Asset Details
Do you wish to reserve the book?
Understanding hospital activity and outcomes for people with multimorbidity using electronic health records
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Understanding hospital activity and outcomes for people with multimorbidity using electronic health records
Do you wish to request the book?
Understanding hospital activity and outcomes for people with multimorbidity using electronic health records
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Understanding hospital activity and outcomes for people with multimorbidity using electronic health records
2025
Overview
As the prevalence of multimorbidity grows, provision of effective healthcare is more challenging. Both multimorbidity and complexity in healthcare delivery may be associated with worse outcomes. We studied consecutive, unique emergency non-surgical hospitalisations for patients over 50 years old to three hospitals in Scotland, UK between 2016 and 2024 using linked primary care and hospital records to define multimorbidity (2 + long-term conditions), and timestamped hospital electronic health record (EHR) contacts with nursing and rehabilitation providers to describe intensity of inpatient care. The primary outcome was emergency hospital readmission within 30 days of discharge, analysed using multivariable logistic regression. Across 98,242 consecutive admissions, 84% of the study population had multimorbidity, 50% had 4 + long-term conditions, and 37% had both physical and mental health conditions. Both higher condition count and contacts (nursing and rehabilitation) were independently associated with the primary outcome in fully adjusted models (example adjusted odds ratio [aOR] 1.62, 95% CI 1.52 to 1.73 for 4 + conditions compared to no multimorbidity,
p
< 0.001; aOR 1.35, 95% CI 1.28 to 1.42 for > 8 nursing contacts compared to 1–3,
p
< 0.001). While multimorbidity was associated with longer hospital stays with more nursing and rehabilitation contacts, the distribution of contacts and activity did not differ by multimorbidity or subsequent emergency readmission status. Higher count multimorbidity was associated with an increased risk of readmission, but we observed uniformity in care despite differential outcomes across multimorbidity groups. This may suggest that EHR data-driven approaches could inform person-centred care and improve hospital resource allocation.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
