Paper Reading Journals #11
A Model Predicting Healthcare Capacity Gaps for Alzheimer’s Disease-Modifying Treatment in Canada
Basic Info
| Item | Content |
|---|---|
| Title | A Model Predicting Healthcare Capacity Gaps for Alzheimer’s Disease-Modifying Treatment in Canada |
| Journal | The Canadian Journal of Neurological Sciences |
| Author | Sandra E. Black, Nathalie Budd, Haakon B. Nygaard, Louis Verret, Shikha Virdi, Laura Tamblyn Watts, Melanie Wilson |
| Year Published | 2024 |
| Link | https://doi.org/10.1017/cjn.2023.270 |
| Geography of Study | Canada |
| Area of Study | Alzheimer’s Disease, Health System Research |
Description
(Including data and methods)
Data:
Dataset were screened and combined by researchers manually this include: (1) demographic and epidemiology data, from Statistics Canada (national bureau); (2) Literature review regarding AD prevalence and epidemiology investigations; (3) healthcare resources capacity data, from government report, - Canadian Agency for Drugs and Technologies in Health (CADTH), Canadian Institute for Health Information(CIHI) and so on. (4) expert estimation and consensus inputs from interdisciplinary expert committee.
Model:
Patient flow + resource capacity model adopting the concepts of system dynamics modeling.
Main Contribution
(Innovative method or Application)
Innovation Type: Application Innovation
This research construct a mode which as detailed as provisional level and covered healthcare system nodes from screening to continuing follow-ups. It provide a new estimation modeling methods to estimate if the Canadian healthcare system could take DMT needs.
Data Source
Dataset were screened and combined by researchers manually this include: (1) demographic and epidemiology data, from Statistics Canada (national bureau); (2) Literature review regarding AD prevalence and epidemiology investigations; (3) healthcare resources capacity data, from government report, - Canadian Agency for Drugs and Technologies in Health (CADTH), Canadian Institute for Health Information(CIHI) and so on. (4) expert estimation and consensus inputs from interdisciplinary expert committee.
Favorite Thing
This article presents a modeling approach to healthcare systems that differs from methods heavily grounded in statistical inference. Its framework relies more on deterministic arithmetic operations and less on inferential or probabilistic modeling. This design offers greater flexibility for modelers, allowing clearer manipulation of system parameters. Furthermore, the inclusion of scenario analysis is particularly valuable and aligns well with approaches we plan to adopt in our own project.