1. Health Information Management in Sierra Leone Ministry of Health and Sanitation Abou Bakarr Kamara, Director of Policy, Planning and Information The Lancet Commission on Global Surgery, Freetown, 19 th June 2014

2. The Lancet Commission in Global Surgery - Information Management2 Content 1.Background 2.Data collection 3.Hospital data 4.Feedback Mechanism 5.Risk analysis

3. The Lancet Commission in Global Surgery - Information Management3 1. Background The Health Information System (HIS) in the Ministry of Health and Sanitation (MOHS) is the processes and mechanisms through which health‐related data is produced and made accessible to users The HIS has several sub‐systems: Health Management Information system (HMIS) Integrated Disease Surveillance and Response (IDSR) Vital Registration (VR) for births and deaths Human Resource Information System (HRIS) Logistics Management Information System (LMIS) Population‐Based Information Systems Research‐generated health information Data collected is stored and analyzed in the District Health Information Software (DHIS2)

4. The Lancet Commission in Global Surgery - Information Management4 2. Data collection Data is produced and used at four levels: community, health facility, district and national level. Daily Health data is captured from clients/patients in 1270 PHUs and 22 government hospitals Outreach data and data submitted by Village Health Committee is collected Daily summaries are generated By 15 th of each month Daily tally books are used to compile 7 monthly reports for DHIS Data submitted to M&E officer at district level M&E officer cleans the data and submits to DPPI By 25 th of each month HMIS specialist at DPPI cleans data and ensures completeness Quarterly/ Annually Reports for programmes or partners are produced upon request Health Bulletin is published

5. The Lancet Commission in Global Surgery - Information Management5

6. 6 3. Hospital data In- and out-patient data is collected for Cases and Deaths, from all government hospitals, capturing data about patients’ diagnosis categorized into specific modules and age cohorts. Data is captured at hospital level and are keyed into a computerized database application that aggregate the data at district and national level Hospital M&E Officers are responsible for data collection of hospital records and to supervise data entry Clerks to key data into the database. Hospital records will soon be keyed into the online DHIS2 software The six modules are split into the below structure: Morbidity Captures data for specific 31 diseases, split into outpatient and inpatient Reports cases and deaths Splits into 6 age brackets and gender Maternity Services Reports on 12 specific diagnosis Reports on cases and deaths Split into 4 age brackets In-patient Admission Split into wards: Medical Paediatric Obstetric/Gynecol ogy Surgical Opthalmic TB Ward Intensive Care Unit Service Utilization Total number of beds Total number of bed days Type of Delivery Split into the same age groups as maternity services Reports: Normal delivery Assisted Vaginal delivery Caesarian section Outcome of Delivery Reports: No of live births No of still births No of Still births maserated

7. The Lancet Commission in Global Surgery - Information Management7 3. Hospital data In- and out-patient data is collected for Cases and Deaths, from all government hospitals, capturing data about patients’ diagnosis categorized into specific modules and age cohorts. Data is captured at hospital level and are keyed into a computerized database application that aggregate the data at district and national level Hospital M&E Officers are responsible for data collection of hospital records and to supervise data entry Clerks to key data into the database. Hospital records will soon be keyed into the online DHIS2 software The six modules are split into the below structure: Morbidity Captures data for specific 31 diseases, split into outpatient and inpatient Reports cases and deaths Splits into 6 age brackets and gender Maternity Services Reports on 12 specific diagnosis Reports on cases and deaths Split into 4 age brackets In-patient Admission Split into wards: Medical Paediatric Obstetric/Gynecol ogy Surgical Opthalmic TB Ward Intensive Care Unit Service Utilization Total number of beds Total number of bed days Type of Delivery Split into the same age groups as maternity services Reports: Normal delivery Assisted Vaginal delivery Caesarian section Outcome of Delivery Reports: No of live births No of still births No of Still births maserated Some surgical indicators captured in hospital forms: # of Appendicitis surgeries performed # of Hernia/Hydrocele surgeries performed # of Caesarian sections performed # of Assisted Vaginal deliveries performed # of Ophthalmic surgeries performed

8. The Lancet Commission in Global Surgery - Information Management8 4. Risk analysis (1/2) RisksMitigating strategy Inadequate financial and human resources for implementing HMIS plans. Continued sourcing of funds to recruit personnel and implement the HMIS plans. Poor engagement of the private sector and community groups in data collection. Private sector and community groups to be engaged in harmonizing data collection and reporting. No maintenance plan for existing ICT infrastructure both at national and district level. Ongoing plans to establish maintenance plan for ICT infrastructure at district and national level. Information security is almost none existent and needs to be established and strengthened. Ongoing plans to establish a modern server room for DHIS2 equipment along with main security policies.

9. The Lancet Commission in Global Surgery - Information Management9 4. Risk analysis (2/2) RisksMitigating strategy Multiple donor‐driven parallel information systems which have overloaded the already existing government systems, affecting the quality of data produced. Data collection and reporting tools harmonization workshop was completed, data forms are being adjusted. Incomplete recording of health data. Data validation and supportive supervision exercises in the districts are performed on a quarterly basis to improve data recording and data entry. Use of multiple non‐standardized forms at service delivery points Improve on the timely delivery of forms.

10. Health Information Management in Sierra Leone Thank you for your attention!