Heuristics in managing complex clinical decision tasks in experts decision making

pre-printBackground: Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. Objective: The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. Method: After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. Results: We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trad e-offs, managing uncertainty and generating rule of thumb. Conclusion: Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Application: Understanding comp lex decision making processes can help design allocation based on the complexity of task for clinical decision support design

Providers' information needs in the care of older adults

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Clinical questions raised by providers in the care of older adults: a prospective observational study

pre-printObjective: To characterise clinical questions raised by providers in the care of complex older adults in order to guide the design of interventions that can help providers answer these questions. Materials and methods: To elicit clinical questions, we observed and audio recorded outpatient visits at three healthcare organisations. At the end of each appointment, providers were asked to identify clinical questions raised in the visit. Providers rated their questions based on their urgency, importance to the patient's care and difficulty in finding a useful answer to. Transcripts of the audio recordings were analysed to identify ageing-specific factors that may have contributed to the nature of the questions. Results: We observed 36 patient visits with 10 providers at the three study sites. Providers raised 70 clinical questions (median of 2 clinical questions per patient seen; range 0-12), pursued 50 (71%) and successfully answered 34 (68%) of the questions they pursued. Overall, 36 (51%) of providers' questions were not answered. Over one-third of the questions were about treatment alternatives and adverse effects. All but two clinical questions were motivated either directly or indirectly by issues related to ageing, such as the normal physiological changes of ageing and diseases with higher prevalence in the elderly. Conclusions: The frequency of clinical questions was higher than in previous studies conducted in general primary care patient populations. Clinical questions were predominantly influenced by ageing-related issues. We propose a series of recommendations that may be used to guide the design of solutions to help providers answer their clinical questions in the care of older adults

Integrating genetic information resources with an EHR

posterThe integration between the electronic health record (HER) and on0line information resources, using tools such as "infobuttons", is considered a promising solution to fulfill clinicians' information needs at the point-of-care. This article describes the implementation of "infobutton" links from a problem list of a web-based HER to two on-line genetic information resources: Genetics Home Reference (GHR) and GeneTests

Identifying Complexity in Infectious Diseases Inpatient Settings: An Observation Study

Background Understanding complexity in healthcare has the potential to reduce decision and treatment uncertainty. Therefore, identifying both patient and task complexity may offer better task allocation and design recommendation for next-generation health information technology system design. Objective To identify specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians. Method We observed and audio recorded clinical rounds of three infectious disease teams. Thirty cases were observed for a period of four consecutive days. Transcripts were coded based on clinical complexity-contributing factors from the clinical complexity model. Ratings of complexity on day 1 for each case were collected. We then used statistical methods to identify complexity-contributing factors in relationship to perceived complexity of clinicians. Results A factor analysis (principal component extraction with varimax rotation) of specific items revealed three factors (eigenvalues \u3e 2.0) explaining 47% of total variance, namely task interaction and goals (10 items, 26%, Cronbach’s Alpha = 0.87), urgency and acuity (6 items, 11%, Cronbach’s Alpha = 0.67), and psychosocial behavior (4 items, 10%, Cronbach’s alpha = 0.55). A linear regression analysis showed no statistically significant association between complexity perceived by the physicians and objective complexity, which was measured from coded transcripts by three clinicians (Multiple R-squared = 0.13, p = 0.61). There were no physician effects on the rating of perceived complexity. Conclusion Task complexity contributes significantly to overall complexity in the infectious diseases domain. The different complexity-contributing factors found in this study can guide health information technology system designers and researchers for intuitive design. Thus, decision support tools can help reduce the specific complexity-contributing factors. Future studies aimed at understanding clinical domain-specific complexity-contributing factors can ultimately improve task allocation and design for intuitive clinical reasoning

Formative evaluation of a patient-specific clinical knowledge summarization tool

To iteratively design a prototype of a computerized clinical knowledge summarization (CKS) tool aimed at helping clinicians finding answers to their clinical questions; and to conduct a formative assessment of the usability, usefulness, efficiency, and impact of the CKS prototype on physicians’ perceived decision quality compared with standard search of UpToDate and PubMed

Can prospective usability evaluation predict data errors?

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance

Developing a Prototype System for Integrating Pharmacogenomics Findings into Clinical Practice

Findings from pharmacogenomics (PGx) studies have the potential to be applied to individualize drug therapy to improve efficacy and reduce adverse drug events. Researchers have identified factors influencing uptake of genomics in medicine, but little is known about the specific technical barriers to incorporating PGx into existing clinical frameworks. We present the design and development of a prototype PGx clinical decision support (CDS) system that builds on existing clinical infrastructure and incorporates semi-active and active CDS. Informing this work, we updated previous evaluations of PGx knowledge characteristics, and of how the CDS capabilities of three local clinical systems align with data and functional requirements for PGx CDS. We summarize characteristics of PGx knowledge and technical needs for implementing PGx CDS within existing clinical frameworks. PGx decision support rules derived from FDA drug labels primarily involve drug metabolizing genes, vary in maturity, and the majority support the post-analytic phase of genetic testing. Computerized provider order entry capabilities are key functional requirements for PGx CDS and were best supported by one of the three systems we evaluated. We identified two technical needs when building on this system, the need for (1) new or existing standards for data exchange to connect clinical data to PGx knowledge, and (2) a method for implementing semi-active CDS. Our analyses enhance our understanding of principles for designing and implementing CDS for drug therapy individualization and our current understanding of PGx characteristics in a clinical context. Characteristics of PGx knowledge and capabilities of current clinical systems can help govern decisions about CDS implementation, and can help guide decisions made by groups that develop and maintain knowledge resources such that delivery of content for clinical care is supported

Text summarization in the biomedical domain: A systematic review of recent research

The amount of information for clinicians and clinical researchers is growing exponentially. Text summarization reduces information as an attempt to enable users to find and understand relevant source texts more quickly and effortlessly. In recent years, substantial research has been conducted to develop and evaluate various summarization techniques in the biomedical domain. The goal of this study was to systematically review recent published research on summarization of textual documents in the biomedical domain