The generation of two specific cancer costing algorithms using Ontario administrative databases.
Costing algorithms
Journal
Current oncology (Toronto, Ont.)
ISSN: 1718-7729
Titre abrégé: Curr Oncol
Pays: Switzerland
ID NLM: 9502503
Informations de publication
Date de publication:
10 2019
10 2019
Historique:
entrez:
12
11
2019
pubmed:
12
11
2019
medline:
2
10
2020
Statut:
ppublish
Résumé
Cancer treatment and management have become increasingly economically burdensome. Consequently, to help with planning health service delivery, it is vital to understand the associated costs. Administrative databases can be used to help understand and generate real-world system-level costs. Using databases to generate costs can take one of two approaches: top-down or bottom-up. Top-down approaches disaggregate the total health care spending from a global health care budget by sector and provider. A bottom-up approach begins with individual-level health care use and its costs, which are then aggregated.
Identifiants
pubmed: 31708661
doi: 10.3747/co.26.5279
pii: conc-26-e682
pmc: PMC6821127
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e682-e692Informations de copyright
2019 Multimed Inc.
Déclaration de conflit d'intérêts
CONFLICT OF INTEREST DISCLOSURES We have read and understood Current Oncology’s policy on disclosing conflicts of interest, and we declare the following interests: NC has received salary support from Cancer Care Ontario as the Clinical Lead in Patient Reported Outcomes and Symptom Management; WKE has received fees as an advisory board member for AbbVie, Astellas, Bristol–Myers Squibb, Eisai, Gilead, Lilly, Takeda, and Merck, and has received consulting fees from AstraZeneca, Boehringer Ingelheim, Celgene, Janssen, Lilly, Roche, Servier, and Sanofi Genzyme. NM, SYC, NL, SJS, FES, CD, NJLH, CCE, MC, and NL have no conflicts to disclose.
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