Length of comorbidity lookback period affected regression model performance of administrative health data

Preen, David B.; Holman, C. DʼArcy J.; Spilsbury, Katrina; Semmens, James B.; Brameld, Kate

doi:10.1016/j.jclinepi.2005.12.013

Cited by 197 publications

(144 citation statements)

References 25 publications

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“…The Charlson Comorbidity Index was derived from CIHI DAD International Classification of Diseases (ICD) diagnostic codes from each patient's index admission and from any hospital admissions in the year before cystectomy. [12][13][14] Because radical cystectomy can be performed for both bladder cancer and nonbladder malignancies (eg, as part of larger exenterative procedures for patients with colorectal, prostate, or gynecological malignancies), we linked the CIHI data to the Ontario Cancer Registry (OCR) to select only those cystectomy patients with a diagnosis of bladder cancer. The OCR contains information concerning all incident cancers detected in the province of Ontario with 97% capture of incident cases of bladder cancer.…”

Section: Cohort Identificationmentioning

confidence: 99%

Higher surgeon and hospital volume improves long‐term survival after radical cystectomy

Kulkarni

Urbach

Austin

et al. 2013

Cancer

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BACKGROUND: Hospital and surgeon (provider) volume are associated with clinically significant outcomes for many types of surgery. Volume-outcome studies in patients undergoing radical cystectomy for bladder cancer have focused primarily on postoperative mortality. In the current study, the authors assessed the effect of cystectomy provider volume on long-term mortality. METHODS: Using administrative databases, 2535 patients who underwent cystectomy by 199 surgeons in 90 hospitals in Ontario, Canada, between 1992 and 2004 were identified. The impact of provider volume on overall survival (OS) was assessed using Cox proportional hazards models fully adjusted for patient and tumor characteristics. Separate models were fit to examine the effect of surgeon and hospital volume. To confirm that the impact of volume on OS was independent of the effect of volume on short-term mortality, analyses were repeated excluding those patients experiencing postoperative deaths. RESULTS: Of 2535 patients, 1796 (70.9%) died during the study period. Both higher hospital volume (hazards ratio [per unit increase in average annual number of procedures], 0.995; 95% confidence interval, 0.990-1.000 [P 5.044]) and higher surgeon volume (hazards ratio, 0.984; 95% confidence interval, 0.975-0.994 [P 5.002]) were found to be significantly associated with improved OS. Excluding post-operative deaths did not alter the results. Further analyses revealed that the benefit of high volume was attained by receiving care from either high-volume hospitals or highvolume surgeons. CONCLUSIONS: High-volume providers were associated with improved long-term mortality rates compared with low-volume providers. This finding was independent of the effect of volume on perioperative mortality, suggesting that provider volume effects continue to manifest long after surgery. Cancer 2013;119:3546-54. V C 2013 American Cancer Society.KEYWORDS: cystectomy; bladder cancer; quality of health care; outcomes; bladder neoplasm. INTRODUCTIONPatients who undergo radical cystectomy for bladder cancer are at significant risk of postoperative death and have a poor life expectancy. Postoperative mortality rates and 5-year overall survival rates typically range between 1% and 4% and 40% and 60%, 1-6 respectively. One way to improve on these outcomes is to optimize the quality of care for patients undergoing radical cystectomy. Several studies have demonstrated that hospitals and surgeons with higher cystectomy volumes generally have better postoperative outcomes compared with lower-volume providers.

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Section: Cohort Identificationmentioning

confidence: 99%

Higher surgeon and hospital volume improves long‐term survival after radical cystectomy

Kulkarni

Urbach

Austin

et al. 2013

Cancer

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“…Specific developments arising from WADLS projects have included a backcasting model to correct for the prevalent pool artifact in first-time incidence rates based on linked multi-event data; 46 the use of cohort-crossover designs to estimate effects of index procedures and health events on short-term readmission risks; 47 the couplet methodology and other new methods for the study of use of private health insurance; 41 and an improved method of risk adjustment, the Multipurpose Australian Comorbidity Scoring System (MACSS). 48,49 The developments of cross-jurisdictional and genealogical linkages have brought further methodological challenges. New methods for the analysis of linked MBS and PBS data documented in successful grant applications have included linkage-based exposure indices for the intensity, periodicity, continuity and disease specialisation of primary medical care, as well as new approaches to comorbidity risk adjustment and case-time-cohort studies of medication safety using linked pharmaceutical data.…”

Section: Methodsologic Researchmentioning

confidence: 99%

A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system

Holman

Bass²,

Rosman³

et al. 2008

Aust. Health Review

465

434

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Objectives: The report describes the strategic design, steps to full implementation and outcomes achieved by the Western Australian Data Linkage System (WADLS), instigated in 1995 to link up to 40 years of data from over 30 collections for an historical population of 3.7 million. Staged development has seen its expansion, initially from a linkage key to local health data sets, to encompass links to national and local health and welfare data sets, genealogical links and spatial references for mapping applications. Applications:The WADLS has supported over 400 studies with over 250 journal publications and 35 graduate research degrees. Applications have occurred in health services utilisation and outcomes, aetiologic research, disease surveillance and needs analysis, and in methodologic research. Benefits:Longitudinal studies have become cheaper and more complete; deletion of duplicate records and correction of data artifacts have enhanced the quality of information assets; data linkage has conserved patient privacy; community machinery necessary for organised responses to health and social problems has been exercised; and the commercial return on research infrastructure investment has exceeded 1000%. Most importantly, there have been unbiased contributions to medical knowledge and identifiable advances in population health arising from the research.

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“…The index was modified to exclude rheumatologic disease; we also collapsed the categories of diabetes with and without chronic complications because this distinction was inaccurate in Manitoba before 2006 29 , and the human immunodeficiency virus/AIDS category was not included because of small numbers. The mCCI was calculated based on hospital discharge ICD-9-CM/ICD-10 codes and using a 5-year look-back period because this improved the prediction of outcomes associated with comorbidity 38 . For the Cox regression analysis, we used time-dependent covariates, updated at 5-year intervals, to account for possible temporal changes in SES and comorbidity.…”

Section: Methodsmentioning

confidence: 99%

A Population-based Study of Intensive Care Unit Admissions in Rheumatoid Arthritis

Peschken

Hitchon²,

Garland³

et al. 2015

J Rheumatol

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Objective.We aimed to determine the incidence of and mortality after critical illness in rheumatoid arthritis (RA) compared with the general population, and to describe the risks for and characteristics of critical illness in patients with RA.Methods.We used population-based administrative data from the Data Repository at the Manitoba Centre for Health Policy from 1984 to 2010, and linked clinical data from an intensive care unit (ICU) database to identify all persons with RA in the province requiring ICU admission. We identified a population-based control group, matched by age, sex, socioeconomic status, and region of residence. The incidence of ICU admission, reasons for, and mortality after ICU admission were compared between populations using age- and sex-standardized rates, rate ratios, Cox proportional hazards models, and logistic regression models.Results.We identified 10,078 prevalent and 5560 incident cases of RA. After adjustment, the risk for ICU admission was higher for RA (HR 1.65, 95% CI 1.50–1.83) versus the matched general population. From 2000–2010, the annual incidence of ICU admission among prevalent patients was about 1% in RA, with a crude 10-year incidence of 8%. Compared with the general population admitted to ICU, 1 year after ICU admission, mortality was increased by 40% in RA. Cardiovascular disorders were the most common reason for ICU admission in RA.Conclusion.Patients with RA have a higher risk for admission to the ICU than the general population and increased mortality 1 year after admission. Even with advances in management, RA remains a serious disease with significant morbidity.

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Length of comorbidity lookback period affected regression model performance of administrative health data

Cited by 197 publications

References 25 publications

Higher surgeon and hospital volume improves long‐term survival after radical cystectomy

Higher surgeon and hospital volume improves long‐term survival after radical cystectomy

A decade of data linkage in Western Australia: strategic design, applications and benefits of the WA data linkage system

A Population-based Study of Intensive Care Unit Admissions in Rheumatoid Arthritis

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