Abstract
Clinical decision support systems (CDSSs) have been central to the large-scale digitalization of health services in high-income nations which has been underway for many decades. Although CDSSs are central to most IT strategies, approaches to system implementation and use are highly variable. This is partly because they are influenced by the organization of health systems and are highly dependent on existing health information infrastructures. There is clear evidence that the international experience with CDSS can be used to study the sociotechnical factors which influence their use and impact. This chapter provides a snapshot of the experience with CDSSs in Australia, New Zealand, Europe and low- and middle-income countries (LMICs) focusing on East Africa and Haiti and discusses the principles of CDSSs implementation and use that are generalizable across contexts.
Current CDSSs across high-income countries are largely aimed at doctors, using facilities within commercially available clinical information systems (CISs) to support individual clinical tasks such as prescribing medications, information retrieval and risk assessment. As electronic health record (EHR) implementations have been optimized, implementation and use of CDSSs appears to be shifting to a problem-driven approach with process support CDSSs that facilitate a bundle of clinical tasks or clinical management of specific conditions. Here, clinical management is built into CDSSs functionality, systems are better integrated with clinical workflow and usable at the point of care delivery. Despite widespread use of digital health technology, current CDSSs are limited to structured clinical data and there is only fragmented interoperability between CISs in different parts of the health system; efforts are underway to enable data exchange. In many LMICs pioneering projects are starting to have an impact in a range of environments and countries. OpenMRS, an open source EHR platform and software, is being used in over 45 developing countries, and there is initial evidence of clinical benefits from CDSSs deployed for HIV care in Kenya and Rwanda. Laboratory information systems have shown clinical benefits in Peru and Zambia, and there is some evidence of benefits from drug order entry systems. Mobile app-based health (mHealth) systems are increasingly being used to collect and deliver critical health. Initial results show evidence that mHealth can support better access to clinical data such as laboratory results, support community health care workers, and help HIV patients in Kenya to improve drug compliance. In both high income and LMICs, significant investments and efforts to implement CDSSs are continuing with an increasing focus on AI and machine-learned algorithms but few are in routine use and there is limited evidence of clinical benefits to date.
Current CDSSs across high-income countries are largely aimed at doctors, using facilities within commercially available clinical information systems (CISs) to support individual clinical tasks such as prescribing medications, information retrieval and risk assessment. As electronic health record (EHR) implementations have been optimized, implementation and use of CDSSs appears to be shifting to a problem-driven approach with process support CDSSs that facilitate a bundle of clinical tasks or clinical management of specific conditions. Here, clinical management is built into CDSSs functionality, systems are better integrated with clinical workflow and usable at the point of care delivery. Despite widespread use of digital health technology, current CDSSs are limited to structured clinical data and there is only fragmented interoperability between CISs in different parts of the health system; efforts are underway to enable data exchange. In many LMICs pioneering projects are starting to have an impact in a range of environments and countries. OpenMRS, an open source EHR platform and software, is being used in over 45 developing countries, and there is initial evidence of clinical benefits from CDSSs deployed for HIV care in Kenya and Rwanda. Laboratory information systems have shown clinical benefits in Peru and Zambia, and there is some evidence of benefits from drug order entry systems. Mobile app-based health (mHealth) systems are increasingly being used to collect and deliver critical health. Initial results show evidence that mHealth can support better access to clinical data such as laboratory results, support community health care workers, and help HIV patients in Kenya to improve drug compliance. In both high income and LMICs, significant investments and efforts to implement CDSSs are continuing with an increasing focus on AI and machine-learned algorithms but few are in routine use and there is limited evidence of clinical benefits to date.
Original language | English |
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Title of host publication | Clinical decision support and beyond |
Subtitle of host publication | progress and opportunities in knowledge-enhanced health and healthcare |
Editors | Robert A. Greenes, Guilherme Del Fiol |
Place of Publication | London |
Publisher | Elsevier Academic Press |
Chapter | 5 |
Pages | 145-188 |
Number of pages | 44 |
Edition | 3rd |
ISBN (Electronic) | 9780323912006 |
ISBN (Print) | 9780323995771 |
DOIs | |
Publication status | Published - 10 Feb 2023 |
Keywords
- Global health
- Digital health
- mHealth
- OpenMRS
- Decision support systems
- Australia
- New Zealand
- Europe