FAST pilot to scale-up: Lessons learnt from Nigeria

Transcription

1 FAST pilot to scale-up: Lessons learnt from Nigeria 47th Union World Conference on Lung Health Liverpool, England Oct 26-29, 2016 Gidado M, Useni S, Eneogu R, Ubochioma E, Adegbola A, Chukwuemeka I, Ogunlade T, Meis M.

2 Objectives--1 Background and country context FAST Approach to pilot Achievements FAST pilot Institutionalization and scale-up Results of scale-up Discussion Conclusion Appreciation

3 TB Situation Nigeria (2015 Global TB Report) Population: 177,000,000 DOTS centers: 5,398 AFB microscopy centers: 1,515 Culture DST laboratories: 6 GeneXpert laboratories: 96 Incidence Rate: 322/100,000 Total notified cases 2014 all forms: 91,354 CNR all forms for TB 2014 (per 100,000): 15.4% HIV prevalence : 3.4 % TB/HIV co-infection: 19% (16,066 cases) ART centers : 491 (85% TB/HIV co-located) MDR among new TB cases: 2.9% MDR among previously treated TB cases: 14%

4 FAST Approach to Pilot Adapted Guidelines, SOPs and training materials for FAST strategy Trained pool of facilitators TB diagnosis in line with National Guidelines (algorithm): use of microscopy and GeneXpert Used existing National recording and reporting tools to monitor the effectiveness of FAST Selected 2 (either secondary/tertiary) referral health facilities in 6 states (12) Proximity/access to AFB and Xpert machine (7 out of 12 had Xpert machines

5 Key achievements - FAST Pilot 7 out of 12 facilities managed to reduce time to diagnosis (5 had Xpert machines) 6 out of 12 facilities managed to reduce time to treatment (5 had Xpert machines) 6 out of 12 reduced both times to diagnosis and treatment (5 had Xpert machines) 11 out of the 12 facilities had 3 months service interruption during the pilot period 4 out of 11 had increase in average monthly Presumptive TB cases tested and TB Patients started on treatment Promising strategy despite prolonged strike action by government health care workers (3 out of the 6 months pilot period)

6 FAST institutionalizing scale up In National Strategic Plan : scale up FAST to other states and facilities As TB infection control measure (stopping transmission) and also considered as strategy for increasing TB case finding and treatment (especially for settings where case detection rates are low)

7 50% 40% 30% 20% 10% 0% Average Time to diagnosis 21% 45% same day 29% 25% 22% 23% next day Immediate results 3-5 days 24% 9% > 5 days Baseline (Jan-Dec. 2015) Follow up (Jan - Jun 2016) 50% 40% 30% 20% 10% 0% 46% same day Average Time to treatment 36% 12% 25% 19% 22% next day 3-5 days 22% 18% 3-5 days Baseline (Jan-Dec. 2015) Follow up (Jan - Jun 2016) 5 Average monthly TB Patients notified Baseline (Jan- Dec. 2015) 0 1 Follow up (Jan - Jun 2016) All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

8 G.H Ugba Benue state (with GeneXpert machine) Average monthly time to diagnosis 64% Average monthly time to treatment 11% 39% 20% 33% 42% 22% 27% 6% 35% 4% 30% 12% 25% 20% 10% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

9 G.H Ikot Abasi Akwa Ibom state ( with GeneXpert machine) Average monthly time to diagnosis Average monthly time to treatment 72% 51% 51% 46% 44% 1% 10% 16% 9% 2% 10% 9% 23% 18% 21% 16% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

10 G.H Otukpo Benue state (with GeneXpert machine) Average monthly time to diagnosis 60% 20% 22% 20% 8% 10% 59% 0% Average monthly time to treatment 50% 34% 30% 31% 23% 20% 11% 0% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days 6 Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

11 G.H Vandeikya Benue state (with GeneXpert machine) Average monthly time to diagnosis 74% 36% 57% 21% 2% 7% 2% 0% Average monthly time to 81% treatment 44% 21% 19% 11% 16% 7% 0% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

12 St. Joseph-Akwa Ibom state (No GeneXpert machine) Average monthly time to diagnosis 81% 84% Average monthly time to treatment 46% 50% 15% 19% 1% 0% 0% 0% 22% 15% 15% 11% 24% 17% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days 6 Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

13 G.H Etinan Akwa Ibom state (no GeneXpert machine) Average monthly time to diagnosis Average monthly time to treatment 60% 46% 40% 63% 47% 17% 16% 0% 0% 21% 7% 24% 12% 4% 26% 18% same day next day 3-5 days > 5 days same day next day 3-5 days 3-5 days 3 Average monthly TB Patients notified All forms Bacteriogical (SS+) Bacteriogical (GeneXpert)

14 Discussion Scale up to states for optimizing FAST: - enabling environment/policy or minimal bureaucracy - easily assessable with minimal logistics challenge - relies to a large extent on strong and efficient health systems e.g effective logistics/commodities management including anti-tb medicines - National policy of GeneXpert as the initial TB diagnostic tool

15 Conclusion Complementary approach of GeneXpert technology as initial TB diagnostic tool and scale up of FAST strategy has a great impact on enhancement of TB infection control and also TB cases notified

16 Thank you for Listening

17 Appreciation USAID Mission KNCV TB Foundation FMoH NTBLCP SMoH Lagos SMoH Benue SMoH Akwa Ibom