Acceptable medication non-adherence: A crowdsourcing study among French physicians for commonly prescribed medications
Acceptable medication non-adherence: A crowdsourcing study among French physicians for commonly prescribed medications
Ste´phanie SidorkiewiczID 0 1
Viet-Thi TranID 0 1
Philippe Ravaud 0 1
0 1 Department of General Medicine, Paris Descartes University , Paris, France, 2 METHODS Team , Centre of Research in Epidemiology and Statistics Sorbonne Paris Cite ́ (CRESS), INSERM, UMR 1153, Paris, France, 3 Cochrane France , Paris , France , 4 Department of Epidemiology, Mailman School of Public Health, Columbia University , New York City, New York , United States of America
1 Editor: Lamberto Manzoli, Universita degli Studi di Ferrara , ITALY
Achieving good medication adherence is a major challenge for patients with chronic conditions.
Our study aimed to assess the Threshold for Unacceptable Risk of Non-adherence (TURN),
defined as the threshold at which physicians consider the health risks incurred by patients due to
medication non-adherence unacceptable, for the most commonly prescribed drugs in France.
We conducted an online study using a crowdsourcing approach among French general
practitioners and specialists from September 2016 to August 2017. Physicians assessed
the TURN for various levels of missed doses by evaluating a series of randomly presented
clinical vignettes, each presenting a given medication with a given therapeutic indication.
For each “drug-indication group” (i.e., all drugs from the same pharmacological class with a
similar therapeutic indication): 1) we described the distribution of physicians’ assessments,
2) we provided a summary estimate of the TURN, defined as the frequency of missed doses
above which 75% of the physicians’ assessments were located; 3) we computed the number
of pill boxes reimbursed in France in 2016 to put our results into context.
We collected a total of 5365 assessments from 544 physicians, each of whom evaluated a
random sample among 528 distinct clinical vignettes. Estimates of the TURN varied widely
across drug-indication groups, ranging from risk considered unacceptable with 1 daily dose
missed per month (e.g., insulin for diabetes) to risk always considered acceptable (e.g.,
anti-dementia drugs). Drugs with an estimated TURN of over one missing daily dose per
week represented 44.9% of the prescription volume of the medications assessed in our
According to physicians, the impact of non-adherence may vary greatly. Patient-physician
discussions on the variable consequences of non-adherence could lead to a paradigm shift
by seeking to reach “optimal adherence” depending on drugs rather than unrealistic “perfect
adherence” to all drugs.
Medication adherence is defined as the extent to which a person’s behavior coincides with
medical advice and is often reported as a percentage of the prescribed doses of the medication
actually taken by the patient over a specified period . The association between medication
non-adherence and clinical outcomes is well described in the literature [1–4]. Adverse events
caused by imperfect medication adherence may range from minor symptoms to suboptimal
clinical benefit, poor control of the illness [5,6], emergence of treatment resistance [7,8] or
lifethreatening events . The seriousness of these adverse events depends on the drug and the
disease being treated and the magnitude of poor adherence. For example, in the
transplantation field, even a minor deviation of optimal adherence to immunosuppressive treatment can
lead to severe consequences . For patients with chronic conditions, a large number of
studies have found that only 50% to 60% of patients take their medications as prescribed [1,9,11]
despite numerous interventions available to improve medication-taking . This finding
suggests that for patients taking multiple medications, perfect drug adherence (all doses taken at
the correct time, during the whole life) may be unrealistic. Therefore, in clinical practice,
physicians seeing patients with various medication-taking behaviors must assess the degree to
which non-adherence is acceptable to achieve desired therapeutic effects [13,14], without
unnecessarily increasing the burden of treatment on patients .
Assessing a threshold of acceptable non-adherence for a large range of medications may
have direct implications on clinical practice. Indeed, it may help physicians prioritize their
interventions and assess at what point and for which medication they should strongly
encourage the patient to change their medication-taking behavior. However, accurately defining a
theoretical threshold may be difficult because it must account for the likelihood, clinical
consequences and time course of treatment failure . It may also depend on the drug of interest
and the medicine-taking behaviors of patients: periodically missing single doses, drug holidays
(sequentially multiple missed doses), schedule errors (variability in time of drug intake) or
extra doses [11,16,17]. To the best of our knowledge, the effect of medication non-adherence
behaviors is only known in very specific therapeutic fields [18,19]. In the literature, the
threshold usually used to define “good adherence” is a patient taking more than 80% of all prescribed
doses [1,20], but this arbitrary cut-off is commonly applied with no clinical rationale  and
likely corresponds more to a theoretical threshold for describing populations than to a
practical rule used by physicians in clinical practice.
An approach to explore this issue could be to consider the concept of drug “forgiveness”
[22,23], that is, the property of a drug, given as a repeated treatment, to forgive the omission of
one dose, or several doses in a row, without a loss of efficacy [16,24]. However, forgiveness
estimated by pharmacokinetic models  only allows to evaluate the short-term risk of adverse
events due to poor implementation of a given drug and does not take into account the severity
of the adverse event, or the long-term consequences (e.g., poor control of the illness or
development of treatment resistance).
In this study, we focused on physicians’ perspectives, who are at the front-line in caring for
patients with chronic treatments. They frequently face non-adherence situations, in which
they have to use their clinical experience to integrate the different factors involved (the risk of
an adverse event, the seriousness of the potential adverse event, the time course of treatment
failure , the disease being treated) to make clinical decisions. We therefore decided to
describe the threshold in terms of frequency of missed doses at which physicians consider the
health risks incurred by patients due to medication non-adherence unacceptable for a large
range of medications. Although medication adherence should not be reduced to an adherence
rate, we considered that this approach would be a first feasible and useful step to explore this
complex issue. We hypothesized that physicians’ estimates would not be in line with the 80%
threshold usually used in the literature but that on the contrary, they would vary widely among
the medications and the diseases.
Our study used a crowdsourcing approach by inviting physicians to assess, via the Internet, the
Threshold for Unacceptable Risk of Non-adherence (TURN) for the most commonly
prescribed medications in France. Physicians determined this threshold for various levels of
missed doses by evaluating a series of clinical vignettes, each presenting a given medication in
a given chronic indication.
Definition of the TURN
In this study, we proposed to focus on the new concept of TURN that we defined as the
threshold at which physicians consider the health risk incurred by patients due to medication
nonadherence unacceptable. For example, for a given medication assessed by a given physician, an
estimated threshold of 2 days per month would mean that the physician considered the risk
incurred due to non-adherence acceptable as long as patients missed 1 daily dose or less per
month. However, 2 daily doses missed per month or more would be unacceptable. Thus, the
lower the TURN for a given medication, the more unacceptable physicians consider the health
risk due to non-adherence.
Development of clinical vignettes to assess the TURN
We asked physicians to estimate the TURN for the most commonly prescribed medications in
France by using randomly presented clinical vignettes. Each vignette presented one
medication (selected according to the number of pill boxes reimbursed by the French national health
insurance system during the first 6 months of 2015) in one of its recommended therapeutic
chronic indications. The complete procedure of medication selection is described in S1 Fig.
For each vignette, physicians estimated the TURN by answering a question inspired from
studies describing the consequences of medication non-adherence [5,9,25–28] and methods of risk
communication and assessment [29–31]: “The patient tells you that he/she skips a daily dose of
this medication periodically. In your opinion, at what frequency of missing doses is the risk to
his/her health unacceptable?” Seven answers were proposed, ranging from 1 to 3 days per
month (i.e., risk considered unacceptable by physicians with 1 to 3 daily doses missed per
month), 1 to 3 days per week, and always acceptable regardless of the frequency. Two other
possible responses were “I do not know” and “Other response”. Respondents were also allowed
to write a free comment for each medication assessed. Most of the medications we selected
had once-daily dosing regimens, but we adapted the wording of the question to fit the
medications with other daily dosing regimens (e.g., 2 or 3 times daily).
A preliminary version of the clinical vignettes was pilot-tested with 4 physicians by using a
double interview method. The final question and answers are detailed in S1 Table.
Participants. Participants were physicians (general physicians or specialists). We
excluded specialists not seeing patients, pediatricians, medical students, residents, and
pharmacists. Participants were approached through university or hospital networks (in particular
the Socie´te´ de Formation The´rapeutique du Ge´ne´raliste–Recherche), congresses (French
National Congress of General Medicine and French National Congress of General Medicine
Teachers), and social media. Physicians who participated were encouraged to invite their
colleagues by a snowball sampling method .
Physicians were informed that the data analysis would respect confidentiality. This study
was not reviewed by an institutional review board (IRB) because, as a non-interventional study
with physicians about their expertise, it did not fall within the scope of French ethics
committees. The study has been declared to the French Data Protection Authority (Commission
Nationale Informatique et Liberte´s, CNIL, identification no. 1980063), as required in France.
No formal consent was required for this type of study according to French law. Physicians
were invited to participate after receiving information about the study on the home page of the
study website, and were able to download the study protocol via a dedicated link. Participation
by logging into the platform was voluntary and anonymous.
Crowdsourcing procedure. Eligible physicians were invited to log into an Internet
platform (http://clinicalepidemio.fr/mapp/), where they provided basic demographic information
(age and sex) and professional information (medical specialty, ambulatory or hospital practice
setting). Then, they assessed as many clinical vignettes as they wanted (they were allowed to
skip clinical vignettes for which they did not feel comfortable to assess the TURN). We used
algorithms to 1) prevent physicians from assessing only medications from the same
pharmacological drug class, and 2) increase the chance that physicians would be evaluating medications
from their own specialty first.
Data are presented with numbers (%) for categorical variables and means (SD) for continuous
variables. We used complete-case analysis to deal with missing data. All statistical analyses
involved the use of R v3.2.2 (http://www.r-project.org).
Drug-indication groups. To present our results at an aggregate level, we grouped all
drugs from the same pharmacological class in a similar therapeutic indication under a
“drugindication group” according to the 3rd level of the WHO Anatomical Therapeutic Chemical
(ATC) classification . Two authors (SS and VT-T) grouped therapeutic indications with
the help of specialists in case of uncertainty.
Estimation of the TURN for each drug-indication group. For each drug-indication
group: 1) we plotted the distribution of all physicians’ estimates (Fig 1); 2) we provided a
summary estimate of the TURN, that we defined as the frequency of missed doses above
which 75% of physicians considered that the health risk incurred by the patients would
become unacceptable. For example, if 75% or more physicians considered that missing 2
daily doses or more per month for a given drug-indication group was unacceptable risk, the
resulting summary TURN for this drug-indication group was “2 days per month”. No
previous data were available about which summary statistic would be clinically relevant to
describe the TURN for each drug-indication group. We therefore decided to present our
results using a 75% cut-off, based on previous studies assessing Patient Acceptable
Fig 1. Distribution of physicians’ estimates: Threshold for Unacceptable Risk of Non-Adherence for 70 drug-indication groups. Each horizontal bar represents the
distribution (in percentage) of physicians’ estimates for a given drug-indication group. TURN corresponds to the frequency of missing doses above which 75% of
physicians’ estimates were located (vertical dashed line). n corresponds to the number of physicians’ assessments for each drug-indication group. For sake of clarity, we
plotted 70 drug-indication groups corresponding to 90% of total prescription volume of the medications assessed in the study. All the 112 drug-indication groups are
plotted in S2 Fig. Abbreviations: ACE: angiotensin-converting enzyme, ARBs: angiotensin receptor blockers, CCBs: calcium channel blockers; COPD: Chronic
Obstructive Pulmonary Disease; GORD: gastro-oesophageal reflux diseases; HBP: high blood pressure; NSAIDs: non-steroidal anti-inflammatory drugs, MI: myocardial
Symptom States  and by adopting a conservative approach for health risk assessment.
We performed sensitivity analyses with other cutoffs (more permissive cutoffs: 50%, 60%;
and more conservative cutoffs: 80% and 90%).
Estimation of the proportion of prescription volume for each drug-indication group.
For each drug-indication group, we computed the number of pill boxes reimbursed in 2016
according to the French national health insurance medication database by summing the
number of pill boxes for all medications belonging to the given group. We presented our results in
a figure that allowed for comparing prescription volumes among the different drug-indication
groups and their respective summary TURN: each drug-indication group was presented as a
rectangle with color and area size by TURN and prescription volume, respectively (Fig 2).
A total of 544 physicians participated in the study from September 2016 to August 2017. Their
mean age was 39.8 years (SD 12.5) and 198 (36.4%) were male. The participants were mainly
general physicians (433, 79.6%); 373 (68.6%) worked in ambulatory care and 115 (21.1%) in
hospitals. Other characteristics are detailed in Table 1.
A total of 5558 vignettes were submitted to physicians for evaluation, corresponding to 528
distinct clinical vignettes (that is, 528 medications for a given therapeutic indication selected
during the process of drug selection detailed in S1 Fig). We collected a total of 5365
assessments (response rate 96.5%) from the 544 physicians, each of whom evaluated a random
sample among the 528 vignettes. We grouped all the medications in 124 drug-indication groups.
We excluded from the analysis 12 drug-indication groups for which we collected fewer than 10
answers. As a result, we analyzed a total of 112 drug-indication groups. For each of these 112
groups, the mean number of physicians’ assessments was 47.2 (SD 31.5). We also collected 825
free comments from physicians.
Estimation of the TURN by physicians
We found that the TURN, as assessed by physicians, varied widely across the different
drugindication groups (see Figs 1 and S2). Summary estimates of the TURN ranged from “1 daily
dose missed per month” unacceptable for 22 (19.6%) drug-indication groups, to “always
acceptable” for 10 (8.9%) groups. The results for other cut-offs are detailed in S2 Table. The
three drug-indication groups with the highest TURNs were progestogens and estrogens in
combination for menopause, anti-rheumatic products for osteoarthrosis, and anti-dementia
drugs (S2 Fig). The three drug-indication groups with the lowest TURNs were
immunosuppressants for preventing graft rejection, hormonal contraceptives for systemic use and
corticosteroids for preventing graft rejection (S2 Fig).
Fig 2. Threshold for Unacceptable Risk of Non-Adherence (TURN) and prescription volume for 112 drug-indication groups. TURN corresponds to the frequency
of missing doses above which 75% of physicians’ estimates were located for each drug-indication group. Results with alternative cut-offs are detailed in S2 Table. Each
drug-indication group is plotted as a rectangle: 1) rectangle color corresponds to the TURN ; 2) rectangle area size is proportional to the number of pill boxes reimbursed
in 2016 in France (according to the French national health insurance database). We summed the number of pill boxes for the medications belonging to each group. In
case of several therapeutic indications for a same medication, we divided the number of pill boxes by the number of indications. Abbreviations: ACE:
angiotensinconverting enzyme, ARBs: angiotensin receptor blockers, CCBs: calcium channel blockers; COPD: Chronic Obstructive Pulmonary Disease; GORD: gastro-oesophageal
reflux diseases; HBP: high blood pressure; NSAIDs: non-steroidal anti-inflammatory drugs, MI: myocardial infarction.
Fig 2 plots all drug-indication groups with their corresponding summary TURN (rectangle
color) and prescription volume (rectangle area size). Overall, 21.0% (in proportion of
reimbursed pill boxes) of the medications assessed corresponded to drugs with the lowest TURN
(i.e., risk of non-adherence considered unacceptable with 1 daily dose missed per month).
Similarly, 44.9% of the medications assessed corresponded to drugs with moderate or high
TURN (i.e., risk of non-adherence considered unacceptable with more than 1 missed daily
dose per week).
In this study, we developed the new concept of “Threshold for Unacceptable Risk of
Nonadherence” and crowdsourced it from 544 physicians who provided a total 5365 assessments
for different drugs in different indications. We found great heterogeneity among physicians in
estimating the TURN among the drug classes, with medications for which the estimated
TURN was high, such as anti-dementia drugs or dermatological drugs, as compared with
medications for which the estimated TURN was low, such as drugs for graft rejection or
antiretroviral therapy for HIV infection. The drugs with higher TURNs were mainly those that
physicians considered had symptomatic therapeutic indication or poor perceived efficacy. For
some of these drugs, physicians stressed the importance of the patient’s decision: “the patient’s
discomfort will guide medication-taking” (anti-acne preparation); “the patient is empowered to
make his own decision about how to take this medication according to his symptoms” (drug used
for benign prostatic hypertrophy). Some physicians even suggested stopping certain drugs
with poor perceived benefit-risk ratio: “I never initiate this treatment, which seems little efficient
and with a bad safety profile. I advise the patient to stop it” (anti-dementia drug). In contrast,
the drugs with lower TURNs were mainly those with harmful consequences of non-adherence
or drugs for which physicians showed accurate knowledge of pharmacokinetics: “a 12-hour
delay exposes the patient to an unwanted pregnancy” (hormonal contraceptive) and “the
halflife of this drug is short and puts the patient at risk of seizure” (antiepileptic).
Strengths and limitations of the study
To the best of our knowledge, this is the first study conducted among physicians about the
TURN at a nation-wide level. Crowdsourcing methods allowed us to involve physicians in
estimating the TURN for a large amount of different medications among most commonly
prescribed medications in France. However, our study has some limitations. First, the physicians
were not representative of all French physicians. Second, we presented our results at an
aggregate level by pooling medications in drug-indication groups, however, within some groups,
the TURN may differ depending on the molecule (e.g., the pharmacokinetic profiles of
different vitamin K antagonists are not equivalent). Third, our clinical vignettes were
theoretical and did not take into account the patient clinical context, the severity of patients’
conditions or concomitant prescribed drugs, which may explain the variability we found among
physicians’ answers for some drug-indication groups (e.g., cardiovascular or antihypertensive
drugs). However, for some drug-indication groups, physicians agreed on a TURN with a good
consistency across their answers (e.g., drugs against graft rejection). Fourth, our approach was
descriptive and does not allow to use the data we collected for future TURN calculation or
definition. But the purpose of our study was to explore the physicians’ perspectives about the new
concept of the TURN rather than to provide guidelines. Potential gaps with other perspectives
(especially patients’) could be interesting to explore in future studies.
Strengths and limitations in relation to other studies
In the literature, adherence is often described as a ratio of doses taken to the total number of
prescribed doses. However, the usual 80% threshold used to define “good adherence” [1,20]
may differ for specific treatments such as antiretroviral therapies [1,35]. In line with studies
describing the possible heterogeneity across drugs [16,21,36], we considered that medication
adherence could not simply be summarized as a unique and identical rate of drug intake for all
drugs. However, we did not explore all medication-taking behaviors described in the literature
(e.g., drug holidays or extra doses) nor all possible complex adherence patterns , which
could be further explored in future studies.
Our findings suggest that for 11.4% (in proportion of reimbursed pill boxes) of the
medications assessed, the estimated TURN was more than 2 daily missed doses per week. Some
physicians even suggested considering non-adherence as a trigger for de-prescribing some
medications with poor benefit-risk ratio. These findings are consistent with a recent survey
conducted in the United States in which 2106 physicians reported that 20.6% of overall
medical care was unnecessary, including 22.0% of prescription medications .
Physicians who are dealing with poor medication adherence in their patients need to decide
whether they should intervene to change patients’ behaviors. Considering the TURN may lead
to a conceptual shift by changing the definition of “good adherence” and by modifying the
care goals for patients taking multiple medications. The care goals for patients taking
longterm treatments should no longer be necessarily to achieve “perfect adherence”, without regard
to the drug of interest, but rather to seek “optimal adherence.” However, the TURN is only
one of the components of decision-making: other aspects may affect the threshold for
physicians’ intervention such as the drug’s expected benefit, therapeutic outcomes, patients’
treatment experiences and preferences.
Our study provides a first answer to the question “how much drug non-adherence is
acceptable?” However, future research on “how much adherence is enough?” is still needed to help
physicians accurately inform their patients, discuss about differential consequences of drug
non-adherence, better prioritize interventions, and achieve the desired therapeutic outcomes
without putting the patient at risk and without unnecessarily increasing the burden of
treatment on patients.
S1 File. Supporting data 1.
S2 File. Supporting data 2.
S3 File. Copy of a clinical vignette used in the study.
S2 Fig. Distribution of physicians’ estimates: Threshold for Unacceptable Risk of
NonAdherence (TURN) for 112 drug-indication groups.
S1 Table. Final version of the questionnaire.
S2 Table. Sensitivity analyses with different cutoffs to define the summary estimate of the
We thank Elise Diard for her help in the development of the study website. We are particularly
indebted to the Socie´te´ de Formation The´rapeutique du Ge´ne´raliste—Recherche (SFTG
Recherche), Paris, France, for distributing the study to their members.
Conceptualization: Ste´phanie Sidorkiewicz, Viet-Thi Tran, Philippe Ravaud.
Data curation: Ste´phanie Sidorkiewicz.
Formal analysis: Ste´phanie Sidorkiewicz.
Investigation: Ste´phanie Sidorkiewicz.
Methodology: Ste´phanie Sidorkiewicz, Viet-Thi Tran.
Validation: Ste´phanie Sidorkiewicz, Viet-Thi Tran, Philippe Ravaud.
Writing – original draft: Ste´phanie Sidorkiewicz.
Writing – review & editing: Viet-Thi Tran, Philippe Ravaud.
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