Agreement between Self-Reported and Routinely Collected Health Care Utilisation Data among Seniors

Objective: To examine the agreement between self-reported and routinely collected administrative health care utilisation data, and the factors associated with agreement between these two data sources. Data Sources/Study Setting: A representative sample of seniors living in an Ontario county within Canada was identified using the Ontario Ministry of Health’s Registered Persons Data Base in 1992. Health professional billing information and hospitalisation data were obtained from the Ontario Ministry of Health and Long-Term Care (OMH) and the Ontario Health Insurance Plan (OHIP). Principal Findings: Substantial to almost perfect agreement was found for the contact utilisation measures, while agreement on volume utilisation measures varied from poor to almost perfect. In surveys, seniors overreported contact with general practitioner and physiotherapists or chiropractors, and underreported contact with other medical specialists. Seniors also underreported the number of contacts with general practitioners and other medical specialists. The odds of agreement decreased if respondents were male, aged 75 years and older, had incomes of less than $25,000, had poor/fair/good self-assessed health status, or had two or more chronic conditions. Conclusion: The findings of this study indicate that there are substantial discrepancies between self-reported and administrative data among older adults. Researchers seeking to examine health care use among older adults need to consider these discrepancies in the interpretation of their results. Failure to recognize these discrepancies between survey and administrative data among older adults may lead to the establishment of inappropriate health care policies.health services utilisation; seniors; self-reports; agreement; billing data

Geographic disparity in premature mortality in Ontario, 1992–1996

BACKGROUND: Standardized mortality ratios are used to identify geographic areas with higher or lower mortality than expected. This article examines geographic disparity in premature mortality in Ontario, Canada, at three geographic levels of population and considers factors that may underlie variations in premature mortality across geographic areas. All-cause, sex and disease chapter specific premature mortality were analyzed at the regional, district and public health unit level to determine the extent of geographic variation. Standardized mortality ratios for persons aged 0–74 years were calculated to identify geographic areas with significantly higher or lower premature mortality than expected, using Ontario death rates as the basis for the calculation of expected deaths in the local population. Data are also presented from the household component of the 1996/97 National Population Health Survey and from the 1996 Statistics Canada Census. RESULTS: Results showed approximately 20% higher than expected all-cause premature mortality for males and females in the North region. However, disparity in all-cause premature mortality in Ontario was most pronounced at the public health unit level, ranging from 20% lower than expected to 30% higher than expected. Premature mortality disparities were largely influenced by neoplasms, circulatory diseases, injuries and poisoning, respiratory diseases and digestive diseases, which accounted for more than 80% of all premature deaths. Premature mortality disparities were also more pronounced for disease chapter specific mortality. CONCLUSION: Geographic disparities in premature mortality are clearly greater at the small area level. Geographic disparities in premature mortality undoubtedly reflect the underlying distribution of population health determinants such as health related behaviours, social, economic and environmental influences

Evaluation of Urine CCA Assays for Detection of Schistosoma mansoni Infection in Western Kenya

Although accurate assessment of the prevalence of Schistosoma mansoni is important for the design and evaluation of control programs, the most widely used tools for diagnosis are limited by suboptimal sensitivity, slow turn-around-time, or inability to distinguish current from former infections. Recently, two tests that detect circulating cathodic antigen (CCA) in urine of patients with schistosomiasis became commercially available. As part of a larger study on schistosomiasis prevalence in young children, we evaluated the performance and diagnostic accuracy of these tests—the carbon test strip designed for use in the laboratory and the cassette format test intended for field use. In comparison to 6 Kato-Katz exams, the carbon and cassette CCA tests had sensitivities of 88.4% and 94.2% and specificities of 70.9% and 59.4%, respectively. However, because of the known limitations of the Kato-Katz assay, we also utilized latent class analysis (LCA) incorporating the CCA, Kato-Katz, and schistosome-specific antibody results to determine their sensitivities and specificities. The laboratory-based CCA test had a sensitivity of 91.7% and a specificity of 89.4% by LCA while the cassette test had a sensitivity of 96.3% and a specificity of 74.7%. The intensity of the reaction in both urine CCA tests reflected stool egg burden and their performance was not affected by the presence of soil transmitted helminth infections. Our results suggest that urine-based assays for CCA may be valuable in screening for S. mansoni infections

Accuracy of Herdsmen Reporting versus Serologic Testing for Estimating Foot-and-Mouth Disease Prevalence

Herdsman-reported disease prevalence is widely used in veterinary epidemiologic studies, especially for diseases with visible external lesions; however, the accuracy of such reports is rarely validated. Thus, we used latent class analysis in a Bayesian framework to compare sensitivity and specificity of herdsman reporting with virus neutralization testing and use of 3 nonstructural protein ELISAs for estimates of foot-and-mouth disease (FMD) prevalence on the Adamawa plateau of Cameroon in 2000. Herdsman-reported estimates in this FMD-endemic area were comparable to those obtained from serologic testing. To harness to this cost-effective resource of monitoring emerging infectious diseases, we suggest that estimates of the sensitivity and specificity of herdsmen reporting should be done in parallel with serologic surveys of other animal diseases.Fil: Morgan, Kenton L.. University of Liverpool; Reino UnidoFil: Handel, Ian G.. University of Edinburgh; Reino UnidoFil: Tanya, Vincent N.. Institute of Agricultural Research for Development; Camerún. Ministry of Scientific Research and Innovation; CamerúnFil: Hamman, Saidou M.. Institute of Agricultural Research for Development; CamerúnFil: Nfon, Charles. Institute of Agricultural Research for Development; CamerúnFil: Bergmann, Ingrid Evelyn. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ciencias y Tecnología "Dr. Cesar Milstein"; Argentina. Pan American Foot and Mouth Disease Center; BrasilFil: Malirat, Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Ciencias y Tecnología "Dr. Cesar Milstein"; Argentina. Pan American Foot and Mouth Disease Center; BrasilFil: Sorensen, Karl J.. Danish Veterinary Institute for Virus Research; DinamarcaFil: Bronsvoort, Barend M de C,. University of Edinburgh; Reino Unid

Assessing the accuracy of land cover change with imperfect ground reference data

The ground data used as a reference in the validation of land cover change products are often not an ideal gold standard but degraded by error. The effects of ground reference data error on the accuracy of land cover change detection and the accuracy of estimates of the extent of change was evaluated. Twelve data sets were simulated to allow the exploration of the impacts of a spectrum of ground data imperfections on the estimation of the producer’s and user’s accuracy of change as well as of change extent. Simulated data were used since this ensured that the actual properties of the data were known and to exclude effects due to other sources of ground reference data error; although the impacts of simulated reference data on two real confusion matrices is also illustrated. The imperfections evaluated ranged from the inclusion of small amounts of known error into the ground reference data through to the extreme situation in which ground data were absent. The results show that even small amounts of error in the ground reference data can introduce large error into studies of land cover change by remote sensing and reinforce the desire to avoid the expression ground truth as this might imply that the data are a gold standard reference. The effect of reference data imperfections was dependent on the degree of association between the errors in the cross tabulated data sets. For example, in the scenarios investigated, a 10% error in the reference data set introduced an under-estimation of the producer’s accuracy of 18.5% if the errors were independent but an over-estimation of the producer’s accuracy of 12.3% if the errors were correlated. The magnitude of the mis-estimation of the producer’s accuracy was also a function of the amount of change and greatest at low levels of change. The amount of land cover change estimated also varied greatly as a function of ground reference data error. Some possible methods to reduce or even remove the impacts of ground reference data error were illustrated. These ranged from simple algebraic means to estimate the actual values of accuracy and change extent if the imperfections were known through to a latent class analysis that allowed the assessment of classification accuracy and estimation of change extent without the use of ground reference data if the underlying model is defined appropriately

The Relationship Between Health Care Need and Standardized Mortality Ratios in Ontario

Needs-based health care funding methods are increasingly being considered for the Canadian health care system, particularly as a basis for allocating funds from central Ministries of Health to local and regional health authorities. Standardized Mortality Ratios are one of the commonly used measures of health care need within such funding formulae. This paper applies the non-linear least-squares method suggested by Bedard et al. (2000) to identify the empirical relationship between standardized mortality ratios (SMRs) and health care need in Ontario. The data used in this analysis allow for a more detailed examination of the SMR-need relationship. Like Bedard et al., we find the SMR-need relationship is highly non-linear; unlike Bedard et al., we find the relationship to be less-than-proportional, reversing the conclusion that needs-based formula based on the linearity assumption under-compensate high-need regions and overcompensate low-need regions. We also find that estimates derived from provider-based expenditure series are especially sensitive to alternative model specifications. Finally, needs-based funding would generate substantial inter-regional reallocations of health care resources in Ontario compared to the current funding methods.

Geographic Disparity in Premature Mortality in Ontario, 1992-1996

Objectives: This article examines the extent of geographic disparity in premature mortality in Ontario and considers factors that may underlie variations in premature mortality across geographic areas. Data Source: Mortality data for years 1992-1996 were obtained from Vital Statistics Records, Office of the Registrar General, Ontario Ministry of Consumer and Commercial Relations. Population data for years 1992-1996 were obtained from Statistics Canada intercensal population estimates (CANSIM database). Data are also presented from the household component of the 1996/97 National Population Health Survey and from the 1996 Statistics Canada Census. Analytical Techniques: All-cause, sex and disease chapter specific premature mortality in Ontario were analyzed at the regional, district health council and public health unit level to determine the extent of geographic disparity. We calculated standardized mortality ratios for persons aged 0-74 years to identify geographic areas with significantly higher or lower premature mortality than expected, using Ontario death rates as the basis for the calculation of expected deaths in the local population. Main Results: Results showed approximately 20% higher than expected all-cause premature mortality for males and females in the North region. However, disparity in all-cause premature mortality in Ontario was most pronounced at the public health unit level, ranging from 20% lower than expected to 30% higher than expected. Premature mortality disparities were largely influenced by neoplasms, circulatory diseases, injuries and poisoning, respiratory diseases and digestive diseases, which accounted for more than 80% of all premature deaths. Premature mortality disparities were also more pronounced for disease chapter specific mortality. Geographic disparities in premature mortality undoubtedly reflect the underlying distribution of population health determinants such as health related behaviours, social, economic and environmental influences.mortality, cause of death, epidemiology, Ontario