Is there an association between medication knowledge and medication compliance in renal transplant recipients?

Uma Rani Adhikari¹, Dr. Abhijit Taraphder², Dr. Avijit Hazra³, Dr. Tapas Das⁴

¹Govt College of Nursing, Burdwan, Aftab Avenue, P.O-Rajbati, Dist-Burdwan, W.B, Pin-713104, India

²Dept. of Nephrology, Apollo Gleneagles Hospital, Kankurgachi, Kolkata-700054, India.

³Dept of Pharmacology, I.P.G.M.E.R and S.S.K.M Hospital, A.J.C. Bose Road, Kolkata-700020, India

⁴Dept of Medicine, K.P.C Medical College, 1F, Raja Subodh Chandra Mullick Road, Jadavpur, Kolkata 700032, West Bengal, India

*Corresponding Author Email: w2uma@yahoo.com

ABSTRACT:

Introduction: It is well known that success of organ transplantation depends on medication compliance. Knowledge about the disease and prescribed medication can contribute to a better medication taking behavior and is associated with higher rates of compliance. The objective of this study was to investigate the association between medication knowledge and medication compliance among kidney transplant recipients.

Methods: The study was conducted with adult subjects attending the nephrology post-transplant clinic of a tertiary care government and two private hospitals in Kolkata. This was a longitudinal study that included 153subjects.

Results: Majority (71.23%) of the kidney recipients’ medication knowledge were good or better. Medication knowledge score was significantly associated with compliance status of renal transplant recipients. There was no statistically significant association of age and education with medication compliance. The transplant recipients were quite young in age; their median age being 37 years with interquartile range 29-48 years.

Conclusions: So improving medication knowledge of renal transplant recipients could improve the medication compliance among adult renal transplant recipients.

KEYWORDS: Adult, Medication knowledge, Renal transplant recipient, Medication compliance.

INTRODUCTION:

The progress of medical science and technology has given us many new drugs with the potential to cure or to control the progression of various diseases. However, the benefits of treatment, especially in situations where multiple drugs have to be taken on a regular basis, will not be realized adequately if there is non-compliance to the medication regimen. Identifying the factors which lead to non-compliance is therefore important in individual clinical situations so that timely remedial measures may be adopted.

Estimates from the World Health Organization¹ indicate that, even in developed countries, only about 50% of patients with chronic diseases follow treatment recommendations. A recent meta-analysis² revealed that the magnitude of nonadherence to immunosuppressants in renal transplant recipients is as high as 35.6 cases per 100 patients per year, and nonadherence to immunosuppressive drugs in overall population of solid organ transplant recipients is 22.6 cases per 100 patients per year. Also non-adherent patients are seven times more at risk of graft failure than adhering patients². It is well known that success of organ transplantation depends on medication compliance. Non compliance therefore leads to poor health outcomes and increased healthcare costs.³A systematic review suggests that median 36% (interquartile range 14-65%) of graft losses may be associated with nonadherence in renal transplant patients.⁴

In India, the demand for organs for transplantation is high but availability of organs is limited. Thus if a transplanted kidney is damaged due to medication noncompliance, it represents not only a loss of quality of life and money for the patient concerned, but also a deprivation for other patients waiting for transplantation. A few studies have shown that better medication knowledge is associated with improved medication adherence.^5,6 However, this aspect has not been explored adequately in the Indian context, so that we are not in a position to state whether greater efforts should be expended on improving medication knowledge among renal transplantation patients in India with the goal of improving compliance. The objective of this study was to investigate this association between medication knowledge and medication compliance among kidney transplant recipients.

MATERIAL AND METHODS:

A prospective observational study was conducted with adult subjects, of either sex, attending the nephrology post-transplant clinic of a tertiary care government hospital and two private hospitals in Kolkata. Following institutional ethics committee approval, total of 179 kidney transplant recipients were recruited in the period July, 2011 to June, 2013 and followed up at the first out-patient visit after transplant and then at 3, 6, 9 and 12^th months following transplant. Purposive sampling technique was used to select subjects for the study and written informed consent was obtained from all. Subjects were excluded if both recipient and close caregivers were illiterate or unwilling to participate.

Patients’ medication knowledge was assessed using the interviewer administered Medication Knowledge Assessment Questionnaire (MKAQ) used by Sathvik et al⁷. This MKAQ questionnaire is valid and reliable for end-stage renal disease patients. This questionnaire comprises 5 questions with two columns named as ‘actual’ and ‘patient’ against the questions. The ‘actual’ column is to list the medications actually taken by the patient and is filled by the interviewer beforehand by referring to case records and prescriptions. An interview is then conducted for each patient to assess parameters like ability to recall correct medicine name, the purpose of use (indication), dose / strength, the number of doses to be taken in each day and adverse effects of the medicine. The responses are used to score questions 1 to 4 separately in the ‘patient’ column and then calculate a percentage knowledge score. The fifth question is not scored. We considered the average percentage score from five study visits for statistical analysis. The knowledge score was categorized as ‘very poor’, ‘poor’, ‘average’, ‘good’ and ‘very good’ in 20% steps with ‘very good’ knowledge implying a score between 80-100%.

To screen for medication compliance status, we adopted the dichotomous questions from the 4-item Morisky Medication Adherence Scale (MMAS-4)⁸. This is a widely used tool for assessing medication adherence and its reliability has been studied across a variety of disease groups.⁸The questions were asked verbally according to patient’s preferred vernacular language. Potential noncompliant behavior was identified by positive response to any of the four items. These subjects were then probed further in details and the actual compliance was assessed as frequency of doses missed or delayed (by more than 2 hours) in a month. Each recipient’s primary family caregiver was also interviewed during the visit about the patient’s compliance.

Taking adherence to denote the extent to which medication taking behavior conforms to that what is advised, non-compliance was taken to be failure to take a dose or take the doses on time. Overall, a patient was deemed to be non-compliant if he or she failed to take medicines (doses missed or delayed by more than 2 hours) on appointed time more than three times in any month during the observation period. Compliance was assessed for immunosuppressant medication and oral medicines for comorbidities and complications.

Data have been summarized by mean and standard deviation (SD) for continuous variables and counts and percentages for categorical variables. Median and interquartile range (IQR) have been provided for continuous variables with skewed distribution. Association between knowledge score and age and monthly family income was quantified by Spearman’s rank correlation coefficient. Knowledge score change over time was assessed for statistical significance by repeated measures analysis of variance (ANOVA) followed by Tukey’s test for post hoc pair-wise comparisons. Numerical variables have been compared between subgroups by Student’s independent samples t-test. Fisher’s exact test or chi-square test was employed for intergroup comparison of categorical variables. Comparisons were two-tailed and p< 0.05 was regarded as statistically significant. To assess the combined impact of predictor variables on overall medication compliance status, all variables that returned p value < 0.2 upon univariate analysis were entered into a binary logistic regression model. SPSS version 19 software was used for statistical analysis.

RESULTS:

Table 1.Demographic profile of the study subjects.

Parameter

n = 153

Age (years)

Range

Mean ± SD

Median (IQR)

18.0 – 65.0

38.5 ± 12.22

37 (29 – 48)

Sex

Male

Female

108 (70.6%)

45 (29.4%)

Education status

Primary

Secondary

Higher secondary

Graduate

Professional

12 (7.84%)

23 (15.03%)

30 (19.60%)

71 (46.40%)

17 (11.11%)

Monthly family income (Rupees)

< 15,000

15,000 – 25,000

> 25,000

47 (30.71%)

13 (8.49%)

93 (60.78%)

Employment status

Employed

Unemployed

97 (63.39%)

56 (36.60%)

§ Abbreviations: IQR = Interquartile range; SD = Standard deviation.

Out of 179 patients, 13 patients were lost to follow-up and another 13 patients died before completing 1 year. The analysis was restricted to the remaining 153 patients. The basic demography of the sample is depicted in Table 1. It shows that 70.06% of the renal transplant recipients were males, majority (77.11%) were educated up to higher secondary level or beyond (i.e. underwent at least 14 years of formal education) and 39.20% were from lower income group (average monthly family income ≤ Rs. 25,000). The transplant recipients were quite young in age; their median age being 37 years with interquartile range 29-48 years.

Figure 1 depicts the distribution of participants’ knowledge score. The average score achieved was 67.7 ± 17.43 (Mean ± SD) over the 5 study visits. Majority (71.23%) achieved a score > 60% (i.e. ‘good’ to ‘very good’ category) but in 7.18% the score was < 40% (i.e. ‘very poor’ to ‘poor’ categories).

There was a progressive increase of score over the 12 month observation period i.e. 56.4 ± 20.46 (baseline), 62.6 ± 18.25 (3^rd month visit), 68.7 ± 18.03 (6^th month visit), 72.93 ± 17.67 (9^th month visit) and 77.6 ± 17.14 (12^th month visit). Comparison of medication knowledge score over 5 visits by repeated measures analysis of variance (ANOVA), F value is 261.17, p< 0.001. The change was significant overall (p< 0.001) as well as from one visit to the next (p< 0.001).

Table 2 depicts the association between average medication knowledge score and selected demographic and socioeconomic variables. Evidently, there is a positive association between knowledge score and education and income levels, but no significant association with age, sex or employment status.

Overall 94 subjects (61.44%, 95% confidence 53.73 to 69.15%) were found to be compliant to their medication regimens in this series.

Table 2.Relationship between medication knowledge and baseline variables (n =153).

Parameter	Knowledge score or its correlation	p value
Age (years)	Rho = 0.131	0.106
Monthly family income	Rho = 0.491	0.000
Sex Male Female	67.83 ± 17.107 67.24 ±18.386	0.848
Education status Primary Secondary and higher secondary Graduate and above	41.6 ± 9.55 60.7 ± 17.10 75.4 ± 12.69	< 0.001
Employment status Employed Unemployed	68.3 ±19.22 66.6 ± 13.89	0.517

Abbreviations: Rho = Spearman’s rank correlation coefficient.

Table 3.Comparisons between medication compliant and non-compliant subjects in the study.

Parameter

Compliant

(n = 94)

Non-compliant

(n = 59)

p value

Age (years)

Range

Mean ± SD

Median (IQR)

18.0 – 62.0

39.3 ± 11.73

32 (26 – 48)

18.0 – 65.0

37.1 ± 12.94

39 (30– 50)

0.173

Sex

Male

Female

60 (63.82%)

34 (36.17%)

48 (81.35%)

11 (18.64%)

0.028

Education status

Primary

Secondary and higher secondary

Graduate and above

4 (33.33%)

33 (62.26%)

57 (64.77%)

8 (66.66%)

20 (37.73%)

31 (35.22%)

0.109

Average medication knowledge score

Range

Mean ± SD

0.0 – 98.0

72.1 ± 15.77

12.0 – 94.0

60.6 ± 17.75

< 0.001

Knowledge level (categorized by score)

Very poor

Poor

Good

Very good

1 (1.02%)

5 (5.32%)

45 (47.87%)

43 (45.74%)

2 (3.39%)

18 (30.51%)

27 (45.76%)

12 (20.34%)

< 0.001

Abbreviations: IQR = Interquartile range; SD = Standard deviation.

Table 4.Summary of logistic regression analysis to identify predictors of compliance.

Parameter	p value	Wald coefficient	Adjusted OR (95% CI)
Age	0.455	.557	1.011 (0.982-1.041)
Average knowledge score	< 0.001	12.264	1.050 (1.022-1.079)
Education	0.285	1.145	0.692 (0.352-1.359)

Abbreviations: OR = Odds ratio, CI = Confidence interval.

Table 3 presents univariate comparison between compliant and non-compliant groups with respect to average medication knowledge score and other variables. Age, gender and educational status distribution were comparable. However, adherent subjects had a higher average knowledge score (by about 11%) and showed a clear distribution to the more knowledgeable categories, indicating that there is potentially a positive impact of medication knowledge on adherence.

Table 4 presents a summary of the logistic regression analysis, which also reveals that medication knowledge score had a significant and positive association with the chance of compliance, although the adjusted odds ratio is modest at 1.05 (95% confidence interval 1.02-1.08). Here again, there was no statistically significant association among age and education with medication compliance. This model Nagelkerke’s r² value is 0.148 and 14.8% of the cases correctly predicted.

DISCUSSION:

It is evident from the present study that medication knowledge has a positive influence on the drug compliance. A number of studies support such an association in which a positive relationship was found between medication knowledge and compliance in the context of chronic diseases.^5,6,9 However, one study from Pakistan reported that knowledge about disease and its management has inverse relationship with drug adherence.¹⁰ In the context of the Indian population, the effect of medication knowledge possessed by the patients on drug compliance is still uncertain as there are few published studies that look into this aspect. However, one education intervention study suggested that educating patients about their disease and its management helps to improve adherence.¹¹

All of our participants had at least some formal education and this study highlights that educational status influence the medication knowledge. Our study also shows that monthly income was correlated with medication knowledge. These findings are in conformity with studies.^5,12 The average score of medication knowledge being achieved was relatively high. This could be reflection of high levels of self-motivation of the transplant patients as well as efforts put in by physicians and caregivers.

The length of time that the patient had been taking medication could also be an important factor as patients taking their medications for a longer period of time are likely to be more knowledgeable. The present study showed that medication knowledge improves significantly in every consecutive study visit.

The prospective observation over a relatively long period, with periodic clinic visits, is strength of this study and helps to minimize recall bias. Also, patients were recruited from government as well as private hospitals thereby covering diverse socioeconomic background. We used the self-reporting method to measure medication compliance because it is considered simple, practical and the least expensive method. However, the possibility of overestimation of adherence by patients remain, to overcome which, responses from primary caregivers were also included to validate the responses. On the flip side, the sample size was limited and the sampling was purposive rather than random.

Finally, we can conclude that this longitudinal observational study suggests that, in the Indian scenario, improving medication knowledge of renal transplant patients can positively influence their compliance and therapeutic outcomes. Healthcare personnel need to involve themselves in medication education and monitoring with a view to improving medication compliance.

ACKNOWLEDGEMENTS:

Author thankful to Head of the Department of Nephrology and Director, I.P.G.M.E.R and S.S.K.M Hospital, Kolkata for providing support to carry out this work. Also thankful to The West Bengal University of Health Sciences, Kolkata for support to carry out this work and heartfelt thank goes to all the study participants who voluntarily participated in this study.

COMPETING INTERESTS:

The authors declare that they have no competing interests.

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Received on 13.06.2015 Modified on 26.06.2015

Asian J. Nur. Edu. and Research 6(1): Jan.- Mar.2016; Page 32-36

DOI: 10.5958/2349-2996.2016.00007.0