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BackgroundEnd-of-life (EOL) care patterns may differ by physician age given differences in how physicians are trained or changes associated with aging. We sought to compare patterns of EOL care delivered to older Americans according to physician age.MethodsWe conducted a cross-sectional study of a 20% sample of Medicare fee-for-service beneficiaries aged ≥66 years who died in 2016-2019 (n = 487,293). We attributed beneficiaries to the physician who had >50% of primary care visits during the last 6 months of life. We compared beneficiary-level outcomes by physician age (

BackgroundPayers and policy makers across the international healthcare market are increasingly using publicly available summary measures to designate providers as "high-performing", but no consistently-applied approach exists to identifying high performers. This paper uses publicly available data to examine how different classification approaches influence which providers are designated as "high-performers".MethodsWe conducted a quantitative analysis of cross-sectional publicly-available performance data in the U.S. We used 2014 Minnesota Community Measurement data from 58 medical groups to classify performance across 4 domains: quality (two process measures of cancer screening and 2 composite measures of chronic disease management), total cost of care, access (a composite CAHPS measure), and patient experience (3 CAHPS measures). We classified medical groups based on performance using either relative thresholds or absolute values of performance on all included measures.ResultsUsing relative thresholds, none of the 58 medical groups achieved performance in the top 25% or 35% in all 4 performance domains. A relative threshold of 40% was needed before one group was classified as high-performing in all 4 domains. Using absolute threshold values, two medical groups were classified as high-performing across all 4 domains. In both approaches, designating "high performance" using fewer domains led to more groups designated as high-performers, though there was little to moderate concordance across identified "high-performing" groups.ConclusionsClassification of medical groups as high performing is sensitive to the domains of performance included, the classification approach, and choice of threshold. With increasing focus on achieving high performance in healthcare delivery, the absence of a consistently-applied approach to identify high performers impedes efforts to reliably compare, select and reward high-performing providers.

BackgroundOlder adults are particularly vulnerable to complications from proton pump inhibitor (PPI) drugs. We sought to characterize the prevalence of potentially low-value PPI prescriptions among older adults to inform a quality improvement (QI) intervention.MethodsWe created a cohort of patients, aged 65 years or older, receiving primary care at a large academic health system in 2018. We identified patients currently prescribed any PPI using the electronic health record (EHR) medication list (current defined as September 1, 2018). A geriatrician, a gastroenterologist, a QI expert, and two primary care physicians (PCPs) created multidisciplinary PPI appropriateness criteria based on evidenced-based guidelines. Supervised by a gastroenterologist and PCP, two internal medicine residents conducted manual chart reviews in a random sample of 399 patients prescribed PPIs. We considered prescriptions potentially low value if they lacked a guideline-based (1) short-term indication (gastroesophageal reflux disease [GERD]/peptic ulcer disease/Helicobacter pylori gastritis/dyspepsia) or (2) long-term (>8 weeks) indication (severe/refractory GERD/erosive esophagitis/Barrett esophagus/esophageal adenocarcinoma/esophageal stricture/high gastrointestinal bleeding risk/Zollinger-Ellison syndrome). We used the Wilson score method to calculate 95% confidence intervals (CIs) on low-value PPI prescription prevalence.ResultsAmong 69 352 older adults, 8729 (12.6%) were prescribed a PPI. In the sample of 399 patients prescribed PPIs, 63.9% were female; their mean age was 76.2 years, and they were seen by 169 PCPs. Of the 399 prescriptions, 143 (35.8%; 95% CI = 31.3%-40.7%) were potentially low value-of which 82% began appropriately (eg, GERD) but then continued long term without a guideline-based indication. Among 169 PCPs, 32 (18.9%) contributed to 59.2% of potentially low-value prescriptions.ConclusionOne in eight older adults were prescribed a PPI, and over one-third of prescriptions were potentially low-value. Most often, appropriate short-term prescriptions became potentially low value because they lacked long-term indications. With most potentially low-value prescribing concentrated among a small subset of PCPs, interventions targeting them and/or applying EHR-based automatic stopping rules may protect older adults from harm. J Am Geriatr Soc 67:2600-2604, 2019.

BackgroundThe belief that there is inefficiency, or the potential to improve patient health at current levels of spending, is driving the push for greater value in health care. Previous studies demonstrate overuse of a narrow set of services, suggesting provider inefficiency, but existing studies neither quantify inefficiency more broadly nor assess its variation across physician organizations (POs).Data and methodsWe used data on quality of care and total cost of care from 129 California POs participating in a statewide value-based pay-for-performance program. We estimated a production function with quality as the output and cost as the input, using a stochastic frontier model, to develop a measure of relative efficiency for each PO. To validate the efficiency measure, we examined correlations of PO efficiency estimates with indicators representing overuse of services.ResultsThe estimated production function showed that PO quality was positively associated with costs, although there were diminishing marginal returns to spending. A certain minimum level of spending was associated with high quality even among efficient POs. Most strikingly, however, POs had substantial variation in efficiency, producing widely differing levels of quality for the same cost.ConclusionsDifferences among POs in the efficiency with which they produce quality suggest opportunities for improvements in care delivery that increase quality without increasing spending.

The expanded use of clinical process-of-care measures to assess the quality of health care in the context of public reporting and pay-for-performance applications has led to a desire to demonstrate the value of such efforts in terms of improved patient outcomes. The inability to observe associations between improved delivery of clinical processes and improved clinical outcomes in practice has raised concerns about the value of holding providers accountable for delivery of clinical processes of care. Analyses that attempt to investigate this relationship are fraught with many challenges, including selection of an appropriate outcome, the proximity of the outcome to the receipt of the clinical process, limited power to detect an effect, small expected effect sizes in practice, potential bias due to unmeasured confounding factors, and difficulties due to changes in measure specification over time. To avoid potentially misleading conclusions about an observed or lack of observed association between a clinical process of care and an outcome in the context of observational studies, individuals conducting and interpreting such studies should carefully consider, evaluate, and acknowledge these types of challenges.

BackgroundThe U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.DesignWe developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as "CDS opportunities," might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists' clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics.

ObjectiveThe validity of quality of care measurement has important implications for practicing clinicians, their patients, and all involved with health care delivery. We used empirical data from managed care patients enrolled in west coast physician organizations to test the hypothesis that observed changes in health-related quality of life across a 2.5-year window reflecting process of care.Data sources/study settingPatient self-report data as well as clinically detailed medical record review regarding 963 patients with chronic disease associated with managed care from three west coast states.Study designProspective cohort study of change in health-related quality of life scores across 30 months as measured by change in SF-12 physical component scores.Data collection/extraction methodsPatient self-report and medical record abstraction.Principal findingsWe found a positive relationship between better process scores and higher burden of illness (p

Few studies of the concordance between patient self-report and medical record data have examined how concordance varies with patient characteristics, and results of such studies have been mixed. Given discrepancies in the quality of care received across patient cohorts, it is important to understand the degree to which concordance metrics are robust across patient characteristics. We hypothesized that concordance between ambulatory medical record and patient survey data varies by patient demographic characteristics, especially education, income, and race/ethnicity. We present the results of bivariate and multivariate analyses including data from 1,270 patients with at least one of: diabetes, ischemic heart disease, asthma or COPD, or low back pain sampled from 39 West Coast medical organizations. We present total agreement, kappa, and survey sensitivity and specificity, stratified by patient demographic and health status characteristics. We conducted logistic regressions to test the impact of patient demographic characteristics, domain of medical care, and health status on these three measures of concordance. Survey sensitivity varied significantly by race/ethnicity in bivariate analyses, but this effect was erased in multivariate analyses. Our findings do not support the hypothesis that patient education, income, or race/ethnicity have an independent effect on concordance when controlling for other factors. However, concordance varied significantly by patient health status. The medical record and patient self-report do not measure quality comparably across patient cohorts. We recommend continued efforts to improve survey data collection across different patient populations and to improve the quality of clinical data. © Springer Science+Business Media, LLC 2006.

ObjectiveTo create an efficient imputation algorithm for imputing the SF-12 physical component summary (PCS) and mental component summary (MCS) scores when patients have one to eleven SF-12 items missing.Study settingPrimary data collection was performed between 1996 and 1998.Study designMulti-pattern regression was conducted to impute the scores using only available SF-12 items (simple model), and then supplemented by demographics, smoking status and comorbidity (enhanced model) to increase the accuracy. A cut point of missing SF-12 items was determined for using the simple or the enhanced model. The algorithm was validated through simulation.Data collectionThirty-thousand-three-hundred and eight patients from 63 physician groups were surveyed for a quality of care study in 1996, which collected the SF-12 and other information. The patients were classified as "chronic" patients if they reported that they had diabetes, heart disease, asthma/chronic obstructive pulmonary disease, or low back pain. A follow-up survey was conducted in 1998.Principal findingsThirty-one percent of the patients missed at least one SF-12 item. Means of variance of prediction and standard errors of the mean imputed scores increased with the number of missing SF-12 items. Correlations between the observed and the imputed scores derived from the enhanced models were consistently higher than those derived from the simple model and the increments were significant for patients with > or =6 missing SF-12 items (p or =6 items missing, leading to estimated scores that are as accurate as that of patients with

ObjectiveTo illustrate, using empirical data, methodological challenges associated with patient responses to longitudinal surveys regarding the quality of process of care and health status, including overall response rate, differential response rate, and stability of responses with time.Data sources/study settingPrimary patient self-report data were collected from 30,308 patients in 1996 and 13,438 patients in 1998 as part of a two-year longitudinal study of quality of care and health status of patients receiving care delivered by 63 physician organizations (physician groups) across three West Coast states.Study designWe analyzed longitudinal, observational data collected by Pacific Business Group on Health (PBGH) from patients aged 18-70 using a four-page survey in 1996 and a similar survey in 1998 to assess health status, satisfaction, use of services, and self-reported process of care. A subset of patients with self-reported chronic disease in the 1996 study received an enriched survey in 1998 to more fully detail processes of care for patients with chronic disease.Data collection/extraction methodsWe measured response rate overall and separately for patients with chronic disease. Logistic regression was used to assess the impact of 1996 predictors on response to the follow-up 1998 survey. We compared process of care scores without and with nonresponse weights. Additionally, we measured stability of patient responses over time using percent agreement and kappa statistics, and examined rates of gender inconsistencies reported across the 1996 and 1998 surveys.Principal findingsIn 1998, response rates were 54 percent overall and 63 percent for patients with chronic disease. Patient demographics, health status, use of services, and satisfaction with care in 1996 were all significant predictors of response in 1998, highlighting the importance of analytic strategies (i.e., application of nonresponse weights) to minimize bias in estimates of care and outcomes associated with longitudinal quality of care and health outcome analyses. Process of care scores weighted for nonresponse differed from unweighted scores (p

OBJECTIVES: Because physicians' decisions drive health care costs and quality, there is growing interest in applying behavioral economics approaches, including behavioral nudges, to influence physicians' decisions. This paper investigates adoption of behavioral nudges by health system--affiliated physician organizations (POs), types of nudges being used, PO leader perceptions of nudge effectiveness, and implementation challenges. STUDY DESIGN: Mixed-methods study design (PO leader survey followed by in-depth qualitative interviews). Purposive sample of 30 health system--affiliated POs in 4 states; POs varied in size and quality performance. METHODS: We collected data between October 2017 and June 2019. The survey asked PO leaders to report their organization's use of 5 categories of nudges to influence primary and specialty physicians' actions. We conducted semistructured phone interviews to confirm survey responses, elicit examples of the nudges that POs reported using, understand how nudges were structured, and identify implementation challenges. We present descriptive tabulations of nudge use and effectiveness ratings. We applied thematic analysis to the interview data. RESULTS: Almost all POs in this study reported nudge use. Clinical templates, patient action lists, and altered order entry were most commonly used. However, PO leaders reported that nudge use was limited to a narrow range of clinical applications, not widespread across the organization, and mostly structured as suggestions rather than default actions or hard stops. CONCLUSIONS: Nudge use remains limited in practice. Opportunities exist to expand use of nudges to influence physician behavior; however, expanding use of behavioral nudges will require PO investment of resources to support their construction and maintenance. [ABSTRACT FROM AUTHOR]