The human immune deficiency virus (HIV) epidemic remains a public health threat and a leading cause of morbidity and mortality in Tanzania. Retaining patients to HIV care is thought to be the biggest challenge facing HIV programs. Since the adoption of the multi-month scripting (MMS) strategy in Tanzania, no study has evaluated its functionality and impact on patients’ retention to care. Therefore, we designed this study to assess the impact of MMS on patient retention of care since its adoption in 2018. This retrospective open cohort study used secondary data from the CTC 3 macro database for patients receiving antiretroviral therapy (ART) in Mwanza between June 2018 and June 2020. The main outcome was patient retention during HIV care. Kaplan-Meier plots were constructed and compared using the log-rank test. Cox proportional hazard regression was used to adjust for potential confounders associated with patient retention in HIV care. Of the 21,742 patients included in the analysis, 14,064 (64.6%) were female, the median age and interquartile range were 35.9 ± 16.7 years and 11,986 (55.1%) were married. Most patients 18,401 (85.5%) received care from public health facilities and 12,573 (57.8%) had WHO clinical stage I disease. The probabilities of retention in HIV care were higher among HIV patients kept in ART MMS as compared to non-MMS group (log rank χ2 = 330.7, P < 0.001), and median survival times were 14 (95% CI: 13.9–14.2) and 11 (95% CI: 10.9–11.4) months, respectively. Factors associated with attrition included non-MMS (adjusted hazard ratio [aHR]: 1.40, 95% CI: 1.35–1.45, P < 0.001), being single (aHR = 1.05, 95% CI: 1.02–1.09, P = 0.002), and young age (15–24 years) (aHR = 1.21, 95% CI: 0.90–1.32, P < 0.001). Retaining HIV-stable patients into care was achieved by using ART MMS. Improvements in retention to care among stable HIV patients may be attained by addressing the challenges hindering patients at 15–24 years. The National AIDS Control Program (NACP) should further promote this strategy by ensuring that health-care providers adhere to the guidelines and keep eligible patients in ART MMS.

Worldwide, more than thirty-seven million people were living with human immunodeficiency virus (HIV) in 2020, with over 90% of them living in sub-Saharan Africa. However, the annual number of new HIV infections globally has been decreasing gradually from 2.1 million in 2010 to 1.5 million in 2020, which is more than a 16% reduction [1]. This is a big step toward achieving control of the HIV/AIDS pandemic by 2030.

Human immunodeficiency virus treatment is an important tool to end the HIV/AIDS pandemic. Ending HIV/AIDS requires uninterrupted access to lifelong treatment with highly active antiretroviral drugs (HAART), good adherence to long-term treatment, and sustainable viral load suppression. Available evidence shows that early initiation of ART, good adherence, and retention to therapy reduces mortality and HIV progression to AIDS by 75%. While achieving optimal and sustainable HIV viral suppression after the use of ART use reduces transmission by 96.4% [2, 3].

In 2018, the Ministry of Health, through the National AIDS Control Program (NACP), adopted a nationwide initiative to lengthen prescribing intervals for HIV antiretroviral therapy (ART) known as multi-month scripting (MMS). In this model, patients who are on ART for more than 6 months, aged 5 years and above, on first- or second-line ART, have demonstrated good adherence (>95% by pill count) to lifelong treatment, and recent undetectable viral load (<50 viral copies per ml) are categorized as stable. Those who did not meet the set criteria were classified as unstable. Stable patients were moved from monthly prescription intervals to 6 months of ART prescription (MMS) with 3 or 6 months of dispensing. Tanzania adopted MMS to respond to the growing burden to health-care system due to frequent visits and growing evidence of MMS improving retention in other parts of Africa [4].

Patients under the MMS strategy have 2 clinical visits per year, where they undergo thorough clinical evaluation, including testing for HIV viral load annually. At the initial MMS visit, stable patients are dispensed with 90 days ART pills and will be given two other prescriptions to be used during their refill visits. On the refill visits, patients will only be seen by the pharmacist or ART nurse, and he/she will not wait in the queues, thus fast tracking the service. It is also allowed by treatment guidelines to send a treatment supporter to collect ART during the refill visit [4]. The aim of Tanzania to adopt this model was to reduce the number of clinic visits, reduce the burden of scarce human resources for health, improve the quality of care, and maximize client retention in HIV care.

From the study conducted in Ethiopia on the clients and health-care providers perception of the MMS, it was noted that participants perceived benefits of the MMS being time and cost serving, fewer work interruption, reduced stigma, and hence improved chances of retention to HIV care [5]. Evidence from other studies also suggest that MMS reduced missed appointments and the cost of transportation while improving retention and viral load suppression [6, 7].

Since the adoption of the MMS strategy in Tanzania, no study has evaluated its functionality and impact on patients’ retention of care. According to the UNADS report, patient retention to care was the greatest single challenge facing efforts to achieve the ambitious goal of 95-95-95 targets that aim to end the AIDS epidemic by 2030 [8]. Therefore, we designed this study to assess the impact of MMS on patient retention of care since its adoption in 2018.

Study design

This was a retrospective open cohort study using routinely collected secondary data from the NACP CTC 3 macro database with a follow-up period of 24 months from June 2018 to June 2020.

Study setting

This study involved HIV care and treatment centers in the Mwanza region, which is in northwestern Tanzania. The prevalence of HIV was reported to be 7.2% in the Tanzania HIV Impact Survey of 2017, which was higher compared to the national prevalence of 4.6% [9]. The region has 219 facilities scattered across 8 councils offering HIV care and treatment, with approximately 91,545 patients currently undergoing treatment.

Data source

The study used secondary data extracted from the electronic CTC 3 macro database harbored by the NACP of the Ministry of Health. This system receives data from the CTC 2 electronic database, which is widely used to record all HIV-infected patients who have ever been enrolled in care. The database was updated daily at the facility level based on patient charts. The registry includes all demographic, laboratory, and ART information, and patient status (dead, on care, or lost to follow-up).

Subjects

The study compared clients who were eligible for MMS and received MMS with those eligible but didn’t receive MMS. This study population comprised HIV-positive patients aged ≥15 years who received HAART from care and treatment facilities in the Mwanza region from June 2018 to June 2020. They had recent viral load results of <50 copies/ml, good adherence to treatment, not on TB treatment or pregnancy, and on ART for >6 months during the study onset. Patients missing the earlier mentioned criteria were excluded from the analysis.

Definitions of variables

The length of ART prescription was the number of days (months) ART drugs were dispensed to a patient when they last visited the care and treatment facility. Not seen for 3 or more months (90 days) since the last scheduled appointment and not classified as dead were considered lost to follow-up. Patients categorized as stable and offered 6-month prescriptions of ART with 3 months of dispensing and only 2 clinical visits per year were on multi-month prescription and dispensing (MMS). Retention in care was measured by loss to follow-up with the dichotomous measure of any “lost to follow-up” (no = retained).

Outcomes

The main outcome was patient retention during HIV care. Because patients classified as stable and kept in MMS should have good adherence to the clinical schedule, follow-up for the retention analysis began after their minimum visit during the study period and ended in June 2020, whichever came first.

Statistical analysis

The study participants’ demographics and clinical characteristics during the analysis time were computed and presented in frequencies and proportions. The chi-square test was used to compare categorical data, and Kaplan-Meier plots were constructed and compared using the log-rank test. Cox regression modeling was performed to adjust for potential confounders. Statistical analyses were performed using STATA version 15 software.

Ethical consideration

This study adhered to existing standard ethical guidelines and obtained ethical clearance from the MUHAS Senate Research and Publication Committee after review and approval number MUHAS-REC-12-2020-435. The Ministry of Health Community Development, Gender, Elderly, and Children granted permission to conduct the study through the NACP. This study analyzed secondary data that were routinely collected by the National AIDS Control program; thus, consent for participation from patients was not sought, and exemption criteria set by the Ethics Review Board were applied for analysis of routinely collected clinical data. No access to patient identification, such as names or unique CTC cards, was granted since the analysis was performed using a special NACP analytic server.

Demographic characteristics of the study participants at the time of analysis

In this study, 21,742 HIV-infected adults on ART from June 2018 to June 2020 were included in the analysis. The median age and interquartile range of the study participants were 35.9 ± 16.7 years and females constituted more than 64.6% of the studied population. Most of the study participants were married 11, 986 (55.0%) and 18,401 (85.5%) received care from public health facilities (Table 1).

Table 1.

Demographic characteristics of the study participants at the time of analysis

Non-MMS (N = 3,437)MMS (N = 18,305)
VariableNumber (%)Number (%)
Sex 
 Male 730 (21.2) 6,948 (37.9) 
 Female 2,707 (78.8) 11,357 (62.1) 
Marital status 
 Single 642 (18.7) 3,587 (19.6) 
 Married 1,933 (56.2) 10,053 (54.9) 
 Divorced 258 (7.5) 1,722 (9.4) 
 Widow/Widower 88 (2.6) 721 (3.9) 
 Cohabiting 27 (0.8) 81 (0.4) 
 Missing 489 (14.2) 1,141 (11.7) 
Age group (years) 
 15–24 382 (11.1) 1,111 (6.1) 
 25–34 1,199 (34.9) 4,610 (25.2) 
 35–44 786 (22.9) 4,736 (25.9) 
 45+ 1,070 (31.1) 6,152 (42.8) 
Health facility ownership 
 Faith-based organization 290 (8.4) 2,189 (11.9) 
 Private 170 (4.9) 692 (3.8) 
 Public 2,977 (86.6) 15,424 (84.3) 
Facility types 
 Health centre 1,159 (33.7) 5,916 (32.3) 
 Hospital 1,380 (40.1) 7530 (41.1) 
 Others 898 (26.1) 4,859 (26.5) 
Non-MMS (N = 3,437)MMS (N = 18,305)
VariableNumber (%)Number (%)
Sex 
 Male 730 (21.2) 6,948 (37.9) 
 Female 2,707 (78.8) 11,357 (62.1) 
Marital status 
 Single 642 (18.7) 3,587 (19.6) 
 Married 1,933 (56.2) 10,053 (54.9) 
 Divorced 258 (7.5) 1,722 (9.4) 
 Widow/Widower 88 (2.6) 721 (3.9) 
 Cohabiting 27 (0.8) 81 (0.4) 
 Missing 489 (14.2) 1,141 (11.7) 
Age group (years) 
 15–24 382 (11.1) 1,111 (6.1) 
 25–34 1,199 (34.9) 4,610 (25.2) 
 35–44 786 (22.9) 4,736 (25.9) 
 45+ 1,070 (31.1) 6,152 (42.8) 
Health facility ownership 
 Faith-based organization 290 (8.4) 2,189 (11.9) 
 Private 170 (4.9) 692 (3.8) 
 Public 2,977 (86.6) 15,424 (84.3) 
Facility types 
 Health centre 1,159 (33.7) 5,916 (32.3) 
 Hospital 1,380 (40.1) 7530 (41.1) 
 Others 898 (26.1) 4,859 (26.5) 

Clinical characteristics of the study participants at the time of analysis

Most of the studied individuals had WHO clinical stage I disease 12,573 (57.8%). Of the study participants, only 1,859 (8.6%) had their CD4 count documented in the system, of which 550 (29.5%) had CD4 count of <200 cells/µl and 981 (57.7%) had CD4 count of >350 cells/µl (Table 2).

Table 2.

Clinical characteristics of the study participants at the time of analysis

Non-MMS (N = 3,437)MMS (N = 18,305)
VariableNumber (%)Number (%)
WHO clinical stage 
 Stage 1 2,162 (62.9) 10,411 (56.9) 
 Stage 2 758 (22.5) 4,520 (24.7) 
 Stage 3 429 (12.5) 2,976 (16.3) 
 Stage 4 54 (1.6) 347 (1.9) 
 Missing 34 (0.9) 51 (0.3) 
CD4 count (cells/µl) 
 <200 62 (1.8) 488 (2.6) 
 200–349 35 (1.1) 293 (1.6) 
 350+ 146 (4.3) 835 (4.5) 
 Missing 3,194 (92.9) 16,689 (91.2) 
BMI 
 Underweight 173 (5.1) 960 (5.2) 
 Normal 673 (19.6) 3,469 (18.5) 
 Obese 38 (1.1) 179 (0.9) 
 Missing 2,407 (70.0) 13,086 (71.49) 
Non-MMS (N = 3,437)MMS (N = 18,305)
VariableNumber (%)Number (%)
WHO clinical stage 
 Stage 1 2,162 (62.9) 10,411 (56.9) 
 Stage 2 758 (22.5) 4,520 (24.7) 
 Stage 3 429 (12.5) 2,976 (16.3) 
 Stage 4 54 (1.6) 347 (1.9) 
 Missing 34 (0.9) 51 (0.3) 
CD4 count (cells/µl) 
 <200 62 (1.8) 488 (2.6) 
 200–349 35 (1.1) 293 (1.6) 
 350+ 146 (4.3) 835 (4.5) 
 Missing 3,194 (92.9) 16,689 (91.2) 
BMI 
 Underweight 173 (5.1) 960 (5.2) 
 Normal 673 (19.6) 3,469 (18.5) 
 Obese 38 (1.1) 179 (0.9) 
 Missing 2,407 (70.0) 13,086 (71.49) 

Retention to HIV care probabilities

In this study, we observed higher retention probabilities among HIV patients kept in ART MMS than in the non-MMS group. The log-rank for the equity probability of survival function for MMS had a value of (log rank χ2 = 330.7, P < 0.001), indicating that there was a significant difference between the survival curves. Thus, stable HIV patients kept in MMS were more likely to be retained in care than the non-MMS group. (Figure 1).

Figure 1.

Kaplan-Meier curves showing HIV client retention in care estimates by MMS category among studied participants from June 2018 to June 2020.

Figure 1.

Kaplan-Meier curves showing HIV client retention in care estimates by MMS category among studied participants from June 2018 to June 2020.

Close modal

Crude and adjusted hazard ratios for attrition from HIV care among the study participants

In Cox regression analysis, the hazard ratios (HR) for loss to follow-up from HIV care were greater for non-MMS patients (HR: 1.40, 95% CI: 1.35–1.45), and the associations was maintained in the adjusted model (aHR: 1.47, 95% CI: 1.23–1.73). In the unadjusted Cox models, the hazard of attrition was also higher in those aged 15–24 years and progressively decreased with an increase in age, with those aged >45 years having the lowest attrition hazards. In addition, being single was weakly associated with loss to follow-up (aHR: 1.06, 95% CI: 1.02–1.09) and attrition rate of 72.3 per 1,000 personal months (Table 3).

Table 3.

Cox regression analysis comparing the rate of loss to follow-up from HIV care among the study participants

CrudeAdjusted
VariableAttrition Rate/1,000 pmHR (95% CI)P-ValueHR (95% CI)P-Value
MMS category 
 MMS 69.4 ref  ref  
 Non-MMS 85.2 1.40 (1.35–1.45) <0.001 1.47 (1.23–1.73) <0.001 
Age (years) 
 15–24 87.3 1.21 (0.90–1.32) 0.020 1.24 <0.001 
 25–34 74.0 0.70 (0.59–0.83) <0.001 0.75 <0.001 
 35–44 71.3 0.61 (0.51–0.71) <0.001 0.77 <0.001 
 45+ 68.4 ref  ref  
Marital status 
 Married 70.3 ref  ref  
 Single 72.3 1.06 (1.02–1.09) 0.002 1.16 (0.99–1.34) 0.050 
 Divorced 68.3 0.92 (0.87–0.96) 0.001 0.90 (0.76–1.07) 0.243 
 Widow/Widower 66.8 0.09 (0.84–0.97) 0.008 0.99 (0.77–1.26) 0.946 
 Cohabiting 74.9 1.10 (0.91–1.33) 0.317 0.93 (0.42–2.01) 0.875 
CD4 count (Cell/µl) 
 350+ 69.3 ref  ref  
 <200 66.6 0.95 (0.86–1.06) 0.429 0.94 (0.82–1.07) 0.362 
 200–349 64.8 0.89 (0.78–1.01) 0.071 0.95 (0.80–1.10) 0.493 
Facility types 
 Hospital 70.7 ref  Ref  
 Health centre 71.5 1.05 (1.02–1.09) <0.001 0.96 (0.75–1.21) 0.729 
 Other 72.6 1.06 (1.03–1.09) <0.001 1.01 (0.88–1.16) 0.851 
Sex 
 Male 71.1 Ref  Ref  
 Female 71.7 1.01 (0.98–1.04) 0.340 1.11 (0.98–1.25) 0.094 
CrudeAdjusted
VariableAttrition Rate/1,000 pmHR (95% CI)P-ValueHR (95% CI)P-Value
MMS category 
 MMS 69.4 ref  ref  
 Non-MMS 85.2 1.40 (1.35–1.45) <0.001 1.47 (1.23–1.73) <0.001 
Age (years) 
 15–24 87.3 1.21 (0.90–1.32) 0.020 1.24 <0.001 
 25–34 74.0 0.70 (0.59–0.83) <0.001 0.75 <0.001 
 35–44 71.3 0.61 (0.51–0.71) <0.001 0.77 <0.001 
 45+ 68.4 ref  ref  
Marital status 
 Married 70.3 ref  ref  
 Single 72.3 1.06 (1.02–1.09) 0.002 1.16 (0.99–1.34) 0.050 
 Divorced 68.3 0.92 (0.87–0.96) 0.001 0.90 (0.76–1.07) 0.243 
 Widow/Widower 66.8 0.09 (0.84–0.97) 0.008 0.99 (0.77–1.26) 0.946 
 Cohabiting 74.9 1.10 (0.91–1.33) 0.317 0.93 (0.42–2.01) 0.875 
CD4 count (Cell/µl) 
 350+ 69.3 ref  ref  
 <200 66.6 0.95 (0.86–1.06) 0.429 0.94 (0.82–1.07) 0.362 
 200–349 64.8 0.89 (0.78–1.01) 0.071 0.95 (0.80–1.10) 0.493 
Facility types 
 Hospital 70.7 ref  Ref  
 Health centre 71.5 1.05 (1.02–1.09) <0.001 0.96 (0.75–1.21) 0.729 
 Other 72.6 1.06 (1.03–1.09) <0.001 1.01 (0.88–1.16) 0.851 
Sex 
 Male 71.1 Ref  Ref  
 Female 71.7 1.01 (0.98–1.04) 0.340 1.11 (0.98–1.25) 0.094 

In this study, we assessed patient retention in HIV care following multi-month prescriptions in the Mwanza region. The overall results indicate that stable HIV patients kept in ART multi-month prescriptions were more likely to be retained in care than non-MMS patients. Other factors that influenced the retention of HIV care were patient age and marital status. This information provides reassurance to policymakers and other stakeholders that MMS is achieving its intended goal of improving client retention in HIV care.

Maintaining stable HIV patients on ART multi-month prescriptions increases the chances of retention in HIV care. These findings were like those of a study conducted in Malawi assessing the retention of HIV care among clinically stable patients after 6 months of clinical consultations [10]. However, the Malawi study had a long follow-up period of 5 years compared to the 2 years of this study, and analysis was done by categorizing patients into groups based on the time of enrollment to 6 months of clinical consultation, which was not the case in our study.

The higher retention rates reported in our study were also like those obtained from a study that assessed the experience of multi-month prescription of ART among children and adolescents in 6 African countries, including Tanzania and studies in Zimbabwe and Uganda [7, 11] . In those study, patients kept in the MMS had higher retention rates compared to those kept in monthly ART prescriptions, despite the difference in study participants in which our study concentrated on HIV patients aged 15 years and above and the study design where the later were randomized trials [12].

However, our study demonstrated that despite good retention probabilities among MMS patients, there were some net worth differences in retention across the age categories with 15–24 years having the lowest retention probabilities and highest attrition hazards. These findings are like those of the above-cited study that highlighted the least favorable Kaplan-Meier curves for adolescents (15–19 years) on ART MMS [12]. Despite the study setting in which the “experience of multi-month prescription of ART among children and adolescents in six African countries” took place being Baylor clinics, which are centers of excellence for pediatric HIV and possess well-trained and adequate staff that closely follow-up HIV patients receiving care from their setting, we still observed similarities in attrition among adolescents aged 15–19 years. Furthermore, similar findings of low retention in HIV care among 15–24 years of age have been recorded in other studies [13, 14, 15, 16]. Age-associated behaviors may be a contributing factor as teenagers tend to question things; hence, further studies are needed to explore the reasons for this observation and tailor interventions that suit the needs of this sensitive group in HIV dynamics.

Furthermore, there was no significant difference in the attrition hazards between male and females displayed in our study. This contrasted with other studies that showed a difference in client retention to care between sexes, with men having a higher attrition risk [15, 16, 17, 18]. This may be due to the similarities in favorable selection criteria used to include these patients in ART MMS and the inclusion of only ART MMS eligible patients in our study, which are well established with good adherence history.

This study was retrospective in nature, using secondary data that were not collected for research purposes; thus, to accomplish our objectives, some variables were generated during the data analysis process using information extracted from the CTC 3 macro database. To ensure reproducibility, the generated variables strictly adhered to the definitions of the terms provided in this study. Another limitation of this study was the missing data for some variables, such as CD4 count and area of residence, which could influence patient retention in HIV care. Nevertheless, this study had sufficient power (sample size = 21,742 patients) to provide evidence of the impact of ART MMS on patient retention in HIV care and its associated factors.

Our study suggests that the retention of stable HIV patients into care has been achieved using the ART MMS strategy and refutes the negative speculations. In addition, younger patients were more likely to be lost to follow-up, and thus, improvements in retention to care among stable HIV patients may further be attained by addressing challenges hindering patients at 19–24 years.

ART MMS seems to work, and the Ministry of Health and NACP should further promote this strategy by ensuring that health-care providers adhere to the guidelines and keep eligible clients in MMS. In addition, while keeping HIV-stable patients in ART MMS, clinicians should consider the age of the patients and provide age-specific services to foster retention of the younger patients in HIV care. Health facilities in Mwanza may design a way to use social media groups that will act as peer support groups to encourage youth adherence to HIV services, which will increase retention.

Future prospective studies with long follow-up durations are needed to further explore the impact of ART MMS on the retention of HIV patients in care and clinical outcomes. In addition, studies to establish factors associated with low retention probabilities among younger HIV patients receiving ART are of paramount importance to further understand the results of our study.

The raw data cannot be accessed but STATA “do file” and outputs will be available upon request.

This study was financially supported by a grant from the Tanzania Field Epidemiology and Laboratory Management Program.

The authors declare no conflict of interest.

Study design: EM, MJ, and KG; data analysis and original draft writing: EM, WM, and KG; review of the manuscript and supervision of the manuscript writing: KG; coordination of data analysis and interpretation and manuscript editing: EM, IK, and KG; manuscript review and editing: all the authors have read and agreed to the published version of the manuscript.

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How to cite this article: Mkonyi E, Kissima I, Maokola W, Janneth M, Gideon K. Status of patients’ retention into HIV care following implementation of multi-month scripting for antiretrovirals in Mwanza, Tanzania (2018–2020). Adv Glob Health. 2024;3(1). https://doi.org/10.1525/agh.2024.2336637

Editor-in-Chief: Craig R. Cohen, University of California San Francisco, CA, USA

Senior Editor: Andres G. Lescano, Cayetano University, Lima, Peru

Section: Improving Health and Well-Being

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.