Reducing uncertainty in health-care resource allocation
Artikel i vetenskaplig tidskrift, 2007

A key task for health policymakers is to optimise the outcome of health care interventions. The pricing of a new generation of cancer drugs, in combination with limited health care resources, has highlighted the need for improved methodology to estimate outcomes of different treatment options. Here we introduce new general methodology, which for the first time employs continuous hazard functions for analysis of survival data. Access to continuous hazard functions allows more precise estimations of survival outcomes for different treatment options. We illustrate the methodology by calculating outcomes for adjuvant treatment of gastrointestinal stromal tumours with imatinib mesylate, which selectively inhibits the activity of a cancer-causing enzyme and is a hallmark representative for the new generation of cancer drugs. The calculations reveal that optimal drug pricing can generate all win situations that improve drug availability to patients, make the most of public expenditure on drugs and increase pharmaceutical company gross profits. The use of continuous hazard functions for analysis of survival data may reduce uncertainty in health care resource allocation, and the methodology can be used for drug price negotiations and to investigate health care intervention thresholds. Health policy makers, pharmaceutical industry, reimbursement authorities and insurance companies, as well as clinicians and patient organisations, should find the methodology useful.

Survival Analysis

*Quality-Adjusted Life Years

Gastrointestinal Stromal Tumors/economics/mortality/surgery/therapy

*Delivery of Health Care

Humans

Proportional Hazards Models

Resource Allocation/*methods

Sweden

Retrospective Studies

Författare

Tomas Simonsson

Göteborgs universitet

Katarina Sjölund

Göteborgs universitet

Per Bümming

Göteborgs universitet

Håkan Ahlman

Göteborgs universitet

Bengt E Nilsson

Göteborgs universitet

Anders Odén

Chalmers, Matematiska vetenskaper

Göteborgs universitet

British Journal of Cancer

0007-0920 (ISSN) 1532-1827 (eISSN)

Vol. 96 1834-8

Ämneskategorier

MEDICIN OCH HÄLSOVETENSKAP

DOI

10.1038/sj.bjc.6603795

PubMed

17519908