OBJECTIVE: To identify key elements and characteristics of complex adaptive systems (CAS) relevant to implementing clinical governance, drawing on lessons from quality improvement programmes and the use of informatics in primary care. METHOD: The research strategy includes a literature review to develop theoretical models of clinical governance of quality improvement in primary care organisations (PCOs) and a survey of PCOs. RESULTS: Complex adaptive system theories are a valuable tool to help make sense of natural phenomena, which include human responses to problem solving within the sampled PCOs. The research commenced with a survey; 76% (n16) of respondents preferred to support the implementation of clinical governance initiatives guided by outputs from general practice electronic health records. There was considerable variation in the way in which consultation data was captured, recorded and organised. Incentivised information sharing led to consensus on coding policies and models of data recording ahead of national contractual requirements. Informatics was acknowledged as a mechanism to link electronic health record outputs, quality improvement and resources. Investment in informatics was identified as a development priority in order to embed clinical governance principles in practice. CONCLUSIONS: Complex adaptive system theory usefully describes evolutionary change processes, providing insight into how the origins of quality assurance were predicated on rational reductionism and linearity. New forms of governance do not neutralise previous models, but add further dimensions to them. Clinical governance models have moved from deterministic and 'objective' factors to incorporate cultural aspects with feedback about quality enabled by informatics. The socio-technical lessons highlighted should inform healthcare management.
OBJECTIVE: To identify key elements and characteristics of complex adaptive systems (CAS) relevant to implementing clinical governance, drawing on lessons from quality improvement programmes and the use of informatics in primary care. METHOD: The research strategy includes a literature review to develop theoretical models of clinical governance of quality improvement in primary care organisations (PCOs) and a survey of PCOs. RESULTS: Complex adaptive system theories are a valuable tool to help make sense of natural phenomena, which include human responses to problem solving within the sampled PCOs. The research commenced with a survey; 76% (n16) of respondents preferred to support the implementation of clinical governance initiatives guided by outputs from general practice electronic health records. There was considerable variation in the way in which consultation data was captured, recorded and organised. Incentivised information sharing led to consensus on coding policies and models of data recording ahead of national contractual requirements. Informatics was acknowledged as a mechanism to link electronic health record outputs, quality improvement and resources. Investment in informatics was identified as a development priority in order to embed clinical governance principles in practice. CONCLUSIONS: Complex adaptive system theory usefully describes evolutionary change processes, providing insight into how the origins of quality assurance were predicated on rational reductionism and linearity. New forms of governance do not neutralise previous models, but add further dimensions to them. Clinical governance models have moved from deterministic and 'objective' factors to incorporate cultural aspects with feedback about quality enabled by informatics. The socio-technical lessons highlighted should inform healthcare management.
Authors: Sharon B Meropol; Nicholas K Schiltz; Abdus Sattar; Kurt C Stange; Ann H Nevar; Christina Davey; Gerald A Ferretti; Diana E Howell; Robyn Strosaker; Pamela Vavrek; Samantha Bader; Mary C Ruhe; Leona Cuttler Journal: Pediatrics Date: 2014-05-05 Impact factor: 7.124
Authors: Jean-Paul Collet; Peter W Skippen; Mir Kaber Mosavianpour; Alexander Pitfield; Bubli Chakraborty; Garth Hunte; Ronald Lindstrom; Niranjan Kissoon; William H McKellin Journal: Implement Sci Date: 2014-01-08 Impact factor: 7.327