Risk-adjusted mortality rates as a potential outcome indicator for outpatient quality assessments.
OBJECTIVE
The quality of outpatient medical care is increasingly recognized as having an important impact on mortality. We examined whether a clinically credible risk adjustment methodology can be developed for outpatient quality assessments.


METHODS
This study used data from the 1998 National Survey of Ambulatory Care Patients, a prospective monitoring system of outcomes of patients receiving ambulatory care in the Veterans Affairs (VA) integrated service networks.


METHODS
Thirty-one thousand eight hundred twenty-three patients were followed for 18 months.


METHODS
The main study outcome measures were observed and risk-adjusted mortality rates.


RESULTS
Of the 31,823 patients, 1559 (5%) died during the 18-months of follow-up. Observed mortality rates across the 22 VA integrated service networks varied significantly from 3.3% to 6.7% (P <0.001). Age, gender, comorbidities (Charlson Index), physical health, and mental health were significant predictors of dying. The resulting risk-adjusted mortality model performed well in cross-validated tests of discrimination (c-statistic = 0.768; 95% CI, 0.749-0.788) and calibration. Analysis of variance confirmed that the 22 integrated service networks differed in their average level of expected risk (P <0.001). Risk-adjusted rates and ranks of the networks differed considerably from unadjusted ratings.


CONCLUSIONS
Risk-adjusted mortality rates may be a useful outcome measure for assessing quality of outpatient care. We have developed a clinically credible risk adjustment model with good performance properties using sociodemographics, diagnoses, and functional status data. The resulting risk adjustment model altered assessments of the performance of the integrated service networks when compared with the unadjusted mortality rates.
Selim
Alfredo J
AJ
Center for Health Quality, Outcomes, and Economic Research, A Health Services Research and Development Field Program, VA Medical Center, Bedford, Massachusetts, USA. Selim.Alfredo_J@Boston.Med.VA.gov
Berlowitz
Dan R
DR
Fincke
Graeme
G
Rosen
Amy K
AK
Ren
Xinhua S
XS
Christiansen
Cindy L
CL
Cong
Zhongxhiao
Z
Lee
Austin
A
Kazis
Lewis
L
D000368:Aged; D000553:Ambulatory Care / Q000592:standards*; D016009:Chi-Square Distribution; D005260:Female; D006302:Health Services Research; D006787:Hospitals, Veterans / Q000592:standards; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009026:Mortality; D017063:Outcome Assessment, Health Care; D011787:Quality of Health Care; D020379:Risk Adjustment / Q000379:methods*; D014481:United States