Researchers at the Universities of Cambridge, Bristol and UCL have developed the Cambridge Multimorbidity Score - a new way of measuring multiple long-term health conditions in primary care.The score is aimed at helping healthcare practitioners when responding to people with multiple health conditions.
The new Cambridge Multimorbidity Score is a transparent, simple measure of multimorbidity that can predict different outcomes in people with multiple conditions.
The number of patients with multiple long-term conditions is going up as the population ages, putting pressure on primary and secondary care. This pressure is exacerbated, the researchers say, by policies that promote rapid access to GPs over longer consultations, and single disease guidelines and performance targets.
Multimorbidity scores offer a means of identifying those patients in the population who are most likely to benefit from a tailored approach to care, helping clinicians to prioritize their efforts accordingly.
The Cambridge Multimorbidity Score can be a useful predictor of future health care use, including primary care utilisation, emergency department visits and death and may be of considerable value for policy development and health care priority setting, providing accurate, easy-to-implement ways of optimizing healthcare delivery to an aging population with multiple illnesses
- Martin Roland, Emeritus Professor, Primary Care Unit, University of Cambridge
This research, published in the Canadian Medical Association Journal (CMAJ), used primary care data from the UK Clinical Practice Research Database to identify 300,000 patients who had more than one of 37 health conditions that often occur together, such as hypertension, anxiety or depression, or painful conditions.
The researchers then modelled how these conditions affected three key patient outcomes: general practitioner visits, unplanned hospital admissions and death.
Rupert A. Payne, Silvia C. Mendonca, Marc N. Elliott, Catherine L. Saunders, Duncan A. Edwards, Martin Marshall and Martin Roland, (2020), CMAJ, 5