The Potential of Training to Increase Acceptance and Use of Computerized Decision Support Systems for Medical Diagnosis

Abstract

These findings have the potential for the identification of methods to help clinicians learn how to use statistical and probabilistic information to better assess risk and to promote integration of decision support tools into medical decision making for improvement of patient safety.

Barriers and Facilitators to Clinical Decision Support Systems Adoption: A Systematic Review

“…Their study of the physician's opinion in the current prescription process and the perceived benefits and obstacles of employing a CDSS noted cultural concerns which influenced the physician's opinions. Kazemi et al (2009) and Lai, Macmillan, Daudelin & Kent (2006), also noted social barriers and a lack of social acceptance as barriers to the use of CDSS in clinical practice settings.…”

“…Trafton et al (2010) and Demakis et al (2000), who studied improving residents' compliance with standards of ambulatory care in a VA hospital setting, also pointed out the difficulty of competing clinical demands within the practice acted as a barrier to the use of CDSS. Varonen et al (2008), in a study group of physicians on implementing CDSSs; Robertson et al (2011);Hor et al (2010), in a study of the attitudes and preparedness towards clinical decision support in e-Prescribing; and Lai, Macmillan, Daudelin & Kent (2006), in their study of the potential of training to increase acceptance and use of CDSS for medical diagnosis; all noted that obscure workflow issues and the ability to incorporate the system within the normal flow of practice acted as barriers to clinician use. Cobos et al (2005), in a study of the cost effectiveness of a CDSS for the management of hypercholesterolemia; pointed out the lack of agreements with the system created an impediment to use.…”

“…Lack of training (Hor, O'Donnell, Murphy, O'Brien, & Kropmans, 2010) Lack of awareness existence (Peek , et al, 2011); (Lai, Macmillan, Daudelin, & Kent, 2006) (Subramanian, et al, 2007) Applicability (Bullard, Graham, Kushniruk, Holroyd, & Rowe, 2008) Improve productivity (Bullard, Graham, Kushniruk, Holroyd, & Rowe, 2008); (Egger, Epstein, Macario, Pearl, & Grunwald, 2008); (Subramanian, et al, 2007); (Robertson, et al, 2011 (Trafton, et al, 2010); (Robertson, et al, 2011) Usability testing (Bullard, Graham, Kushniruk, Holroyd, & Rowe, 2008); (Trafton, et al, 2010); (Tierney, et al, 2005) Fast information retrieval/ (Varonen, Kortteisto, & Kaila, 2008); (Murray, et al, 2004); (Derose, et al, 2005) …”

How Incorporating Feedback Mechanisms in a DSS Affects DSS Evaluations

“…Yet, Sullivan (2005) reports that only 5% to 6% of retailers use such DSS, with most managers preferring to use gut feeling for pricing decisions. Similarly, clinical DSS significantly improve clinical performance in prescribing decisions (Hunt et al 1998), yet medical professionals are largely unwilling to use them (Sintchenko et al 2004, Lai et al 2006. Ashton (1991), Singh and Singh (1997), and Sieck and Arkes (2005) among others have noted decision makers' disinclination to use DSS in a variety of different environments, even when the models embedded in the systems are known to improve decision quality and performance.…”

“…Gonul et al (2006) show that confident and long explanations associated with DSS advice can improve user acceptance of that advice. In the context of medical diagnosis of acute cardiac ischemia, Lai et al (2006) found that a tutorial on the advice given by a clinical DSS increased the use of that advice by emergency care physicians, leading to better patient outcomes. Limayem and DeSanctis (2000) find that system explanations improve group DSS usability, particularly because of improvements in user understanding of decision models.…”