Medication regimen complexity and its association with adherence and blood pressure control among hypertensive patients at selected hospitals of South Gondar Zone: A hospital based cross sectional study.

INTRODUCTION: Despite the availability of effective antihypertensive medications, blood pressure (BP) control is suboptimal. High medication regimen complexity index (MRCI) is known to reduce adherence and may be the reason for poor BP control. However, there is no data in the present study areas. Hence, the aim of this study was to assess MRCI and its association with adherence and BP control among hypertensive patients at selected hospitals of South Gondar Zone.
METHODS: A hospital based cross sectional study was conducted from December 1, 2020 to February 30, 2021 at selected hospitals of South Gondar Zone. Medication regimen complexity and adherence was evaluated using 65-item validated tool called MRCI and eight items Morisky Medication Adherence, respectively. Multivariable logistic regression analysis was done to determine the association between predictive and outcome variables.
RESULTS: About 3.3% of participants were classified as having high HTN specific MRCI whereas 34.75% of participants were classified as having high patient level MRCI. Among participants, 37.8% were adherent to their medications, and 52.2% of respondents were categorized as having controlled BP. Multivariate logistic regression showed being married, and having lower education level was more likely and less likely to be adherent, respectively. Being illiterate, and having low HTN MRCI were more likely to have controlled BP in adjusted analyses. On the contrary, being non-adherent, not having health insurance, and having lower monthly income were less likely to have controlled BP.
CONCLUSION: A considerable proportion of patients had high MRCI. Having low HTN MRCI was more likely to have controlled BP. Simplification of a complex medication regimen for patients with HTN should be sought by physicians and pharmacists to improve BP control.

Introduction

Hypertension (HTN) is defined as an average systolic blood pressure of ≥ 140 mmHg and/or average diastolic blood pressure of ≥ 90 mmHg in adult individuals [1]. The worldwide prevalence of HTN among adults was 31.1% in 2010 and its prevalence was higher in lower and middle-income countries [1]. A systematic review and meta-analysis in Ethiopia revealed that the prevalence of HTN was estimated to be 19.6% in 2014 [2]. HTN is a very important public-health challenge and also the leading reason for the development of cardiovascular disease and premature death worldwide [3]. HTN is managed with a combination of antihypertensive drugs and self-care practices [4,5]. Antihypertensive drugs are known to scale back the speed of cardiovascular complications [4]. Despite the provision of effective drugs, blood pressure (BP) control is suboptimal. In Indiana, 57% of hypertensive patients who received antihypertensive drugs had uncontrolled HTN [6]. Additionally, in Ethiopia a systematic review and meta-analysis of pieces of the literature showed that 48% of hypertensive patients had uncontrolled HTN even if they were taking antihypertensive drugs [7]. The foremost reason for poor BP control is non-adherence to antihypertensive drugs and self-care practices [5,8]. Approximately 43% to 65.5% of hypertensive patients didn’t adhere to prescribed regimens and non-adherence to medications could be a potential contributing factor to the occurrence of concomitant diseases [9]. Several factors such as socio-demographic factors, individual’s knowledge and skills, individual’s beliefs and perceptions, physical/mental ability, quality of healthcare services, cost of treatment, patient resources, provider-patient relationship and communication, and drugs regimen complexity affect medication adherence, and subsequently therapeutic outcomes [10-12].

Medication regimen complexity comprises number of medicines, dosage forms, dosage frequency and other instructions for usage and it’s quantified by medication regimen complexity index (MRCI) [13]. Medication regimen complexity could be one of modifiable factors that affect patients’ adherence to their medication and in turn, it affects their clinical outcomes. Teamwork between pharmacists and other healthcare providers has been effective to simplify complex medication regimens to boost adherence and clinical outcomes [14,15]. A count of prescribed medications could be an easy and common measure of medication regimen complexity. However, medication count doesn’t address other regimen features contributing to complexity, like dosage forms, dose administration frequencies, and additional instructions, so it is unlikely to be a sufficient measure of regimen complexity. Moreover, medication count might not comprise non-prescription medications, which can contribute a significant part to medication complexity in some patients [16]. Median HTN specific MRCI was found to be 3 in one study [17], and 3.39 in another study [18]. Although some studies found that high MRCI had positive association with adherence, most studies found negative association between high MRCI and adherence [19]. By contributing for non-adherence, high MRCI may affect treatment effectiveness and patient safety because of the clinical consequences caused by not taking the medications, the utilization of below or above the recommended dose of medicines [20]. Moreover, the negative impact of non-adherence on blood pressure control has been established [21,22]. In Ethiopia, a big percentage of hypertensive patients (> 24%) were not adhered to their antihypertensive medications and there was high prevalence of uncontrolled hypertension (48%) [7,22,23]. The main contributing factor for uncontrolled hypertension is medication non-adherence [24]. There are limited studies regarding medication regimen complexity, and its association with medication adherence in hypertensive patients in the world. Moreover, there are no previous studies regarding the association of medication regimen complexity with BP control in the world. Therefore, this study is aimed to assess medication regimen complexity and its association with medication adherence and BP control among hypertensive patients.

Methods

Study area

The study will be conducted at 4 selected hospitals in South Gondar Zone of Amhara Region, Ethiopia. South Gondar Zone is one of 11 administrative zones of Amhara region, Ethiopia. It has 18 woredas (13 rural and 5 urban). There are 1 general hospital, 7 primary hospitals and 95 health centers in this zone. According to the 2007 national census conducted by Central Statistical Agency of Ethiopia (CSA), this zone has a total population of 2, 051, 738 and among this, 1, 041, 061 are men [25].

Study design and period

A hospital based cross sectional study was conducted from December1, 2020 to February 30, 2021.

Source and study population

All hypertensive patients on follow-up and attending the selected hospitals were used as a source population. Those patients who got treatment and fulfill the inclusion criteria were the study population.

Sample size and sampling technique

The sample size was calculated using a single population proportion formula as follows Where n is the desired sample size for pollution, Z is the standard normal distribution set as 1.96 (which corresponds to 95% CI), P value means that we used positive prevalence estimated to maximize the sample size, and W is the degree of accuracy 0.05 desired. There is no previous study regarding MRCI, so a p value of 0.5 was used. Then the sample size was, n = (1.96)2 * 0.5*((1–0.5)/(0.05)2 = 384. By adding 10% non-respondent, the final sample size was 423. By random and purposive sampling method, 3 primary hospitals (Addis Zemen, Mekane Eyesus, Nifas Mewcha) and 1 specialized hospital (Debre Tabor Comprehensive Specialized Hospital) were selected, respectively. Then, using systematic random sampling method and proportional allocation to each selected hospitals, 423 study participants were interviewed and their charts were reviewed. Systematic random sampling was applied by assuming all study population come to each respective study sites from December 1, 2020 –February 30, 2021. The sampling interval was determined by dividing the total population of study sites by sample size of study sites. Finally, the sampling interval was 4, and every 4th of study participants was included until the desired sample was achieved.

Dependent variables: Adherence, BP control

Independent variables: Medication regimen complexity, sex, age, co-morbidity, duration of hypertension treatment, adherence, type of antihypertensive drug, education level, income level, marital status

Inclusion and exclusion criteria

All adult hypertensive patients (≥ 18 years) who came to hospitals for follow up during the study period, treated with antihypertensive drug for at least 6 months, and willing to participate were included. Hypertensive patients who have hearing and cognitive impairment and incomplete chart were excluded. Furthermore, hospitalized patients during data collection period were excluded from the study.

Operational definitions

The Eighth Joint National Committee (JNC-8): It consists of members from different expertise such as in hypertension, primary care, pharmacology, nursing, epidemiology, evidence based medicine and the development and implementation of clinical guidelines in systems of care. JNC-8 evidence based guideline for the management of high blood pressure was prepared by the committee members. This guideline considers age, race and commodities while selecting antihypertensive drugs [26].

Controlled hypertension: BP < 150/90 mmHg in hypertensive patients aged 60 or older, or BP < 140/90 mmHg in hypertensive patients aged less than 60 years and all ages of hypertensive patients with diabetes mellitus or nondiabetic chronic kidney disease [26].

Uncontrolled hypertension: BP ≥150/90 mmHg in hypertensive patients aged 60 or older, or BP ≥140/90 mmHg in hypertensive patients aged less than 60 years and all ages of hypertensive patients with diabetes mellitus or nondiabetic chronic kidney disease [26].

Hypertension specific MRCI: It is defined as the component of the MRCI that only included in antihypertensive medications [13].

Patient level MRCI: It is defined as the overall MRCI, including antihypertensive medications in addition to all other prescription and OTC medications [13].

MRCI: With the cut-off set at ≤4 for low complexity, 5–8 for medium complexity, and a score >8 will be considered as high complexity [12].

Adherence: MMAS-8 will be trichotomized into three levels of adherence as that was done to facilitate its use in clinical practice: high adherence (MMAS score of 8); medium adherence (MMAS scores of 6 to < 8), and low adherence (MMAS scores of <6) [27,28]. Non-adherence was considered when MMAS score <8.

Data collection procedures

Clinical, demographic data and patients’ details of current medications were obtained from the chart. Socioeconomics, over the counter drugs, medication adherence status, and other demographics data that are not available from the chart were collected by interviewing the patients using structured questionnaire. The questionnaire was translated to Amharic language in order to make understandable by the study participants.

Medication complexity index (MRCI) is a validated 65-item tool for quantifying drug regimen complexity based on the quantity of medications, dosage form, dosage frequency, and additional instructions (eg, break/crush the tablet, take at a specified time, and relation to food/liquid) [13]. The 65-item tool consists of three sections related to the route of drug administration (section A), dosing frequency (section B), and additional directions (section C). The sum of the scores of each of the three sections (A+B+C) contributes to a complexity index [12].

An eight item Morisky’s Medication Adherence Scale (MMAS-8) was employed to assess the study participant’s medication adherence [27]. A scoring scheme of “Yes” = 0 and “No” = 1 for the first seven items except item number five in which the values are of “Yes” and “No” are reversed and for the last item a five-point Likert response are used with options “never”, “once in a while”, “sometimes”, “usually”, and “always” [28]. A BP value of participants, which has been measured recently, was used to assess whether BP is controlled or not.

Data quality control

Pretest was done on 5% of the sample size before the actual data collection initiation in Ebinat primary hospital. Data collectors were 4 pharmacists. One data collector was assigned for each study site to interview the participant and to review the patient charts. Data collectors were trained intensively by the principal investigator and 1 co-investigator for 2 days on the contents of the questionnaire, data collection methods, and ethical concerns. The filled questionnaire was checked daily for completeness by the principal investigator.

Data processing and analysis

The data were entered and analyzed using SPSS version 21.0. Descriptive statistics like frequencies for categorical variables and means and Standard deviation (SD) for variables measured on a continuous scale was calculated. Association between predictive variables (regimen complexity, sociodemographic, and clinical data of patients) and dependent variables (adherence and BP control) was determined by using binary logistic regression. Therefore, univariate logistic regression, which is used to analyze the association between an individual independent variable and outcome of interest, was done to compute the crude odds ratio, whereas multivariate logistic regression for analyzing two or more variables with the outcome of interest was also done to compute the adjusted odds ratio (AOR). In univariate analysis, variables with p value < 0.2 were included in multivariate logistic regression and a statistical significance was set at a p value < 0.05.

Ethical consideration

Ethical approval was obtained from Ethical Review Committee of the College of Health Sciences, Debre Tabor University (Approval number: 2044/2020). Official letter of cooperation was presented to the medical director of selected hospitals in order to facilitate data collection process. Informed verbal consent was also obtained from each respondent after explaining the purpose of the study. Participant’s confidentiality was kept by not recording their identifiers on the data collection formats.

Results

Socio-demographics and clinical characteristics of the study participants

A total of 423 patients with hypertension who met the inclusion criteria were included in the final data analysis. The mean age of the study participants was 58.48 years with a SD of 12.96. Among the study participants, women comprised the higher proportion (59.8%). The higher percentages of participants (58.6%) were unable to read and write. The mean (±SD) duration of hypertension treatment of the patients was 3.98 ±3.61 years ranging from half a year to thirty seven years, and 49.4% of the participants had at least one more disease in addition to hypertension. Details of other characteristics are available in Table 1.

Table 1

Socio-demographic and clinical characteristics of the study participants (N = 423).

Variables		Frequency (%)
Sex	Male	170 (40.2)
	Female	253 (59.8)
Age, mean (SD)		58.48±12.96
Resident	Rural	156 (36.9)
	Urban	267 (63.1)
Marital status	Single	27 (6.4)
	Married	287 (67.8)
	Divorced	32 (7.6)
	Widowed	77 (18.2)
Educational status	Unable to read and write	248 (58.6)
	Able to read and write	18 (4.3)
	Primary education	73 (17.3)
	Secondary school	32 (7.6)
	Higher education	52 (12.3)
Employment status	Farmer	70 (16.5)
	Merchant	77 (18.2)
	Daily laborer	3 (0.7)
	Retired	31 (7.3)
	Unemployed	196 (46.3)
	Government employed	46 (10.9)
Monthly income in ETB	<1500	106 (25.1)
	1500–2499	137 (32.4)
	≥2500	180 (42.6)
Do you have insurance	No	118 (27.9)
	Yes	305 (72.1)
Ever had hypertensive education	No	4 (0.9)
	Yes	419 (99.1)
Distance from hospital	<100 km	418 (98.8)
	≥100 km	5 (1.2)
Co-morbidity	Absent	214 (50.6)
	Present	209 (49.4)

Medication regimen complexity, adherence and blood pressure control

Hypertension-specific MRCI ranged from 2 to 12.5; more than half (55.8%) was categorized as low complexity, 40.9% as moderate complexity, and 3.3% as high complexity. Patient level MRCI ranged from 2 to 28; approximately one-fifth (20.5%) was categorized as low complexity, 44.7% as moderate complexity, and 34.8% as high complexity. Based on the Morisky 8 scale adherence measuring tool, 160 (37.8%) of the respondents were found to be adherent. Regarding to blood pressure control, the mean systolic and diastolic blood pressure reading were 132.34 (±18.21 SD) and 82.11 (+9.26 SD) mmHg, respectively. And majority of respondents (52.2%) were categorized as having good blood pressure control (Table 2).

Table 2

Percentage distribution of regimen complexity, adherence and blood pressure control (N = 423).

Variables	Study hospitals, n (%)				Total, n (%)
	DTCSH	NMWH	ADZH	MEYH
Hypertension-specific regimen complexity
Low	67 (44.7)	59 (59)	65 (65)	45 (61.6)	236 (55.8)
Moderate	77 (51.3)	37 (37)	34 (34)	25 (34.3)	173 (40.9)
High	6 (4)	4 (4)	1 (1)	3 (4.1)	14 (3.3)
Patient level regimen complexity
Low total	22 (14.7)	15 (15)	34 (34)	16 (21.9)	87 (20.5)
Moderate total	71 (47.3)	40 (40)	37 (37)	41 (56.2)	189 (44.7)
High total	57 (38)	45 (45)	29 (29)	16 (21.9)	147 (34.8)
Medication adherence
Adherent	83 (55.3)	18 (18)	56 (56)	3 (4.1)	160 (37.8)
Non adherent	67 (44.7)	82 (82)	44 (44)	70 (95.9)	263 (62.2)
Blood pressure control
Controlled	62 (41.3)	47 (47)	81 (81)	31 (42.5)	221 (52.2)
Uncontrolled	88(58.7)	53 (53)	19 (19)	42 (57.5)	202 (47.8)

DTCSH, Debre Tabor Comprehensive Specialized Hospital; NMWH, Nifas Mewcha Hospital; ADZH, Addis Zemen Hospital; MEYH, Mekane Eyesus Hospital.

Determination of the association between medication regimen complexity and other variables with adherence

According to multivariate logistic regression analysis result, those participants who can read and write, and those who completed their primary education were less likely to be adherent compared with those who completed their higher education (AOR = 0.19, 95% CI: 0.04–0.94, P = 0.042; AOR = 0.24, 95% CI: 0.08–0.74, P = 0.013, respectively). Being married, divorced, and widowed were more likely to be adherent compared to being single (AOR = 4.18, 95% CI: 1.18–14.77, P = 0.027; AOR = 5.27, 95% CI: 1.24–22.48, P = 0.025; AOR = 4.48, 95% CI: 1.16–17.41, P = 0.03, respectively). However, hypertension-specific MRCI (all low, moderate, and high regimen complexity) didn’t fulfill the inclusion criteria to be entered into multivariate logistic regression, and patient level regimen complexity, monthly income, residence, employment status, health insurance, and length of years since hypertension treatment) were not significantly related to adherence (Table 3).

Table 3

Determination of the association between predictive variables and adherence.

Variables		Level of adherence		OR (95% CI)
		Non-adherent	Adherent	COR	AOR
Patient level MRCI	Low total MRCI	49	38	1	1
	Moderate total MRCI	118	71	0.78 (0.46–1.3)	0.87 (0.50–1.51)
	High total MRCI	96	51	0.69 (0.4–1.18)	0.68 (0.38–1.22)
Residency	Urban	155	112	1	1
	Rural	108	48	0.62 (0.41–0.93)+	0.75 (0.44–1.26)
Marital status	Single	24	3	1	1
	Married	178	109	4.9 (1.44–16.65)+	4.18 (1.18–14.77)*
	Divorced	17	15	7.06 (1.76–28.24)+	5.27 (1.24–22.48)*
	Widowed	44	33	6 (1.66–21.63)+	4.48 (1.16–17.41)*
Educational status	Unable to read & write	152	96	0.46 (0.25–0.85)+	0.56 (0.18–1.74)
	Able to read & write	15	3	0.15 (0.04–0.57)+	0.19 (0.04–0.94)*
	Primary education	57	16	0.21 (0.09–0.45)+	0.24 (0.08–0.74)*
	Secondary education	17	15	0.65 (0.27–1.57)	0.67 (0.25–1.84)
	Higher education	22	30	1	1
Employment status	Farmer	50	20	0.4 (0.18–0.87)+	0.81 (0.24–2.77)
	Merchant	54	23	0.43 (0.2–0.91)+	1.05 (0.34–3.23)
	Daily laborer	1	2	2 (0.17–23.62)	1.92 (0.13–27.85)
	Retired	15	16	1.07 (0.43–2.65)	1.23 (0.44–3.43)
	Unemployed	120	76	0.63 (0.33–1.21)	0.95 (0.32–2.82)
	Government employed	23	23	1	1
Monthly income	< 1500 birr	62	44	1.02 (0.62–1.66)	1.04 (0.58–1.89)
	1500–2499 birr	95	42	0.63 (0.4–1.01)	0.78 (0.46–1.34)
	≥ 2500 birr	106	74	1	1
Health insurance	Yes	67	51	1	1
	No	196	109	1.37 (0.89–2.11)	.087 (o.49-1.52)
Length of treatment	< 5 years	183	100	0.73 (0.48–1.1)	(9.54–1.32)
	≥ 5 years	80	60	1	1

+ Stands for variables significant at p <0.2;

*Stands for variables which are significant at p value less than 0.05 in multivariate analysis.

Determination of the association between medication regimen complexity and other variables with blood pressure control

Having low hypertension-specific MRCI was four fold more likely to have controlled blood pressure level compared with having high hypertension-specific MRCI (AOR = 4.38, 95% CI: 1.08–17.84, P = 0.039). From other variables, being non-adherent, and not having health insurance were negatively related to controlled blood pressure in adjusted analyses (AOR = 0.51, 95% CI: 0.32–0.79, P = 0.003; AOR = 0.47, 95% CI: 0.27–0.82, P = 0.008, respectively). Additionally, having monthly income of less than 1500 birr, and from 1500 to less than 2500 birr were negatively related to controlled blood pressure in adjusted analyses (AOR = 0.41, 95% CI: 0.22–0.78, P = 0.006; AOR = 0.57, 95% CI: 0.33–0.99, P = 0.044, respectively). In contrast, participants who were unable to write and read were three times more likely to have controlled blood pressure compared to participants who had higher education level (AOR = 3.34, 95% CI: 1.05–10.65, P = 0.041). However, patient level regimen complexity, and other variables (sex, age, marital status, doing aerobic exercise, employment status and having co-morbidity) were not significantly related to blood pressure control in adjusted analyses (Table 4).

Table 4

Determination of the association between predictive variables and blood pressure control.

Variables		Blood pressure		OR (95% CI)
		Uncontrolled	Controlled	COR	AOR
Hypertension specific MRCI	Low MRCI	98	138	5.16 (1.40–18.99)+	4.38 (1.08–17.84)*
	Moderate MRCI	93	80	3.15(0.85–11.70)	2.67 (0.67–10.56)
	High MRCI	11	3	1	1
Patient level MRCI	Low total MRCI	31	56	2.16(1.25–3.72)+	1.38 (0.70–2.76)
	Moderate total MRCI	91	98	1.29 (0.84–1.98)	1.10 (0.68–1.80)
	High total MRCI	80	67	1	1
Age	<60 years	109	101	0.72 (0.49–1.05)	1
	≥60 years	93	120	1	0.79 (0.49–1.28)
Marital status	Single	16	11	1	1
	Married	143	144	1.47 (0.66–3.27)	1.44 (0.61–3.39)
	Divorced	12	20	2.47 (0.85–6.92)	2.15 (0.69–6.63)
	Widowed	31	46	2.16 (0.88–5.27)	2.19 (0.79–6.07)
Educational status	Unable to read & write	112	136	1.66(0.91–3.03)	3.34 (1.05–10.65)*
	Able to read & write	8	10	1.71(0.58–5.02)	2.9 2(0.65–13.02)
	Primary education	38	55	1.26(0.61–2.57)	1.93 (0.62–6.05)
	Secondary education	14	18	1.75 (0.72–4.27)	2.62 (0.89–7.67)
	Higher education	30	22	1	1
Employment status	Farmer	31	39	1.64 (0.77–3.46)	0.7 (0.21–2.37)
	Merchant	35	42	1.56 (0.75–3.26)	0.88 (0.29–2.73)
	Daily laborer	111	220	2.60 (0.22–30.75)	0.44 (0.03–6.91)
	Retired	11	20	2.36 (0.93–6.04)	1.47 (0.49–4.39)
	Unemployed	98	98	1.30 (0.68–2.48)	0.51 (0.17–1.57)
	Government employed	26	20	1	1
Monthly income	< 1500 birr	59	67	0.56 (0.34–0.90)+	0.41 (0.22–0.78)*
	1500–2499 birr	69	68	0.69 (0.44–1.08)	0.57 (0.33–0.99)*
	≥ 2500 birr	74	106	1	1
Health insurance	Yes	133	172	1	1
	No	69	49	0.55 (0.36–0.85)+	0.47 (0.27–0.82)*
Adherence status	Adherent	61	99	1	1
	Non-adherent	141	122	0.53 (0.36–0.80)+	0.51 (0.32–0.79)*
Aerobic exercise	Yes	38	60	1	1
	No	164	161	0.61 (0.39–0.99)+	0.70 (0.40–1.23)

+Stands for variables significant at p <0.2;

*Stands for variables which are significant at p value less than 0.05 in multivariate analysis.

Discussion

The current study aimed to determine MRCI and its association with adherence, and blood pressure control. This study used a validated 65 item MRCI tool for computing medication regimen complexity among patients with hypertension. As far as we know, there was no such type of study in Africa before, so this study was the first study in Africa. About 3% and 35% of patients in this study had high hypertension-specific MRCI and high patient level MRCI, respectively according to a category of the MRCI score. The mean (±SD), and median (range) of hypertension MRCI was 4.66 ± 1.75, and 4 (2–12.5), respectively. This result was higher than the findings from the previously done researches using 65-item MRCI as a complexity measuring tool [17,18].

Before the coming of 65-item MRCI, medication regimen complexity was computed employing a simple count of medicines within which it fails to catch many components of medicines leads to not adequately showing medication regimen complexity [16]. A validated tool called MRCI which is a 65-item instrument was employed in our study to determine medication regimen complexity which will be computed from data collected from patient’s medical chart [13]. Number of drugs, drug dosage forms, dosage frequency, and other instructions contribute to medication regimen complexity levels. In the present study, the prevalence of high regimen complexity was higher in patient-level complexity compared with hypertension-specific complexity, One might argue that the total patient-level regimen complexity should reveal the level of antihypertensive regimen complexity since patient-level MRCI contains the hypertension-specific MRCI. Nevertheless, the scoring could be affected by the gathering of other prescriptions and non-prescription drugs which frequently outshines the antihypertensive component. Therefore, a high patient-level MRCI might not surely arise from a high hypertension-specific MRCI. Hence, patient level MRCI includes all prescriptions and non-prescription medications, which is critical to judge, even when a selected disease treatment goes to be addressed. Earlier study showed that patient-level MRCI scores were greater than disease-specific scores for every patient group [17].

In the present study, 37.8% of the sampled population had high adherence to their antihypertensive medications evidenced in MMAS-8 score of 8. This finding is equivalent to the results of studies in Nigeria 36.8% [29], 12 Sub-Sahara African countries 35.6% [30], and Central Ethiopia 36.0% [31]. However, the result of this study is higher than the findings of the studies in Saudi Arabia 22.5% [32], West Ethiopia 31.4% [33], and Shashemene in Ethiopia 16.2% [34]. The discrepancy may be due to the difference in sample size, and socio-demographic characteristics of the study participants. The sample size was lower in studies done in Saudi Arabia (n = 204), West Ethiopia (n = 172) and Shashemene (n = 197) compared to the sample size of our study (n = 423). Some patients also were smokers in studies of Saudi Aradia and West Ethiopia. And the extent to engage in self-care practice may vary from individual to individual even within the same community due to religious view, economic status, and perception of individuals.

The contribution of complex medication regimens to non-adherence may be more than the total number of drugs taken do. Therapeutic regimen features like dosage frequency, dosage forms, and other instructions could significantly affect adherence principally in hypertensive patients [19]. However, as far as we know, medication regimen features are not taken into account as a possible factors affecting adherence in the globe including Ethiopia.

In our study, hypertension specific and patient level MRCI was not significantly associated with adherence. Adherence was found to be more likely in patients who married, divorced and widowed in this study compared to those patients with single marital status (AOR = 4.18, 95% CI: 1.18–14.77, P = 0.027; AOR = 5.27, 95% CI: 1.24–22.48, P = 0.025; AOR = 4.48, 95% CI: 1.16–17.41, P = 0.03, respectively). This finding is in line with the results of the studies in Indiana [6], and hospitals of Jimma Town [35]. The current study revealed that having lower education levels were less likely to be adherent to medications compared with those having higher education level. This result is in agreement with the findings of the previous studies in Korea [36], and hospitals of Jimma Town [35].

Our study found that 52.2% of patients had controlled blood pressure according to the Eighth Joint National Committee (JNC8) criteria [26]. This finding is higher than the results of previous studies in different part of Ethiopia with the same cut off points for the definition of controlled blood pressure [23,37]. The disagreement of findings may be due to difference in sample size, socio-demographic characteristics, and lifestyle practice of study participants. In study conducted at Debre Tabore General Hospital, some patients were smokers, percentage of female patients (51.2% versus 60.8%) and the sample size was lower (n = 346 versus 423) than the sample size of our study. The study conducted in Addis Ababa had some patients who smoke lower percentage of female patients than the present study. On the other hand, the result of the current study is lower than the findings of previous studies in Ethiopia [38,39]. The discrepancy of these findings may be justified by the difference in magnitude of co-morbidity, socio-demographic characteristics, and lifestyle practice of study participants. The percentage of female patients and mean age was lower in studies done at Gondar University Hospital, presence of comorbid illness and illiterate patients were lower in study done at Nekemte compared to the current study. Plus the extent of practicing recommended life style factors may vary from community to community as well as individual to individual.

High MRCI may affect treatment effectiveness and patient safety possibly by contributing to non-adherence. Non-adherence could be explained by not taking the medications, the use of under or overdoses of medications [20]. Moreover, the negative impacts of non-adherence on blood pressure control have been established [21,22]. In line with this idea, low hypertension specific MRCI was significantly associated with controlled blood pressure. In this study, patients with low hypertension specific MRCI was four times more likely to have controlled blood pressure compared with patients with high hypertension specific MRCI (AOR = 4.38, 95% CI: 1.08–17.84, P = 0.039). Being non-adherent was found to be less likely to have controlled blood pressure compared to being adherent in the present study (AOR = 0.51, 95% CI: 0.324–0.79, P = 0.003). This finding is in line with the findings of other studies [24,38,39].

Our study found that having monthly income of less than 1500 birr, and from 1500 to less than 2500 birr were less likely to have controlled blood pressure compared to having higher monthly income (AOR = 0.41, 95% CI: 0.22–0.78, P = 0.006; AOR = 0.57, 95% CI: 0.33–0.99, P = 0.044, respectively). This is happened due to patients with lower income may be unable to fully access medications, so become non-adherent, in turn, non-adherent could cause uncontrolled blood pressure [30]. In addition, in our study, those not having health insurance were less likely to have controlled blood pressure compared to those having health insurance (AOR = 0.47, 95% CI: 0.27–0.82, P = 0.008). This result is similar with the result of another study done in United States of America [40].

It is logical as education level increases, adherence to medications, and self-care practices could be increased and in turn, these lead to improvement of blood pressure control. In contrast to this logic, our study showed that those unable to write and read were more likely to have controlled blood pressure compared to those having higher education level (AOR = 3.34, 95% CI: 1.05–10.65, P = 0.041). This finding is supported by the result of another study conducted in Addis Ababa [37].

The crucial components of medication regimen complexity are the type of dosage form, the number of medications per day, dose frequency, and other instructions. But these crucial components have not been sufficiently addressed in the earlier studies. Furthermore, medication regimen complexity was not taken into account as an influential factor in achieving optimal adherence and blood pressure control. Therefore, being the first research in Africa that calculates medication regimen complexity and its association with adherence and blood pressure control by employing a validated instrument is the strength of the present study. Nevertheless, our research has a limitation of that MRCI was calculated using only medications ordered and recorded in the patients’ medical chart. Therefore, any medicines or directions not documented were missed.

Conclusion

Among participants, 3.3% had high hypertension-specific medication regimen complexity. The prevalence of high patient level MRCI was found to be higher than that of high hypertension-specific MRCI. Being married, divorced, and widowed were more likely to be adherent compared to being single. Additionally, being adherent to medications was less likely in patients having lower education level. Low hypertension specific MRCI and being unable to write and read were significantly associated and more likely to have controlled blood pressure in adjusted analyses. Being non-adherent, having lower monthly income, and not having health insurance were less likely to have controlled blood pressure. In the current study, majority of patients were not adherent to their medications, and about half of participants had controlled blood pressure. Carefully organized information about benefit of adherence and the negative impact of non-adherence should be provide for patients in order to improve adherence level and controlled blood pressure. Simplification of a complex medication regimen for patients with hypertension should be sought by physicians and pharmacists to improve blood pressure control.

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20 May 2022

Medication regimen complexity and its association with adherence and blood pressure control among hypertensive patients at selected Hospitals of South Gondar Zone: A hospital based cross sectional study

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26 Jul 2022

Medication regimen complexity and its association with adherence and blood pressure control among hypertensive patients at selected Hospitals of South Gondar Zone: A hospital based cross sectional study

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PONE-D-21-37608R1

Medication regimen complexity and its association with adherence and blood pressure control among hypertensive patients at selected Hospitals of South Gondar Zone: A hospital based cross sectional study

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