Adherence to TB treatment remains low during continuation phase among adult patients in Northwest Ethiopia

An Institutional based cross-sectional study was conducted with adult TB patients in the continuation treatment phase from March 9 to May 30, 2019. It was supplemented with qualitative data to explore the lived experiences and perspectives of the healthcare providers on patient adherence during the continuation phase.

The study was conducted in 9 districts of Central Gondar Zone and Gondar town administration in Northwestern Ethiopia. Namely, Gondar Zuria, Tach Armachio, Wegera, East Dembia, West Belesa, Takusa, East Belesa, Alefa, and Gondar town administration were included in the study. The study area consists of 74 functional public health facilities (Health centers and Hospitals) serving approximately 2.9 million people in the area. Primary healthcare units that involves Health posts, Health Centers and district hospitals are mandated to provide TB treatment and care. In each health facility, a TB clinic has been established with at least one TB focal healthcare provider to regularly manage cases and follow their treatment. TB focal healthcare provider is a healthcare provider that received additional short-term training on TB and permanently assigned to TB Clinic.

The study population included all adult (≥18 years) TB patients enrolled in the continuation treatment phase as eligible participants. Patients with Multi-drug-resistant Tuberculosis (MDR-TB) and Extensively Drug-resistant Tuberculosis (XDR-TB) were not included in the study due to the distinct treatment period and approaches. All healthcare providers who were assigned as TB focal person in TB clinics were eligible for the key-informant interview.

We calculated the sample size using a single population proportion formula with assumptions, including, proportion of patients adherent to TB medications (P = 66%) during the continuation phase [19]; margin of error (d = 5%), and 1.5 design effect. Considering the finite population and 10% non-response rate, the final sample size was 331 TB patients selected from 22 health facilities in the 9 districts. Facilities were randomly selected stratifying by urban (town administrations) and rural settings. All eligible TB patients were included during the study period. Nine TB focal healthcare providers were purposively selected for key-informant interview from nine different health facilities.

In this study, socio-demographic characteristics, disease characteristics, TB treatment-related knowledge, and attitude, provider-patient relationship using below and above the average score as a cut-off values. Family wealth quantiles were also included as predictor variables. We used an interviewer-administered questionnaire for socio-demographic, behavioral, and treatment adherence related data using Amharic (local language). But the treatment related information was taken from TB unit registers. The internal consistency of the tool was checked through piloting, hence, the Cronbach’s α value found to be 0.769, which was approaching well with the cut of value [28]. The content and face validity were also evaluated by six senior domain experts selected from TB treatment centers, TB experts in health offices, and behavioral researchers in research and teaching institutes. We trained and employed six data collectors and two supervisors. We assessed patients’ TB treatment-related knowledge using 8 questions that include, TB curability, how to confirm cure of the disease, TB treatment period, refilling time and adherence, feeding practice, side-effects, and treatment supporter’s role. Those patients who scored above the median value were determined as good knowledge [17, 19, 29, 30]. Similarly, a 4 attitude questions that include, patient trust on TB medication, medication related misconceptions, value for medication and belief of cure were used to assess attitude towards TB treatment [19, 20]. Those patients who score above the median value of attitude questions were determined as good attitude towards TB treatment. In order to measure provider-patient relationship, we used a 6 questions that include ways of communication, [19] were adapted from literatures. The family wealth quantiles (lowest, second, middle, fourth, highest) was constructed from multiple items including household assets, services, and facilities [31]. Then for simplicity of analysis, we merged into three outcomes (poor, middle and rich) by categorizing below middle quantiles into poor, middle quantiles as it is and above the middle quantiles into rich.

For the qualitative data, a semi-structured key informant interview guide was used to explore the existing provider-patient relationship and support during the continuation treatment phase. Participants were asked mainly about their opinion on which TB treatment phase is the risk for non-adherence? Why non-adherence to TB treatment was high on the specified phase? How was the communication and relationship between patients and healthcare providers? And how effective was the community-based treatment support system? The key-informant interview was recorder for audio after getting consent from each participants.

To assess adherence to TB treatment during continuation phase we deployed a short (11 questions) version of the Adherence to Refill and Medication Scale (ARMS) [32]. The original ARMS tool consists of 12 questions with two subscales, 8 questions about medication-taking, and 4 questions about refilling [33]. One of the items, “How often do you forget to take your medicine when you are supposed to take it more than once a day?” was not relevant to TB medication, since TB pills often are taken once a day. Each of the items were structured as a Likert scale with responses of “none,” “some,” “most,” or “all” of the time, which were given values from 1 to 4.

We used a Principal Component Analysis (PCA) technique to compute the family wealth index quantile separately for urban and rural depending on assets and services specific to the urban and rural population [31].

Adherence to TB treatment was measured using the short (11 questions) version ARMS values that range from 1= “none of the time” to 4=“all of the time”. One item was reverse coded then the overall adherence score ranges from 11 to 44. The lower scores indicate better adherence and the higher score represents a higher level of non-adherence, items were asking about how frequently failed to adhere to specific elements [33]. The scales were further transformed into dichotomous outcomes using the recommended classification (scored 11 as adhered and > 11 as non-adhered) [32, 33].

We used the Variance Inflation Factor (VIF) to check the multicollinearity effect among predictor variables [34]. We conducted a single-level analysis using binary logistic regression to identify factors that are associated with adherence to TB treatment during the continuation phase. The Crude Odds Ratio (COR) and Adjusted Odds Ratio (AOR) with 95% CI and p value < 0.05 were computed using STATA version 14 software to determine statistical significance of the association between predictor and outcome variables.

For the qualitative data analysis, we transcribed the audio data into the Amharic language by experts in the field and translated into English by fluent speakers. After familiarization with the transcript, we assigned codes inductively and deductively and categorized into themes. We examine patterns, relationships, contradictory responses, and gaps in understanding in each theme. Quotes were selected and presented for norms of the participants’ shared perceptions.

In this study, a total of 307 participants (92% response rate) were interviewed. More than half of the participants 178 (58.0%) were males. Of the total participants, 110 (35.8%) were aged between 35 and 44 years. The median age of the participants was 29.0 years with a minimum of 18 and a maximum of 84 years. Regarding marital status, 142 (46.3%) of the participants were single. The majority, 285 (92.8%) of them were Orthodox Christian followers. Of the total participants, 220 (71.7%) were urban residents. Among the participants, 101 (32.9%) could not read and write. The family asset evaluation shown that 62 (20.2%) were in lowest quantile. One hundred twenty two (39.7%) of the participants did not have a mobile phone at all (Table 1).

Of the nine key-informants, seven were selected from Health Centers and two from Hospitals. Six were males. The age of the participants ranged from 26 to 40 years. Only three of the participants had a first degree and above. Working experience ranged from 6 months to 7 years in TB clinic.

Overall, 197 (64.2%) of the participants were adherent (95% CI 58.6–69.4%) to TB treatment during continuation phase. The finding showed that 65 (34.8%) of pulmonary TB and 45 (37.5%) of extra pulmonary TB cases were adherent to TB treatment during continuation phase. One hundred three (35.9%) new and 7 (35.0%) repeated treatment cases were adherent to TB treatment (Table 2).

Focal TB healthcare providers were asked about “which treatment phase has a higher risk of non-adherence to the treatment?” Five of nine focal healthcare providers agreed that non-adherence to TB treatment worsens during the continuation phase as compared with the intensive phase, where patients take their daily pills at the clinic directly observed by the healthcare provider. One male TB focal healthcare provider replied that:

“… when patients enrolled in the continuation phase, they often get reluctant to their pills. Let alone daily medication, they even miss weekly refilling appointments, however, during the intensive phase, they come to take their pills on time”

The univariate logistic regression analysis showed that patient age, educational level, distance to the health facility, provider-patient relationship, patient knowledge on TB treatment, and family wealth index were associated with adherence to TB treatment during the continuation phase.

Whereas, in the multivariable binary logistic regression analysis, patients’ educational level, provider-patient relationship, patient knowledge on TB treatment, and family wealth index were associated with the outcome variable. Secondary level educated patients were about four times more likely to adhere to TB treatment as compared to non-educated patients (AOR = 4.138, 95% CI; 1.594–10.740). Similarly, patients who reported good provider-patient relationships were about two times more likely to adhere to the treatment than their counterparts, with (AOR = 1.863, 95% CI; 1.014–3.423). Those who have good knowledge of TB treatment were also more likely to adhere (AOR = 1.845, 95% CI; 1.012–3.362). Patients with middle family wealth were about three times more likely to adhere than patients with poor family wealth (AOR = 2.646, 95% CI; 1.360–5.148) (Table 3).

Patients who were non-adherent to their TB medication were asked for their reasons for failure to treatment adherence. More than half (58%) of 110 non-adherent participants reported forgetfulness to daily medication, 17.3% reported traveling away from home without pills, 8.2 and 5.5% were due to feeling sick and fearing side effects of the drugs, respectively (Fig. 1).

TB focal healthcare providers were also asked for their perspectives about contributing factors for non-adherence to TB treatment. Poor communication and relationship with their patients, transportation and related costs for pill refilling, relapsing of the disease, political unrest, and poor treatment support at the community were found major contributing factors for non-adherence to TB treatment during the continuation phase.

All respondents agreed that good communication and relationship was essential for patient adherence to TB medications. However, about half (4/9) of participants reported that their communication with patients declined as the patients shifted from the intensive phase (facility-based treatment) to the continuation phase. Another male TB focal healthcare provider also added that:

“During the continuation phase, we do not have daily contact with patients as we do on intensive phase. Even, weekly attendance was not easy. Some patients did not come, they send their supporter/family member to the clinic for refilling, and they were busy with family matters, social events like a funeral.”

In the key-informant interview, the majority of TB focal providers also exemplified that patients with low income tend to miss and/or interrupt refilling due to transportation and related costs. Besides, relapse cases tend to default treatments. A female TB focal healthcare provider replied that

“TB patients on continuation phase often miss refilling and from my experience, their reasons are mainly related to transportation cost and unintended social events”.

Participants also mentioned that relapsing cases tend to lost-to-follow-up. Another female focal healthcare provider added that:

“This year alone we lost two patients due to relapse of the case [TB]. One female insisted not to take the pills anymore and decided to go to Monastery. Similarly, one male patient lost from treatment follow-up …”

Political unrest and security problems were among the challenges for the patient, the health facility, and central drug suppliers (hubs for supplying drugs based on the health facilities’ need). A male TB focal healthcare provider replied that

“Our community was victimized with frequent political turmoil and security problems which results in lost-to-follow due to massive displacement, migration of healthcare providers, and interruption of drug supply from the center.”

Respondents were also asked their opinion on whether the assigned treatment supporters were helpful during the continuation treatment phase. Seven of nine participants replied that they were not helpful as intended, and (2/9) reported as helpful. The problem begins with assigning treatment supporters. A male TB focal healthcare provider reported that:

“During assigning treatment supporters, patients often choose educated relatives without considering the distance away from their home: mostly, they choose their relatives in urban while the patient living in rural.”

In addition, the commitment of treatment supporters was confronted by their income level and their prior commitments as reported by the respondents. A male TB focal healthcare provider mentioned that:

“Treatment supporters very rarely accompany patients during refilling, they mention transportation cost, own family, and social commitments.”

Another male TB focal healthcare provider also added that:

“During the continuation phase, we assign treatment supporters but in practice, most did not follow and most focal providers lack skills to influence patients to take their pills at home”

This study specifically focused on continuation treatment phase that could give insight for policy, program and delivery of TB treatment and care. The limitation of the study includes use of self-reported adherence that often distort the problem due to recall and social desirability biases. Our study participants were enrolled from public health centres and hospitals. We did not address patients at private health facilities and health post levels. This could affect the generalizability of the study findings to the wider context. The ARMS tool looks to have very strict criteria in classifying adherence level. As a result, the level of adherence could be underestimated. We did not address all possible predictors of adherence to TB treatment during continuation phase. ARMS tool do not allow to classify adherence at data collection stage, it classifies after data analysis. Therefore, we asked about patient reasons for non-adherence to TB medication based on those missed one or more doses.