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Protocol-Driven Decision Support within e-Referral Systems to Streamline Patient Consultation, Triaging and Referrals from Primary Care to Specialist Clinics
Patient referral is a protocol where the referring primary care physician refers the patient to a specialist for further treatment. The paper-based current referral process at times lead to communication and operational issues, resulting in either an unfulfilled referral request or an unnecessary re...
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Published in: | Journal of medical systems 2017-09, Vol.41 (9), p.139-139, Article 139 |
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creator | Maghsoud-Lou, Ehsan Christie, Sean Abidi, Samina Raza Abidi, Syed Sibte Raza |
description | Patient referral is a protocol where the referring primary care physician refers the patient to a specialist for further treatment. The paper-based current referral process at times lead to communication and operational issues, resulting in either an unfulfilled referral request or an unnecessary referral request. Despite the availability of standardized referral protocols they are not readily applied because they are tedious and time-consuming, thus resulting in suboptimal referral requests. We present a semantic-web based
Referral Knowledge Modeling and Execution Framework
to computerize referral protocols, clinical guidelines and assessment tools in order to develop a computerized e-Referral system that offers protocol-based decision support to streamline and standardize the referral process. We have developed a Spinal Problem E-Referral (SPER) system that computerizes the
Spinal Condition Consultation Protocol
(SCCP) mandated by the Halifax Infirmary Division of Neurosurgery (Halifax, Canada) for referrals for spine related conditions (such as back pain). The SPER system executes the ontologically modeled SCCP to determine (i) patient’s triaging option as per severity assessments stipulated by SCCP; and (b) clinical recommendations as per the clinical guidelines incorporated within SCCP. In operation, the SPER system identifies the critical cases and triages them for specialist referral, whereas for non-critical cases SPER system provides clinical guideline based recommendations to help the primary care physician effectively manage the patient. The SPER system has undergone a pilot usability study and was deemed to be easy to use by physicians with potential to improve the referral process within the Division of Neurosurgery at QEII Health Science Center, Halifax, Canada. |
doi_str_mv | 10.1007/s10916-017-0791-7 |
format | article |
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Referral Knowledge Modeling and Execution Framework
to computerize referral protocols, clinical guidelines and assessment tools in order to develop a computerized e-Referral system that offers protocol-based decision support to streamline and standardize the referral process. We have developed a Spinal Problem E-Referral (SPER) system that computerizes the
Spinal Condition Consultation Protocol
(SCCP) mandated by the Halifax Infirmary Division of Neurosurgery (Halifax, Canada) for referrals for spine related conditions (such as back pain). The SPER system executes the ontologically modeled SCCP to determine (i) patient’s triaging option as per severity assessments stipulated by SCCP; and (b) clinical recommendations as per the clinical guidelines incorporated within SCCP. In operation, the SPER system identifies the critical cases and triages them for specialist referral, whereas for non-critical cases SPER system provides clinical guideline based recommendations to help the primary care physician effectively manage the patient. The SPER system has undergone a pilot usability study and was deemed to be easy to use by physicians with potential to improve the referral process within the Division of Neurosurgery at QEII Health Science Center, Halifax, Canada.</description><identifier>ISSN: 0148-5598</identifier><identifier>EISSN: 1573-689X</identifier><identifier>DOI: 10.1007/s10916-017-0791-7</identifier><identifier>PMID: 28766103</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Back pain ; Consultation ; Decision support systems ; Guidelines ; Health care ; Health Informatics ; Health Sciences ; Humans ; Medical personnel ; Medical referrals ; Medicine ; Medicine & Public Health ; Neurosurgery ; Pain ; Physicians ; Pilot Projects ; Primary care ; Primary Health Care ; Referral and Consultation ; Specialists ; Specialization ; Spine ; Statistics for Life Sciences ; Systems-Level Quality Improvement ; Triage</subject><ispartof>Journal of medical systems, 2017-09, Vol.41 (9), p.139-139, Article 139</ispartof><rights>Springer Science+Business Media, LLC 2017</rights><rights>Journal of Medical Systems is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c372t-432dc8a3551cf6af8d85df77ddc5110e776e8e66cb0638852c68cc6ce6ebfa423</citedby><cites>FETCH-LOGICAL-c372t-432dc8a3551cf6af8d85df77ddc5110e776e8e66cb0638852c68cc6ce6ebfa423</cites><orcidid>0000-0003-3075-7736</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28766103$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Maghsoud-Lou, Ehsan</creatorcontrib><creatorcontrib>Christie, Sean</creatorcontrib><creatorcontrib>Abidi, Samina Raza</creatorcontrib><creatorcontrib>Abidi, Syed Sibte Raza</creatorcontrib><title>Protocol-Driven Decision Support within e-Referral Systems to Streamline Patient Consultation, Triaging and Referrals from Primary Care to Specialist Clinics</title><title>Journal of medical systems</title><addtitle>J Med Syst</addtitle><addtitle>J Med Syst</addtitle><description>Patient referral is a protocol where the referring primary care physician refers the patient to a specialist for further treatment. The paper-based current referral process at times lead to communication and operational issues, resulting in either an unfulfilled referral request or an unnecessary referral request. Despite the availability of standardized referral protocols they are not readily applied because they are tedious and time-consuming, thus resulting in suboptimal referral requests. We present a semantic-web based
Referral Knowledge Modeling and Execution Framework
to computerize referral protocols, clinical guidelines and assessment tools in order to develop a computerized e-Referral system that offers protocol-based decision support to streamline and standardize the referral process. We have developed a Spinal Problem E-Referral (SPER) system that computerizes the
Spinal Condition Consultation Protocol
(SCCP) mandated by the Halifax Infirmary Division of Neurosurgery (Halifax, Canada) for referrals for spine related conditions (such as back pain). The SPER system executes the ontologically modeled SCCP to determine (i) patient’s triaging option as per severity assessments stipulated by SCCP; and (b) clinical recommendations as per the clinical guidelines incorporated within SCCP. In operation, the SPER system identifies the critical cases and triages them for specialist referral, whereas for non-critical cases SPER system provides clinical guideline based recommendations to help the primary care physician effectively manage the patient. The SPER system has undergone a pilot usability study and was deemed to be easy to use by physicians with potential to improve the referral process within the Division of Neurosurgery at QEII Health Science Center, Halifax, Canada.</description><subject>Back pain</subject><subject>Consultation</subject><subject>Decision support systems</subject><subject>Guidelines</subject><subject>Health care</subject><subject>Health Informatics</subject><subject>Health Sciences</subject><subject>Humans</subject><subject>Medical personnel</subject><subject>Medical referrals</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Neurosurgery</subject><subject>Pain</subject><subject>Physicians</subject><subject>Pilot Projects</subject><subject>Primary care</subject><subject>Primary Health Care</subject><subject>Referral and Consultation</subject><subject>Specialists</subject><subject>Specialization</subject><subject>Spine</subject><subject>Statistics for Life 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Syst</addtitle><date>2017-09</date><risdate>2017</risdate><volume>41</volume><issue>9</issue><spage>139</spage><epage>139</epage><pages>139-139</pages><artnum>139</artnum><issn>0148-5598</issn><eissn>1573-689X</eissn><abstract>Patient referral is a protocol where the referring primary care physician refers the patient to a specialist for further treatment. The paper-based current referral process at times lead to communication and operational issues, resulting in either an unfulfilled referral request or an unnecessary referral request. Despite the availability of standardized referral protocols they are not readily applied because they are tedious and time-consuming, thus resulting in suboptimal referral requests. We present a semantic-web based
Referral Knowledge Modeling and Execution Framework
to computerize referral protocols, clinical guidelines and assessment tools in order to develop a computerized e-Referral system that offers protocol-based decision support to streamline and standardize the referral process. We have developed a Spinal Problem E-Referral (SPER) system that computerizes the
Spinal Condition Consultation Protocol
(SCCP) mandated by the Halifax Infirmary Division of Neurosurgery (Halifax, Canada) for referrals for spine related conditions (such as back pain). The SPER system executes the ontologically modeled SCCP to determine (i) patient’s triaging option as per severity assessments stipulated by SCCP; and (b) clinical recommendations as per the clinical guidelines incorporated within SCCP. In operation, the SPER system identifies the critical cases and triages them for specialist referral, whereas for non-critical cases SPER system provides clinical guideline based recommendations to help the primary care physician effectively manage the patient. The SPER system has undergone a pilot usability study and was deemed to be easy to use by physicians with potential to improve the referral process within the Division of Neurosurgery at QEII Health Science Center, Halifax, Canada.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>28766103</pmid><doi>10.1007/s10916-017-0791-7</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-3075-7736</orcidid></addata></record> |
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subjects | Back pain Consultation Decision support systems Guidelines Health care Health Informatics Health Sciences Humans Medical personnel Medical referrals Medicine Medicine & Public Health Neurosurgery Pain Physicians Pilot Projects Primary care Primary Health Care Referral and Consultation Specialists Specialization Spine Statistics for Life Sciences Systems-Level Quality Improvement Triage |
title | Protocol-Driven Decision Support within e-Referral Systems to Streamline Patient Consultation, Triaging and Referrals from Primary Care to Specialist Clinics |
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