Predicting health care utilization using CIHI's Population Grouping Methodology
Introduction CIHI’s Population Grouping Methodology uses data from multiple sectors to create clinical profiles and to predict the entire population’s current and future morbidity burden and healthcare utilization. Outputs from the grouper can be applied to healthcare decision making and planning pr...
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| Format: | Article |
| Language: | English |
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Swansea University
2018-08-01
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| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/762 |
| _version_ | 1797427919814918144 |
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| author | Yvonne Rosehart |
| author_facet | Yvonne Rosehart |
| author_sort | Yvonne Rosehart |
| collection | DOAJ |
| description | Introduction
CIHI’s Population Grouping Methodology uses data from multiple sectors to create clinical profiles and to predict the entire population’s current and future morbidity burden and healthcare utilization. Outputs from the grouper can be applied to healthcare decision making and planning processes.
Objectives and Approach
The population grouping methodology starts with everyone who is eligible for healthcare, including those who haven’t interacted with the healthcare system, providing a true picture of the entire population. The grouper uses diagnosis information over a 2-year period to create health profiles and predict individuals’ future morbidity and expected use of primary care, emergency department and long-term care services.
Predictive models were developed using age, sex, health conditions and the most influential health condition interactions as the predictors. These models produce predictive indicators for the concurrent period as well as one year into the future.
Results
The power of the model lies in the user’s ability to aggregate the data by population segments and compare healthcare resource utilization by different geographic regions, health sectors and health status.
The presentation will focus on how CIHI’s population grouping methodology helps client’s monitor population health and conduct disease surveillance. It assists clients with population segmentation, health profiling, predicting health care utilization patterns and explaining variation in health care resource use. It can be used for risk adjustment of populations for inter-jurisdictional analysis, for capacity planning and it can also be used as a component in funding models.
Conclusion/Implications
CIHI’s population grouping methodology is a useful tool for profiling and predicting healthcare utilization, with key applications for health policy makers, planners and funders. The presentation will focus on how stakeholders can apply the outputs to aid in their decision-making and planning processes. |
| first_indexed | 2024-03-09T08:51:45Z |
| format | Article |
| id | doaj.art-1018ad8ec0814a7fa1dde4db5d002a67 |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T08:51:45Z |
| publishDate | 2018-08-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-1018ad8ec0814a7fa1dde4db5d002a672023-12-02T14:01:00ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-08-013410.23889/ijpds.v3i4.762Predicting health care utilization using CIHI's Population Grouping MethodologyYvonne Rosehart0Canadian Institute for Health InformationIntroduction CIHI’s Population Grouping Methodology uses data from multiple sectors to create clinical profiles and to predict the entire population’s current and future morbidity burden and healthcare utilization. Outputs from the grouper can be applied to healthcare decision making and planning processes. Objectives and Approach The population grouping methodology starts with everyone who is eligible for healthcare, including those who haven’t interacted with the healthcare system, providing a true picture of the entire population. The grouper uses diagnosis information over a 2-year period to create health profiles and predict individuals’ future morbidity and expected use of primary care, emergency department and long-term care services. Predictive models were developed using age, sex, health conditions and the most influential health condition interactions as the predictors. These models produce predictive indicators for the concurrent period as well as one year into the future. Results The power of the model lies in the user’s ability to aggregate the data by population segments and compare healthcare resource utilization by different geographic regions, health sectors and health status. The presentation will focus on how CIHI’s population grouping methodology helps client’s monitor population health and conduct disease surveillance. It assists clients with population segmentation, health profiling, predicting health care utilization patterns and explaining variation in health care resource use. It can be used for risk adjustment of populations for inter-jurisdictional analysis, for capacity planning and it can also be used as a component in funding models. Conclusion/Implications CIHI’s population grouping methodology is a useful tool for profiling and predicting healthcare utilization, with key applications for health policy makers, planners and funders. The presentation will focus on how stakeholders can apply the outputs to aid in their decision-making and planning processes.https://ijpds.org/article/view/762 |
| spellingShingle | Yvonne Rosehart Predicting health care utilization using CIHI's Population Grouping Methodology International Journal of Population Data Science |
| title | Predicting health care utilization using CIHI's Population Grouping Methodology |
| title_full | Predicting health care utilization using CIHI's Population Grouping Methodology |
| title_fullStr | Predicting health care utilization using CIHI's Population Grouping Methodology |
| title_full_unstemmed | Predicting health care utilization using CIHI's Population Grouping Methodology |
| title_short | Predicting health care utilization using CIHI's Population Grouping Methodology |
| title_sort | predicting health care utilization using cihi s population grouping methodology |
| url | https://ijpds.org/article/view/762 |
| work_keys_str_mv | AT yvonnerosehart predictinghealthcareutilizationusingcihispopulationgroupingmethodology |