Budgetary policies and available actions: A generalisation of decision rules for allocation and research decisions

被引:24
作者
McKenna, Claire [1 ]
Chalabi, Zaid [2 ]
Epstein, David [1 ]
Claxton, Karl [1 ]
机构
[1] Univ York, Ctr Hlth Econ, York YO10 5DD, N Yorkshire, England
[2] Univ London London Sch Hyg & Trop Med, Dept Publ Hlth & Policy, London WC1E 7HT, England
基金
英国医学研究理事会;
关键词
Allocation decisions; Cost-effectiveness analysis; Research decisions; Stochastic mathematical programming; Decision analysis; COST-EFFECTIVENESS ANALYSIS; CARE RESOURCE-ALLOCATION; ROBUST OPTIMIZATION; HEALTH; UNCERTAINTY; INFORMATION; PORTFOLIO; PROGRAMS; UTILITY;
D O I
10.1016/j.jhealeco.2009.11.005
中图分类号
F [经济];
学科分类号
02 ;
摘要
The allocation problem in health care can be characterised as a mathematical programming problem but attempts to incorporate uncertainty in costs and effect have suffered from important limitations. A two-stage stochastic mathematical programming formulation is developed and applied to a numerical example to explore and demonstrate the implications of this more general and comprehensive approach. The solution to the allocation problem for different budgets, budgetary policies, and available actions are then demonstrated. This analysis is used to evaluate different budgetary policies and examine the adequacy of standard decision rules in cost-effectiveness analysis. The research decision is then considered alongside the allocation problem. This more general formulation demonstrates that the value of further research depends on: (i) the budgetary policy in place; (ii) the realisations revealed during the budget period: (iii) remedial actions that may be available; and (iv) variability in parameters values. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:170 / 181
页数:12
相关论文
共 32 条
[1]   Expected value of sample information calculations in medical decision modeling [J].
Ades, AE ;
Lu, G ;
Claxton, K .
MEDICAL DECISION MAKING, 2004, 24 (02) :207-227
[2]   Optimal allocation of resources over health care programmes: dealing with decreasing marginal utility and uncertainty [J].
Al, MJ ;
Feenstra, TL ;
van Hout, BA .
HEALTH ECONOMICS, 2005, 14 (07) :655-667
[3]   Gains and costs of information in stochastic programming [J].
Artstein, Z .
ANNALS OF OPERATIONS RESEARCH, 1999, 85 (0) :129-152
[4]  
AZONDEKON SH, 1999, EUR J OPER RES, V117, P456
[5]   COST-EFFECTIVENESS UTILITY ANALYSES - DO CURRENT DECISION RULES LEAD US TO WHERE WE WANT TO BE [J].
BIRCH, S ;
GAFNI, A .
JOURNAL OF HEALTH ECONOMICS, 1992, 11 (03) :279-296
[6]   CHANGING THE PROBLEM TO FIT THE SOLUTION - JOHANNESSON AND WEINSTEIN (MIS) APPLICATION OF ECONOMICS TO REAL-WORLD PROBLEMS [J].
BIRCH, S ;
GAFNI, A .
JOURNAL OF HEALTH ECONOMICS, 1993, 12 (04) :469-476
[7]   Resource allocation for control of infectious diseases in multiple independent populations: beyond cost-effectiveness analysis [J].
Brandeau, ML ;
Zaric, GS ;
Richter, A .
JOURNAL OF HEALTH ECONOMICS, 2003, 22 (04) :575-598
[8]   Uncertainty and value of information when allocating resources within and between healthcare programmes [J].
Chalabi, Zaid ;
Epstein, David ;
McKenna, Claire ;
Claxton, Karl .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2008, 191 (02) :529-538
[9]   The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies [J].
Claxton, K .
JOURNAL OF HEALTH ECONOMICS, 1999, 18 (03) :341-364
[10]   Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra [J].
Claxton, K ;
Sculpher, M ;
McCabe, C ;
Briggs, A ;
Akehurst, R ;
Buxton, M ;
Brazier, J ;
O'Hagan, T .
HEALTH ECONOMICS, 2005, 14 (04) :339-347