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Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report
BACKGROUND: Clinical decision support (CDS) has the potential to improve clinical decision-making consistent with evidence-based care. CDS can be designed to save health care providers time and help them provide safe and personalized analgesic prescribing. OBJECTIVE: The aim of this report is to des...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664010/ https://www.ncbi.nlm.nih.gov/pubmed/37934572 http://dx.doi.org/10.2196/45636 |
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author | Rindal, D Brad Pasumarthi, Dhavan Prasad Thirumalai, Vijayakumar Truitt, Anjali R Asche, Stephen E Worley, Donald C Kane, Sheryl M Gryczynski, Jan Mitchell, Shannon G |
author_facet | Rindal, D Brad Pasumarthi, Dhavan Prasad Thirumalai, Vijayakumar Truitt, Anjali R Asche, Stephen E Worley, Donald C Kane, Sheryl M Gryczynski, Jan Mitchell, Shannon G |
author_sort | Rindal, D Brad |
collection | PubMed |
description | BACKGROUND: Clinical decision support (CDS) has the potential to improve clinical decision-making consistent with evidence-based care. CDS can be designed to save health care providers time and help them provide safe and personalized analgesic prescribing. OBJECTIVE: The aim of this report is to describe the development of a CDS system designed to provide dentists with personalized pain management recommendations to reduce opioid prescribing following extractions. The use of CDS is also examined. METHODS: This study was conducted in HealthPartners, which uses an electronic health record (EHR) system that integrates both medical and dental information upon which the CDS application was developed based on SMART (Substitutable Medical Applications and Reusable Technologies) on FHIR (Fast Healthcare Interoperability Resources). The various tools used to bring relevant medical conditions, medications, patient history, and other relevant data into the CDS interface are described. The CDS application runs a drug interaction algorithm developed by our organization and provides patient-specific recommendations. The CDS included access to the state Prescription Monitoring Program database. IMPLEMENTATION (RESULTS): The pain management CDS was implemented as part of a study examining opioid prescribing among patients undergoing dental extraction procedures from February 17, 2020, to May 14, 2021. Provider-level use of CDS at extraction encounters ranged from 0% to 87.4% with 12.1% of providers opening the CDS for no encounters, 39.4% opening the CDS for 1%-20% of encounters, 36.4% opening it for 21%-50% of encounters, and 12.1% opening it for 51%-87% of encounters. CONCLUSIONS: The pain management CDS is an EHR-embedded, provider-facing tool to help dentists make personalized pain management recommendations following dental extractions. The SMART on FHIR–based pain management CDS adapted well to the point-of-care dental setting and led to the design of a scalable CDS tool that is EHR vendor agnostic. TRIAL REGISTRATION: ClinicalTrials.gov NCT03584789; https://clinicaltrials.gov/study/NCT03584789 |
format | Online Article Text |
id | pubmed-10664010 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-106640102023-11-07 Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report Rindal, D Brad Pasumarthi, Dhavan Prasad Thirumalai, Vijayakumar Truitt, Anjali R Asche, Stephen E Worley, Donald C Kane, Sheryl M Gryczynski, Jan Mitchell, Shannon G JMIR Med Inform Implementation Report BACKGROUND: Clinical decision support (CDS) has the potential to improve clinical decision-making consistent with evidence-based care. CDS can be designed to save health care providers time and help them provide safe and personalized analgesic prescribing. OBJECTIVE: The aim of this report is to describe the development of a CDS system designed to provide dentists with personalized pain management recommendations to reduce opioid prescribing following extractions. The use of CDS is also examined. METHODS: This study was conducted in HealthPartners, which uses an electronic health record (EHR) system that integrates both medical and dental information upon which the CDS application was developed based on SMART (Substitutable Medical Applications and Reusable Technologies) on FHIR (Fast Healthcare Interoperability Resources). The various tools used to bring relevant medical conditions, medications, patient history, and other relevant data into the CDS interface are described. The CDS application runs a drug interaction algorithm developed by our organization and provides patient-specific recommendations. The CDS included access to the state Prescription Monitoring Program database. IMPLEMENTATION (RESULTS): The pain management CDS was implemented as part of a study examining opioid prescribing among patients undergoing dental extraction procedures from February 17, 2020, to May 14, 2021. Provider-level use of CDS at extraction encounters ranged from 0% to 87.4% with 12.1% of providers opening the CDS for no encounters, 39.4% opening the CDS for 1%-20% of encounters, 36.4% opening it for 21%-50% of encounters, and 12.1% opening it for 51%-87% of encounters. CONCLUSIONS: The pain management CDS is an EHR-embedded, provider-facing tool to help dentists make personalized pain management recommendations following dental extractions. The SMART on FHIR–based pain management CDS adapted well to the point-of-care dental setting and led to the design of a scalable CDS tool that is EHR vendor agnostic. TRIAL REGISTRATION: ClinicalTrials.gov NCT03584789; https://clinicaltrials.gov/study/NCT03584789 JMIR Publications 2023-11-07 /pmc/articles/PMC10664010/ /pubmed/37934572 http://dx.doi.org/10.2196/45636 Text en ©D Brad Rindal, Dhavan Prasad Pasumarthi, Vijayakumar Thirumalai, Anjali R Truitt, Stephen E Asche, Donald C Worley, Sheryl M Kane, Jan Gryczynski, Shannon G Mitchell. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 07.11.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Implementation Report Rindal, D Brad Pasumarthi, Dhavan Prasad Thirumalai, Vijayakumar Truitt, Anjali R Asche, Stephen E Worley, Donald C Kane, Sheryl M Gryczynski, Jan Mitchell, Shannon G Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title | Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title_full | Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title_fullStr | Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title_full_unstemmed | Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title_short | Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report |
title_sort | clinical decision support to reduce opioid prescriptions for dental extractions using smart on fhir: implementation report |
topic | Implementation Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10664010/ https://www.ncbi.nlm.nih.gov/pubmed/37934572 http://dx.doi.org/10.2196/45636 |
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