Secondary Logo

Journal Logo

Improved HIV and TB Knowledge and Competence Among Mid-level Providers in a Cluster-Randomized Trial of One-on-One Mentorship for Task Shifting

Naikoba, Sarah MSc Epi, MPH, MBChB*,†; Senjovu, Kaggwa D. MSc, HSM, MBChB*; Mugabe, Pallen BSc STAT*; McCarthy, Carey F. PhD, MPH, RN‡,§; Riley, Patricia L. FACNM, MPH, CHN; Kadengye, Damazo T. PhD‖,¶; Dalal, Shona MSc, PhD‖,#

JAIDS Journal of Acquired Immune Deficiency Syndromes: August 15, 2017 - Volume 75 - Issue 5 - p e120–e127
doi: 10.1097/QAI.0000000000001378
Clinical Science

Introduction: Health worker shortages pose a challenge to the scale up of HIV care and treatment in Uganda. Training mid-level providers (MLPs) in the provision of HIV and tuberculosis (TB) treatment can expand existing health workforce capacity and access to HIV services.

Methods: We conducted a cluster-randomized trial of on-site clinical mentorship for HIV and TB care at 10 health facilities in rural Uganda. Twenty MLPs at 5 randomly assigned to an intervention facilities received 8 hours a week of one-on-one mentorship, every 6 weeks over a 9-month period; and another 20 at 5 control facilities received no clinical mentorship. Enrolled MLPs' clinical knowledge and competence in management of HIV and TB was assessed using case scenarios and clinical observation at baseline and immediately after the 9-month intervention. The performance of the study health facilities on 8 TB and HIV care indicators was tracked over the 9-month period using facility patient records.

Results: Thirty-nine out 40 enrolled MLPs had case scenario and clinical observation scores for both the baseline and end of intervention assessments. Mentorship was associated with a mean score increase of 16.7% (95% confidence interval: 9.8 to 23.6, P < 0.001) for the case scenario assessments and 25.9% (95% confidence interval: 14.4 to 37.5, P < 0.001) for the clinical observations. On-site clinical mentorship was significantly associated with an overall improvement for 5 of the 8 health facility TB and HIV indicators tracked.

Conclusions: One-on-one on-site mentorship improves individual knowledge and competence, has a downstream effect on facility performance, and is a simple approach to training MLPs for task shifting.

*Department of Training and Capacity Building, Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda;

Currently, Maternal Child Survival Program, John Snow Inc (JSI), Kampala, Uganda;

Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Atlanta, GA;

§Currently, National Council of State Boards of Nursing, Chicago, IL;

Division of Global HIV/AIDS, Centers for Disease Control and Prevention, Kampala, Uganda;

Currently, School of Statistics, Makerere University, Kampala, Uganda; and

#Currently, Department of HIV/AIDS, World Health Organization, Geneva, Switzerland.

Correspondence to: Sarah Naikoba, MSc Epi, MPH, MBChB, Infectious Diseases Institute, College of Health Sciences, Makerere University, Kampala, Uganda (e-mail:

This publication was made possible by the support from the US President's Emergency Plan for AIDS Relief through cooperative agreement 1U01GH000527 from the US Centers for Disease Control and Prevention, Division of Global HIV/AIDS to Makerere University College of Health Sciences, Infectious Diseases Institute. The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention/the Agency for Toxic Substances and Disease Registry.

The authors have no conflicts of interest to disclose.

S.N., K.D.S., P.M., C.M., P.L.R., and S.D. designed the study, S.N., K.D.S., and P.M. conducted the study, S.N., K.D.S., P.M., D.T.K., and S.D. analyzed the data, S.N. prepared the first draft of the manuscript, and all authors contributed to the manuscript and approved the final version for submission.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (

Received August 23, 2016

Accepted March 13, 2017

Back to Top | Article Outline


Health worker shortages pose a major challenge to the scale up of HIV care and treatment including the fulfillment of the global goal to end the AIDS epidemic. Uganda is among 57 countries that have a critical shortage of health professionals defined as a ratio of less than 2.5 health professionals per 1000 people.1 The national medical officer to population ratio is 1:12,500 and is typically worse in rural areas where posts are difficult to fill. Most available health workers in Uganda are mid-level providers (MLPs) which include clinical officers, nurses, and midwives.2

Training MLPs to perform tasks conventionally assigned to medical officers, known as task shifting, can expand the capacity of the existing health workforce and increase access to HIV services.3–7 The World Health Organization (WHO) defines task shifting as a process of empowering, through short-term training, available cadres of health workers to enable them share and be delegated to tasks originally preserved for cadres with higher levels of training.8,9 Globally, task shifting has been embraced and recommended by WHO as a strategy for addressing shortages in human resources needed to scale up HIV care and treatment.10 However, ensuring that MLPs receive appropriate training and skills to enable them to take on additional clinical tasks and maintain quality of patient care is key. Traditional training away from the workplace has the disadvantage of disrupting clinical service delivery while staff are sent for training. Until more comprehensive training can be incorporated into MLP preservice degree/diploma programs, alternate approaches to facilitate the dissemination of new and evidence-based best practices within the workplace setting, such as clinical mentorship, could provide the support and training that MLPs need to treat these complex conditions.

Clinical mentoring is an approach of in-service knowledge translation that uses social influence through interpersonal interactions to increase knowledge and uptake of evidence-based practices11 by providing individualized support based on mentees' learning needs. There is, however, scant evidence as to which mentoring approaches are most effective.6,12

We built on the findings of a previous mentoring study that observed improvements in multiple areas, such as emergency care13 patient triage and diagnosis, management of malaria and enrollment of patients into HIV care, but was less than expected for tuberculosis (TB) and HIV management. Our goal was to determine whether more in depth mentorship on HIV and TB care would improve the clinical knowledge, competence, and practice of MLPs in patient diagnosis and management of HIV and TB.

Back to Top | Article Outline


We conducted a cluster-randomized trial of on-site clinical mentorship for HIV and TB.

Back to Top | Article Outline

Study Sites and Participants

Four MLPs (40 in total), were selected from each of 10 Health Center IV facilities in rural Uganda. The 10 health center IV facilities were identified from a list of all level IV facilities that were part of the 36 health facilities that participated in the IDCAP study.13 This was done to build on data management infrastructure such as computers and backup power supply put in place during the IDCAP study. Health Center IV facilities serve a typical catchment population of 100,000 and provide outpatient and inpatient facilities for minor ailments, labor, and delivery, and are frequently managed by MLPs. The Health Center IV facilities provide antiretroviral therapy (ART) and TB treatment and have laboratories to support testing for both conditions (namely HIV testing, CD4 and microscopy for acid-fast bacilli).

To be included in the study, a site was required to have a minimum of 4 MLPs and not be involved in the implementation of a similar study. Twelve Health Center IV facilities met eligibility criteria, and from these 10 were randomly selected for study participation using a random number generator. Five facilities were then randomized to the intervention group and 5 to the control group. Supplemental Digital Content 1, shows the location of the different study sites on the Uganda map.

Back to Top | Article Outline

Mid-level Provider Definition and Selection

We defined MLPs as clinical officers, registered nurses, and registered midwives with diploma-level training—a minimum of 3 years post-secondary school education. MLPs are authorized to prescribe ART and TB medication to patients in Uganda. Clinical officers, unlike the registered nurses and midwives, are also allowed to conduct minor surgery; however, they are not trained to conduct deliveries. Preference for inclusion in the study was given to those MLPs who spent approximately 80% of their time in daily clinical management of patients with TB and HIV.

Any MLPs who dropped out in the first 3 months of the intervention were replaced with another MLP from their site who met the inclusion criteria. After 3 months of the start of the intervention, no MLPs were replaced because they would not have been able to cover training material in the time remaining. Discussions were held and commitment was obtained from the District Health Officers to avoid, where necessary, staff transfers of MLPs enrolled in the study to other health facilities during the study period. The CONSORT diagram in Figure 1 provides details of the criteria for inclusion and exclusion for MLPs in the study.



Back to Top | Article Outline


The intervention comprised one-on-one on-site clinical mentorship of participating MLPs for 8 hours a week, every 6 weeks, over a 9-month period at each of the 5 intervention sites from a trained mentor on HIV and TB care. Seven mentors participated (5 were men, and 2 were women). One district mentor was identified from each of 5 districts in which the 5 intervention health facilities were located. These were paired with either 1 of 2 centrally based Infectious Diseases Institute (IDI) mentors. Selected mentors were clinical officers with at least 4 years of relevant clinical experience, expertise in HIV/AIDS and TB care, and good facilitation and mentoring or coaching skills. The district-level mentors, selected in collaboration with the District Health officer, had similar qualifications to the IDI-based mentor. Each mentoring team was attached to the same sites, and at each site each mentor was randomly matched to 2 MLPs for the duration of the intervention to allow the MLPs to develop and maintain a relationship with the same mentor throughout the intervention period. Before study initiation, MLPs were briefed on expectations for participation, the schedule for mentoring team visits, and data collection procedures. Mentees agreed on a strategy with mentors to achieve 8 hours of training a week during the mentorship visits. Thereafter, each mentorship team visited a site from Monday to Friday every 6 weeks for a total of 6 visits over the course of the 9-month intervention period. Each mentorship session was provided using structured tools focusing on the general aspects of how to do mentorship and how to facilitate mentee learning for the set of key HIV and TB competences, including taking a medical history, conducting a physical examination, conducting disease investigations and diagnosis, and providing treatment, patient education, and follow-up care. Typical activities during the mentorship sessions included working alongside the MLPs to provide real-time consultation for complex cases; review of mentee's logbook to provide retrospective guidance on difficult clinical cases that the MLP has seen since the last visit by the mentor; one-on-one continuous professional development session in areas relevant to the MLP's clinical learning objectives; and provision of MLPs with tools and resources with which to engage in self-directed learning between visits, such as reading materials, logbooks to record complex cases, and clinical algorithms. The mentors would also be available through phone and e-mail to answer clinical questions from MLPs between site visits. Over the 9-month period, each mentee received approximately 48 hours of mentoring. At the 5 control sites, MLPs were recruited but after the initial information session received no intervention.

Back to Top | Article Outline


The primary study outcome was the difference in differences in mean clinical knowledge and competence scores measured at baseline and immediately postintervention between MLPs assigned to the intervention group and MLPs assigned to the control group. The mean scores for clinical knowledge and competence were assessed using case scenarios and clinical observations. Case scenarios were validated relative to standardized patients as tools for measuring quality of clinical practice. The case scenarios were rewritten using templates adapted from the IDCAP study, ensuring alignment of their content to competencies included in the mentorship sessions. At each assessment point each MLP was given 4 case scenarios that mimicked a TB or HIV patient visit. All MLPs were assessed on the same set of case scenarios; with 2 of 4 the case scenarios kept the same at both time points of assessments; and the remaining 2 differed at each assessment. Each assessment for the 4 case scenarios lasted a maximum of 3 hours. The case scenarios were administered centrally at the IDI in Kampala. The case scenarios were graded by 2 independent senior clinicians who were not involved in the implementation of the study and employed as tutors and examiners of training institutions for clinical officers and nurses. The assessors were blinded to study arms.

The clinical observations were performed in persons using tools of patient care administered at the study participants' workstations. Each MLP was observed, assessed, and scored on 4 types of patients identified by the health facility manager with the following conditions: HIV patient not on ART, HIV patient on ART, TB patient on treatment, and HIV patient with TB. Inclusion criteria for patients were that they were older than 18 years and able to provide informed consent. Patients with need for emergency care and those whose conditions could be worsened by participating in the study were excluded. A prescored HIV and TB clinical observation checklist was used to document MLP's performance while managing each patient and each observation lasted a maximum of 1 hour. The clinical assessment tool was a revised version of the tool used in the IDCAP study which was adapted from tools used by Brentlinger et al14,15 for measurement of clinical outcomes. Each clinical observation for a MLP was conducted and graded by 2 independent senior clinicians employed as tutors for clinical officers and nurses. Immediately after each observation, the 2 assessors reviewed their scores and came to agreement on a final score.

We also measured health facility performance against a set of 8 TB and HIV care indicators by extracting anonymized individual patient care data from October 2013 to July 2014 from the standard Ministry of Health Medical Form 5 for general outpatient visits. Anonymized individual HIV care and treatment patient data were obtained from the HIV care and treatment database (using OpenMRS software); TB care and treatment data were collected from the TB register. The HIV and TB care facility indicators are based on national standard care and treatment guidelines adopted from WHO guidelines and included the proportions of outpatients: (1) with unknown HIV sero status who were offered an HIV test or (2) who were suspected of having TB and had an acid-fast bacilli smear ordered. Among patients with HIV, facility indicators were the proportion of visits with recorded (3) TB screening, (4) WHO clinical staging, (5) prescription of daily co-trimoxazole, (6) adherence to daily co-trimoxazole, (7) adherence to antiretroviral (ARV), and (8) patient weight measurement.

Back to Top | Article Outline

Sample Size

This study was designed to detect a 10% absolute difference in knowledge with 80% power at a 5% level of significance. From the sample size estimations, the expected number of MLPs per arm was 14 per arm. The number of MLPs recruited per arm was increased to 20 to account for potential loss to follow up.

Back to Top | Article Outline

Data Analysis

For each measure, the effect of the intervention was calculated as the difference between the mean change from baseline to end-line in the intervention arm, and the mean change from baseline to end-line in the control arm (difference in difference). We used a mixed effects linear regression model to estimate the expected difference in mean change in knowledge and competence scores between the 2 time points (baseline and end-line) in the intervention arm in comparison with control arm; with arm as the main predictor variable adjusted for other potential confounding factors and clustering at the health facility level. We used linear regression to determine variation in facility performance indicators during the intervention period by study arm; and to test the null hypothesis that there are no differences between the variations observed in the 2 arms for each of the facility indicators.

Stata software (version 11; StataCorp, College Station, TX) was used for all analyses.

Back to Top | Article Outline

Ethical Approval

The informed consent process for MLPs was confidential with the liberty to opt out of the study at any time. No incentives to participate were provided. Ethical approval for this study was provided by Joint Clinical Research Centres's HIV/AIDS Research Committee IRB#1-IRB00001515, the Uganda National Council for Science and Technology and the Center for Diseases Control and Prevention-Division of Global HIV/AIDS Science Office/Institutional Research Board.

Back to Top | Article Outline


Study Participants

Overall, the 10 participating health facilities had a total of 66 MLPs. Of these 63 MLPs, 51 (81%) met eligibility criteria and expressed interest in participating, and of these 40 (78%) were randomly selected to participate—20 MLPs for each arm. One MLP in the intervention arm dropped out for medical reasons and was not considered in analyses. Figure 1 shows the detailed flow of participants through the study period.

Table 1 shows the baseline characteristics of the MLP and health facilities that participated in the study. MLPs' characteristics were generally similar in the intervention and control arms. The average MLP age was 39 years, the majority were women (78%), the median years of practice was 4 and majority (70%) were registered nurses/midwives.



Back to Top | Article Outline

Change in Knowledge and Competence (Case Scenarios and Clinical Observation Scores)

The average case scenario scores of MLPs in the intervention arm increased significantly over the 9-month period of mentorship by 13.4% [95% confidence interval (CI): 7.2 to 19.6], but no significant change occurred in the control arm (Table 2). The unadjusted difference between the mean change in knowledge scores for MLPs in the control and the intervention arms was 14.5 (P < 0.001). The average clinical observation scores of MLPs in the intervention arm also increased from baseline to end-line by 27.8% (95% CI: 21.1 to 34.5), with no change in the control group. Overall, the difference in mean clinical observation scores between the intervention and control arms was 27.0% (P < 0.001).



The intervention improved knowledge and competence scores among registered nurses/midwives, both men and women, and regardless of years of practice or monthly average of patients with HIV treated as compared with the control arm (See Supplemental Digital Content 2 and 3, The only group which did not show improvement in case scenarios was clinical officers.

After adjusting for cadre, gender, years of work experience, and monthly average HIV clients at the workplace, the difference in difference in mean MLP clinical knowledge and competence scores as assessed using case scenarios, comparing intervention to control arm, was 16.7 (95% CI: 9.8 to 23.6; P < 0.001) and 25.9 (95% CI: 14.4 to 37.5; P < 0.001) as assessed using clinical observation (Table 3).



Back to Top | Article Outline

Effect of Intervention on Health Facility TB and HIV Care Performance Indicators

The total number of Outpatient Department patients seen during the study (October 2013–July 2014) in both intervention and control sites was 161,655. Of these, 57% were seen in the intervention arm and 43% were seen in the control arm (as shown in Supplemental Digital Content 4,

Overall, facility performance indicators started at high levels (≥80%) for both control and intervention facilities for TB screening among patients with HIV, WHO clinical staging, prescription of co-trimoxazole, and the recording of patients with HIV' weight (as shown in Fig. 2 graphs B, D, E, and H). Statistically significant improvements were seen for 5 of 8 facility indicators in the intervention arm compared with the control arm (HIV testing for outpatients; TB screening for patients with HIV; WHO clinical staging; reviewing adherence to co-trimoxazole; and checking for adherence to ARV treatment as shown in Supplemental Digital Content 5, table of coefficient for trend curves for health facility performance indicators by arm).



The most improvement in the intervention arm was seen in the proportion of new outpatients with unknown HIV status who were offered an HIV test which increased from 32% to 53% [regression coefficient = 2.862 (95% CI: 1.062 to 4.661, P value = 0.030)].

Although improvement was seen in the intervention sites for the checking and recording of adherence to ARVs and to co-trimoxazole, the performance on these indicators, in both intervention and control remained unsatisfactorily low. By the end of the intervention, recording of adherence to ARVs in intervention and control sites was 43% and 45%, respectively; recording of adherence to co-trimoxazole in intervention and control sites was 49% and 65%, respectively (Fig. 2, graph F and G, and Supplemental Digital content 5).

Facility performance in control sites started and remained higher than in intervention sites for patients with HIV screened for TB and WHO clinical staging.

Back to Top | Article Outline


Traditional training approaches away from the workplace are limited in the number of practicing MLPs who can be trained, are often costly, and by taking clinicians out of health facilities during the training period, can cause service disruption. Another training challenge identified in a South African study of nurse-initiated and managed ART was the lack of follow-up mentoring and competency assessment, where nurses reported providing ART before feeling confident to do so.16 The mentorship approach addresses these limitations by conducting training on-site, allowing direct and practical observation of trainee performance, and providing a continued consultation resource for questions or difficult cases after the training period. Previous studies on task shifting for MLPs have been able to demonstrate improvements in MLPs' knowledge, competence, and practice as a result of on-site clinical mentorship, but only as part of a combination of interventions including traditional training, and continuous quality improvement.7,13 The findings from our trial demonstrate that more depth one-on-one mentorship of MLPs involved in task shifting as a single intervention significantly improved their knowledge and competence in TB and HIV patient care.

Ensuring the provision of quality patient care and treatment is essential for task shifting between different cadres of health workers to succeed. In practice, many MLPs in sub-Saharan Africa have prescriptive authority and manage patients with HIV and TB. Studies of task shifting have found that nonphysician care is similar to physician-managed care in outcomes such as mortality, CD4 cell count, viral failure, adherence measurements, and loss to follow up.17–20 We found that the overall starting levels of knowledge and competence of MLPs providing HIV and TB care and treatment were low, highlighting the need for further training. Clinical officers had higher baseline knowledge scores than nurses/midwives, as may be expected with their longer period of education. Nurses/midwives showed most improvements, having started off with much lower knowledge and competence scores than the clinical officers. The improvements in knowledge and competence scores though significant for clinical officers were modest compared with what has been observed in previous studies. A further analysis of clinical officers' attitudes toward mentorship in a follow-on article will provide a better understanding of possible reasons for the modest increases in knowledge and competences observed among clinical officers.

Furthermore, although only 4 MLPs were trained in each intervention facility, significant trends in improvements were seen during the study period in the intervention arm compared with the control arm in 5 of 8 HIV and TB facility indicators, including the overall proportion of patients with unknown HIV status who were offered or received an HIV test, proportion of patients with HIV screened for TB, and who had WHO staging, checking for and recording adherence to co-trimoxazole and to ARV treatment.

This indicates that mentoring even a few MLPs at a facility may influence the practice of other clinicians and result in significant changes in facility performance. Mentoring or training larger numbers of MLPs in a facility is ideal, creates a supportive environment, divides clinical tasks more evenly, and may result in a greater cascade effect on other MLPs' practice. Options for broader training include team or group mentorship, feedback, and audits. Several studies have demonstrated impact with team mentorship as part of a multifaceted intervention7,13,21 and that nurses feel more supported and have higher motivation in facilities where more colleagues are trained.22

We found very high compliance with the recording of co-trimoxazole prescription, TB screening of patients with HIV and WHO clinical staging, and recording of weight for patients with HIV. However, recording and very likely checking for adherence for co-trimoxazole and for ARV, both of which are critical for components of HIV patient follow-up care, were poor at 65% and 45%, respectively, although it did improve in intervention facilities.

In addition to improved individual performance, mentored MLPs in the intervention arm began managing a larger proportion of HIV clinic consultations than those in the control arm. In anecdotal feedback, mentored MLPs found mentorship useful and that it enhanced their confidence in handling HIV and TB cases. They also appreciated the ability to consult on cases with their mentors after mentoring sessions and to share their learning with their peers afterward.

In an effort to ensure sustainability, we recruited mentors based on district health facilities to work with those from the Infectious Diseases Institute during the intervention, so that the training they received could continue to serve MLPs in more rural areas. District mentors work in similar environments as target MLPs, understand local issues, and may be able to more easily maintain contact with mentees. Although we paired study mentors with mentees from another district to avoid influencing results or create perceived bias, district mentors could be a valuable resource in mentoring MLPs in their own districts.

The sample size of MLPs used in this study limited the stratified analysis that could be performed. Although the study sites were selected from health facilities that previously participated in the IDCAP study,21 we believe that our results may be generalizable to typical rural Ugandan health center IVs, because IDCAP study sites were all level IV facilities which provide similar services to other level IV facilities not included in the study. However, the findings may not be generalizable to health facilities in urban settings that have varying staff composition and higher HIV patient load. The small number of health facilities from which the study health facilities were randomly selected could have rendered the randomization process ineffective. The proportion of average number of patients with HIV seen per month was higher in the intervention arm; however, this was not found to significantly affect the outcomes in the multivariate analysis (Table 3). Despite the small sample size, we determined that the effect of the intervention was successful in MLPs of diverse cadres. The durability of these results over longer periods was not assessed in this analysis and will be the focus of a follow-on article.

In conclusion, task shifting has been embraced by the public health community as one solution to the critical health care workforce shortage in low resource settings.7 However, the best means to ensure quality training for practicing MLPs has remained in question. Our results at baseline showed low competence of MLPs in HIV and TB patient management. Addressing this competence gap is essential to ensure that HIV/AIDS programs planning or implementing MLP task shifting to ease the human resources bottleneck does not result in lowered quality of treatment services. One-on-one mentorship improves individual knowledge and competence, has a downstream effect on facility performance, and should be used as an approach to train MLPs who are already managing clinical cases for which they are currently ill-equipped. Mentorship further builds confidence and ability to manage complex cases and forms lasting relationships for sustainability. Clinical mentorship is a sustainable approach to in-service training for HIV and TB, which we have shown to be effective; others should also be explored.

Back to Top | Article Outline


The authors wish to thank the study participants, mentors, evaluators, and facility and district managers who made this study possible.

Back to Top | Article Outline


1. World Health Organization. The World Health Report 2006: Working Together for Health. Geneva, Switzerland: World Health Organization; 2006.
2. World Health Organization. Human Resources for Health-Country Profile Uganda. Geneva, Switzerland: World Health Organization; 2009.
3. Callaghan M, Ford N, Schneider H. A systematic review of task-shifting for HIV treatment and care in Africa. Hum Resour Health. 2010;8:8–16.
4. Dovlo D. Using mid-level cadres as substitutes for internationally mobile health professionals in Africa-A Desk review. Hum Resour Health. 2004;2:7.
5. Mullan F, Frehywot S. Non physician clinicians in 47 sub-Saharan African countries. Lancet. 2008;370:2158–2163.
6. Samb B, Celletti F, Holloway J, et al. Rapid expansion of the health workforce in response to the HIV epidemic. N Engl J Med. 2007;357:2510–2514.
7. Morris MB, Chapula BT, Chi BH, et al. Use of Task Shifting to rapidly scale up HIV treatment services: experiences from Lusaka, Zambia. BMC Health Serv Res. 2009;9:1–9.
8. World Health Organization. WHO Recommendations: Optimizing Health Worker Roles to Improve Access to Key Maternal and Newborn Health Interventions through Task Shifting. Geneva, Switzerland: World Health Organization; 2012.
9. Janowitz B, Stanback J, Boyer B. Task sharing in family planning. Stud Fam Plann. 2012;43:57–62.
10. World Health Organization, PEPFAR, UNAIDS. Task Shifting: Rational Distribution of Tasks Among Health Workforce Teams: Global Recommendations and Guidelines. Geneva, Switzerland: World Health Organization; 2007.
11. Ministry of Health Uganda. Clinical Mentors Pocket Reference Guide. Kampala, Uganda: Ministry of Health Uganda; 2010.
12. Jokelainen M, Tutunen H, Tossavainen K, et al. A systematic review of mentoring nursing students in clinical placements. J Clin Nurs. 2011;20:2854–2867.
13. Weaver MR, Burnett SM, Crozier I, et al. Improving facility performance in infectious disease care in Uganda: a mixed design study with pre/post and cluster randomized trail components. PLoS One. 2014;9:e103017.
14. Brentlinger PE, Assan A, Mudender F, et al. Task Shifting in Mozambique: a cross sectional evaluation of non-physicians clinicians' performance in HIV/AIDS care. Hum Resour Health. 2010;8:23.
15. Brentlinger PE, Torres JV, Martinez PM, et al. Clinical Staging of HIV related illness in Mozambique: performance of non-physician clinicians based in direct observation of clinical care and implications for health worker training. J Acquir Immune Defic Syndr. 2010;55:351–355.
16. Mdege ND, Chindove S, Ali S. The effectiveness and cost implications of task-shifting in the delivery of antiretroviral therapy to HIV infected patients: a systematic review. Health Policy Plan. 2013;28:223–226.
17. Emdin CA, Millson P. A systematic review evaluating the impact of task shifting on access to antiretroviral therapy in Sub Saharan Africa. Afr Health Sci. 2012;12:318–324.
18. Emdin CA, Chong NJ, Millson PE. Non-physician clinician provided HIV treatment results in equivalent outcomes as physician- provided care: a meta-analysis. J Int AIDS Soc. 2013;16:18445.
19. Kredo T, Adeniyi FB, Bateganya M, et al. Task shifting from Doctors to non-doctors for initiation and maintenance of antiretroviral therapy. Cochrane Database Syst Rev. 2014;7:CD007331.
20. Shumbusho F, van Griensven J, Lowrance D, et al. Task shifting for scale -up of HIV care: evaluation of nurse-centered antiretroviral treatment at rural health centers in Rwanda. PLoS Med. 2009;6:e1000163.
21. Weaver RM, Crozier I, Eleku S, et al. Capacity building and clinical competence in infectious disease in Uganda: a mixed-design study with pre/post and cluster -randomized trail components. PLoS One. 2012;7:e51319.
22. Davies NE, Homfray M, Venables EC. Nurse and Manager perceptions of Nurse Initiated and Managed Antiretroviral Therapy (NIMART) implementation in South Africa: a qualitative study. BMJ Open. 2013;3:e003840.

task shifting; sharing; HIV; TB; nurse; mid-level providers

Supplemental Digital Content

Back to Top | Article Outline
Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.