"Low 5": A Five-Step Electronic Medical Record Prescribing Checklist to Lower Opioid Prescribing in Primary Care.

Since the start of the 21st Century, the use of opioids for pain management in primary care has increased along with a concomitant rise in opioid associated deaths. The use of opioids is associated with risks of addiction, respiratory depression, sedation, and death. There is no checklist available in electronic medical records to guide safe prescribing of non-opioid pain management options prior to opioids in primary care. Our quality improvement project pilot study aimed to reduce unnecessary opioid prescribing in an urban academic internal medicine clinic by incorporating a checklist of five first-line non-opioid therapy suggestions into electronic medical records. Following its implementation, opioid prescribing dropped by an average of 38.4 percent per month.

One-Year Health Status Outcomes Following Early Invasive and Noninvasive Treatment in Symptomatic Peripheral Artery Disease.

BACKGROUND: Lifestyle changes and medications are recommended as the first line of treatment for claudication, with revascularization considered for treatment-resistant symptoms, based on patients' preferences. Real-world evidence comparing health status outcomes of early invasive with noninvasive management strategies is lacking. METHODS: In the international multicenter prospective observational PORTRAIT (Patient-Centered Outcomes Related to Treatment Practices in Peripheral Arterial Disease: Investigating Trajectories) registry, disease-specific health status was assessed by the Peripheral Artery Questionnaire in patients with new-onset or worsening claudication at presentation and 3, 6, and 12 months later. One-year health status trajectories were compared by early revascularization versus noninvasive management on a propensity-matched sample using hierarchical generalized linear models for repeated measures adjusted for baseline health status. RESULTS: In a propensity-matched sample of 1000 patients (67.4±9.3 years, 62.8% male, and 82.4% White), 297 (29.7%) underwent early revascularization and 703 (70.3%) were managed noninvasively. Over 1 year of follow-up, patients who underwent early invasive management reported significantly higher health status than patients managed noninvasively (interaction term for time and treatment strategy; P<0.001 for all Peripheral Artery Questionnaire domains). The average 1-year change in Peripheral Artery Questionnaire summary scores was 30.8±25.2 in those undergoing early invasive, compared with 16.7±23.4 in those treated noninvasively (P<0.001). CONCLUSIONS: Patients with claudication undergoing early invasive treatment had greater health status improvements over the course of 1 year than those treated noninvasively. These data can be used to support shared decision-making with patients. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT01419080.

Association of number of primary care physicians with preventable hospitalizations and premature deaths.

BACKGROUND: Primary care physicians (PCPs) may be the first providers for patients in a healthcare interaction, putting them in a unique position that may determine the health trajectory of a patient. Assessing whether PCPs improve the overall health of a community through reducing preventable hospital stays and premature deaths may provide necessary information towards improving the health outcomes at grassroots. METHODS: County-level data on the number of primary care physicians, preventable hospital stays and 'years of potential life lost' (YPLL) were obtained from the Physician Master File data of the American Medical Association, Centers for Medicare & Medicaid Services Office of Minority Health's Mapping Medicare Disparities data, and Center for Disease Control and Prevention's WONDER database, respectively. We employed linear regression model to assess the association of PCP rate with preventable hospital stays and YPLL. RESULTS: Preventable hospitalization rate in the United States was 6303.4 (95% CI, 6212.5-6394.3) hospitalizations per 100,00 population, while the average YPLL across the counties in the United States was 7792.9 (95% CI, 7697.6-7888.3) years per 100,000 population. For an increase of 1 PCP in a county, around 16 hospitalizations were prevented per 100,000 population (P = 0.001) each year. Furthermore, around 14 years of life were saved per 100,000 population for every additional PCP in a county across the United States (P < 0.001). CONCLUSION: Higher number of PCPs in a county was associated with lower hospitalizations for preventable causes and lower premature deaths. Increasing PCPs may be an important metric to improve overall health in a community.

Geographical affiliation with top 10 NIH-funded academic medical centers and differences between mortality from cardiovascular disease and cancer.

Community engagement and rapid translation of findings for the benefit of patients has been noted as a major criterion for NIH decisions regarding allocation of funds for research priorities. We aimed to examine whether the presence of top NIH-funded institutions resulted in a benefit on the cardiovascular and cancer mortality of their local population. METHODS AND RESULTS: Based on the annual NIH funding of every academic medical from 1995 through 2014, the top 10 funded institutes were identified and the counties where they were located constituted the index group. The comparison group was created by matching each index county to another county which lacks an NIH-funded institute based on sociodemographic characteristics. We compared temporal trends of age-standardized cardiovascular mortality between the index counties and matched counties and states. This analysis was repeated for cancer mortality as a sensitivity analysis. From 1980 through 2014, the annual cardiovascular mortality rates declined in all counties. In the index group, the average decline in cardiovascular mortality rate was 51.5 per 100,000 population (95% CI, 46.8-56.2), compared to 49.7 per 100,000 population (95% CI, 45.9-53.5) in the matched group (P = .27). Trends in cardiovascular mortality of the index counties were similar to the cardiovascular mortality trends of their respective states. Cancer mortality rates declined at higher rates in counties with top NIH-funded medical centers (P < .001). CONCLUSIONS: Cardiovascular mortality rates have decreased with no apparent incremental benefit for communities with top NIH-funded institutions, underscoring the need for an increased focus on implementation science in cardiovascular diseases.

The National Institutes of Health funding for clinical research applying machine learning techniques in 2017.

Machine learning (ML) techniques have become ubiquitous and indispensable for solving intricate problems in most disciplines. To determine the extent of funding for clinical research projects applying ML techniques by the National Institutes of Health (NIH) in 2017, we searched the NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER) system using relevant keywords. We identified 535 projects, which together received a total of $264 million, accounting for 2% of the NIH extramural budget for clinical research.

Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction.

OBJECTIVES: This study sought to develop models for predicting mortality and heart failure (HF) hospitalization for outpatients with HF with preserved ejection fraction (HFpEF) in the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist) trial. BACKGROUND: Although risk assessment models are available for patients with HF with reduced ejection fraction, few have assessed the risks of death and hospitalization in patients with HFpEF. METHODS: The following 5 methods: logistic regression with a forward selection of variables; logistic regression with a lasso regularization for variable selection; random forest (RF); gradient descent boosting; and support vector machine, were used to train models for assessing risks of mortality and HF hospitalization through 3 years of follow-up and were validated using 5-fold cross-validation. Model discrimination and calibration were estimated using receiver-operating characteristic curves and Brier scores, respectively. The top prediction variables were assessed by using the best performing models, using the incremental improvement of each variable in 5-fold cross-validation. RESULTS: The RF was the best performing model with a mean C-statistic of 0.72 (95% confidence interval [CI]: 0.69 to 0.75) for predicting mortality (Brier score: 0.17), and 0.76 (95% CI: 0.71 to 0.81) for HF hospitalization (Brier score: 0.19). Blood urea nitrogen levels, body mass index, and Kansas City Cardiomyopathy Questionnaire (KCCQ) subscale scores were strongly associated with mortality, whereas hemoglobin level, blood urea nitrogen, time since previous HF hospitalization, and KCCQ scores were the most significant predictors of HF hospitalization. CONCLUSIONS: These models predict the risks of mortality and HF hospitalization in patients with HFpEF and emphasize the importance of health status data in determining prognosis. (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist [TOPCAT]; NCT00094302).

Characterizing Patient-Centered Postoperative Recovery After Adult Cardiac Surgery: A Systematic Review.

Background Improving postoperative recovery is important, with a national focus on postacute care, but the volume and quality of evidence in this area are not well characterized. We conducted a systematic review to characterize studies on postoperative recovery after adult cardiac surgery using patient-reported outcome measures. Methods and Results From MEDLINE and Web of Science, studies were included if they prospectively assessed postoperative recovery on adult patients undergoing cardiac surgery using patient-reported outcome measures. Six recovery domains were defined by prior literature: nociceptive symptoms, mental health, physical function, activities of daily living, sleep, and cognitive function. Of the 3432 studies, 105 articles met the inclusion criteria. The studies were small (median sample size, 119), and mostly conducted in single-center settings (n=81; 77%). Study participants were predominantly men (71%) and white (88%). Coronary artery bypass graft was included in 93% (n=98). Studies commonly selected for elective cases (n=56; 53%) and patients with less comorbidity (n=67; 64%). Median follow-up duration was 91 (interquartile range, 42-182) days. Studies most commonly assessed 1 domain (n=42; 40%). The studies also varied in the instruments used and differed in their reporting approach. Studies commonly excluded patients who died during the follow-up period (n=48; 46%), and 45% (n=47) did not specify how those patients were analyzed. Conclusions Studies of postoperative patient-reported outcome measures are low in volume, most often single site without external validation, varied in their approach to missing data, and narrow in the domains and diversity of patients. The evidence base for postoperative patient-reported outcome measures needs to be strengthened.

Digoxin Use and Associated Adverse Events Among Older Adults.

BACKGROUND: Over the past 2 decades, guidelines for digoxin use have changed significantly. However, little is known about the national-level trends of digoxin use, hospitalizations for toxicity, and subsequent outcomes over this time period. METHODS: To describe digoxin prescription trends, we conducted a population-level, cohort study using data from IQVIA, Inc.'s National Prescription Audit (2007-2014) for patients aged ≥65 years. Further, in a national cohort of Medicare fee-for-service beneficiaries aged ≥65 years in the United States, we assessed temporal trends of hospitalizations associated with digoxin toxicity and the outcomes of these hospitalizations between 1999 and 2013. RESULTS: From 2007 through 2014, the number of digoxin prescriptions dispensed decreased by 46.4%; from 8,099,856 to 4,343,735. From 1999 through 2013, the rate of hospitalizations with a principal or secondary diagnosis of digoxin toxicity decreased from 15 to 2 per 100,000 person-years among Medicare fee-for-service beneficiaries. In-hospital and 30-day mortality rates associated with hospitalization for digoxin toxicity decreased significantly among Medicare fee-for-service beneficiaries; from 6.0% (95% confidence interval [CI], 5.2-6.8) to 3.7% (95% CI, 2.2-5.7) and from 14.0% (95% CI, 13.0-15.2) to 10.1% (95% CI, 7.6-13.0), respectively. Rates of 30-day readmission for digoxin toxicity decreased from 23.5% (95% CI, 22.1-24.9) in 1999 to 21.7% (95% CI, 18.0-25.4) in 2013 (P < .05). CONCLUSION: While digoxin prescriptions have decreased, it is still widely prescribed. However, the rate of hospitalizations for digoxin toxicity and adverse outcomes associated with these hospitalizations have decreased. These findings reflect the changing clinical practice of digoxin use, aligned with the changes in clinical guidelines.

Association of access to exercise opportunities and cardiovascular mortality.

We sought to examine the patterns of cardiovascular disease (CVD) mortality in varying degrees of access to exercise opportunities at county level in the United States. Access to exercise opportunities was significantly associated with adjusted CVD mortality (P < .001); higher access to exercise opportunities correlated with lower CVD mortality. Counties with lower access to exercise facilities had higher prevalence of obesity and diabetes when compared with counties with higher access (P < .001). Furthermore, the states with fewer people living in close proximity to a park had higher percentage of people not engaging in any leisure physical activity (P < .001).

Submissions from the SPRINT Data Analysis Challenge on clinical risk prediction: a cross-sectional evaluation.

OBJECTIVES: To collate and systematically characterise the methods, results and clinical performance of the clinical risk prediction submissions to the Systolic Blood Pressure Intervention Trial (SPRINT) Data Analysis Challenge. DESIGN: Cross-sectional evaluation. DATA SOURCES: SPRINT Challenge online submission website. STUDY SELECTION: Submissions to the SPRINT Challenge for clinical prediction tools or clinical risk scores. DATA EXTRACTION: In duplicate by three independent reviewers. RESULTS: Of 143 submissions, 29 met our inclusion criteria. Of these, 23/29 (79%) reported prediction models for an efficacy outcome (20/23 [87%] of these used the SPRINT study primary composite outcome, 14/29 [48%] used a safety outcome, and 4/29 [14%] examined a combined safety/efficacy outcome). Age and cardiovascular disease history were the most common variables retained in 80% (12/15) of the efficacy and 60% (6/10) of the safety models. However, no two submissions included an identical list of variables intending to predict the same outcomes. Model performance measures, most commonly, the C-statistic, were reported in 57% (13/23) of efficacy and 64% (9/14) of safety model submissions. Only 2/29 (7%) models reported external validation. Nine of 29 (31%) submissions developed and provided evaluable risk prediction tools. Using two hypothetical vignettes, 67% (6/9) of the tools provided expected recommendations for a low-risk patient, while 44% (4/9) did for a high-risk patient. Only 2/29 (7%) of the clinical risk prediction submissions have been published to date. CONCLUSIONS: Despite use of the same data source, a diversity of approaches, methods and results was produced by the 29 SPRINT Challenge competition submissions for clinical risk prediction. Of the nine evaluable risk prediction tools, clinical performance was suboptimal. By collating an overview of the range of approaches taken, researchers may further optimise the development of risk prediction tools in SPRINT-eligible populations, and our findings may inform the conduct of future similar open science projects.

Trends in 30-Day Readmission Rates for Medicare and Non-Medicare Patients in the Era of the Affordable Care Act.

BACKGROUND: Temporal changes in the readmission rates for patient groups and conditions that were not directly under the purview of the Hospital Readmissions Reduction Program (HRRP) can help assess whether efforts to lower readmissions extended beyond targeted patients and conditions. METHODS: Using the Nationwide Readmissions Database (2010-2015), we assessed trends in all-cause readmission rates for 1 of the 3 HRRP conditions (acute myocardial infarction, heart failure, pneumonia) or conditions not targeted by the HRRP in age-insurance groups defined by age group (≥65 years or <65 years) and payer (Medicare, Medicaid, or private insurance). RESULTS: In the group aged ≥65 years, readmission rates for those covered by Medicare, Medicaid, and private insurance decreased annually for acute myocardial infarction (risk-adjusted odds ratio [OR; 95% confidence interval] among Medicare patients, 0.94 [0.94-0.95], among Medicaid patients, 0.93 [0.90-0.97], and among patients with private-insurance, 0.95 [0.93-0.97]); heart failure (ORs, 0.96 [0.96-0.97], 0.96 [0.94-0.98], and 0.97 [0.96-0.99], for the 3 payers, respectively), and pneumonia (ORs, 0.96 [0.96-0.97), 0.94 [0.92-0.96], and 0.96 [0.95-0.97], respectively). Readmission rates also decreased in the group aged <65 years for acute myocardial infarction (ORs: Medicare 0.97 [0.96-0.98], Medicaid 0.94 [0.92-0.95], and private insurance 0.93 [0.92-0.94]), heart failure (ORs, 0.98 [0.97-0.98]: 0.96 [0.96-0.97], and 0.97 [0.95-0.98], for the 3 payers, respectively), and pneumonia (ORs, 0.98 [0.97-0.99], 0.98 [0.97-0.99], and 0.98 [0.97-1.00], respectively). Further, readmission rates decreased significantly for non-target conditions. CONCLUSIONS: There appears to be a systematic improvement in readmission rates for patient groups beyond the population of fee-for-service, older, Medicare beneficiaries included in the HRRP.

Sex and Race Differences in the Utilization and Outcomes of Coronary Artery Bypass Grafting Among Medicare Beneficiaries, 1999-2014.

BACKGROUND: With over a decade of directed efforts to reduce sex and racial differences in coronary artery bypass grafting (CABG) utilization, and post-CABG outcomes, we sought to evaluate how the use of CABG and its outcomes have evolved in different sex and racial subgroups. METHODS AND RESULTS: Using data on all fee-for-service Medicare beneficiaries undergoing CABG in the United States from 1999 to 2014, we examined differences by sex and race in calendar-year trends for CABG utilization and post-CABG outcomes (in-hospital, 30-day, and 1-year mortality and 30-day readmission). A total of 1 863 719 Medicare fee-for-service beneficiaries (33.6% women, 4.6% black) underwent CABG from 1999 to 2014, with a decrease from 611 to 245 CABG procedures per 100 000 person-years. Men compared with women and whites compared with blacks had higher CABG utilization, with declines in all subgroups. Higher post-CABG annual declines in mortality (95% confidence interval) were observed in women (in-hospital, -2.70% [-2.97, -2.44]; 30-day, -2.29% [-2.54, -2.04]; and 1-year mortality, -1.67% [-1.88, -1.46]) and blacks (in-hospital, -3.31% [-4.02, -2.60]; 30-day, -2.80% [-3.49, -2.12]; and 1-year mortality, -2.38% [-2.92, -1.84]), compared with men and whites, respectively. Mortality rates remained higher in women and blacks, but differences narrowed over time. Annual adjusted 30-day readmission rates remained unchanged for all patient groups. CONCLUSIONS: Women and black patients had persistently higher CABG mortality than men and white patients, respectively, despite greater declines over the time period. These findings indicate progress, but also the need for further progress.

Adherence to Methodological Standards in Research Using the National Inpatient Sample.

Importance: Publicly available data sets hold much potential, but their unique design may require specific analytic approaches. Objective: To determine adherence to appropriate research practices for a frequently used large public database, the National Inpatient Sample (NIS) of the Agency for Healthcare Research and Quality (AHRQ). Design, Setting, and Participants: In this observational study of the 1082 studies published using the NIS from January 2015 through December 2016, a representative sample of 120 studies was systematically evaluated for adherence to practices required by AHRQ for the design and conduct of research using the NIS. Exposures: None. Main Outcomes and Measures: All studies were evaluated on 7 required research practices based on AHRQ's recommendations and compiled under 3 domains: (1) data interpretation (interpreting data as hospitalization records rather than unique patients); (2) research design (avoiding use in performing state-, hospital-, and physician-level assessments where inappropriate; not using nonspecific administrative secondary diagnosis codes to study in-hospital events); and (3) data analysis (accounting for complex survey design of the NIS and changes in data structure over time). Results: Of 120 published studies, 85% (n = 102) did not adhere to 1 or more required practices and 62% (n = 74) did not adhere to 2 or more required practices. An estimated 925 (95% CI, 852-998) NIS publications did not adhere to 1 or more required practices and 696 (95% CI, 596-796) NIS publications did not adhere to 2 or more required practices. A total of 79 sampled studies (68.3% [95% CI, 59.3%-77.3%]) among the 1082 NIS studies screened for eligibility did not account for the effects of sampling error, clustering, and stratification; 62 (54.4% [95% CI, 44.7%-64.0%]) extrapolated nonspecific secondary diagnoses to infer in-hospital events; 45 (40.4% [95% CI, 30.9%-50.0%]) miscategorized hospitalizations as individual patients; 10 (7.1% [95% CI, 2.1%-12.1%]) performed state-level analyses; and 3 (2.9% [95% CI, 0.0%-6.2%]) reported physician-level volume estimates. Of 27 studies (weighted; 218 studies [95% CI, 134-303]) spanning periods of major changes in the data structure of the NIS, 21 (79.7% [95% CI, 62.5%-97.0%]) did not account for the changes. Among the 24 studies published in journals with an impact factor of 10 or greater, 16 (67%) did not adhere to 1 or more practices, and 9 (38%) did not adhere to 2 or more practices. Conclusions and Relevance: In this study of 120 recent publications that used data from the NIS, the majority did not adhere to required practices. Further research is needed to identify strategies to improve the quality of research using the NIS and assess whether there are similar problems with use of other publicly available data sets.

Home Health Agency Performance in the United States: 2011-15.

OBJECTIVES: To evaluate home health agency quality performance. DESIGN: Observational study. SETTING: Home health agencies. PARTICIPANTS: All Medicare-certified agencies with at least 6 months of data from 2011 to 2015. MEASUREMENTS: Twenty-two quality indicators, five patient survey indicators, and their composite scores. RESULTS: The study included 11,462 Medicare-certified home health agencies that served 92.4% of all ZIP codes nationwide, accounting for 315.2 million people. The mean composite scores were 409.1 ± 22.7 out of 500 with the patient survey indicators and 492.3 ± 21.7 out of 600 without the patient survey indicators. Home health agency performance on 27 quality indicators varied, with the coefficients of dispersion ranging from 4.9 to 62.8. Categorization of agencies into performance quartiles revealed that 3,179 (27.7%) were in the low-performing group (below 25th percentile) at least one time during the period from 2011-12 to 2014-15 and that 493 were in the low-performing group throughout the study period. Geographic variation in agency performance was observed. Agencies with longer Medicare-certified years were more likely to have high-performing scores; agencies providing partial services, with proprietary ownership, and those with long travel distances to reach patients had lower performance. Agencies serving low-income counties and counties with lower proportions of women and senior residences and greater proportions of Hispanic residents were more likely to attain lower performance scores. CONCLUSION: Home health agency performance on several quality indicators varied, and many agencies were persistently in the lowest quartile of performance. Still, there is a need to improve the quality of care of all agencies. Many parts of the United States, particularly lower-income areas and areas with more Hispanic residents, are more likely to receive lower quality home health care.

Evaluation of breast parenchymal density with QUANTRA software.

PURPOSE: To evaluate breast parenchymal density using QUANTRA software and to correlate numerical breast density values obtained from QUANTRA with ACR BI-RADS breast density categories. MATERIALS AND METHODS: Two-view digital mammograms of 545 consecutive women (mean age - 47.7 years) were categorized visually by three independent radiologists into one of the four ACR BI-RADS categories (D1-D4). Numerical breast density values as obtained by QUANTRA software were then used to establish the cutoff values for each category using receiver operator characteristic (ROC) analysis. RESULTS: Numerical breast density values obtained by QUANTRA (range - 7-42%) were systematically lower than visual estimates. QUANTRA breast density value of less than 14.5% could accurately differentiate category D1 from the categories D2, D3, and D4 [area under curve (AUC) on ROC analysis - 94.09%, sensitivity - 85.71%, specificity - 84.21%]. QUANTRA density values of <19.5% accurately differentiated categories D1 and D2 from D3 and D4 (AUC - 94.4%, sensitivity - 87.50%, specificity - 84.60%); QUANTRA density values of <26.5% accurately differentiated categories D1, D2, and D3 from category D4 (AUC - 90.75%, sensitivity - 88.89%, specificity - 88.621%). CONCLUSIONS: Breast density values obtained by QUANTRA software can be used to obtain objective cutoff values for each ACR BI-RADS breast density category. Although the numerical density values obtained by QUANTRA are lower than visual estimates, they correlate well with the BI-RADS breast density categories assigned visually to the mammograms.