Improving adherence depends on identifying specific patient reasons for non-adherence, then choosing the right intervention(s) to address them. This is part one of a two-part post that explores how this can be achieved in everyday practice.
Some posts are easy to write. You get an idea – often sparked by a new piece of information – and away you go! This two-part post is different. It has taken research time and taken still more time to think through. Even now it’s a “work in progress”. However, I would like to share these early ideas with you, to get comments and feedback.
Firstly, let me lay out the key points on which these ideas are built. Also, as a general note, the term “reasons” is used below as a catch-all for any factor, barrier, reason, or cause that influences non-adherence.
- To be most effective, interventions for improving adherence must align with individual patient reasons for non-adherence
- The current, most comprehensive list of non-adherence reasons is so long (55 items) it’s difficult to use
- The five ‘Dimensions’ in this list reflect reason sources and don’t relate to solutions
- The literature currently does not offer any comprehensive guidance for aligning reasons with solutions
In short, there’s very little out there that offers healthcare providers (HCPs) practical guidance for aligning interventions to reasons. Developing such guidance can help HCPs choose the right interventions for improving adherence. Availability of such guidance can also be a big help to HCPs looking to set up or improve adherence-related processes in their day-to-day work.
Aggregating and Prioritizing Adherence Reasons
This posts focuses on reasons, with two main aims:
- To look for ways to simplify the current long list of reasons (eg, aggregation). We need a shorter list than 55!
- To look for hard data on the most common reasons for non-adherence (ie, prioritize). If we know the ‘top ten’, then we can check we’ve got good interventions to address them.
Web searches produced over 60 ‘hits’ for reasons influencing non-adherence. Of these, nine publications provided quantitative data. All sources were considered in developing the “aggregated reasons” list shown in the table below. A combined analysis of the eight hard data sources produced the “mean % impact” figures and ranking.
A list of the nine data studies appears at the foot of this post. If you have suggestions to add to this list of studies/surveys, please let me know!
Based on these analyses, here’s a ranked ‘top ten’ reasons for medication non-adherence:
|'Top Ten' Aggregated Reasons||Mean % Impact on Nonadherence|
OK, so you’ve probably noticed there are 11 items in the list! The reason for including the 11th is to offer an important comment. At first sight, the 8% figure for ‘Understanding/Knowledge’ looks low. Particularly if you consider that patient education is one of the most commonly used interventions for improving adherence (more about this in Part 2). Poor ‘Understanding/Knowledge’, though, is a key contributing factor to poor motivation, mistaken beliefs, and poor attitude. Combining all these reasons might easily make ‘Understanding/Knowledge’ the most common factor influencing adherence. However, interventions to address understanding, motivation, beliefs, and attitude will most likely be different. So for the list above, I’ve kept them separate.
Hope this makes sense?
If you would like to get a copy of how I arrived at the list and percentages above, send me an email request at: email@example.com. I’ll be happy to share with you the Excel spreadsheet file of my workings.
Improving Adherence – ‘Work in Progress’
So that’s the first part of this two-part post.
I’d appreciate your thoughts on the approach? Also what are your thoughts on the list above? Does it ‘look right’? Is it what you would have expected? Is anything ‘obvious’ missing? Please let me know. Any other comments welcomed too!
In part 2 of the post, I’ll focus more on the interventions side of the equation. Plus, I’ll look at matching up reasons to interventions.
Links to Source References for Quantitative Data
AARP Survey, 2004
Improving Medication Adherence in Older Adults
BCG/Harris Survey, 2002
Patient nonadherence: Tools for Combating Persistence and Compliance
HealthPrize Survey, 2013
Improving Adherence Requires Addressing Psychological Barriers
NCPA Survey, 2013
Adherence in America – A National Report Card
N Engl J Med Review, 2005
Adherence in Medication
Am J Pharm Benefits Study, 2013
Barriers to and Facilitators of Medication Adherence
JAMA Intern Med Study, 2013
Communication and Medication Adherence: The Diabetes Study of Northern California
United Health Survey, date uncertain
Adherence Barriers Survey
Medical Care Meta-analysis, 2009
Physician Communication and Patient Adherence to Treatment: A Meta-analysis