National Quality Measures Clearinghouse | Expert Commentaries: Challenges and Opportunities for Improving Quality of Care and Outcomes for Lupus

National Quality Measures Clearinghouse | Expert Commentaries: Challenges and Opportunities for Improving Quality of Care and Outcomes for Lupus

Challenges and Opportunities for Improving Quality of Care and Outcomes for Lupus

By: Jinoos Yazdany, MD, MPH

Lupus is a chronic autoimmune disease that can affect virtually any organ system in the body, leading to diverse symptoms and substantial morbidity. This condition is significantly more common in women and racial/ethnic minorities, and it has among the highest mortality rates among the rheumatic diseases (1, 2). Although prognosis has improved over the last several decades, long-term complications and comorbidities related to the disease, as well as toxicities associated with therapy, continue to exert a toll on patient health and quality of life.

In this commentary, I will review key findings from the last decade of quality measurement in lupus, which yield important insights into where the healthcare system is working and where it needs to improve. To frame my remarks, I discuss two types of quality measures commonly used by researchers to understand quality of care in lupus: process measures and outcome measures (3). With each type of measure, I also discuss some of the challenges and opportunities posed by currently available data streams and measurement approaches.

Process measures. Processes of care are the things that health care providers do in caring for patients. Most of what we know about health care quality in lupus comes from studies examining performance on clinical process measures in the ambulatory setting. Because lupus can affect so many organs, care for the disease often spans various medical specialties. Rheumatologists, nephrologists, pulmonologists, cardiologists, hematologists, dermatologists and primary care physicians are just some of the clinicians that lupus patients encounter. The heterogeneity of the disease itself and the complexity of clinical care pose technical challenges for quality measurement. To overcome these challenges, researchers have relied on innovative methodologies and cross-cutting process measures to study quality in the ambulatory setting.

Three research study designs have been used to apply process quality measures in the ambulatory setting. In the first study design, researchers used telephone interviews or mailed surveys to ask patients about the care they receive (4, 5, 6, 7, 8). The strength of this design is that it efficiently collects information from a large number of patients with a rare disease, but a major limitation is that only some quality measures are amenable to patient self-report (e.g., while measures ascertaining receipt of recommended medications or counseling can often be accurately collected directly from patients, measures requiring detailed clinical information, e.g., laboratory results, may not). In one longitudinal study, patients were interviewed once per year by phone and also consented to medical record review (4). Using quality measures derived from the Systemic Lupus Erythematosus (SLE) Quality Indicators Project (9), patients were surveyed about receipt of 13 recommended processes of care. Among the 814 individuals with lupus in the study, average performance on the quality measures by providers was 65%. Relatively large gaps in care were found in some areas, such as cardiovascular risk assessment and treatment, counseling regarding drugs with teratogenic potential in women starting immunosuppressive medications, and care related to bone health in women receiving steroids (4). Using the same cohort, the study subsequently demonstrated that higher performance on these process quality measures was associated with significantly better long-term outcomes (10)

A second type of study design used chart abstraction, either of paper or electronic health records within single health systems, to examine performance on process quality measures (11, 12). The strength of this design is the detailed clinical information in the medical record available for review; however, a significant limitation is the time-consuming and expensive nature of chart review, which may limit implementation of quality measures in the clinic. The conclusions from medical record chart abstraction studies examining performance on quality measures are remarkably consistent with the initial studies using phone interviews. Cardiovascular risk assessment and treatment, attention to bone health, and counseling around the use of teratogens were again identified as key targets for quality improvement (12, 13).

Researchers have also used large administrative databases to examine process quality measures (14). Claims data have the advantage of providing information on all patients who received a specified set of services for lupus. We have employed Medicaid data to study an at-risk population of low-income individuals with lupus nephritis, one of the most serious forms of the disease (14). Our study strongly suggested low overall quality, with many patients not receiving drugs that improve kidney survival, such as immunosuppressive, anti-proteinuric, and anti-malarial agents. In addition, the study painted a sobering picture of health care access, with 1 in 8 patients utilizing the emergency room as a usual source of care and experiencing substantial delays in therapy. Significant geographic variation in performance on quality measures also suggested room for quality improvement.

Outcome measures. Outcome measures examine the end-result of health care, in terms of the patient's health and health status. There remain significant challenges to developing outcome performance measures in lupus. Key lupus outcomes, such as accumulated organ damage, may take years to develop and are therefore perceived as not entirely within the immediate control of individual providers. In addition, risk adjustment of averaged patient outcomes within a clinic or healthcare system is daunting in a disease that can affect virtually any organ in the body and results in dramatically different levels of severity in the population. Despite these challenges, however, research is beginning to lay a foundation for outcomes measurement in lupus, given that the ultimate goal of quality measurement is to improve patient outcomes.

Most work to date has involved examining the quality of inpatient care for lupus. Measuring and monitoring health care quality during hospitalizations is important, since 1 in 4 patients with the condition are hospitalized each year (15, 16). One series of studies examined risk-adjusted hospital mortality rates for lupus (13, 17, 18, 19). The most important finding from these studies was that volume matters; in other words, hospitals with more experience treating the disease have lower rates of inpatient mortality, and this effect was most pronounced for at-risk populations, including racial/ethnic minorities and those with public insurance.

Hospital readmissions are also a potentially important outcome measure, given that lupus has the sixth highest such rate among all medical conditions in the U.S. (20). One in 6 hospitalized patients with this disease are readmitted within 30 days of discharge (21). In a recent study, we found significant geographic and hospital-level variation in 30 day hospital readmission rates for lupus, even after adjusting for a broad array of factors influencing this outcome, including case-mix (21). This study also found that risk-adjusted hospital readmission rates were significantly higher among at-risk populations, including racial/ethnic minorities and those with lower socioeconomic status.

Both studies begin to paint a picture of uneven quality of hospital care for people with lupus. Although more research is needed, for now, these studies do provide some benchmarking data for health systems seeking to measure and improve lupus outcomes.

Future work on developing outcome measures will also need to incorporate areas identified as important to patients. In formative work, researchers engaged individuals with lupus, the majority of whom were African American women from medically underserved communities, to discuss barriers to care and strategies for quality improvement (22). Patients identified outcome measures that they think are most important, including measures of quality of life, functioning, mental health, and self-efficacy. More work is needed, but partnering with patients to further develop these priorities into quality measures will prove important.

Conclusion

Despite significant challenges posed by the complexity and relatively low prevalence of lupus and the multifaceted health care needed to treat it, the last decade of research overcame some of these challenges to lay a framework for quality measurement and improvement. Process measures with specifications for a variety of data sources are available for use, and preliminary data suggest that better performance on process measures is associated with improved health outcomes for lupus patients. Outcome measures have been applied to assess quality during hospitalizations, and the results of these studies provide benchmarking information for researchers and health systems aiming to enhance care. Lastly, patients themselves identified several areas they believe are important for quality measurement. In the next decade, a key priority should include creating collaborative networks of patients, researchers and physicians who work together to build high-quality, patient-centered systems of care that then disseminate successes for the benefit of all lupus patients.

Measure Concepts
Process Measures
Lupus-specific	Sun avoidance counseling (4, 9)
	Renal protective-antihypertensive drugs in lupus nephritis (9,14)
	Anti-malarial drugs in lupus nephritis (14)
	Immunosuppressive drugs in lupus nephritis (9, 14)
	Immunosuppressive drug counseling and education (4, 9)
	Teratogenic drug counseling for reproductive age women (4,9)
	Drug toxicity monitoring (4, 9)
	Glucocorticoid management (4, 9)
Comorbidities/preventive health	Cardiovascular risk assessment (4, 5, 9, 11)
	Pneumococcal vaccination (4, 5, 6, 9)
	Influenza vaccination (4, 5, 6, 9)
	Bone mineral density testing or treatment in glucocorticoid users (9, 11)
	Osteoporosis treatment (4, 9, 11)
Outcome Measures
	Hospital mortality rate (18)
	30-day readmission rate (21)

---

Authors

Jinoos Yazdany, MD, MPH
Associate Professor of Medicine, University of California, San Francisco

Disclaimer

The views and opinions expressed are those of the author and do not necessarily state or reflect those of the National Quality Measures Clearinghouse™ (NQMC), the Agency for Healthcare Research and Quality (AHRQ), or its contractor ECRI Institute.

Potential Conflicts of Interest

Dr. Jinoos Yazdany declared no conflicts of interest with respect to this expert commentary.

References

1. Callahan LF, Pincus T. Mortality in the rheumatic diseases. Arthritis Care Res. 1995 Dec;8(4):229-41.
2. Somers EC, Marder W, Cagnoli P, et al. Population-based incidence and prevalence of systemic lupus erythematosus: The Michigan Lupus Epidemiology & Surveillance (MILES) Program. Arthritis Rheumatol. 2014 Feb;66(2):369-78.
3. Donabedian A. Explorations in quality assessment and monitoring. Vol. 1. The definition of quality and approaches to its assessment. Ann Arbor (MI): Health Administration; 1980.
4. Yazdany J, Trupin L, Tonner C, et al. Quality of care in systemic lupus erythematosus: application of quality measures to understand gaps in care. J Gen Intern Med. 2012 Oct;27(10):1326-33.
5. Drenkard C, Rask KJ, Easley KA, Bao G, Lim SS. Primary preventive services in patients with systemic lupus erythematosus: study from a population-based sample in Southeast U.S. Semin Arthritis Rheum. 2013 Oct;43(2):209-16.
6. Yazdany J, Tonner C, Trupin L, et al. Provision of preventive health care in systemic lupus erythematosus: data from a large observational cohort study. Arthritis Res Ther. 2010;12(3):R84.
7. Yazdany J, Trupin L, Kaiser R, et al. Contraceptive counseling and use among women with systemic lupus erythematosus: a gap in health care quality? Arthritis Care Res. 2011 Mar;63(3):358-65.
8. Schmajuk G, Yelin E, Chakravarty E, Nelson LM, Panopolis P, Yazdany J. Osteoporosis screening, prevention, and treatment in systemic lupus erythematosus: application of the systemic lupus erythematosus quality indicators. Arthritis Care Res. 2010 Jul;62(7):993-1001.
9. Yazdany J, Panopalis P, Gillis JZ, et al. A quality indicator set for systemic lupus erythematosus. Arthritis Rheum. 2009 Mar 15;61(3):370-7.
10. Yazdany J, Trupin L, Schmajuk G, Katz PP, Yelin EH. Quality of care in systemic lupus erythematosus: the association between process and outcome measures in the Lupus Outcomes Study. BMJ Qal Saf. 2014 Aug;23(8):659-66.
11. Demas KL, Keenan BT, Solomon DH, Yazdany J, Costenbader KH. Osteoporosis and cardiovascular disease care in systemic lupus erythematosus according to new quality indicators. Semin Arthritis Rheum. 2010 Dec;40(3):193-200.
12. Quinzanos I, Davis L, Keniston A, et al. Application and feasibility of systemic lupus erythematosus reproductive health care quality indicators at a public urban rheumatology clinic. Lupus. 2014 Sep 29.
13. Ward MM. Hospital experience and mortality in patients with systemic lupus erythematosus. Arthritis Rheum. 1999 May;42(5):891-8.
14. Yazdany J, Feldman CH, Liu J, Ward MM, Fischer MA, Costenbader KH. Quality of care for incident lupus nephritis among Medicaid beneficiaries in the United States. Arthritis Care Res. 2014 Apr;66(4):617-24.
15. Chakravarty EF, Bush TM, Manzi S, Clarke AE, Ward MM. Prevalence of adult systemic lupus erythematosus in California and Pennsylvania in 2000: estimates obtained using hospitalization data. Arthritis Rheum. 2007 Jun;56(6):2092-4.
16. Panopalis P, Yazdany J, Gillis JZ, et al. Health care costs and costs associated with changes in work productivity among persons with systemic lupus erythematosus. Arthritis Rheum. 2008 Dec 15;59(12):1788-95.
17. Ward MM. Hospital experience and expected mortality in patients with systemic lupus erythematosus: a hospital level analysis. J Rheumatol. 2000 Sep;27(9):2146-51.
18. Ward MM. Hospital experience and mortality in patients with systemic lupus erythematosus: which patients benefit most from treatment at highly experienced hospitals? J Rheumatol. 2002 Jun;29(6):1198-206.
19. Ward MM. Association between physician volume and in-hospital mortality in patients with systemic lupus erythematosus. Arthritis Rheum. 2005 Jun;52(6):1646-54.
20. Elixhauser A, Steiner C. Readmissions to U.S. hospitals by diagnosis, 2010. Rockville (MD): Agency for Healthcare Research and Quality (AHRQ); 2013 Apr. 19 p. (Statistical brief; no. 153)
21. Yazdany J, Marafino BJ, Dean ML, et al. Thirty-day hospital readmissions in systemic lupus erythematosus: predictors and hospital- and state-level variation. Arthritis Rheumatol. 2014 Oct;66(10):2828-36.
22. Feldman CH, Bermas BL, Zibit M, et al. Designing an intervention for women with systemic lupus erythematosus from medically underserved areas to improve care: a qualitative study. Lupus. 2013 Jan;22(1):52-62.