HEALTH ECONOMICSHealth Econ. 18: 1109–1113 (2009)Published online 17 July 2009 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hec.1532

EDITORIAL

HOSPITAL-BASED PAY-FOR-PERFORMANCE INTHE UNITED STATES

ANDREW RYAN�

Department of Public Health, Division of Outcomes and Effectiveness Research Weill Medical College – Cornell University,402 East 67th Street, LA-215, NY 10065, New York, USA

As evidenced by recent testimony from both the US Office of Budget and Management Director PeterOrszag (2009) and the American Hospital Association (2008), the imperative of value improvement inMedicare has become an established dictum in US health policy. In addition to ‘comparativeeffectiveness’ research, intended to increase our knowledge of the benefits and costs of alternativemedical treatments, pay-for-performance (P4P) will likely be a key part of the value reform toolkitof the Obama administration (Orszag, 2009). Although P4P in the United States began in earnest underthe Bush administration, the Obama administration appears ready to ramp up these efforts as part ofthe strategy to reduce Medicare cost growth while improving the value of care.

The Medicare programme, a national programme providing health insurance primarily to seniorsover the age of 65, is likely to be the focus of payment reform efforts in coming years for at least threereasons: First it is a massive entitlement programme with expected spending of $484 billion in 2009,approximately 3.6% of GDP, (Kaiser Family Foundation, 2009) and is projected to increase rapidly in theshort term. Second, it has well-documented value problems, with strong evidence that much of Medicare’sspending yields little benefit for patients (Fisher et al., 2003). Third, Medicare payment is controlled entirelyby the federal government, as opposed to Medicaid and private health insurance, allowing for relative easein the implementation of reform efforts. Further, because inpatient hospital care accounts forapproximately 30% of Medicare spending (Kaiser Family Foundation, 2009) and because much of thepresumed unnecessary spending in Medicare spending occurs in inpatient settings, the inpatient sector willlikely be at the center of payment reform in Medicare. Planning for such inpatient payment reform byMedicare, generally termed hospital Value-Based Purchasing (VBP), is already well underway.

Unfortunately, while the desire to implement hospital-based P4P in Medicare is strong, the evidenceof its effectiveness remains weak. As described in a recent systematic review of the hospital P4P evidenceliterature (Mehrotra et al., 2009), only three hospital-based P4P programmes that implemented explicitfinancial incentives for improved quality of care have been evaluated in a total of eight publishedarticles. Three of these articles evaluated the Premier Hospital Quality Incentive Demonstration(PHQID). The PHQID is a collaboration between the Centers for Medicare and Medicaid Services(CMS) and Premier Inc. The first phase of the demonstration took place from October 1, 2003 toSeptember 30, 2006 and an extension of the PHQID began in October 2006 and is plannedto continue until September 2009. In the first phase, Medicare paid a 2% bonus on payment rates to

*Correspondence to: Department of Public Health, Division of Outcomes and Effectiveness Research Weill Medical College –Cornell University, 402 East 67th Street, LA-215, NY 10065, New York, USA. E-mail: amr2015@med.cornell.edu

Copyright r 2009 John Wiley & Sons, Ltd.

hospitals performing in the top decile of a composite quality measure for each clinical conditionincentivized in the PHQID (heart failure, acute myocardial infarction (AMI), community-acquiredpneumonia, coronary-artery bypass grafting (CABG), and hip and knee replacement) and a 1% bonusfor hospitals performing in the second highest decile. Penalties for very low performing hospitalswere implemented in the third year of the programme. In both phases of implementation, thecomposite quality measures have included both process (e.g. aspirin administered to AMI patients atadmission) and outcome measures (inpatient mortality for CABG patients), but have consisted largelyof process measures. Of the 421 hospitals invited to participate, 266 (63%) chose to do so (Lindenaueret al., 2007).

Two of the three published evaluations of the PHQID concluded that the programme improvedquality beyond what would have occurred in its absence (Grossbart, 2006; Lindenauer et al., 2007).The dissenting article by Glickman et al., (2007) found minimal evidence of process performanceimprovement and no greater improvement for in-hospital AMI mortality. Each of these studiesexamined the effect of the PHQID among slightly different samples. Because the Lindenauer et al.analysis used the most complete set of PHQID hospitals and did the most to control for hospital-levelconfounds, results from this study are the most credible. However, even accepting the Lindenauer et al.results as accurate, doubt remains as to the true impact of the PHQID on patient health. The only studyin the Mehrotra et al. review that examined the effect of the PHQID on mortality did so only for AMI,and found no evidence of an effect (Glickman et al., 2007).

Since the publication of the Mehrotra et al. review, two additional studies have been publishedthat cast further doubt on the effects of the PHQID. An article by Bhattacharya et al. (2009) evaluatedthe correlation between PHQID composite performance scores for hip and knee replacement andoutcomes for hip and knee replacement that were not incentivized in the PHQID (inpatient mortalityafter hip and knee arthroplasty, iatrogenic complications, urinary tract infection, and surgical volume).They found that (1) given minimal between-hospital variance in the outcomes incentivized in thePHQID, composite performance scores were determined almost exclusively by process qualityperformance; and (2) composite performance scores were not correlated with non-incentivizedoutcomes.

An article in Health Services Research evaluated the effect of the PHQID on risk-adjusted (RA)30-day patient mortality, RA 60-day inpatient cost, and RA outlier classification for AMI, heart failure,and pneumonia (Ryan, 2009). Using a six-year panel of hospitals constructed from Medicare data, threeestimators were used to evaluate the effects of the PHQID on mortality, cost, and outlier classificationin the presence of unobserved selection, resulting from the PHQID being voluntary. The analysisfound no evidence that the PHQID reduced mortality or cost growth for AMI, heart failure,pneumonia, or CABG and weak evidence that the PHQID increased outlier classification for heartfailure and pneumonia, suggesting that the effect of the PHQID on value for Medicare has beenlimited.

In summary, while the PHQID appears to have improved process performance, it does not appear tohave decreased mortality (which was incentivized for AMI and CABG) nor has it decreased inpatientcost growth (which was not incentivized). Further, other research has shown a tenuous relationshipbetween process performance and outcomes in acute care (Bhattacharya et al., 2009; Werner andBradlow, 2006; Werner et al., 2008; Ryan et al., 2009) casting serious doubt as to whether processimprovement in the PHQID has resulted in meaningful improvements in healthcare quality.

THE DESIGN OF P4P AND THE PHQID

P4P is just a concept, and the PHQID is just a prototype. Myriad other designs for P4P are possible,which may have drastically different effects on provider behavior. There are four basic design issues in

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P4P: (1) Who gets paid? (2) What are they paid for? (3) What are the criteria for bonuses and penalties?(4) How big are the payouts? Each of these issues is discussed in turn in the context of the PHQID:

� Who gets paid? The PHQID disburses bonus payments to bonus-achieving hospitals directly.Hospitals are then free to either keep the payments themselves or redistribute bonuses to physiciansor staff, but apparently have not redistributed bonuses within the hospital (Damberg et al., 2007).The absence of performance bonuses trickling down to physicians has been noted in other P4Pprogrammes (Sauter et al., 2007). As an alternative, CMS could directly incentivize physicianquality, in addition to hospital quality. While incentivizing non-physician behavior (e.g. nurses)through group-level incentives may be preferable still (Town et al., 2004), CMS has a limited abilityto implement such incentives given that non-physician staff are paid by the hospitals themselves.

� What are they paid for? In the first phase of the PHQID, approximately 80% of the incentivizedmeasures, from which condition-specific composite measures were derived, were processmeasures. The measure mix has subsequently changed slightly, but remains dominated byprocess measures. Further, incentivized PHQID outcome measures, as currently specified, havebeen noted as contributing little variance to composite scores (Bhattacharya et al., 2009).Incentivizing outcomes that have substantial between-provider variation could result in strongerincentives for meaningful quality improvement.

� What are the criteria for bonuses or penalties? The PHQID initially disbursed bonus payments tohospitals based on relative attainment of quality: the top 10% received 2% bonuses on theirMedicare reimbursement rates while the second highest decile of hospitals received a 1% bonus.Beginning in 2006, incentive payments in the PHQID are now disbursed to high improvinghospitals as well as high attaining hospitals, and an additional attainment threshold has beenestablished for lower performing hospitals. While the effects of changes in payout criteria remainto be evaluated, it is likely that the move from incentives for high attainment alone to incentivesfor lower levels of attainment and for improvement will create stronger incentives for morehospitals to improve quality.

� How big are the payouts? The first phase of the PHQID paid a 2% and 1% bonus to hospitalsperforming in the highest and the second highest deciles of quality performance, respectively.In the second phase of the PHQID, a total of $12 million per year, up from an average of$8.2 million per year in the first phase of the PHQID (Premier, 2008) will be disbursed in financialincentives, which will likely increase incentives for quality improvement.

P4P programmes face a fundamental dilemma: as the incentives for quality improvement increase,the incentives for counterproductive gaming and patient avoidance also increase, particularly ifoutcome measures are incentivized. The key is to design programmes that maximize the incentives formeaningful quality improvement while minimizing incentives for gaming and patient avoidance.

To minimize gaming behavior by providers, quality measures should not be based on self-reported data,which is subject to manipulation. This basically rules out process measures for use in P4P programmes.Instead, claims-based measures, such as 30-day mortality, readmission rates, the AHRQ patient-safetyindicators, and the Comorbidity Adjusted Complications Index (Brailer et al., 1996) should be used asquality metrics. These measures should be supplemented with measures based on patient surveys: therecently implemented HCAHPS measures of patient experience are an excellent start, but these measurescould be enhanced with functional status measures (potentially derived from the PROMIS initiative(www.nihpromis.org)) that would add little burden to existing data collection. These proposed outcomemeasures also have the benefit of measuring inherently meaningful and important indicators of healthcarequality, as opposed to structure or process measures whose ultimate effect on outcomes is uncertain.

To minimize provider avoidance of sicker patients in hospital-based P4P, CMS has two options. Thefirst is to improve risk adjustment and implement more reliable methods of profiling of provider

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outcome performance: CMS has taken a step in the right direction here by deciding to publicly reportthree-year moving averages for 30-day mortality rates, instead of 1-year rates. The second approach isto directly measure and report patient severity and, potentially, conduct audits of patient avoidance.Ideally, P4P and public quality reporting programmes would result in shifts of sicker, more complexpatients to higher quality hospitals: if claims-based severity measures indicate that higher qualityhospitals appear to be avoiding sicker patients, CMS could investigate individual hospitals, with thethreat of financial sanctions.

Finally, Medicare should test different P4P designs before deciding on a national plan: the risk ofgetting a national plan wrong far outweighs the benefit of implementing a plan in the short term. To dothis, Medicare could convene an expert panel to create between 5 and 10 alternative designs of P4P,some favoring process measures, others favoring outcomes, some paying doctors and hospitals, othersjust paying hospitals, etc. Next, Medicare could make the annual payment update of the more than 3500hospitals paid by the Inpatient Prospective Payment System conditional on participation in P4P, as hasbeen done with the ‘Reporting Hospital Quality Data for Annual Payment Update’ programme forpublic reporting. Medicare could then conduct a cluster randomization trial (assigning P4P designs toregions of the country), study the results, and arrive at a national plan in 3–5 years.

Such a policy experiment would be costly, but would advance knowledge of what works for hospital-based P4P. If Medicare is not serious about designing a P4P programme that creates strong incentivesfor meaningful quality improvement while simultaneously minimizing gaming behavior and patientavoidance, it should not attempt to implement a national P4P programme at all. The PHQID is a noblefirst attempt at P4P, and changes to its design are encouraging. However, emerging evidence suggeststhat, to date, it has not improved value for Medicare. Further experimentation, and evaluation, arerequired to get hospital P4P right.

REFERENCES

American Hospital Association. 2008. Statement of the American Hospital Association, Roundtable to Discuss theCenters for Medicare and Medicaid Services’ Hospital Value-based Purchasing Program Implementation Plan,Committee on Finance, United States Senate March 6, 2008 [accessed April 28, 2009]. Available from:www.aha.org/aha/testimony/2008/080306-tes-cms-vbp.pdf.

Bhattacharya T, Freiberg AA, Mehta P, Katz JN, Ferris T. 2009. Measuring the report card: the validity of pay for-performance metrics in orthopedic surgery. Health Affairs 28(2): 526–532.

Brailer DJ, Kroch E, Pauly MV, Huang JP. 1996. Comorbidity-adjusted complication risk – a new outcome qualitymeasure. Medical Care 34(5): 490–505.

Damberg CL, Sorbero ME, Mehrotra AA, Teleki SS, Lovejoy S, Bradley L. 2007. An environmental scan of Payfor Performance in the Hospital Setting: Final Report. Prepared for United States Department of Health andHuman Services [accessed April 28, 2009]. Available from: http://aspe.hhs.gov/health/reports/08/payperform/PayPerform07.html.

Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EtL. 2003. The implications of regionalvariations in medicare spending. Part 2: health outcomes and satisfaction with care. Archives of InternalMedicine 138(4): 288–298.

Glickman SW, Ou FS, DeLong ER, Roe MT, Lytle BL, Mulgund J, Rumsfeld JS, Gibler WB, Ohman EM,Schulman KA, Peterson ED. 2007. Pay for performance, quality of care, and outcomes in acute myocardialinfarction. Journal of the American Medical Association 297(21): 2373–2380.

Grossbart SR. 2006. What’s the return? Assessing the effect of pay-for-performance initiatives on the quality of caredelivery. Medical Care Research and Review 63(1): 29S–48S.

Kaiser Family Foundation. 2009. Medicare Spending and Financing Fact Sheet [accessed June 2, 2009]. Availablefrom: http://www.kff.org/medicare/upload/7305_03.pdf.

Lindenauer PK, Remus D, Roman S, Rothberg MB, Benjamin EM, Ma A, Bratzler DW. 2007. Public reportingand pay for performance in hospital quality improvement. New England Journal of Medicine 356(5): 486–496.

Mehrotra A, Damberg CL, Sorbero MES, Teleki SS. 2009. Pay for performance in the hospital setting: what is thestate of the evidence? American Journal of Medical Quality 24(1): 19–28.

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Orszag PR. (Nominee To Serve As Director of the Office of Management and Budget). 2009. Committee onBudget, United States Senate, January 13, 2009 [accessed April 28, 2009]. Available from: http://budget.senate.gov/democratic/testimony/2009/OrszagFINAL011309.pdf.

Premier Inc. 2008. About the Hospital Quality Incentive Demonstration [accessed April 28, 2009]. Available from:http://www.premierinc.com/quality-safety/tools-services/p4p/hqi/year-3-results/HQID-FactsonlyPartic%20_2_.pdf.

Ryan AM. 2009. The effects of the premier hospital quality incentive demonstration on mortality and hospital costsin medicare. Health Services Research 64(3): 821–842.

Ryan AM, Tompkins C, Burgess J, Wallack S. 2009. The relationship between performance on medicare’s processquality measures and mortality: evidence of correlation, not causation. Inquiry; 46(3).

Sautter KM, Bokhour BG, White B. 2007. The early experience of a hospital-based pay-for-performance program.Journal of Healthcare Management 52(2): 95–108.

Town R, Wholey DR, Kralewski J, Dowd B. 2004. Assessing the influence of incentives on physicians and medicalgroups. Medical Care Research and Review 61: 80S–118S.

Werner RM, Bradlow ET. 2006. Relationship between medicare’s hospital compare performance measures andmortality rates. Journal of the American Medical Association 296(22): 2694–2702.

Werner RM, Bradlow ET, Asch DA. 2008. Does hospital performance on process measures directly measure highquality care or is it a marker of unmeasured care? Health Services Research 43(5): 1464–1484.

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