Modernising NHS Records
The study, carried out by Yevgeniya and co-authors from King's College London, investigated the effect of digitising health records, such as key patient and treatment information, and whether it can help identify illness, effectiveness of treatments and the influence of patients’ gender and ethnicity.
Methods of research
The researchers analysed 500,000 diagnoses recorded for a cohort of around 200,000 mental health patients between 2008 and 2015.
Traditionally, research into medical conditions needs to be carried out using lengthy one-to-one interviews or large national databases, providing either detailed information on small numbers of people or few details for a large number of people.
The research found that the most common diagnoses in the considered population were depression, stress-related disorders, mental and behavioural disorders (due to the use of alcohol), and schizophrenia. It also found that women were more likely to be diagnosed with mood, neurotic, stress-related or eating disorders, while men were more likely to receive a diagnosis linked to substance abuse. Social and economic factors were more likely to impact on men's mental health, as well as those from black ethnic backgrounds, while patients of white ethnicities commonly suffered from problems linked to alcohol, opioids and sedatives.
By analysing unstructured patient records, researchers can turn mountains of routinely collected data into useful insights that can improve our understanding of mental health problems and the provision of healthcare services.
It is hoped the research will demonstrate how anonymous databases set up across the NHS could play a key role in helping researchers shape future medical treatments by providing data which can be easily analysed. The new system will also be able to automatically search for key information like courses of treatment and side effects, helping to improve how illnesses are understood and treated.
Opening up healthcare records for research has a number of benefits, including finding more effective forms of treatment and establishing adverse drug reactions, which will save time and money for both patients and doctors. Previous barriers, formed through ethnicity, technology and politics, can be overcome as security experts, software engineers and data scientists can work alongside clinicians and management to build secure pipelines providing researchers with de-identified, clean and structured data.