Implementing an mHealth triage intervention for health care workers at primary health centres in urban Blantyre, Malawi - a pilot study

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Dr Nicola Desmond's presentation at Meningitis Research Foundation's 2013 conference, Meningitis & Septicaemia in Children & Adults

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Implementing an mHealth triage intervention for health care workers at primary health centres in urban Blantyre, Malawi - a pilot study

  1. 1. A pilot study implementing an mHealth triage intervention for health care workers at primary health clinics in Blantyre, Malawi Nicola Desmond Liverpool School of Tropical Medicine Malawi-Liverpool-Wellcome Trust
  2. 2. Treatment seeking for acute bacterial meningitis • More than 1 million cases of ABM annually in SSA • Prompt treatment vital to effective management • Late presentation identified as major contributor to high case fatality rates for ABM
  3. 3. Responses to ABM HCW diagnosis practices Timeliness dependent on social position Misdiagnosis as malaria Recognition of severity Perceptions of health services Recognition Lay interpretation of symptoms Social validation of illness Financial constraints Action High numbers of patients Unsystematic triage
  4. 4. Primary health level contributors High numbers of patients Primary health level misdiagnoses Erratic consultation systems Unsystematic & informal triage
  5. 5. Aims  Explore the feasibility of implementing a triage system within PHCs facilitated through the use of mHealth technologies – To develop mHealth algorithm based on Emergency Triage component of ETAT (WHO) – To implement prioritisation system using mHealth triage algorithm – To encourage appropriate referral decisions to QECH & track referrals – To evaluate triage system using mixed methods approaches
  6. 6. ETAT for resource-poor settings • ETAT: Emergency Triage, Assessment and Treatment • Component of Integrated Management of Childhood Illness (IMCI) • Identify children with immediately life-threatening conditions • Reliance on few clinical signs • Assessment carried out quickly if negative • Easy to follow guidelines for all cadres with limited clinical background • Easy to conduct when patients queuing
  7. 7. mHealth Active prompts Improved diagnosis Consistent Training & monitoring tool
  8. 8. The Intervention
  9. 9. Pilot study framework Training • ETAT triage • mHealth tool • Study protocols Oct ‘12 Intervention • 5 Blantyre PHC • Bangwe • Chilomoni • Mpemba • Ndirande • Zingwangwa • 0-14 year olds • Monitoring of patient pathways Dec‘12 – May ‘13 Evaluation • Baseline & postintervention • Mixed methods Oct‘12 – June ‘13
  10. 10. Chipatala Robots Outcomes EMERGENCY CHILD IS EXTREMELY SICK. TO BE SEEN IMMEDIATELY PRIORITY CHILD IS VERY SICK. PRIORITY MUST BE GIVEN IN THE QUEUE QUEUE CHILD HAS MINOR INJURY/ILLNESS. TO WAIT IN THE QUEUE
  11. 11. Improving patient pathways Triage Patient Patient assigned E, P, Q Patient enters PHC HCW conducts rapid triage QECH Fieldworker If referred to QECH data entered on arrival Adapted from Sarah Bar-Zeev (2012) PHC Clinician Patient follows clinician instructions Clinician conducts consultation & enters data
  12. 12. The Evaluation
  13. 13. Evaluation Quantitative mHealth tool • Monitor patient pathways • Assess if systematic and timely Self completed questionnaires • Explore accuracy of E,P and Q assignments pre and post intervention Qualitative Patient Journey Modelling • Baseline and post intervention • Document practice and patient flows • Structured observations Qualitative Interviews • Capture staff feedback • Impact on overall clinic management and practice
  14. 14. Results
  15. 15. 41358 Number of Cases Triaged Dec 2012 - May 2013 Total catchment population by clinic Ndirande Zingwangwa Bangwe Chilomoni Mpemba Total 12043 10412 213,613 142,594 131,667 80,940 48,176 616,990 9191 5091 Total Cases Bangwe Ndirande 4621 Chilomoni Zingwangwa Mpemba
  16. 16. Mean time between triage and consultation Triage evaluation Time taken (Mins) Paediatric cases E P 28.34 44.64 131 13,585 Q 59.02 26,452 (Anova: P < 0.001)
  17. 17. Age distribution of triage assessments 60.0 50.0 40.0 < 1 year 1-5 30.0 6-10 >10 20.0 10.0 0.0 Queue Priority Emergency
  18. 18. Triage compared to clinician evaluation 100.0 80.0 60.0 Triage Queue Triage Priority 40.0 Triage Emergency 20.0 0.0 Queue Priority Clinician Assessment Emergency
  19. 19. Cadre specific levels of engagement • Health Surveillance Assistants (HSAs) – Salaried community health workers – 10,507 (2009) across Malawi – Average clinical training of 8 weeks • Triage conducted predominantly by Health Surveillance Assistants • Nurses rarely involved in triage of patients
  20. 20. Referrals Out of 41,358 children triaged 1.6% (644) were referred to QECH  15.5% (100) - Emergency  74.9% (482) - Priority  9.6% (62) - Queue From the 644 referrals 37.3% (240) arrived at QECH 62.7% (404) of referrals from PHCS did not reach QECH
  21. 21. Successful referrals Overall mean time 5.5 hours Triage evaluation E P Time taken (Hours) 3.5 5.7 Paediatric cases 33 193 Q 6.8 14 (Anova: P = 0.39)
  22. 22. Patient journey modelling: Bangwe
  23. 23. Improved patient flows ‘There is now improvement, those children don’t take long to be attended to.” HCW ‘At Bangwe we are now working together as a team. It is helping us manage the children so much better. We are seeing them far more quickly than before’ HCW ‘In the past even if you come with a child who is very sick your fellow carers could not give you a chance to go in front of a queue for your child to be helped immediately but now things have improved because when a child is very sick s/he is put in front of a queue’ Carer
  24. 24. Improved recognition of severe illness ‘Ever since ETAT started, I have never heard any news that a child died on the way or maybe in the doctor’s room’ HCW ‘Triage is being done systematically and children with critical illnesses are being identified and treated on time’ HCW ‘I am so thankful because of what has happened today. My baby was identified among others that he was an emergency and he was taken in front of the queue to be seen immediately by the clinician and he is now better’ Carer
  25. 25. Conclusions Health worker wearing Chipatala Robots T-Shirt • Separation of sick from non-sick • Paediatric definitions • Consistent quality of triage • High levels of ownership • High levels of acceptability
  26. 26. “I only wish the primary health centres could improve on diagnosis and recognising symptoms quicker...” Mphatso Cheonga, 2012
  27. 27. Investigators Naor Bar-Zeev Queen Dube Norman Lufesi Elizabeth Molyneux Sarah Bar-Zeev Rob Heyderman Acknowledgments ETAT trainers Zondiwe Mwanza Thembi Katangwe Yabwile Mulambia Mtisunge Gondwe MRF Thomasena O’Byrne Chris Head Linda Glennie Sara Marshall Rachel Perrin AcMen team at MLW Deborah Nyirenda Bernadetta Payesa Malango Msukwa Alick Masala Lilian Ulayah Farouk Edward Wilard Chilunga Blantyre DHO Dr Owen Malema Dr Eltas Nyirenda Dr Palesa Chisala D-Tree International Dr Marije Geldof Dr Marc Mitchell Phidelis Suwedi All photos reproduced by kind permission of participants Primary Health Centres Bangwe: Martha Makuta Christopher Mkunga Chilomoni: Dalitso Namasani Ndirande: Francis Phiri Mpemba: Rodgers Kuyokwa Zingwangwa: Margaret Chingona

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