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Rees SE, Spadaro S, Dalla Corte F, Dey N, Brohus JB, Scaramuzzo G, Lodahl D, Winding RR, Volta CA, Karbing DS. Transparent decision support for mechanical ventilation using visualization of clinical preferences. Biomed Eng Online 2022; 21:5. [PMID: 35073928 PMCID: PMC8785460 DOI: 10.1186/s12938-021-00974-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 12/27/2021] [Indexed: 12/02/2022] Open
Abstract
Background Systems aiding in selecting the correct settings for mechanical ventilation should visualize patient information at an appropriate level of complexity, so as to reduce information overload and to make reasoning behind advice transparent. Metaphor graphics have been applied to this effect, but these have largely been used to display diagnostic and physiologic information, rather than the clinical decision at hand. This paper describes how the conflicting goals of mechanical ventilation can be visualized and applied in making decisions. Data from previous studies are analyzed to assess whether visual patterns exist which may be of use to the clinical decision maker. Materials and methods The structure and screen visualizations of a commercial clinical decision support system (CDSS) are described, including the visualization of the conflicting goals of mechanical ventilation represented as a hexagon. Retrospective analysis is performed on 95 patients from 2 previous clinical studies applying the CDSS, to identify repeated patterns of hexagon symbols. Results Visual patterns were identified describing optimal ventilation, over and under ventilation and pressure support, and over oxygenation, with these patterns identified for both control and support modes of mechanical ventilation. Numerous clinical examples are presented for these patterns illustrating their potential interpretation at the bedside. Conclusions Visual patterns can be identified which describe the trade-offs required in mechanical ventilation. These may have potential to reduce information overload and help in simple and rapid identification of sub-optimal settings. Supplementary Information The online version contains supplementary material available at 10.1186/s12938-021-00974-5.
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Lin YL, Trbovich P, Kolodzey L, Nickel C, Guerguerian AM. Association of Data Integration Technologies With Intensive Care Clinician Performance: A Systematic Review and Meta-analysis. JAMA Netw Open 2019; 2:e194392. [PMID: 31125104 PMCID: PMC6632132 DOI: 10.1001/jamanetworkopen.2019.4392] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
IMPORTANCE Sources of data in the intensive care setting are increasing exponentially, but the benefits of displaying multiparametric, high-frequency data are unknown. Decision making may not benefit from this technology if clinicians remain cognitively overburdened by poorly designed data integration and visualization technologies (DIVTs). OBJECTIVE To systematically review and summarize the published evidence on the association of user-centered DIVTs with intensive care clinician performance. DATA SOURCES MEDLINE, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, and Web of Science were searched in May 2014 and January 2018. STUDY SELECTION Studies had 3 requirements: (1) the study tested a viable DIVT, (2) participants involved were intensive care clinicians, and (3) the study reported quantitative results associated with decision making in an intensive care setting. DATA EXTRACTION AND SYNTHESIS Of 252 records screened, 20 studies, published from 2004 to 2016, were included. The human factors framework to assess health technologies was applied to measure study completeness, and the Quality Assessment Instrument was used to assess the quality of the studies. PRISMA guidelines were adapted to conduct the systematic review and meta-analysis. MAIN OUTCOMES AND MEASURES Study completeness and quality; clinician performance; physical, mental, and temporal demand; effort; frustration; time to decision; and decision accuracy. RESULTS Of the 20 included studies, 16 were experimental studies with 410 intensive care clinician participants and 4 were survey-based studies with 1511 respondents. Scores for study completeness ranged from 27 to 43, with a maximum score of 47, and scores for study quality ranged from 46 to 79, with a maximum score of 90. Of 20 studies, DIVTs were evaluated in clinical settings in 2 studies (10%); time to decision was measured in 14 studies (70%); and decision accuracy was measured in 11 studies (55%). Measures of cognitive workload pooled in the meta-analysis suggested that any DIVT was an improvement over paper-based data in terms of self-reported performance, mental and temporal demand, and effort. With a maximum score of 22, median (IQR) mental demand scores for electronic display were 10 (7-13), tabular display scores were 8 (6.0-11.5), and novel visualization scores were 8 (6-12), compared with 17 (14-19) for paper. The median (IQR) temporal demand scores were also lower for all electronic visualizations compared with paper, with scores of 8 (6-11) for electronic display, 7 (6-11) for tabular and bar displays, 7 (5-11) for novel visualizations, and 16 (14.3-19.0) for paper. The median (IQR) performance scores improved for all electronic visualizations compared with paper (lower score indicates better self-reported performance), with scores of 6 (3-11) for electronic displays, 6 (4-11) for tabular and bar displays, 6 (4-11) for novel visualizations, and 14 (11-16) for paper. Frustration and physical demand domains of cognitive workload did not change, and differences between electronic displays were not significant. CONCLUSIONS AND RELEVANCE This review suggests that DIVTs are associated with increased integration and consistency of data. Much work remains to identify which visualizations effectively reduce cognitive workload to enhance decision making based on intensive care data. Standardizing human factors testing by developing a repository of open access benchmarked test protocols, using a set of outcome measures, scenarios, and data sets, may accelerate the design and selection of the most appropriate DIVT.
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Affiliation(s)
- Ying Ling Lin
- Institute of Biomaterials and Biomedical Engineering, Faculty of Engineering, University of Toronto, Toronto, Ontario, Canada
- Department of Critical Care Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Patricia Trbovich
- Institute of Biomaterials and Biomedical Engineering, Faculty of Engineering, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Badeau Family Research Chair in Patient Safety and Quality Improvement, North York General Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Lauren Kolodzey
- Institute of Biomaterials and Biomedical Engineering, Faculty of Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Cheri Nickel
- Hospital Library and Archives, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Anne-Marie Guerguerian
- Institute of Biomaterials and Biomedical Engineering, Faculty of Engineering, University of Toronto, Toronto, Ontario, Canada
- Department of Critical Care Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
- Neurosciences and Mental Health Program, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
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Lin YL, Guerguerian AM, Tomasi J, Laussen P, Trbovich P. "Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology". BMC Med Inform Decis Mak 2017; 17:122. [PMID: 28806954 PMCID: PMC5557066 DOI: 10.1186/s12911-017-0520-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2017] [Accepted: 08/04/2017] [Indexed: 11/17/2022] Open
Abstract
Background Intensive care clinicians use several sources of data in order to inform decision-making. We set out to evaluate a new interactive data integration platform called T3™ made available for pediatric intensive care. Three primary functions are supported: tracking of physiologic signals, displaying trajectory, and triggering decisions, by highlighting data or estimating risk of patient instability. We designed a human factors study to identify interface usability issues, to measure ease of use, and to describe interface features that may enable or hinder clinical tasks. Methods Twenty-two participants, consisting of bedside intensive care physicians, nurses, and respiratory therapists, tested the T3™ interface in a simulation laboratory setting. Twenty tasks were performed with a true-to-setting, fully functional, prototype, populated with physiological and therapeutic intervention patient data. Primary data visualization was time series and secondary visualizations were: 1) shading out-of-target values, 2) mini-trends with exaggerated maxima and minima (sparklines), and 3) bar graph of a 16-parameter indicator. Task completion was video recorded and assessed using a use error rating scale. Usability issues were classified in the context of task and type of clinician. A severity rating scale was used to rate potential clinical impact of usability issues. Results Time series supported tracking a single parameter but partially supported determining patient trajectory using multiple parameters. Visual pattern overload was observed with multiple parameter data streams. Automated data processing using shading and sparklines was often ignored but the 16-parameter data reduction algorithm, displayed as a persistent bar graph, was visually intuitive. However, by selecting or automatically processing data, triggering aids distorted the raw data that clinicians use regularly. Consequently, clinicians could not rely on new data representations because they did not know how they were established or derived. Conclusions Usability issues, observed through contextual use, provided directions for tangible design improvements of data integration software that may lessen use errors and promote safe use. Data-driven decision making can benefit from iterative interface redesign involving clinician-users in simulated environments. This study is a first step in understanding how software can support clinicians’ decision making with integrated continuous monitoring data. Importantly, testing of similar platforms by all the different disciplines who may become clinician users is a fundamental step necessary to understand the impact on clinical outcomes of decision aids. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0520-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ying Ling Lin
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Rosebrugh Building (RS), 164 College Street, Room 407, Toronto, ON, M5S 3G9, Canada.,Department of Critical Care Medicine, The Hospital for Sick Children, Canada, 555 University Ave., 2nd Floor, Atrium - Room 2830A, Toronto, ON, M5G 1X8, Canada
| | - Anne-Marie Guerguerian
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Rosebrugh Building (RS), 164 College Street, Room 407, Toronto, ON, M5S 3G9, Canada.,Department of Critical Care Medicine, The Hospital for Sick Children, Canada, 555 University Ave., 2nd Floor, Atrium - Room 2830A, Toronto, ON, M5G 1X8, Canada.,Neurosciences and Mental Health Research, The Hospital for Sick Children Research Institute, Peter Gilgan Centre for Research & Learning, 686 Bay Street, Toronto, ON, M5G 0A4, Canada
| | - Jessica Tomasi
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Rosebrugh Building (RS), 164 College Street, Room 407, Toronto, ON, M5S 3G9, Canada
| | - Peter Laussen
- Department of Critical Care Medicine, The Hospital for Sick Children, Canada, 555 University Ave., 2nd Floor, Atrium - Room 2830A, Toronto, ON, M5G 1X8, Canada
| | - Patricia Trbovich
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Rosebrugh Building (RS), 164 College Street, Room 407, Toronto, ON, M5S 3G9, Canada. .,Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College St., Suite 425, Toronto, ON, M5T 3M6, Canada. .,Research and Innovation, North York General Hospital, 4001 Leslie Street, Toronto, ON, M2K 1E1, Canada.
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Farzandipour M, Meidani Z, Riazi H, Sadeqi Jabali M. Task-specific usability requirements of electronic medical records systems: Lessons learned from a national survey of end-users. Inform Health Soc Care 2017; 43:280-299. [DOI: 10.1080/17538157.2017.1290639] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Mehrdad Farzandipour
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
| | - Zahra Meidani
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
| | - Hossein Riazi
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Monireh Sadeqi Jabali
- Health Information Management Research Center, Department of Health Information Management & Technology, School of Allied Health Professions, Kashan University of Medical Sciences, Kashan, Iran
- Esabne Maryam Hospital, Isfahan University of Medical Sciences, Isfahan, Iran
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Kamaleswaran R, McGregor C. A Review of Visual Representations of Physiologic Data. JMIR Med Inform 2016; 4:e31. [PMID: 27872033 PMCID: PMC5138451 DOI: 10.2196/medinform.5186] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 02/23/2016] [Accepted: 09/06/2016] [Indexed: 11/13/2022] Open
Abstract
Background Physiological data is derived from electrodes attached directly to patients. Modern patient monitors are capable of sampling data at frequencies in the range of several million bits every hour. Hence the potential for cognitive threat arising from information overload and diminished situational awareness becomes increasingly relevant. A systematic review was conducted to identify novel visual representations of physiologic data that address cognitive, analytic, and monitoring requirements in critical care environments. Objective The aims of this review were to identify knowledge pertaining to (1) support for conveying event information via tri-event parameters; (2) identification of the use of visual variables across all physiologic representations; (3) aspects of effective design principles and methodology; (4) frequency of expert consultations; (5) support for user engagement and identifying heuristics for future developments. Methods A review was completed of papers published as of August 2016. Titles were first collected and analyzed using an inclusion criteria. Abstracts resulting from the first pass were then analyzed to produce a final set of full papers. Each full paper was passed through a data extraction form eliciting data for comparative analysis. Results In total, 39 full papers met all criteria and were selected for full review. Results revealed great diversity in visual representations of physiological data. Visual representations spanned 4 groups including tabular, graph-based, object-based, and metaphoric displays. The metaphoric display was the most popular (n=19), followed by waveform displays typical to the single-sensor-single-indicator paradigm (n=18), and finally object displays (n=9) that utilized spatiotemporal elements to highlight changes in physiologic status. Results obtained from experiments and evaluations suggest specifics related to the optimal use of visual variables, such as color, shape, size, and texture have not been fully understood. Relationships between outcomes and the users’ involvement in the design process also require further investigation. A very limited subset of visual representations (n=3) support interactive functionality for basic analysis, while only one display allows the user to perform analysis including more than one patient. Conclusions Results from the review suggest positive outcomes when visual representations extend beyond the typical waveform displays; however, there remain numerous challenges. In particular, the challenge of extensibility limits their applicability to certain subsets or locations, challenge of interoperability limits its expressiveness beyond physiologic data, and finally the challenge of instantaneity limits the extent of interactive user engagement.
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Affiliation(s)
- Rishikesan Kamaleswaran
- Center for Biomedical Informatics, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Carolyn McGregor
- University of Ontario Institute of Technology, Oshawa, ON, Canada
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Herasevich V, Ellsworth MA, Hebl JR, Brown MJ, Pickering BW. Information needs for the OR and PACU electronic medical record. Appl Clin Inform 2014; 5:630-41. [PMID: 25298804 DOI: 10.4338/aci-2014-02-ra-0015] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Accepted: 06/01/2014] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE The amount of clinical information that anesthesia providers encounter creates an environment for information overload and medical error. In an effort to create more efficient OR and PACU EMR viewer platforms, we aimed to better understand the intraoperative and post-anesthesia clinical information needs among anesthesia providers. MATERIALS AND METHODS A web-based survey to evaluate 75 clinical data items was created and distributed to all anesthesia providers at our institution. Participants were asked to rate the importance of each data item in helping them make routine clinical decisions in the OR and PACU settings. RESULTS There were 107 survey responses with distribution throughout all clinical roles. 84% of the data items fell within the top 2 proportional quarters in the OR setting compared to only 65% in the PACU. Thirty of the 75 items (40%) received an absolutely necessary rating by more than half of the respondents for the OR setting as opposed to only 19 of the 75 items (25%) in the PACU. Only 1 item was rated by more than 20% of respondents as not needed in the OR compared to 20 data items (27%) in the PACU. CONCLUSION Anesthesia providers demonstrate a larger need for EMR data to help guide clinical decision making in the OR as compared to the PACU. When creating EMR platforms for these settings it is important to understand and include data items providers deem the most clinically useful. Minimizing the less relevant data items helps prevent information overload and reduces the risk for medical error.
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Affiliation(s)
- V Herasevich
- Department of Anesthesiology, Mayo Clinic College of Medicine , Rochester, MN ; Multidisciplinary Epidemiology and Translation Research in Intensive Care (METRIC), Mayo Clinic College of Medicine , Rochester, MN
| | - M A Ellsworth
- Division of Neonatal Medicine, Mayo Clinic College of Medicine , Rochester, MN
| | - J R Hebl
- Department of Anesthesiology, Mayo Clinic College of Medicine , Rochester, MN
| | - M J Brown
- Department of Anesthesiology, Mayo Clinic College of Medicine , Rochester, MN
| | - B W Pickering
- Department of Anesthesiology, Mayo Clinic College of Medicine , Rochester, MN ; Multidisciplinary Epidemiology and Translation Research in Intensive Care (METRIC), Mayo Clinic College of Medicine , Rochester, MN
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Görges M, Westenskow DR, Markewitz BA. Evaluation of an integrated intensive care unit monitoring display by critical care fellow physicians. J Clin Monit Comput 2012; 26:429-36. [PMID: 22588528 DOI: 10.1007/s10877-012-9370-0] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2011] [Accepted: 05/02/2012] [Indexed: 11/28/2022]
Abstract
In the past two far-view displays, which showed vital signs, trends, alarms, infusion pump status, and therapy support indicators, were developed and assessed by critical care nurses (Görges et al. in Dimens Crit Care Nurs. 30(4):206-17, 2011). The aim of the current study is to assess the generalizability of these findings to physicians. The first aim is to test whether an integrated far-view display, designed to be readable from 3 to 5 m, enables critical care physicians to more rapidly and accurately (1) recognize a change in patient condition; (2) identify alarms; and (3) identify near-empty infusion pumps, than a traditional patient monitor and infusion pump. A second aim is to test if the new displays reduce the mental workload required for this decision making. Fifteen critical care fellow physicians (median age of 34 years, with 2-8 years of ICU experience) were asked to use the three displays to compare the data from two patients and decide which patient required their attention first. Each physician made 60 decisions: 20 with each of the two far-view displays and 20 decisions with a standard patient monitor next to an infusion pump. A 41 and 26 % improvement in decision accuracy was observed with the bar and clock far-view displays, respectively. Specifically, the identification of near empty infusion pumps, a task normally performed by nurses, and patients with a single alarm were better with the new displays. Using the bar display physicians made their decision 12 % faster than when using the control display, a median improvement of 2.1 s. No significant differences were observed in measured workload. Displays that present patient data in a redesigned format enables critical care clinicians to more rapidly identify changes in patient conditions and to more accurately decide which patient needs their attention. In a clinical setting, this could improve patient safety. In future work, an evaluation of the display using live patient data from an ICU should be performed.
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Affiliation(s)
- Matthias Görges
- Electrical and Computer Engineering Department, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
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Evolving approaches to assessing and monitoring patient–ventilator interactions. Curr Opin Crit Care 2010; 16:261-8. [DOI: 10.1097/mcc.0b013e328338661e] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Lamy JB, Duclos C, Bar-Hen A, Ouvrard P, Venot A. An iconic language for the graphical representation of medical concepts. BMC Med Inform Decis Mak 2008; 8:16. [PMID: 18435838 PMCID: PMC2413217 DOI: 10.1186/1472-6947-8-16] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2007] [Accepted: 04/24/2008] [Indexed: 11/30/2022] Open
Abstract
Background Many medication errors are encountered in drug prescriptions, which would not occur if practitioners could remember the drug properties. They can refer to drug monographs to find these properties, however drug monographs are long and tedious to read during consultation. We propose a two-step approach for facilitating access to drug monographs. The first step, presented here, is the design of a graphical language, called VCM. Methods The VCM graphical language was designed using a small number of graphical primitives and combinatory rules. VCM was evaluated over 11 volunteer general practitioners to assess if the language is easy to learn, to understand and to use. Evaluators were asked to register their VCM training time, to indicate the meaning of VCM icons and sentences, and to answer clinical questions related to randomly generated drug monograph-like documents, supplied in text or VCM format. Results VCM can represent the various signs, diseases, physiological states, life habits, drugs and tests described in drug monographs. Grammatical rules make it possible to generate many icons by combining a small number of primitives and reusing simple icons to build more complex ones. Icons can be organized into simple sentences to express drug recommendations. Evaluation showed that VCM was learnt in 2 to 7 hours, that physicians understood 89% of the tested VCM icons, and that they answered correctly to 94% of questions using VCM (versus 88% using text, p = 0.003) and 1.8 times faster (p < 0.001). Conclusion VCM can be learnt in a few hours and appears to be easy to read. It can now be used in a second step: the design of graphical interfaces facilitating access to drug monographs. It could also be used for broader applications, including the design of interfaces for consulting other types of medical document or medical data, or, very simply, to enrich medical texts.
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Affiliation(s)
- Jean-Baptiste Lamy
- Laboratoire d'Informatique Médicale et de Bioinformatique (LIM&BIO), UFR SMBH, Université Paris 13, 74 rue Marcel Cachin, 93017 Bobigny cedex, France.
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Görges M, Staggers N. Evaluations of Physiological Monitoring Displays: A Systematic Review. J Clin Monit Comput 2007; 22:45-66. [DOI: 10.1007/s10877-007-9106-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2007] [Accepted: 11/13/2007] [Indexed: 11/27/2022]
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Wachter SB, Johnson K, Albert R, Syroid N, Drews F, Westenskow D. The evaluation of a pulmonary display to detect adverse respiratory events using high resolution human simulator. J Am Med Inform Assoc 2006; 13:635-42. [PMID: 16929038 PMCID: PMC1656961 DOI: 10.1197/jamia.m2123] [Citation(s) in RCA: 39] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Authors developed a picture-graphics display for pulmonary function to present typical respiratory data used in perioperative and intensive care environments. The display utilizes color, shape and emergent alerting to highlight abnormal pulmonary physiology. The display serves as an adjunct to traditional operating room displays and monitors. DESIGN To evaluate the prototype, nineteen clinician volunteers each managed four adverse respiratory events and one normal event using a high-resolution patient simulator which included the new displays (intervention subjects) and traditional displays (control subjects). Between-group comparisons included (i) time to diagnosis and treatment for each adverse respiratory event; (ii) the number of unnecessary treatments during the normal scenario; and (iii) self-reported workload estimates while managing study events. MEASUREMENTS Two expert anesthesiologists reviewed video-taped transcriptions of the volunteers to determine time to treat and time to diagnosis. Time values were then compared between groups using a Mann-Whitney-U Test. Estimated workload for both groups was assessed using the NASA-TLX and compared between groups using an ANOVA. P-values < 0.05 were considered significant. RESULTS Clinician volunteers detected and treated obstructed endotracheal tubes and intrinsic PEEP problems faster with graphical rather than conventional displays (p < 0.05). During the normal scenario simulation, 3 clinicians using the graphical display, and 5 clinicians using the conventional display gave unnecessary treatments. Clinician-volunteers reported significantly lower subjective workloads using the graphical display for the obstructed endotracheal tube scenario (p < 0.001) and the intrinsic PEEP scenario (p < 0.03). CONCLUSION Authors conclude that the graphical pulmonary display may serve as a useful adjunct to traditional displays in identifying adverse respiratory events.
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Affiliation(s)
- S Blake Wachter
- University of Utah, Department of Anesthesiology, 3C444 SOM, 30 North 1900 East, Salt Lake City, UT 84132-2304, USA.
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Zhang J. Human-centered computing in health information systems part 2: evaluation. J Biomed Inform 2005; 38:173-5. [PMID: 15896690 DOI: 10.1016/j.jbi.2004.12.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2004] [Accepted: 12/27/2004] [Indexed: 10/25/2022]
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