Innovations in Information Communication Technology
1 like382 views
The document discusses innovations in information and communication technologies (ICT) for health information systems. It addresses questions around integrating data from different sources, ensuring systems can communicate through interoperability and standardization, and challenges of infrastructure in rural areas. Mobile phones are discussed as both empowering local health workers but also potentially increasing fragmentation if outsourced to Western companies. Building local capacity for new ICT skills is also addressed.
Innovations in Information Communication Technology
- 1. 4 th International RHINO Workshop Guanajuato, Mexico March 8, 2010 Measuring and Improving Routine Health Information System Performance Concurrent session: Innovations in ICT
- 2. Innovations in ICT– Concurrent RHINO session Questions to be debated: Integration. From silos to integrated information - Can integrated data warehouses, as according to the HMN Framework, help bring about integration? Interoperability and standardization . How to get systems to interoperate, e.g. Sending aggregate data from patient records, human resource, finance, lab, GIS, cell phones, etc. to the data warehouse Poor and uneven infrastructure . How to make RHIS work “uniformly” in a country with “non-uniform” infrastructure , e.g. rural / urban Mobile telephones ; Hype or reality? Efficient tool for peripheral health workers? Causing increased fragmentation? Outsource ICT services to Western companies? Capacity building. More and different capacity needed to master new and networked ICT. Do we outsource ICT? – or build capacity ? –How?
- 3. ICT innovations – outline of the presentation Integration, Interoperability & Standardisation - Example: WHO / HMN project to develop Free and Open Source Public Health Toolkit Uneven infrastructure in countries - how to achieve “uniform” and scalable RHIS approach? Architecture? Addressing interoperability and standardisation at different levels: syntactic /technical; semantic & “political” Mobile telephones; two conflicting trends: Empowering the people - Or Western companies? Networked ICT: More and different capacity needed
- 4. Objective: To work with partners in a collaborative effort to deliver a suite of free interoperable information tools for public health Approach: Leveraging existing products/efforts and providing a standard-based extensible platform for technology and data integration Data Warehouse Other Data Sources Census Human resources Environmental Demographic & Health surveys Surveys Finance Electronic patient record systems etc. Clinical systems Eg. OpenMRS Health Management DHIS, CRIS ... Interoperability Standards Additional Databases HR management eg.. iHRIS e.g. SDMX-HD (WHO project) OpenHealth Platform Indicator & Metadata Registry (IMR) Public Health Starter Toolkit Suite of interoperable tools for public health for countries Field data collection tools SAM etc Data Exchange and Integration Platform
- 5. Patient management/tracking Surveys Outbreaks Investigations Surveillance Logistics & Supplies HR managemt Financial management Monitoring & evaluation District health Management Public health data architecture Laboratory systems Drug monitoring … Public health applications framework – examples - Approaching a RHIS architecture
- 6. Open MRS CSpro Episurveyor .. EpiInfo … iHRIS … CRIS DHIS OpenHealth – Platform/Architecture … … Patient management Epi surveillance Health info mgt Surveys Logistics & supplies Financial mgt Outbreaks invest. HR management Monit. & eval. L Laboratories Drug monitoring . . . Leveraging existing tools and systems For starter integrated toolkit …
- 7. Criteria/operating principles For the Public Health toolkit be freely available support data standards and open communication protocols allow for local customisation, peer user support and adaptation over time. be capable of being deployed by appropriate personnel adopt industry best practices and standards for scalability, modularity, and expandability
- 8. Example: DHIS-OpenHealthMapper in Sierra Leone Indicators by Chiefdom displayed using colours
- 10. The Adapted HMN Data warehouse approach (for aggregate data) An integrative “umbrella” across programs, sub-systems & infrastructures (paper, computers, Internet, mobile telephones Data warehouse Reports, GIS, Pivot, graphs, etc, (for aggregate data) Import Electronic data Data capture from paper reports Electronic Patient records Paper patient records Electronic e.g. HR records Export electronic summary data Monthly summary reports Replicated at each Administrative Level: National State/Province District Municipality Data from / to Mobile telephones
- 11. National/ MoH Facility Region/ District: Patient level Registration From paper based to computer based Levels of the health system (2) From Stand-alone to networked computers (3) From paper records to electronic patient records Comprehensive and scalable approach – “scaling the umbrella” Architecture enables uniform approach despite uneven infrastructure From paper to computer From “stand alone” to networked computers From paper records to electronic patient records (and other records, e.g. HR)
- 12. Increasing differences between views 3 Levels of (achieving) Interoperability/ Standardisation: -- Organisational/ Political /pragmatic -- Semantic -- Syntactic /technical Compared to telephone conversations: -Interested in talking? -Shared language and Shared understanding? -compatible telephones & networks? Interoperability and integration require standards Standardisation & interoperability may be seen as going on at 3 levels of increasing complexity Standardisation process: cycling through the levels. For each level, “solutions” based/running on solutions at level below, and rely on agreement at level above SDMX-HD, etc . Shared / agreed indicators & meta data Programs / donors /agencies Agree to standardisation Unique id.
- 13. Mobile telephones - Example: Two trends (1) Globally uniform infrastructure at peripheral levels – first time! But, mobile telephones have limited capacity Small or reduced data sets – may lead to Two different outcomes: India: Reduced data set for village health worker reporting From hundreds to 75 data items Java enabled phones, good user interface, sending data directly to DHIS data warehouse at state level scaling rapidly, because - users know the data to report - users know the technology - users burdened by paper based manual data reporting
- 14. Mobile telephones - Example: Two trends (2) “ Country in Africa”: Network provider & Western software company provide /sell services to health program, funded by donor “ We provide infrastructure, incentives to data collectors (airtime), security, data management & reports” Data sent to company server - cloud computing Increased fragmentation & “ Solving “ Africa’s capacity problem by outsourcing complicated technology to Western companies! Same technology – two different outcomes Humans, not the technology, is the determinant!
- 15. HR & Capacity development; How may Developing countries NOT get disempowered in the age of Networked ICT – some concerns Mastering & “controlling” ICT in the context of Internet, Servers, WEB & Mobile telephones Different & new skills & capacity At the same time: ICT services are being globalised – “cloud computing” How can countries cope? (Apart from traditional training) RHIS interventions should always be based on local participation, ownership and control – ALSO in the area of ICT!