The document summarizes requirements analysis conducted for developing an mHealth application for midwives in Ghana. Interviews and observations of midwives found they had heavy workloads and data reporting burdens. The technology and infrastructure constraints of rural clinics were also identified. Functional requirements and system qualities were defined based on the needs and constraints, focusing on accuracy, learnability and working with limited technology. A sample use case for fever reporting was presented to illustrate how findings were translated into design specifications.

1. Requirements Analysis for an
mHealth Application with
Midwives in Ghana
Olivia Vélez, RN, MS, MPH, PhD
Adjunct Associate Research Scientist
Department of Biomedical Informatics, Columbia University
Senior mHealth Advisor
Maternal Child Health Integrated Program(MCHIP)ICF International

2. Centering Clinical Users in UserCentered Design (on a budget)
Olivia Vélez, RN, MS, MPH, PhD
Adjunct Associate Research Scientist
Department of Biomedical Informatics, Columbia University
Senior mHealth Advisor
Maternal Child Health Integrated Program(MCHIP)ICF International

3. Overview
• What is requirements analysis?
• Why do we do it?
• Methods for requirements analysis
• Case study – Turning requirements data into functional specs

4. What is Requirements Analysis?
• Determining stakeholder needs and translating them into
software/systems requirements
• What do users need
• What will you do to address those needs
• Not how

6. Steps for conducting requirements analysis
• Identify who you are building the system for (hint: might not be just the
end-user)
• Interview stakeholders
• Write, review, and revise requirements with stakeholders
• Write developer requirements and check for consistency

7. Methods for collecting requirements
• Focus groups
• Surveys
• One-on-one interviews
• Observations
• Contextual interviewing

8. What can we learn from focus groups/surveys/
one-on-one interviews
• What stakeholders think they need
• Issues
• Bounce ideas off of one another
• Things they wouldn’t say otherwise

9. Why we need to do observations

10. Why we need to do contextual interviews

11. Methods for writing requirements
• Vignettes
• Use-cases
• Data flow diagrams
• User interfaces

12. Challenges of Health Information Systems in
Low-Resource Settings
• Health information system (HIS) implementations in developing
countries have a failure rate of 20-25% (Heeks, 2006)
• Causes of failure
– Insufficient equipment/infrastructure
– Poor project buy-in
– Lack of resources to support intervention
– Poor design and implementation planning
• Disconnect between local needs and designers

13. Heek’s Design-Actuality Gaps Model

14. Project Context
• Millennium Villages Project (MVP)
• MGV-Net: Comprehensive open source e-health delivery
platform enabling
– Facility-based data capture
– Community-based data capture of individual-level data
– Data storage of patient health records
– Automated mechanism for aggregating data and generating
reports and feedback to healthcare providers and managers

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16. Bonsaaso, Ghana
•
•
Population: 30,000
Primarily farmers and miners

18. Goals & Outputs
• Understand application domain to identify problems and opportunities
that can be addressed using mHealth
• What is the future state we want to achieve?
• Outputs:
– Functional Requirements
– System Qualities
– Use Cases

19. Research questions
•
People
– What is the current workflow of MVP midwives?
– What are the roles and responsibilities of midwives at MVP facilities?
– What is the current experience of the midwives with technology and
their comfort level in learning new technology?
– What are the information needs and information seeking behaviors of
midwives working in MVP facilities in Ghana?
•
Organizations
– What are the issues in collecting data from the health facilities?
– What is the support capacity for and HIS implementation at MVP
Ghana?
•
Technology
– What is the current technology infrastructure at MVP Ghana?
•
Problems & Opportunities
– What is the required functionality needed for the application based on
the need and constraints of the application environment?

20. Design & Procedures
• User centered design approach
• Participant Observation
• Contextual inquiry1
• Review of paper tools (document analysis)
• Iterative Design through usability testing/evaluation
• General interviews
– Non-Governmental Organization (NGO) ICT eReadiness Self-Assessment
Readiness Tool used to guide interview2
– Data quality assessment
• Comparison to country and/or international standards
1. Coble, Maffitt, Orland, & Kahn, 1995
2. VanBelle, 2009

21. Turning data
sources into design
Goal
Is achieved by
enabling…
Use Case
Constraints: restrictions on
System What we aka of
Functional Description to user
Use cases: Requirements: how
GOALS:Qualities:want Non-what
functional
are system interaction such as
and the requirementsto be
achievesystem inputs, how does
can
implemented
availability, task
the system behave, etc.
complete a security, how are the
inputs processed, what are the
Example: Appropriate testing
outputs
Data sources: Participant
and treatment of all patients who
interviews,
interviews
participant observation
observation, Midwife
present with a fever interviews,
Data sources: use cases,
contextual inquiry, document
interviews, document and
analysis, comparison analysis,
Data sources: Midwifewith staff
standards
international standards
interviews, contextual inquiry,
document analysis, comparison
with international standards
Is achieved by
enabling…
Functional
Requirements
System
Qualities
Design
Constraints
…with these
characteristics
…with these
restrictions
Adapted from: http://tynerblain.com/blog/2006/01/04/foundation-series-structured-requirements/

22. Participants
• Interviewed/observed 6 midwives in September 2010, 7 May 2011
Midwife
Interview 1
Interview 2
1
2
3
4
5
6
7
8
X
X
X
X
X
X
X
X
X
X
X
X
X
MW Years Exp. Nursing
Exp.
20
Yes
26
Yes
3
Yes
43
Yes
4
No
42
Yes
8
Yes
2
Yes
• Interviewed key staff members at MVP administrative site: IT manager,
Health Manager, Data Analyst, Data Manager, Telemedicine Project
Lead

23. Results – People
• Midwives had heavy patient loads and intense work schedules
– Average 30 patients a day
– Every other weekend off, 24/7 call schedule
– Little administrative support
• Extensive reporting and documentation requirements
– High degree of duplication

24. Monthly Reporting Requirements
Report Name
Key data elements
Addendum Antenatal/Maternity Monthly Data
Returns
ANC visit information; Malaria prophylaxis; Delivery information
Communicable disease surveillance report
Malaria cases; Pneumonia cases, Diarrhea, AIDS, STDs
Facility report of HIV test kit usage
HIV test kits used
Family planning returns
Contraceptives administered
Immunization and vaccine monthly returns
Vaccines used and immunizations given by age and dose
Institution monthly returns
Malaria medication used
Malaria reports of outpatient cases
Malaria cases (by age and pregnancy)
Malaria reports ITN/SP Stock
Malaria medication used and stock holdings
Midwives return
ANC visit information; Delivery information; Postnatal data; Abortion
data; PMTCT data
Monthly data returns on ArtesunateAmodiaquine
Malaria medication used; Children and pregnant women receiving
treatment
Medication and testing stock
Malaria medication use; RDTs used
National AIDS/STI control programme
monthly returns
HIV testing and treatment; STD testing and treatment; PMTCT data
Outpatients Morbidity
Causes of morbidity
PMTCT monthly returns
PMTCT data
Returns on deliveries
Delivery data
Statement of Outpatients
Patient age and insurance status
Weekly notifiable diseases report
Cholera, meningitis, measles, H1N1, Guinea worm, yellow fever,
polio

25. Poor Documentation Tools

26. Results – People continued
• Low technical self-efficacy
– “They have to come and train us so we are more confident with the computer.
We don’t know what we are doing with the computer. None of us.”
• Limited information resources
– Relied primarily on textbooks
– No access to systematic reviews, journals, or other sources of up-to-date
information
• Perceived limited support

27. Results - Organization
• Data sources are not searchable/easily referenced
• High potential for errors in current documentation practice
• Errors may go unnoticed for a long time

28. Paper Record Storage
Medical Records
Personal Health
Records
Encounter
Registers

29. Fever Register
Action Taken
1. ACT & home
2. ACT & referred

30. Results – Organization Continued
• Only 2 full time technical staff members
• Distance to clinic will make supporting implementation challenging
• No infrastructure for remote support currently in place

31. Results - Technology
• Power infrastructure is limited
– Clinics rely on solar power
• Network infrastructure inadequate
– Inadequate signal strength at some of the clinics
– Network outages
– Internet outages at administrative site

32. From Goals: Overview of Planned Forms
• Patient lookup and registration
• Capture patient register data needed for reporting
• Fevers (malaria)
• Vaccinations
• Prevention of mother-to-child transmission of HIV

33. System Qualities
System Quality Category
Accuracy
Documentation
Interoperability
Document analysis;
contextual inquiry;
Rationale from data
interviews with data
A primary goal of this system is to improve the accuracy of data collection from the
analyst/manager
facilities. Data validation should be a key component of the interface
Interviews with
midwives;
Easy-to-use, picture based manuals should be made available at the clinic due to the
Interviews with IT
lack to technical support available to midwives
Staff
Because OpenMRS will serve as the back-end the system must be fully compatible.
Additional compatibility with other MVP mHealth and eHealth initiatives, particularly the
telemedicine center is highly desirable.
Learnability
Due to the low technical self-efficacy of the end-users and the limited availability of
technical support ease of learnability should take precedence over advanced
functionality.
Resource
Utilization
Midwives see about 30 patients in the morning. Hardware selection should support allow
for this level of use without needing recharging
Security
The system will be used to collect patient data. The phones and the software itself should
be secure. Remote deleting of data should be implemented in case the phone is lost.
Data should be encrypted when sent over wireless network.
Participant
observation
Participant
observation;
Interviews;
Literature

34. Constraints
• Selection of OpenDataKit (ODK)
– Review of existing software available that met identified system qualities and
constraints
• Must work with OpenMRS
• Must work on low-cost Android phones
• Developed within contract requirements
• Minimize text entry

35. Use Case Example
Use Case FR1. Enter new fever encounter
Primary Actor: MW
Preconditions: User was found or entered in patient registration/Look-module and added to patient list
Success end condition: Patient data is entered.
System: Fever Register
1. MW selects patient from list
2. MW verifies patient demographic items
3. MW completes the following items
Encounter date
Temperature
Duration of fever
Test Done
RDT or Malarial Smear results
Danger signs of severe malaria
Anti-malarial treatment given
–
–
If RDT or Danger signs alert if no
If not RDT and Dangers alert if yes
If treatment yes, which medication
Referral
4. MW uploads data to OpenMRS
Extensions:
2a. Data needs to be updated, changes recorded to patient registration
4a. No network connection is available
Data for use case
development came from
participant observation and
contextual inquiry

36. Functional Requirements Example
Name
Gender
DOB
Age
DOB Estimated
NHIS #
Encounter date
Type
Text
Date
Number
Boolean
Number
Date
Possible Values
M/F
DD/MM/YYYY
Calculated from DOB
Yes/No
Alphanumeric 16
DD/MM/YYYY
Duration of fever
Number
Number of days
RDT results
Danger signs,
Malaria
Treatment given
Boolean
Boolean
Yes/No
Yes/No
Boolean
Yes/No
If yes, which
medication
Referral
Text
ACT, SP, Quinine, other
Text
Hospital, none, other
Data Sources
Contextual Inquiry
(Document
analysis)
Participant
Observation
Data Analyst
interviews
Comparison to
standards

37. mClinic

41. mClinic

42. Current Status of mClinic
• Positive feedback from usability testing
• Existing deployments for capturing baseline immunization data and
verbal autopsy data by CHWs
• Refining software and pre-implementation planning, seeking funding
opportunities

43. Contact Information
• Email: olivia.velez@icfi.com
• Twitter: @mHealthNurse
• LinkedIn: www.linkedin.com/in/oliviavelez/

44. Acknowledgements
• National Institute for Nursing Research (P30NR010677)
• Health Services Resource Administration (1D11 HP07346)
• International Development Research Centre
• Rockefeller Foundation
• Novartis Fund for Sustainable Development
• OpenROSA Consortium
• Jonas Center for Nursing Excellence
• National Library Medicine Biomedical Informatics Training Grant (5 T15
LM007079-20)
• PAHO Collaborating Center at Columbia University