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Article Excerpt
A solution proposed to address the quality and cost problems plaguing health care in the United States is pay-for-performance (P4P), where health care organizations and physicians are compensated not only for what they do, but whether their actions conform to quality standards or result in positive patient outcomes. The promise of P4P has been strong enough to motivate considerable interest among payers. Recent evidence suggests that the majority of commercial HMOs now use P4P (Rosenthal et al. 2006), most state Medicaid programs use P4P (Kuhmerker and Hartman 2007), and Medicare has launched a number of P4P demonstrations (Centers for Medicare and Medicaid Services [CMS] 2009).
Despite its hope, evidence of the effectiveness of P4P is limited. Several recent reviews have examined the small body of empirical evidence on the effect of explicit financial incentives on the quality of health care and have found little evidence supporting the effectiveness of P4P (Armour et al. 2001; Town et al. 2005; Petersen et al. 2006; Rosenthal and Frank 2006). To the extent that P4P programs have improved performance, improvement has tended to occur for processes of care and not outcomes (e.g., Lindenauer et al. 2007).
To date, P4P has been targeted primarily toward physician practices (Rosenthal et al. 2006). The hospital P4P program that has attracted the most attention as a potential model for a national rollout is the Premier Hospital Quality Incentive Demonstration (PHQID). The PHQID is a collaboration between the CMS and Premier Inc. that began in the fourth quarter of 2003 and continues today. The PHQID pays a 2 percent bonus on Medicare reimbursement rates to hospitals performing in the top decile of performance of a composite quality measure for each clinical condition incentivized in the PHQID (heart failure, acute myocardial infarction [AMI], community-acquired pneumonia, coronary-artery bypass grafting [CABG], and hip and knee replacement) and a 1 percent bonus for hospitals performing in the second highest decile. Penalties for very low performing hospitals were implemented in 2006.
To examine the potential of P4P to improve the value of inpatient care purchased by Medicare, this study will estimate the effect of the PQHID on patient mortality and Medicare cost.
EFFECT OF THE PHQID ON QUALITY: SUMMARY OF EMPIRICAL EVIDENCE
Two published evaluations (Grossbart 2006; Lindenauer et al. 2007) concluded that the PHQID improved quality beyond what would have occurred in its absence while one article found no effect of the PHQID (Glickman et al. 2007). Each of these studies examined the effect of the PHQID among slightly different samples. Because the Lindenauer and colleagues' analysis used the most complete set of PHQID hospitals and did the most to control for hospital-level confounds, results from this study are the most credible. However, even accepting the Lindenauer and colleagues' results as accurate, doubt remains as to the true impact of the PHQID on patient health. Although seven of the 33 PHQID quality measures are outcomes, the Lindenauer and colleagues' analysis examined only hospital performance on process measures. As noted in other P4P programs, improvement in record keeping or the gaming of measures may be, at least in part, responsible for increased performance on process measures (Petersen et al. 2006). Further, research has shown only a small inverse association between process performance and mortality for AMI, heart failure, and pneumonia among Medicare beneficiaries (Werner and Bradlow 2006; Jha et al. 2007) and also indicates that improvement in process performance has not decreased mortality among Medicare beneficiaries (Ryan et al. 2009, unpublished data). Taken together, this evidence suggests that the PHQID's emphasis on process performance measures may not create incentives that will result in decreases on mortality. The only study that has examined the effect of the PHQID on mortality did so only for AMI, and found no evidence of an effect (Glickman et al. 2007).
POTENTIAL EFFECTS OF THE HQID ON MEDICARE COST
While not previously addressed in the literature, changes in hospital practice in response to the PHQID may also impact Medicare costs. Medicare hospital payment is fixed per admission, based on Diagnosis-Related Groups. However, the PQHID could affect Medicare costs by affecting the number of hospital admissions or hospitals' classification of outliers. (Hospitals are able to receive additional payments for inpatient admissions as a result of particularly costly patients.) To the extent that the PHQID affects admissions (if higher quality care decreases complications and readmissions) or outliers (as a result of greater resource use associated with more intensive treatment or through the gaming of outlier classification, (1) potentially to defray the cost of quality improvement) the PHQID may affect Medicare cost.
METHODS
This analysis estimates the effects of the PHQID on Medicare patient mortality, cost, and outlier classification for AMI, heart failure, pneumonia, and CABG. Although incentivized in the PHQID, hip and knee replacement are not evaluated because mortality rates are low for these procedures (approximately 0.7 percent). Also, while the financial incentives in the PHQID apply to all patients, not just Medicare beneficiaries, the analysis focuses on Medicare patients because of the availability of mortality and cost data. The econometric approach uses three estimators of the effect of the PHQID to account for unobserved time-varying and time-invariant confounds at the hospital level.
Data
We use several sources of Medicare data from 2000 to 2006: inpatient claims, Denominator files, and Provider of Service files. Inpatient claims are used to identify the principal diagnoses for which beneficiaries are admitted, secondary diagnoses and type of admission for risk adjustment, cost data, and discharge status to exclude transfer patients. The Medicare Denominator File is used to add additional risk adjusters and to determine 30-day mortality. Data from the Medicare Provider of Service file are used to identify hospital structural characteristics. Only short-term, acute care hospitals are included in the analysis. To align the panel with the start of the PHQID, the study period spans the 6-year interval from the fourth quarter of 2000 through the third quarter of 2006. This includes 11,232,452 admissions from 6,713,928 patients with principal diagnoses of AMI, heart failure, pneumonia, or a CABG procedure from the 3,570 acute care hospital entities (2) included in the analysis.
Dependent Variables
Hospital-level risk-adjusted (RA) 30-day mortality, RA 60-day cost, and RA outlier classification for each incentivized condition are used as the dependent variables. For each admission, 60-day cost is calculated as the sum of each patient's Medicare hospital costs over a 60-day post admission interval. Costs are attributed to the hospital in which the patient is initially admitted. Classification of outlier status varies substantially over hospitals, with approximately half the hospitals reporting no outliers for AMI, heart failure, and pneumonia over the entire observation period (only around 1 percent of hospitals reported no outliers for CABG). The hospitals that reported no outliers over the observation period are excluded...
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