Scaling Information Systems in Kano State, Nigeria

1
Scaling Information Systems in Kano State,
Nigeria
Vincent Shaw
2
Jigawa State Some Facts
3
Staffing of the HMIS services

4
Access to electricity and computers

5
Hierarchical arrangement of health services

• Work with
• State HMIS Officer
• National consultant (more or less full time
  contract)
• Focus of my support is to develop the HMIS
  officer and national consultant
• Their focus is on the LGA level and facility level

6
What data is being collected

• 127 data elements
• Only about 50 completed on a regular basis

7
Sept 2003
Jan 2006
Jan 2005
Jan 2004
Aug
May
Nov
60 data submission rate by 8 LGAs
68 data submission rate
Capture of data from facilities initiated
58 data submission rate
Project initiated
Pilot in 8 LGAs and 188 facilities
Expanded to remaining 19 LGAs and 320 facilities
2 Computers purchased
HMIS officer obtains laptop
1 additional computers obtained
International consultant and State HMIS Officer
provide training for facility and LGA staff on
use of information
State HMIS Officer and National consultant
provide training to facility staff and LGA staff
in 19 LGAs
Meetings and workshops with LGA ME officers held
on approx. quarterly basis
8
What are we debating?

• Should we decentralise?
• Accountability
• Increase resource pool
• Improve efficiency
• As a developmental initiative
• Risks?
• Less control over the quality of data entry
• Will accountability increase?
• Will efficiency improve?
• To which level?
• Cannot go to LGA immediately
• No computers, infrastructure (secure and dust
  free venue)
• Questionable ability to support 27 LGAs
• 6 zones (now gundumas), between LGA and State
• 6 computers and generators located at hospitals
• 6 data capturers from efficient LGAs

9
Time taken for data capture
10
What are the requirements?

• Technology
• Computers
• Generators/electricity
• Secure venue
• Staff with appropriate skills
• DHIS data capture skills
• Understanding of information management (draw on
  existing LGA ME officers)

11
Increasing sophistication
12

• Data volume and granularity
• Decision to maintain the 127 data elements
• But are alert to opportunities to integrate
  vertical programmes (increase vol)
• E.g. NPI, DRF
• In terms of scaling, this is held static
• Also a decision to maintain the granularity
  (depth or penetration)
• But we can expect the decentralisation to impact
  on this, and increase opportunities for
  integration

13

• Human resources
• Within the state health system
• Limitations
• Level of education
• Skills level (data capture, but also beyond that
  production of reports and data manipulation)
• Fragile team for provision of support
• Questionable ability to provide ongoing support
• institutionalisation of training capacity is weak
• Advantages
• Have the staff appointed
• Excellent HMIS officer
• Ability to provide limited support
• From an external NGO perspective?

14

• Technical aspects
• Limitations
• No internet access
• Computers (and generators) are scarce resources
• Infrastructural aspects of roads, secure
  buildings, access to electricity
• Advantages
• Robust software
• Decision to introduce Gundumas (District system)

15

• Some considerations
• Balance between the three axis
• Which factors can we control
• Data
• Technical somewhat
• HR only the development
• Accepting uneveness in development
• Different view when viewed from for instance the
  Federal level

High
Data
Low
Weak
Poor
Human resources
Technical aspects
Strong
Well developed