Impact of Patient-Centered Medical Home Implementation on Diabetes Control in the Veterans Health Administration.

BACKGROUND: Given its widespread dissemination across primary care, the Veterans Health Administration (VA) is an ideal setting to examine the impact of the patient-centered medical home (PCMH) on diabetes outcomes. OBJECTIVE: To assess the impact of PCMH implementation on diabetes outcomes among patients receiving care in the Veterans Health Administration. DESIGN: Retrospective cohort analysis and multilevel logistic regression. PATIENTS: Twenty thousand eight hundred fifty-eight patients in one Midwest VA network who had a diabetes diagnosis in both 2009 and 2012 and who received primary care between October 1, 2008 and September 30, 2009. MAIN MEASURES: Glycemic and lipid control using VA quality indicators [hemoglobin (Hb) A1c < 9%, low-density lipoprotein cholesterol (LDL-C) < 100 mg/dL]. KEY RESULTS: Odds of glycemic control were lower in 2012 than 2009 (OR = 0.72, 95% CI = 0.67-0.77, p < 0.001), and this change in control over time varied by race (OR of the interaction between time and race = 1.18, 95% CI = 1.02-1.36, p = 0.028). While the disparity in glycemic control between white and black patients persisted post-PCMH, the magnitude of the disparity was smaller in 2012 compared to 2009 (2012: OR = 1.32, 95% CI = 1.18-1.47, p < 0.0001 and 2009: OR = 1.59, 95% CI = 1.39-1.82, p < 0.0001). Odds of lipid control did not significantly change between 2009 and 2012 and change did not vary by race and/or gender. CONCLUSIONS: Although there were no significant improvements in odds of lipid control, and odds of glycemic control decreased following PCMH implementation, there was evidence of reduced racial disparities in glycemic control post-PCMH implementation.

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'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. 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' 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%) to an increase of $18.20 (+7.4%) for medication use (interquartile range, -14.4% to 0%) and a decrease of $100.10 (-31.4%) to an increase of $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.

Proxy use of patient portals on behalf of children: Federally Qualified Health Centers as a case study.

Objective: This study examined the proxy use of patient portals for children in a large Federally Qualified Health Centers (FQHC) network in Texas. Methods: We used de-identified individual-level data of patients, 0-18 years, who had 1+ visits between December 2018 and November 2020. Logistic regression was used to examine patient-, clinic-, and geographic-level factors associated with portal usage by an assumed proxy (i.e. parent or guardian). Results: The proxy portal usage rate increased from 28% in the pre-pandemic months (November 2018-February 2020) to 34% in the pandemic months (March-Nov 2020). Compared to patients 0-5 years, patients aged 6 to 18 years had lower odds of portal usage (6-10 OR: 0.77, p < 0.001; 11-14 OR: 0.62, p < 0.001; 15-18 OR: 0.51, p < 0.001). Minoritized groups had significantly lower odds of portal usage when compared to their non-Hispanic White counterparts (non-Hispanic Black OR: 0.78, p < 0.001; Hispanic OR 0.63, p < 0.001; Asian OR: 0.69, p < 0.001). Having one chronic condition was associated with portal usage (OR: 1.57, p < 0.001); however, there were no significant differences in portal usage between those with none or multiple chronic conditions. Portal usage also varied by service lines, with obstetrics and gynecology (OR: 1.84, p < 0.001) and behavioral health (OR 1.82, p < 0.001) having the highest odds of usage when compared to pediatrics. Having a telemedicine visit was the strongest predictor of portal usage (OR: 2.30, p < 0.001), while residence in zip codes with poor broadband internet access was associated with lower odds of portal usage (OR: 0.97, p < 0.001). Conclusion: While others have reported portal usage rates as high as 64% in pediatric settings, our analysis suggests proxy portal usage rates of 30% in pediatric FQHC settings, with race/ethnicity, age group, and chronic disease status being significant drivers of portal non-usage. These findings highlight the need for appropriate and responsive health information technology approaches for vulnerable populations receiving care in low-resource settings.

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

IMPORTANCE: Pay for performance is intended to align incentives to promote high-quality care, but results have been contradictory. OBJECTIVE: To test the effect of explicit financial incentives to reward guideline-recommended hypertension care. DESIGN, SETTING, AND PARTICIPANTS: Cluster 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). INTERVENTIONS: Physician-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 MEASURES: Among 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. RESULTS: Mean (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 RELEVANCE: Individual 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 REGISTRATION: clinicaltrials.gov Identifier: NCT00302718.

Examining longitudinal disparities in COVID-19 prevalence in the U.S.: a county level growth rate perspective.

Background: The objectives of the present study are to understand the longitudinal variability in COVID-19 reported cases at the county level and to associate the observed rates of infection with the adoption and lifting of stay-home orders.Materials and Methods: The study uses the trajectory of the pandemic in a county and controls for social and economic risk factors, physical environment, and health behaviors to elucidate the social determinants contributing to the observed rates of infection.Results and conclusion: Results indicated that counties with higher percentages of young individuals, racial and ethnic minorities and, higher population densities experienced greater difficulty suppressing transmission.Except for Education and the Gini Index, all factors were influential on the rate of COVID-19 spread before and after stay-home orders. However, after lifting the orders, six of the factors were not influential on the rate of spread; these included: African-Americans, Population Density, Single Parent Households, Average Daily PM2.5, HIV Prevalence Rate, and Home Ownership. It was concluded that different factors from the ones controlling the initial spread of COVID-19 are at play after stay-home orders are lifted.KEY MESSAGESObserved rates of COVID-19 infection at the County level in the U.S. are not directly associated with adoption and lifting of stay-home orders.Disadvantages in sociodemographic determinants negatively influence the rate of COVID-19 spread.Counties with more young individuals, racial and ethnic minorities, and higher population densities have greater difficulty suppressing transmission.

Institutional, provider, and patient correlates of low-density lipoprotein and non-high-density lipoprotein cholesterol goal attainment according to the Adult Treatment Panel III guidelines.

BACKGROUND: The aim of this analysis was to identify the proportion of coronary heart disease (CHD) patients achieving guideline-recommended low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) goals and to identify correlates of dual goal attainment. METHODS: We analyzed patient, provider, and facility characteristics for 21,801 CHD patients in one Veterans Affairs Hospitals Network. RESULTS: Low-density lipoprotein cholesterol goal attainment was 80%, but optional LDL-C goal attainment was 41%. Of patients with triglycerides ≥200 mg/dL, 51% attained both LDL-C and non-HDL-C goals. Correlates of higher dual goal attainment included older age (65-74 years: odds ratio [OR] 1.47, 95% CI 1.28-1.69), diabetes (OR 1.33, 95% CI 1.16-1.53), obesity (OR 1.25, 95% CI 1.04-1.50), a higher number of primary care visits (OR 1.04, 95% CI 1.04-1.05), and mild increase in illness severity of patients in provider's panel (OR 1.20, 95% CI 1.0008-1.46), whereas African American patients were less likely to achieve dual lipid goals (OR 0.63, 95% CI 0.48-0.82). Receipt of care from physician (vs nonphysician) or specialist (vs primary care) provider, number of patients in provider's panel, and percentage of patients in provider's panel with diagnosis of hyperlipidemia were not associated with dual goal attainment. CONCLUSIONS: A large proportion of CHD patients attained LDL-C goal, but optional LDL-C goal attainment was low. Patients with elevated triglycerides had poor attainment of dual LDL-C and non-HDL-C goals, suggesting a treatment gap. Factors associated with dual goal attainment may identify interventions needed to improve future guideline adherence.

Frequency and correlates of treatment intensification for elevated cholesterol levels in patients with cardiovascular disease.

BACKGROUND: Although current performance measures define low-density-lipoprotein cholesterol (LDL-C) levels <100 mg/dL in patients with cardiovascular disease (CVD) as good quality, they provide a snapshot and do not address whether treatment intensification was performed to manage elevated LDL-C levels. METHODS: We determined the proportion of patients with CVD (n = 22,888) with LDL-C <100 mg/dL and the proportion with uncontrolled LDL-C levels (≥100 mg/dL) who received treatment intensification within the 45-day follow-up in a Veterans Affairs Network. We evaluated facility, provider, and patient correlates of treatment intensification. RESULTS: Low-density-lipoprotein cholesterol levels were at goal in 16,350 (71.4%) patients. An additional 2,093 (one third of those eligible for treatment intensification) received treatment intensification. Controlling for clustering between facilities and patient's illness severity: history of diabetes (odds ratio [OR] 1.15, 95% CI 1.01-1.32), hypertension (OR 1.19, 95% CI 1.01-1.42), good medication adherence (OR 2.20, 95% CI 1.91-2.54), and a higher number of lipid panels (OR 1.20, 95% CI 1.14-1.27) were associated with treatment intensification. Patients older than 75 years (OR 0.65, 95% CI 0.56-0.75) and women (OR 0.66, 95% CI 0.43-1.00) were less likely to receive treatment intensification. Teaching status of the facility, physician or specialist primary care provider, and patient's race were not associated with treatment intensification. CONCLUSIONS: Only one third of the CVD patients with elevated LDL-C received treatment intensification. Diabetic and hypertensive patients were more likely to receive treatment intensification, whereas, older patients, female patients, and patients with poor medication adherence were less likely to receive treatment intensification. Our findings highlight areas for quality improvement initiatives.

Impact of comorbidity type on measures of quality for diabetes care.

OBJECTIVE: Studies provide conflicting results about the impact of comorbid conditions on the quality of chronic illness care. We assessed the effect of comorbidity type (concordant, discordant, or both) on the receipt of guideline-recommended care among patients with diabetes. RESEARCH DESIGN: Patients were assigned to 1 of 4 condition groups: diabetes-concordant (hypertension, ischemic heart disease, hyperlipidemia), and/or diabetes-discordant (arthritis, depression, chronic obstructive pulmonary disease) conditions, or neither. We evaluated hemoglobin A1c, blood pressure, and low-density lipoprotein cholesterol readings at index and measured overall good quality of diabetes care, including a 6-month follow-up interval. We assessed the effect of condition group on overall good quality of care with logistic regression and generalized ordered logistic regression. RESULTS: We assigned 35,872 patients to the diabetes comorbid condition groups, ranging from 2.0% in the discordant-only group to 58.0% in the concordant-only group. Patients with both types of conditions were more likely than those with no comorbidities to receive overall good quality for glycemic [odds ratio (OR), 2.13; 95% confidence interval (CI), 1.86-2.41], blood pressure (OR, 1.62; 95% CI, 1.40-1.84), and low-density lipoprotein cholesterol (OR, 3.57; 95% CI, 3.08-4.05) control within 6 months of an index visit. They were also more likely to receive overall good quality for all 3 quality measures combined (OR, 2.17; 95% CI, 1.96-2.39). CONCLUSIONS: Patients with the greatest clinical complexity were more likely than less complex patients to receive high quality diabetes care, suggesting that increased complexity does not necessarily predispose chronically ill patients to receiving poorer care. However, caution should be used in treating certain patient groups, such as the elderly, for whom adherence to multiple condition-specific guidelines may lack benefit or cause harm.

Overcoming COVID-19 Vaccine Hesitancy: Insights from an Online Population-Based Survey in the United States.

This study sought to identify individual-level determinants of COVID-19 vaccine hesitancy based on the Health Belief Model (HBM) and Theory of Planned Behavior (TPB). An online population-based survey was distributed in English and Spanish. Data were derived from 1208 U.S. adults (52% female; 38.7% minorities), 43.5% of whom reported vaccine hesitancy. Multivariable analysis revealed that unemployed individuals were more likely (OR = 1.78, 95% CI: 1.16-2.73, p = 0.009) and married (OR = 0.57, 95% CI: 0.39-0.81, p = 0.002) and higher income individuals (OR = 0.52, 95% CI 0.32-0.84, p = 0.008) were less likely to be hesitant. Individuals with greater perceived susceptibility to COVID-19 (OR = 0.82, 95% CI: 0.71-0.94, p = 0.006), who perceived vaccination as being convenient (OR = 0.86, 95% CI: 0.74-1.00, p = 0.047), and who afforded greater importance to cues to action from government (OR = 0.84, 95% CI: 0.74-0.95, p = 0.005), public health (OR = 0.70, 95% CI: 0.59-0.82, p < 0.001), and healthcare experts (OR = 0.59, 95% CI: 0.50-0.69, p < 0.001) were also less likely to be hesitant. Findings suggest that HBM and TPB constructs may be useful in informing strategies to improve COVID-19 vaccine uptake. Specifically, framing appeals based on perceptions of COVID-19 susceptibility, making vaccination convenient, and rebuilding trust through unified cues to action may help to overcome vaccine hesitancy.

Toward the Development of the Perfect Medical Team: Critical Components for Adaptation.

OBJECTIVE: Medical teams play a vital role in the delivery of safe and effective patient care. Toward the goal of becoming a high-reliability health system, the authors posit that the "perfect" medical team is one that develops their attitudes, behaviors, and cognitions (ABCs) to facilitate adaptation. METHODS: The authors synthesized the literature (frameworks, measures, and conceptual models) on teamwork in healthcare (k = 161) to develop an evidence-based model of ABCs, which current evidence suggests, are requisite for medical team adaptation. Clinical vignettes were garnered from the media and other sources to illustrate how these ABCs-or failure in using these ABCs-can lead to positive or negative events in healthcare. RESULTS: The resulting model contains the most frequently included ABCs in healthcare teamwork models, measures, and frameworks: psychological safety (41, 25.5%), situation assessment (66, 41.0%), shared mental models (56, 34.8%), team leadership behaviors (78, 48.4%), role awareness (64, 39.7%), team decision-making (61, 37.9%) and planning (41, 25.5%), conflict management (51, 31.7%), task coordination (71, 44.1%), adaptation (46, 28.6%), and backup behavior (54, 33.5%). The authors posit that communication and organizational conditions-other highly cited components-(141, 87.6%, and 90, 55.9%, respectively) serve as moderators of these relationships. CONCLUSIONS: The authors argue that each of these ABCs is critical for enhancing team adaptation and subsequently increasing patient safety. A list of practical tools and educational strategies that teams and organizations can use to improve their performance on each of these ABCs is provided.

Will hypertension performance measures used for pay-for-performance programs penalize those who care for medically complex patients?

BACKGROUND: There is concern that performance measures, patient ratings of their care, and pay-for-performance programs may penalize healthcare providers of patients with multiple chronic coexisting conditions. We examined the impact of coexisting conditions on the quality of care for hypertension and patient perception of overall quality of their health care. METHODS AND RESULTS: We classified 141 609 veterans with hypertension into 4 condition groups: those with hypertension-concordant (diabetes mellitus, ischemic heart disease, dyslipidemia) and/or -discordant (arthritis, depression, chronic obstructive pulmonary disease) conditions or neither. We measured blood pressure control at the index visit, overall good quality of care for hypertension, including a follow-up interval, and patient ratings of satisfaction with their care. Associations between condition type and number of coexisting conditions on receipt of overall good quality of care were assessed with logistic regression. The relationship between patient assessment and objective measures of quality was assessed. Of the cohort, 49.5% had concordant-only comorbidities, 8.7% had discordant-only comorbidities, 25.9% had both, and 16.0% had none. Odds of receiving overall good quality after adjustment for age were higher for those with concordant comorbidities (odds ratio, 1.78; 95% confidence interval, 1.70 to 1.87), discordant comorbidities (odds ratio, 1.32; 95% confidence interval, 1.23 to 1.41), or both (odds ratio, 2.25; 95% confidence interval, 2.13 to 2.38) compared with neither. Findings did not change after adjustment for illness severity and/or number of primary care and specialty care visits. Patient assessment of quality did not vary by the presence of coexisting conditions and was not related to objective ratings of quality of care. CONCLUSIONS: Contrary to expectations, patients with greater complexity had higher odds of receiving high-quality care for hypertension. Subjective ratings of care did not vary with the presence or absence of comorbid conditions. Our findings should be reassuring to those who care for the most medically complex patients and are concerned that they will be penalized by performance measures or patient ratings of their care.

Development of a Hybrid, Interprofessional, Interactive Quality Improvement Curriculum as a Model for Continuing Professional Development.

Over the past 20 years, there has been an increased focus on quality improvement (QI) in health care, which is critical in achieving care that is patient-centered, safer, timelier, and more effective, efficient, and equitable. At the center of this movement is QI education, which is known to lead to learning, behavior change, and improved outcomes. However, there is a need for the development and provision of long-duration, interactive, interprofessional training in QI, to allow for in-depth learning and application of learned skills. To this end, we designed a curriculum for an established interprofessional, interactive, web-based QI fellowship for doctorally prepared clinicians. Curricular content is delivered virtually to geographically dispersed learners over a 2-year time span. The didactic curriculum and experiential learning opportunities provide learners with the foundational knowledge and practical skills to engage in-and eventually, lead-QI initiatives around the country. Evaluation of learner satisfaction and cognitive, affective, and skills-based learning has found that this model is an effective method to train geographically distributed learners. A hybrid training structure is used, where learners interact with the material through 3 distinct delivery modes: (1) virtual instruction in QI topics; (2) face-to-face training, mentorship, and the opportunity for practical application of applied knowledge and skills through the completion of QI projects; and (3) opportunities for other types of training, tailored to each learner's Individual Development Plan. This training program model holds value for QI learning in various health care settings, which are interprofessional by nature. These foundational concepts of hybrid learning to distributed learners-wherein an instructor delivers curriculum in small, face-to-face batches, interprofessional learning is supplemented in a virtual, longitudinal manner, and learners are allowed the opportunity to put skills into action for real-world problems in interdisciplinary clinical teams-can be applied in a multitude of settings, with comparatively lower time and cost expenditure than traditional training programs.

Qualitative findings on building a partnered approach to implementation of a group-based diabetes intervention in VA primary care.

OBJECTIVE: Conduct a formative evaluation to inform the implementation of 'Empowering Patients in Chronic Care' (EPIC), an evidence-based interdisciplinary group medical appointment intervention to improve collaborative goal-setting in patients with treated but uncontrolled diabetes. DESIGN: The formative evaluation involved qualitative, in-depth interviews with clinicians, structured according to the Promoting Action on Research in Health Services framework. Interviews elicited (1) participants' knowledge regarding interdisciplinary group self-management and goal-setting programmes and how well clinicians embrace these interventions (evidence), (2) physical and social climate at each target facility and how the intervention can best be embedded into routine primary care (context) and (3) site-specific needs to be addressed by our implementation team and clinicians' preparedness and intentions to participate in the intervention (facilitation). SETTING: Clinicians were part of a primary care setting at one of five participating medical facilities within one Veterans Health Administration Veterans Affairs regional network. PARTICIPANTS: We interviewed a snowball sample of 35 interdisciplinary clinicians engaged in diabetes management, practising leadership and administrators at target sites. RESULTS: Most participants had previous experience with diabetes group self-management programmes and viewed group appointments as an effective approach to enhancing care. Discussions about existing group appointments provided a context for evaluating potential barriers and facilitators to implementing EPIC into target sites. Interviews revealed clinicians' expectations about the roles they would play in the intervention, their assessments of the roles and strategies to facilitate their performance in those roles. CONCLUSIONS: Successful implementation of evidence-based practices into routine care requires a partnered approach with engaged local staff. The intervention should address local goals and research objectives to encourage bidirectional engagement. Robust partnerships are nurtured further by sustained, open communication and must consider the context, target population and local experience to address barriers and facilitators to implementation.

Evaluation of a Distance Learning Curriculum for Interprofessional Quality Improvement Leaders.

As health care systems move toward value-based care, training future leaders in quality improvement (QI) is essential. Web-based training allows for broad dissemination of QI knowledge to geographically distributed learners. The authors conducted a longitudinal evaluation of a structured, synchronous web-based, advanced QI curriculum that facilitated engagement and real-time feedback. Learners (n = 54) were satisfied (overall satisfaction; M = 3.31/4.00), and there were improvements in cognitive (immediate QI knowledge tests; P = .02), affective (self-efficacy of QI skills; P < .001), and skill-based learning (Quality Improvement Knowledge Application Tool; P < .001). There was significant improvement in affective transfer (interprofessional attitudes on the job; p < .01) but no significant change on cognitive (distal QI knowledge test; P = .91), or skill-based transfer (self-reported interprofessional collaboration job skills; P = .23). The findings suggest that this model can be effective to train geographically distributed future QI leaders.

Does pay-for-performance improve the quality of health care?

BACKGROUND: Most physicians and hospitals are paid the same regardless of the quality of the health care they provide. This produces no financial incentives and, in some cases, produces disincentives for quality. Increasing numbers of programs link payment to performance. PURPOSE: To systematically review studies assessing the effect of explicit financial incentives for improved performance on measures of health care quality. DATA SOURCES: PubMed search of English-language literature (1 January 1980 to 14 November 2005), and reference lists of retrieved articles. STUDY SELECTION: Empirical studies of the relationship between explicit financial incentives designed to improve health care quality and a quantitative measure of health care quality. DATA EXTRACTION: The authors categorized studies according to the level of the incentive (individual physician, provider group, or health care payment system) and the type of quality measure rewarded. DATA SYNTHESIS: Thirteen of 17 studies examined process-of-care quality measures, most of which were for preventive services. Five of the 6 studies of physician-level financial incentives and 7 of the 9 studies of provider group-level financial incentives found partial or positive effects on measures of quality. One of the 2 studies of incentives at the payment-system level found a positive effect on access to care, and 1 showed evidence of a negative effect on access to care for the sickest patients. In all, 4 studies suggested unintended effects of incentives. The authors found no studies examining the optimal duration of financial incentives for quality or the persistence of their effects after termination. Only 1 study addressed cost-effectiveness. LIMITATIONS: Few empirical studies of explicit financial incentives for quality were available for review. CONCLUSIONS: Ongoing monitoring of incentive programs is critical to determine the effectiveness of financial incentives and their possible unintended effects on quality of care. Further research is needed to guide implementation of financial incentives and to assess their cost-effectiveness.

Impact of a Pay-for-Performance Program on Care for Black Patients with Hypertension: Important Answers in the Era of the Affordable Care Act.

OBJECTIVE: Evaluate the effect of a pay-for-performance intervention on the quality of hypertension care provided to black patients and determine whether it produced risk selection. DATA SOURCE/STUDY SETTING: Primary data collected between 2007 and 2009 from Veterans Affairs physicians and their primary care panels. STUDY DESIGN: Nested study within a cluster randomized controlled trial of three types of financial incentives and no incentives (control). We compared the proportion of physicians' black patients meeting hypertension performance measures for baseline and final performance periods. We measured risk selection by comparing the proportion of patients who switched providers, patient visit frequency, and panel turnover. Due to limited power, we prespecified in the analysis plan combining the three incentive groups and oversampling black patients. DATA COLLECTION/EXTRACTION METHOD: Data collected electronically and by chart review. PRINCIPAL FINDINGS: The proportion of black patients who achieved blood pressure control or received an appropriate response to uncontrolled blood pressure in the final period was 6.3 percent (95 percent confidence interval, 0.8-11.7 percent) greater for physicians who received an incentive than for controls. There was no difference between intervention and controls in the proportion of patients who switched providers, visit frequency, or panel turnover. CONCLUSIONS AND RELEVANCE: A pay-for-performance intervention improved blood pressure control or appropriate response to uncontrolled blood pressure in black patients and did not produce risk selection.

Statin Use and Its Facility-Level Variation in Patients With Diabetes: Insight From the Veterans Affairs National Database.

We sought to determine use of any and at least moderate-intensity statin therapy in a national sample of patients with diabetes mellitus (DM), with the hypothesis that nationwide frequency and facility-level variation in statin therapy are suboptimal. We sampled patients with DM age 40 to 75 years receiving primary care between October 1, 2012, and September 30, 2013, at 130 parent facilities and associated community-based outpatient clinics in the Veterans Affairs Health Care System. We examined frequency and facility-level variation in use of any or at least moderate-intensity statin therapy (mean daily dose associated with ≥30% low-density lipoprotein cholesterol lowering). In 911 444 patients with DM, 68.3% and 58.4% were receiving any and moderate- to high-intensity statin therapy, respectively. Patients receiving statin had higher burden of cardiovascular disease, were more likely to be on nonstatin lipid-lowering therapy and to receive care at a teaching facility, and had more frequent primary-care visits. Median facility-level uses of any and at least moderate-intensity statin therapy were 68.7% (interquartile range, 65.9%-70.8%) and 58.6% (interquartile range, 55.8%-61.4%), respectively. After adjusting for several patient-related and some facility-related characteristics, the median rate ratios for any and moderate- to high-intensity statin therapy were 1.20 (95% confidence interval: 1.18-1.22) and 1.29 (95% confidence interval: 1.24-1.33) respectively, indicating 20% to 29% variation in statin use between 2 identical patients receiving care at 2 random facilities. Statin use was suboptimal in a national sample of patients with DM with modest facility-level variation, likely indicating differences in statin-prescribing patterns.