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Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center

OBJECTIVE: To describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR). METHODS: We employed the collection of the PRAPARE tool i...

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Autores principales: Howell, Carrie R, Bradley, Heather, Zhang, Li, Cleveland, John D, Long, Dustin, Horton, Trudi, Krantz, Olivia, Mugavero, Michael J, Williams, Winter L, Amerson, Alesha, Cherrington, Andrea L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214080/
https://www.ncbi.nlm.nih.gov/pubmed/37252259
http://dx.doi.org/10.1177/20552076231176652
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author Howell, Carrie R
Bradley, Heather
Zhang, Li
Cleveland, John D
Long, Dustin
Horton, Trudi
Krantz, Olivia
Mugavero, Michael J
Williams, Winter L
Amerson, Alesha
Cherrington, Andrea L
author_facet Howell, Carrie R
Bradley, Heather
Zhang, Li
Cleveland, John D
Long, Dustin
Horton, Trudi
Krantz, Olivia
Mugavero, Michael J
Williams, Winter L
Amerson, Alesha
Cherrington, Andrea L
author_sort Howell, Carrie R
collection PubMed
description OBJECTIVE: To describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR). METHODS: We employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR. RESULTS: Assessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH. CONCLUSIONS: Integrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter.
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spelling pubmed-102140802023-05-27 Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center Howell, Carrie R Bradley, Heather Zhang, Li Cleveland, John D Long, Dustin Horton, Trudi Krantz, Olivia Mugavero, Michael J Williams, Winter L Amerson, Alesha Cherrington, Andrea L Digit Health Original Research OBJECTIVE: To describe the real-world deployment of a tool, the Protocol for Responding to and Assessing Patients’ Assets, Risks, and Experiences (PRAPARE), to assess social determinants of health (SDoH) in an electronic medical record (EMR). METHODS: We employed the collection of the PRAPARE tool in the EMR of a large academic health system in the ambulatory clinic and emergency department setting. After integration, we evaluated SDoH prevalence, levels of missingness, and data anomalies to inform ongoing collection. We summarized responses using descriptive statistics and hand-reviewed data text fields and patterns in the data. Data on patients who were administered with the PRAPARE from February to December 2020 were extracted from the EMR. Patients missing ≥ 12 PRAPARE questions were excluded. Social risks were screened using the PRAPARE. Information on demographics, admittance status, and health coverage were extracted from the EMR. RESULTS: Assessments with N = 6531 were completed (mean age 54 years, female (58.6%), 43.8% Black). Missingness ranged from 0.4% (race) to 20.8% (income). Approximately 6% of patients were homeless; 8% reported housing insecurity; 1.4% reported food needs; 14.6% had healthcare needs; 8.4% needed utility assistance; and 5% lacked transportation related to medical care. Emergency department patients reported significantly higher proportions of suboptimal SDoH. CONCLUSIONS: Integrating the PRAPARE assessment in the EMR provides valuable information on SDoH amenable to intervention, and strategies are needed to increase accurate data collection and to improve the use of data in the clinical encounter. SAGE Publications 2023-05-22 /pmc/articles/PMC10214080/ /pubmed/37252259 http://dx.doi.org/10.1177/20552076231176652 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Howell, Carrie R
Bradley, Heather
Zhang, Li
Cleveland, John D
Long, Dustin
Horton, Trudi
Krantz, Olivia
Mugavero, Michael J
Williams, Winter L
Amerson, Alesha
Cherrington, Andrea L
Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title_full Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title_fullStr Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title_full_unstemmed Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title_short Real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
title_sort real-world integration of the protocol for responding to and assessing patients’ assets, risks, and experiences tool to assess social determinants of health in the electronic medical record at an academic medical center
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10214080/
https://www.ncbi.nlm.nih.gov/pubmed/37252259
http://dx.doi.org/10.1177/20552076231176652
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