Marcela Horvitz-Lennon, Margarita Alegría, and Sharon-Lise T Normand. 2012. “The effect of race-ethnicity and geography on adoption of innovations in the treatment of schizophrenia.” Psychiatr Serv, 63, 12, Pp. 1171-7.Abstract
OBJECTIVE: This study evaluated the effect of race-ethnicity and geography on the adoption of a pharmacological innovation (long-acting injectable risperidone [LAIR]) among Medicaid beneficiaries with schizophrenia as well as the contribution of geographic location to observed racial-ethnic disparities. METHODS: The data source was a claims data set from the Florida Medicaid program for the 2.5-year period that followed the launch of LAIR in the U.S. market. Study participants were beneficiaries with schizophrenia who had filled at least one antipsychotic prescription during the study period. The outcome variable was any use of LAIR; model variables were need indicators and random effects for 11 Medicaid areas, which are multicounty units used by the Medicaid program to administer benefits. Adjusted probability of use of LAIR for blacks and Latinos versus whites was estimated with logistic regression models. RESULTS: The study cohort included 13,992 Medicaid beneficiaries: 25% of the cohort was black, 37% Latino, and 38% white. Unadjusted probability of LAIR use was lower for Latinos than whites, and use varied across the state's geographic areas. Adjustment for need confirmed the unadjusted finding of a disparity between Latinos and whites (odds ratio=.58, 95% confidence interval=.49-.70). The inclusion of geographic location in the model eliminated the Latino-white disparity but confirmed the unadjusted finding of geographic variation in adoption. CONCLUSIONS: Within a state Medicaid program, the initial finding of a disparity between Latinos and whites in adopting LAIR was driven by geographic disparities in adoption rates and the geographic concentration of Latinos in a low-adoption area. Possible contributors and implications of these results are discussed.
Sotiris C Stamou, Michael Robich, Robert E Wolf, Ann Lovett, Sharon-Lise T Normand, and Frank W Sellke. 2012. “Effects of gender and ethnicity on outcomes after aortic valve replacement.” J Thorac Cardiovasc Surg, 144, 2, Pp. 486-92.Abstract
OBJECTIVE: To evaluate the clinical outcomes after aortic valve replacement or aortic valve replacement and coronary artery bypass grafting in a large contemporary population, and to determine if outcomes are associated with patient ethnicity and gender status. METHODS: Using the Massachusetts Cardiac Surgery Database, we identified 6809 adults aged 18 years or older who had undergone isolated aortic valve replacement or aortic valve replacement and coronary artery bypass grafting in all non-federal acute-care Massachusetts hospitals from 2002 to 2008. Univariate and multivariate logistic regression analyses were used to identify differences in patient characteristics, major morbidity, and 30-day and 1-year mortality between men (n=4043) and women (n=2766) and between whites (n=6481) and nonwhites (n=328). RESULTS: The unadjusted 30-day mortality rate was 2.6% for the men and 3.1% for the women (P=.296) and 2.8% for whites and 3.7% for nonwhites (P=.342). In adjusted logistic regression models, the 30-day mortality was not different between the female and male patients (odds ratio, 0.88; 95% confidence interval, 0.26-3.02, P=.84) nor between the nonwhites and whites (odds ratio, 1.57; 95% confidence interval, 0.45-5.44; P=.48). The incidence of postoperative stroke was greater in women (3.0% women and 2.2% men, P=.031), and the incidence of postoperative myocardial infarction (10.9% women and 13.6% men; P=.001) and septicemia (1.2% women and 2.0% men; P=.009) was greater in men. CONCLUSIONS: Ethnicity and gender were not associated with greater 30-day and 1-year mortality after aortic valve replacement or aortic valve replacement and coronary artery bypass grafting. Differences in postoperative outcomes were not observed between ethnic groups.
Robert W Yeh, Sharon-Lise T Normand, Yun Wang, Christopher D Barr, and Francesca Dominici. 2012. “Geographic disparities in the incidence and outcomes of hospitalized myocardial infarction: does a rising tide lift all boats?” Circ Cardiovasc Qual Outcomes, 5, 2, Pp. 197-204.Abstract
BACKGROUND: Improvements in prevention have led to declines in incidence and mortality of myocardial infarction (MI) in selected populations. However, no studies have examined regional differences in recent trends in MI incidence, and few have examined whether known regional disparities in MI care have narrowed over time. METHODS AND RESULTS: We compared trends in incidence rates of MI, associated procedures and mortality for all US Census Divisions (regions) in Medicare fee-for-service patients between 2000-2008 (292 773 151 patient-years). Two-stage hierarchical models were used to account for patient characteristics and state-level random effects. To assess trends in geographic disparities, we calculated changes in between-state variance for outcomes over time. Although the incidence of MI declined in all regions (P<0.001 for trend for each) between 2000-2008, adjusted rates of decline varied by region (annual declines ranging from 2.9-6.1%). Widening geographic disparities, as measured by percent change of between-state variance from 2000-2008, were observed for MI incidence (37.6% increase, P=0.03) and percutaneous coronary intervention rates (31.4% increase, P=0.06). Significant declines in risk-adjusted 30-day mortality were observed in all regions, with the fastest declines observed in states with higher baseline mortality rates. CONCLUSIONS: In a large contemporary analysis of geographic trends in MI epidemiology, the incidence of MI and associated mortality declined significantly in all US Census Divisions between 2000-2008. Although geographic disparities in MI incidence may have increased, regional differences in MI-associated mortality have narrowed.
Sherine E Gabriel and Sharon-Lise T Normand. 2012. “Getting the methods right--the foundation of patient-centered outcomes research.” N Engl J Med, 367, 9, Pp. 787-90.
Chohreh Partovian, Scott R Gleim, Purav S Mody, Shu-Xia Li, Haiyan Wang, Kelly M Strait, Larry A Allen, Tara Lagu, Sharon-Lise T Normand, and Harlan M Krumholz. 2012. “Hospital patterns of use of positive inotropic agents in patients with heart failure.” J Am Coll Cardiol, 60, 15, Pp. 1402-9.Abstract
OBJECTIVES: This study sought to determine hospital variation in the use of positive inotropic agents in patients with heart failure. BACKGROUND: Clinical guidelines recommend targeted use of positive inotropic agents in highly selected patients, but data are limited and the recommendations are not specific. METHODS: We analyzed data from 376 hospitals including 189,948 hospitalizations for heart failure from 2009 through 2010. We used hierarchical logistic regression models to estimate hospital-level risk-standardized rates of inotrope use and risk-standardized in-hospital mortality rates. RESULTS: The risk-standardized rates of inotrope use ranged across hospitals from 0.9% to 44.6% (median: 6.3%, interquartile range: 4.3% to 9.2%). We identified various hospital patterns based on the type of agents: dobutamine-predominant (29% of hospitals), dopamine-predominant (25%), milrinone-predominant (1%), mixed dobutamine and dopamine pattern (32%), and mixed pattern including all 3 agents (13%). When studying the factors associated with interhospital variation, the best model performance was with the hierarchical generalized linear models that adjusted for patient case mix and an individual hospital effect (receiver operating characteristic curves from 0.77 to 0.88). The intraclass correlation coefficients of the hierarchical generalized linear models (0.113 for any inotrope) indicated that a noteworthy proportion of the observed variation was related to an individual institutional effect. Hospital rates or patterns of use were not associated with differences in length of stay or risk-standardized mortality rates. CONCLUSIONS: We found marked differences in the use of inotropic agents for heart failure patients among a diverse group of hospitals. This variability, occurring in the context of little clinical evidence, indicates an urgent need to define the appropriate use of these medications.
David M Shahian, Lisa I Iezzoni, Gregg S Meyer, Leslie Kirle, and Sharon-Lise T Normand. 2012. “Hospital-wide mortality as a quality metric: conceptual and methodological challenges.” Am J Med Qual, 27, 2, Pp. 112-23.Abstract
Hospital-wide mortality rates are used as a measure of overall hospital quality. However, their parsimony and apparent simplicity belie significant conceptual and methodological concerns. For many diagnoses included in hospital-wide mortality, the association between short-term mortality and quality of care is not well established. Furthermore, compared with condition-specific or procedure-specific mortality, hospital-wide mortality rates pose greater methodological challenges (ie, eligibility and exclusion criteria, risk adjustment, statistical techniques for aggregating across diagnoses, usability). Many of these result from substantial interprovider heterogeneity in diagnosis frequency, sample sizes, and patient severity. Hospital-wide mortality is problematic as a quality metric for public reporting, although hospitals may elect to use such measures for other purposes. Potential alternative approaches include multidimensional composite metrics or mortality measurement limited to selected conditions and procedures for which the link between hospital mortality and quality is clear, legitimate exclusions are uncommon, and sample sizes, end points, and risk adjustment are adequate.
Catherine A Fullerton, Arnold M Epstein, Richard G Frank, Sharon-Lise T Normand, Christina X Fu, and Thomas G McGuire. 2012. “Medication use and spending trends among children with ADHD in Florida's Medicaid program, 1996-2005.” Psychiatr Serv, 63, 2, Pp. 115-21.Abstract
OBJECTIVE: How the introduction of new pharmaceuticals affects spending for treatment of children with attention-deficit hyperactivity disorder (ADHD) is unknown. This study examined trends in use of pharmaceuticals and their costs among children with ADHD from 1996 to 2005. METHODS: This observational study used annual cohorts of children ages three to 17 with ADHD (N=107,486 unique individuals during the study period) from Florida Medicaid claims to examine ten-year trends in the predicted probability for medication use for children with ADHD with and without psychiatric comorbidities as well as mental health spending and its components. Additional outcome measures included average price per day and average number of days filled for medication classes. RESULTS: Overall, the percentage of children with ADHD treated with ADHD drugs increased from 60% to 63%, and the percentage taking antipsychotics more than doubled, from 8% to 18%. In contrast, rates of antidepressant use declined from 21% to 15%, and alpha agonist use was constant, at 15%. Mental health spending increased 61%, with pharmaceutical spending representing the fastest-rising component (up 192%). Stimulant spending increased 157%, mostly because of increases in price per prescription. Antipsychotic spending increased 588% because of increases in both price and quantity (number of days used). By 2005, long-acting ADHD drugs accounted for over 90% of stimulant spending. CONCLUSIONS: Long-acting ADHD drugs have rapidly replaced short-acting stimulant use among children with ADHD. The use of antipsychotics as a second-tier agent in treating ADHD has overtaken traditional agents such as antidepressants or alpha agonists, suggesting a need for research into the efficacy and side effects of second-generation antipsychotics among children with ADHD.
Dulal K Bhaumik, Anup Amatya, Sharon-Lise Normand, Joel Greenhouse, Eloise Kaizar, Brian Neelon, and Robert D Gibbons. 2012. “Meta-Analysis of Rare Binary Adverse Event Data.” J Am Stat Assoc, 107, 498, Pp. 555-567.Abstract
We examine the use of fixed-effects and random-effects moment-based meta-analytic methods for analysis of binary adverse event data. Special attention is paid to the case of rare adverse events which are commonly encountered in routine practice. We study estimation of model parameters and between-study heterogeneity. In addition, we examine traditional approaches to hypothesis testing of the average treatment effect and detection of the heterogeneity of treatment effect across studies. We derive three new methods, simple (unweighted) average treatment effect estimator, a new heterogeneity estimator, and a parametric bootstrapping test for heterogeneity. We then study the statistical properties of both the traditional and new methods via simulation. We find that in general, moment-based estimators of combined treatment effects and heterogeneity are biased and the degree of bias is proportional to the rarity of the event under study. The new methods eliminate much, but not all of this bias. The various estimators and hypothesis testing methods are then compared and contrasted using an example dataset on treatment of stable coronary artery disease.
2012. “Methodological standards and patient-centeredness in comparative effectiveness research: the PCORI perspective.” JAMA, 307, 15, Pp. 1636-40.Abstract
Rigorous methodological standards help to ensure that medical research produces information that is valid and generalizable, and are essential in patient-centered outcomes research (PCOR). Patient-centeredness refers to the extent to which the preferences, decision-making needs, and characteristics of patients are addressed, and is the key characteristic differentiating PCOR from comparative effectiveness research. The Patient Protection and Affordable Care Act signed into law in 2010 created the Patient-Centered Outcomes Research Institute (PCORI), which includes an independent, federally appointed Methodology Committee. The Methodology Committee is charged to develop methodological standards for PCOR. The 4 general areas identified by the committee in which standards will be developed are (1) prioritizing research questions, (2) using appropriate study designs and analyses, (3) incorporating patient perspectives throughout the research continuum, and (4) fostering efficient dissemination and implementation of results. A Congressionally mandated PCORI methodology report (to be issued in its first iteration in May 2012) will begin to provide standards in each of these areas, and will inform future PCORI funding announcements and review criteria. The work of the Methodology Committee is intended to enable generation of information that is relevant and trustworthy for patients, and to enable decisions that improve patient-centered outcomes.
Sharon-Lise T Normand, Laura Hatfield, Joseph Drozda, and Frederic S Resnic. 2012. “Postmarket surveillance for medical devices: America's new strategy.” BMJ, 345, Pp. e6848.
Frederic S Resnic and Sharon-Lise T Normand. 2012. “Postmarketing surveillance of medical devices--filling in the gaps.” N Engl J Med, 366, 10, Pp. 875-7.
Marc L Berger, Nancy Dreyer, Fred Anderson, Adrian Towse, Art Sedrakyan, and Sharon-Lise Normand. 2012. “Prospective observational studies to assess comparative effectiveness: the ISPOR good research practices task force report.” Value Health, 15, 2, Pp. 217-30.Abstract
OBJECTIVE: In both the United States and Europe there has been an increased interest in using comparative effectiveness research of interventions to inform health policy decisions. Prospective observational studies will undoubtedly be conducted with increased frequency to assess the comparative effectiveness of different treatments, including as a tool for "coverage with evidence development," "risk-sharing contracting," or key element in a "learning health-care system." The principle alternatives for comparative effectiveness research include retrospective observational studies, prospective observational studies, randomized clinical trials, and naturalistic ("pragmatic") randomized clinical trials. METHODS: This report details the recommendations of a Good Research Practice Task Force on Prospective Observational Studies for comparative effectiveness research. Key issues discussed include how to decide when to do a prospective observational study in light of its advantages and disadvantages with respect to alternatives, and the report summarizes the challenges and approaches to the appropriate design, analysis, and execution of prospective observational studies to make them most valuable and relevant to health-care decision makers. RECOMMENDATIONS: The task force emphasizes the need for precision and clarity in specifying the key policy questions to be addressed and that studies should be designed with a goal of drawing causal inferences whenever possible. If a study is being performed to support a policy decision, then it should be designed as hypothesis testing-this requires drafting a protocol as if subjects were to be randomized and that investigators clearly state the purpose or main hypotheses, define the treatment groups and outcomes, identify all measured and unmeasured confounders, and specify the primary analyses and required sample size. Separate from analytic and statistical approaches, study design choices may strengthen the ability to address potential biases and confounding in prospective observational studies. The use of inception cohorts, new user designs, multiple comparator groups, matching designs, and assessment of outcomes thought not to be impacted by the therapies being compared are several strategies that should be given strong consideration recognizing that there may be feasibility constraints. The reasoning behind all study design and analytic choices should be transparent and explained in study protocol. Execution of prospective observational studies is as important as their design and analysis in ensuring that results are valuable and relevant, especially capturing the target population of interest, having reasonably complete and nondifferential follow-up. Similar to the concept of the importance of declaring a prespecified hypothesis, we believe that the credibility of many prospective observational studies would be enhanced by their registration on appropriate publicly accessible sites (e.g., and in advance of their execution.
Vivek T Kulkarni, Sachin J Shah, Susannah M Bernheim, Yongfei Wang, Sharon-Lise T Normand, Lein F Han, Michael T Rapp, Elizabeth E Drye, and Harlan M Krumholz. 2012. “Regional associations between Medicare Advantage penetration and administrative claims-based measures of hospital outcomes.” Med Care, 50, 5, Pp. 406-9.Abstract
BACKGROUND: Risk-standardized measures of hospital outcomes reported by the Centers for Medicare and Medicaid Services include Medicare fee-for-service (FFS) patients and exclude Medicare Advantage (MA) patients due to data availability. MA penetration varies greatly nationwide and seems to be associated with increased FFS population risk. Whether variation in MA penetration affects the performance on the Centers for Medicare and Medicaid Service measures is unknown. OBJECTIVE: To determine whether the MA penetration rate is associated with outcomes measures based on FFS patients. RESEARCH DESIGN: In this retrospective study, 2008 MA penetration was estimated at the Hospital Referral Region (HRR) level. Risk-standardized mortality rates and risk-standardized readmission rates for heart failure, acute myocardial infarction, and pneumonia from 2006 to 2008 were estimated among HRRs, along with several markers of FFS population risk. Weighted linear regression was used to test the association between each of these variables and MA penetration among HRRs. RESULTS: Among 304 HRRs, MA penetration varied greatly (median, 17.0%; range, 2.1%-56.6%). Although MA penetration was significantly (P<0.05) associated with 5 of the 6 markers of FFS population risk, MA penetration was insignificantly (P≥0.05) associated with 5 of 6 hospital outcome measures. CONCLUSION: Risk-standardized mortality rates and risk-standardized readmission rates for heart failure, acute myocardial infarction, and pneumonia do not seem to differ systematically with MA penetration, lending support to the widespread use of these measures even in areas of high MA penetration.
Sharon-Lise T Normand. 2012. “Registry studies for improving the quality of cardiovascular care: the role of variance components.” Circ Cardiovasc Qual Outcomes, 5, 5, Pp. e42-3.
Jersey Chen, Joseph S Ross, Melissa DA Carlson, Zhenqiu Lin, Sharon-Lise T Normand, Susannah M Bernheim, Elizabeth E Drye, Shari M Ling, Lein F Han, Michael T Rapp, and Harlan M Krumholz. 2012. “Skilled nursing facility referral and hospital readmission rates after heart failure or myocardial infarction.” Am J Med, 125, 1, Pp. 100.e1-9.Abstract
BACKGROUND: Substantial hospital-level variation in the risk of readmission after hospitalization for heart failure (HF) or acute myocardial infarction (AMI) has been reported. Prior studies have documented considerable state-level variation in rates of discharge to skilled nursing facilities (SNFs), but evaluation of hospital-level variation in SNF rates and its relationship to hospital-level readmission rates is limited. METHODS: Hospital-level 30-day all-cause risk-standardized readmission rates (RSRRs) were calculated using claims data for fee-for-service Medicare patients hospitalized with a principal diagnosis of HF or AMI from 2006-2008. Medicare claims were used to calculate rates of discharge to SNF following HF-specific or AMI-specific admissions in hospitals with ≥25 HF or AMI patients, respectively. Weighted regression was used to quantify the relationship between RSRRs and SNF rates for each condition. RESULTS: Mean RSRR following HF admission among 4101 hospitals was 24.7%, and mean RSRR after AMI admission among 2453 hospitals was 19.9%. Hospital-level SNF rates ranged from 0% to 83.8% for HF and from 0% to 77.8% for AMI. No significant relationship between RSRR after HF and SNF rate was found in adjusted regression models (P=.15). RSRR after AMI increased by 0.03 percentage point for each 1 absolute percentage point increase in SNF rate in adjusted regression models (P=.001). Overall, HF and AMI SNF rates explained <1% and 4% of the variation for their respective RSRRs. CONCLUSION: SNF rates after HF or AMI hospitalization vary considerably across hospitals, but explain little of the variation in 30-day all-cause readmission rates for these conditions.
Robert W Yeh, Kenneth Rosenfield, Katya Zelevinsky, Laura Mauri, Rahul Sakhuja, Daniel M Shivapour, Ann Lovett, Bonnie H Weiner, Alice K Jacobs, and Sharon-Lise T Normand. 2012. “Sources of hospital variation in short-term readmission rates after percutaneous coronary intervention.” Circ Cardiovasc Interv, 5, 2, Pp. 227-36.Abstract
BACKGROUND: Risk-standardized all-cause 30-day readmission rates (RSRRs) after percutaneous coronary intervention (PCI) have been endorsed as a national measure of hospital quality. Little is known about variation in the performance of hospitals on this measure, and whether high hospital rates of readmission after PCI are due to modifiable deficiencies in quality of care has not been assessed. METHODS AND RESULTS: We estimated 30-day, all-cause RSRRs for all nonfederal PCI-performing hospitals in Massachusetts, adjusted for clinical and angiographic variables, between 2005 and 2008. We assessed if differences in race, insurance type, and PCI and post-PCI characteristics, including procedural complications and discharge characteristics, could explain variation between hospitals using nested hierarchical logistic regression models. Of 36 060 patients undergoing PCI at 24 hospitals and surviving to discharge, 4469 (12.4%) were readmitted within 30 days of discharge. Hospital RSRRs ranged from 9.5% to 17.9%, with 8 of 24 hospitals being identified as outliers (4 lower than expected and 4 higher than expected). Differences in race, insurance, PCI, and post-PCI factors accounted for 10.4% of the between-hospital variance in RSRRs. CONCLUSIONS: We observed wide variation in hospital 30-day all-cause RSRRs after PCI, most of which could not be explained by identifiable differences in procedural and postprocedural factors. A better understanding of etiologies of hospital variation is necessary to determine whether this measure is an actionable assessment of hospital quality, and, if so, how hospitals might improve their performance.
Amit P Amin, John A Spertus, David J Cohen, Adnan Chhatriwalla, Kevin F Kennedy, Katherine Vilain, Adam C Salisbury, Lakshmi Venkitachalam, Sue Min Lai, Laura Mauri, Sharon-Lise T Normand, John S Rumsfeld, John C Messenger, and Robert W Yeh. 2012. “Use of drug-eluting stents as a function of predicted benefit: clinical and economic implications of current practice.” Arch Intern Med, 172, 15, Pp. 1145-52.Abstract
BACKGROUND: Benefits of drug-eluting stents (DES) in percutaneous coronary intervention (PCI) are greatest in those at the highest risk of target-vessel revascularization (TVR). Drug-eluting stents cost more than bare-metal stents (BMS) and necessitate prolonged dual antiplatelet therapy (DAPT), which increases costs, bleeding risk, and risk of complications if DAPT is prematurely discontinued. Our objective was to assess whether DES are preferentially used in patients with higher predicted TVR risk and to estimate if lower use of DES in low-TVR-risk patients would be more cost-effective than the existing DES use pattern. METHODS: We analyzed more than 1.5 million PCI procedures in the National Cardiovascular Data Registry (NCDR) CathPCI registry from 2004 through 2010 and estimated 1-year TVR risk with BMS using a validated model. We examined the association between TVR risk and DES use and the cost-effectiveness of lower DES use in low-TVR-risk patients (50% less DES use among patients with <10% TVR risk) compared with existing DES use. RESULTS: There was marked variation in physicians' use of DES (range 2%-100%). Use of DES was high across all predicted TVR risk categories (73.9% in TVR risk <10%; 78.0% in TVR risk 10%-20%; and 83.2% in TVR risk >20%), with a modest relationship between TVR risk and DES use (relative risk, 1.005 per 1% increase in TVR risk [95% CI, 1.005-1.006]). Reducing DES use by 50% in low-TVR-risk patients was projected to lower US health care costs by $205 million per year while increasing the overall TVR event rate by 0.5% (95% CI, 0.49%-0.51%) in absolute terms. CONCLUSIONS: Use of DES in the United States varies widely among physicians, with only a modest correlation to patients' risk of restenosis. Less DES use among patients with low risk of restenosis has the potential for significant cost savings for the US health care system while minimally increasing restenosis events.
Venkatesan D Vidi, Michael E Matheny, Usha S Govindarajulu, Sharon-Lise T Normand, Susan L Robbins, Vikram V Agarwal, Sripal Bangalore, and Frederic S Resnic. 2012. “Vascular closure device failure in contemporary practice.” JACC Cardiovasc Interv, 5, 8, Pp. 837-44.Abstract
OBJECTIVES: The goal of this study was to assess the frequency and predictors of vascular closure device (VCD) deployment failure, and its association with vascular complications of 3 commonly used VCDs. BACKGROUND: VCDs are commonly used following percutaneous coronary intervention on the basis of studies demonstrating reduced time to ambulation, increased patient comfort, and possible reduction in vascular complications as compared with manual compression. However, limited data are available on the frequency and predictors of VCD failure, and the association of deployment failure with vascular complications. METHODS: From a de-identified dataset provided by Massachusetts Department of Health, 23,813 consecutive interventional coronary procedures that used either a collagen plug-based (n = 18,533), a nitinol clip-based (n = 2,284), or a suture-based (n = 2,996) VCD between June 2005 and December 2007 were identified. The authors defined VCD failure as unsuccessful deployment or failure to achieve immediate access site hemostasis. RESULTS: Among 23,813 procedures, the VCD failed in 781 (3.3%) procedures (2.1% of collagen plug-based, 6.1% of suture-based, 9.5% of nitinol clip-based VCDs). Patients with VCD failure had an excess risk of "any" (7.7% vs. 2.8%; p < 0.001), major (3.3% vs. 0.8%; p < 0.001), or minor (5.8% vs. 2.1%; p < 0.001) vascular complications compared with successful VCD deployment. In a propensity score-adjusted analysis, when compared with collagen plug-based VCD (reference odds ratio [OR] = 1.0), nitinol clip-based VCD had 2-fold increased risk (OR: 2.0, 95% confidence interval [CI]: 1.8 to 2.3, p < 0.001) and suture-based VCD had 1.25-fold increased risk (OR: 1.25, 95% CI: 1.2 to 1.3, p < 0.001) for VCD failure. VCD failure was a significant predictor of subsequent vascular complications for both collagen plug-based VCD and nitinol clip-based VCD, but not for suture-based VCD. CONCLUSIONS: VCD failure rates vary depending upon the type of VCD used and are associated with significantly higher vascular complications as compared with deployment successes.
Harlan M Krumholz, Zhenqiu Lin, Elizabeth E Drye, Mayur M Desai, Lein F Han, Michael T Rapp, Jennifer A Mattera, and Sharon-Lise T Normand. 2011. “An administrative claims measure suitable for profiling hospital performance based on 30-day all-cause readmission rates among patients with acute myocardial infarction.” Circ Cardiovasc Qual Outcomes, 4, 2, Pp. 243-52.Abstract
BACKGROUND: National attention has increasingly focused on readmission as a target for quality improvement. We present the development and validation of a model approved by the National Quality Forum and used by the Centers for Medicare & Medicaid Services for hospital-level public reporting of risk-standardized readmission rates for patients discharged from the hospital after an acute myocardial infarction. METHODS AND RESULTS: We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with acute myocardial infarction. The model was derived using Medicare claims data for a 2006 cohort and validated using claims and medical record data. The unadjusted readmission rate was 18.9%. The final model included 31 variables and had discrimination ranging from 8% observed 30-day readmission rate in the lowest predictive decile to 32% in the highest decile and a C statistic of 0.63. The 25th and 75th percentiles of the risk-standardized readmission rates across 3890 hospitals were 18.6% and 19.1%, with fifth and 95th percentiles of 18.0% and 19.9%, respectively. The odds of all-cause readmission for a hospital 1 SD above average were 1.35 times that of a hospital 1 SD below average. Hospital-level adjusted readmission rates developed using the claims model were similar to rates produced for the same cohort using a medical record model (correlation, 0.98; median difference, 0.02 percentage points). CONCLUSIONS: This claims-based model of hospital risk-standardized readmission rates for patients with acute myocardial infarction produces estimates that are excellent surrogates for those produced from a medical record model.
Dale W Bratzler, Sharon-Lise T Normand, Yun Wang, Walter J O'Donnell, Mark Metersky, Lein F Han, Michael T Rapp, and Harlan M Krumholz. 2011. “An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.” PLoS One, 6, 4, Pp. e17401.Abstract
BACKGROUND: Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia. METHODOLOGY/PRINCIPAL FINDINGS: Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error = 0.032). CONCLUSIONS/SIGNIFICANCE: An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model.