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      Impact of a Search Engine on Clinical Decisions Under Time and System Effectiveness Constraints: Research Protocol


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          Many clinical questions arise during patient encounters that clinicians are unable to answer. An evidence-based medicine approach expects that clinicians will seek and apply the best available evidence to answer clinical questions. One commonly used source of such evidence is scientific literature, such as that available through MEDLINE and PubMed. Clinicians report that 2 key reasons why they do not use search systems to answer questions is that it takes too much time and that they do not expect to find a definitive answer. So, the question remains about how effectively scientific literature search systems support time-pressured clinicians in making better clinical decisions. The results of this study are important because they can help clinicians and health care organizations to better assess their needs with respect to clinical decision support (CDS) systems and evidence sources. The results and data captured will contribute a significant data collection to inform the design of future CDS systems to better meet the needs of time-pressured, practicing clinicians.


          The purpose of this study is to understand the impact of using a scientific medical literature search system on clinical decision making. Furthermore, to understand the impact of realistic time pressures on clinicians, we vary the search time available to find clinical answers. Finally, we assess the impact of improvements in search system effectiveness on the same clinical decisions.


          In this study, 96 practicing clinicians and final year medical students are presented with 16 clinical questions which they must answer without access to any external resource. The same questions are then represented to the clinicians; however, in this part of the study, the clinicians can use a scientific literature search engine to find evidence to support their answers. The time pressures of practicing clinicians are simulated by limiting answer time to one of 3, 6, or 9 min per question. The correct answer rate is reported both before and after search to assess the impact of the search system and the time constraint. In addition, 2 search systems that use the same user interface, but which vary widely in their search effectiveness, are employed so that the impact of changes in search system effectiveness on clinical decision making can also be assessed.


          Recruiting began for the study in June 2018. As of the April 4, 2019, there were 69 participants enrolled. The study is expected to close by May 30, 2019, with results to be published in July.


          All data collected in this study will be made available at the University of Queensland’s UQ eSpace public data repository.

          International Registered Report Identifier (IRRID)


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          Most cited references57

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          The harassed decision maker: Time pressures, distractions, and the use of evidence.

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            Analysis of questions asked by family doctors regarding patient care.

            To characterise the information needs of family doctors by collecting the questions they asked about patient care during consultations and to classify these in ways that would be useful to developers of knowledge bases. Observational study in which investigators visited doctors for two half days and collected their questions. Taxonomies were developed to characterise the clinical topic and generic type of information sought for each question. Eastern Iowa. Random sample of 103 family doctors. Number of questions posed, pursued, and answered; topic and generic type of information sought for each question; time spent pursuing answers; information resources used. Participants asked a total of 1101 questions. Questions about drug prescribing, obstetrics and gynaecology, and adult infectious disease were most common and comprised 36% of all questions. The taxonomy of generic questions included 69 categories; the three most common types, comprising 24% of all questions, were "What is the cause of symptom X?" "What is the dose of drug X?" and "How should I manage disease or finding X?" Answers to most questions (702, 64%) were not immediately pursued, but, of those pursued, most (318, 80%) were answered. Doctors spent an average of less than 2 minutes pursuing an answer, and they used readily available print and human resources. Only two questions led to a formal literature search. Family doctors in this study did not pursue answers to most of their questions. Questions about patient care can be organised into a limited number of generic types, which could help guide the efforts of knowledge base developers.
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              Answering physicians' clinical questions: obstacles and potential solutions.

              To identify the most frequent obstacles preventing physicians from answering their patient-care questions and the most requested improvements to clinical information resources. Qualitative analysis of questions asked by 48 randomly selected generalist physicians during ambulatory care. Frequency of reported obstacles to answering patient-care questions and recommendations from physicians for improving clinical information resources. The physicians asked 1,062 questions but pursued answers to only 585 (55%). The most commonly reported obstacle to the pursuit of an answer was the physician's doubt that an answer existed (52 questions, 11%). Among pursued questions, the most common obstacle was the failure of the selected resource to provide an answer (153 questions, 26%). During audiotaped interviews, physicians made 80 recommendations for improving clinical information resources. For example, they requested comprehensive resources that answer questions likely to occur in practice with emphasis on treatment and bottom-line advice. They asked for help in locating information quickly by using lists, tables, bolded subheadings, and algorithms and by avoiding lengthy, uninterrupted prose. Physicians do not seek answers to many of their questions, often suspecting a lack of usable information. When they do seek answers, they often cannot find the information they need. Clinical resource developers could use the recommendations made by practicing physicians to provide resources that are more useful for answering clinical questions.

                Author and article information

                JMIR Res Protoc
                JMIR Res Protoc
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                May 2019
                28 May 2019
                : 8
                : 5
                : e12803
                [1 ] School of Information Technology and Electrical Engineering The University of Queensland St Lucia Australia
                [2 ] Australian eHealth Research Centre, The Commonwealth Scientific and Industrial Research Organisation Brisbane Australia
                [3 ] School of Medicine University of Queensland St Lucia Australia
                Author notes
                Corresponding Author: Anton van der Vegt a.vandervegt@ 123456uq.net.au
                Author information
                ©Anton van der Vegt, Guido Zuccon, Bevan Koopman, Anthony Deacon. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 28.05.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org.as well as this copyright and license information must be included.

                : 13 November 2018
                : 2 April 2019
                : 11 April 2019
                : 12 April 2019

                information storage and retrieval,clinical decision making,evidence-based medicine


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