Examining the potential for microeconometric analysis health data sets: An exploratory study using the psychiatric morbidity surveys

Introduction

NIHR is concerned to build capacity in research methods relevant to their work. At the same time academic health economists are concerned that a separation is emerging between economists and health economists which may be detrimental to the quality of health economics research. An important factor limiting the involvement of economists in areas relevant to the NIHR is a lack of awareness of data sets which might include variables of interest to economics researchers alongside health variables. Our study focuses on ways in which large health-related data sets can be used by economists to tackle questions that are relevant to both economists and to NIHR, and which offer the opportunity to develop and test econometric methods. In this way economists may be attracted to health-related work, thus increasing the knowledge base on which NIHR can draw. We explore these issues using the Office of National Statistics (ONS) Psychiatric Morbidity Surveys (PMS), which are described in more detail in the sections that follow.

The stated objectives of our project were to apply microeconometric methods to the Psychiatric Morbidity Surveys in order to:

  1. generate accurate estimates of different mental health conditions on health related quality of life, after controlling for background variables and physical health problems;
  2. examine how stable the marginal impact of these conditions is over time;
  3. provide important data to populate economic models of interventions for preventing and treating mental health conditions used by NICE in developing is guidance for the NHS;
  4. explore the interrelationships between debt and mental health;
  5. explore more generally the potential for large health–related data sets to be used by economists to increase the knowledge base on which NIHR can draw.