Published Online: December 21, 2011
Jared Lane K. Maeda, PhD, MPH; and Anthony T. LoSasso, PhD
Objectives: To investigate whether market competition is a potential driver of hospital performance on the key evidence-based Joint Commission heart-failure (HF) quality indicators of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker prescribed, left ventricular function assessment, smoking-cessation counseling, and discharge instructions.
Study Design: Retrospective multivariate analysis.
Methods: Hospital performance data for HF was obtained from The Joint Commission’s ORYX program from 2003 to 2006. The performance data were linked with hospital characteristics from the American Hospital Association Annual Survey and area-level sociodemographic information from the Area Resource File. Healthcare markets
were defined as hospital referral regions (HRRs) and market competition intensity was defined by the Herfindahl-Hirschman Index. Hospital-level and HRR-level ordinary least squares fixed effects regression models were used to estimate the relationship between market competition and performance.
Results: A paired comparison indicated that there was a significant change in the mean hospital-level performance over time on all of the HF quality indicators. From the multivariate analyses, hospitals in the least competitive markets (Quintile 5) performed slightly better (2.9%) than the most competitive markets (Quintile 1) for left ventricular
function assessment (P <.01). At the HRR level, however, the least competitive markets (Quintile 5) performed moderately worse (5.1%) on the discharge-instructions quality indicator compared with the most competitive markets (Quintile 1) (P = .05).
Conclusions: Market competition intensity was associated with only small differences in hospital performance. The level of market competitiveness may produce only marginal incremental benefits to inpatient HF care.
(Am J Manag Care. 2011;17(12):816-822)
This study empirically examines whether market competition is a potential driver of hospital performance on The Joint Commission heart-failure quality indicators.
Given the growth of performance measures as a way to stimulate quality improvement efforts, this is a timely and policy-relevant article.
This study adds to the existing literature by examining whether quality improvements made by hospitals based on public performance reports are occurring through the mechanism of market competition.
We include data from all patients 18 years and older who were treated for heart failure at a Joint Commission–accredited hospital and were eligible for the performance measure.
The significant chasm between the quality of care that heart failure (HF) patients should receive and actually receive has been widely documented. Previous studies have reported on the extensive variation in the treatment and management of HF patients in hospitals across the country.1,2 Because of the substantial geographic practice variations and underuse of appropriate HF therapies, payers and accrediting bodies have begun to measure hospital performance as a way to stimulate quality-improvement efforts. The Joint Commission now requires that hospitals submit information on their performance for the core conditions of heart attacks, HF, pneumonia, and others as part of the ORYX program, which is publicly reported on Quality Check (http://www.qualitycheck.org).2
ORYX was first developed by The Joint Commission in 1997 as a way to integrate performance and outcomes measures into a continuous accreditation process.2 The ORYX quality indicators are aligned with the Centers for Medicare & Medicaid Services (CMS) Hospital Compare performance measures. Since the ORYX program was initiated, there have been substantial improvements in hospital quality, although there remains a wide variation in performance across individual hospitals and states.3
Despite the enormous progress that has been made to narrow the quality gap, the underlying motivation for hospitals to increase their compliance with the standardized quality indicators and the reasons for the wide heterogeneity in performance across hospitals and geographic areas is unclear. Previous research suggests that hospitals might be motivated to act on publicly reported performance data due to market competition, professional standards, and/or to preserve or enhance their reputation.4 In this study, we sought to empirically test whether market competition is a potential driver of hospital performance on the key evidence- based Joint Commission HF quality indicators. We focus specifically on HF because it is one of the core conditions that are measured by The Joint Commission and it is a common and costly chronic condition.
Pathways to Performance on Quality Indicators
There are 3 possible pathways through which hospitals might be motivated to act on publicly reported quality indicators.4 Hospitals may be motivated to improve their performance on quality indicators due to market forces because they would like to hold on to or increase their market share of patients. Hospitals’ awareness of quality deficits might also be enough to stimulate quality improvement efforts because of professional standards. Lastly, hospitals may be motivated to improve quality because they are concerned about protecting or enhancing their public image, since consumers may form certain opinions about a hospital.4 In this study, we focus on market competition as a potential driver of hospital performance. We hypothesize that if hospitals compete on quality, then we expect hospitals in competitive markets will provide a higher level of quality and hospitals in concentrated (less competitive) markets will provide a lower level of quality.
DATA AND METHODS
The Joint Commission accounts for more than 3000 hospitals that represent approximately 80% of hospitals in the United States and comprises more than 90% of all acutecare hospital beds.2 Quarterly data from The Joint Commission’s ORYX hospital performance measurement program for HF from 2003 to 2006 was used. The 4 evidence-based HF quality indicators examined were (1) angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) prescribed at discharge, (2) left ventricular (LV) function assessment, (3) smoking-cessation counseling, and (4) discharge instructions. Only yearly data points for the ACEI or ARB quality indicator in 2003 and 2004 were available, with the exception of Quarters 1 and 2 of 2003, since the definition for this quality indicator changed in 2005 to include ARB. A total of 3011 non-Federal, shortstay, Joint Commission–accredited acute-care hospitals were used as the primary units of analysis over 16 quarters (n = 48,176), with a secondary analysis that aggregated hospitals to 306 hospital referral regions (HRRs) over 16 quarters (n = 4896). Patients 18 years and older with LV systolic dysfunction HF defined by International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, and 428.XX, who were admitted to Joint Commission– accredited hospitals and who met the reporting requirements, comprised the data elements for the individual HF quality indicators.
The ORYX data were linked with hospital characteristics data from the American Hospital Association Annual Survey and sociodemographic and market-level characteristics from the Area Resource File to serve as control variables. Market share was derived from the Medicare Provider and Analysis Review (MedPAR) file based on the total number of Medicare HF patients.
As part of our secondary analysis, we aggregated hospitals to the HRR level to mitigate the potential issue of the small number of cases at a particular hospital that may adversely impact a hospital’s performance, as well as the endogeneity problem of patient selection of hospitals based on perceived or other unobservable characteristics that may be correlated with quality of care. A fixed-effects approach was used to examine within unit changes over time so that the results would not be affected by any heterogeneous differences across HRRs that might be constant over time.
We used HRRs to construct the measure of the healthcare market according to the crosswalk methodology of the Dartmouth Atlas of Health Care. HRRs are a naturally occurring healthcare market and they represent a geographic area where a significant proportion of medical care is provided by a referral hospital(s) serving an entire region.5
A quarterly measure of market competition was constructed based on the Herfindahl-Hirschman Index (HHI). The HHI is a standard measure of market competition and it has been widely applied for hospitals in HRRs. The HHI measure was created using Medicare HF patient volume derived from the MedPAR data file. Hospital market share was calculated as the total number of Medicare HF patients at a hospital divided by the total number of Medicare HF patients within an HRR, and it was scaled by 100.6 The HHI was then determined by taking the sum of the square of market shares for Medicare HF patients for all hospitals within an HRR.7,8 The HHI ranges from 0, which represents an infinitesimally small number of competitors in a market, to 10,000, which represents a monopoly. In our analyses, however, we used quintiles of HHI where Quintile 1 represents the most competitive markets and Quintile 5 represents the least competitive markets.8
Heart Failure Quality Metrics
Hospital-level performance on the quality indicators was used in the primary analyses. For the HRR-level analyses, the weighted average of performance based on the total number of eligible HF patients at each hospital for the quality indicators (ACEI or ARB prescribed at discharge, LV function assessment, smoking-cessation counseling, and discharge instructions) was calculated. By using the HRR-level weighted average of hospital performance, hospitals in a market that had a higher volume of HF patients had their performance score weighted more highly than hospitals that had a lower volume of HF patients.
We first examined descriptive statistics on the hospitallevel performance and market intensity data. We then used a paired t test to assess the change in the mean hospital-level performance on the HF quality indicators from Quarter 1 of 2003 to Quarter 4 of 2006. We specified hospital-level ordinary least squares (OLS) fixed-effects regression models with Quintile 1 (most competitive markets) serving as our reference group to estimate the relationship between market competition and performance and account for the time invariant–omitted variables. We lagged market competition by one quarter in our models because we would reasonably expect a delayed response between the time when the HF performance data are made publicly available and the time when the effect of market competition occurs. Additionally, the temporal sequence of the lagged model would make it less likely for an external shock in the future to affect past performance.
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