The aim of this work was to identify and review the evidence base on approaches taken within the health and care system to improve the quality of the data used for the identification and monitoring of health inequalities.
Introduction
Data analysis is a critical exercise for improving our understanding of health inequalities. For example, the Covid-19 pandemic highlighted health inequalities in England. Higher mortality in males, in many ethnic groups and in areas of higher deprivation replicated the pattern that existed already for non-communicable diseases. This knowledge, and researchers’ collective ability to analyse data effectively to reach these conclusions, illustrates the fundamental importance of having high-quality data for determining patterns of morbidity and mortality in the general population.
Relatedly, several policy reports released in the UK have highlighted the importance of improving the quality of data used for identification and monitoring of health inequalities. This links to two important questions:
- How can clinicians, administrators, and researchers help to improve the evidence base for informing decisions around health inequalities?
- What have institutions done across the country to effectively collect and maintain high-quality patient data at the population level?
For this project, we aimed to answer these questions through a systematic literature review. The review was published in the International Journal of Environmental Research and Public Health, and can be accessed here.
Project aims
The aim of this work was to identify and review the evidence base on approaches taken within the health and care system to improve the quality of the data used for the identification and monitoring of health inequalities.
The specific objectives were:
- Describe approaches that have been used or recommended to improve the quality (availability, completeness, accuracy, relevance and timeliness) of data for identification of health inequalities.
- Describe approaches that have been used or recommended to improve the quality of data for monitoring changes in health inequalities and describe the evidence base on the effectiveness of such approaches or recommendations.
Ultimately the aim is to make the highly valuable insights from the PHE/OHID project more accessible to the research and practice community. We will do this by disseminating findings of this project via an academic publication as well as a summary of findings through other mediums such as a short article on our website or a blog.
We are actively pursuing funding opportunities to develop a resources to guide strategies and approaches across health and care settings to improving the quality of data in relation to health inequalities.
Project activity
We have developed a search strategy and conducted a systematic search of the literature. Currently we have identified papers to be included in the review and are in the process of analysing them.
What we did
Our objective was to identify and review the evidence base on approaches taken within the health and care system to improve the quality of the data used for the identification and monitoring of health inequalities. Specifically:
- We described previously used or recommended approaches for improving the quality (availability, completeness, accuracy, relevance and timeliness) of data for the identification of health inequalities.
- Relatedly, we described the evidence for the effectiveness of these approaches or recommendations.
- Finally, we aimed to make insights from a previous Office for Health Improvement and Disparities (OHID, formerly Public Health England) project more accessible to the research and practice community.
What we found
Upon systematically searching the literature, we included information from 57 reports from the peer review and grey literature, which highlighted both observed problems in data collection and maintenance and strategies for mitigating these issues.
The majority of papers highlighted patient ethnicity as a key variable that is both essential for effectively establishing patterns about health inequalities and one that is frequently missed during the data collection process. The reasons for this omission in data collection are myriad, but include staff reluctance to ask patient about sensitive issues, lack of staff understanding about the importance of complete data collection and patient reluctance to provide information related to demographics, which includes ethnicity.
Importantly, we identified consistent recommendations in the literature from organisations who had experience with these problems and strategies for mitigating them. We describe the major themes comprising best practices at length in our published paper but summarise them here:
- Distal factors: Strategies for mitigating problems upstream of data collection should include mandating data collection and ensuring non-discrimination through legal safeguards.
- Enabling improvements: When preparing for data collection, it is necessary to inform and educate senior-level staff to ensure their support. Organisations should also engage with communities and patients to improve trust at the population level, and it is similarly important to train staff about why data collection, including around demographics, is essential for improving health inequalities.
- Data collection infrastructure: When collecting data, organisations should ensure that multidisciplinary teams are consulted throughout the process. For example, standardising the data collection process across an organisation (or nationally) will help to avoid mistakes at the individual level.
- Improving data quality: At the time of data analysis, researchers should aim to draw from multiple data sources when data fields, such as patient ethnicity, are empty. Moreover, researchers may rely on proxy variables or imputation to complete missing data fields.
We discuss these factors and other best practice recommendations at length in our published paper, which completes Phase 1 of our broader project of improving data on health inequalities. We are now in the process of completing Phase 2, for which we conducted a qualitative study based on interviews with health and care professionals in England. Through these interviews, we aimed to understand the resources professionals require for improving the quality of data used to investigate health inequalities.
Read the full paper based on our scoping review here.
Who was involved
- Principal Investigator: Dr Louise Lafortune (University of Cambridge)
- Vicki Peacey (OHID)
- Sowmiya Moorthie
- Sian Evans (OHID)
- Andres Roman-Urrestarazu (University of Cambridge)
- Carol Brayne (University of Cambridge)
Contact
ARC Core Team, ARCOffice@cpft.nhs.uk
