A community pharmacy text messaging intervention to support medication taking. Who does it work for, and in what circumstances?
Problem
Up to half of people with long-term conditions (LTCs) do not take their medicines as prescribed. Digital technology is often suggested for supporting medicines taking. However, the results of previous research are mixed. We have developed a new intervention using a combination of a community pharmacist consultation and automated text messaging to support medicines taking. This has been developed using peer-reviewed literature and focus groups with patients and healthcare professionals (GPs, pharmacists, nurses). The intervention is tailored to the individual using a questionnaire and delivers content for up to eight LTCs. In this study, we sought to develop a realist programme theory which would describe how our intervention may work, for whom and in what circumstances.
Approach
A prototype of the new intervention was delivered to patients, including a consultation with a pharmacist and two weeks of text messaging. The text messaging intervention makes use of a ‘persona’ called Alice. Diary-interviews were used to gather feedback from eight patients, recruited through a public, patient and carer involvement group. Patients kept a diary during the period of text messaging and follow-up semi-structured interviews were conducted. Interviews were audio recorded and transcribed verbatim for analysis. Transcripts were coded to identify the potential contexts, mechanisms and outcomes which may explain how our intervention may work using realist evaluation principles.
Findings
Participants recruited into the study allowed us to test the intervention for patients with asthma, chronic pain, depression, ischaemic heart disease, hypertension, and type 2 diabetes mellitus. The intervention seems to improve medication taking by ‘checking in’ with patients. Checking in is achieved using one-way messages which remind patients to take their medication and why their medicines are important. The intervention also checks that patients are OK using two-way text message monitoring of health (using home monitoring devices or symptom assessment) and medication taking. Contexts which were important to the text messaging mechanism included participants ‘accepting’ Alice as a vehicle to provide support and mobile phone use. The consultation with the pharmacist worked to ensure that patients knew what their medicines were for, how to take their medication, and lay a foundation for the communication with Alice. The intervention seemed particularly helpful for patients with high treatment burden.
Consequences
This study allowed us to build an initial realist programme theory for how our new intervention may work and some of our findings may be transferable to other text messaging interventions for health. There are few digital interventions which have accounted for multimorbidity, but our programme theory suggests that this may be a population which particularly benefits. Our findings will be used to plan future evaluations and ultimately recommendations for when to use this intervention to support medication taking.