Post-acute care for older people in community hospitals--a cost-effectiveness analysis within a multi-centre randomised controlled trial.
ABSTRACT to compare the cost effectiveness of post-acute care for older people provided in community hospitals with general hospital care.
cost-effectiveness study embedded within a randomised controlled trial.
seven community hospitals and five general hospitals at five centres in the midlands and north of England. Participants: 490 patients needing rehabilitation following hospital admission with an acute illness. Intervention: multidisciplinary team care for older people in community hospitals.
EuroQol EQ-5D scores transformed into quality-adjusted life years; health and social service costs during the 6-month period following randomisation.
there was a non-significant difference between the community hospital and general hospital groups for changes in quality-adjusted life-year values from baseline to 6 months (mean difference 0.048; 95% confidence interval -0.028 to 0.123; P = 0.214). Resource use was similar for both groups. The mean (standard deviation) costs per patient for health and social services resources used were comparable for both groups: community hospital group 8,946 pounds ( 6,514 pounds); general hospital group 8,226 pounds ( 7,453 pounds). These findings were robust to sensitivity analyses. The incremental cost-effectiveness ratio estimate was 16,324 pounds per quality-adjusted life year. A cost effectiveness acceptability curve suggests that if decision makers' willingness to pay per quality-adjusted life year was 10,000 pounds, then community hospital care was effective in 47% of cases, and this increased to only 50% if the threshold willingness to pay was raised to 30,000 pounds.
the cost effectiveness of post-acute rehabilitation for older people was similar in community hospitals and general hospitals.
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ABSTRACT: Decision-making in health care is inevitably undertaken in a context of uncertainty concerning the effectiveness and costs of health care interventions and programmes. One method that has been suggested to represent this uncertainty is the cost-effectiveness acceptability curve. This technique, which directly addresses the decision-making problem, has advantages over confidence interval estimation for incremental cost-effectiveness ratios. However, despite these advantages, cost-effectiveness acceptability curves have yet to be widely adopted within the field of economic evaluation of health care technologies. In this paper we consider the relationship between cost-effectiveness acceptability curves and decision-making in health care, suggest the introduction of a new concept more relevant to decision-making, that of the cost-effectiveness frontier, and clarify the use of these techniques when considering decisions involving multiple interventions. We hope that as a result we can encourage the greater use of these techniques.Health Economics 01/2002; 10(8):779-87. · 2.23 Impact Factor
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ABSTRACT: Cost-effectiveness analysis is now an integral part of health technology assessment and addresses the question of whether a new treatment or other health care program offers good value for money. In this paper we introduce the basic framework for decision making with cost-effectiveness data and then review recent developments in statistical methods for analysis of uncertainty when cost-effectiveness estimates are based on observed data from a clinical trial. Although much research has focused on methods for calculating confidence intervals for cost-effectiveness ratios using bootstrapping or Fieller's method, these calculations can be problematic with a ratio-based statistic where numerator and/or denominator can be zero. We advocate plotting the joint density of cost and effect differences, together with cumulative density plots known as cost-effectiveness acceptability curves (CEACs) to summarize the overall value-for-money of interventions. We also outline the net-benefit formulation of the cost-effectiveness problem and show that it has particular advantages over the standard incremental cost-effectiveness ratio formulation.Statistical Methods in Medical Research 01/2003; 11(6):455-68. · 2.36 Impact Factor
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ABSTRACT: The assessment of the validity and reliability of generic quality of life (QoL) instruments among elderly patient groups has tended to lag behind such assessments in general populations, yet it is an important methodological issue. This paper presents the findings from a study of the use of the EuroQoL among an elderly acute care patient group, focusing particularly on the ability to self-complete, construct validity and sensitivity to change. Two hundred and fourteen UK patients aged 65 years and over, participating in a randomized controlled trial comparing hospital at home and routine hospital care were asked to complete the EuroQoL and a number of other instruments at randomization and at 4 week and 3 month follow-ups. The inability to self-complete the EuroQol was found to be strongly related to both increased age and reduced cognitive function (p < 0.0001). From logistic regression, the expected probability of an acute care patient requiring interview administration at age 65 years is 11%, at age 75 years is 37% and at age 85 years is 73%. The relationships with age and limiting long-standing illness/disability were weaker than expected, but the results obtained from the EuroQoL were highly correlated with those from both the Barthel Index and the COOP-WONCA charts where this was anticipated. Preliminary evidence of sensitivity to change was found from descriptive statistics of the changes in scores for four specific subgroups of patients, but the small numbers and high variability in each sub-sample means that this should be interpreted with caution. The most important issue arising from the research concerns the impact of age on the ability to self-complete the EuroQoL questionnaire. It is argued that this research points to the need for rigorous studies (such as randomized controlled trials) to assess the impact of the format of administration of the EuroQoL on the scores obtained.Quality of Life Research 01/1998; 7(1):1-10. · 2.41 Impact Factor