A Population-Based Health Information System

Roos, Noralou P.; Black, Charlyn; Frohlich, Norman; DeCoster, Carolyn; Tataryn, Douglas J.; Mustard, Cameron; Toll, Fred; Carrière, Keumhee C.; Burchill, Charles; MacWilliam, Leonard; Bogdanovic, Bogdan

doi:10.1097/00005650-199512001-00005

Cited by 37 publications

(22 citation statements)

References 14 publications

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“…In South Africa, there are no comprehensive systems of pre-linked health data covering large or entire populations such as the Manitoba Population Health Information System in Canada [45] or systems that routinely or periodically link data at any level of jurisdiction. In this study, we have assessed the feasibility of setting up and executing record linkage of mortality data and evaluated the quality of the matched records between the Agincourt HDSS and the CR system.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa

Kabudula

Joubert

Tuoane-Nkhasi³

et al. 2014

Popul Health Metrics

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Background: Health and Demographic Surveillance Systems (HDSS) collect independent mortality data that could be used for assessing the quality of mortality data in national civil registration (CR) systems in low-and middle-income countries. However, the use of HDSS data for such purposes depends on the quality of record linkage between the two data sources. We describe and evaluate the quality of record linkage between HDSS and CR mortality data in South Africa with HDSS data from Agincourt HDSS.

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Section: Discussionmentioning

confidence: 99%

Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa

Kabudula

Joubert

Tuoane-Nkhasi³

et al. 2014

Popul Health Metrics

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“…[10][11][12] While limitations to the usefulness of administrative data exist, 13,14 and caution must be applied in the interpretation of findings, these data are still of consideri i able value. 10,13 One advantage is that they are available from existing systems making them relatively inexpensive.…”

Section: Introductionmentioning

confidence: 99%

“…hospitalization rates and LOS) have a face validity, with service patterns which, at least to some extent, reflect patient care needs. [14][15][16] Administrative health data can also proi i vide sound information on the presence of comorbid conditions. 17 The aim of this study was to quani i tify health service use (HSU) for 10 years postiinjury, controlling for demographic factors and preiexisting comorbidities.…”

Section: Introductionmentioning

confidence: 99%

Ten-year health service use outcomes in a population-based cohort of 21 000 injured adults: the Manitoba Injury Outcome Study

Cameron

Purdie

Kliewer

et al. 2006

Bull World Health Organ

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Objective To quantify long-term health service use (HSU) following non-fatal injury in adults. Methods A retrospective, population-based, matched cohort study identified an inception cohort (1988-91) of injured people who had been hospitalized (ICD-9-CM 800-995) aged 18-64 years (n = 21 032) and a matched non-injured comparison group (n = 21 032) from linked administrative data from Manitoba, Canada. HSU data (on hospitalizations, cumulative length of stay, physician claims and placements in extended care services) were obtained for the 12 months before and 10 years after the injury. Negative binomial and Poisson regressions were used to quantify associations between injury and long-term HSU. Findings Statistically significant differences in the rates of HSU existed between the injured and non-injured cohorts for the preinjury year and every year of the follow-up period. After controlling for pre-injury HSU, the attributable risk percentage indicated that 38.7% of all post-injury hospitalizations (n = 25 183), 68.9% of all years spent in hospital (n = 1031), 21.9% of physician claims (n = 269 318) and 77.1% of the care home placements (n = 189) in the injured cohort could be attributed to being injured. Conclusion Many people who survive the initial period following injury, face long periods of inpatient care (and frequent readmissions), high levels of contact with physicians and an increased risk of premature placement in institutional care. Population estimates of the burden of injury could be refined by including long-term non-fatal health consequences and controlling for the effect of preinjury comorbidity. Voir page 808 le résumé en français. En la página 809 figura un resumen en español.

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“…It was not surprising, therefore, that the international review by Roos et al described only a handful of information-rich environments worldwide, which have been constructed from the linkage of multiple, large, population-based, administrative data sets. 3 They included the Manitoba Population Health Information System, 4 Oxford Record Linkage Study, 5 Scottish Record Linkage System, 6 Rochester Epidemiology Project, 7 the Centre for Health Services and Policy Research in British Columbia, 8 and the Western Australian Data Linkage System (WADLS). 9 This report describes the strategic design, the steps to full implementation and the outcomes achieved by one of the world' s few comprehensive, population-based data linkage systems, the WADLS, which has linked over 30 health data collections for a population of 2.0 million living in the western one-third of the Australian continent.…”

mentioning

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

476

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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A Population-Based Health Information System

Cited by 37 publications

References 14 publications

Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa

Evaluation of record linkage of mortality data between a health and demographic surveillance system and national civil registration system in South Africa

Ten-year health service use outcomes in a population-based cohort of 21 000 injured adults: the Manitoba Injury Outcome Study

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

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