A Successful Computerized Protocol for Clinical Management of Pressure Control Inverse Ratio Ventilation in ARDS Patients

East, Thomas D.; Böhm, Stephan H.; Wallace, C. J.; Clemmer, Terry P.; Weaver, Lindell K.; Orme, James F.; Morris, Alan H.

doi:10.1378/chest.101.3.697

Cited by 94 publications

(31 citation statements)

References 15 publications

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“…Besides regular ventilatory modes as pressure controlled ventilation and SIMV, PC-IRV was introduced. Adequacy of use of this ventilatory mode was observed in previous investigations [6,23] despite questions regarding its impact in patient's hemodynamics [15]. The hemodynamic evaluation module introduced in DSSARDS together with the experience of the medical team with this mode gave support to its use.…”

Section: Discussionmentioning

confidence: 87%

“…Secondly, decision making during several phases is based essentially on expert knowledge from experienced physicians [4,5]. The need for organization of knowledge in the area has been expressed in the trend towards establishment of protocols for mechanical ventilation [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Different aspects of the process have been approached as: critique of physicians therapeutic suggestions of ventilator settings [8]; suggestion of changes in ventilator variables and modes based on data received from a ventilator and other hospital information systems (HIS) [9]; weaning in ARDS [10]; advice on ventilatory support modes in ARDS [11] and monitoring of patients on mechanical ventilation with prediction of the effects of diverse ventilator settings [12]. Different methods are used in these systems as expert systems [8], protocols [6,13] and mathematical models [12]. Regarding their interconnections, the DSS may involve the availability of a HIS [11], automatic data acquisition [9] or function as a stand-alone unit [7].…”

Section: Introductionmentioning

confidence: 99%

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Decision support system to assist mechanical ventilation in the adult respiratory distress syndrome

Bottino

Giannella-Neto

David

et al. 1997

Int. J. Clin. Mon. Comp.

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This paper presents a knowledge-based decision support system to assist mechanical ventilation in patients with the Adult Respiratory Distress Syndrome (DSSARDS). The knowledge base uses clinical algorithms developed from interviews and seminars with experts. The system contains 140 rules, applies backward chaining and was built on an IBM-PC compatible microcomputer. Clinical and physiological data and ventilator settings were used for suggestions of ventilatory support mode (VSMODE) and settings (MVSET) and for hemodynamic evaluation and therapy (HEMO). Success rates (s) and kappa coefficient (k) were used to measure agreement between DSSARDS and physicians at 4 decision steps related to: beginning of mechanical ventilation (FIRSTSET), VSMODE, MVSET and HEMO, DSSARDS prototype was evaluated in a development phase with 6 patients aged 48.6 +/- 15.9 years. Agreement results for 142 decision steps were: FIRSTSET k = 0.90, s = 0.93; VSMODE k = 0.76, s = 0.92; HEMO k = 0.58, s = 0.70, MVSET k = 0.86, s = 0.92 (p < 0.05 for all k). Improvements in the knowledge base were performed mainly in HEMO and VSMODE modules. The subsequent test phase studied 5 patients aged 54.8 +/- 11.0 years in a total of 900 decision steps. Results were: FIRSTSET k = 0.93, s = 0.95; VSMODE k = 0.93, s = 0.96; HEMO k = 0.97, s = 0.99, MVSET k = 0.96, s = 0.97 (p < 0.05 for all k). The results indicate significant agreement between DSSARDS and physicians for all decision steps. This suggests that DSSARDS may be used as a support for decision making and a training tool for mechanical ventilation in patients with the adult respiratory distress syndrome.

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Section: Discussionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Decision support system to assist mechanical ventilation in the adult respiratory distress syndrome

Bottino

Giannella-Neto

David

et al. 1997

Int. J. Clin. Mon. Comp.

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“…The eProtocols are typically implemented in computer software to facilitate accurate and consistent navigation of the protocol, to reduce protocol complexity by hiding detail until needed, and to facilitate data capture regarding protocol usage. We have used eProtocols to improve healthcare quality [10][11][12][13][14][15][16]. These results refute the objections of some clinicians.…”

Section: Introductionmentioning

confidence: 84%

“…Our unique, supportive local environment and goal alignment between the clinicians and administrators enabled local development of eProtocols before extensive data regarding eProtocol effectiveness and outcomes were available. We began with a hardcoded mainframe computer program for mechanical ventilation [10][11][12]. During the last two decades, our eProtocols have evolved to stand-alone applications, and then to webbased applications available in multiple languages ( Fig.…”

Section: Introductionmentioning

confidence: 99%

The evolution of eProtocols that enable reproducible clinical research and care methods

Blagev

Sward

Thompson

et al. 2012

J Clin Monit Comput

Self Cite

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Unnecessary variation in clinical care and clinical research reduces our ability to determine what healthcare interventions are effective. Reducing this unnecessary variation could lead to further healthcare quality improvement and more effective clinical research. We have developed and used electronic decision support tools (eProtocols) to reduce unnecessary variation. Our eProtocols have progressed from a locally developed mainframe computer application in one clinical site (LDS Hospital) to web-based applications available in multiple languages and used internationally. We use eProtocol-insulin as an example to illustrate this evolution. We initially developed eProtocol-insulin as a local quality improvement effort to manage stress hyperglycemia in the adult intensive care unit (ICU). We extended eProtocol-insulin use to translate our quality improvement results into usual clinical care at Intermountain Healthcare ICUs. We exported eProtocol-insulin to support research in other US and international institutions, and extended our work to the pediatric ICU. We iteratively refined eProtocol-insulin throughout these transitions, and incorporated new knowledge about managing stress hyperglycemia in the ICU. Based on our experience in the development and clinical use of eProtocols, we outline remaining challenges to eProtocol development, widespread distribution and use, and suggest a process for eProtocol development. Technical and regulatory issues, as well as standardization of protocol development, validation and maintenance, need to be addressed. Resolution of these issues should facilitate general use of eProtocols to improve patient care.

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Guidelines You Can Follow and Can Trust

McDonald¹

1994

JAMA

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A Successful Computerized Protocol for Clinical Management of Pressure Control Inverse Ratio Ventilation in ARDS Patients

Cited by 94 publications

References 15 publications

Decision support system to assist mechanical ventilation in the adult respiratory distress syndrome

Decision support system to assist mechanical ventilation in the adult respiratory distress syndrome

The evolution of eProtocols that enable reproducible clinical research and care methods

Guidelines You Can Follow and Can Trust

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