Measuring meaningful healthcare outcomes
It’s an obvious thing to say but healthcare outcomes are important. Most clinicians and patients would like to know if an operation or treatment was successful, or carried out in a timely and safe manner. Yet the obviousness of this statement hides the complexity of measuring outcomes – for example, how best to define “success” or “safe”? Indeed, systematically measuring the effect of healthcare activity (or inactivity) on people and populations is still a relatively young science.
Outcomes research, “the study of the end results of health services that takes patients' experiences, preferences, and values into account”1 is however becoming recognised as a priority for clinicians, policy makers, managers and patients and is now supported by a number of funding bodies such as the NIHR2 in the UK and AHRQ3 in the USA. In addition, outcome measures are increasingly being used in the performance management of healthcare organisations and individuals, and have an important role in supporting accountability, transparency and public engagement with healthcare decision making.
What to measure?
Healthcare outcomes have typically been measured in terms of traditional biomedical measures: mortality, laboratory or physiological parameters, or defined clinical events. Although such measures are clearly relevant and important, they may not be the most important outcomes for patients or fully reflect the many ways that their lives have been affected by illness. For example, patients may consider quality of life, the ability to work or study unimpeded, satisfaction with healthcare services or the impact on carers and family members as being of equal or greater importance than a clinical measure of improvement. Measuring these more subjective and less easily defined outcomes is challenging but an increasing number of validated tools and methodologies have been developed to allow these to be measured. As a result the use of such measures is increasingly common in the NHS: Patient Reported Outcome Measures (PROMs) for hip and knee surgery4 or the routine reporting of patient experience survey data for example.
How to measure?
Outcomes data may come from many sources: administrative datasets (e.g. Hospital Episode Statistics), incident reporting, surveys, audit and disease registries for example. Not all such data is of the same quality or reliability however and secondary use of data primarily collected for other purposes (such as financial reimbursement of healthcare providers) can poses challenges in data linkage and information governance. Despite these challenges, such observational data are now increasingly being used in outcomes research to address questions about the efficacy, safety and value of healthcare practices. Such research adds value because it documents the effect of real world processes of care, outwith the artificial (and sometimes misleadingly unrepresentative) environment of a controlled trial. This research has been supported by the development of a variety of novel statistical methodologies such as propensity score matching and instrumental variable analysis that seek to address the limitations inherent to observational data5.
Recent decades have seen major changes in the way that healthcare outcomes are defined, measured and used. Routinely measuring outcomes for performance management, quality improvement and developing the healthcare evidence base is becoming more common, and, thanks to the advance of information technology, more feasible. Methodologies and tools are increasingly more patient-centred and more sensitive to the multidimensional nature of health and disease. It may have taken a long time, but measuring outcomes is now a key concept in modern healthcare.
- Clancy CM, Eisenberg JM. Outcomes Research: Measuring the End Results of Health Care. Science 1998; 282: 245-246
- www.nihr.ac.uk
- www.ahrq.gov/
- www.hscic.gov.uk/proms
- Concato J. Is it time for medicine-based evidence? JAMA 2012; 307: 1641-1643