James, J; (2017) Design of a Domain Information Model for a Medication Profile to support Patient Care and Clinical Research. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Use of medicines is the commonest intervention in healthcare. Information about an individual’s medication use over their lifetime, managed as a coherent whole but presented appropriately for context, is central to providing good quality care. Considerable investment continues to be made in specifying the information structures underpinning electronic health systems to provide clinicians with patient information to support care provision, yet medication errors continue to occur at unacceptable rates. At the same time, the quantity of healthcare information - which includes medication information – is increasing, and there is growing interest in “secondary uses” of this, particularly to support clinical research. Unfortunately, for both primary and secondary uses, the requirements for the data elements that are needed for medication information are poorly specified, despite a variety of major national and international initiatives and effort. The process for population of those data elements with high quality, consistent, trustworthy information that can be presented to the use cases efficiently and clearly is even more poorly specified. By gathering requirements from processes within clinical research alongside the requirements from the processes of patient care, an integrated data element view of a patient’s medication use over their lifetime has been described; this is termed the patient’s Medication Profile. Examination of the care processes that provide the data to populate that integrated view elicits the method and rules for the realisation of the Medication Profile. These together are provided in a formally scoped fully specified information model which defines the data elements of the Medication Profile (the static model) and the processes and rules to instantiate it (the dynamic model). The Medication Profile, populated with data based on the rules and processes of the dynamic model, is evaluated against test scenarios to assess its success to support use cases from both clinical care and clinical research. This evaluation indicated that the model provided both sufficiency of information coverage and clarity in the information presented.

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