SPECIAL ARTICLE
www.jasn.org
Performance Measurement in Chronic Kidney Disease Kimberly A. Smith*† and Rodney A. Hayward*‡ Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Divisions of *General Internal Medicine and †Nephrology, University of Michigan, Ann Arbor, Michigan, and ‡Department of Veterans Affairs, VA Health Services Research & Development Center of Excellence, VA Ann Arbor Healthcare System, Ann Arbor, Michigan
ABSTRACT Do Americans receive high-value health care? Value only improves by advancing key indicators in one of two directions: increasing quality, decreasing cost, or both. In the face of unyielding mortality rates and the relentless expense of end-stage renal disease, government agencies and professional organizations are now focusing on new quality measures for patients with advancing chronic kidney disease. These performance measures are in early stages of refinement but reflect efforts of payers to slow the incidence of progressive renal disease across the population. To improve quality of care, one must study the performance measures themselves and determine how to capture the necessary data efficiently, identify the appropriate patients for measurement, and assign accountability to providers. Here, we discuss the challenges of doing this well. J Am Soc Nephrol 22: 225–234, 2011. doi: 10.1681/ASN.2010111152
There is a growing miasma over the real value of our health care dollar in the United States.1–3 Value is the ratio of quality to cost; in most economic sectors, lower quality products or services require a lower price to avoid extinction by market forces. The strong perception that suboptimal quality is widespread despite escalating health care costs has encouraged various national programs to measure the quality and expense of hospital care and, increasingly, outpatient services. Quality measures are well established for inpatients with myocardial infarction4 – 6 and outpatients with diabetes,7,8 and attention is now turning to chronic kidney disease (CKD).9 Blue Cross Blue Shield (BCBS) will begin a payment incentive program for CKD based on performance measures in the state of Michigan this year,10 the Medicare Quality Improvement Organizations are piloting three CKD measures,11 and the Joint Commission awarded its first CKD certification to the University of CaliJ Am Soc Nephrol 22: 225–234, 2011
fornia San Diego Medical Center in 2010 based, in part, on performance measurement.12 Despite these efforts, performance measurement for CKD is still in its infancy. Here, we examine several issues that will shapetheapproachtoqualityofcareinCKD.
ESRD remains at the forefront of CMS’s quality efforts with the proposed rollout of the Quality Incentive Program in January 2012, which will be the first pay-forperformance program in a Medicare feefor-service environment.15,16 In many respects, these early efforts successfully increased quality and accountability within the ESRD Program,17 but dialysis outcomes remain poor despite continued high costs, making a poor showing for value.18,19,13,20 As a result, payers are now shifting their gaze to CKD in the hopes of limiting progression to ESRD and bending the curve on long-term costs.21–24,14 In an effort to jump-start improvements in the treatment of patients with CKD, payers are proposing quality initiatives that are based on performance measures.10,11 Various stakeholders are now delineating details for the management of this population.
END-STAGE RENAL DISEASE INITIATIVES CURRENT CKD MEASURES
Performance measurement and quality improvement are not new to nephrology. The Centers for Medicare & Medicaid Services (CMS) initiated their first quality improvement effort for a population with chronic illness in the 1990s: they charged the 18 regional end-stage renal disease (ESRD) networks to monitor and improve the quality of dialysis services. The publication of national guidelines provided a basis for the development of measures, comparative feedback on performance, and initiatives to improve quality.13,14 Moving forward,
Relevant measures developed by national organizations rarely assess CKD directly. For example, the RAND Cor-
Published online ahead of print. Publication date available at www.jasn.org. Correspondence: Dr. Kimberly Smith, University of Michigan, 6312 Medical Science Building I, 1150 W. Medical Center Drive, Ann Arbor, Michigan 481095604. Phone: 734-647-4844; Fax: 734-647-3301; Email: kcandido@umich.edu Copyright © 2011 by the American Society of Nephrology
ISSN : 1046-6673/2202-225
225
SPECIAL ARTICLE
www.jasn.org
Table 1. Comparison of practice guidelines and performance measures Definition Purpose Focus
Specificity
Practice Guidelines
Performance Measures
Recommendations for clinical care based on best available evidence and/or expert opinion Objectively summarize complex and expanding medical literature for use by clinicians Comprehensive coverage of diverse aspects of care for a condition
Tools to assess compliance with standards of clinical care
General, as physician is ultimately responsible for applying recommendations appropriately to specific patient circumstance
poration’s prominent Quality of Care Assessment Tools system measures the frequency of screening for kidney disease among persons with diabetes and the control of BP among hypertensive patients. However, none of their 439 indicators, which cover a broad range of acute, chronic, or preventive care, is applicable specifically to patients with CKD.25 In 2010, the National Committee for Quality Assurance’s (NCQA) Healthcare Effectiveness Data and Information Set (HEDIS) contains one measure specific to CKD for the first time: whether patients over age 65 years with CKD are prescribed nonsteroidal medications or COX-2 inhibitors.26 General measurement systems have largely addressed CKD-relevant interventions primarily in the context of other diseases. Given the importance of CKD as a public health issue, how should quality be measured directly to promote and reward better care? Within nephrology, national and international organizations have developed guidelines for CKD, which provide a framework for developing CKD-specific measures. Between 2002 and 2007, the National Kidney
Measure, report, and compare the quality of care Most essential recommendations backed by highest quality evidence and a commitment to improved performance Detailed, as predetermined technical specifications are needed for objective and fair comparisons between groups
Foundation (NKF) Kidney Disease Outcomes Quality Initiative (K/DOQI) and the Renal Physicians Association (RPA) both released clinical practice guidelines for the identification and management of patients with CKD.27–32 More recently, the international Kidney Disease Improving Global Outcomes (KDIGO) initiative released the first of several planned guidelines for specific aspects of CKD management.33 Although consensus guidelines are a step toward improving management of CKD, their passive dissemination has limited clinical utility.34,35 Translating guidelines into routine practice often requires robust information systems as well as continuous quality improvement programs informed by performance measures; however, guidelines do not readily translate into performance measures (Table 1).36,37 Guidelines summarize available evidence and provide recommendations while recognizing the need to individualize treatment plans. Performance measures, however, hold providers accountable to specific standards; therefore, these measures should meet more stringent criteria— how stringent depends on the purpose of the
measurement. Measures used for formative purposes, such as internal use by a physician group or health care system for quality initiatives, do not necessarily require the same standard of accuracy as measures used for evaluative purposes, such as highstakes public reporting, payment, or accreditation.6 Members of task forces for CKD guidelines acknowledge that direct translation of their recommendations into performance measures is not appropriate. 38 The K/DOQI guidelines prioritize areas for measurement whereas the RPA guidelines include 35 measures, 39 many of which overlap with the K/DOQI priorities. Although initially broad in focus, only 6 of these 35 RPA measures ultimately survived review and revision by stakeholders in the Physician Consortium for Performance Improvement (PCPI) (Table 2).40 CMS’s Physician Quality Reporting Initiative subsequently incorporated these six measures, although their validity remains uncertain. Although the development of these measures is a noteworthy start toward CKD performance measurement, several issues remain as they undergo refinement and other measures emerge.
Table 2. Renal Physicians Association/Physician Consortium for Performance Improvement Chronic Kidney Disease Physician Performance Measurement Set (October 2007) Patients with hypertension and proteinuria who were prescribed ACE inhibitor or ARB therapy Had the following laboratory testing ordered at least once: serum levels of calcium, phosphorus and intact PTH, and lipid profile Received the influenza immunization during the flu season (September through February) Referred for AV fistula at least once Percentage of calendar months in which patients receiving ESA therapy have a hemoglobin ⬍13 g/dl OR patients whose hemoglobin is ⱖ13 g/dl and have a documented plan of care Blood pressure ⬍130/80 mmHg OR blood pressure ⱖ130/80 mmHg with a documented plan of care All measures report the percentage of patients aged 18 years and older with a diagnosis of advanced CKD (stage 4 or 5, not receiving renal replacement therapy) who met the measure during the previous 12-month reporting period.
226
Journal of the American Society of Nephrology
J Am Soc Nephrol 22: 225–234, 2011
www.jasn.org
TYPES OF MEASURES
In the broadest sense, measurement can be implicit or explicit. Implicit measurement refers to expert practitioners reviewing the details of cases and using their clinical expertise and judgment to assess overall quality of care. Explicit measurement refers to the application of prespecified and clearly defined metrics to patient circumstance. Although implicit measurement recognizes the nuances of individual cases and can be a powerful method for distinguishing the quality of different providers, it is timeintensive and each review has a subjective component.41,42 For these reasons, most large-scale reporting systems use explicit measures, which are more limited in their ability to account for specific details but are more politically tenable because of the perception of objectivity, although it is frequently overlooked that criteria for explicit review are often derived subjectively. Explicit measures can assess aspects of quality ranging from processes of care to ultimate patient outcomes, each carrying advantages and disadvantages (Table 3).43– 45 In defining explicit measures, it is intuitively appealing to measure outcomes of ultimate clinical importance, such as death or progression to ESRD. Unfortunately here there are two major limitations that are difficult to overcome. The first is sample size; it requires a much larger sample size to detect differences in outcomes than in processes. Consider two clinics in which the prevalence of statin prescriptions is 40 versus 80%. One year of data on 25 patients per clinic will detect this large process difference with 80% power of discrimination. In contrast, given the same prescription practices, detecting a difference in cardiovascular events would require ⬎30,000 patients per clinic; detecting a difference in mortality would require ⬎1 million patients per clinic (Table 4).46 – 48,43 Process measures produce the clearest signals relative to the noise generated by patient variation, thereby requiring far fewer patients to detect meaningful differences. The second major limitation is that risk for adverse outcomes often depends J Am Soc Nephrol 22: 225–234, 2011
more on disease severity and health behaviors, which varies widely between patients, than on the quality of medical care.49,50 Whereas medical therapy may delay ESRD or death, the GFR at the time the clinician becomes involved is more influential. Also, patient behaviors like medication adherence, smoking, and substance use substantially impact outcomes. A measurement system that does not adequately account for these factors will, at best, systematically punish those who treat sicker patients and, at worst, lead physicians to avoid these patients altogether. Although case-mix adjustment attempts to account for disease severity— methods similar to All Patient Refined DRGs (APR-DRGs)51 used in hospital-based care—this relies on the identification and accurate measurement of important variables that often fall short.48,49,52 For CKD specifically, calibration of creatinine measurement53 and disputes about the prognostic value of the staging system54,55 further confound adjustment for disease severity. For all these reasons, none of the currently recommended CKD measures directly assesses ultimate clinical outcomes.56,57 Instead, the focus of current measures is on intermediate outcomes and what are called processes of care. Two of the RPA/ PCPI measures focus on intermediate outcomes: BP ⬍130/80 and, among patients receiving erythropoietin-stimulating agents (ESA), hemoglobins ⬍13 g/dl. The remaining measures assess processes of care such as ordering laboratory studies or prescribing inhibitors of the renin-angiotensin system. These types of measures are easier to associate with the quality of medical care provided by physicians or physician groups, facilitating assignment of accountability, interpretation of results, and identification of necessary actions for improvement.
CHALLENGES WITH EXISTING MEASURES
Despite theoretical advantages of intermediate outcome or process measures, pitfalls remain. These measures do not individually provide a global assessment of quality as a result of their narrow def-
SPECIAL ARTICLE
initions and their typical focus on a specific aspect of management for a single disease.41 In addition, the targets for these measures, which are often expressed as summary statistics such as proportion of patients for whom a measure is met, can be controversial. Furthermore, process measures do not necessarily capture the distinction between performing a process and performing it well, such as the skill of a proceduralist.6 Thus, a simple process measure sometimes will not reflect quality adequately. Intermediate outcome measures often require much smaller sample size than ultimate outcomes but do share the other major limitation: if disease severity is not adequately adjusted, the measurement may not reflect true differences in quality.49,52,58,59 Consider the problems that accompany the apparently straightforward intermediate outcome of achieving a BP ⬍130/80. First, the majority of CKD in the United States results from poorly controlled hypertension and/or diabetes.19 Although undoubtedly some of these patients suffer from poor-quality health care, many simply have more severe disease or sought medical attention late in its course. With the development of CKD, BP control becomes only more challenging.60,61 Many patients will never achieve tight control because of severe disease, contraindications to medications, access to care, or nonadherence.62,63 With current measures, the easiest path to improved performance would be to drop patients with difficult-to-control hypertension. As suggested by Kerr et al., tightly linked measures may overcome these limitations by tying a specific process, such as intensifying treatment to an indication for an intermediate outcome that is not yet at target. With these measures, providers get credit for responding appropriately to clinical situations, which should decrease the incentive to drop patients who are less likely to reach targets.64,65 As an example, the RPA/PCPI BP measure grants credit for either achieving the goal BP or appropriately responding to an elevated BP (BP ⬍130/80 mmHg or BP ⱖ130/80 mmHg with a documented plan of care). Of Performance Measurement in CKD
227
228
Specific action of provider
Outcome not of direct importance but linked to ultimate clinical outcomes
Achievement of an intermediate outcome Or appropriate response to abnormal value
Health status of patients
Intermediate outcome
“Tightly linked”
Outcome
Definition
Process
Type
Journal of the American Society of Nephrology
Progression to ESRD Death
Reflects the ultimate goal of the health care system Provides global assessment of quality Meaningful to consumers
Combines advantages of process and intermediate outcome measures
Long time line for many conditions Influenced by many providers, types of care, and factors other than health care Requires large samples sizes to detect meaningful differences
Requires data that may not be readily available
Can reflect factors outside of a provider’s control
More sensitive to provider action than ultimate outcome measures Closer to important downstream outcomes than process measures Blood pressure ⬍130/80 OR appropriate response to a higher value
Value dependent on link to important outcomes
Assesses effectiveness of interventions
Value dependent on link to important outcomes Focus is narrow “Right” performance level may be unknown Difficult to assess how well process is performed
Disadvantages
Blood pressure ⬍130/80 Hemoglobin ⬍13 g/dl
Advantages Directly assesses provider action Occurs in short time period Sensitive to quality differences even with small sample sizes
Examples Assessing proteinuria Prescribing ACE therapy
Table 3. Comparison of performance measures types
SPECIAL ARTICLE www.jasn.org
J Am Soc Nephrol 22: 225–234, 2011
www.jasn.org
Table 4. Sample size required for 80% power to detect a quality difference between two clinics related to statin prescription (true prescription prevalence: 40 versus 80%) Type of Measure
Measure
Sample Size Required (No. Patients per Clinic per Year)
Process Intermediate outcome Outcome
Prescription of statins Cardiovascular events Mortality
25 30,000 1,000,000
course, collecting data to identify a plan of care is complex and, without these data, the measure reduces to the less informative, dichotomous intermediate outcome. The RPA/PCPI measure of anemia management makes a similar attempt with the same limitations: percentage of calendar months in which patients receiving ESA therapy have a hemoglobin ⬍13 g/dl or patients whose hemoglobin is ⱖ13 g/dl have a documented plan of care. A lack of evidence linking a process or intermediate outcome measure to clinically important outcomes also undermines its validity. Simply ordering a test or writing a prescription does not necessarily improve health. Health outcomes will not improve if no one reviews or appropriately responds to a test result or if the prescribed therapy is not taken or is ineffective. To ensure the focus remains on maximizing health benefits for patients, there must be strong evidence linking measures to clinically meaningful outcomes. For example, one RPA/PCPI measure assesses the prescription of reninangiotensin system inhibitors among patients with hypertension and proteinuria; randomized controlled trials in this population show delayed progression to ESRD with minimal safety concerns, supporting the use of this as a process measure.66 – 68 However, the lack of high-quality evidence for many other process-outcome relationships presents a significant challenge for measuring the quality of care for patients with CKD. Performance metrics supported by limited evidence can also interfere with individualized decision-making between patients and physicians. For example, early K/DOQI guidelines for the management of anemia in CKD recommended a target hemoglobin of ⬎11 J Am Soc Nephrol 22: 225–234, 2011
g/dl; even at the time, this recommendation was controversial because of the limited evidence, high costs, and concerns about the safety of erythropoeisisstimulating agents (ESAs).69 Subsequent evidence70 –72 led to a 2007 update that highlighted the need to individualize treatment goals but continued to recommend specific hemoglobin targets.73 An early performance measure encouraged these targets;39 fortunately, during the RPA/PCPI review process, this measure was eliminated and replaced with one that supported a less controversial upper hemoglobin limit (Table 2).74 More recent evidence further validates early concerns about the potential hazards of ESA therapy in CKD.75–78 This history warns against the adoption of performance measures without high-quality evidence that achieving the metric will improve clinical outcomes. Evidence for the screening and treatment of mineral bone disease in CKD is limited similarly. The authors of the 2009 KDIGO CKD-mineral bone disease guideline highlight that the guideline encompasses many aspects of care for which there is little or no evidence to inform recommendations.33 In fact, out of 49 recommendations, only 2 are supported by evidence from well-designed trials with patient-centered outcomes as end points. The authors contend there are few opportunities for developing clinical performance measures from the mineral bone disease guidelines. Consider the performance measure that assesses whether serum levels of calcium, phosphorus, and intact PTH are measured at least annually (Table 2), a measure derived from a 2003 K/DOQI guideline. The parallel 2009 KDIGO guideline rates the evidence as 1C, designating a strong recommendation but
SPECIAL ARTICLE
low-quality evidence, cautioning that the true effect may be substantially different from the estimate of the effect.79,33 Despite evidence in ESRD that abnormalities in these labs reflect abnormal bone turnover and associate with cardiovascular events and mortality,80 there is no evidence that changing therapy based on the results improves outcomes. Data are even more limited for CKD.81 Even if it is assumed these mineral tests should be ordered routinely, should they be checked annually or at some other interval? Notably, both primary care physicians and nephrologists perform poorly on these performance measures.82– 84 Does this represent ignorance of the guidelines, disagreement with the guidelines, or individualization of treatment goals? Even more important, high-stakes performance measures drive performance toward achieving what is measured, and this may result in adverse consequences. In the above example, consider the burden to patients and the costs of screening for and treating mineral and bone disorders without strong evidence for improved outcomes. Beyond this, what if a measure inadvertently encourages potentially harmful therapy? For example, again consider the measure of whether a CKD patient achieves a BP ⬍130/80 mmHg. As Lewis summarized recently, this target derives primarily from the Modification of Diet in Renal Disease study, which randomly assigned patients with CKD to a mean arterial pressure (MAP) of ⱕ92 or ⱕ107.85,86 Randomization to a MAP allows for a wide range of SBP and DBP combinations; although the mean BP in the low MAP group was 126/77, the SBP ranged from 98 to 154. These data, along with observational studies, define the goal BP of ⬍130/80, ignoring the actual range of SBP achieved in the study. Attempting to achieve SBP ⬍130 runs the risk of increasing the diastolic hypotension, which associates with increased risk for cardiovascular events in the general population—the exact opposite of the intended goal.87,88 Although whether this association is causal remains controversial,85 is it appropriate to drive all patients toward this SBP target without Performance Measurement in CKD
229
SPECIAL ARTICLE
www.jasn.org
regard for the DBP, the number of medications required, or patient preference? For some patients, high quality may mean accepting a higher SBP to avoid a potentially dangerous diastolic hypotension or the adverse effects of polypharmacy. Appropriate performance measures should address clinical scenarios in which there is not only expert consensus about the net benefit of treatment but high-quality supportive data. Although many aspects of CKD management require further study before performance measurement is appropriate, measurement is more tenable in the areas with both high-quality evidence and general consensus about the value of treatment. For example, there is broad support for the use of renin-angiotensin system inhibitors to delay progression of CKD.89,90 The RPA/PCPI measure of prescription of these medications for patients with hypertension and proteinuria reflects this critical aspect of CKD care. As data become available, this measure should expand to include other important CKD populations. There is also broad agreement that arteriovenous fistulas in late stage CKD are preferable for hemodialysis access in most situations.91–94 One RPA/PCPI measure assesses referral for arteriovenous fistula placement for appropriate patients with CKD. Future measures could address other elements of the complex system that culminates in a functional vascular access for hemodialysis. So, although RPA releases CKD guideline and initial performance measures
performance measurement for CKD remains in an early stage of development, the past decade has witnessed substantial progress (Figure 1).
PATIENTS, PROVIDERS, AND DATA
Once appropriate measures are identified, the problem remains that specific subgroups of patients may receive most if not all of the benefit from an intervention. For example, some patients are at very high risk of ESRD or cardiovascular death, whereas for others, CKD may be an incidental diagnosis of little consequence long term.95,96 Ideally, performance measures and quality improvement initiatives would target the highest risk patients for whom aggressive management is worth the risk and cost.97,98 Unfortunately, there is not yet a reliable tool to stratify risk of CKD progression. In a blunt effort to tailor performance measurement, HEDIS excludes patients older than 75 years. Because a substantial number of CKD patients are over this age, with a growing number progressing to ESRD, this may be inappropriate for CKD performance measurement, especially when an elderly patient is high functioning and otherwise healthy. In contrast, RPA/PCPI measures target patients with an eGFR ⬍30 ml/min per 1.73 m2; although this certainly identifies a high-risk population, it eliminates many relevant patients such as those with
RPA/PCPI releases revised performance measures CMS incorporates RPA/PCPI measures into PQRI
K/DOQI releases CKD guidelines (through 2007)
KDIGO releases 1st CKD guideline HEDIS incorporates 1st CKD measure Understanding of process-outcome relationships in CKD improves Performance measures updated to reflect new knowledge Ability to target measurement to high-risk patients improves Data infrastructure efficiently provides clinical detail
2002
2007
2009 2010 2011+
Figure 1. Time line of important events in development of performance measures for CKD. 230
Journal of the American Society of Nephrology
substantial proteinuria, rapid decline in GFR, or a GFR between 30 and 45 ml/ min per 1.73 m2.99,100 Until validated risk-stratification models are available for CKD, the identification of high-risk patients may need to rely on a combination of eGFR, rate of progression, and/or magnitude of proteinuria.101 Increasingly, primary care providers and nephrologists are working together to manage CKD patients, but the roles and responsibilities of each also remain unclear.102 Primary care providers will almost certainly become more involved in the management of CKD in the future, which demands consideration of whether the current guidelines are appropriate for the primary care setting.103 Primary care providers are often unaware of CKD guidelines, written by nephrology stakeholders, and do not follow recommended practices.104,105 This is not surprising given the guideline length, complexity, and focus on conditions that primary care providers are unlikely to manage such as acidosis,106 bone disease,107 or anemia of CKD.77 Whereas nephrologists often dedicate their attention to CKD alone, primary care providers must balance several concurrent illnesses and preventive interventions.108 Yarnall et al. estimated that it would require approximately 8 h/d to provide recommended preventive care to a typical patient panel, leaving no time for acute or chronic disease management.109 The current CKD guidelines do not adequately summarize or prioritize CKD interventions but rather dilute the most critical messages in a sea of recommendations mainly relevant to nephrologists. Even after defining appropriate measures, defining the patient population, and assigning accountability, the challenge of data collection remains for the majority of clinical practices that still lack an adequate informatics infrastructure.110,65,111 Ultimately, the hope is that measures reflect real differences in quality, but oversimplification of measures to ease data collection and interpretation may discard the details necessary to identify true distinctions. All too often, logistical challenges—rather than clinical importance or validity— dictate the choice J Am Soc Nephrol 22: 225–234, 2011
www.jasn.org
of measures. As described previously, it is far easier to simplify the BP or anemia measures by eliminating credit for plans of care when intermediate outcome targets are unmet. The national push toward universal electronic medical records may facilitate integrated measures that better represent true quality. Given the priority for quality monitoring and improvement, developers should proactively design systems that can capture necessary data elements as they are needed.
CONCLUSION
The value of health care in the United States is increasingly the focus of modern interest. Attention must shift from whether to measure value toward how to measure it in an efficient and meaningful way. Although some providers view performance measurement as an unwarranted intrusion into the sanctity of the physician-patient relationship, these efforts are here to stay and continue to gain momentum. As a group, nephrologists must actively engage to ensure that measures optimize benefit to patients with CKD. Performance measurement is an evolving discipline. To advance the field and to improve the care of patients, measures must encourage quality improvement rather than incentivize providers to drop challenging patients or risk harm by having to enact unproven treatments. Unfortunately, high-quality evidence for many interventions in nephrology is scarce, providing a less than adequate foundation on which to build performance metrics. Given the potential for unintended consequences, it is important to start with a small set of well-designed measures based on good evidence rather than a large number of measures that are not—measures that may distract or impede our focus on making the quality movement work for nephrology. Last, it is necessary to regularly assess whether this process is accomplishing its goal—to improve value for patients with CKD. Other national initiatives have produced mixed results,112–115 although J Am Soc Nephrol 22: 225–234, 2011
measures, methods, and quality improvement strategies continue to evolve. As experts in the care of patients with CKD, nephrologists have an obligation to proactively shape the future of performance measurement and quality improvement.
ACKNOWLEDGMENTS The authors thank James P. Smith for helpful comments on versions of this work. Both authors are supported by the Robert Wood Johnson Foundation Clinical Scholars Program. R.H. is also supported by the Department of Veteran Affairs Cooperative Studies Program (CSP #465 FS) and the Measurement Core of the Michigan Diabetes Research & Training Center (NIDDK of the National Institutes of Health [P60 DK-20572]).
DISCLOSURES None.
REFERENCES 1. McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr EA: The quality of health care delivered to adults in the United States. N Engl J Med 348: 2635– 2645, 2003 2. Kerr EA, McGlynn EA, Adams J, Keesey J, Asch SM: Profiling the quality of care in twelve communities: Results from the CQI study. Health Aff (Millwood) 23: 247–256, 2004 3. Chassin MR, Galvin RW: The urgent need to improve health care quality. Institute of Medicine National Roundtable on Health Care Quality. JAMA 280: 1000 – 1005, 1998 4. Krumholz HM, Anderson JL, Brooks NH, Fesmire FM, Lambrew CT, Landrum MB, Weaver WD, Whyte J, Bonow RO, Bennett SJ, Burke G, Eagle KA, Linderbaum J, Masoudi FA, Normand SL, Pina IL, Radford MJ, Rumsfeld JS, Ritchie JL, Spertus JA: ACC/AHA clinical performance measures for adults with ST-elevation and non-STelevation myocardial infarction: A report of the American College of Cardiology/American Heart Association Task Force on Performance Measures (Writing Committee to Develop Performance Measures on ST-Elevation and Non-ST-Elevation Myocardial Infarction). Circulation 113: 732–761, 2006
SPECIAL ARTICLE
5. Lee TH: Eulogy for a quality measure. N Engl J Med 357: 1175–1177, 2007 6. Chassin MR, Loeb JM, Schmaltz SP, Wachter RM: Accountability measures– using measurement to promote quality improvement. N Engl J Med 363: 683– 688, 2010 7. Fleming BB, Greenfield S, Engelgau MM, Pogach LM, Clauser SB, Parrott MA: The Diabetes Quality Improvement Project: Moving science into health policy to gain an edge on the diabetes epidemic. Diabetes Care 24: 1815–1820, 2001 8. Kerr E: Assessing Quality of Care for Diabetes: Conference Final Report. AHRQ Publication No. 08-0037-EF, Rockville, MD, Agency for Healthcare Research and Quality, 2008 9. Seliger SL, Zhan M, Hsu VD, Walker LD, Fink JC: Chronic kidney disease adversely influences patient safety. J Am Soc Nephrol 19: 2414 –2419, 2008 10. Blue Cross Blue Shield of Michigan: Physician Group Incentive Program Chronic Kidney Disease Initiative. Available at: http://www. bcbsm.com/provider/value_partnerships/ pgip/chronic_kidney_disease.shtml. Accessed October 26, 2010 11. QIO Synergy. Available at: http://www. qiosynergy.org/default.aspx?ID⫽ckd. Accessed October 26, 2010 12. The Joint Commission Chronic Kidney Disease Certification. Available at: http:// www.jointcommission.org/certification/ chronic_kidney_disease.aspx. Accessed October 26, 2010 13. Himmelfarb J, Kliger AS: End-stage renal disease measures of quality. Annu Rev Med 58: 387–399, 2007 14. Wish JB: Quality and accountability in the ESRD program. Adv Ren Replace Ther 8: 89 –94, 2001 15. Desai AA, Garber AM, Chertow GM: Rise of pay for performance: Implications for care of people with chronic kidney disease. Clin J Am Soc Nephrol 2: 1087– 1095, 2007 16. Himmelfarb J, Pereira BJ, Wesson DE, Smedberg PC, Henrich WL: Payment for quality in end-stage renal disease. J Am Soc Nephrol 15: 3263–3269, 2004 17. McClellan WM, Frankenfield DL, Frederick PR, Helgerson SD, Wish JB, Sugarman JR: Improving the care of ESRD patients: A success story. Health Care Financ Rev 24: 89 –100, 2003 18. Foley RN, Hakim RM: Why is the mortality of dialysis patients in the United States much higher than the rest of the world? J Am Soc Nephrol 20: 1432–1435, 2009 19. United States Renal Data System: 2010 Atlas of End-Stage Renal Disease in the United States. Available at: http://www. usrds.org/2010/slides/indiv/1v2index.html. Accessed on October 26, 2010 20. Rocco MV, Frankenfield DL, Hopson SD,
Performance Measurement in CKD
231
SPECIAL ARTICLE
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
232
www.jasn.org
McClellan WM: Relationship between clinical performance measures and outcomes among patients receiving long-term hemodialysis. Ann Intern Med 145: 512–519, 2006 Levin, A: The need for optimal and coordinated management of CKD. Kidney Int Suppl: S7–S10, 2005 Parker TF 3rd, Blantz R, Hostetter T, Himmelfarb J, Kliger A, Lazarus M, Nissenson AR, Pereira B, Weiss J: The chronic kidney disease initiative. J Am Soc Nephrol 15: 708 –716, 2004 Rettig RA, Norris K, Nissenson AR: Chronic kidney disease in the United States: A public policy imperative. Clin J Am Soc Nephrol 3: 1902–1910, 2008 McClellan WM, Wasse H, McClellan AC, Kipp A, Waller LA, Rocco MV: Treatment center and geographic variability in preESRD care associate with increased mortality. J Am Soc Nephrol 20: 1078 –1085, 2009 RAND Health: Quality of Care Assessment Tools. Available at: http://www.rand.org/ health/surveys_tools/qatools/index.html. Accessed October 26, 2010 National Committee for Quality Assurance: HEDIS 2010 Version 2. Available at: http://www.ncqa.org/Portals/0/HEDISQM/ HEDIS2010/2010_Measures.pdf. Accessed October 26, 2010 KDOQI Clinical Practice Guidelines and Clinical Practice Recommendations for Diabetes and Chronic Kidney Disease. Am J Kidney Dis 49: S12–S154, 2007 Kimoto E, Shoji T, Shinohara K, Hatsuda S, Mori K, Fukumoto S, Koyama H, Emoto M, Okuno Y, Nishizawa Y: Regional arterial stiffness in patients with type 2 diabetes and chronic kidney disease. J Am Soc Nephrol 17: 2245–2252, 2006 K/DOQI clinical practice guidelines on hypertension and antihypertensive agents in chronic kidney disease. Am J Kidney Dis 43: S1–S290, 2004 K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease. Am J Kidney Dis 42: S1– S201, 2003 K/DOQI clinical practice guidelines for chronic kidney disease: Evaluation, classification, and stratification. Am J Kidney Dis 39: S1–S266, 2002 Bolton WK: Renal physicians association clinical practice guideline: Appropriate patient preparation for renal replacement therapy: Guideline number 3. J Am Soc Nephrol 14: 1406 –1410, 2003 KDIGO clinical practice guideline for the diagnosis, evaluation, prevention, and treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney Int Suppl: S1–S130, 2009 Grimshaw JM, Russell IT: Effect of clinical guidelines on medical practice: A system-
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
atic review of rigorous evaluations. Lancet 342: 1317–1322, 1993 Curry SJ: Organizational interventions to encourage guideline implementation. Chest 118: 40S–46S, 2000 Hayward RA, Hofer TP, Kerr EA, Krein SL: Quality improvement initiatives: Issues in moving from diabetes guidelines to policy. Diabetes Care 27[Suppl 2]: B54 –B60, 2004 O’Malley AS, Clancy C, Thompson J, Korabathina R, Meyer GS: Clinical practice guidelines and performance indicators as related– but often misunderstood–tools. Jt Comm J Qual Saf 30: 163–171, 2004 Kliger AS, Haley WE: Clinical practice guidelines in end-stage renal disease: A strategy for implementation. J Am Soc Nephrol 10: 872– 877, 1999 Renal Physicians Association Clinical Performance Measures on Appropriate Patient Preparation for Renal Replacement Therapy. Available at: http://www.qualitymeasures. ahrq.gov/browse/by-organization-indiv.aspx? orgid⫽23&objid⫽532. Accessed November 19, 2010, Renal Physician’s Association/Physician Consortium for Performance Improvement (PCPI) Chronic Kidney Disease Performance Measures Chronic Kidney Disease Measures. Available at: http://www.ama-assn.org/ama1/ pub/upload/mm/370/ckdws110107.pdf. Kerr EA, Hofer TP, Hayward RA, Adams JL, Hogan MM, McGlynn EA, Asch SM: Quality by any other name?: A comparison of three profiling systems for assessing health care quality. Health Serv Res 42: 2070 –2087, 2007 Hofer TP, Asch SM, Hayward RA, Rubenstein LV, Hogan MM, Adams J, Kerr EA: Profiling quality of care: Is there a role for peer review? BMC Health Serv Res 4: 9, 2004 Mant J: Process versus outcome indicators in the assessment of quality of health care. Int J Qual Health Care 13: 475– 480, 2001 McGlynn EA, Asch SM: Developing a clinical performance measure. Am J Prev Med 14: 14 –21, 1998 Donabedian A: The quality of care. How can it be assessed? JAMA 260: 1743–1748, 1988 Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG: The unreliability of individual physician “report cards” for assessing the costs and quality of care of a chronic disease. JAMA 281: 2098 –2105, 1999 Mant J, Hicks N: Detecting differences in quality of care: The sensitivity of measures of process and outcome in treating acute myocardial infarction. BMJ 311: 793–796, 1995 Hofer TP, Hayward RA: Identifying poorquality hospitals. Can hospital mortality rates detect quality problems for medical diagnoses? Med Care 34: 737–753, 1996
Journal of the American Society of Nephrology
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
59. 60.
61.
62.
63.
Salem-Schatz S, Moore G, Rucker M, Pearson SD: The case for case-mix adjustment in practice profiling. When good apples look bad. JAMA 272: 871– 874, 1994 Bernard AM, Hayward RA, Rosevear J, Chun H, McMahon LF: Comparing the hospitalizations of transfer and non-transfer patients in an academic medical center. Acad Med 71: 262–266, 1996 All Patient Refined Diagnosis Related Groups: Methodology Overview. Available at: http://www.hcup-us.ahrq.gov/db/nation/ nis/APR-DRGsV20MethodologyOverviewand Bibliography.pdf. Accessed November 16, 2010 Blumenthal D, Weissman JS, Wachterman M, Weil E, Stafford RS, Perrin JM, Ferris TG, Kuhlthau K, Kaushal R, Iezzoni LI: The who, what, and why of risk adjustment: A technology on the cusp of adoption. J Health Polit Policy Law 30: 453– 473, 2005 Hsu CY: Where is the epidemic in kidney disease? J Am Soc Nephrol 21: 1607–1611, 2010 Ikizler TA: CKD classification: Time to move beyond KDOQI. J Am Soc Nephrol 20: 929 –930, 2009 Bauer C, Melamed ML, Hostetter TH: Staging of chronic kidney disease: Time for a course correction. J Am Soc Nephrol 19: 844 – 846, 2008 Cho K, Hsu CY: Quantifying severity of chronic kidney disease as a risk factor for acute kidney injury. J Am Soc Nephrol 21: 1602–1604, 2010 Grams ME, Astor BC, Bash LD, Matsushita K, Wang Y, Coresh J: Albuminuria and estimated glomerular filtration rate independently associate with acute kidney injury. J Am Soc Nephrol 21: 1757–1764, 2010 Hong CS, Atlas SJ, Chang Y, Subramanian SV, Ashburner JM, Barry MJ, Grant RW: Relationship between patient panel characteristics and primary care physician clinical performance rankings. JAMA 304: 1107–1113, 2010 Iezzoni LI: The risks of risk adjustment. JAMA 278: 1600 –1607, 1997 Fischer MJ, O’Hare AM: Epidemiology of hypertension in the elderly with chronic kidney disease. Adv Chronic Kidney Dis 17: 329 –340, 2010 Zamboli P, De Nicola L, Minutolo R, Bertino V, Catapano F, Conte G: Management of hypertension in chronic kidney disease. Curr Hypertens Rep 8: 497–501, 2006 Timbie JW, Hayward RA, Vijan S: Diminishing efficacy of combination therapy, response-heterogeneity, and treatment intolerance limit the attainability of tight risk factor control in patients with diabetes. Health Serv Res 45: 437– 456, 2010 Norris K, Nissenson AR: Race, gender, and socioeconomic disparities in CKD in the United States. J Am Soc Nephrol 19: 1261– 1270, 2008
J Am Soc Nephrol 22: 225–234, 2011
www.jasn.org
64. Kerr EA, Krein SL, Vijan S, Hofer TP, Hayward RA: Avoiding pitfalls in chronic disease quality measurement: A case for the next generation of technical quality measures. Am J Manag Care 7: 1033–1043, 2001 65. Kerr EA, Smith DM, Hogan MM, Hofer TP, Krein SL, Bermann M, Hayward RA: Building a better quality measure: are some patients with ‘poor quality’ actually getting good care? Med Care 41: 1173–1182, 2003 66. Lewis EJ: Captopril and diabetic nephropathy. JAMA 273: 1831, 1995 67. Brenner BM, Cooper ME, de Zeeuw D, Keane WF, Mitch WE, Parving HH, Remuzzi G, Snapinn SM, Zhang Z, Shahinfar S: Effects of losartan on renal and cardiovascular outcomes in patients with type 2 diabetes and nephropathy. N Engl J Med 345: 861– 869, 2001 68. Lewis EJ, Hunsicker LG, Clarke WR, Berl T, Pohl MA, Lewis JB, Ritz E, Atkins RC, Rohde R, Raz I: Renoprotective effect of the angiotensin-receptor antagonist irbesartan in patients with nephropathy due to type 2 diabetes. N Engl J Med 345: 851– 860, 2001 69. Foley RN: Do we know the correct hemoglobin target for anemic patients with chronic kidney disease? Clin J Am Soc Nephrol 1: 678 – 684, 2006 70. Singh AK, Szczech L, Tang KL, Barnhart H, Sapp S, Wolfson M, Reddan D: Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Med 355: 2085– 2098, 2006 71. Drueke TB, Locatelli F, Clyne N, Eckardt KU, Macdougall IC, Tsakiris D, Burger HU, Scherhag A: Normalization of hemoglobin level in patients with chronic kidney disease and anemia. N Engl J Med 355: 2071– 2084, 2006 72. Levin A, Djurdjev O, Thompson C, Barrett B, Ethier J, Carlisle E, Barre P, Magner P, Muirhead N, Tobe S, Tam P, Wadgymar JA, Kappel J, Holland D, Pichette V, Shoker A, Soltys G, Verrelli M, Singer J: Canadian randomized trial of hemoglobin maintenance to prevent or delay left ventricular mass growth in patients with CKD. Am J Kidney Dis 46: 799 – 811, 2005 73. KDOQI Clinical Practice Guideline and Clinical Practice Recommendations for anemia in chronic kidney disease: 2007 update of hemoglobin target. Am J Kidney Dis 50: 471–530, 2007 74. Locatelli F, Nissenson AR, Barrett BJ, Walker RG, Wheeler DC, Eckardt KU, Lameire NH, Eknoyan G: Clinical practice guidelines for anemia in chronic kidney disease: Problems and solutions. A position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int 74: 1237–1240, 2008 75. Solomon SD, Uno H, Lewis EF, Eckardt
J Am Soc Nephrol 22: 225–234, 2011
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
KU, Lin J, Burdmann EA, de Zeeuw D, Ivanovich P, Levey AS, Parfrey P, Remuzzi G, Singh AK, Toto R, Huang F, Rossert J, McMurray JJ, Pfeffer MA: Erythropoietic response and outcomes in kidney disease and type 2 diabetes. N Engl J Med 363: 1146 –1155, 2010 Pfeffer MA, Burdmann EA, Chen CY, Cooper ME, de Zeeuw D, Eckardt KU, Feyzi JM, Ivanovich P, Kewalramani R, Levey AS, Lewis EF, McGill JB, McMurray JJ, Parfrey P, Parving HH, Remuzzi G, Singh AK, Solomon SD, Toto R: A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N Engl J Med 361: 2019 –2032, 2009 Singh AK: Does TREAT give the boot to ESAs in the treatment of CKD anemia? J Am Soc Nephrol 21: 2– 6, 2010 Strippoli GF, Tognoni G, Navaneethan SD, Nicolucci A, Craig JC: Haemoglobin targets: We were wrong, time to move on. Lancet 369: 346 –350, 2007 Uhlig K, Berns JS, Kestenbaum B, Kumar R, Leonard MB, Martin KJ, Sprague SM, Goldfarb S: KDOQI US commentary on the 2009 KDIGO Clinical Practice Guideline for the Diagnosis, Evaluation, and Treatment of CKD-Mineral and Bone Disorder (CKDMBD). Am J Kidney Dis 55: 773–799, 2010 Ketteler M, Gross ML, Ritz, E: Calcification and cardiovascular problems in renal failure. Kidney Int Suppl: S120 –S127, 2005 Moe SM, Drueke TB: A bridge to improving healthcare outcomes and quality of life. Am J Kidney Dis 43: 552–557, 2004 Hoy T, Fisher M, Barber B, Borker R, Stolshek B, Goodman W: Adherence to K/DOQI practice guidelines for bone metabolism and disease. Am J Manag Care 13: 620 – 625, 2007 Patwardhan MB, Samsa GP, Matchar DB, Haley WE: Advanced chronic kidney disease practice patterns among nephrologists and non-nephrologists: A database analysis. Clin J Am Soc Nephrol 2: 277– 283, 2007 Philipneri MD, Rocca Rey LA, Schnitzler MA, Abbott KC, Brennan DC, Takemoto SK, Buchanan PM, Burroughs TE, Willoughby LM, Lentine KL: Delivery patterns of recommended chronic kidney disease care in clinical practice: Administrative claims-based analysis and systematic literature review. Clin Exp Nephrol 12: 41–52, 2008 Lewis JB: Blood pressure control in chronic kidney disease: Is less really more? J Am Soc Nephrol 21: 1086 –1092, 2010 Klahr S, Levey AS, Beck GJ, Caggiula AW, Hunsicker L, Kusek JW, Striker G: The effects of dietary protein restriction and blood-pressure control on the progression of chronic renal disease. Modification of Diet in Renal Disease Study Group. N Engl J Med 330: 877– 884, 1994 Messerli FH, Mancia G, Conti CR, Hewkin
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
98.
99.
100.
SPECIAL ARTICLE
AC, Kupfer S, Champion A, Kolloch R, Benetos A, Pepine CJ: Dogma disputed: Can aggressively lowering blood pressure in hypertensive patients with coronary artery disease be dangerous? Ann Intern Med 144: 884 – 893, 2006 Choe HM, Bernstein SJ, Standiford CJ, Hayward RA: New diabetes HEDIS blood pressure quality measure: Potential for overtreatment. Am J Manag Care 16: 19 – 24, 2010 Mehdi UF, Adams-Huet B, Raskin P, Vega GL, Toto RD: Addition of angiotensin receptor blockade or mineralocorticoid antagonism to maximal angiotensin-converting enzyme inhibition in diabetic nephropathy. J Am Soc Nephrol 20: 2641–2650, 2009 Hou FF, Xie D, Zhang X, Chen PY, Zhang WR, Liang M, Guo ZJ, Jiang JP: Renoprotection of Optimal Antiproteinuric Doses (ROAD) Study: A randomized controlled study of benazepril and losartan in chronic renal insufficiency. J Am Soc Nephrol 18: 1889 –1898, 2007 Hurst FP, Abbott KC, Raj D, Krishnan M, Palant CE, Agodoa LY, Jindal RM: Arteriovenous fistulas among incident hemodialysis patients in Department of Defense and Veterans Affairs facilities. J Am Soc Nephrol 21: 1571–1577, 2010 Schwab SJ, Brown KD: Immature public policy for vascular access. J Am Soc Nephrol 21: 1420 –1421, 2010 Santoro A, Canova C, Freyrie A, Mancini E: Vascular access for hemodialysis. J Nephrol 19: 259 –264, 2006 Fistula First. Available at: http://www. fistulafirst.org/. Accessed on December 8, 2010 Glassock RJ, Winearls C: Diagnosing chronic kidney disease. Curr Opin Nephrol Hypertens 19: 123–128, 2010 Anderson S, Halter JB, Hazzard WR, Himmelfarb J, Horne FM, Kaysen GA, Kusek JW, Nayfield SG, Schmader K, Tian Y, Ashworth JR, Clayton CP, Parker RP, Tarver ED, Woolard NF, High KP: Prediction, progression, and outcomes of chronic kidney disease in older adults. J Am Soc Nephrol 20: 1199 –1209, 2009 Zulman DM, Vijan S, Omenn GS, Hayward RA: The relative merits of populationbased and targeted prevention strategies. Milbank Q 86: 557–580, 2008 Hayward RA, Krumholz HM, Zulman DM, Timbie JW, Vijan S: Optimizing statin treatment for primary prevention of coronary artery disease. Ann Intern Med 152: 69 –77, 2010 Patel UD, Young EW, Ojo AO, Hayward RA: CKD progression and mortality among older patients with diabetes. Am J Kidney Dis 46: 406 – 414, 2005 Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney disease and
Performance Measurement in CKD
233
SPECIAL ARTICLE
101.
102.
103.
104.
105.
234
www.jasn.org
the risks of death, cardiovascular events, and hospitalization. N Engl J Med 351: 1296 –1305, 2004 Hallan SI, Ritz E, Lydersen S, Romundstad S, Kvenild K, Orth SR: Combining GFR and albuminuria to classify CKD improves prediction of ESRD. J Am Soc Nephrol 20: 1069 –1077, 2009 Shahinian VB, Saran R: The role of primary care in the management of the chronic kidney disease population. Adv Chronic Kidney Dis 17: 246 –253, 2010 Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW: Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: Implications for pay for performance. JAMA 294: 716–724, 2005 Agrawal V, Ghosh AK, Barnes MA, McCullough PA: Awareness and knowledge of clinical practice guidelines for CKD among internal medicine residents: A national online survey. Am J Kidney Dis 52: 1061–1069, 2008 Charles RF, Powe NR, Jaar BG, Troll MU, Parekh RS, Boulware LE: Clinical testing patterns and cost implications of variation in the evaluation of CKD among US
106.
107.
108.
109.
110.
111.
physicians. Am J Kidney Dis 54: 227–237, 2009 de Brito-Ashurst I, Varagunam M, Raftery MJ, Yaqoob MM: Bicarbonate supplementation slows progression of CKD and improves nutritional status. J Am Soc Nephrol 20: 2075–2084, 2009 Nickolas TL, Stein E, Cohen A, Thomas V, Staron RB, McMahon DJ, Leonard MB, Shane E: Bone mass and microarchitecture in CKD patients with fracture. J Am Soc Nephrol 21: 1371–1380, 2010 Hofer TP, Zemencuk JK, Hayward RA: When there is too much to do: How practicing physicians prioritize among recommended interventions. J Gen Intern Med 19: 646 – 653, 2004 Yarnall KS, Pollak KI, Ostbye T, Krause KM, Michener JL: Primary care: Is there enough time for prevention? Am J Public Health 93: 635– 641, 2003 McGlynn EA: Six challenges in measuring the quality of health care. Health Aff (Millwood) 16: 7–21, 1997 Hayward RA: Access to clinically-detailed patient information: A fundamental element for
Journal of the American Society of Nephrology
112.
113.
114.
115.
improving the efficiency and quality of healthcare. Med Care 46: 229–231, 2008 Patterson ME, Hernandez AF, Hammill BG, Fonarow GC, Peterson ED, Schulman KA, Curtis LH: Process of care performance measures and long-term outcomes in patients hospitalized with heart failure. Med Care 48: 210 –216, 2010 Fonarow GC, Abraham WT, Albert NM, Stough WG, Gheorghiade M, Greenberg BH, O’Connor CM, Pieper K, Sun JL, Yancy C, Young JB: Association between performance measures and clinical outcomes for patients hospitalized with heart failure. JAMA 297: 61–70, 2007 Stulberg JJ, Delaney CP, Neuhauser DV, Aron DC, Fu P, Koroukian SM: Adherence to surgical care improvement project measures and the association with postoperative infections. JAMA 303: 2479 –2485, 2010 Landon BE, Hicks LS, O’Malley AJ, Lieu TA, Keegan T, McNeil BJ, Guadagnoli E: Improving the management of chronic disease at community health centers. N Engl J Med 356: 921–934, 2007
J Am Soc Nephrol 22: 225–234, 2011