Cargando…
Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework
OBJECTIVE: There are signals of clinicians’ expert and knowledge-driven behaviors within clinical information systems (CIS) that can be exploited to support clinical prediction. Describe development of the Healthcare Process Modeling Framework to Phenotype Clinician Behaviors for Exploiting the Sign...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200261/ https://www.ncbi.nlm.nih.gov/pubmed/33624765 http://dx.doi.org/10.1093/jamia/ocab006 |
_version_ | 1783707569968119808 |
---|---|
author | Rossetti, Sarah Collins Knaplund, Chris Albers, Dave Dykes, Patricia C Kang, Min Jeoung Korach, Tom Z Zhou, Li Schnock, Kumiko Garcia, Jose Schwartz, Jessica Fu, Li-Heng Klann, Jeffrey G Lowenthal, Graham Cato, Kenrick |
author_facet | Rossetti, Sarah Collins Knaplund, Chris Albers, Dave Dykes, Patricia C Kang, Min Jeoung Korach, Tom Z Zhou, Li Schnock, Kumiko Garcia, Jose Schwartz, Jessica Fu, Li-Heng Klann, Jeffrey G Lowenthal, Graham Cato, Kenrick |
author_sort | Rossetti, Sarah Collins |
collection | PubMed |
description | OBJECTIVE: There are signals of clinicians’ expert and knowledge-driven behaviors within clinical information systems (CIS) that can be exploited to support clinical prediction. Describe development of the Healthcare Process Modeling Framework to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals). MATERIALS AND METHODS: We employed an iterative framework development approach that combined data-driven modeling and simulation testing to define and refine a process for phenotyping clinician behaviors. Our framework was developed and evaluated based on the Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) predictive model to detect and leverage signals of clinician expertise for prediction of patient trajectories. RESULTS: Seven themes—identified during development and simulation testing of the CONCERN model—informed framework development. The HPM-ExpertSignals conceptual framework includes a 3-step modeling technique: (1) identify patterns of clinical behaviors from user interaction with CIS; (2) interpret patterns as proxies of an individual’s decisions, knowledge, and expertise; and (3) use patterns in predictive models for associations with outcomes. The CONCERN model differentiated at risk patients earlier than other early warning scores, lending confidence to the HPM-ExpertSignals framework. DISCUSSION: The HPM-ExpertSignals framework moves beyond transactional data analytics to model clinical knowledge, decision making, and CIS interactions, which can support predictive modeling with a focus on the rapid and frequent patient surveillance cycle. CONCLUSIONS: We propose this framework as an approach to embed clinicians’ knowledge-driven behaviors in predictions and inferences to facilitate capture of healthcare processes that are activated independently, and sometimes well before, physiological changes are apparent. |
format | Online Article Text |
id | pubmed-8200261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82002612021-06-14 Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework Rossetti, Sarah Collins Knaplund, Chris Albers, Dave Dykes, Patricia C Kang, Min Jeoung Korach, Tom Z Zhou, Li Schnock, Kumiko Garcia, Jose Schwartz, Jessica Fu, Li-Heng Klann, Jeffrey G Lowenthal, Graham Cato, Kenrick J Am Med Inform Assoc Research and Applications OBJECTIVE: There are signals of clinicians’ expert and knowledge-driven behaviors within clinical information systems (CIS) that can be exploited to support clinical prediction. Describe development of the Healthcare Process Modeling Framework to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals). MATERIALS AND METHODS: We employed an iterative framework development approach that combined data-driven modeling and simulation testing to define and refine a process for phenotyping clinician behaviors. Our framework was developed and evaluated based on the Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) predictive model to detect and leverage signals of clinician expertise for prediction of patient trajectories. RESULTS: Seven themes—identified during development and simulation testing of the CONCERN model—informed framework development. The HPM-ExpertSignals conceptual framework includes a 3-step modeling technique: (1) identify patterns of clinical behaviors from user interaction with CIS; (2) interpret patterns as proxies of an individual’s decisions, knowledge, and expertise; and (3) use patterns in predictive models for associations with outcomes. The CONCERN model differentiated at risk patients earlier than other early warning scores, lending confidence to the HPM-ExpertSignals framework. DISCUSSION: The HPM-ExpertSignals framework moves beyond transactional data analytics to model clinical knowledge, decision making, and CIS interactions, which can support predictive modeling with a focus on the rapid and frequent patient surveillance cycle. CONCLUSIONS: We propose this framework as an approach to embed clinicians’ knowledge-driven behaviors in predictions and inferences to facilitate capture of healthcare processes that are activated independently, and sometimes well before, physiological changes are apparent. Oxford University Press 2021-02-24 /pmc/articles/PMC8200261/ /pubmed/33624765 http://dx.doi.org/10.1093/jamia/ocab006 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permitsunrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research and Applications Rossetti, Sarah Collins Knaplund, Chris Albers, Dave Dykes, Patricia C Kang, Min Jeoung Korach, Tom Z Zhou, Li Schnock, Kumiko Garcia, Jose Schwartz, Jessica Fu, Li-Heng Klann, Jeffrey G Lowenthal, Graham Cato, Kenrick Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title | Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title_full | Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title_fullStr | Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title_full_unstemmed | Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title_short | Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework |
title_sort | healthcare process modeling to phenotype clinician behaviors for exploiting the signal gain of clinical expertise (hpm-expertsignals): development and evaluation of a conceptual framework |
topic | Research and Applications |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200261/ https://www.ncbi.nlm.nih.gov/pubmed/33624765 http://dx.doi.org/10.1093/jamia/ocab006 |
work_keys_str_mv | AT rossettisarahcollins healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT knaplundchris healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT albersdave healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT dykespatriciac healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT kangminjeoung healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT korachtomz healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT zhouli healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT schnockkumiko healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT garciajose healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT schwartzjessica healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT fuliheng healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT klannjeffreyg healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT lowenthalgraham healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework AT catokenrick healthcareprocessmodelingtophenotypeclinicianbehaviorsforexploitingthesignalgainofclinicalexpertisehpmexpertsignalsdevelopmentandevaluationofaconceptualframework |