Tools for the assessment of adherence
- Combining measures and survey tools with objective measures can help to characterize patient health behaviors, with the potential to increase adherence
Quantitative methods can be used to characterize health behavior
Measures and survey tools are useful mechanisms to gain an understanding of health behavior, thereby providing effective support to patients in managing their own conditions. Surveys and questionnaires are simple to implement at the point of care and acceptable to patients. Outputs can then be used by physicians to personalize care to individual patients.1
These methods have varying levels of complexity. Simpler, self-reporting tools may only assess the extent or type of non-adherence (e.g. the Medication Activation Questionnaire2 or Medication Adherence Scale3) whereas others may dig deeper to assess the reasons behind non-adherence.4 The Patient Activation Measure is a reliable tool used to assess a patient’s capacity to manage their own health, including adherence.5,6
Adherence to pancreatic enzyme replacement therapy has been assessed in a standalone patient-completed questionnaire, which found that overall compliance with PERT administration guidelines was low (50%).7
Medication Adherence Questionnaire (MAQ)
The MAQ (also known as the 4-item Morisky Medication Adherence Scale [MMAS-4] and Morisky Scale) is the most common adherence scale. It is a self-reported questionnaire, designed to help physicians to understand their patient’s beliefs and concerns, how well they are adhering, and provide feedback and support. It is simple to use, and has been validated in many disease areas.2
Questions for patients with PEI disease might include:
- Have you ever stopped taking your medication without telling your doctor, because you felt worse when you took it?
- When you travel or leave home, do you sometimes forget to bring along your medication?
The answers to these questions can help physicians to understand their patients’ behavior and help to inform their practices.
A modified version (8-Question) has been used as part of an investigation into the impact of the medication beliefs, illness perceptions and quality of life in people with decompensated cirrhosis. It allowed patients to be assigned into ‘High’, ‘Medium’ or ‘Low’ adherence groups, and found that self-reported medication non-adherence in ambulatory patients was prevalent (over 1/5 categorized as ‘Low’, and more than 1/3 as ‘Medium’).8 A similar low rate of adherence has been shown in patients awaiting liver transplantation using this tool; total number of medications and regimen complexity were shown to strongly correlate with adherence.9 A pilot study in patients with cirrhosis, in part using this tool, also suggested that there is significant discrepancy between patient reporting of medications they were taking and their medical records.10
Medication Adherence Report Scale (MARS)
The MARS is a self-reporting adherence scale that assesses both intentional and non-intentional adherence, consisting of either 5 or 10 items. It places patients on an ‘adherence dimension’ rather than simply describing them as adherent or non-adherent via questions with closed answers (yes/no, high/low). The items are deliberately phrased to normalize adherence, avoiding passing judgement or inflaming the situation.3
Patient Activation Measure (PAM)
The PAM has been used to tailor a range of interventions for patients with chronic disease.11 It aims to assess ‘patient self-reported knowledge, skill and confidence for self-management of one’s health or chronic condition based on a scale between 0 and 100, and categorizing patients into four developmental levels:11
- Patients may be passive and feel overwhelmed about managing their health. They may be unprepared to take an active role in their own health.
- Patients may lack the knowledge and confidence to self-manage their health.
- Patients are beginning to take action, but may lack the confidence and skill to support and sustain these behaviors.
- Patients have adopted many behaviors to support their health, but may be unable to maintain them when faced with adversity or life stressors.
Higher activation stages indicate that the patient is more engaged with a behavior. A link between higher patient activation and adherence has been established, and it is therefore a useful target for behavior change. Physicians are an important source of support in this process; emotionally supportive providers who make themselves available to their patients and are able to motivate them to self-manage tend to have higher levels of patient activation.6
Limitations of existing measures
A key limitation of existing measures is that they are not designed to differentiate between the extent to which doses are missed, and the reasons that they are. Recently, tools have been developed that measure these separately, such as utilizing both cognitive interviews (to measure extent) and the Medication Adherence Self-Efficacy Scale (to measure reasons).4
Screeners and digital questionnaires
It may be beneficial to use ‘screeners’ that allow patients to indicate whether they are struggling with their adherence without asking directly. Patients may be reluctant to admit to issues if they are asked in a way that they perceive to be judgmental or threatening.12
The ‘Making Medicines Work for You’ screener is based on the COM-B framework and includes items which assess Capability, Opportunity and Motivation. It allows patients to indicate whether they are experiencing any one or more of seven problems with their medicines. A pilot study of patients with diabetes suggested that this screener is capable of identifying a range of medicines-related issues, with 88% of the sample indicating at least one issue, in contrast to the relatively small proportion of patients who typically disclose that they are non-adherent.12
An interactive digital questionnaire based on the SPUR framework (Social, Psychological, Usage, Rational) has been developed that describes the patient’s behavioral risks of non-adherence and the factors that influence this. The digital format may allow for more flexible support from physicians, whilst making fewer demands on their time.13
Objective measures for measuring medication adherence
There are also a number of objective methods that can demonstrate whether the patient is taking their medication. Pharmacokinetic models show the dose that the patient has taken,14 and electronic pill bottles that record opening of the pill bottle electronically can be used.15 Prescription data in electronic medical records (EMRs) and pharmacy claims data can show whether prescriptions are appropriately filled.16
- Culig J, Leppée M. From Morisky to Hill-bone; self-reports scales for measuring adherence to medication. Coll Antropol. 2014;38(1):55–62.
- Lam WY, Fresco P. Medication Adherence Measures: An Overview. BioMed Res Int. 2015;2015:217047.
- Chan AHY, Horne R, Hankins M, Chisari C. The Medication Adherence Report Scale: A measurement tool for eliciting patients’ reports of nonadherence. Br J Clin Pharmacol. 2020;86(7):1281–1288.
- Voils CI, MacIejewski ML, Hoyle RH, et al. Initial validation of a self-report measure of the extent of and reasons for medication nonadherence. Med Care. 2012;50(12):1013–1019.
- Kinney RL, Lemon SC, Person SD, Pagoto SL, Saczynski JS. The association between patient activation and medication adherence, hospitalization, and emergency room utilization in patients with chronic illnesses: A systematic review. Patient Educ Couns. 2015;98(5):545–552.
- Graffigna G, Barello S, Bonanomi A. The role of Patient Health Engagement model (PHE-model) in affecting patient activation and medication adherence: A structural equation model. PLoS ONE. 2017;12(6):e0179865.
- Barkin JA, Westermann A, Hoos W, et al. Frequency of Appropriate Use of Pancreatic Enzyme Replacement Therapy and Symptomatic Response in Pancreatic Cancer Patients. Pancreas. 2019;48(6):780–786.
- Hayward KL, Valery PC, Martin JH, et al. Medication beliefs predict medication adherence in ambulatory patients with decompensated cirrhosis. World J Gastroenterol. 2017;23(40):7321–7331.
- Kuo SZ, Haftek M, Lai JC. Factors Associated with Medication Non-adherence in Patients with End-Stage Liver Disease. Dig Dis Sci. 2017;62(2):543–549.
- Hayward KL, Valery PC, Cottrell WN, et al. Prevalence of medication discrepancies in patients with cirrhosis: A pilot study. BMC Gastroenterol. 2016;16(1):114.
- Kearns R, Harris-Roxas B, McDonald J, Song HJ, Dennis S, Harris M. Implementing the Patient Activation Measure (PAM) in clinical settings for patients with chronic conditions: a scoping review. Integr Healthc J. 2020;2(1):e000032.
- Weinman J, Ali I, Hodgkinson A, Canfield M, Jackson C. Pilot testing of a brief pre-consultation screener for improving the identification and discussion of medication adherence in routine consultations. Patient Prefer Adherence. 2019;13:1895–1898.
- Dolgin K. The SPUR model: A framework for considering patient behavior. Patient Prefer Adherence. 2020;14:97–105.
- Özdemir V, Endrenyi L. A New Approach to Measure Adherence to Medicines Using Biomarkers and Sensors. OMICS. 2019;23(7):334–337.
- van Heuckelum M, van den Ende CHM, Houterman AEJ, Heemskerk CPM, van Dulmen S, van den Bemt BJF. The effect of electronic monitoring feedback on medication adherence and clinical outcomes: A systematic review. PLoS ONE. 2017;12(10):e0185453.
- Park Y, Yang H, Das AK, Yuen-Reed G. Prescription fill rates for acute and chronic medications in claims-EMR linked data. Medicine (Baltimore). 2018;97(44):e13110.