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Presentation on theme: " Stepping Up: Nurses Role in MDR- TB/HIV Co-Infection in South Africa Primary Healthcare-Nurse Practitioner (PHC-NP) and Medical Officer."— Presentation transcript:

1 Stepping Up: Nurses Role in MDR- TB/HIV Co-Infection in South Africa Primary Healthcare-Nurse Practitioner (PHC-NP) and Medical Officer (MO) Task Sharing of MDR-TB in Rural Kwa-Zulu Natal, South Africa Jason Farley, PhD, MPH, NP, FAAN Associate Professor, Johns Hopkins University School of Nursing Adjunct Associate Professor, Uni. of KZN, SA and Uni. of Technology Sydney Pres-Elect, Association of Nurses in AIDS Care

2 Co-Investigators Farley, J.E. 1 ; Walshe, L. 1 ; Budhathoki, C. 1 ; Mlandu, N. 2 ; Nomusa, N.; Ndjeka, N. 3 ; van der Walt, M. 4 Johns Hopkins University School of Nursing 1 ; Ugu District Department of Health, KwaZulu Natal, South Africa 2 ; South African National Department of Health 3 ; South African Medical Research Council 4

3 TB in South Africa South Africa has the 2 nd highest rate of new TB cases in the world ( Highest rate of drug-resistant TB cases in Africa ( 4 th Highest Prevalence of HIV/AIDS ( Over 70% of all TB cases co-infected with HIV (SA DOH, 2012)

4 Background Following national guidelines, every effort should be made to ensure eligible clients are enrolled as soon as possible. –all primary care, antenatal, TB and mobile outreach health facilities must become fully functional nurse-initiated ART and MDR-TB initiation sites for adults, children and pregnant women.

5 Methods Prospective cohort of MDR-TB patients jointly managed by a PHC-NP and a MO. –Patients who initiated treatment between January 1 and December 31, 2012 –Who either completed IP or experienced a negative outcome (i.e., death, failure, default) were included. We evaluate the intensive phase (IP) quality indicators and risk for IP negative outcomes. Descriptive statistics by provider type for demographic and time-to-event variables.

6 Methods Cont’d Provider comparisons for time-to-event IP indicators were made using a log-rank test, and contribution of other covariates, e.g. gender, HIV status assessed. Cumulative risk of remaining event free beyond a time point shown using a Kaplan-Meier plot A competing risk analysis with death, failure or default as competing negative outcomes was completed.

7 Ethical Approval Approval was obtained at the following institutions: –Johns Hopkins University School of Medicine –SA Medical Research Council –KZN Provincial Research Committee –Murchison District Hospital Management


9 1 week intensive theory + 1 Month CNP Clinical Mentoring + Competency Evaluation + Ongoing Clinical Mentoring Diagnosis and Clinical Management of MDR-TB Short Course Overview Mentored Training Experiences:  Audiology training  Visual assessment training  Laboratory Monitoring & Evaluation  ADR evaluation & treatment

10 Developing Systems Level Strategies for Safe Prescribing

11 Original Assignment to Provider After extensive training of the PHC-NP, patients were assigned a primary provider with task sharing throughout. CNP Outpatient Standardized MDR- TB Treatment per guidelines Standardized HIV Management MD Hospital Patients requiring any changes to standardized treatment Baseline liver disease, baseline renal disease, seizure, psychosis, pregnant, low BMI (<45 kg) <13 years old, Diabetic, past Drug induced hepatitis, Re-treatment MDR- TB, Requires O2 support; Non- ambulatory; Critical values for Baseline FBC, U&E, LFTs?


13 Baseline Patient Data on Enrollment 186 eligible patients, 50% females with 77% unemployment. At enrollment, median age was 33 years (Q1-Q3 26- 40), median weight 54 kg (Q1-Q3 47-60). HIV co-infection was 73% (median CD4 count 237, Q1-Q3 121-399); 77% on ART.

14 Baseline Cohort Data CharacteristicOverallNursePhysicianP-value* Age (yrs), Median (Q1-Q3), n 33 (26-40), n=186 34 (26-40), n=122 32 (26-40.5), n=64 0.732 Sex, n (%) Male Female 93 (49.7) 94 (50.3) 65 (52.8) 58 (47.2) 28 (43.8) 36 (56.2) 0.281 Unemployed, n(%), n=173133 (76.9)91 (78.5)42 (73.7)0.565 BMI, Median (Q1-Q3), n19.6 (16.4- 22.6), n=133 19.1 (16.4- 21.9), n=110 22.3 (15.9-26.1), n=23 0.109 Normal ALT, n (%), n=158 142 (89.9) 95 (89.6) 47 (90.4) 0.950 Normal creat clearance, n (%), n=128 116 (90.6) 84 (93.3) 32 (84.2) 0.180 HIV positive, n (%), n=185135 (73.0)92 (75.4)43 (68.3)0.301 CD4 count, Median (Q1-Q3), n 237 (121-399), n=120 233 (120-424), n=85 241 (135-352), n=35 0.324 On ART, n (%), n=138106 (76.8)72 (76.6)34 (77.3)0.950

15 Are Initial Intensive Phase Outcomes Worsened by Task Sharing? CharacteristicOverallNursePhysicianP-value* Outcome, n (%), n=186 MDR-TB diagnosis to Tx start (days), Median (Q1-Q3), n 71 (51-97), 186 71 (51-96), 123 74.5 (51-98), 64 0.810 Tx start to culture conversion (days), Median (Q1-Q3), n 58 (32-92), 149 57 (32-91), 101 62 (32-111.5), 48 0.594 Tx start to end of intensive phase (days), Median (Q1-Q3), n 196 (180- 210) 143 196 (186-212) 98 196 (176-205) 45 0.608 *P-value from a Fisher’s exact test for categorical outcome, from a Wilcoxon rank-sum test for diagnosis to Tx start, and from a log-rank test for the time-to-event variables

16 Are Intensive Phase Outcomes Worsened by Task Sharing?

17 Are Negative Outcomes Increased? There was no significant difference between nurse managed patients and physician managed patients for time from treatment initiation to a negative outcome (default, failure or death) (p=0.561, HR=1.17) Andersen, P.K., et al. 2012. Competing risks in epidemiology: possibilities and pitfalls; International Journal of Epidemiology; Fine, J. P., & Gray, R.J. 1999. A proportional hazards model for the subdistribution of a competing risk. Journal of the American Statistical Association, 94(446), 496{509.

18 Are Final Treatment Outcomes Worsened? CharacteristicOverallNursePhysicianP-value* Outcome, n (%), n=186 Still on Treatment (Tx)68 (36.6)47 (38.2)21 (33.3) Cure Failure Death Default 51 (27.4) 12 (6.5) 26 (14.0) 29 (15.6) 35 (28.5) 6 (4.9) 18 (14.6) 17 (13.8) 16 (25.4) 6 (9.5) 8 (12.7) 12 (19.1) 0.609 Tx start to a negative outcome (default, failure or death) (days), Median (Q1-Q3), n 134 (32-350) 61 134 (26-370) 39 167.5 (32-308) 22 0.561 *P-value from a log-rank test


20 Conclusions from Data MDR-TB IP quality indicators are similar among patients initiated in a task sharing model. No difference in risk for negative outcomes was noted based on provider type suggesting task sharing may be a human resource solution to improve access to care in MDR-TB/HIV co-infection.

21 Implementation Science Lessons Learned Task sharing = equivalent, although not ideal outcomes Increase # of new initiations per week –6 in baseline period to 18 in NI-MDR period CNP see’s all patients at triage Implementation of baseline physical exams and symptom screening on 100% of CNP patients Increase in community-based management –Less than 10% in baseline period to 29% in NIT period

22 Nurses Stepping Up to Increase Access to Care Individual Resources Taxi availability Health status Clinician competence Diagnostic Capability Bed capacity HCW availability What if the CNP could start care here? What if a MDR-TB center transforms to a center of excellence? What if a patient can have direct timely diagnosis and linkage to care? What if the provider has been trained to care at the hospital, clinic or home?


24 Acknowledgements Medical Research Council –Martie van der Walt National Department of Health DR-TB Directorate –Norbert Ndjeka –Pamela Richards –David Mamjeta KwaZulu-Natal Department of Health –Jackie Ngozo –Bruce Margot Ugu District Department of Health –Ntombasekaya Mlandu –Bheki Shazi Murchison & KGV Hospitals –Simi Lachman & Iqbal Master –Marge Govender-Singh –BL Ngesi Johns Hopkins University –Louise Walshe & Jeane Davis –Chakra Budhathoki –Rachel Kidane, Keya Joshi, Katrina Reisner, Maria Brown

25 Contact Details Jason Farley – –@jasonfarleyJHU


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