Groundbreaking research examines how the sequence of disease acquisition affects life expectancy

New research, led by Population Data Science at Swansea University Medical School, published in The Lancet Public Health, examines how co-existing diseases develop over time and how they impact patient outcomes and healthcare resources.

Researchers looked at how a cluster of physical and mental health conditions (psychosis, diabetes, and congestive heart failure) can develop over time and what effect this can have on life expectancy for patients in Wales, UK.

The burden on patients and their health service providers worsens as the number of patients’ different health conditions increases. The associated health and social care costs of this are greater than the expected costs of managing individual conditions, with costs approximately doubling for every additional chronic condition.

In the UK, it is estimated that more than 25% of the adult population has two or more long-term health conditions. This estimate increases to 65% for those older than 65 years, and almost 82% for those aged 85 years or older.

This has major implications for the NHS and Social Care providers. This research supports a targeted approach for the prevention or delay of multiple health conditions for effective future healthcare planning. This is the first study to examine how the order of developing multiple chronic health conditions impacts patients’ life expectancy.

The UK-wide study team was led by Associate Professor of Statistics at Swansea University Medical School, Dr Rhiannon Owen, and was funded by Health Data Research (HDR) UK.

The team used SAIL Databank to analyse the outcomes of over 1.5 million patients and found that the sequence and timing of diagnosis of these conditions had an important effect on a patient’s life expectancy.

SAIL Databank is a Trusted Research Environment that provides secure, approved access to 85% of primary care and 100% of secondary care anonymised health records for the population of Wales. The research was approved by SAIL’s independent governance panel and scrutinised by its Consumer Panel of lay, public members.

Using this data, researchers were able to produce statistical models to examine the trajectory and outcomes of these conditions in different sequences of development. This revealed that the order of disease acquisition had a significant association with a patient’s life expectancy. These statistical analyses were adjusted for age, sex, and area levels of deprivation.

Individuals who developed diabetes, psychosis, and congestive heart failure, in that order, had reduced life expectancy compared with people who developed the same three conditions in a different order.

Commenting on the research, Dr Owen, said “This work is of vital importance to begin to understand how diseases accumulate over time and identify opportunities for potential screening and earlier intervention to benefit patients with two or more long-term conditions, known as multimorbidity. We were able to assess the accumulation of diseases over a 20-year period in the population of Wales using linked primary and secondary care health records.

“We found that both the combination of conditions and the order in which you develop them can have a substantial impact on life-expectancy. This work was only made possible through the use of the SAIL Databank, and the richness and scale of the data available for research in Wales. The generosity of patients and the public across the UK through their active engagement with this project further strengthened the applicability and relevance of this research to individuals with complex care needs.”

The application of these models could be used to help inform patients, clinicians, and healthcare decision-makers on the appropriate identification and management of patient care, leading to improved patient outcomes and healthcare cost reductions.

These models provide the research community with a flexible framework to analyse trajectories of other disease development and their associated effects on patient outcomes. This helps to support healthcare delivery through risk factor assessment, identifying screening opportunities, and targeted interventions for healthcare policy and decision-making.

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