Literature DB >> 21085744

From clinical practice guidelines to computer-interpretable guidelines. A literature overview.

A Latoszek-Berendsen1, H Tange, H J van den Herik, A Hasman.   

Abstract

BACKGROUND: Guidelines are among us for over 30 years. Initially they were used as algorithmic protocols by nurses and other ancillary personnel. Many physicians regarded the use of guidelines as cookbook medicine. However, quality and patient safety issues have changed the attitude towards guidelines. Implementing formalized guidelines in a decision support system with an interface to an electronic patient record (EPR) makes the application of guidelines more personal and therefore acceptable at the moment of care.
OBJECTIVE: To obtain, via a literature review, an insight into factors that influence the design and implementation of guidelines.
METHODS: An extensive search of the scientific literature in PubMed was carried out with a focus on guideline characteristics, guideline development and implementation, and guideline dissemination.
RESULTS: We present studies that enable us to explain the characteristics of high-quality guidelines, and new advanced methods for guideline formalization, computerization, and implementation. We show how the guidelines affect processes of care and the patient outcome. We discuss the reasons of low guideline adherence as presented in the literature and comment upon them.
CONCLUSIONS: Developing high-quality guidelines requires a skilled team of people and sufficient budget. The guidelines should give personalized advice. Computer-interpretable guidelines (CIGs) that have access to the patient's EPR are able to give personal advice. Because of the costs, sharing of CIGs is a critical requirement for guideline development, dissemination, and implementation. Until now this is hardly possible, because of the many models in use. However, some solutions have been proposed. For instance, a standardized terminology should be imposed so that the terms in guidelines can be matched with terms in an EPR. Also, a dissemination model for easy updating of guidelines should be established. The recommendations should be based on evidence instead of on consensus. To test the quality of the guideline, appraisal instruments should be used to assess the guideline as a whole, as well as checking the quality of the recommendations individually. Only in this way optimal guideline advice can be given on an individual basis at a reasonable cost.

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Mesh:

Year:  2010        PMID: 21085744     DOI: 10.3414/ME10-01-0056

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  18 in total

1.  Reconciling pairs of concurrently used clinical practice guidelines using Constraint Logic Programming.

Authors:  Szymon Wilk; Martin Michalowski; Wojtek Michalowski; Marisela Mainegra Hing; Ken Farion
Journal:  AMIA Annu Symp Proc       Date:  2011-10-22

2.  A physician order category-based clinical guideline comparison system.

Authors:  Hwan-Jeu Yu; Chia-Ping Shen; Sarangerel Dorjgochoo; Chi-Huang Chen; Jin-Ming Wu; Mei-Shu Lai; Ching-Ting Tan; Chinburen Jigjidsuren; Erdenebaatar Altangerel; Hung-Chang Lee; Chih-Wen Hsueh; Yufang Chung; Feipei Lai
Journal:  J Med Syst       Date:  2012-03-30       Impact factor: 4.460

Review 3.  Translating next generation sequencing to practice: opportunities and necessary steps.

Authors:  Sitharthan Kamalakaran; Vinay Varadan; Angel Janevski; Nilanjana Banerjee; David Tuck; W Richard McCombie; Nevenka Dimitrova; Lyndsay N Harris
Journal:  Mol Oncol       Date:  2013-05-15       Impact factor: 6.603

Review 4.  Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems.

Authors:  Phil Gooch; Abdul Roudsari
Journal:  J Am Med Inform Assoc       Date:  2011-07-01       Impact factor: 4.497

5.  Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms.

Authors:  Manuel Quesada-Martínez; Mar Marcos; Francisco Abad-Navarro; Begoña Martínez-Salvador; Jesualdo Tomás Fernández-Breis
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

6.  Creating computable algorithms for symptom management in an outpatient thoracic oncology setting.

Authors:  Mary E Cooley; David F Lobach; Ellis Johns; Barbara Halpenny; Toni-Ann Saunders; Guilherme Del Fiol; Michael S Rabin; Pamela Calarese; Isidore L Berenbaum; Ken Zaner; Kathleen Finn; Donna L Berry; Janet L Abrahm
Journal:  J Pain Symptom Manage       Date:  2013-05-13       Impact factor: 3.612

7.  Creating Shareable Clinical Decision Support Rules for a Pharmacogenomics Clinical Guideline Using Structured Knowledge Representation.

Authors:  Margaret K Linan; Davide Sottara; Robert R Freimuth
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

8.  Expanding a First-Order Logic Mitigation Framework to Handle Multimorbid Patient Preferences.

Authors:  Martin Michalowski; Szymon Wilk; Daniela Rosu; Mounira Kezadri; Wojtek Michalowski; Marc Carrier
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

9.  Evaluating acceptance and user experience of a guideline-based clinical decision support system execution platform.

Authors:  David Buenestado; Javier Elorz; Eduardo G Pérez-Yarza; Ander Iruetaguena; Unai Segundo; Raúl Barrena; Juan M Pikatza
Journal:  J Med Syst       Date:  2013-02-03       Impact factor: 4.460

10.  Feasibility of using algorithm-based clinical decision support for symptom assessment and management in lung cancer.

Authors:  Mary E Cooley; Traci M Blonquist; Paul J Catalano; David F Lobach; Barbara Halpenny; Ruth McCorkle; Ellis B Johns; Ilana M Braun; Michael S Rabin; Fatma Zohra Mataoui; Kathleen Finn; Donna L Berry; Janet L Abrahm
Journal:  J Pain Symptom Manage       Date:  2014-05-29       Impact factor: 3.612

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