Web-based DHIS Daily Capturing (DDC) Strategy for improving Data Quality at Service Point Level

TABLE OF CONTENT Project Rationale Legislation, Policies and SOPs Business Process Prior WebDCC Business Process after WebDCC Principles of webDHISDDC

5 webDHIS Transition Phases Project Rationale Reduce Audit Findings Improve Timely Access to Data Rationalisation of Registers By improving Data Quality and Integrity Strengthen Information Management Promote EBD Making Reduce Multiple Data Collection tools . The Auditor General (AG) bi-annual audit main finding relates to the reliability of data = discrepancies between registers and monthly input forms. DDC is one of the strategies NDOH embarked on to improve data quality and audit outcomes Establish Building Block of NHI

Legislation, Policies, Strategies, Norms & Standards The WebDHIS eHealth Project conforms with all applicable legislative frameworks,. The include: The National Health Act 2nd Version; The District Health Management Information System (DHMIS) Policy 2011; The Medium Term Strategic Framework (MTSF) 2014 – 2019; National Development Plan 2030; eHealth Strategy for South Africa 2014 – 2019; National Health Normative Standards Framework for Interoperability in eHealth in South Africa (version 2.0, March 2014); White Paper - National Health Insurance for South Africa (Version 40, 11 December 2015)

Business Process prior webDHISDDC RESOURCES SKILLS & TIME Patient record Step 1 Doctor or nurse interacts with patient No patient record, Incomplete, illegible, undated data Multiplicity of data collection tools, duplication non-standardised Step 2 Sub-set of data recorded in Tick Register Inability to collate data accurately Step 3 Weekly & monthly summary report compiled (manual calculation) Inability to collate data accurately Step 4 Monthly summaries collated (manual calculation) In this slide we look at the challenges we face to improve data quality. It describes the current steps followed in the information cycle and highlights the challenges experiences during each step Data capture errors Incorrect data elements activated Validation not done Step 5 Monthly data capture into webDHIS mostly sub-district level No feedback Little data analysis and use by program managers Step 6 Data analysis and feedback

Business Process after WebDHISDDC Data entered Patient clinical records standardise – verify data & rapid internal audits Step 1 Doctor or nurse interacts with patient Patient record Register rationalisation Less & specific elements per consulting room – reduce human error Step 2 Sub-set of data recorded in Tick Register Reduces manual calculation time Internal aggregation reduces human error Step 3 Monthly summary report compiled Step 4 Monthly summaries collated In this slide we propose a new approach that can address the challenges identified at each step in the previous slide. Errors can be identified and corrected with clinicians daily Capture & validate DAILY totals into WebDHIS by consulting room (subset) Capture & validate MONTHLY totals by facility (subset) Step 5 Less time on validation & verification = more time for analysis, feedback & use Step 6 Data analysis, feedback and use

Principles of Daily Data Capturing DATA CLERK OM CLINICIAN PATIENT CAPTURE & VALIDATE CONSULTATION VERIFICATION REGISTRATION AND DATA CAPTURERS ROOM RECORD SERVICES OFFERED SIGNED OFF BULK FILLING CABINETS Walkthrough in the facility to do assessment of patient flow, service points and services rendered at each point All patients start at reception for registration and collection of their files before consultation PHC headcount to be collected at the Reception as stated on the (DHMIS Policy) Facility SOP. Daily data is captured from the registers in each service point to Web-based DHIS Computer with Internet access. Facility staff have been trained on web-DHIS Data capturer or other computer-literate staff member to capture daily summaries. Information officer who is able to provide support to optimise sustainability. FACILTIY HELD PATIENT CARDS