Literature DB >> 19885205

Impact of human factors on clinical protocol performance: a proposed assessment framework and case examples.

J Geoffrey Chase1, Steen Andreassen, Karsten Jensen, Geoffrey M Shaw.   

Abstract

BACKGROUND: Hyperglycemia is prevalent in critical care and tight control can save lives. Current ad-hoc clinical protocols require significant clinical effort and can often produce highly variable results. Thus, tight control remains elusive as there is not enough understanding of the relationship between control performance and protocol design, particularly with regard to how a given protocol is implemented.
METHODS: This article examines the role of human factors and how individuals relate to technological protocols in clinical settings. The study consists of an overall brief review that is used to create a first graphical representation of the impact of human factors in clinical medical protocol implementations. This initial framework is examined in the context of two similar, but different, case studies-the specialized relative insulin and nutrition tables glycemic control protocol and the TREAT system for antibiotic selection.
RESULTS: A graphical framework relating the human factors impact on medical protocol implementation is created. This framework describes the primary impacts on performance as resulting from clinical burden and protocol transparency. Their primary effect is on compliance with the protocol, which directly affects performance and outcome, particularly in long-term studies versus short pilot studies.
SUMMARY: Compliance is a key element in obtaining the best clinical outcome that a given protocol can provide. The issues that most affect compliance are quite often unrelated to the patient or treatment, but are a function of the protocol design and its ability to integrate (by its design) into a given clinical setting. A framework for examining these issues in design and in post-hoc assessment is therefore proposed and examined in two brief case studies.

Entities:  

Keywords:  clinical protocol; clinical results; compliance; control; glucose variability; human factors; hyperglycemia; intensive insulin therapy; metabolism; model based; mortality; performance

Year:  2008        PMID: 19885205      PMCID: PMC2769730          DOI: 10.1177/193229680800200310

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  41 in total

1.  Intensive insulin therapy in critically ill patients.

Authors:  G van den Berghe; P Wouters; F Weekers; C Verwaest; F Bruyninckx; M Schetz; D Vlasselaers; P Ferdinande; P Lauwers; R Bouillon
Journal:  N Engl J Med       Date:  2001-11-08       Impact factor: 91.245

2.  Intensive insulin therapy in mixed medical/surgical intensive care units: benefit versus harm.

Authors:  Greet Van den Berghe; Alexander Wilmer; Ilse Milants; Pieter J Wouters; Bernard Bouckaert; Frans Bruyninckx; Roger Bouillon; Miet Schetz
Journal:  Diabetes       Date:  2006-11       Impact factor: 9.461

3.  Model-based insulin and nutrition administration for tight glycaemic control in critical care.

Authors:  J Geoffrey Chase; Geoffrey M Shaw; Thomas Lotz; Aaron LeCompte; Jason Wong; Jessica Lin; Timothy Lonergan; Michael Willacy; Christopher E Hann
Journal:  Curr Drug Deliv       Date:  2007-10       Impact factor: 2.565

4.  TRPV1+ sensory neurons control beta cell stress and islet inflammation in autoimmune diabetes.

Authors:  Rozita Razavi; Yin Chan; F Nikoo Afifiyan; Xue Jun Liu; Xiang Wan; Jason Yantha; Hubert Tsui; Lan Tang; Sue Tsai; Pere Santamaria; John P Driver; David Serreze; Michael W Salter; H-Michael Dosch
Journal:  Cell       Date:  2006-12-15       Impact factor: 41.582

5.  Performance obstacles of intensive care nurses.

Authors:  Ayse P Gurses; Pascale Carayon
Journal:  Nurs Res       Date:  2007 May-Jun       Impact factor: 2.381

6.  Facilitating clinician adherence to guidelines in the intensive care unit: A multicenter, qualitative study.

Authors:  Tasnim Sinuff; Deborah Cook; Mita Giacomini; Daren Heyland; Peter Dodek
Journal:  Crit Care Med       Date:  2007-09       Impact factor: 7.598

7.  Workflow in intensive care unit remote monitoring: A time-and-motion study.

Authors:  Zhihua Tang; Liza Weavind; Janine Mazabob; Eric J Thomas; Ming Ying L Chu-Weininger; Todd R Johnson
Journal:  Crit Care Med       Date:  2007-09       Impact factor: 7.598

Review 8.  Strategies to enhance compliance to physical activity for patients with insulin resistance.

Authors:  Alison Kirk; Pierpaolo De Feo
Journal:  Appl Physiol Nutr Metab       Date:  2007-06       Impact factor: 2.665

9.  Heterogeneity in the prevalence of risk factors for cardiovascular disease and type 2 diabetes mellitus in obese individuals: effect of differences in insulin sensitivity.

Authors:  Tracey McLaughlin; Fahim Abbasi; Cindy Lamendola; Gerald Reaven
Journal:  Arch Intern Med       Date:  2007-04-09

10.  Is there more to glycaemic control than meets the eye?

Authors:  J Geoffrey Chase; Geoffrey M Shaw
Journal:  Crit Care       Date:  2007       Impact factor: 9.097

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  25 in total

1.  Stochastic targeted (STAR) glycemic control: design, safety, and performance.

Authors:  Alicia Evans; Aaron Le Compte; Chia-Siong Tan; Logan Ward; James Steel; Christopher G Pretty; Sophie Penning; Fatanah Suhaimi; Geoffrey M Shaw; Thomas Desaive; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

2.  Interface design and human factors considerations for model-based tight glycemic control in critical care.

Authors:  Logan Ward; James Steel; Aaron Le Compte; Alicia Evans; Chia-Siong Tan; Sophie Penning; Geoffrey M Shaw; Thomas Desaive; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

Review 3.  "One more thing to think about…" Cognitive burden experienced by intensive care unit nurses when implementing a tight glucose control protocol.

Authors:  Lit Soo Ng; Martha A Q Curley
Journal:  J Diabetes Sci Technol       Date:  2012-01-01

4.  Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

Authors:  Tony Zhou; Jennifer L Dickson; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2017-07-14

5.  Interpretation of Retrospective BG Measurements.

Authors:  Kent W Stewart; Christopher G Pretty; Geoffrey M Shaw; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2018-07-12

Review 6.  Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support.

Authors:  Kristen Miller; Danielle Mosby; Muge Capan; Rebecca Kowalski; Raj Ratwani; Yaman Noaiseh; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  J Am Med Inform Assoc       Date:  2018-05-01       Impact factor: 4.497

7.  Blood glucose controller for neonatal intensive care: virtual trials development and first clinical trials.

Authors:  Aaron Le Compte; J Geoffrey Chase; Adrienne Lynn; Chris Hann; Geoffrey Shaw; Xing-Wei Wong; Jessica Lin
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

8.  Pilot study of the SPRINT glycemic control protocol in a Hungarian medical intensive care unit.

Authors:  Balazs Benyo; Attila Illyés; Noémi Szabó Némedi; Aaron J Le Compte; Attila Havas; Levente Kovacs; Liam Fisk; Geoffrey M Shaw; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2012-11-01

Review 9.  The design of decisions: Matching clinical decision support recommendations to Nielsen's design heuristics.

Authors:  Kristen Miller; Muge Capan; Danielle Weldon; Yaman Noaiseh; Rebecca Kowalski; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold
Journal:  Int J Med Inform       Date:  2018-05-21       Impact factor: 4.046

10.  Usability study of a new tool for nutritional and glycemic management in adult intensive care: Glucosafe 2.

Authors:  Aude de Watteville; Ulrike Pielmeier; Séverine Graf; Nils Siegenthaler; Bernard Plockyn; Steen Andreassen; Claudia-Paula Heidegger
Journal:  J Clin Monit Comput       Date:  2020-03-27       Impact factor: 2.502

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