John S. Rumsfeld

Background—: Stress testing after percutaneous coronary intervention (PCI) in fee-for-service settings is common and rates vary by hospital. Rates of stress testing after PCI within integrated healthcare systems, such as the Veterans Affairs (VA) are unknown. Methods and Results—: We evaluated all VA patients who underwent PCI from October 2007 through June 2010. To avoid the influence of Medicare eligibility on rates of stress testing use in the VA, we excluded Medicare eligible patients during the follow-up period. Hospital-level variation in risk-standardized rates of stress testing and the association with 1-year mortality and myocardial infarction was determined from Markov chain Monte Carlo methods. Among 10 293 patients undergoing PCI at 55 VA hospitals, 2239 (21.8%) had a stress test performed within 1 year of PCI and 3902 (37.9%) within 2 years. Most stress tests after PCI were performed with nuclear imaging (79.8%). The hospital-level risk-standardized rate of stress testing differed significantly from the average at 14 hospitals, with 8 (14.5%) hospitals significantly below and 6 (10.9%) hospitals significantly above the average stress testing rate. Hospital-level risk-standardized stress testing rates were not significantly correlated with risk-standardized mortality (Spearman ρ=−0.24; P =0.08) or myocardial infarction rates (Spearman ρ=0.20; P =0.14). Conclusions—: In the VA, nearly 40% of patients underwent stress testing in the 2 years after PCI, which is a third less than published studies from other healthcare systems. However, stress testing rates varied across VA hospitals, suggesting opportunities to optimize the use of stress testing are still present in integrated healthcare systems.

To examine the association between primary care provider turnover in managed care organizations and measures of member satisfaction and preventive care. Retrospective cohort study of a national sample of 615 managed care organizations that reported HEDIS data to the National Committee for Quality Assurance from 1999 through 2001. Multivariable hierarchical regression modeling was used to evaluate the association between health plan primary care provider turnover rate and member satisfaction and preventive care measures, including childhood immunization, well-child visits, cholesterol, diabetes management, and breast and cervical cancer screening, adjusting for patient and organizational characteristics, time, and repeated measures. The median primary care provider turnover rate was 7.1% (range, 0%-53.3%). After adjustment for plan characteristics, health plans with higher primary care provider turnover rates had significantly lower measures of member satisfaction, including overall rating of healthcare (P < .01). A 10% higher primary care provider turnover rate was associated with 0.9% fewer members rating high overall satisfaction with healthcare. Health plans with higher provider turnover rates also had lower rates of preventive care, including childhood immunization (P = .045), well-child visits (P = .002), cholesterol screening after cardiac event (P = .042), and cervical cancer screening (P = .024). For example, a 10% higher primary care provider turnover was associated with a 2.7% lower rate of child-members receiving well-child visits in the first 15 months of life. Primary care provider turnover is associated with several measures of care quality, including aspects of member satisfaction and preventive care. Future studies should evaluate whether interventions to reduce primary care provider turnover can improve quality of care and patient outcomes.

Background Hyperlipidemia and hypertension are well-established risk factors for recurrent cardiovascular events among patients with ischemic heart disease (IHD). Despite national recommendations, concordance with guidelines for LDL cholesterol and blood pressure remains inadequate. The objectives of this study were to 1) determine concordance rates with LDL cholesterol and BP recommendations; and 2) identify patient factors, processes and structures of care associated with guideline concordance among VA IHD patients. Methods This was a cross sectional study of veterans with IHD from 8 VA hospitals. Outcomes were concordance with LDL guideline recommendations (LDL<100 mg/dl), and BP recommendations (<140/90 mm Hg). Cumulative logit and hierarchical logistic regression analyses were performed to identify patient factors, processes, and structures of care independently associated with guideline concordance. Results Of 14,114 veterans with IHD, 55.7% had hypertension, 71.5% had hyperlipidemia, and 41.6% had both conditions. Guideline concordance for LDL and BP were 38.9% and 53.4%, respectively. However, only 21.9% of the patients achieved both LDL <100 mg/dl and BP <140/90 mm Hg. In multivariable analyses, patient factors including older age and the presence of vascular disease were associated with worse guideline concordance. In contrast, diabetes was associated with better guideline concordance. Several process of care variables, including higher number of outpatient visits, higher number of prescribed medications, and a recent cardiac hospitalization were associated with better guideline concordance. Among structures of care, having on-site cardiology was associated with a trend towards better guideline concordance. Conclusion Guideline concordance with secondary prevention measures among IHD patients remains suboptimal. It is hoped that the findings of this study can serve as an impetus for quality improvement efforts to improve upon secondary prevention measures and reduce the morbidity and mortality of patients with known IHD.

Background: Few studies report on the effect of organizational factors facilitating transfer between primary and tertiary care hospitals either within an integrated health care system or outside it. In this paper, we report on the relationship between degree of clinical integration of cardiology services and transfer rates of acute coronary syndrome (ACS) patients from primary to tertiary hospitals within and outside the Veterans Health Administration (VHA) system. Methods: Prospective cohort study. Transfer rates were obtained for all patients with ACS diagnoses admitted to 12 primary VHA hospitals between 1998 and 1999. Binary variables measuring clinical integration were constructed for each primary VHA hospital reflecting: presence of on-site VHA cardiologist; referral coordinator at the associated tertiary VHA hospital; and/or referral coordinator at the primary VHA hospital. We assessed the association between the integration variables and overall transfer from primary to tertiary hospitals, using random effects logistic regression, controlling for clustering at two levels and adjusting for patient characteristics. Results: Three of twelve hospitals had a VHA cardiologist on site, six had a referral coordinator at the tertiary VHA hospital, and four had a referral coordinator at the primary hospital. Presence of a VHA staff cardiologist on site and a referral coordinator at the tertiary VHA hospital decreased the likelihood of any transfer (OR 0.45, 95% CI 0.27–0.77, and 0.46, p = 0.002, CI 0.27–0.78). Conversely, having a referral coordinator at the primary VHA hospital increased the likelihood of transfer (OR 6.28, CI 2.92–13.48). Conclusions: Elements of clinical integration are associated with transfer, an important process in the care of ACS patients. In promoting optimal patient care, clinical integration factors should be considered in addition to patient characteristics.

Background: The objective of this study was to demonstrate the use of the Heckman two-step method to assess and correct for bias due to missing health related quality of life (HRQL) surveys in a clinical study of acute coronary syndrome (ACS) patients. Methods: We analyzed data from 2,733 veterans with a confirmed diagnosis of acute coronary syndromes (ACS), including either acute myocardial infarction or unstable angina. HRQL outcomes were assessed by the Short-Form 36 (SF-36) health status survey which was mailed to all patients who were alive 7 months following ACS discharge. We created multivariable models of 7-month post-ACS physical and mental health status using data only from the 1,660 survey respondents. Then, using the Heckman method, we modeled survey non-response and incorporated this into our initial models to assess and correct for potential bias. We used logistic and ordinary least squares regression to estimate the multivariable selection models. Results: We found that our model of 7-month mental health status was biased due to survey non-response, while the model for physical health status was not. A history of alcohol or substance abuse was no longer significantly associated with mental health status after controlling for bias due to non-response. Furthermore, the magnitude of the parameter estimates for several of the other predictor variables in the MCS model changed after accounting for bias due to survey non-response. Conclusion: Recognition and correction of bias due to survey non-response changed the factors that we concluded were associated with HRQL seven months following hospital admission for ACS as well as the magnitude of some associations. We conclude that the Heckman two-step method may be a valuable tool in the assessment and correction of selection bias in clinical studies of HRQL.