Managing Health Information in Low Resource Settings
William A. Lester
Chief Information Officer - EngenderHealth

Objectives of the Presentation
• Identify some of the problems associated with capturing,
managing, and sharing health data in low resource settings
• Discuss some existing ICT solutions, with a focus on 3 case
studies
• Discuss what’s missing and what doesn’t work
• Help the presentation participant to better evaluate the health
toolkit
• Capture suggestions to take back to the developers of ICT
solutions

Definitions
• Information and Communications Technologies (ICT)
• Low Resource Settings
• Clinics
• Community-based healthcare organizations
• Health Management Information Systems (HMIS)
• eRiders/iRiders
• PDAs (Personal Digital Assistants)
• Interoperability
• Resource Bucket

The Problem - 1
• The number of people living with HIV/AIDS continues to grow
• The crisis is particularly acute in the developing world
• Front line workers operate out of public and private clinics, and
community and religious groups
• Providers need to capture, manage, and share health care
information
• Developers assume local infrastructure will support prescribed
solutions
• If the resources are not in place, the solutions will fail
• Digital Divide/Last Mile Problem
• The physical distance may be short, but the resource gap can be
insurmountable

The Problem - 2
So, the problem we are facing is to
…find effective solutions to capture, manage,
retrieve, and share health care information that
will work in low resource areas…

The History - 1
• In 2004, under a grant from the Soros Foundation, we visited
5 countries in southern and western Africa (Botswana, Ghana,
South Africa, Swaziland, and Zambia)
• We conducted focus groups with 60 individuals (all involved in
HIV/AIDS care within organizations in their countries)
• We explored patterns and practices related to data capture,
management, and sharing, as well as identifying the most
critical gaps and shortcomings associated with current data
management systems
• We performed in-depth technology assessments of several
NGOs in these countries

The History - 2
• In parallel, we looked at existing proprietary and open-source
medical records systems:
– Care2x
– CareWare
– Cell-Life
– DHIS
– EpiInfo
– ESTHER/ESOPE
– FUCHIA
– GAP Zimbabwe
– Haiti HIV-EMR
– HIPS DOCA+
– OpenEMR
– OpenVista
– PKC
– SOLUTIONS
– SQL Clinic
– Starfish Project
– VOXIVA

The History - 3
• We wrote a report (static)
• We created a web site (dynamic)
– Resources
– Tools
– Field Research
– Partners and local organizations
www.healthtoolkit.org

Interesting Study Results
• Most clinics in low resource areas are overworked,
understaffed, lacking in many basic necessities
– Capacity building is necessary
– Training of staff, especially non-medical staff, is needed
• When dealing with HIV/AIDS, many patients never get to a
clinic
– The contact is often a local person from a community or religious
affiliation
– Faith-based NGOs play a significant role in the process
– Community-based healthcare workers need training

Medical Information
• Medical records
– Patient information
– Patient history
– Current status
– Treatment Regimen
– Test results
• Clinic Management
– Appointments
– Best practices
• Local health information and regulations
• Regional information
• Global information
– Research
– Journal Articles
– Communities of Practice

Medical Information
• Medical Records Requirements
– Unique
– Searchable
– Comply with policies of privacy and access
– Safe (backup)

Beliefs
• Paper-based systems are the only solution for low resource
areas
• Staff are unskilled and not capable of learning new ways.
• The costs of new solutions are prohibitive
• There’s no local support available to keep new systems up
and running
• The return on investment is minimal. There’s nothing to be
gained by implementing new systems and solutions

Suggestions
• There are other solutions, beyond paper-based systems
– Affordable
– Sustainable
– Appropriate for low-resource settings
• There are cost-effective approaches to training staff
– In the use of ICTs
– In long term capacity building skills, like clinic management,
informed consent, infection prevention, etc.
• One size does not fit all
– In some locations, there is no better solution, yet…
– Often, there are many solutions (which creates a new problem)
– In all locations, there is room for improvement

Standards
• The need
– Data standards are the principal informatics component
necessary for information flow and exchange.
– Data is collected and reused for multiple purposes
– Common data standards support effective assimilation of new
knowledge into decision support tools.
• The problems
– There is no agreement on standards. There are competing
standards experts.
– There is only negligible sharing or exchange of health
information concerning individuals or communities between the
disparate electronic health record systems employed by provider
organizations.
– Unique identifier

Interoperability*
• Uniform movement of healthcare data from one system to another
such that the clinical or operational purpose and meaning of the data
is preserved and unaltered.
• Uniform presentation of data, enabling disparate stakeholders to
use different underlying systems to have consistent presentation of
data when doing so is clinically or operationally important.
• Uniform user controls, to the extent that a stakeholder is
accessing a variety of underlying systems, and the contextual
information and navigational controls are presented consistently and
provide for consistent actions in all relevant systems.
• Uniform safeguarding data security and integrity as data moves
from system to system such that only authorized people and
programs may view, manipulate, create, or alter the data.
*Healthcare Information and Management Systems Society 2005

Web-based Resources
• Trusted sources
• Timely information
• Federated search engines
– Information buckets
– Prioritized by user
• Tagging, XML

Case Study #1: The Starfish Project*
Location:
Sagamu, Nigeria
Participants:
Two private clinics
Ogun State University Teaching Hospital
New York Presbyterian Hospital (Center for Special Studies)
Situation:
Two private clinics, affiliated with a teaching hospital. Entire patient
caseload are HIV/AIDS and related. ARV regimen in place, using
donated drugs from the states. However, partner organization
wanted a way to monitor clinic records, including patient records,
prescribed treatment, test results, and drug inventory.
*Based on presentation by Rachel Yasky/The Starfsh Project

The Starfish Project - 2
http://www.thestarfishproject.org
Vision
- Promoting a collaborative care model, in which clinicians from
the USA and clinicians from Nigeria work together to care for
patients in Nigeria
- Information exchange regarding advances in clinical practice,
research, new policies, etc. can be shared and discussed
across long distances
- Develop a model to demonstrate an innovative approach,
using technology and organized communication systems, to
enhance health care delivery in a limited-resource setting

The Starfish Project - 3
Visit to Sagamu (May 2004):
- Who: EngenderHealth, Consultants, Starfish
- Where: 2 Clinics, University, local NGOs
- Why:
Assess current physical environment
Do an information audit
Evaluate internet access
Evaluate possibilities for a computer network
Identify key staff
Demo HMIS applications

The Starfish Project - 4

The Starfish Project - 5
Recommendations (three stages):
- Stage 1:
Dedicated dial-up line
Small Server (ShuttleX)
Build collaborative database application (separate project)
Train one local staff person (iRider)
Evaluate results
- Stage 2:
If warranted, expand project
Wired network
Satellite connection to the University
IT Support person (eRider)
Evaluate results
- Stage 3:
Complete network
Train all staff
Evaluate results
Start process again for future development

The Starfish Project - 6
• Began work on Starfish Database
– Written in MS Access (for testing)
– To be ported to PHP/MySQL
– HMIS system, including:
• Medical records
• Patient Tracking
• Laboratory records
• Inventory Management
• Clinician <-> Clinician discussions
• Multi-user, multi-station

Summary Tab
Simple look and feel
Tabbed screens
Unique ID #
English

Demographics Tab

Visits Tab - Popup
SOAP Contains 4 fields:
Subjective, Objective,
Assessment, and Plan.
Remember that this form
can be filled out for each of
a patient’s visits.

Consultation Tab

Labs Form

Other Forms
• Other forms within the patient database system include:
– Data Export: a form that allows all patient data to be
automatically exported to a new file (which can then be sent to
Starfish).
– Date Import: a form the allows data from a file downloaded from
Starfish to be brought into the database.
– Starfish Bulletins: a form that pops up automatically after a
data import, and may also be opened manually, that notifies the
clinic of there are new Starfish bulletins, and if so allows them to
be printed.
– Inventory Review: a form for reviewing the clinic’s stock of
drugs and to manage that inventory.
– Log Incoming Bottles: a form for logging incoming bottles of
drugs, as from Starfish, into the inventory.

Reports (Examples)
• Visit Report: all fields from every field on the visit popup on one page. This
is the report that prints when the printer button is pressed next to a row on
the visit tab.
• List of upcoming visits, overdue visits
• Report for Lab of requested tests that do not yet have results entered
• List of all messages written about one patient on the consultation tab
• List of all NEW messages about ALL patients (the report we called “Starfish
Bulletins” in our first meetings)
• Patient Chart: all the information that would go on a patient’s chart
• This week’s visits (taken from [Next Visit Date] fields).
• This month’s visits in calendar format
• List of all of the comments entered for a patient on the Nurses tab of Visit
popup.
• Patient visits stats, including past weights, CD4s, etc, from all past visits, in
tabular format

Summary of The Starfish Project
• Continues today
• Model for other similar collaborations
• This project had external money and support
• Improvements included new generator, satellite internet
connection
• Plans for a new clinic facility

Case Study #2: Uganda Health Information
Network (UHIN)*
Location:
Uganda (Mbale and Rakai districts)
Participants:
Satellife
Uganda Chartered HealthNet
Makerere University Medical School
Connectivity Africa (IDRC funded)
Situation:
In Uganda, collecting data from rural health centers on utilization,
disease surveillance, and supply management is difficult and
expensive. Continuing provider development is expensive and
difficult to sustain for workers.
*Based on presentation by Holly Ladd/Satellife

UHIN - 2
www.healthnet.org
Vision
- Provide affordable connectivity for healthcare information
exchange
- Provide a method for data collection and exchange
- Make it easy to learn and use by non-technical workers
- Make it sustainable

UHIN - 3
Solution
- Handheld computers (PDAs) in 160 health centers
- 500 healthcare workers trained to collect, send and receive
information
- Wireless access points at HCIII
/ HC IV
- Use existing cellular network

UHIN - 4
Approach
- Use existing HMIS and other MOH forms
- Provide Health Centers with PDAs
- Route data two-ways overnight
- Provide district health information managers with database
training
- Automate data exchange and uploading to existing database
- Broadcast CME/CPD regularly to health workers

UHIN - 5
• Recycled Hardware (free)
• Battery powered
• Rechargeable
• Nothing lost, if power dies
•Synch with access point
• Pendragon forms

UHIN - 6

UHIN - 7
Router
GSM/GPRS
Wireless
Server
Sub-district
Office
DDHS Office
Ministry of
Health
Village Clinic

UHIN - 8
Access Points

UHIN - 9
Project Focus Year 1
- Proof of concept
- Trial of equipment and network
- Develop protocols
- Train users
- Compare data collection
efficacy and cost

UHIN - 10
Project Focus Year 2
- Expand to 160 sites
- Study on impact of
access to information
- Concentration on provider
education and content
development

UHIN - 11
General Outcomes
- Discussions underway to integrated UHIN into NHS
- Reduced time and cost in data collection and management
- Request for more forms on PDA
- Sustained usage
- Request for more content
- Request for more units and email

UHIN - 12
Data Collection Outcomes
- 24% cost savings over paper
- Sustained improvement in reporting timeliness and accuracy
- More rapid response to disease
outbreaks and critical needs
- Processing reduced from 30 days to
5 days

UHIN - 13
User Feedback
- 75 % report having content at POC improves health care
delivery
- 41% report setting aside their own
funds to replace PDA in case
project ends
- 68% regularly access content
from access points
- All want email, more PDAs and
access points

UHIN - 14
Next Steps
- Country-wide adoption
- Replication this year in another country
- New, less expensive equipment

Case Study #3: Aftercare*
Location:
Cape Town, South Africa
Participants:
Cell-Life
Desmond Tutu HIV Foundation
Situation:
Once patients are accepted into an ARV treatment program,
counselors visit on a regular basis to monitor their status. Often
patients are in remote areas, or not able to get to clinics easily.
Counselors need a better method for collecting data, sharing
medical information with clinicians, and accessing medical
resources appropriate for the patient.
*Based on presentation by Rory Flynn/Cell-Life

Aftercare - 2
Statistics (South Africa)
- 26.5% prevalence rate
- 5.6 million people infected
- 1 million HIV+ people require ART
- 200,000 people currently being treated
Challenges
- Geographical distribution
- Difficulty in administering treatment
- Lacking infrastructures
- Limited resources

Aftercare - 3
Solution
- Trained counselors monitor patients
- Closing the gap between hospital and home
Cell-Life Aftercare Solution
- Uses mobile phones equipped with customized application
software
- Menu-based, real-time system to capture treatment-relevant
data
- Supports home-based care organizations

Aftercare - 4
Goals
- Reduce errors
- Increase throughput
- Attain user satisfaction and comfort
Achieved through
- Simplicity & Consistency
- Confirmed Response
- Participatory Design
- Language localization

Aftercare - 4

Aftercare - 5

Aftercare - 6
Network Availability
- 90% of population have access
- Approximately 65% geographical area covered

Aftercare - 7
Considerations
- Can use most inexpensive phones (i.e. Nokia 1100)
- Cost per transaction varies from month to month depending on
number of transactions received
- Application stored on SIM card
- Can use in any handset

Aftercare - 8
Future
- Migration to Java/GPRS, will lower costs
- Confirmation of successful data capture
- Ability to store and forward later
- Can cater any language
English Afrikaans

Summary of Cell-Life Aftercare
• Cell-Life has identified a number of requirements in order
to further such developments and to grow active
implementations as follows:
– Develop integrated systems
– Establish public-private partnerships
– Source adequate funding
– Adapt technology for other chronic illnesses
– Keep systems affordable
– Build strategic development partnerships
– Interoperability

Acknowledgements
• Open Society Institute Information Program – Budapest,
Hungary
• Teresa Crawford – nonprofit IT Consultant
teresa@speakeasy.net
• Ungana-Afrika http://www.ungana-afrika.org
• Portman Wills – Voxiva http://www.voxiva.net
• Council for Scientific and Industrial Research
http://www.csir.co.za
• Rachel Yassky – The Starfish Project
• Holly Ladd – Satellife
• Rory Flynn – Cell-Life

Resources
Discussion lists, field research tools,
Health Toolkit www.healthtoolkit.org protocols and guidelines, reports
eRiders are roving technology
Global eRiders www.eriders.net consultants who work with a group of
related NGOs, helping each organization
to develop and implement an ICT
strategy
Provides technology solutions to remote
Inveneo www.inveneo.org villages through non-governmental
organizations (NGOs) and through
commercial or government owned
organizations
To promote high quality and practical
Routine Health www.rhinonet.org approaches to the collection and use of
Information Network routine health information in developing
countries, we have created the RHINO
(RHINO) Network, comprised of developing
country governments, donor agencies,
technical groups, and PVOs.

Thank You!

Managing Health Information in Low Resource Settings
William A. Lester
Chief Information Officer - EngenderHealth