Design, rationale, and baseline characteristics of a cluster randomized controlled trial of pay for performance for hypertension treatment: study protocol

<p>Abstract</p> <p>Background</p> <p>Despite compelling evidence of the benefits of treatment and well-accepted guidelines for treatment, hypertension is controlled in less than one-half of United States citizens.</p> <p>Methods/design</p> <p>This randomized controlled trial tests whether explicit financial incentives promote the translation of guideline-recommended care for hypertension into clinical practice and improve blood pressure (BP) control in the primary care setting. Using constrained randomization, we assigned 12 Veterans Affairs hospital outpatient clinics to four study arms: physician-level incentive; group-level incentive; combination of physician and group incentives; and no incentives (control). All participants at the hospital (cluster) were assigned to the same study arm. We enrolled 83 full-time primary care physicians and 42 non-physician personnel. The intervention consisted of an educational session about guideline-recommended care for hypertension, five audit and feedback reports, and five disbursements of incentive payments. Incentive payments rewarded participants for chart-documented use of guideline-recommended antihypertensive medications, BP control, and appropriate responses to uncontrolled BP during a prior four-month performance period over the 20-month intervention. To identify potential unintended consequences of the incentives, the study team interviewed study participants, as well as non-participant primary care personnel and leadership at study sites. Chart reviews included data collection on quality measures not related to hypertension. To evaluate the persistence of the effect of the incentives, the study design includes a washout period.</p> <p>Discussion</p> <p>We briefly describe the rationale for the interventions being studied, as well as the major design choices. Rigorous research designs such as the one described here are necessary to determine whether performance-based payment arrangements such as financial incentives result in meaningful quality improvements.</p> <p>Trial Registration</p> <p><url>http://www.clinicaltrials.gov</url><a href="http://www.clinicaltrials.gov/ct2/show/NCT00302718">NCT00302718</a></p

Identification of Emergency Care-Sensitive Conditions and Characteristics of Emergency Department Utilization.

Importance: Monitoring emergency care quality requires understanding which conditions benefit most from timely, quality emergency care. Objectives: To identify a set of emergency care-sensitive conditions (ECSCs) that are treated in most emergency departments (EDs), are associated with a spectrum of adult age groups, and represent common reasons for seeking emergency care and to provide benchmark national estimates of ECSC acute care utilization. Design, Setting, and Participants: A modified Delphi method was used to identify ECSCs. In a cross-sectional analysis, ECSC-associated visits by adults (aged ≥18 years) were identified based on International Statistical Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes and analyzed with nationally representative data from the 2016 US Nationwide Emergency Department Sample. Data analysis was conducted from January 2018 to December 2018. Main Outcomes and Measures: Identification of ECSCs and ECSC-associated ED utilization patterns, length of stay, and charges. Results: An expert panel rated 51 condition groups as emergency care sensitive. Emergency care-sensitive conditions represented 16 033 359 of 114 323 044 ED visits (14.0%) in 2016. On average, 8 535 261 of 17 886 220 ED admissions (47.7%) were attributed to ECSCs. The most common ECSC ED visits were for sepsis (1 716 004 [10.7%]), chronic obstructive pulmonary disease (1 273 319 [7.9%]), pneumonia (1 263 971 [7.9%]), asthma (970 829 [6.1%]), and heart failure (911 602 [5.7%]) but varied by age group. Median (interquartile range) length of stay for ECSC ED admissions was longer than non-ECSC ED admissions (3.2 [1.7-5.8] days vs 2.7 [1.4-4.9] days; P \u3c .001). In 2016, median (interquartile range) ED charges per visit for ECSCs were $2736 ($1684-$4605) compared with$2179 ($1118-$4359) per visit for non-ECSC ED visits (P \u3c .001). Conclusions and Relevance: This comprehensive list of ECSCs can be used to guide indicator development for pre-ED, intra-ED, and post-ED care and overall assessment of the adult, non-mental health, acute care system. Health care utilization and costs among patients with ECSCs are substantial and warrant future study of validation, variations in care, and outcomes associated with ECSCs

Impact of clinical complexity on the quality of diabetes care

Objectives: To assess the impact of clinical complexity on 3 dimensions of diabetes care.Study design: We identified 35,872 diabetic patients receiving care at 7 Veterans Affairs facilities between July 2007 and June 2008 using administrative and clinical data. We examined control at index and appropriate care (among uncontrolled patients) within 90 days, for blood pressure (\u3c130/80 mm Hg), glycated hemoglobin (\u3c7%), and low-density lipoprotein cholesterol (\u3c100 mg/dL). We used ordered logistic regression to examine the impact of complexity, defined by comorbidities count and illness burden, on control at index and a combined measure of quality (control at index or appropriate follow-up care) for all 3 measures.Results: There were 6260 (17.5%) patients controlled at index for all 3 quality indicators. Patients with \u3e3 comorbidities (odds ratio [OR], 1.94; 95% confidence interval [CI], 1.67-2.26) and illness burden \u3e2.00 (OR, 1.22; 95% CI, 1.13-1.32) were more likely than the least complex patients to be controlled for all 3 measures. Patients with \u3e3 comorbidities (OR, 2.30; 95% CI, 2.07-2.54) and illness burden \u3e2.00 (OR, 1.25; 95% CI, 1.18-1.33) were also more likely than the least complex patients to meet the combined quality indicator for all 3 measures.Conclusions: Patients with greatest complexity received higher quality diabetes care compared with less complex patients, regardless of the definition of complexity chosen. Although providers may appropriately target complex patients for aggressive control, deficits in guideline achievement among all diabetic patients highlight the challenges of caring for chronically ill patients and the importance of structuring primary care to promote higher-quality, patient-centered care

Treating chronically ill people with diabetes mellitus with limited life expectancy: Implications for performance measurement

Objectives: To develop an algorithm to identify individuals with limited life expectancy and examine the effect of limited life expectancy on glycemic control and treatment intensification in individuals with diabetes mellitus.Design: Individuals with diabetes mellitus and coexisting congestive heart failure, chronic obstructive pulmonary disease, dementia, end-stage liver disease, and/or primary or metastatic cancer with limited life expectancy were identified. To validate the algorithm, 5-year mortality was assessed in individuals identified as having limited life expectancy. Rates of meeting performance measures for glycemic control between individuals with and without limited life expectancy were compared. In individuals with uncontrolled glycosylated hemoglobin (HbA(1c) ) levels, the effect of limited life expectancy on treatment intensification within 90 days was examined.Setting: One hundred ten Department of Veterans Affairs facilities; October 2006 to September 2007.Participants: Eight hundred eighty-eight thousand six hundred twenty-eight individuals with diabetes mellitus.Measurements: HbA(1c) ; treatment intensification within 90 days of index HbA(1c) reading.Results: Twenty-nine thousand sixteen (3%) participants had limited life expectancy. Adjusting for age, 5-year mortality was five times as high in participants with limited life expectancy than in those without. Participants with limited life expectancy had poorer glycemic control than those without (glycemic control: 77.1% vs 78.1%; odds ratio (OR) = 0.84, 95% confidence interval (CI) = 0.81-0.86) and less-frequent treatment intensification (treatment intensification: 20.9% vs 28.6%; OR = 0.71, 95% CI = 0.67-0.76), even after controlling for patient-level characteristics.Conclusion: Participants with limited life expectancy were less likely than those without to have controlled HbA(1c) levels and to receive treatment intensification, suggesting that providers treat these individuals less aggressively. Quality measurement and performance-based reimbursement systems should acknowledge the different needs of this population

Calculations of financial incentives for providers in a pay-for-performance program: Manual review versus data from structured fields in electronic health records

Background: Hospital report cards and financial incentives linked to performance require clinical data that are reliable, appropriate, timely, and cost-effective to process. Pay-for-performance plans are transitioning to automated electronic health record (EHR) data as an efficient method to generate data needed for these programs.Objective: To determine how well data from automated processing of structured fields in the electronic health record (AP-EHR) reflect data from manual chart review and the impact of these data on performance rewards.Research design: Cross-sectional analysis of performance measures used in a cluster randomized trial assessing the impact of financial incentives on guideline-recommended care for hypertension.Subjects: A total of 2840 patients with hypertension assigned to participating physicians at 12 Veterans Affairs hospital-based outpatient clinics. Fifty-two physicians and 33 primary care personnel received incentive payments.Measures: Overall, positive and negative agreement indices and Cohen\u27s kappa were calculated for assessments of guideline-recommended antihypertensive medication use, blood pressure (BP) control, and appropriate response to uncontrolled BP. Pearson\u27s correlation coefficient was used to assess how similar participants\u27 calculated earnings were between the data sources.Results: By manual chart review data, 72.3% of patients were considered to have received guideline-recommended antihypertensive medications compared with 65.0% by AP-EHR review (κ=0.51). Manual review indicated 69.5% of patients had controlled BP compared with 66.8% by AP-EHR review (κ=0.87). Compared with 52.2% of patients per the manual review, 39.8% received an appropriate response by AP-EHR review (κ=0.28). Participants\u27 incentive payments calculated using the 2 methods were highly correlated (r≥0.98). Using the AP-EHR data to calculate earnings, participants\u27 payment changes ranged from a decrease of $91.00 (-30.3$18.20 (+7.4%) for medication use (interquartile range, -14.4% to 0%) and a decrease of $100.10 (-31.4$36.40 (+15.4%) for BP control or appropriate response to uncontrolled BP (interquartile range, -11.9% to -6.1%).Conclusions: Pay-for-performance plans that use only EHR data should carefully consider the measures and the structure of the EHR before data collection and financial incentive disbursement. For this study, we feel that a 10% difference in the total amount of incentive earnings disbursed based on AP-EHR data compared with manual review is acceptable given the time and resources required to abstract data from medical records

Hospital-level variation in risk-standardized admission rates for emergency care–sensitive conditions among older and younger Veterans

ObjectivesResearch examining emergency department (ED) admission practices within the Department of Veterans Affairs (VA) is limited. This study investigates facility-level variation in risk-standardized admission rates (RSARs) for emergency care–sensitive conditions (ECSCs) among older (≥65 years) and younger (<65 years) Veterans across VA EDs.MethodsVeterans presenting to a VA ED for an ECSC between October 1, 2016 and September 30, 2019 were identified and the 10 most common ECSCs established. ECSC-specific RSARs were calculated using hierarchical generalized linear models, adjusting for Veteran and encounter characteristics. The interquartile range ratio (IQR ratio) and coefficient of variation were measures of dispersion for each condition and were stratified by age group. Associations with facility characteristics were also examined in condition-specific multivariable models.ResultsThe overall cohort included 651,336 ED visits across 110 VA facilities for the 10 most common ECSCs—chronic obstructive pulmonary disease (COPD), heart failure, pneumonia, volume depletion, tachyarrhythmias, acute diabetes mellitus, gastrointestinal (GI) bleeding, asthma, sepsis, and myocardial infarction (MI). After adjusting for case mix, the ECSCs with the greatest variation (IQR ratio, coefficient of variation) in RSARs were asthma (1.43, 32.12), COPD (1.39, 24.64), volume depletion (1.38, 23.67), and acute diabetes mellitus (1.28, 17.52), whereas those with the least variation were MI (1.01, 0.87) and sepsis (1.02, 2.41). Condition-specific RSARs were not qualitatively different between age subgroups. Association with facility characteristics varied across ECSCs and within condition-specific age subgroups.ConclusionsWe identified unexplained facility-level variation in RSARs for Veterans presenting with the 10 most common ECSCs to VA EDs. The magnitude of variation did not appear to be qualitatively different between older and younger Veteran subgroups. Variation in RSARs for ECSCs may be an important target for systems-based levers to improve value in VA emergency care.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/1/acem14691-sup-0004-Captions.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/2/acem14691_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/3/acem14691-sup-0001-FigureS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/4/acem14691-sup-0002-TableS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/5/acem14691.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/176312/6/acem14691-sup-0003-TableS2.pd

Calculations of Financial Incentives for Providers in a Pay-for-Performance Program: Manual Review Versus Data From Structured Fields in Electronic Health Records.

BackgroundHospital report cards and financial incentives linked to performance require clinical data that are reliable, appropriate, timely, and cost-effective to process. Pay-for-performance plans are transitioning to automated electronic health record (EHR) data as an efficient method to generate data needed for these programs.ObjectiveTo determine how well data from automated processing of structured fields in the electronic health record (AP-EHR) reflect data from manual chart review and the impact of these data on performance rewards.Research designCross-sectional analysis of performance measures used in a cluster randomized trial assessing the impact of financial incentives on guideline-recommended care for hypertension.SubjectsA total of 2840 patients with hypertension assigned to participating physicians at 12 Veterans Affairs hospital-based outpatient clinics. Fifty-two physicians and 33 primary care personnel received incentive payments.MeasuresOverall, positive and negative agreement indices and Cohen's kappa were calculated for assessments of guideline-recommended antihypertensive medication use, blood pressure (BP) control, and appropriate response to uncontrolled BP. Pearson's correlation coefficient was used to assess how similar participants' calculated earnings were between the data sources.ResultsBy manual chart review data, 72.3% of patients were considered to have received guideline-recommended antihypertensive medications compared with 65.0% by AP-EHR review (κ=0.51). Manual review indicated 69.5% of patients had controlled BP compared with 66.8% by AP-EHR review (κ=0.87). Compared with 52.2% of patients per the manual review, 39.8% received an appropriate response by AP-EHR review (κ=0.28). Participants' incentive payments calculated using the 2 methods were highly correlated (r≥0.98). Using the AP-EHR data to calculate earnings, participants' payment changes ranged from a decrease of $91.00 (-30.3$18.20 (+7.4%) for medication use (interquartile range, -14.4% to 0%) and a decrease of $100.10 (-31.4$36.40 (+15.4%) for BP control or appropriate response to uncontrolled BP (interquartile range, -11.9% to -6.1%).ConclusionsPay-for-performance plans that use only EHR data should carefully consider the measures and the structure of the EHR before data collection and financial incentive disbursement. For this study, we feel that a 10% difference in the total amount of incentive earnings disbursed based on AP-EHR data compared with manual review is acceptable given the time and resources required to abstract data from medical records

Inequities in Academic Compensation by Gender

PurposeCross-sectional studies have demonstrated gender differences in salaries within academic medicine. No research has assessed longitudinal compensation patterns. This study sought to assess longitudinal patterns by gender in compensation, and to understand factors associated with these differences in a longitudinal cohort.MethodA 17-year longitudinal follow-up of the National Faculty Survey was conducted with a random sample of faculty from 24 U.S. medical schools. Participants employed full-time at initial and follow-up time periods completed the survey. Annual pretax compensation during academic year 2012-2013 was compared by gender. Covariates assessed included race/ethnicity; years since first academic appointment; retention in academic career; academic rank; departmental affiliation; percent effort distribution across clinical, teaching, administrative, and research duties; marital and parental status; and any leave or part-time status in the years between surveys.ResultsIn unadjusted analyses, women earned a mean of $20,520 less than men (P = .03); women made 90 cents for every dollar earned by their male counterparts. This difference was reduced to$16,982 (P = .04) after adjusting for covariates. The mean difference of $15,159 was no longer significant (P = .06) when adjusting covariates and for those who had ever taken a leave or worked part-time.ConclusionsThe continued gender gap in compensation cannot be accounted for by metrics used to calculate salary. Institutional actions to address these disparities include both initial appointment and annual salary equity reviews, training of senior faculty and administrators to understand implicit bias, and training of women faculty in negotiating skills

Effects of individual physician-level and practice-level financial incentives on hypertension care: a randomized trial.

ImportancePay for performance is intended to align incentives to promote high-quality care, but results have been contradictory.ObjectiveTo test the effect of explicit financial incentives to reward guideline-recommended hypertension care.Design, setting, and participantsCluster randomized trial of 12 Veterans Affairs outpatient clinics with 5 performance periods and a 12-month washout that enrolled 83 primary care physicians and 42 nonphysician personnel (eg, nurses, pharmacists).InterventionsPhysician-level (individual) incentives, practice-level incentives, both, or none. Intervention participants received up to 5 payments every 4 months; all participants could access feedback reports.Main outcomes and measuresAmong a random sample, number of patients achieving guideline-recommended blood pressure thresholds or receiving an appropriate response to uncontrolled blood pressure, number of patients prescribed guideline-recommended medications, and number who developed hypotension.ResultsMean (SD) total payments over the study were $4270 ($459), $2672 ($153), and $1648 ($248) for the combined, individual, and practice-level interventions, respectively. The unadjusted baseline and final percentages and the adjusted absolute change over the study in patients meeting the combined blood pressure/appropriate response measure were 75% to 84% and 8.84% (95% CI, 4.20% to 11.80%) for the individual group, 80% to 85% and 3.70% (95% CI, 0.24% to 7.68%) for the practice-level group, 79% to 88% and 5.54% (95% CI, 1.92% to 9.52%) for the combined group, and 86% to 86% and 0.47% (95% CI, -3.12% to 4.04%) for the control group. The adjusted absolute estimated difference in the change between the proportion of patients with blood pressure control/appropriate response for individual incentive and control groups was 8.36% (95% CI, 2.40% to 13.00%; P=.005). The other incentive groups did not show a significant change compared with controls for this outcome. For medications, the unadjusted baseline and final percentages and the adjusted absolute change were 61% to 73% and 9.07% (95% CI, 4.52% to 13.44%), 56% to 65% and 4.98% (95% CI, 0.64% to 10.08%), 65% to 80% and 7.26% (95% CI, 2.92% to 12.48%), and 63% to 72% and 4.35% (95% CI, -0.28% to 9.28%), respectively. These changes in the use of guideline-recommended medications were not significant in any of the incentive groups compared with controls, nor was the incidence of hypotension. The effect of the incentive was not sustained after a washout.Conclusions and relevanceIndividual financial incentives, but not practice-level or combined incentives, resulted in greater blood pressure control or appropriate response to uncontrolled blood pressure; none of the incentives resulted in greater use of guideline-recommended medications or increased incidence of hypotension compared with controls. Further research is needed on the factors that contributed to these findings.Trial registrationclinicaltrials.gov Identifier: NCT00302718