Health Management Information System HMIS in Zanzibar

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Health Management Information System (HMIS) in
Zanzibar
John Lewis
GOALS

• Develop an integrated HMIS
• Develop a culture of indicator information USE
  in the health services
• Develop human and institutional capacity

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Background

• HMIS Unit established in 2001
• strengthened in 2004 (Funded by DANIDA, HISP
  started work in 2005)
• Problems by that time
• Fragmentation - Multiple uncoordinated data
  collection forms and routines
• Poor quality of data ?? little use
• Poor capacity and routines for analysing and
  using information at all levels
• Poor capacity at HMIS focal points in districts,
  hospitals central HMIS unit

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Approaches to the functional HMIS (1)

• Multiple data sets in data repository
  software
• - Routine health data
• Population /census data
• Health facility resources availability data
• Human resources
• Finances
• Population health surveys

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Approaches to the functional HMIS (2)

• Develop essential indicator set and streamline
  data collection forms accordingly
• Integrated Monitoring Evaluation system
• Include targets in system

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Approaches to the functional HMIS (3)

• Capacity development
• Strengthen HMIS unit including Pemba
• HMIS focal staff to run HMIS
• Facility staff data collection use
• Managers at all levels analysis and information
  use
• Long term sustainability
• Continuous education Masters PhD programmes
  UDSM, SUZA Oslo University

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Progress to date

• Essential indicator set developed
• Revised data collection forms implemented
• Some programmes still insisted on additional
  forms
• Software system (DHIS) developed implemented
  for Districts Mnazi Mmoja hospital
• Other hospitals in the process (but no computers)
• - Sample data extracted from the software
  database attached
• Training of HMIS staff including UDSM course
• HMIS unit gradually being strengthened

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Focus ahead

• Improve QUALITY (Completeness, Accuracy and
  Timeliness) USE of information
• Disseminate indicator-based and all other
  important information to the appropriate
  stakeholders regularly
• Establishing HMIS continuous training program at
  local educational institution
• Monitor evaluate the HMIS process

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Challenges ahead

• Vertical programs lack consistency in adhering to
  corporate commitments to HMIS process - critical
• Collaboration between programs and HMIS unit
• Poor capacity at all levels
• Lack of awareness and commitment to some key
  managers in some districts
• Health facility staff yet to learn on the new
  HMIS
• HMIS implementation relies upon capacity
  support at facility district levels - critical

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Sample data Top ten Quarter 1, 2006
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Sample data Top ten Quarter 1, 2006
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Sample data Immunization Vitamin A coverage
for children Quarter 1, 2006
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Sample data Immunization Vitamin A coverage
for mothers Quarter 1, 2006
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Sample data FP use for selected methods Quarter
1, 2006
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Sample data Malaria Quarter 1, 2006
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Sample data Infant / Maternal deaths Quarter 1,
2006
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Distribution of Health Facilities
Unguja
Pemba
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Constraints

• Data collection under HMIS has left out some
  essential RH indicators e.g. indicators for the
  assessment of BEmoC, CEmoC and quality of care.
• No timely analysis of the collected information
  under HMIS
• No timely feedback to all stakeholders
  responsible for data collection
• No forum for dissemination of health-related
  information so that stakeholders can share
  problems and concerns so far obtained under the
  new data collection system of integrated HMIS.

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Constraints

• -
• Low priority is given to data by most of the
  concerned management. Most statistical units
  have staffs who are not competent for the work.
• Almost no resources are allocated for data
  collection and management. Things like
  stationery for data collection are frequently
  reported to be missing.
• No adequate skills for appropriate and timely
  data collection, analysis and interpretation to
  give the intended result. Management shows no or
  little initiative to build the capacity of staff
  responsible for information collection.

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Constraints

• No equipment for data management and storage at
  the peripheral level, while we require the same
  staff at the peripherals to collect, manage,
  analyse and utilise their own data for measuring
  their performance and for planning their
  activities.
• Collected information are not well organised and
  utilised for purposes that are intended for, and
  most of the time they are left totally unused/or
  not effectively used.
• Collected information are not of the required
  quality due to the above-mentioned reasons.

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How HMIS can Work Together with the Programme to
strengthen the Information

• There should be timely availability of data
  collection forms, timely analysis at all levels
  and timely feedback to RH programme and all other
  stakeholders so that the programme can make use
  of the minimum accepted data collected under HMIS
• Capacity building in data collection, management
  and utilization should be provided so that all
  those responsible to collect data for HMIS speak
  the same language or dancing the same tune.

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How HMIS can Work Together.

• There should be a stakeholders forum for sharing
  of information and having a collective discussion
  on problems encountered in data collection,
  analysis, interpretation and utilization under
  HMIS.
• Regular data auditing to ensure quality of data
  collected need to be carried out by technical
  team on HMIS involving data focal persons at each
  level of the programme/project/unit.

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How HMIS can Work Together

• Scaling up quality data collection, analysis,
  utilization at the maximum desirable level and
  strengthening integration with all potential
  stakeholders (including private practitioners)
  should be the focus and the way forward for the
  successful HMIS.
• This can be only achieved if adequate involvement
  of all players is enhanced for the necessary
  support and ownership of the health information
  system.

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Some achievements gtgtgt Big challenge
AHSANTENI