Article

Empirically derived composite measures of surgical performance.

Department of Economics and the Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, New Hampshire, USA.
Medical care (Impact Factor: 2.94). 03/2009; 47(2):226-33. DOI: 10.1097/MLR.0b013e3181847574
Source: PubMed

ABSTRACT Individual quality measures have significant limitations for assessing surgical performance. Despite growing interest in composite measures, empirically-based methods for combining multiple domains of surgical quality are not well established.
To develop and validate a composite measure of surgical performance that best describes variation in hospital mortality rates and forecasts future performance.
Using the national Medicare claims database, we identified all patients undergoing aortic valve replacement in 2000 to 2001 (n = 53,120). To serve as input variables, we identified hospital-level predictors of mortality with aortic valve replacement, including hospital volume, complication rates, and mortality with other procedures. Hospital-specific predicted mortality rates were then determined using Bayesian-derived modeling techniques and assessed against subsequent hospital mortality (2002-2003).
Our composite measure explained 78% of the variation in aortic valve replacement mortality rates (2000-2001). The most important input variables were hospital volume, mortality with aortic valve replacement, and mortality for other high-risk cardiac procedures. The composite measure forecasted 70% of future hospital-level variation in mortality rates (2002-2003), and was substantially better in this regard than individual measures. Hospitals scoring in the bottom quintile on the composite measure in 2000 to 2001 had 2-fold higher mortality rates in 2002 to 2003 than hospitals in the top quintile (adjusted odds ratio, 1.97; 95% CI, 1.73-2.23).
Compared with individual surgical quality indicators, empirically derived composite measures are superior in explaining variation in hospital mortality rates and in forecasting future performance. Such measures could be useful for public reporting, value-based purchasing, or benchmarking for quality improvement purposes.

0 Followers
 · 
156 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: To assess the relationship between long-term colorectal patient survival and methods of calculating composite performance scores.
  • [Show abstract] [Hide abstract]
    ABSTRACT: To evaluate adherence to perioperative processes of care associated with major cancer resections. Mortality rates associated with major cancer resections vary across hospitals. Because mechanisms underlying such variations are not well-established, we studied adherence to perioperative care processes. There were 1,279 hospitals participating in the National Cancer DataBase (2005-2006) ranked on a composite measure of mortality for bladder, colon, esophagus, stomach, lung, and pancreas cancer operations. We sampled hospitals from among those with the lowest and highest mortality rates, with 19 low-mortality hospitals [(LMHs), risk-adjusted mortality rate of 2.84 %] and 30 high-mortality hospitals [(HMHs), risk-adjusted mortality rate of 7.37 %]. We then conducted onsite chart reviews. Using logistic regression, we examined differences in perioperative care, adjusting for patient and tumor characteristics. Compared to LMHs, HMHs were less likely to use prophylaxis against venous thromboembolism, either preoperative or postoperatively [adjusted relative risk (aRR) 0.74, 95 % CI 0.50-0.92 and aRR 0.80, 95 % CI 0.56-0.93, respectively]. The two hospital groups were indistinguishable with respect to processes aimed at preventing surgical site infections, such as the use of antibiotics prior to incision (aRR, 0.99, 95 % CI 0.90-1.04), and processes intended to prevent cardiac events, including the use of β-blockers (1.00, 95 % CI 0.81-1.14). HMHs were significantly less likely to use epidurals (aRR, 0.57, 95 % CI 0.32-0.93). HMHs and LMHs differ in several aspects of perioperative care. These areas may represent opportunities for improving cancer surgery quality at hospitals with high mortality.
    Annals of Surgical Oncology 04/2014; 21(7). DOI:10.1245/s10434-014-3692-8 · 3.94 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background:Composite measures are useful for distilling quality data into summary scores; yet, there has been limited use of composite measures for cancer care.Objective:Compare multiple approaches for generating cancer care composite measures and evaluate how well composite measures summarize dimensions of cancer care and predict survival.Study Design:We computed hospital-level rates for 13 colorectal, lung, and prostate cancer process measures in 59 Veterans Affairs hospitals. We computed 4 empirical-factor (based on an exploratory factor analysis), 3 cancer-specific (colorectal, lung, prostate care), and 3 care modality-specific (diagnosis/evaluation, surgical, nonsurgical treatments) composite measures. We assessed correlations among all composite measures and estimated all-cause survival for colon, rectal, non-small cell lung, and small cell lung cancers as a function of composite scores, adjusting for patient characteristics.Results:Four factors emerged from the factor analysis: nonsurgical treatment, surgical treatment, colorectal early diagnosis, and prostate treatment. We observed strong correlations (r) among composite measures comprised of similar process measures (r=0.58-1.00, P<0.0001), but not among composite measures reflecting different care dimensions. Composite measures were rarely associated with survival.Conclusions:The empirical-factor domains grouped measures variously by cancer type and care modality. The evidence did not support any single approach for generating cancer care composite measures. Weak associations across different care domains suggest that low-quality and high-quality cancer care delivery may coexist within Veterans Affairs hospitals.
    Medical Care 11/2014; 53(1). DOI:10.1097/MLR.0000000000000257 · 2.94 Impact Factor