On March 1, 2001 the Institute of Medicine (IOM) released “Crossing the Quality Chasm: A New Health System for the 21st Century” in response to alarming rates of medical errors that led to thousands of unnecessary deaths. (Washburn 2001) The report called for changes within information technology (IT), payment policies, and the medical workforce. By stressing a “new paradigm for health care delivery,” rules, aims, and the top fifteen medical conditions to impart change were identified. (Washburn 2001)
But was change really needed? By examining publicly-available medical records, a seminal study found on average, Americans received only 50% of recommended care in both acute and chronic conditions. Simple tasks like providing smoking cessation counseling had a demoralizing 18.3% level of adherence. (McGlynn et al. 2003) Dismal performance in diabetes management had US providers achieving less than one-fourth the success the United Kingdom’s National Health Service (NHS) had in reducing microvascular complications. (McGlynn et al. 2003) The Center for Medicare and Medicaid Services (CMS) was called on to quickly impart change in order to improve quality of care in the US.
Looking to strengthen quality measures, improve patient outcomes, and maintain physician accountability, CMS established pay-for-performance (P4P) initiatives at the end of 2003. The goals of the project were simple: if various healthcare stakeholders could not only demonstrate higher quality but publicly report such results, financial incentives would follow. The top 10% of hospitals enforcing the greatest number of quality measures would receive a 2% bonus; others below threshold of top performers would financially incur penalties. Did CMS overstep their mandate? Would these measures improve quality of care, especially amongst underserved populations it looked to target, or would it simply contribute to the existing rift?
In November 2005, after one year of implementation, CMS boasted an average improvement of 6.6% in 22 of the 33 clinical indicators they set forth. As promised, CMS paid over $8.85 million in incentives to the top 20% of performers. Hospitals in the 9th and 10th deciles faced reimbursement penalties for future care provided.
The achievements made by low performing hospitals, however, were overshadowed by CMS’s current method of incentive distribution. CMS rewards absolute performance rather than rates of improvement so that low performers who never achieved CMS’s top 20% threshold were actually penalized for their improvements. For such hospitals, many questioned the benefits relative to costs and complexity associated with achieving such levels.
Whether improvements made at CMS participating hospitals can be attributed to P4P is of debate, a greater problem exists. Are the quality composite scores CMS looks to improve in need of improvement? Choosing and implementing metrics without analyzing the process flow and specifics to a particular hospital, practice, or department can be detrimental, imposing change where change is not needed. For example, emergency departments and urgent care clinics nationally have implemented many of CMS’s guidelines for years. Performance metrics such as giving aspirin for treatment in an AMI or monitoring pulse oximetry in cases of CAP already have high levels of adherence nationally (94.7% and 99.4% respectively). (Glickman et al. 2008) Questions then arise as to what benefits are gained from devoting resources to CMS metrics already practiced frequently in many institutions.
The gain in improvements has also been overshadowed by reported disparities created by P4P metrics.
Using Medicare data, researchers have set forth to determine whether hospital performance varies, after controlling for pertinent variables, as a function of the percentage of African Americans patients the hospital serves. In the care of acute MI or community acquired pneumonia, there is a significant inverse relationship between P4P hospitals’ composite performance scores and the percentage of African Americans hospitals treat. (Karve et al. 2008) Such hospitals are thereby at greater financial risk for serving such patients under the CMS P4P program. Additionally of the 4,464 hospitals that participated in a recent study, those that treat a higher percentage of Medicaid patients had comparatively worse performance scores and made significantly smaller improvements over time. (Werner et al. 2008)
While it remains unclear as to whether caring for minorities results in hospitals achieving lower performance scores or if racial disparities are in part due to the intrinsic nature of a hospital, what is certain is care for underserved patients concentrates at low performing hospitals. With revenue margins for such hospitals already in the red, it becomes difficult to shift costs onto payers while continuing to deliver health care. By restructuring CMS’ performance schemes to look at rates of improvement rather than absolute numbers, CMS can potentially correct some of the disparities, allowing P4P financial gains to be incurred at such institutions over time.
Glickman SW, Schulman KA, Peterson ED, et al. Evidence-Based Perspectives on Pay for Performance and Quality of Patient Care and Outcomes in Emergency Medicine. Annals of Emergency Medicine. May 2008; 51(5): 622-631.
McGlynn EA, Asch SM, Adams J, et al. The Quality of Health Care Delivered to Adults in the United States. N Engl J Med. 26 June 2003; 348(26): 2635-2645.
Karve AM, Ou F, Lytle BL, et al. Potential unintended financial consequences of pay-for-performance on the quality of care for minority patients. American Heart Journal. Mar 2008; 155(3): 571-576.
Washburn ER. Fast Forward: A Blueprint for the Future from the Institute of Medicine. Physician Executive. May/June 2001; 27(3): 8.
Werner RM, Goldman EL, Dudley RA, et al. Comparison of Change in Quality of Care between Safety-Net and Non-Safety-Net Hospitals. JAMA. 14 May 2008; 299(18):2180-2187.