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Evidence for Population Health$

Richard Heller

Print publication date: 2005

Print ISBN-13: 9780198529743

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780198529743.001.0001

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Applying evidence to inform public health practice and health policy decision-making

Applying evidence to inform public health practice and health policy decision-making

Chapter:
(p.91) Chapter 10 Applying evidence to inform public health practice and health policy decision-making
Source:
Evidence for Population Health
Author(s):

Richard F. Heller

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198529743.003.0010

Abstract and Keywords

This chapter discusses the tensions between the health evidence base and other factors in making prioritization decisions that will influence public health and its practice. It concludes with a challenge to develop better methods for incorporating evidence into health priority setting.

Keywords:   priority setting, decision-making, public health practice, prioritization decisions

This chapter discusses the tensions between the health evidence base and other factors in making prioritization decisions that will influence public health and its practice.

General issues in setting priorities for population health

The need for priority setting in the field of health care comes from the reality that the demand for health care exceeds the availability of resources. This excess is clearly different in different settings, but the problem is getting worse everywhere, due partly to the ageing of the population and the increasing availability of new (and expensive) technologies, including medications. How the need for health care can be balanced with the need for improving the health of the community through means other than health care is a particular issue of interest to population health.

We have spent much of the book examining the evidence base for population health. However, the implementation of evidence into policy is in many ways more difficult than just collecting the evidence, and has not been tackled in as systematic a way. I have drawn on the work of a number of authors to develop this schema, resulting in Figure 10.1, which has the form of a balance between the two drivers of the policy-making process. Rychetnick and colleagues1 have offered a useful classification, which I have used as a basis for describing the balance between rigorous appraisal of the evidence (as per our (p.92)

                      Applying evidence to inform public health practice and health policy decision-making

Fig. 10.1 The balance between evidence and context—rigorous appraisal of the evidence and the sociopolitical processes that go into policy decision-making for implementing an intervention.

discussion of levels of evidence in Chapter 5) and the sociopolitical process that are also crucial to implementation of policy. Bhopal, in his excellent book Concepts of Epidemiology identifies two major drivers to priority setting—scientific and social/political/economic.2 The same distinction is nicely encapsulated by Dobrow and colleagues who identify ‘evidence’ and ‘context’ axes for decision-making.3 They show how the evidence-based medicine movement rates highly on the ‘evidence’ scale, but low on the ‘context’ scale. Singer identifies fairness and legitimacy (who should have the authority to make decisions),4 which also map onto the two drivers, which seem to revolve around the evidence and the context. I have added some points made by Elliott and Popay, who described some of the barriers to evidence-based decision-making,5 in drawing the figure. You can see which way I have tilted the balance!

Rosenstock and Lee comment on ways of responding to the threats to obtaining evidence in a way that will lead to its incorporation into policy:6

Maintaining the capacity for evidence-based policy requires differentiating between honest scientific challenge and evident vested interest and responding accordingly, building and diversifying partnerships, assuring the transparency of funding sources, agreeing on rules for publication, and distinguishing the point where science ends and policy begins.

(p.93) As we develop evidence for population health, we must ensure that the context in which decisions are made is fully understood as crucial to the implementation of evidence into public health practice. The quantification of costs and health gain may play only a small part in the decision-making process. I think that this is partly due to the poor methods currently available for estimating and comparing health gains to the population. It is one of my missions to show how health gain can be assessed at the population level so that it plays a more important role in decision-making.

Collecting the evidence

Returning to the ‘collect’ part of the Population Health Evidence Cycle, there is now increasing recognition that the way the evidence is generated in the first place will have an impact on how it is utilized. Research priorities have to be set, and these should not only reflect the interest of the researcher, but the values of the users of the

Table 10.1 Combined approach matrix for priority setting

Five steps in priority setting

Actors/factors determining the health status of a population (intervention levels)

Global level

Individual, family and community level

Level of health ministry, health research institutions health systems and services

Level of sectors other than health

Level of central government

1. Level of disease burden

2. Determinants for persistence

3. Present level of knowledge

4. Cost-effectiveness of future interventions

5. Resource flows

From the Global Forum on Health Research (http://www.globalforumhealth.org).

(p.94) research. Lomas and colleagues identify two main approaches to setting research priorities as ‘technical’ and ‘interpretive’: the latter can use their ‘listening model’ for involving stakeholders at various stages of the priority-setting process.7

Those of us who work in high income health economies have a great deal to learn from those in low to middle income economies in many ways, including how to set priorities. Where resources are limited, the imperative to spend the small amount available in the most effective way is greater than where we are playing at the margins of health gain. The Global Forum on Health Research is the latest in a distinguished line of initiatives to help low income economies to identify disease burden and health care and prevention priorities. This arises from the identification of the ‘10/90 gap’—only about 10 per cent of health research funds from public and private sources are devoted to 90 per cent of the world’s health problems. The Global Forum has encouraged use of the ‘combined approach matrix’ which brings together in a systematic framework all current knowledge related to a particular disease or risk factor, and relates the ‘five steps in priority setting’ (an economic axis) to those who can make decisions on the health status of a population the ‘actors and factors’ (Table 10.1). This model can be used in a number of health settings.

The size of the problem

Part of the rigorous appraisal of the evidence involves making an assessment of the size of the problem and the potential benefits of the new policy. In Chapter 4, we spent some time discussing how we can measure the burden of disease and the population impact of interventions and disease causation. We will, in fact, come back to this in the final chapter with a toolkit for assessing the population impact. There have been many attempts to measure the burden of illness, but one is worth picking out here as it is designed to be directly relevant to policy making for preventive services. Coffield and colleagues designed a method to compare the value of clinical preventive services.8 They ranked these services on the basis of the ‘clinically preventable burden’ and the cost-effectiveness, using the quality adjusted life year (QALY) as the main outcome measure. They calculated a score (p.95) from 0 to 10 for each potential service, and found a number which scored highly, are delivered to 50 per cent or less of the target population, and are important missed opportunities for preventing disease and promoting health. We have previously discussed the different ways of assessing cost-effectiveness, and the limitations of the QALY as a measure of use to population health decision-making. Despite these limitations, this combination of the QALY and other ways of providing a ranking offers considerable potential for determining policy priorities.

A debate took place in the pages of the BMJ that nicely captured the issue of evidence and public policy. A group, which included the editors of the Lancet and BMJ, blamed a UK government inquiry into health inequalities of lacking an evidence base for its recommendations.9 A commentary provided a counterpoint, that for a number of public health interventions (including many of those which might help to reduce health inequalities) the evidence base just was not available.10

Back to implementation

Whatever methods of measuring the burden of illness are chosen there is an issue of identifying need in terms that can be related to a defined population and in a way that can be fed into identifying priorities and then into decision-making. The pathway described below, where the measurement of the disease burden leads to some action such as commissioning of services, is the ideal.

The challenge is not only to make sure that the measurement of the disease burden is appropriate, but that systems are in place to follow the path to lead to action, and that effective interventions are available to be commissioned.

The debate continues

Some have argued that there are limits to the value of evidence in policy-making,11 others respond that research is essential to

                      Applying evidence to inform public health practice and health policy decision-making

Fig. 10.2 From measurement to commissioning.

(p.96) contribute to health policy-making12 and that it is also possible to apply evidence to policy and management!13 , 14

I can’t claim to have the answer to all this, but this chapter should serve to indicate the debate and some of the parameters for thinking about this important issue. Singer has an excellent quote suggesting that more work is required:

The pressing research challenge is to develop and evaluate an interdisciplinary methodology for resource allocation decision making that incorporates but goes beyond EBM (Evidence-Based Medicine) and CEA (Cost-Effectiveness Analysis); integrates the various theoretical approaches to resource allocation of philosophy, law, political science, economics, and clinical epidemiology; proves useful to resource allocation decision makers; and is perceived as fair by the communities whose resources are at stake.15

Key summary points

  • The Student. The implementation of evidence into policy is driven by two balancing themes—the rigour of the evidence and the sociopolitical decision-making process.

  • The Practitioner. The way in which stakeholders are listened to and involved in designing the research will be important in how the results are implemented.

  • The Policy-maker. There is a challenge to develop better methods of incorporating evidence into health priority setting.

References

Bibliography references:

1 Rychetnik L., Frommer M., Hawe P., Shiell A. Criteria for evaluating evidence on public health interventions. J. Epidemiol. Community Health 2002; 56: 119–27.

2 Bhopal R. Concepts of Epidemiology: an integrated introduction to the ideas, theories, principles and methods of epidemiology. Oxford: Oxford University Press, 2002.

3 Dobrow M. J., Goel V., Upshur R. E. Evidence-based health policy: context and utilisation. Soc. Sci. Med. 2004; 58: 207–17.

4 Singer P. A., Martin D. K., Giacomini M., Purdy L. Priority setting for new technologies in medicine: qualitative case study. BMJ 2000; 321: 1316–18.

5 Elliott H., Popay J. How are policy makers using evidence? Models of research utilisation and local NHS policy making. J. Epidemiol. Community Health 2000; 54: 461–8.

(p.97) 6 Rosenstock L. and Lee L. J. Attacks on science: the risks to evidence-based policy. Am. J. Public Health 2002; 92: 14–18.

7 Lomas J., Fulop N., Gagnon D., Allen P. On being a good listener: setting priorities for applied health services research. Milbank Q. 2003; 81: 363–88.

8 Coffield A. B., Maciosek M. V., McGinnis J. M., Harris J. R., Caldwell M. B., Teutsch S. M. et al. Priorities among recommended clinical preventive services. Am. J. Prev. Med. 2001; 21: 1–9.

9 Macintyre S., Chalmers I., Horton R., Smith R. Using evidence to inform health policy: case study. BMJ 2001; 322: 222–5.

10 Davey S. G., Ebrahim S., Frankel S. How policy informs the evidence. BMJ 2001; 322: 184–5.

11 Black N. Evidence-based policy: proceed with care. BMJ 2001; 323: 275–9.

12 Donald A. Commentary: research must be taken seriously. BMJ 2001; 323: 278–9.

13 Walshe K. Evidence-based policy: don’t be timid. BMJ 2001; 323: 1187.

14 Walshe K. and Rundall T. G. Evidence-based management: from theory to practice in health care. Milbank Q. 2001; 79: 429–57.

15 Singer P. A. Resource allocation: beyond evidence-based medicine and cost-effectiveness analysis. ACP J. Club. 1997; 127: A16–18. (p.98)