objectives: To evaluate FU-CY rates after a positive SBT result and to assess the association of the early COVID-19 pandemic with FU-CY rates. Design, Setting, and Participants: This mixed-methods cohort study included retrospective analysis of deidentified administrative claims and electronic health records data between June 1, 2015, and June 30, 2021, from the Optum Labs Data Warehouse and qualitative, semistructured interviews with clinicians from 5 health care organizations (HCOs). The study population included data from average-risk primary care patients aged 50 to 75 years with a positive SBT result between January 1, 2017, and June 30, 2020, at 39 HCOs. Main Outcomes and Measures: The primary outcome was the FU-CY rate within 1 year of a positive SBT result according to patient age, sex, race, ethnicity, insurance type, Charlson Comorbidity Index (CCI), and prior SBT use. Results: This cohort study included 32 769 individuals (16 929 [51.7%] female; mean [SD] age, 63.1 [7.1] years; 2092 [6.4%] of Black and 28 832 [88.0%] of White race; and 825 [2.5%] of Hispanic ethnicity). The FU-CY rates were 43.3% within 90 days of the positive SBT result, 51.4% within 180 days, and 56.1% within 360 days (n = 32 769). In interviews, clinicians were uniformly surprised by the low FU-CY rates. Rates varied by race, ethnicity, insurance type, presence of comorbidities, and SBT used. In the Cox proportional hazards regression model, the strongest positive association was with multitarget stool DNA use (hazard ratio, 1.63 [95% CI, 1.57-1.68] relative to fecal immunochemical tests; P < .001), and the strongest negative association was with the presence of comorbidities (hazard ratio, 0.64 [95% CI, 0.59-0.71] for a CCI of >4 relative to 0; P < .001). The early COVID-19 pandemic was associated with lower FU-CY rates. Conclusions and Relevance: This study found that FU-CY rates after a positive SBT result for colorectal cancer screening were low among an average-risk population, with the median HCO achieving a 53.4% FU-CY rate within 1 year. Socioeconomic factors and the COVID-19 pandemic were associated with lower FU-CY rates, presenting opportunities for targeted intervention by clinicians and health care systems.

Perspectives on Lower Extremity Peripheral Artery Disease: A Qualitative Study of Early Diagnosis and Treatment and the Impact of Health Disparities.

Lower-extremity peripheral artery disease (PAD), the accumulation of atherosclerotic plaque in the arteries of the legs, causes substantial morbidity and mortality. Frequent under- and delayed diagnosis result in poor outcomes, disproportionately affecting individuals from racial and ethnic minority groups. To understand barriers to early detection and treatment and factors contributing to disparities, American Medical Group Association (AMGA) conducted roundtable discussions and semistructured interviews in 2021. Eighteen participants discussed PAD evaluation, diagnosis, early medical management, and disparities in care. A qualitative case study approach and data reduction methods were used to generate themes, draw conclusions, and make actionable recommendations. Identified themes included lack of (1) prioritization of PAD for population health; (2) engagement of primary care providers in early evaluation and referral; (3) "ownership" of lower-extremity PAD within health systems; and (4) focus on disparities in care. Participant solutions included (1) financial impact of early PAD management, in the context of value-based payment; (2) embedding an advanced practice provider into a vascular surgery practice to facilitate evaluation and provide medical therapy; and (3) leveraging care coordination, multidisciplinary clinics, and telehealth technology to provide comprehensive care for patients with PAD and address disparities. A deliberate focused effort is necessary to close gaps and the accompanying disparities in early evaluation, diagnosis, and treatment for people with lower-extremity PAD. The authors describe 3 models that can be emulated to improve care for this high-risk population. With improved reimbursement and better medical therapies, now is the time to focus on early diagnosis and management of PAD.

Predicting Chronic Opioid Use Among Patients With Osteoarthritis Using Electronic Health Record Data.

OBJECTIVE: To estimate the risk of a patient with osteoarthritis (OA) developing chronic opioid use (COU) within 1 year of a new opioid prescription by using electronic health record (EHR) data and predictive models. METHODS: We used EHR data from 13 health care organizations to identify patients with OA with an opioid prescription between March 1, 2017 and February 28, 2019 and no record of opioid use in the prior 6 months. We evaluated 4 machine learning models to estimate patients' risk of COU (≥3 prescriptions ≥84 days, maximum gap ≤60 days). We also estimated the transportability of models to organizations outside the training set. RESULTS: The cohort consisted of 33,894 patients with OA, of whom 2,925 (8.6%) developed COU within 1 year. All models demonstrated good discrimination, with the best-performing model (random forest) achieving an area under the receiver operating characteristic curve (AUC) of 0.728 (95% CI 0.711-0.745), but the simplest regression model performed nearly as well (AUC 0.717 [95% CI 0.699-0.734]). Predicted risk deciles spanned a range of 2% risk for the 10th percentile to 18% risk for the 90th percentile for well-calibrated models. Models showed highly variable discrimination across organizations (AUC 0.571-0.842). CONCLUSIONS: We found that EHR-based predictive models could estimate the risk of future COU among patients with OA to help inform care decisions. Black-box methods did not have significant advantages over more interpretable models. Care should be taken when extending all models into organizations not included in model training because of a high variability in performance across held-out organizations.

Health systems and telemedicine adoption for diabetes and hypertension care.

OBJECTIVES: The COVID-19 pandemic accelerated telemedicine use nationally, but differences across health systems are understudied. We examine telemedicine use for adults with diabetes and/or hypertension across 10 health systems and analyze practice and patient characteristics associated with greater use. STUDY DESIGN: Encounter-level data from the AMGA Optum Data Warehouse for March 13, 2020, to December 31, 2020, were analyzed, which included 3,016,761 clinical encounters from 764,521 adults with diabetes and/or hypertension attributed to 1 of 1207 practice sites with at least 50 system-attributed patients. METHODS: Linear spline regression estimated whether practice size and ownership were associated with telemedicine during the adoption (weeks 0-4), de-adoption (weeks 5-12), and maintenance (weeks 13-42) periods, controlling for patient socioeconomic and clinical characteristics. RESULTS: Telemedicine use peaked at 11% to 42% of weekly encounters after 4 weeks. In adjusted analyses, small practices had lower telemedicine use for adults with diabetes during the maintenance period compared with larger practices. Practice ownership was not associated with telemedicine use. Practices with higher proportions of Black patients continued to expand telemedicine use during the de-adoption and maintenance periods. CONCLUSIONS: Practice ownership was not associated with telemedicine use during first months of the pandemic. Small practices de-adopted telemedicine to a greater degree than medium and large practices. Technical support for small practices, irrespective of their ownership, could enable telemedicine use for adults with diabetes and/or hypertension.

Physician Practices With Robust Capabilities Spend Less On Medicare Beneficiaries Than More Limited Practices.

No research has considered a range of physician practice capabilities for managing patient care when examining practice-level influences on quality of care, utilization, and spending. Using data from the 2017 National Survey of Healthcare Organizations and Systems linked to 2017 Medicare fee-for-service claims data from attributed beneficiaries, we examined the association of practice-level capabilities with process measures of quality, utilization, and spending. In propensity score-weighted mixed-effects regression analyses, physician practice locations with "robust" capabilities had lower total spending compared to locations with "mixed" or "limited" capabilities. Quality and utilization, however, did not differ by practice-level capabilities. Physician practice locations with robust capabilities spend less on Medicare fee-for-service beneficiaries but deliver quality of care that is comparable to the quality delivered in locations with low or mixed capabilities. Reforms beyond those targeting practice capabilities, including multipayer alignment and payment reform, may be needed to support larger performance advantages for practices with robust capabilities.

Using Quality Measures to Drive Improvements in Immunization Rates: Findings from a Real-World Evaluation from 3 US Health Care Organizations.

Adult immunization rates are low and continue to fail to meet national targets. The coronavirus disease 2019 pandemic halted routine health care services for many, including vaccinations. This study explored whether the National Committee for Quality Assurance's Adult Immunization Status (AIS) measure, which had previously only been evaluated for reporting by health plans, could be leveraged by health care organizations (HCOs) as a tactic to improve immunization rates. Methods included a quantitative analysis of deidentified patient electronic health record data from 3 HCOs, supplemented by qualitative interviews to further understand opportunities and barriers. The analysis indicated that the data necessary for calculation of the AIS measure are available within HCOs and that measure performance could be enhanced with supplemental data from external sources, such as state immunization registries. Although HCOs rates were consistent with national estimates, this research further validated that adult immunization rates in the United States are low and highlighted the profound disparities that exist. For instance, the likelihood of completing all age-appropriate vaccinations was lower if patients were Black or African American, enrolled in Medicaid, or without health insurance. As a result of this study, the authors concluded that the AIS measure is feasible for use in medical groups and could potentially help drive quality improvements in immunization rates; however, there are considerations for implementation particularly if providers are being held accountable for measure performance.

Successful Implementation of an All-or-None Diabetes Measure in 10 US Health Systems.

Type 2 diabetes mellitus (T2DM) affects 31.5 million adults in the United States and is commonly treated in primary care settings. One promising approach to comprehensive care is to focus on an all-or-none diabetes bundle measure, which ensures each patient meets a set of guideline-recommended measures. This requires a practice-level coordinated strategy. The purpose of this initiative was to help health care organizations (HCOs) improve the care and outcomes of patients with T2DM using an all-or-none bundle measure. This observational study was carried out in the context of a national best practices learning Collaborative that implemented targeted interventions in primary care settings and measured success using an all-or-none bundle measure. Ten AMGA member-HCOs, across 8 states, treating nearly 300,000 adult patients with T2DM in primary care participated. The primary measure, the Together 2 Goal® Core Bundle, included hemoglobin A1c (A1c) control (<8%), blood pressure (BP) control (<140/90 mmHg), lipid management (prescribed a statin), and medical attention for nephropathy. All 10 HCOs improved the Core Bundle measure during the 12-month Collaborative. The rate for the Core Bundle improved from 40.2% to 42.8%, an absolute increase of 2.6% (P < 0.001). In addition, 9 HCOs improved BP control, 8 improved lipid management, 6 improved attention to nephropathy, and 4 improved A1c control. Implementing interventions in primary care settings was successful in achieving comprehensive care for an estimated additional 7700 people living with T2DM who met all 4 components of the bundle measure during the 12-month intervention period.

Potential barriers to filling buprenorphine and naltrexone prescriptions among a retrospective cohort of individuals with opioid use disorder.

INTRODUCTION: Medications for opioid use disorder (MOUD) are highly effective, but barriers along the cascade of care for opioid use disorder (OUD) from diagnosis to treatment limit their reach. For individuals desiring MOUD, the final step in the cascade is filling a written prescription, and fill rates have not been described. METHODS: We used data from a large de-identified database linking individuals' electronic medical records (EMR) and administrative claims data and employed a previously developed algorithm to identify individuals with a new diagnosis of OUD. We included individuals with a prescription for buprenorphine or naltrexone recorded in the EMR. The outcome was a prescription fill within 30 days as reported in claims data. We compared demographic and clinical characteristics between those who did and did not fill the prescription and used a Kaplan-Meier curve to assess whether fill rates differed based on patient copay. RESULTS: We identified 264 individuals with a new diagnosis of OUD who had a prescription written for buprenorphine or oral naltrexone. Of these, 70% (184) filled the prescription within 30 days, and more than half (57%) filled the prescription on the day it was written. Individuals with prescription copay at or below the mean had a 75% fill rate at 30 days compared with 63% for those with copay above the mean (p < 0.05) and this difference was consistent across fill times (log rank p-value <0.05). CONCLUSIONS: It is alarming that nearly 1 in 3 MOUD prescriptions go unfilled. More research is needed to understand and reduce barriers to this final step of the OUD cascade of care.

An Electronic Health Record-Compatible Model to Predict Personalized Treatment Effects From the Diabetes Prevention Program: A Cross-Evidence Synthesis Approach Using Clinical Trial and Real-World Data.

OBJECTIVE: To develop an electronic health record (EHR)-based risk tool that provides point-of-care estimates of diabetes risk to support targeting interventions to patients most likely to benefit. PATIENTS AND METHODS: A risk prediction model was developed and validated in a large observational database of patients with an index visit date between January 1, 2012, and December 31, 2016, with treatment effect estimates from risk-based reanalysis of clinical trial data. The risk model development cohort included 1.1 million patients with prediabetes from the OptumLabs Data Warehouse (OLDW); the validation cohort included a distinct sample of 1.1 million patients in OLDW. The randomly assigned clinical trial cohort included 3081 people from the Diabetes Prevention Program (DPP) study. RESULTS: Eleven variables reliably obtainable from the EHR were used to predict diabetes risk. This model validated well in the OLDW (C statistic = 0.76; observed 3-year diabetes rate was 1.8% (95% confidence interval [CI], 1.7 to 1.9) in the lowest-risk quarter and 19.6% (19.4 to 19.8) in the highest-risk quarter). In the DPP, the hazard ratio (HR) for lifestyle modification was constant across all levels of risk (HR, 0.43; 95% CI, 0.35 to 0.53), whereas the HR for metformin was highly risk dependent (HR, 1.1; 95% CI, 0.61 to 2.0 in the lowest-risk quarter vs HR, 0.45; 95% CI, 0.35 to 0.59 in the highest-risk quarter). Fifty-three percent of the benefits of population-wide dissemination of the DPP lifestyle modification and 73% of the benefits of population-wide metformin therapy can be obtained by targeting the highest-risk quarter of patients. CONCLUSION: The Tufts-Predictive Analytics and Comparative Effectiveness DPP Risk model is an EHR-compatible tool that might support targeted diabetes prevention to more efficiently realize the benefits of the DPP interventions.

Using telehealth to provide diabetes care to patients in rural Montana: findings from the promoting realistic individual self-management program.

OBJECTIVE: The objectives of this study were to demonstrate the feasibility of telehealth technology to provide a team approach to diabetes care for rural patients and determine its effect on patient outcomes when compared with face-to-face diabetes visits. MATERIALS AND METHODS: An evaluation of a patient-centered interdisciplinary team approach to diabetes management compared telehealth with face-to-face visits on receipt of recommended preventive guidelines, vascular risk factor control, patient satisfaction, and diabetes self-management at baseline and 1, 2, and 3 years postintervention. RESULTS: One-year postintervention the receipt of recommended dilated eye exams increased 31% and 43% among telehealth and face-to-face patients, respectively (p=0.28). Control of two or more risk factors increased 37% and 69% (p=0.21). Patient diabetes care satisfaction rates increased 191% and 131% among telehealth and face-to-face patients, respectively (p=0.51). A comparison of telehealth with face-to-face patients resulted in increased self-reported blood glucose monitoring as instructed (97% vs. 89%; p=0.63) and increased dietary adherence (244% vs. 159%; p=0.86), respectively. Receipt of a monofilament foot test showed a significantly greater improvement among face-to-face patients (17% vs. 35%; p=0.01) at 1 year postintervention, but this difference disappeared in years 2 and 3. CONCLUSIONS: Telehealth proved to be an effective mode for the provision of diabetes care to rural patients. Few differences were detected in the delivery of a team approach to diabetes management via telehealth compared with face-to-face visits on receipt of preventive care services, vascular risk factor control, patient satisfaction, and patient self-management. A team approach using telehealth may be a viable strategy for addressing the unique challenges faced by patients living in rural communities.

A Retrospective Analysis of Therapeutic Inertia in Type 2 Diabetes Management Across a Diverse Population of Health Care Organizations in the USA.

INTRODUCTION: If their target glycated hemoglobin (HbA1c) is not achieved after 3 months, timely treatment intensification is recommended in people with type 2 diabetes to maintain glycemic control and minimize vascular complications. We retrospectively investigated potential therapeutic inertia in the management of type 2 diabetes in multiple health care organizations across the USA. METHODS: Electronic health records were analyzed from 22 American Medical Group Association (AMGA) health care organizations. Bolus insulin-naïve patients with type 2 diabetes and HbA1c ≥ 8.0% (≥ 64 mmol/mol) at baseline were followed for 24 months to identify the frequency and average duration of therapeutic inertia (no new class of glucose-lowering medication prescribed, or not achieving their target HbA1c [< 8.0%; < 64 mmol/mol]). RESULTS: The study cohort comprised almost 28,000 patients. Therapeutic inertia was observed in ≈ 50% of patients after 6 months, and in > 10% after 24 months. Less therapeutic inertia was observed in patients receiving one or no oral antidiabetic drugs (OADs) (36% or 28%, respectively, at 6 months), while more inertia was seen following multiple OADs or basal insulin (54% of those on baseline basal insulin at 6 months). Although an observable action was recorded for 90% of patients, many (44%) had still not achieved their target HbA1c after 24 months. CONCLUSION: The results corroborate the presence of therapeutic inertia in people with type 2 diabetes, suggesting that treatment intensification guidelines are not being followed. Extensive variability in the presence of therapeutic inertia was observed both across and within organizations; investigating this further and sharing best practices across providers might help improve the quality of patient care at organizational and national levels.

People with type 2 diabetes have their glycated hemoglobin (HbA_1c) level measured regularly by their care provider to check their blood sugar levels over the previous 2­3 months and the diabetes control achieved with their current treatment. To keep HbA_1c within an individually recommended range, changes to therapies or doses may be needed, which is known as 'treatment intensification.' Despite guidelines describing this best-practice approach, 'therapeutic inertia' (not intensifying treatment when needed) is common. This therapeutic inertia may be a result of complicated or confusing guidelines, a lack of time or awareness/understanding on the part of the health care provider, or patient-specific barriers such as treatment cost or fear of side effects. Due to therapeutic inertia, patients can have poorly controlled diabetes for a long time, increasing their risk of other diabetes-related health problems or complications. This study describes widespread therapeutic inertia in the management of type 2 diabetes across the USA, suggesting that treatment intensification in patients with poor diabetes control is not taking place when needed. Diabetes-related health complications caused by poorly controlled disease over a period of time can significantly reduce quality of life. Diabetes and its complications also increase costs for the health care system due to the resulting medical costs and diabetes-related reductions in productivity. It is important to encourage early diagnosis of diabetes and appropriate and timely treatment. Investigating the variations in therapeutic inertia seen within and between health care organizations and sharing the lessons learned by the top-performing organizations may help spread best practices and improve the quality of patient care.

Cardiovascular Disease in Patients With Type 2 Diabetes: A Qualitative Analysis of Knowledge, Attitudes, and Beliefs of Health Care Professionals.

Guidelines for the management of patients with type 2 diabetes mellitus (T2DM) recommend SGLT-2 (sodium-glucose cotransporter 2) inhibitors and GLP-1 RAs (glucagon-like peptide 1 receptor agonists) as second-line agents for patients with, or at risk for, cardiovascular disease. A better understanding of guideline implementation will further the provision of evidence-based health care to patients. Interviews and surveys of clinicians were conducted to understand providers' knowledge, attitudes, and beliefs related to the 2019 American Diabetes Association Standards of Care for T2DM. There was a lack of widespread knowledge of the guidelines and comfort with their use. Clinicians require additional training and education on the efficacy of the new medications and accompanying clinical guidelines.

Measuring What Matters: Beyond Quality Performance Measures in Caring for Adults with Obesity.

Obesity is a chronic disease that poses serious health and societal burdens. Although guidelines exist for obesity management in primary care, evaluating the success of obesity treatment programs is hampered by lack of established, robust quality measures. This study aimed to develop, and test for feasibility, measures for operational tracking, quality performance, and patient-centered care in the context of a national collaborative to develop a model for obesity management in the US primary care setting. The authors developed and evaluated 7 measures used to track the care of patients with overweight or obesity (n = 226,727 at baseline) receiving care within 10 health care organizations (HCOs). Measure categories included: (1) operational tracking (obesity/overweight prevalence and prevalence of obesity-related complications); (2) quality performance (obesity diagnosis, change in weight over time, anti-obesity medication prescriptions, and assessment of obesity-related complications); and (3) patient-centered care (patient-reported outcomes). Measures were tested for feasibility, variability across HCOs, ability to detect differences over time, and value to the HCOs. All measures were feasible to collect, provided value to the participating HCOs, and demonstrated variation and ability to detect differences over time (eg, rates of documented diagnosis of obesity classes 1, 2, and 3 increased from 29%, 46%, and 66%, respectively, at baseline to 35%, 53%, and 71% at study end). This study confirmed the feasibility and perceived value of 7 operational, performance, and patient-centered measures collected in primary care practices in 10 HCOs over an 18-month period.