Knowledge acquisition, synthesis, and validation: a model for decision support systems

O’Neill, Eileen; Dluhy, Nancy M.; Fortier, Paul; Michel, Howard E.

doi:10.1111/j.1365-2648.2004.03072.x

Cited by 38 publications

(25 citation statements)

References 29 publications

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“…In 2002, researchers at the University of Massachusetts Dartmouth began the development of a CDSS entitled ''The Nurse Computer Decision Support Project.'' 29 The CDSS was developed using the model entitled ''The Knowledge Development Process'' (Figure 2). Although the authors indicated that the model was designed to support the decision-making needs of novice nurses, it may also be useful to support the decisionmaking needs of experienced nurses.…”

Section: Design and Implementationmentioning

confidence: 99%

Design and Implementation of a Nursing Clinical Decision Support System to Promote Guideline Adherence

Lyerla

2008

CIN: Computers, Informatics, Nursing

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This article describes the development and implementation of a nursing clinical decision support system that prompts nurses to place mechanically ventilated patients in a semirecumbent position in the absence of contraindications. A literature review is provided regarding (1) ventilator-associated pneumonia and recommendations from expert panels to maintain mechanically ventilated patients in a semirecumbent position (unless contraindicated) and (2) clinical decision support systems. Use of clinical decision support systems has primarily been developed for physicians; however, there is growing interest in expanding this technology to nurses working in the clinical area. Despite recommendations from organizations such as the Center for Disease Control and Prevention to maintain mechanically ventilated patients in a head-elevated position, there is evidence that the practice is not adequately adhered to. Therefore, a nursing clinical decision support system (in the form of a reminder) that prompts nurses to adhere to this recommendation was designed and implemented.

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Section: Design and Implementationmentioning

confidence: 99%

Design and Implementation of a Nursing Clinical Decision Support System to Promote Guideline Adherence

Lyerla

2008

CIN: Computers, Informatics, Nursing

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“…24 The CDSS we used was based on the knowledge development process model. 25 The model depicts the process of meeting the clinical decision-making needs of nurses via a decision support system. The process begins with identifying the decision-making need and the associated knowledge domain.…”

Section: Review Of Relevant Literaturementioning

confidence: 99%

A Nursing Clinical Decision Support System and Potential Predictors of Head-of-Bed Position for Patients Receiving Mechanical Ventilation

Lyerla

LeRouge

Cooke

et al. 2010

American Journal of Critical Care

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Background Patients receiving mechanical ventilation are at high risk for pneumonia due to aspiration. Published guidelines recommend elevating the head of the bed 30º to 45º, if not contraindicated, to reduce risk, but this intervention is underused. Objectives To facilitate incorporating evidence-based practice by improving positioning of patients receiving mechanical ventilation and to identify patient and nurse characteristics that predict use of the guideline. Methods A modified interrupted time-series design was used. Data were collected on 43 patients and 33 nurses 3 separate times in a 12-bed intensive care unit at a medium-sized hospital. A total of 105 observations were recorded for analysis each time. Results Mean elevations of the head of the bed increased significantly from phase 1 (27.7º) to phase 2 (31.7º) and from phase 1 to phase 3 (31.1º). Elevations were higher for tube-fed patients than for patients not given enteral tube feedings. Elevations were higher for patients with a pulmonary-related diagnosis and lower for patients with a gastrointestinal diagnosis than for patients with other diagnoses. Elevations were lower for patients with a body mass index between 25.0 and 29.9 (overweight) than for patients with other body mass index values. Nurse characteristics were not significant predictors of elevation. Conclusion A nursing clinical decision support system integrated into a patient's electronic flow sheet can increase nurses' adherence to guidelines. Pulmonary and gastrointestinal diagnoses, body mass index, and tube feeding are predictors of elevation of the head of the bed.

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“…12 They discuss innovative approaches for knowledge development such as integration of clinical experts and a practice network to incorporate practice knowledge. These strategies will assist scientists and practitioners interested in determining the best evidence to support clinical decision support systems.…”

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confidence: 99%

Investigating patients' and general practitioners' views of computerised decision support software for the assessment and management of cardiovascular risk

Wilson¹,

Duszynski²,

Turnbull³

et al. 2007

Journal of Innovation in Health Informatics

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Purpose This paper reports an evaluation of the usability and acceptability of a computer-based decision support program (EMPOWER TM ) for cardiovascular risk from the perspectives of both general practitioners (GPs) and consumers. Methods A qualitative research design utilised semi-structured telephone interviews to assess the program from participants' perspectives. Qualitative approaches included the use of purposeful sampling, the collection of open-ended data, and the analysis of text and personal interpretation of findings. The theoretical foundations for the methods chosen are explained. Results Consumers enjoyed being involved in the study and thought the program had benefits for encouraging confidence in seeking health care. Consumers reported feeling reassured about the processes followed during consultation. GPs found the application of the software program increased demands on their time but admired several features of the program, especially its educational advantages. Participants were of the opinion that the program would be of particular benefit to inexperienced GPs and newly diagnosed patients. Conclusion Computer decision support programs are becoming more prevalent, but little is known about their usability and acceptability to both health professionals and consumers. The complexities of cardiovascular risk assessment and management can be adequately managed with such programs. As a contemporary report this study contributes to the growing knowledge required for developers of medical software and decision support systems to better understand the needs of endusers.

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Knowledge acquisition, synthesis, and validation: a model for decision support systems

Abstract: These strategies will assist scientists and practitioners interested in determining the best evidence to support clinical decision support systems.

Cited by 38 publications

References 29 publications

Design and Implementation of a Nursing Clinical Decision Support System to Promote Guideline Adherence

Design and Implementation of a Nursing Clinical Decision Support System to Promote Guideline Adherence

A Nursing Clinical Decision Support System and Potential Predictors of Head-of-Bed Position for Patients Receiving Mechanical Ventilation

Investigating patients' and general practitioners' views of computerised decision support software for the assessment and management of cardiovascular risk

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