mHealth

2

mHealthAggregate

Clinical Use

Patient Centered

Program tracking

Medical Sensors

Diagnostic tool

Smartphone

Routine reporting

SMS-reminders

Treatment Support

Voice consultation

Low-end Phone

Use case Types of mobile application & data bearer

Plaintext SMS Structured SMS SIM-apps “GPRS-apps” (Java J2ME) Mobile Browser – offline/online Voice! Interactive voice response (IVR)

Paper is still a viable option in many contexts!

Sheet to help compose SMS message:TEST. 8. 0. 0. 8. 7. 3. 4

Aggregate data: routine reporting of health data from facilities/communities

RobustAvailableNot so prone to theftsometimes privately owned Long standby time on one charge (e.g. with small solar panel)Local service /maintenance competenceLocal mobile phone literacy Mobile coverage [ where there is no road, no power, no fixed

line phone]

Low End Mobile Phones

mHealth & HMIS goals

Timeliness Assist local decision making based on accurate

data on time

NB: Not all solutions have to be measurable in terms of improved health service quality.

Cost effective HMIS is also important

How can mobiles improve HMIS?Data Quality - Validation rules on phoneOn the spot data capture and transferSave time and reduce mistakes caused by manual collation and transfer

of data

mHealth application areas Routine data (HMIS) Notifiable Diseases (IDSR) Individual “Tracking” => aggregate Stock-outs Individual health monitoring Reminders Etc.

Types of mHealth dataName based/program tracking (ANC, HIV,

TB)or aggregate data (ISDR & routine HMIS)

CHALLENGES Security of identifiable patient data Complexity of work routine (not easy to capture

on a small screen – or any screen) mHealth - Additional burden or Helpful tool?

mHealth; empowering health workers or job surveillance?

Integrate with GIS/GPS – for disease surveillance or can be used for task force surveillance and control

[Example: daily reporting Punjab]Some managers would love to have a camera-drone following their

health workers 24-7!

Missing Feedback in HMISSupervision feedback only when there are errors, mistakes,

shortcomingsSupervision is often irregular and non-supportive and requires

time & resourcesMobile “Feedback” (access to processed data) Progress over time Comparisons to other organization units [vertical/horizontal] HMIS metadata – completness, timeliness % Push or Pull?

What’s in it for the end users?

Save money and time spent on travel [maybe!]More time for service provision [ideally…]Closed User Group (CUG) agreement with

mobile operator = free communication with colleagues!

Processed data ”Feedback”Phone Credit top-up/ reimbursements/bonus

Pilotitis in Uganda

Problems with mHealth PilotsAdditional burden for health workersDonor short attention span - unsustainableWhat works as a pilot does not necessarily scalePilots may focus on technical feasibility while ignoring larger

organizational and political mechanisms (e.g. health worker unions)

Hard to evaluate and-compare across mHelath projects

Partners in mHealth“Ecosystem of actors”: Ministry of Health, NGOs,

researchers, Programme Donors &…

Mobile Operators Network coverage Closed User Group Agreement Social responsibility or New revenue streams?

BUT mHealth Initiative may get stuck with one operator!

Win-Win-Win?