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. RESEARCH DESIGN: 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. SUBJECTS: Thirty-one thousand eight hundred twenty-three patients were followed for 18 months. MEASURES: 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.
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. RESEARCH DESIGN: 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. SUBJECTS: Thirty-one thousand eight hundred twenty-three patients were followed for 18 months. MEASURES: 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.
Authors: Paul K J Han; Minjung Lee; Bryce B Reeve; Angela B Mariotto; Zhuoqiao Wang; Ron D Hays; K Robin Yabroff; Marie Topor; Eric J Feuer Journal: J Pain Symptom Manage Date: 2011-11-08 Impact factor: 3.612
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Authors: Alfredo J Selim; Lewis E Kazis; William Rogers; Shirley X Qian; James A Rothendler; Avron Spiro; Xinhua S Ren; Donald Miller; Bernardo J Selim; Benjamin G Fincke Journal: Qual Life Res Date: 2007-05-25 Impact factor: 4.147
Authors: Zachary A Marcum; Megan E Amuan; Joseph T Hanlon; Sherrie L Aspinall; Steven M Handler; Christine M Ruby; Mary Jo V Pugh Journal: J Am Geriatr Soc Date: 2011-12-08 Impact factor: 5.562
Authors: Adnan I Qureshi; Mustapha A Ezzeddine; Abu Nasar; M Fareed K Suri; Jawad F Kirmani; Haitham M Hussein; Afshin A Divani; Alluru S Reddi Journal: Am J Emerg Med Date: 2007-01 Impact factor: 2.469
Authors: Chuan-Fen Liu; Anne E Sales; Nancy D Sharp; Paul Fishman; Kevin L Sloan; Jeff Todd-Stenberg; W Paul Nichol; Amy K Rosen; Susan Loveland Journal: Health Serv Res Date: 2003-10 Impact factor: 3.402