Decision time for clinical decision support systems

Abstract

KEYWORDS: Clinical decision support systems, decision-making, diagnosis ContextInformation technology (IT) is now commonplace in almost every branch of healthcare. Electronic health records, eprescribing and digital medical imaging are well known to clinicians and have been implemented with varying degrees of success. 1 In addition, clinicians increasingly make use of online repositories such as PubMed and Google Scholar, 2 and specialised search engines such as FindZebra 3 to help answer clinical questions. One often overlooked set of IT tools are clinical decision support systems (CDSSs), which have been defi ned as systems that 'provide clinicians or patients with computer-generated clinical knowledge and patient-related information, intelligently fi ltered or presented at appropriate times, to enhance patient care'. 4 Such CDSSs have been the subject of academic computer science research for more than ABSTRACT 50 years 5 and offer the potential for better supported decision making by clinicians, improved compliance with medical standards and improved clinical effi ciency and safety. 6,7 Nonetheless, utilisation of CDSSs remains limited, and most healthcare IT systems do not include robust CDSS functions that can be widely employed across organisations, clinical presentations and domains. 8 Some of the challenges to implementation of CDSSs relate to the volume of high-quality data required for state-of-the-art systems, the translation of such data to machine-readable states and the mapping of CDSS processes to fi t with existing clinical workfl ows. As a result, successful implementation of CDSSs has tended to be site and domain specifi c, with major diffi culties replicating these successes more extensively throughout healthcare systems. 9 This is in contrast to commercial fi elds such as fi nance, where decision support technologies have been widely deployed. For example, risk-profi ling tools for fi nancial experts have been developed as easy-to-use programs that can assimilate information and guide users through complex fi nancial information and associated decisions tailored to individual customer needs. Healthcare decision making is signifi cantly more complex than fi nancial planning; however, some of the challenges in both domains are similar: large quantities of data need to be linked, integrated and translated to machine readable formats, and expert knowledge is required to contextualise and apply the data in a meaningful way. We discuss some reasons for the limited dissemination and adoption of CDSSs to date and refl ect on the major barriers that need to be overcome for these useful tools to be adopted more widely.

Quality in Australian after‐hours doctor home visits: exploring the clinical, professional and security supports available to involved practitioners

“…The third form of support, clinical support for AHHC doctors, can be in the form electronic clinical decision support systems (CDSSs), books, manuals, drug formularies and so on, which help clinicians with point‐of‐care decision making on issues like diagnosis, prioritizing investigations, recommending treatments and ordering medications . In Australian general practice, most clinical support tools are built‐in in softwares like the ‘Medical Director’ or ‘Best Practice’ and are easily available to regular‐hour office‐based GPs through their computers.…”

“…The third form of support, clinical support for AHHC doctors, can be in the form electronic clinical decision support systems (CDSSs), books, manuals, drug formularies and so on, which help clinicians with point-of-care decision making on issues like diagnosis, prioritizing investigations, recommending treatments and ordering medications. [13][14][15][16][17][18][19][20][21][22] In Australian general practice, most clinical support tools are built-in in softwares like the 'Medical Director' or 'Best Practice' and are easily available to regular-hour office-based GPs through their computers. They create opportunities for accessing and incorporating up-to-date, robust and evidence-based recommendations into everyday practice [18] and have been reported to be the most valued aspect of support for rural-based doctors.…”

The Role of Explanations on Trust and Reliance in Clinical Decision Support Systems

“…A CDSS often applies highly complex and multi dimensional reasoning that is difficult for a user to understand [13,23] and explanations are often provided by the system to help the user understand what it is doing [11,12,26]. Previous work has stressed the importance of explaining various aspects of the decision-making process to users [10,14,20], and these different kinds of explanation types -for example, Confidence explanations showing the probability of the diagnosis being correct and Why explanations providing facts used in reasoning about the diagnosis -have been used previously in CDSS [12].…”

“…It has been suggested that the intelligibility of system behavior is an important factor in ensuring that the user understands how the CDSS operates [23]. This in turn could help clinicians identify if the system has erred and also ensure that the clinician forms a more accurate picture of the system's reliability.…”

The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review

“…Usually, the basis of these knowledge systems is formed by combining information obtained from electronic health records (EHR) with clinical practice guidelines. Following the article of O'Sullivan et al, CDSSs can be distinguished in simple, mid-and complex level systems [7]. He defines simple level CDSSs as CDSSs that are usually embedded in order entry systems and verify whether the input provided by a clinician is allowable or within a specified range.…”