A pilot study implementing an mHealth triage intervention for health care workers at

primary health clinics in Blantyre, Malawi

Nicola DesmondLiverpool School of Tropical Medicine

Malawi-Liverpool-Wellcome Trust

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

Responses to ABM

Recognition

HCW diagnosis practices

Recognition of severity

Social validation of illness

Lay interpretation of symptoms

Misdiagnosis as malaria

Action

Timeliness dependent on social

position

Financial constraints

Unsystematic triageHigh numbers of patients

Perceptions of health services

High numbers of patients

Erratic consultation systems

Unsystematic & informal triage

Primary health level contributorsPrimary health level misdiagnoses

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

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

mHealth

Consistent

Improved diagnosis

Active prompts

Training & monitoring

tool

The Intervention

Pilot study framework

Training

• ETAT triage • mHealth tool• Study protocols

Intervention• 5 Blantyre PHC

• Bangwe• Chilomoni• Mpemba• Ndirande• Zingwangwa

• 0-14 year olds• Monitoring of

patient pathways

Evaluation

• Baseline & post-intervention

• Mixed methods

Oct ‘12 Dec‘12 – May ‘13 Oct‘12 – June ‘13

Chipatala RobotsOutcomes

CHILD IS EXTREMELY SICK. TO BE

SEEN IMMEDIATELY

CHILD IS VERY SICK. PRIORITY MUST BE GIVEN IN THE QUEUE

CHILD HAS MINOR

INJURY/ILLNESS. TO WAIT IN THE

QUEUE

EMERGENCY

PRIORITY

QUEUE

Improving patient pathways

Patient enters PHC

HCW conducts rapid triage

Patient assigned E, P, Q

Clinician conducts consultation &

enters dataAdapted from Sarah Bar-Zeev (2012)

Patient follows clinician

instructions

Patient Triage

PHC Clinician

QECH Fieldworker

If referred to QECH data entered on arrival

The Evaluation

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

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

Evaluation

Quantitative Qualitative

Results

Total Cases Bangwe Ndirande Chilomoni Zingwangwa Mpemba

41358

1204310412 9191

5091 4621

Number of Cases Triaged Dec 2012 - May 2013

Total catchment population by clinic

Ndirande 213,613Zingwangwa 142,594Bangwe 131,667Chilomoni 80,940Mpemba 48,176

Total 616,990

Triage evaluation

Time taken (Mins)

Paediatric cases

E 28.34 131P 44.64 13,585

Q 59.02 26,452

Mean time between triage and consultation

(Anova: P < 0.001)

Age distribution of triage assessments

Queue Priority Emergency0.0

10.0

20.0

30.0

40.0

50.0

60.0

< 1 year1-56-10>10

Triage compared to clinician evaluation

Queue Priority Emergency0.0

20.0

40.0

60.0

80.0

100.0

Triage QueueTriage PriorityTriage Emergency

Clinician Assessment

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

ReferralsOut 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

Overall mean time 5.5 hours

Triage evaluation

Time taken (Hours)

Paediatric cases

E 3.5 33P 5.7 193Q 6.8 14

(Anova: P = 0.39)

Successful referrals

Patient journey modelling: Bangwe

Improved patient flows

‘There is now improvement, those children don’t take long to be attended to.” 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

‘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

Improved recognition of severe illness‘Triage is being done systematically and children with critical illnesses are being identified and treated on time’ HCW

‘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

‘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

Conclusions

• Separation of sick from non-sick

• Paediatric definitions• Consistent quality of triage• High levels of ownership• High levels of acceptability

Health worker wearing Chipatala Robots T-Shirt

Mphatso Cheonga, 2012

“I only wish the primary health centres could improve on diagnosis

and recognising symptoms quicker...”

Acknowledgments InvestigatorsNaor Bar-ZeevQueen DubeNorman LufesiElizabeth MolyneuxSarah Bar-ZeevRob Heyderman

MRFThomasena O’ByrneChris HeadLinda GlennieSara MarshallRachel Perrin

AcMen team at MLWDeborah NyirendaBernadetta PayesaMalango MsukwaAlick MasalaLilian UlayahFarouk EdwardWilard Chilunga

Blantyre DHODr Owen MalemaDr Eltas NyirendaDr Palesa Chisala

ETAT trainersZondiwe MwanzaThembi KatangweYabwile MulambiaMtisunge Gondwe

D-Tree InternationalDr Marije GeldofDr Marc Mitchell

Phidelis Suwedi

Primary Health CentresBangwe: Martha Makuta

Christopher MkungaChilomoni: Dalitso Namasani

Ndirande: Francis PhiriMpemba: Rodgers Kuyokwa

Zingwangwa: Margaret ChingonaAll photos reproduced by kind permission of

participants