What may help or hinder the implementation of computerized decision support systems (CDSSs): a focus group study with physicians

Abstract

Physicians had relatively positive attitudes towards the idea of CDSS. They expected flexibility, individuality and reliability of the CDSS. The rather high level of computerized practices and wide use of electronic guidelines probably have paved the way for the CDSS in Finland.

Decision support systems for adoption in dental clinics: A survey

“…Medical practitioners are used to the culture of autonomy, and using such a system will disrupt that autonomy leading to resistance to their adoption within the clinical workflow (Varonen et al, 2008). A study on perceived barriers for a group of rheumatologists discovered a sense of ambivalence relating to concerns that using technology could impair doctor-patient communication (Zong et al, 2015).…”

Success Factors and Barriers for Implementation of Advanced Clinical Decision Support Systems

“…Therefore, it is vitally important to validate the clinical rules extensively before bringing these into practice to ensure reliable recommendations. (Dexter et al, 2001;Wetter, 2002;Wessels-Basten et al, 2007;Sucher et al, 2008;Varonen et al, 2008) The above mentioned obstacles need to be taken into account when designing en implementing these newer systems. Also, validation of the alerts is fundamental for success.…”

“…(Kawamoto et al, 2005;Varonen et al, 2008) This can be accomplished by giving clear advice and a straightforward way to perform the action indicated. Osheroff et al, 2005;Varonen et al, 2008;Mollon et al, 2009) Besides that, applications must anticipate physicians needs for gathering and translating data into actionable recommendations.…”

“…(Kawamoto et al, 2005;Varonen et al, 2008) This can be accomplished by giving clear advice and a straightforward way to perform the action indicated. Osheroff et al, 2005;Varonen et al, 2008;Mollon et al, 2009) Besides that, applications must anticipate physicians needs for gathering and translating data into actionable recommendations. Kawamoto et al, 2005;Mollon et al, 2009) For example, a clinical rule is developed to check if a patient needs a gastroprotective drug when using a NSAID or dosage adjustment because of renal insufficiency.…”

“…(Kawamoto et al, 2005;Garg et al, 2005;Mollon et al, 2009) This provides relevant information to physicians at key times in decision making, enabling to prompt alerts during drug prescription or chart review. (Denekamp, 2007;Varonen et al, 2008) …”