Malawi Health Management Information System

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Malawi Health Management Information System

• Chris Moyo
• Central Monitoring and Evaluation Division
• May 2009

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Summary of presentation

• Introduction
• Implementation status of HMIS in Malawi
• Designing HMIS Guiding principles
• Achievements and Strengths
• Weaknesses and Implementation Challenges
• General Guiding Principles for HMIS review

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Introduction

• A comprehensive and decentralized routine health
  management information system (HMIS) being
  implemented in the country from January 2002.
• Developed through consultative and collaborative
  process
• Objective is to provide reliable, relevant,
  timely and complete information for health
  workers at all levels to facilitate decision
  making process.

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Guiding Principles
C. Human Resources
Strong links between all data collection systems
Data collection for local analysis and use
Simple to establish and maintain
Paper and pen based
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Guiding Principles of HMIS

• Data for decision making
• collection of only essential health data used for
  decision making
• Data collection for local analysis and use by the
  health worker -Data collected by all health
  workers as they perform their day to day duties
• Data processing and analysis are done starting
  from the point of collection
• Integration of all routine information systems
• Simple to operate and maintain

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Guiding Principles (contd.)
Decision for Action
Action
Data for Decision
Decision
Information
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HMIS Indicators and Tools
110 core health sector indicators have been
developed for monitoring EHP, SWAp, MGDS, MDGD
Development of HMIS tools for collecting data for
calculating indicators
HMIS registers, data aggregation and reporting
tools
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Health Information Flow in Malawi
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MANAGEMENT OF HEALTH INFORMATION
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Achievements Strengths
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Policy EnvironmentHealth information policy

• Provides a policy and strategic framework for
• Management of health information to ensure
  required information is reliable, available and
  accessible to all users
• Fostering use of information in planning and
  management of health services
• Monitoring health sector performance

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Implementation of a comprehensive
decentralized HMIS.
Strengths identified

• Health information system
• policy strategy has been
• developed approved by MOH

HMIS activities included in the joint POW for
the implementation of SWAp
Use of wide range of data sources
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Key Achievements (1)

• Policy Environment
• Health information system policy and strategy
  developed
• and in use
• System developed and functioning
• Development of a comprehensive and decentralized
  health information system
• Paper based at facility level and electronic at
  district national level using DHIS software.
• Set of national core health sector indicators
• Data collection tools developed and in use
• Data collated monthly at facility level, reported
  quarterly to DHO

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Key Achievements (2)

• Process
• Institutionalization of HMIS Zonal review
  meetings for improving data quality, use and
  reporting
• Harmonization and integration with other ME
  systems for
• HIV/AIDS
• SWAp
• Malawi Growth and Development Strategy (MGDS)
• Millennium Development Goals (MDG)
• Availability of data
• Data available at facility, district and national
  levels (although delayed)
• Half-yearly and Annual HMIS Bulletins published
  and disseminated regularly

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Key Achievements (3)

• Data use
• HMIS data used in District Implementation Plan
  preparation and monitoring its implementation
• Capacity building in headquarters, zones,
  districts and central hospitals strengthened
• Training of Health workers in data collection,
  analysis and use
• Assistant Statisticians deployed for data
  processing
• Computerization of data processing at Hqs,
  districts and CH levels
• HMIS introduced in health training institutions

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Weaknesses Implementation Challenges
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Some sub-systems not yet fully developed
Weaknesses identified

• Low data quality
• completeness, reliability
• timeliness

Weak linkages between various sources of data
Limited data analysis use of information at
facility district levels
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Implementation Challenges/ Issues(1)

• 1. Poor Data Quality
• Completeness of data
• Not all health facilities (Public, CHAM and
  Private) are submitting reports to district
  health office
• Not all data elements are reported by those
  facilities that report
• Timeliness of reporting
• HMIS has been unable to provide data timely
• Facilities send Quarterly Reports to DHO late
• DHOs send reports to Headquarters late
• Correctness/Accuracy
• Reported data not the same as in the Registers

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Implementation Challenges/ Issues (2)

• 2. Inadequate in addressing the data needs at all
  levels
• Inadequate appreciation for use of HMIS in
  decision making and DIP preparation
• Weak ME systems at district level resulting in
  overemphasis on national level capacity
• Lack of ownership of the system
• 3. Human Resource crisis in the health sector
• Inadequate HR for data collection, analysis and
  dissemination especially at facility level

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Implementation Challenges/ Issues (3)

• 5. Some sub systems not fully developed
• unable to provide the required data in
  appropriate formats
• 6. Persisting weak linkages between various
  sources of data within the Ministry
• Promotes parallel ME systems designed to respond
  to funders
• 7. Unable to respond to emerging
  issues/initiatives
• Many initiatives have taken place after the
  system was introduced
• Need to have a review of HMIS

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Opportunities for further development
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General Guiding Principles for HMIS review
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Data collection guiding principles

• WHO health care workers at all levels
• WHAT Essential Data Set
• WHEN daily collated weekly processed monthly
• WHERE work sites, facilities, districts (info
  filter)
• HOW data sources (tally sheets, registers etc)
• WHY -to monitor progress towards goals, targets
• -to plan new policies and changes
• -to evaluate current services
• -to assist health management processes

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What data elements should be collected?

• Can provide useful information (affecting the
  management decisions)
• Cannot be obtained elsewhere
• Are easy to collect
• Do not require much work or time
• Can be collected relatively accurately
• ESSENTIAL DATA SET based on indicators
  reflecting the health status of the community

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Essential data set
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Essential Dataset
WHAT? The minimum amount of data that needs to be
collected WHY? for the effective management of
services which allows them to make the greatest
impact on the health needs of the community which
they serve (improving coverage quality)
HOW? through routine data collection
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EDS - Choosing a Type

• Data led
• Focuses on the need to collect data which is
  required, is of interest or which may be useful
• Is usually vague on what information output can
  be obtained from data
• Action-led
• Focuses on the need to collect data that
  reflect identified priority health needs
  are required by pre-determined indicators
• Indicator driven national local
• Usually directly linked to specific objectives
  targets
• Action-led systems are the most practical way to
  go

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Developing an Action-led EDS make it simple
sustainable . . . 1

• Data collection
• start small - as data quality improves
  systems are streamlined - add slowly
• collect data linked to objectives - that can
  be used to calculate indicators
• collect only data that is easily available -
  determine easiest site for recording of data -
  do not duplicate points of data collection
• use clear standardised definitions
• train provide ongoing support to data
  collectors improve data quality
• Data collection tools
• use a minimum number of tools - user friendly,
  familiar acceptable

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Developing an Action-led EDS make it simple
sustainable . . . 2

• Use of information
• Indicators linked to national local issues
• Vertical horizontal flow of information
• Information interpreted routinely
• Information used in decision-making planning

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EDS at each levelThe Information filter

• Standardised
• Usefulness
• Address the needs of all stakeholders
• User-friendly
• Dynamic

Indicators, Procedures, datasets use of info
for ACTION
International IS
Community
National Inf. Systems
District
Zonal Information Systems
Province
National
District Information Systems
International
Community Information Systems
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Principles on data flow
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Data Flow traditional model
National Level Service Management

• EPI
• TB
• Notifiable diseases

Hospitals
Zonal office
Maternal Health
HIV/AIDS
District Management - LA
District Management - Prov
District HIS Units
Maternal Health
HIV/AIDS
TB
Hospitals
PHC Services Prov / LA
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Data flow-streamlined model
National HMIS/ME Division
Zonal HMIS/ME Office collate , analyse
disseminate data

• Health Programmes
• EPI
• TB
• Maternal

District Management Team interpret use
information District HIS Unit capture, validate,
analyse present disseminate
Community Structures
HEALTH SERVICES collect, collate, validate,
analyse data
PHC LA PHC
Hospitals
Special Services
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Principles to Practice

• KISS (Keep it Simple Sustainable)
• Keep it useful
• Be sensitive to reality
• Review EDS periodically
• Collect mainly (only) what you really need to
  know

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Essential data set
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Thanks for your attention