Using economic analyses for local priority setting : the population cost-impact approach

The sociology of rationing: Towards increased interdisciplinary dialogue - A critical interpretive literature review

Since the 1990s, the sociology of rationing has developed in explicit opposition to health economic and bioethical approaches to healthcare rationing. This implies a limited engagement with other disciplines and a limited impact on political debates. To bring the sociology of rationing into an interdisciplinary dialogue, it is important to understand the disciplines' analytical differences and similarities. Based on a critical interpretive literature synthesis, this article examines four disciplinary perspectives on healthcare rationing and priority setting: (1) Health economics, which seeks to develop decision models to provide for more rational resource allocation; (2) Bioethics, which seeks to develop normative principles and procedures to facilitate a just allocation of resources; (3) Health policy studies, which focus on issues of legitimacy and implementation of decision models; and lastly (4) Sociology, which analyses the uncertainty of rationing and the resulting value conflicts and negotiations. The article provides an analytical overview and suggestions on how to advance the impact of sociological arguments in future rationing debates: Firstly, we discuss how to develop the concepts and assumptions of the sociology of rationing. Secondly, we identify specific themes relevant for sociological inquiry, including the recurring problem of how to translate administrative priority setting decisions into clinical practice.

Prioritizing investment in public health and health equity: what can commissioners do?

OBJECTIVES

To explore commissioners' views on prioritizing for investment in health. This study reviewed: methods for decision support; their relevance for prioritizing health and health equity in principle; and their adoption by decision makers in practice.

METHODS

Decision makers' views were sought through semi-structured interviews and an online survey, and prioritization tools were reviewed. Interviews were held in 2008-2009 with a subsample followed up in 2009-2010. In late 2009, a national online survey was sent to 508 individuals across 146 primary care trusts (PCTs). The two phases of the interviews comprised 52 and 17 participants, respectively. Responses to the national survey were received from 138 decision makers in 95 (65%) PCTs. Prioritization tools were identified through interviews and the survey as above, a rapid review of literature and in consultation with health economists. A grounded theory approach was adopted for the qualitative interview analysis.

RESULTS

Although most PCTs used a prioritization framework, few of the tools identified in this review were used by public health commissioners. This was partly a consequence of limitations of priority-setting tools in the context of public health investment, and partly a lack of relevant skills and data. Tensions in relation to developing strategies for disinvestment and in prioritizing a long-term public health agenda in a context of economic austerity were evident.

CONCLUSIONS

The context for decision making appears to be more important than the deployment of specific tools and techniques. Commissioners need to recognize the limitations of priority-setting tools, but also know how to apply them to help maximize health gain and health equity over the longer term. Decision-support tools should be developed in collaboration with public health commissioners to ensure relevance and practicality of use.

The use of epidemiological measures to estimate the impact of primary prevention interventions on CHD, stroke and cancer outcomes: experiences from Herefordshire, UK

Background: CHD, stroke and cancers are the major causes of mortality in the UK and are responsible for significant amounts of morbidity and healthcare costs. This study examines the proportion of CHD, stroke and cancer owing to specific risk factors in Herefordshire, UK. It estimates the population impact of a number of interventions being implemented to reduce these risk factors, through the NHS Health Check program and the Herefordshire Health Improvement Plan. The present study also aims to demonstrate the value of epidemiological measures in providing evidence-based public health information in policy-making to aid decision makers when prioritizing investments and optimal use of resources.

Methods: The epidemiological measures–‘Population Attributable Risk’ and ‘Population Impact Measures’–were used to assess the impact of interventions to reduce the burden of CHD, stroke and cancer.

Results: Implementation of the NHS Health Check program will prevent 63 CHD events, 90 MI events and 125 stroke events, and one lung cancer over a period of 5 years. Reducing specific risk factors by 5% annually through the Health Improvement Plan will prevent 65 CHD events, 25 MI events, 140 stroke events, four lung cancer, one breast cancer and four colorectal cancer cases in Herefordshire if targets are met over a period of 5 years.

Conclusion: Physical inactivity and obesity are the major causes of CHD and stroke events (incidence and mortality) in Herefordshire. Their impact is greater than the combined effect of hypercholesterolemia and hypertension.

Epidemiological measures used in this study proved to be excellent tools in providing evidence-based public health information. Their use is strongly recommended to support prioritization of primary prevention interventions.

What are the benefits of cognitive enhancers for Alzheimer's Disease: use of Population Impact Measures

Background

The study aims to quantify the population impact of prescribing cholinesterase inhibitors to slow the cognitive decline in Alzheimer's disease (AD), and to compare with the benefit of treating hypertension to prevent the onset of AD.

Methods

Literature review to ascertain the prevalence of AD, benefits of interventions, analysis of local and national surveys to measure the current use of interventions in the relevant population and application of the relevant findings to calculate Population Impact Measures. The Number of Events Prevented in a Population (NEPP) by the intervention over a defined time period is calculated for a UK urban population in one Local Authority (population size 217,000).

Results

Treatment of all eligible patients with mild to moderate AD with Cholinesterase Inhibitors would prevent cognitive deterioration (measured by ADAS – cog scale) in 123.6 (95% Confidence Intervals (CI) 82.3, 169.1), 16.4 (95% CI 2.1, 31.2) would show a mild improvement (4 points or more on the ADAS – cog scale) and 2.6 (95% CI 0.2, 5.8) would show an improvement of 7 points or more over a period of 6 months. This would require the treatment of 406 patients with Cholinesterase Inhibitors.

Increasing from the current treatment rate of 46% of eligible patients to 'best practice' level would prevent cognitive deterioration in 66.8 (95% CI 44.0, 92.6), 8.99 (95% CI 1.2, 16.8) and 1.4 (95% CI 0.11, 3.2) would improve by 4 and 7 points respectively on the ADAS – cog scale over 6 months. This would require the treatment of an extra 187 patients with Cholinesterase Inhibitors beyond current practice, at an additional annual direct drug cost of £187,000.

Improving the treatment of hypertension from current practice by 20% could prevent 8.2 (95% CI 2.3, 16.8) incident cases of AD in the next year. This would require the treatment of an extra 2711 patients with antihypertensive drugs.

Conclusion

Population Impact Measures are a new method to allow a demonstration of the magnitude of the benefit for the whole population following interventions. The use of drugs to slow cognitive decline, or to prevent AD by treating hypertension, can thus be assessed in a prioritisation exercise in competition with alternative use of resources.

Prioritising between direct observation of therapy and case-finding interventions for tuberculosis: use of population impact measures

BACKGROUND

Population impact measures (PIMs) have been developed as tools to help policy-makers with locally relevant decisions over health risks and benefits. This involves estimating and prioritizing potential benefits of interventions in specific populations. Using tuberculosis (TB) in India as an example, we examined the population impact of two interventions: direct observation of therapy and increasing case-finding.

METHODS

PIMs were calculated using published literature and national data for India, and applied to a notional population of 100,000 people. Data included the incidence or prevalence of smear-positive TB and the relative risk reduction from increasing case finding and the use of direct observation of therapy (applied to the baseline risks over the next year), and the incremental proportion of the population eligible for the proposed interventions.

RESULTS

In a population of 100,000 people in India, the directly observed component of the Directly Observed Treatment, Short-course (DOTS) programme may prevent 0.188 deaths from TB in the next year compared with 1.79 deaths by increasing TB case finding. The costs of direct observation are (in international dollars) 5960 I dollars and of case finding are 4839 I dollars or 31702 I dollars and 2703 I dollars per life saved respectively.

CONCLUSION

Increasing case-finding for TB will save nearly 10 times more lives than will the use of the directly observed component of DOTS in India, at a smaller cost per life saved. The demonstration of the population impact, using simple and explicit numbers, may be of value to policy-makers as they prioritize interventions for their populations.