A new national dataset developed in Scotland is set to transform how researchers, clinicians, and health policymakers understand the use of specialist medicines delivered directly to patients’ homes, including medicines safety surveillance and real-world evidence generation. The Homecare Medicines (HCM) dataset, created and maintained by Public Health Scotland, provides the first comprehensive national picture of homecare medicine supply and has now been profiled in the International Journal of Population Data Science (IJPDS).

Homecare services allow patients with long-term conditions—such as rheumatoid arthritis, or immune-mediated diseases—to receive specialist medicines at home instead of attending hospital for regular treatment. These services have grown rapidly in recent years and now account for around 30% of secondary care medicine spending in Scotland. Until recently, however, data on medicines supplied this way were fragmented and held locally, making it difficult to evaluate access, patient outcomes, or national spending patterns.

The HCM dataset was established during the COVID-19 pandemic to identify clinically vulnerable patients for vaccine prioritisation. It has since evolved into a permanent national resource, supporting research, planning, and health intelligence. The dataset contains more than 1.3 million medicine supply records for over 41,000 patients from 2019 onwards, covering approximately 98% of the Scottish homecare market. Each anonymised record includes detailed information about the medicine supplied, who received it, and when.

One of the most powerful features of the HCM dataset is its ability to link to other national health datasets through a unique patient identifier. This creates a powerful platform for medicine safety surveillance, enabling researchers and policymakers to examine real-world treatment pathways, monitor patient outcomes, identify inequalities in access, and detect early safety concerns or unintended harms. As a result, Scotland now has a unique ability to study real-world medicine use and its impact across the healthcare system, supporting improvements in safety, access, and efficiency.

The dataset is already generating insights, particularly in areas where real-world data is critical for regulatory, clinical, and policy purposes—such as the uptake and safe use of biologic and immunomodulatory therapies. Researchers believe this resource will play a key future role in real-world evidence generation, saftey surveillance, value-based healthcare, and population health research. With ongoing developments to improve indication capture and integration with wider prescribing systems, the resource will continue to strengthen Scotland’s medicines safety intelligence ecosystem.

“The Homecare Medicines dataset is a significant step forward for national medicines safety surveillance,” said Professor Kurdi, lead author of the publication. “It gives Scotland the capability to track the real-world impact of specialist medicines, identify safety concerns early, and support fair and evidence-based decision-making to improve patient outcomes.”

Approved researchers can access the HCM dataset through Public Health Scotland’s Trusted Research Environment, ensuring secure and ethical use of data for public benefit. This new national resource places Scotland at the forefront of real-world data use for specialist medicines and offers a valuable model for other countries seeking to improve transparency, safety, and equity in high-cost medicines.

 

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Professor Amanj Kurdi, Strathclyde Institute of Pharacy and Biomedical Sciences, University of Strathclyde, and Public Health Scotland, UK

Kurdi, A., Stobo, L., Millar, M., Clayton , W., Merrick , A., McTaggart, S., Mueller, T. and Bennie , M. (2023) “Data Resource Profile: Public Health Scotland (PHS) Homecare Medicines Dataset: A National Resource for Linked Prescribing Data for Specialist Medicines Prescribed in Hospital Outpatient setting and Supplied Via Homecare Services”, International Journal of Population Data Science, 8(6). doi: 10.23889/ijpds.v8i6.3139.