Background
The WHO reported that medication adherence in patients with long-term conditions averages to 50% in developed countries.1 Based on the results of a 2017 US survey, roughly 40% of patients who are chronically ill were interested in using technology to assist them with medication, diagnosis, test results and managing their condition in their home environment.2 National Health Service (NHS) England policies published over the past decade such as Personalised Health and Care 2020 (PHC2020)3 and the Five Year Forward View4 specify that the NHS needs to use information and communication technologies (ICT) to reduce healthcare costs and improve healthcare outcomes. The most recent NHS policy document, The NHS Long Term Plan,5 focuses on ‘personalised healthcare’ to improve quality of life and public health and aspires that over the next 5 years with the introduction of further ICT, outpatient visits will drop by one-third. The aim is that people with long-term conditions such as diabetes, respiratory or renal problems will have further access to technology designed to help them manage their condition, for example, continuous glucose monitoring for all pregnant patients with type 1 diabetes.
Recent literature suggests that there is limited evidence that the use of health applications can improve patient adherence to prescribed medication, and the quality of the evidence is often questionable.6–8 The impact of ICT on cost, quality and safety of healthcare remains questionable, based on the conflicting evidence of more ‘optimistic’9–11 versus more cautious studies.6
Medication adherence is ‘the extent to which a person’s behaviour—taking medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a healthcare provider’12 and is considered a well-known challenge in healthcare,13 acknowledged by PHC2020.3 The ABC taxonomy14 is selected as the conceptual framework for medication adherence in this study, since it is well cited and it is considered more comprehensive than the WHO Five interacting dimensions that affect adherence,12 which will still inform this study as a secondary source.
It is widely suggested in the literature that medication adherence should be measured in conjunction with quality of life in order to define whether a patient’s health is better.15 16 Health-related quality of life (HRQoL) is the ‘subjective assessment of the impact of disease and treatment across the physical, psychological, social and somatic domains of functioning and well-being’.13 Literature also suggests that patient personality traits often affect medication adherence.17 18 The Five-Factor Model is an established taxonomy of personality traits.19 According to it, personality can be described in terms of five basic personality trait dimensions: agreeableness, conscientiousness, extraversion, neuroticism and openness to experience.20 21
The NHS standards for commissioning personal health records (PHR)22 provide guidance on good practice for the development of PHRs in England, but they do not provide enough evidence on how the PHR standards impact public health, nor on what design features should a PHR include nor evidence on how these features impact health outcomes. PHRs are ‘online systems that include collections of patients’ healthcare and medical data, which utilise health informatics standards to enable patients to share, organize and manage these data according to their own views’.7 Some of the many claimed benefits of PHRs are the ability of PHR to improve patient outcomes, decrease healthcare costs, allow patients the ability to self-manage their health, empower patients and improve medication adherence.23–25
Aim and objectives
The aim of this study is to determine how best computerised PHR features should be designed to help patients get the full benefit of their prescribed medication. It could be hypothesised that health and information technology literacy may be important factors in identifying these essential PHR design features. Health literacy is ‘the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions’.26 The Health Education England defines digital literacy as ‘the capabilities that fit someone for living, learning, working, participating and thriving in a digital society’.27
Primary objective
Identify the essential design features of PHRs to improve medication adherence in adults with long-term conditions.
Secondary objectives
Identify how patient and disease-specific factors mediate the impact of PHRs.
Patient specific: personality traits and sociodemographics.
Disease specific: progression, severity, intervention type, polypharmacy.
Develop a theoretical model that describes the interaction between the PHR design features and the patient and disease-specific factors, to help determine what works for whom in what circumstances.
