Biomedical subjects

A James O'Malley

Publications and source records attributed to A James O'Malley.

At least 19 recordsLinked to original sources

PubMed2006

Diabetes and cardiovascular disease during androgen deprivation therapy for prostate cancer.

PURPOSE: Androgen deprivation therapy with a gonadotropin-releasing hormone (GnRH) agonist is associated with increased fat mass and insulin resistance in men with prostate cancer, but the risk of obesity-related disease during treatment has not been well studied. We assessed whether androgen deprivation therapy is associated with an increased incidence of diabetes and cardiovascular disease. PATIENTS AND METHODS: Observational study of a population-based cohort of 73,196 fee-for-service Medicare enrollees age 66 years or older who were diagnosed with locoregional prostate cancer during 1992 to 1999 and observed through 2001. We used Cox proportional hazards models to assess whether treatment with GnRH agonists or orchiectomy was associated with diabetes, coronary heart disease, myocardial infarction, and sudden cardiac death. RESULTS: More than one third of men received a GnRH agonist during follow-up. GnRH agonist use was associated with increased risk of incident diabetes (adjusted hazard ratio [HR], 1.44; P < .001), coronary heart disease (adjusted HR, 1.16; P < .001), myocardial infarction (adjusted HR, 1.11; P = .03), and sudden cardiac death (adjusted HR, 1.16; P = .004). Men treated with orchiectomy were more likely to develop diabetes (adjusted HR, 1.34; P < .001) but not coronary heart disease, myocardial infarction, or sudden cardiac death (all P > .20). CONCLUSION: GnRH agonist treatment for men with locoregional prostate cancer may be associated with an increased risk of incident diabetes and cardiovascular disease. The benefits of GnRH agonist treatment should be weighed against these potential risks. Additional research is needed to identify populations of men at highest risk of treatment-related complications and to develop strategies to prevent treatment-related diabetes and cardiovascular disease.

Aged↗

PubMed2006

Frequency and cost of chemotherapy-related serious adverse effects in a population sample of women with breast cancer.

BACKGROUND: The number, nature, and costs of serious adverse effects experienced by younger women receiving chemotherapy for breast cancer outside of clinical trials are unknown. METHODS: From a database of medical claims made by individuals with employer-provided health insurance between January 1998 and December 2002, we identified 12,239 women 63 years of age or younger with newly diagnosed breast cancer, of whom 4075 received chemotherapy during the 12 months after the initial breast cancer diagnosis and 8164 did not. Diagnostic codes for eight chemotherapy-related adverse effects were identified. Total hospitalizations for all causes, hospitalizations or emergency room visits for adverse effects that are typically related to chemotherapy, and health care expenditures were compared between the two groups of women. All statistical tests were two-sided. RESULTS: Women who received chemotherapy were more likely than those who did not to be hospitalized or to visit the emergency room for all causes (61% versus 42%; mean difference = 19%, 95% confidence interval [CI] = 16.7% to 21.3%, P<.001) and for chemotherapy-related serious adverse effects (16% versus 5%, mean difference = 11%, 95% CI = 9.6% to 12.4%, P<.001). The percentages of chemotherapy recipients who were hospitalized or visited the emergency room during the year after their breast cancer diagnosis were 8.4% for fever or infection; 5.5% for neutropenia or thrombocytopenia; 2.5% for dehydration or electrolyte disorders; 2.4% for nausea, emesis, or diarrhea; 2.2% for anemia; 2% for constitutional symptoms; 1.2% for deep venous thrombosis or pulmonary embolus; and 0.9% for malnutrition. Chemotherapy recipients incurred large incremental expenditures for chemotherapy-related serious adverse effects (1271 dollars per person per year) and ambulatory encounters (17,617 dollars per person per year). CONCLUSIONS: Chemotherapy-related serious adverse effects among younger, commercially insured women with breast cancer may be more common than reported by large clinical trials and lead to more patient suffering and health care expenditures than previously estimated.

Adult↗

PubMed2006

Bayesian multivariate hierarchical transformation models for ROC analysis.

A Bayesian multivariate hierarchical transformation model (BMHTM) is developed for receiver operating characteristic (ROC) curve analysis based on clustered continuous diagnostic outcome data with covariates. Two special features of this model are that it incorporates non-linear monotone transformations of the outcomes and that multiple correlated outcomes may be analysed. The mean, variance, and transformation components are all modelled parametrically, enabling a wide range of inferences. The general framework is illustrated by focusing on two problems: (1) analysis of the diagnostic accuracy of a covariate-dependent univariate test outcome requiring a Box-Cox transformation within each cluster to map the test outcomes to a common family of distributions; (2) development of an optimal composite diagnostic test using multivariate clustered outcome data. In the second problem, the composite test is estimated using discriminant function analysis and compared to the test derived from logistic regression analysis where the gold standard is a binary outcome. The proposed methodology is illustrated on prostate cancer biopsy data from a multi-centre clinical trial.

Bayes Theorem↗

PubMed2006

Impact of alternative interventions on changes in generic dispensing rates.

OBJECTIVES: To evaluate the effectiveness of four alternative interventions (member mailings, advertising campaigns, free generic drug samples to physicians, and physician financial incentives) used by a major health insurer to encourage its members to switch to generic drugs. METHODS: Using claim-level data from Blue Cross Blue Shield of Michigan, we evaluated the success of four interventions implemented during 2000-2003 designed to increase the use of generic drugs among its members. Around 13 million claims involving seven important classes of drugs were used to assess the effectiveness of the interventions. For each intervention a control group was developed that most closely resembled the corresponding intervention group. Logistic regression models with interaction effects between the treatment group (intervention versus control) and the status of the intervention (active versus not active) were used to evaluate if the interventions had an effect on the generic dispensing rate (GDR). Because the mail order pharmacy was considered more aggressive at converting prescriptions to generics, separate generic purchasing models were fitted to retail and mail order claims. In secondary analyses separate models were also fitted to claims involving a new condition and claims refilled for preexisting conditions. RESULTS: The interventions did not appear to increase the market penetration of generic drugs for either retail or mail order claims, or for claims involving new or preexisting conditions. In addition, we found that the ratio of copayments for brand name to generic drugs had a large positive effect on the GDR. CONCLUSIONS: The interventions did not appear to directly influence the GDR. Financial incentives expressed to consumers through benefit designs have a large influence on their switching to generic drugs and on the less-costly mail-order mode of purchase.

Advertising↗

PubMed2006

Derivation and confirmation of scales measuring medical directors' attitudes about the hospitalization of nursing home residents.

OBJECTIVE: To derive and confirm scales measuring medical director's attitudes about hospitalization of nursing home residents. METHOD: The authors surveyed nursing facility medical directors about the necessity of hospitalizing residents for eight clinical conditions and compared the ratings to those obtained from an expert panel to derive a relative hospitalization score. They also asked about factors that might influence hospitalization decisions. They performed a factor analysis to derive scales that measure attitudinal determinants of hospitalization and used the relative hospitalization score to confirm the scales. RESULTS: The survey had a 79% response rate. The relative hospitalization score demonstrated that medical directors were slightly less likely to recommend hospitalization than expert panel physicians. Factor analyses yielded 10 scales focusing on nursing home functioning, economics, resident specific considerations, and physician attitudes. Eight of the 10 scales had significant bivariable associations with the relative hospitalization score, and 6 had significant multivariable associations. DISCUSSION: Medical directors identify multiple determinants of hospitalization for nursing facility residents across several domains. Hospitalization decisions for nursing facility residents are complex and involve clinical and nonclinical factors.

Attitude of Health Personnel↗

PubMed2005

Comparison of thrombosis and restenosis risk from stent length of sirolimus-eluting stents versus bare metal stents.

Selection of coronary stent length varies from covering only the zone of maximum obstruction to stenting from normal- to normal-appearing vessels. With bare metal stenting, for any given lesion there is a high restenotic risk associated with longer stent length. With drug-eluting stents, the relation between stent length and restenosis has not been evaluated. In the angiographic follow-up cohort of the SIRIUS trial that compared the sirolimus-eluting Bx Velocity stent with the standard Bx Velocity stent (n = 699), we constructed a multiple regression model to predict 8-month percent diameter stenosis using the main effects of lesion length and excess stent length beyond the lesion length and adjusting for known predictors of restenosis. Stent length exceeded lesion length in 94% of lesions overall. Mean difference in length was 8.3 +/- 8.3 mm (mean lesion length 14.6 +/- 5.9 mm, mean stent length 22.9 +/- 9.6 mm). Stented lesion length and excess stent length were associated with absolute increases in percent diameter stenosis per 10 mm of 9.1% (p <0.0001) and 3.6% (p = 0.053) in the bare metal arm and 3.5% (p = 0.047) and 2.1% (p = 0.040) in the sirolimus-eluting stent arm. Although the effects of lesion length and excess stent length on restenosis were markedly decreased with sirolimus-eluting stents (vs bare metal stents), a small restenotic penalty is still paid for excessive stent length. Longer stent-to-lesion length strategies should be used only when a shorter stent is likely to result in incomplete lesion coverage and edge dissection, a strong determinant of stent thrombosis.

Angioplasty, Balloon, Coronary↗

PubMed2005

Relationship of late loss in lumen diameter to coronary restenosis in sirolimus-eluting stents.

BACKGROUND: Observed rates of restenosis after drug-eluting stenting are low (<10%). Identification of a reliable and powerful angiographic end point will be useful in future trials. METHODS AND RESULTS: Late loss (postprocedural minimum lumen diameter minus 8-month minimum lumen diameter) was measured in the angiographic cohorts of the SIRIUS (n=703) and E-SIRIUS (n=308) trials. Two techniques, the standard normal approximation and an optimized power transformation, were used to predict binary angiographic restenosis rates and compare them with observed restenosis rates. The mean in-stent late loss observed in the SIRIUS trial was 0.17+/-0.45 mm (sirolimus) versus 1.00+/-0.70 mm (control). If a normal distribution was assumed, late loss accurately estimated in-stent binary angiographic restenosis for the control arm (predicted 35.4% versus observed 35.4%) but underestimated it in the sirolimus arm (predicted 0.6% versus observed 3.2%). Power transformation improved the reliability of the estimate in the sirolimus arm (predicted 3.2% [CI 1.0% to 6.7%]) with similar improvements in the E-SIRIUS trial (predicted 4.0% [CI 1.2% to 7.0%] versus observed 3.9%). In the sirolimus-eluting stent arm, in-stent late loss correlated better with target-lesion revascularization than in-segment late loss (c-statistic=0.915 versus 0.665). CONCLUSIONS: Because distributions of late loss with a low mean are right-skewed, the use of a transformation improves the accuracy of predicting low binary restenosis rates. Late loss is monotonically correlated with the probability of restenosis and yields a more efficient estimate of the restenosis process in the era of lower binary restenosis rates.

Coronary Restenosis↗

PubMed2005

A Bayesian hierarchical non-linear regression model in receiver operating characteristic analysis of clustered continuous diagnostic data.

Receiver operating characteristic (ROC) analysis is a useful evaluative method of diagnostic accuracy. A Bayesian hierarchical nonlinear regression model for ROC analysis was developed. A validation analysis of diagnostic accuracy was conducted using prospective multi-center clinical trial prostate cancer biopsy data collected from three participating centers. The gold standard was based on radical prostatectomy to determine local and advanced disease. To evaluate the diagnostic performance of PSA level at fixed levels of Gleason score, a normality transformation was applied to the outcome data. A hierarchical regression analysis incorporating the effects of cluster (clinical center) and cancer risk (low, intermediate, and high) was performed, and the area under the ROC curve (AUC) was estimated.

Bayes Theorem↗

PubMed2005

Improving traditional intention-to-treat analyses: a new approach.

BACKGROUND: Drop-out, often accompanied by treatment non-compliance, is common in psychiatric trials. Methodologists have criticized the use of a traditional intention-to-treat (ITT) approach in such cases, and have proposed alternative methods. We set out to describe and assess methods for estimation of a treatment effect when the trial is 'broken'. METHOD: We describe a stratified method of moments (SMOM) estimator that assesses treatment effects on subjects who are willing to comply with all the treatments under study. A simulation study and a re-analysis of data from an antipsychotics trial are used to compare SMOM to ITT, as-treated, and adequate estimators. RESULTS: The new estimator retains good statistical properties under different levels of non-compliance and drop-out mechanisms. The re-analysis indicates that SMOM yields more precise results. CONCLUSIONS: Although the traditional ITT approach provides a valid method to estimate treatment effects, it can be biased in the presence of treatment non-compliance and drop-out. It is critical that researchers move beyond traditional approaches when trials are broken. A key first step is to consider non-compliance and drop-out as two independent phenomena, tracking and reporting rates separately.

Antipsychotic Agents↗

PubMed2005

Case-mix adjustment of the CAHPS Hospital Survey.

OBJECTIVES: To develop a model for case-mix adjustment of Consumer Assessment of Healthcare Providers and Systems (CAHPS) Hospital survey responses, and to assess the impact of adjustment on comparisons of hospital quality. DATA SOURCES: Survey of 19,720 patients discharged from 132 hospitals. METHODS: We analyzed CAHPS Hospital survey data to assess the extent to which patient characteristics predict patient ratings ("predictive power") and the heterogeneity of the characteristics across hospitals. We combined the measures to estimate the impact of each predictor ("impact factor") and selected high impact variables for adjusting ratings from the CAHPS Hospital survey. PRINCIPLE FINDINGS: The most important case-mix variables are: hospital service (surgery, obstetric, medical), age, race (non-Hispanic black), education, general health status (GHS), speaking Spanish at home, having a circulatory disorder, and interactions of each of these variables with service. Adjustment for GHS and education affected scores in each of the three services, while age and being non-Hispanic black had important impacts for those receiving surgery or medical services. Circulatory disorder, Spanish language, and Hispanic affected scores for those treated on surgery, obstetrics, and medical services, respectively. Of the 20 medical conditions we tested, only circulatory problems had an important impact within any of the services. Results were consistent for the overall ratings of nurse, doctor, and hospital. Although the overall impact of case-mix adjustment is modest, the rankings of some hospitals may be substantially affected. CONCLUSIONS: Case-mix adjustment has a small impact on hospital ratings, but can lead to important reductions in the bias in comparisons between hospitals.

Adolescent↗

PubMed2005

Exploratory factor analyses of the CAHPS Hospital Pilot Survey responses across and within medical, surgical, and obstetric services.

OBJECTIVES: To estimate the associations among hospital-level scores from the Consumer Assessments of Healthcare Providers and Systems (CAHPS) Hospital pilot survey within and across different services (surgery, obstetrics, medical), and to evaluate differences between hospital- and patient-level analyses. DATA SOURCE: CAHPS Hospital pilot survey data provided by the Centers for Medicare and Medicaid Services. STUDY DESIGN: Responses to 33 questionnaire items were analyzed using patient- and hospital-level exploratory factor analytic (EFA) methods to identify both a patient-level and hospital-level composite structures for the CAHPS Hospital survey. The latter EFA was corrected for patient-level sampling variability using a hierarchical model. We compared results of these analyses with each other and to separate EFAs conducted at the service level. To quantify the similarity of assessments across services, we compared correlations of different composites within the same service with those of the same composite across different services. DATA COLLECTION: Cross-sectional data were collected during the summer of 2003 via mail and telephone from 19,720 patients discharged from November 2002 through January 2003 from 132 hospitals in three states. PRINCIPAL FINDINGS: Six factors provided the best description of inter-item covariation at the patient level. Analyses that assessed variability across both services and hospitals suggested that three dimensions provide a parsimonious summary of inter-item covariation at the hospital level. Hospital-level factor structures also differed across services; as much variation in quality reports was explained by service as by composite. CONCLUSIONS: Variability of CAHPS scores across hospitals can be reported parsimoniously using a limited number of composites. There is at least as much distinct information in composite scores from different services as in different composite scores within each service. Because items cluster slightly differently in the different services, service-specific composites may be more informative when comparing patients in a given service across hospitals. When studying individual-level variability, a more differentiated structure is probably more appropriate.

Attitude of Health Personnel↗

PubMed2005

Methods used to streamline the CAHPS Hospital Survey.

OBJECTIVE: To identify a parsimonious subset of reliable, valid, and consumer-salient items from 33 questions asking for patient reports about hospital care quality. DATA SOURCE: CAHPS Hospital Survey pilot data were collected during the summer of 2003 using mail and telephone from 19,720 patients who had been treated in 132 hospitals in three states and discharged from November 2002 to January 2003. METHODS: Standard psychometric methods were used to assess the reliability (internal consistency reliability and hospital-level reliability) and construct validity (exploratory and confirmatory factor analyses, strength of relationship to overall rating of hospital) of the 33 report items. The best subset of items from among the 33 was selected based on their statistical properties in conjunction with the importance assigned to each item by participants in 14 focus groups. PRINCIPAL FINDINGS: Confirmatory factor analysis (CFA) indicated that a subset of 16 questions proposed to measure seven aspects of hospital care (communication with nurses, communication with doctors, responsiveness to patient needs, physical environment, pain control, communication about medication, and discharge information) demonstrated excellent fit to the data. Scales in each of these areas had acceptable levels of reliability to discriminate among hospitals and internal consistency reliability estimates comparable with previously developed CAHPS instruments. CONCLUSION: Although half the length of the original, the shorter CAHPS hospital survey demonstrates promising measurement properties, identifies variations in care among hospitals, and deals with aspects of the hospital stay that are important to patients' evaluations of care quality.

Adolescent↗

PubMed2005

Likelihood methods for treatment noncompliance and subsequent nonresponse in randomized trials.

While several new methods that account for noncompliance or missing data in randomized trials have been proposed, the dual effects of noncompliance and nonresponse are rarely dealt with simultaneously. We construct a maximum likelihood estimator (MLE) of the causal effect of treatment assignment for a two-armed randomized trial assuming all-or-none treatment noncompliance and allowing for subsequent nonresponse. The EM algorithm is used for parameter estimation. Our likelihood procedure relies on a latent compliance state covariate that describes the behavior of a subject under all possible treatment assignments and characterizes the missing data mechanism as in Frangakis and Rubin (1999, Biometrika 86, 365-379). Using simulated data, we show that the MLE for normal outcomes compares favorably to the method-of-moments (MOM) and the standard intention-to-treat (ITT) estimators under (1) both normal and non-normal data, and (2) departures from the latent ignorability and compound exclusion restriction assumptions. We illustrate methods using data from a trial to compare the efficacy of two antipsychotics for adults with refractory schizophrenia.

Algorithms↗

PubMed2004

Covariate adjustment in clinical trials with non-ignorable missing data and non-compliance.

Estimating causal effects in psychiatric clinical trials is often complicated by treatment non-compliance and missing outcomes. While new estimators have recently been proposed to address these problems, they do not allow for inclusion of continuous covariates. We propose estimators that adjust for continuous covariates in addition to non-compliance and missing data. Using simulations, we compare mean squared errors for the new estimators with those of previously established estimators. We then illustrate our findings in a study examining the efficacy of clozapine versus haloperidol in the treatment of refractory schizophrenia. For data with continuous or binary outcomes in the presence of non-compliance, non-ignorable missing data, and a covariate effect, the new estimators generally performed better than the previously established estimators. In the clozapine trial, the new estimators gave point and interval estimates similar to established estimators. We recommend the new estimators as they are unbiased even when outcomes are not missing at random and they are more efficient than established estimators in the presence of covariate effects under the widest variety of circumstances.

Antipsychotic Agents↗

PubMed2004

Effects of stent length and lesion length on coronary restenosis.

The choice of drug-eluting versus bare metal stents is based on costs and expectations of restenosis and thrombosis risk. Approaches to stent placement vary from covering just the zone of maximal obstruction to stenting well beyond the lesion boundaries (normal-to-normal vessel). The independent effects of stented lesion length, nonstented lesion length, and excess stent length, on coronary restenosis have not been evaluated for bare metal or drug-eluting stents. We analyzed the angiographic follow-up cohort (1,181 patients) from 6 recent bare metal stent trials of de novo lesions in native coronary arteries. Stent length exceeded lesion length in 87% of lesions (mean lesion length 12.4 +/- 6.3 mm, mean stent length 20.0 +/- 7.9 mm, mean difference 7.6 +/- 7.9 mm). At 6- to 9-month follow-up, the mean percent diameter stenosis was 39.1 +/- 20.1%. In an adjusted multivariable model of percent diameter stenosis, each 10 mm of stented lesion length was associated with an absolute increase in percent diameter stenosis of 7.7% (p <0.0001), whereas each 10 mm of excess stent length independently increased percent diameter stenosis by 4.0% (p <0.0001) and increased target lesion revascularization at 9 months (odds ratio 1.12, 95% confidence interval 1.02 to 1.24). Significant nonstented lesion length was uncommon (12.5% of cases). In summary, stent length exceeded lesion length in most stented lesions, and the amount of excess stent length increased the risk of restenosis independent of the stented lesion length. This analysis supports a conservative approach of matching stent length to lesion length to reduce the risk of restenosis with bare metal stents.

Clinical Trials as Topic↗

PubMed2003

Application of models for multivariate mixed outcomes to medical device trials: coronary artery stenting.

The approval process for some medical devices involves a single-arm trial in which the outcomes associated with the new device are compared to the expected outcomes associated with approved devices, the latter denoted the objective performance criterion (OPC). In this paper, models for multivariate mixed outcomes are applied to derive the OPC for a medical device to be used in clinical evaluations of the same type of device. We illustrate the techniques by determining the OPC for coronary artery stents, metal cages used to widen blocked coronary arteries in patients with coronary artery disease, using data from seven randomized trials of stents approved for use in the U.S.A. involving 5806 patients. The OPC is based on two 9-month endpoints: target lesion revascularization, a binary outcome, and proportion diameter stenosis, a continuous outcome. To account for the correlation between mixed outcomes we consider factorization of the likelihood into marginal and conditional components, or adoption of a latent variable model. Because the models have different structural forms, standard methods for model comparison (such as the AIC and BIC) cannot be used. We discuss how model identifiability and valid inference are achieved, and then adapt the deviance information criterion (DIC) and the pseudo-Bayes factor (PSBF) to select the best model. Nine months post-stenting, we find that the average posterior probability (standard deviation) of target lesion revascularization ranges from 0.086 (0.008) for non-diabetics with one diseased vessel to 0.163 (0.022) for diabetics with three diseased vessels. When considering proportion diameter stenosis, the corresponding posterior means are 0.375 (0.020) and 0.427 (0.030). The correlation coefficient of the components of the OPC lies in the range 0.042 to 0.116.

Bayes Theorem↗

PubMed2002

Sample size calculation for a historically controlled clinical trial with adjustment for covariates.

We present a Bayesian approach to determining the optimal sample size for a historically controlled clinical trial. This work is motivated by a trial of a new coronary stent that uses a retrospective control group formed from seven trials of coronary stents currently marketed in the United States. In studies involving nonrandomized control groups, hierarchical regression, propensity score methods, or other sophisticated models are typically required to account for heterogeneity among groups which, if ignored could bias the results. Sample size calculations for historically controlled trials of medical devices are often based on formulae derived for randomized trials and fail to account for estimation of model parameters, correlation of observations, and uncertainty in the distribution of covariates of the patients recruited in the new trial. We propose methodology based on stochastic optimization that overcomes these deficiencies. The methodology is demonstrated using an objective function based on the power of the trial from a Bayesian approach. Analytic approximations based on a covariate-free analysis that convey features of the power function are developed. Our principle conclusions are that exact sample size calculations can be substantially different from current approximations, and stochastic optimization provides a convenient method of computation.

Bayes Theorem↗

PubMedDate not supplied

Quality of care for the treatment of acute medical conditions in US hospitals.

BACKGROUND: The Joint Commission on Accreditation of Healthcare Organizations and the Centers for Medicare and Medicaid Services recently began reporting on quality of care for acute myocardial infarction, congestive heart failure, and pneumonia. METHODS: We linked performance data submitted for the first half of 2004 to American Hospital Association data on hospital characteristics. We created composite scales for each disease and used factor analysis to identify 2 additional composites based on underlying domains of quality. We estimated logistic regression models to examine the relationship between hospital characteristics and quality. RESULTS: Overall, 75.9% of patients hospitalized with these conditions received recommended care. The mean composite scores and their associated interquartile ranges were 0.85 (0.81-0.95), 0.64 (0.52-0.78), and 0.88 (0.80-0.97) for acute myocardial infarction, congestive heart failure, and pneumonia, respectively. After adjustment, for-profit hospitals consistently underperformed not-for-profit hospitals for each condition, with odds ratios (ORs) ranging from 0.79 (95% confidence interval [CI], 0.78-0.80) for the congestive heart failure composite measure to 0.90 (95% CI, 0.89-0.91) for the pneumonia composite. Major teaching hospitals had better performance on the treatment and diagnosis composite (OR, 1.37; 95% CI, 1.34-1.39) but worse performance on the counseling and prevention composite (OR, 0.83; 95% CI, 0.82-0.84). Hospitals with more technology available, higher registered nurse staffing, and federal/military designation had higher performance. CONCLUSIONS: Patients are more likely to receive high-quality care in not-for-profit hospitals and in hospitals with high registered nurse staffing ratios and more investment in technology. Because payments and sources of payments affect some of these factors (eg, investments in technology and staffing ratios), policy makers should evaluate the effect of alternative payment approaches on quality.

Acute Disease↗