Medication Adherence: Gaining Insights on Patient-Reported Facilitators and Barriers

doi:10.21203/rs.3.rs-3438705/v1

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Medication Adherence: Gaining Insights on Patient-Reported Facilitators and Barriers

https://doi.org/10.21203/rs.3.rs-3438705/v1

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Background: Evaluating patient-reported facilitators and barriers to medication adherence allows us to better understand patients' perceptions, which continue to be the root cause of medication nonadherence.

Objective: This study aimed to assess patient-reported facilitators of and barriers to medication adherence.

Methods: The principles of the concurrent method of triangulation were used for chronic disease patients aged ≥ 18 years who were hospitalized in a South Indian tertiary care teaching hospital. This six-month study used a semi-structured, pre-validated questionnaire for interviewing; responses were recorded to identify the reported facilitators and barriers. The patients were counselled, and the data collected were statistically analyzed categorically.

Results: A total of 431 patients were enrolled, and the majority [223 (51.7%)] were non-adherent to the medication. The barriers included forgetfulness, attitudes, misbeliefs, lack of follow-up and refilling, lack of social support, financial constraints, lack of accessibility to healthcare, improper rapport with healthcare professionals, lack of disease knowledge, complex dosage regimens, and adverse effects. Facilitators included regular refills, good social support, good rapport with healthcare professionals, and good access to healthcare and routines. The older age group of 71-80 years [OR 3.18 (95% CI, 1.27–7.91)], annual income (INR) of 3-5 Lakhs [OR 6.75 (95% CI, 1.26–36.03)], two or more number of past medications [OR 2.85 (95% CI, 1.75–4.66)], number of current medications (during hospitalization) being 6-10 [OR 4.10 (95% CI, 1.07–15.71)], number of disease conditions more than 3 [OR 9.19 (95% CI, 2.02–41.64)] and management of discharge medications by others than self [OR 2.93 (95% CI, 1.10–7.77)] were found to be significant predisposing factors.

Conclusions: This study provides a framework for research on medication non-adherence in patients with chronic disease by describing a set of predictors along with facilitators and barriers to medication adherence identified through patient-reported measures.

Medication adherence

Facilitators and barriers

Clinical pharmacist

Medication non-adherence is a serious drug-related problem that has been associated with sub-standard treatment outcomes, worsened disease progression, increased hospital admissions, increased healthcare costs, and mortality. ^[1–3] Furthermore, medication non-adherence is linked to over 50% of treatment failures and 125,000 preventable deaths each year.^[4]

Compared to acute conditions, the level of medication adherence in chronic diseases is much lower.^[2] According to several studies, adherence to long-term medications is only approximately 50% on average in developed countries and could be far lower in developing and underdeveloped countries. ^[5–7] This is disappointingly low, as it is important to achieve an optimal therapeutic outcome of 80% or more. ^{[1, 4]}

Studies conducted in and around India that focused on medication adherence among patients with specific chronic diseases have shown a varying prevalence of medication non-adherence. ^[8–10] Apart from poor attitudes towards disease and lower rates of health literacy, out-of-pocket costs are likely to worsen patients' non-adherence behavior. It is noteworthy that in India, 80% of the total health expenditure is paid through the patient's pocket ^[8], and the major reasons for non-adherence are poor disease attitude and low health literacy. ^{[11, 12]} Despite these hurdles, if we can achieve medication adherence to the prescribed treatment regimen, the benefits are better clinical outcomes and decreased mortality rate. As this is evident, a thorough understanding of the triggers of non-adherence to medication is critical. This is important for adopting effective interventions to improve adherence and clinical outcomes in chronic diseases. Knowing that medication adherence is a complex process, an in-depth understanding of the patient’s perspective on various factors that affect medication adherence is essential to overcome these hurdles.

Factors are considered facilitators if their presence promotes adherence to medication, and barriers if their presence impedes overall medication adherence. The WHO further divides these factors into socioeconomic-related, healthcare teams, healthcare system-related, therapy-related, condition-related, and patient-related factors. The facilitators and barriers of medication adherence provide insight into the predictors of medication adherence, which can be considered in determining the risk factors for non-adherence.

While previous studies focused only on one domain, which is patient-related ^[13] and mostly on only one chronic disease, studies that focus exclusively on chronic diseases and patients' perspectives on facilitators and barriers are needed. This will help us obtain a broader picture of the positive and negative aspects of medication end-users. To achieve a broader understanding of patient perspectives, a suitable method involving both qualitative and quantitative studies can be implemented. This is a mixed-method design that considers the patient's point of view and ensures that the results are rooted in the patient's experience. Thus, we intended to assess facilitators and barriers as reported by patients using a mixed method of concurrent triangulation.

Ethics Approval

The study was approved by the Institutional Human Ethics Committee of JSS College of Pharmacy, Mysuru (JSSCPM/ IHEC/ 2019/ 021)

Development and Validation of the Questionnaire

Based on an extensive literature review, a suitable questionnaire (Supplementary File 1) was developed regarding patient-reported facilitators and barriers to medication adherence. The questionnaire comprised open- and closed-ended questions. The prepared questionnaire was validated using the Content Validity Index developed by Waltz and Bausell ^[10], and Cronbach’s alpha ^[11] was used to measure the internal consistency.

Design, Setting, and Study Population

A mixed-method study design of concurrent triangulation was adopted, as it included a combination of both quantitative and qualitative research methods. This study was conducted in a tertiary care teaching hospital in Southern India. Patients of either sex, aged ≥ 18 years, admitted to any of the general wards, with at least one chronic disease, and on active therapy were included. Patients who were non-cooperative and/or with cognitive impairment and those not willing to provide consent were excluded from the study.

Study Procedure

Patients who met the study criteria were enrolled, and all necessary details were recorded in the prepared data collection form from medical records by interviewing patients and/or patient caregiver(s) and health care professional(s) after which the interview was conducted using a semi-structured questionnaire.

Data Analysis

Assessment of medication non-adherence

All patients were classified as adherent or non-adherent based on questions 2, 3, 4, 5, 17, 23, 27, and 28 selected from the prepared and validated study questionnaire, which were directly associated with medication adherence. Patients who responded ‘yes’ to at least one of the eight questions were considered non-adherent. Patients in the non-adherent group were furthermore subdivided into three categories which included ‘highly non-adherent,’ ‘moderately non-adherent’ and ‘low non-adherent’ groups. The grouping was based on a non-adherence score which was calculated from a set of answers, each ‘positive’ answer (response ‘Yes’) was given a score of ‘+1’, and each ‘negative’ answer (response ‘No’) a score of ‘0.’ On a scale of 1–8, patients who scored ‘8’ were considered highly non-adherent, ‘6–7’ were moderately non-adherent, and ‘<6’ were low-non adherent.

Facilitators and barriers

The questionnaire contained 29 questions separated into four domains: patient (14 questions), healthcare system (6 questions), therapy (5 questions), and socially connected (4 questions). This survey included both open- and closed-ended questions. The open-ended questions were broad, eliciting participants' perspectives and attitudes regarding their medical status and treatment. Closed-ended inquiries were more specific in terms of extracting the patient's perspective, experience, and behavior. Each patient’s interview lasted approximately 20 to 30 minutes and was recorded and transcribed. NVivo-12 was used to code all transcripts. A third reviewer resolved any inconsistencies after two reviewers separately reviewed the transcripts for possible themes.

Predictors

Odds ratios (OR) at 95% confidence intervals was measured to evaluate the association between non-adherence and contributing factors. Further, all categorical variables are represented as numbers with percentages, wherever applicable.

Demographic Characteristics of the Study Population

In total, 431 eligible patients were interviewed using a questionnaire. The demographic characteristics of the study population are shown in Table 1.

Table 1

Demographic characteristics of study population
Characteristics		Distribution of Patients (%) (n = 431)
Age (years)	18–30	31 (7.1)
	31–40	38 (8.8)
	41–50	61 (14.1)
	51–60	125 (29)
	61–70	106 (24.5)
	71–80	56 (12.9)
	81–90	12 (2.7)
	91–100	2 (0.46)
Gender	Male	284 (65.8)
Gender	Female	147 (34.1)
Level of education	Primary	42 (9.7)
	Secondary	35 (8.1)
	Higher	125 (29)
	Under graduation	12 (2.7)
	Post-graduation	2 (0.46)
	Nil	215 (49.8)
Annual income (INR)	≤ 50000	35 (8.1)
	> 50,000–3 Lakhs	25 (5.8)
	> 3–5 Lakhs	11 (2.5)
	> 5 Lakhs	11 (2.5)
	Dependant on family	17 (3.9)
	Prefer not to say	332 (77)
Preferred language	Kannada	393 (91.1)
	English	22 (5.1)
	Others*	16 (3.7)
Marital status	Married	406 (94.1)
Marital status	Single	25 (5.8)
Type of family	Nuclear	313 (72.6)
Type of family	Large	118 (27.3)
Area of residence	Urban	62 (14.3)
	Sub-urban	257 (59.6)
	Rural	112 (25.9)
Total number of medications (past history)	1	188 (43.6)
	2	108 (25)
	3	67 (15.5)
	4 to 6	60 (13.9)
	> 6	8 (1.8)
Total number of current physicians	1	137 (31.7)
	2	160 (37.1)
	3	22 (5.1)
	> 3	112 (25.9)
Number of current medication (hospitalized)	1 to 5	173 (40.1)
	6 to 10	246 (57)
	> 10	12 (2.7)
Number of disease conditions	1	239 (55.4)
	2	142 (32.9)
	3	35 (8.1)
	> 3	15 (3.4)
Discharge medications managed by	Self	267 (61.9)
	Spouse	47 (10.9)
	Self and spouse	21 (4.8)
	Others**	96 (22.2)
*Tamil, Telugu, Malayalam
**Family members other than spouse

Status of Medication Adherence among the Study Population

The study population was classified based on nonadherence, as mentioned in the Methods section. More than half of the study population 223 (51.7%) was non-adherent to their prescribed medications. Further, the classification of non-adherent patients revealed that all non-adherent patients were in the class of low non-adherence, that is, a non-adherence score of < 6.

Facilitators and Barriers

The survey questionnaire was used to interview eligible patients to assess their facilitators and barriers to medication adherence, the responses are presented in Table 2.

Table 2

Survey questionnaire responses
Sl. No.	Question	Distribution of Patients (%) (n = 431)
Sl. No.	Question	Yes	No
1	Do you tend to forget taking your medications?	133 (30.8)	298 (69.1)
2	Have you ever stopped taking your medications or decreased the dose on your own without informing your health care professional	101 (23.4)	330 (76.5)
3	Do you stop taking your medications when the expected outcome is not on time?	23 (5.3)	408 (94.6)
4	Have you ever started taking medications on your own without informing your health care professional?	60 (13.9)	371 (86)
5	Have you ever switched to different medications on your own without informing your health care practitioner?	38 (8.8)	393 (91.1)
6	Did you ever take someone else’s medication?	10 (2.3)	421 (97.6)
7	Do you miss scheduled doctor appointments?	194 (45)	237 (54.9)
8	Do you get your prescription refilled on time?	353 (81.9)	78 (18)
9	Do you visit the same pharmacy for buying your medications every time?	190 (44)	241 (55.9)
10	Do you recheck the medications dispensed with your doctor?	175 (40.6)	256 (59.2)
11	Do you often leave the pharmacy dispensary without taking your prescribed medicines	92 (21.3)	339 (78.6)
12	Do you think medicines do more harm than any good?	77 (17.8)	354 (82.1)
13	Are natural remedies safer than allopathic medicines?	107 (24.8)	324 (75.1)
14	Do you have any of fear being discriminated within or outside your home for your medical condition	14 (3.2)	417 (96.7)
15	Have you ever missed taking any medication because of religious beliefs?	9 (2)	422 (97.9)
16	Do any of your relatives or friends discourage you from taking medication?	24 (5.5)	407 (94.4)
17	Do you feel that the health care system is easily accessible?	312 (72.3)	119 (27.6)
18	Do you think patient counseling will help you to take your medications regularly?	397 (92.1)	34 (7.8)
19	Do you ask a pharmacist or physician when you have any doubt or concern regarding your medication?	304 (70.5)	127 (29.4)
20	Do you prefer taking generic medicines rather than branded medicines?	93 (21.5)	179 (41.5)
21	Under the financial constraints do you purchase insufficient quantities of prescribed medications?	31 (7.1)	400 (92.8)
22	Do you get all the required medication in the same pharmacy?	313 (72.6)	118 (27.2)
23	Do you feel that you have too many medications to take every day?	90 (20.8)	341 (79.1)
24	Do you get confused with the timings of taking prescribed medications?	73 (16.9)	358 (83)
25	Do you ever purposely miss medication to avoid side effects?	28 (6.4)	403 (93.5)
26	Do you feel most of the medicines are addictive or have side effects?	99 (22.9)	332 (77)

In-depth interviews with the study participants identified several factors that impacted medication adherence. The themes that emerged during the interviews are summarized in Table 3, and thematic analysis of the interviews is described below.

Table 3

Common themes that emerged during interviews
Sl. No.	Themes
1	Patient related	a. Forgetfulness b. Attitude and misbelieves c. Follow up and refilling
2	Social related	a. Social support
3	Health care system related	a. Healthcare related costs b. The behaviour of service provider c. Health care accessibility
4	Therapy related	a. Disease knowledge b. The complexity of dosage regimen c. Adverse effects d. Routine

Two open-ended questions were coded to interpret the results better. For the question “In general, how satisfied are you with the overall support you get from your friends and family members regarding your medical condition?” Coding was based on responses given by participants. Post coding, the different levels of perceived social support were very satisfied, satisfied, neutral, and not satisfied. Results showed that slightly more than half of the patients 286 (66.3%) were very satisfied with the social support received, while 133 (30.8%) patients opined they were just satisfied, and the remaining two (0.4%) and 10 (2.3%) patients expressed that they were neutral and not satisfied with the level of social support they received, respectively.

While for the question “Please tell me what you know about your disease,” post-coding results were classified as excellent if the participant knew about their disease, medications, and lifestyle modifications that they needed to follow. Patients who knew any two or one of the three were classified as good or average patients, respectively. Patients who knew nothing were ranked very poor. The results revealed that only two (0.4%) patients had excellent knowledge, and 23 (5.3%) patients had good knowledge regarding their diseases. Furthermore, the majority 147 (34.1%), 169 (39.2%), and 90 (20.8%) were classified as average, poor, and very poor, respectively.

Understanding the facilitators and barriers of medication adherence will give us insight into the factors that could affect the pattern of adherence in a particular patient, which will help us aim for better interventions. Different factors, that is, barriers and facilitators affecting medication adherence, as perceived from the study, are presented in Figs. 1 and 2, respectively.

Predictors

Patients aged 71–80 years were 3.18 times more non-adherent and those with lower income were 6.75 times more non-adherent. Patients with a history of polypharmacy were more prone to non-adherence compared to patients who received only one medication. Patients with more than three chronic disease conditions were 9.19 times more non-adherent when compared to patients with one chronic disease. Similarly, in patients whose discharged medications were managed by others, the likelihood of non-adherence was 1.64 times higher compared to patients whose discharged medications were managed by themselves alone. An overview of the predictors of medication nonadherence is presented in Table 4.

Table 4

Overview of predictors of medication non-adherence
Variable	Odds ratio	Confidence interval (95%)	P value
Age (in years)
18–30	Standard
31–40	0.72	0.27–1.91	0.510
41–50	1.43	0.59–3.42	0.42
51–60	1.28	0.57–2.83	0.54
61–70	1.80	0.80–4.06	0.153
71–80	3.18	1.27–7.91	0.013
81–90	1.93	0.50–7.48	0.337
Gender
Male	Standard
Female	0.74	0.5–1.11	0.151
Level of Education
Primary	Standard
Secondary	0.52	0.21–1.31	0.167
Higher	0.56	0.27–1.16	0.120
Under graduation	0.77	0.20–2.88	0.706
Nil	0.57	0.28–1.13	0.109
Annual Income (INR)
≤ 50000	Standard
> 50,000–3 Lakhs	1.17	0.41–3.33	0.757
> 3–5 Lakhs	6.75	1.26–36.03	0.025
> 5 Lakhs	4	0.90–17.70	0.068
Dependant on family	0.81	0.24–2.72	0.744
Prefer not to say	1.67	0.82–3.40	0.156
Marital status
Married	Standard
Single	0.85	0.38–1.91	0.700
Type of Family
Nuclear	Standard
Joint	1.32	0.86–2.02	0.199
Area of Residency
Urban	Standard
Sub-urban	1.05	0.60–1.84	0.841
Rural	1.47	0.79–2.75	0.222
Total No. of Past Medications
1	Standard
2	2.85	1.75–4.66	0.0001
3	1.99	1.12–3.49	0.017
4–6	2.59	1.43–4.71	0.0018
No. of Current Physicians
1	Standard
2	1.40	0.88–2.21	0.146
3	0.76	0.30–1.91	0.569
> 3	1.21	0.74–2.03	0.412
Total Number of Current Medications (Hospitalization)
1–5	Standard
6–10	1.84	1.24–2.72	0.002
> 10	4.10	1.07–15.71	0.039
No. of Disease Conditions
1	Standard
2	2.04	1.34–3.12	0.0009
3	4.77	2.08–10.9	0.0002
> 3	9.19	2.02–41.64	0.004
Management of Discharge Medications
Self	Standard
Self and Spouse	1.89	0.99–3.56	0.050
Others †	1.64	1.02–2.63	0.040
†Family members other than spouse.

Facilitators and Barriers

The study findings revealed that most patients do not forget to take their medications, do not stop taking medications regardless of the late outcome, and do not start or switch to a new medication without informing a healthcare professional. While this is encouraging, patients’ attitudes towards doctors’ appointments are of great concern, as only a little more than half of the patients keep up with scheduled appointments with their doctors.

An on-time refill of medications by most of the patients is another encouraging finding, as only 18% of the patients did not refill prescriptions on time. This low level of non-adherence to medication refilling is in concordance with the National Report Card on medication adherence in America, as only 28% of patients cannot refill prescriptions on time.^[14] The different reasons for the late refill were financial constraints, unavailability of medicines, absence of caretakers, and a feeling of neglect towards their medications.

Apart from the practice of on-time medication refills, most patients used different pharmacies to refill medications, which created a sense of easy availability in healthcare systems. This is evident, as 72.3% of the patients in this study felt that healthcare systems are easily accessible whenever needed. It should also be noted that visiting the same pharmacy every time could facilitate medication adherence. This finding, however, is different when compared to a previous study ^[15] by Martin Schulz et al., who concluded that a weekly visit to a pharmacy (need not be the same pharmacy) is a motivating factor for adherence as visiting pharmacies resulted in updating their medication plan and referring to doctors if there were any significant changes in vitals and/or any new drug-related problems.

The presence of support from family, friends, and relatives seems to be a huge source of support for these patients and hence a facilitator for adherence. Most patients were satisfied with the level of family support they received from family, friends, and relatives. Several previous studies have reported that support from the family has helped achieve optimal adherence to medications in patients with chronic diseases. ^[16–18] In addition to family support, most patients stated that there was no form of discouragement from family and friends concerning medication use, and they had no fear of discrimination.

Furthermore, 92.1% of the patients reported that patient counselling was efficient and that it would help them take medications regularly. This finding is similar to that of a study ^[19] carried out by Kayyali et al., wherein it was reported that most patients wanted to be counselled, especially regarding information regarding side effects and lifestyle modifications.

The cost of medication was not a concern among patients, as only 7.1% purchased insufficient quantities of medication due to financial constraints. However, in a study ^{by Gellad et al. [20]}, the cost has been stated as a barrier to medication adherence in patients with chronic diseases, as patients were not able to refill their medications because of increased medication costs and missed medication to make prescriptions last longer despite having insurance coverage.

A total of 22.9% of patients felt that most medicines were either addictive or could cause side effects, and only 6.4% of these patients missed taking medications to avoid these side effects. This is in line with a study conducted by Horne et.al that reported the side effects and addiction as patients' concerns.^[21] This study found that these patients considered taking medications regularly to be more beneficial than avoiding side effects. Additionally, another study ^[22] by Hincapie et al. reported that 40% of their study participants started and stopped taking medication owing to a side effect.

Other reasons for non-adherence to medications included difficulties or confusion with the timing of medications and having too many medications to take.

Studies have also reported that with an increase in age, non-adherence also increases owing to forgetfulness, confusion associated with age-related cognitive impairment, and an increased number of medications. ^{[23, 24]} Also, patients with false beliefs about healthcare and low income are more likely to have uncontrolled disease conditions due to non-adherence, as they cannot meet the requirements for healthcare. ^{[25, 26]} However, in this study, the busy schedule and travelling long distances were possible reasons for non-adherence despite financial stability.

In addition, an increase in the number of medications and diseases was associated with increased non-adherence. This finding is similar to those of several other studies. ^[27–29] However, in contrast, a study by Richard W. Grant et al. ^[30] showed an independent relationship between adherence and the number of medications as patients were well-engaged with the healthcare system and had improved perceptions of the immediate and future benefits of prescribed medications.

LIMITATIONS

The responses to a few of the questions could have been counterproductive, as the questionnaire was elaborate and time-consuming. Despite these limitations, this is the first study to explore patient-reported facilitators and barriers considering all chronic disease conditions.

The overall findings of this study suggest that the interplay of these factors is involved in patient medication adherence. Hence, the predominant factors affecting the patients’ final decision on whether to take medications. Although some factors, such as financial constraints, are more difficult to tackle, other factors can be improved through interventions. Nonetheless, individual factors that affect medication adherence may vary according to the practical scenario.

FUNDING

The authors (s) received no specific funding for this study.

ACKNOWLEDGMENT

The authors would like to thank Dr. Krishna Undela for assistance with statistical analysis. Special thanks to all the teaching and non-teaching staff of JSS College of Pharmacy and JSS Hospital, Mysuru, for their exceptional support.

CONFLICT OF INTEREST

The authors (s) declare(s) that they have no conflict of interest.

ETHICAL APPROVAL

The study was approved by the Institutional Human Ethics Committee, JSS College of Pharmacy, Mysuru, Karnataka, India. Letter No.: JSSCPM/IHEC/2019/021.

AUTHOR CONTRIBUTION:

MKA: Mohith Kumar Abaka; EEC: Emelda Elechi Chinemerem; PMR: Patric Manakuzhiyil Rejimon; FMPV: Fasil Majeed P.V; MR: M. Ramesh; CSH: Sri Harsha Chalasani; JS: Jehath Syed

Conceptualization: MR; Data curation: MKA, EEC, PMR, FMPV; Formal analysis: MKA, EEC, PMR, FMPV, CSH, JS; Investigation: MKA, EEC, PMR, FMPV; Methodology: MR, CSH; Project administration: MKA, EEC, PMR, FMPV, MR, CSH, JS; Supervision and Validation: MR, CSH; Visualization: MKA, EEC, PMR, FMPV, CSH, JS; Writing- original draft: MKA, EEC, PMR, FMPV, JS; Writing- review & editing: MR, CSH

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Barriers and Facilitators of medication adherence questionnaire

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Medication Adherence: Gaining Insights on Patient-Reported Facilitators and Barriers

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Abstract

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INTRODUCTION

METHODS

Ethics Approval

Development and Validation of the Questionnaire

Design, Setting, and Study Population

Study Procedure

Data Analysis

Assessment of medication non-adherence

Facilitators and barriers

Predictors

RESULTS

Demographic Characteristics of the Study Population

Status of Medication Adherence among the Study Population

Facilitators and Barriers

Predictors

DISCUSSION

Facilitators and Barriers

LIMITATIONS

CONCLUSION

Declarations

References

Supplementary Files

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