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How can digital approaches be used to monitor and improve medication adherence?

By Livia Adalbert Pharmacovigilance Consultant

Medication non-adherence – when patients don’t take their medicines as prescribed – is a global issue impacting health and economic outcomes for patients and society (S. F. Stewart et al., 2023). The World Health Organisation (WHO) estimated that around 50% of medicines prescribed for chronic conditions (e.g. hypertension, asthma and diabetes) are not taken as advised (S. De Geest and E. Sabate, 2003), and low adherence rates result in 200,000 premature deaths in Europe, each year (Rabia Khan and Karolina Socha-Dietrich, 2018).

Why does non-adherence matter?

Non-adherence to medicines is an unmet medical challenge that is scarcely on the radar of most prescribing physicians. A recent communication commented that unlike better-known causes of death such as heart attack or cancer, medication nonadherence is usually in­visible to patients, their families, and the medical profession (F. Kleinsinger, 2018) as it is tricky to recognise or monitor.  However, medication non-adherence puts a massive financial burden on healthcare systems in addition to the missed opportunity for health gain for the patients (S. F. Stewart, Z. Moon and R. Horne, 2023). For example, Trueman et al (2010) reported that non-adherent patients show a higher likelihood of hospitalisation in addition to the costs associated with unused medications (over £300 million each year in the UK alone).

Stewart et al (2023) stated that ‘the implicit assumption behind adherence interventions is that adherence improves patient outcomes’. Provided that the prescription was evidence-based and appropriate for the patient, then higher adherence rates will translate to greater therapeutic benefit (Haynes et al., 2002, Rob Horne et al., 2005).

Understanding and managing non-adherence

Various patient-centred frameworks have been developed for measuring and interpreting non-adherence and for designing interventions. The Perceptions and Practicalities Approach (PaPA) developed by Horne is a well-known example. It offers a pragmatic framework that focuses on the interaction between a patient and their treatment to help understand the factors affecting adherence and the development of interventions, in line with the NICE medicines adherence guidelines (Nunes et al 2009).

The PaPA model is based on health psychology theory and research and describes the ‘core’ elements that underlie adherence that need to be taken into account and addressed. It distinguishes between intentional and unintentional non-adherence. Intentional non-adherence refers to a deliberate decision to not take medicine as prescribed, due to perceptual factors such as medication necessity beliefs, concerns and emotions. Unintentional non-adherence refers to practical constraints such as capacity and resource limitations (Horne 2001, Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D 2005). Although many intrinsic and external factors can impact adherence, they all operate through the patient’s motivation and ability to engage with the treatment. It is critical to understand how sociodemographic and environmental factors influence these factors (Horne et al 2019).

The Perceptions and Practicalities Approach (PaPA) developed by Horne (Horne et al 2019)

Adherence support interventions

Adherence support interventions can target several ‘levels’ (Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D 2005). These are the healthcare system (e.g. improving the opportunity to access medicines); patient-provider interactions (e.g. improving HCP-patient communication); and the patient (e.g. improving motivation and ability to adhere).

Targeting patient-level factors is usually the most effective in promoting adherence, particularly where it is tailored to address the specific perceptions (e.g. beliefs about illness and treatment) and practicalities (e.g. capability and resources) influencing patients’ motivation and ability to adhere (S. F. Stewart, Z. Moon and R. Horne, 2023).

Measuring non-adherence

Different self-reporting methods (validated questionnaires, interviews and medication diaries) to measure non-adherence are available that are simple and inexpensive. However, these contain elements of recall and self-presentational bias (S. F. Stewart, Z. Moon and R. Horne, 2023). Objective measures of adherence also exist, including direct observations of the patient taking a medication, detection of the drug in the bloodstream or urine, and electronic monitoring (S. F. Stewart, Z. Moon and R. Horne, 2023). Detecting drug concentration in the blood is often considered to be the most objective method. However, it is invasive and risky, and the pharmacokinetics of the drug and the administration route prescribed could lead to variations. Stewart et al also proposed a less invasive method using electronic monitors to count how many doses a patient takes. Electronic adherence monitoring is often regarded as the gold standard of adherence measurement due to its objectivity and data recording accuracy (A. H. Chan et al., 2013, A. H. Y. Chan et al., 2022, J. M. Foster et al., 2012) and because it can facilitate patient reminders for medication-taking and adherence feedback to patients.

Examples of advances in detection include wearable devices and smart pills, such as the Ingestible Sensor System (U. Eisenberger et al., 2013), where microsensors are imbedded into oral pharmaceuticals. These devices are more reliable, though the acceptability data were mixed (Chan 2022). Hence, there is an increasing interest in combining techniques to include self-report measures of medication-taking behaviour, with objective forms of adherence such as electronic monitoring to achieve integrated and comprehensive adherence assessment (Dobbels et al 2010 and (A. H. Y. Chan et al., 2020). Patients and HCPs were reported to find the ‘adherence review and discussions the most beneficial parts of the intervention and “looked forward” to receiving their adherence data’ (H. Brath et al., 2013, T. M. Ruppar, 2010). One report highlighted that in Kaiser Permanente Northern California, a combination of approaches centred on the electronic health record improved medication adherence rates to above 80% (Kleisinger 2018).

The role of digital solutions in improving adherence

Digital solutions have been reported as improving intervention sustainability through automation and reduction of resources needed for implementation (Chan et al 2013). A recent study with 329 participants concluded that personalised adherence support using a digital algorithm can support patients overcome perceptual factors (concerns about treatment necessity and medication concerns) and barriers to adherence (Chapman et al 2020). The online intervention contained educational messages personalised to address beliefs about inflammatory bowel disease (IBD), maintenance treatment and also gave advice on overcoming practical difficulties with taking regular medication (Chapman et al 2020). In a systematic review and meta-analysis with chronic conditions, (A. H. Y. Chan, H. Foot, C. J. Pearce, R. Horne, J. M. Foster and J. Harrison, 2022) concluded that ‘patients receiving an electronic adherence monitoring intervention had significantly better adherence than those who did not’; however, ‘electronic adherence monitoring device by itself, without reminders or healthcare provider’s input did not improve adherence’. Comprehensive training was identified as a factor to consider in increasing intervention and device acceptability.

Conclusion and next steps

Non-adherence to medication regimes is an important and overlooked element of public health. There are many frameworks and approaches already available for understanding and reducing non-adherence. Digital methods of communicating information and gathering and analysing data can offer further opportunities for healthcare providers and administrators.

The pharmaceutical industry may have a role to play in supporting the development of these possible approaches, and linking them to drug safety and Patient Support Programmes. If you’d like to explore the opportunities for working in this area, do contact us.


Brath, H.; J. Morak; T. Kastenbauer; R. Modre-Osprian; H. Strohner-Kastenbauer; M. Schwarz; W. Kort and G. Schreier. 2013. “Mobile Health (Mhealth) Based Medication Adherence Measurement – a Pilot Trial Using Electronic Blisters in Diabetes Patients.” Br J Clin Pharmacol, 76 Suppl 1(Suppl 1), 47-55.

Chan, A. H.; H. K. Reddel; A. Apter; M. Eakin; K. Riekert and J. M. Foster. 2013. “Adherence Monitoring and E-Health: How Clinicians and Researchers Can Use Technology to Promote Inhaler Adherence for Asthma.” J Allergy Clin Immunol Pract, 1(5), 446-54.

Chan, A. H. Y.; H. Foot; C. J. Pearce; R. Horne; J. M. Foster and J. Harrison. 2022. “Effect of Electronic Adherence Monitoring on Adherence and Outcomes in Chronic Conditions: A Systematic Review and Meta-Analysis.” PLoS One, 17(3), e0265715.

Chan, A. H. Y.; R. Horne; M. Hankins and C. Chisari. 2020. “The Medication Adherence Report Scale: A Measurement Tool for Eliciting Patients’ Reports of Nonadherence.” Br J Clin Pharmacol, 86(7), 1281-88.

De Geest, S. and E. Sabate. 2003. “Adherence to Long-Term Therapies: Evidence for Action.” Eur J Cardiovasc Nurs, 2(4), 323.

Eisenberger, U.; R. P. Wuthrich; A. Bock; P. Ambuhl; J. Steiger; A. Intondi; S. Kuranoff; T. Maier; D. Green; L. DiCarlo, et al. 2013. “Medication Adherence Assessment: High Accuracy of the New Ingestible Sensor System in Kidney Transplants.” Transplantation, 96(3), 245-50.

Foster, J. M.; L. Smith; T. Usherwood; S. M. Sawyer; C. S. Rand and H. K. Reddel. 2012. “The Reliability and Patient Acceptability of the Smarttrack Device: A New Electronic Monitor and Reminder Device for Metered Dose Inhalers.” J Asthma, 49(6), 657-62.

Haynes, R. B.; H. McDonald; A. X. Garg and P. Montague. 2002. “Interventions for Helping Patients to Follow Prescriptions for Medications.” Cochrane Database Syst Rev, (2), CD000011.

Horne, Rob; N. H. S. Service Delivery National Co-ordinating Centre for and Organisation. 2005. Concordance, Adherence and Compliance in Medicine Taking : Report for the National Co-Ordinating Centre for Nhs Service Delivery and Organisation R & D (Nccsdo). London: NCCSDO.

Khan, Rabia and Karolina Socha-Dietrich. 2018. “Investing in Medication Adherence Improves Health Outcomes and Health System Efficiency.”

Kleinsinger, F. 2018. “The Unmet Challenge of Medication Nonadherence.” Perm J, 22, 18-033.

Ruppar, T. M. 2010. “Randomized Pilot Study of a Behavioral Feedback Intervention to Improve Medication Adherence in Older Adults with Hypertension.” J Cardiovasc Nurs, 25(6), 470-9.

Stewart, S. F.; Z. Moon and R. Horne. 2023. “Medication Nonadherence: Health Impact, Prevalence, Correlates and Interventions.” Psychol Health, 38(6), 726-65.

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