EURURO Vol. 72 No. 3

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Most national quality measures are reported individually
and interpreted, such as the Surgical Care Improvement
Project (SCIP), which consists of nine independent mea-
sures. At the most extreme, MIPS currently contains
271 measures, allowing participants to pick and choose
by which measures they are evaluated. However, it is safe to
say that no single metric can define ‘‘quality’’ in any domain,
especially health care. It has been shown that composite
scores provide better predictive performance and explain a
higher proportion of the observed variation in general
and cardiac surgery. Although individual SCIP components
were not associated with soft-tissue infection rates, a
composite SCIP score was . These trends have led to the
development of disease-specific scores, such as the Ameri-
can College of Surgeons colectomy score . Importantly,
the RC-QS weighs the five components equally, while others
have shown that empiric weights with a shrinkage
estimator based on the measured reliability of the metric
may provide better performance .
The work by Lawson and colleagues is an important step
in creating disease-specific quality measures in urology. The
future of health care reporting and reimbursement lies in
quality assessment across and within process, outcome, and
structure domains for specific disease cohorts. As these
measures will be specific to the clinical and technical
challenges of each disease and surgery, it is critical for
urologists to lead development and implementation.
Although the NCDB is a retrospective resource not devel-
oped with quality measurement in mind, it remains a useful
resource for preliminary investigation. Measure develop-
ment is an iterative process, and as measures are shown to
be important and useful, data collection efforts will follow.
This should include incorporation of patient-reported
outcomes, which may be the most challenging to collect,
yet may also be the most relevant. Finally, measure
development is fraught with competing interests from
many stakeholders and usually complex statistical compu-
tations. As a result, an open and transparent approach must
be taken, including the publication of relevant software and
code so that others may reproduce the results and iterate .
Although patient data cannot be shared, many investigators
have independent access to similar data sets (such as the
NCDB), allowing for rapid validation and iteration.
Whether we like it or not, quality measures will play an
increasingly dominant role in health care delivery. As a field,
we must take a leadership role to ensure appropriate,
accurate, and fair measures are adopted that promote
patient-centered care.
Conflicts of interest: The authors have nothing to disclose.
References
[1] Chun J, Bafford AC. History and background of quality measurement.
Clin Colon Rectal Surg 2014;27:5–9.
.
[2] Ingraham AM, Cohen ME, Bilimoria KY, et al. Association of surgical
care improvement project infection-related process measure com-
pliance with risk-adjusted outcomes: implications for quality mea-
surement. J Am Coll Surg 2010;211:705–14.
.
[3] 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 2010;303:2479–85.
.
[4] Lawson KA, Saarela O, Aboussaly R, Kim SP, Breau RH, Finelli A. The
impact of quality variations on patients undergoing surgery for renal
cell carcinoma: a National Cancer Database study. Eur Urol
2017;72:379–86.
[5] O’Brien SM, Shahian DM, DeLong ER, et al. Quality measurement in
adult cardiac surgery: part 2—statistical considerations in composite
measure scoring and provider rating. Ann Thorac Surg 2007;83:
S13–26.
[6] Dimick JB, Staiger DO, Hall BL, Ko CY, Birkmeyer JD. Composite
measures for profiling hospitals on surgical morbidity. Ann Surg
2013;257:67–72. .
[7] Merkow RP, Hall BL, Cohen ME, et al. Validity and feasibility of the
American College of Surgeons colectomy composite outcome quality
measure. Ann Surg 2013;257:483–9
[8] Dimick JB, Staiger DO, Hall BL, Ko CY, Birkmeyer JD. Composite
measures for profiling hospitals on surgical morbidity. Ann Surg
2013;257:67–72. .
[9] Peng RD. Reproducible epidemiologic research. Am J Epidemiol
2006;163:783–9.
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