Back

Multimorbidity and Medication Order Patterns in Skilled Nursing Facilities: A Real-World Evidence Study

Ashraf, H.; Tsasis, P.; Mathers, K. E.; DiSanto, L.; Wong, A.; Sharma, D.; Heffernan, J. M.; Wagner, B.; Saumur, T. M.

2026-09-23 geriatric medicine
10.64898/2026.09.22.26363593 medRxiv
Show abstract

BackgroundMultimorbidity is common among U.S. skilled nursing facilities (SNFs) residents and complicates pharmacologic management, yet real-world evidence on treatment patterns in this population remains limited. This study evaluated medication order rates and identified resident- and facility-level factors among SNF residents with multimorbidity. MethodsRetrospective, observational study using electronic health record (EHR) data from PointClickCares Life Sciences database. Participants were 728,222 residents active in a U.S. SNF on April 30, 2025 with at least one documented diagnosis of hypertension, hyperlipidaemia, type 2 diabetes (T2D), depression, or Alzheimers disease and related dementias (ADRD). The outcome was presence of guideline-recommended medication order for each condition, modelled with modified Poisson regression to estimate adjusted prevalence risk ratios (RRs) and 95% confidence intervals. ResultsMedication order rates were 79% for ADRD, 79.1% for T2D, 87.7% for hypertension, 83.3% for hyperlipidaemia, and 90.8% for depression. Rates varied across comorbidity combinations: ADRD was associated with lower medication order prevalence, while cardiometabolic multimorbidity profiles associated with higher prevalence. Black/African American identity had the lowest likelihoods of a medication order for 3 of 5 conditions (RRs of 0.93 to 0.92), while having hypertension or hyperlipidaemia medication order was associated with higher likelihood of having orders for 3 of remaining 4 conditions (RRs of 1.02 to 1.19). ConclusionsMost SNF residents with multimorbidity had a medication order for common chronic conditions, although important variability and disparities remain. Differences by comorbidity profile and social context underscore the need for targeted strategies supporting equitable, integrated prescribing and person-centred care in SNFs.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.