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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 4 of 4 Research Studies DisplayedDe Marchis EH, Hessler D, Fichtenberg C
Part I: A quantitative study of social risk screening acceptability in patients and caregivers.
This study evaluated patient and caregiver acceptability of social risk screening. Adult patients and the adult caregivers of pediatric patients were recruited from primary care clinics and emergency departments across nine states for a survey; survey items included the Center for Medicare and Medicaid Innovation Accountable Health Communities' social risk screening tool and questions about the appropriateness of screening and including social risk data in electronic health records. Results showed that a strong majority of surveyed patients and caregivers found social risk screening to be appropriate. Most also felt comfortable including social risk data in electronic health records. The researchers conclude that lack of patient acceptability is unlikely to be a major implementation barrier.
AHRQ-funded; HS026664.
Citation: De Marchis EH, Hessler D, Fichtenberg C .
Part I: A quantitative study of social risk screening acceptability in patients and caregivers.
Am J Prev Med 2019 Dec;57(6 Suppl 1):S25-s37. doi: 10.1016/j.amepre.2019.07.010..
Keywords: Children/Adolescents, Caregiving, Screening, Social Determinants of Health, Electronic Health Records (EHRs), Health Information Technology (HIT)
Cottrell EK, Dambrun K, Cowburn S
Variation in electronic health record documentation of social determinants of health across a national network of community health centers.
This paper described the adoption of an electronic health record-based social determinants of health screening tool in a national network of more than 100 community health centers. The investigators concluded that screening documentation patterns varied widely across the network of community health centers. The investigators suggested that despite the growing national emphasis on the importance of screening for social determinants of health, the findings suggested that simply activating electronic health record tools for social determinants of health screening did not lead to widespread adoption.
AHRQ-funded; HS022651.
Citation: Cottrell EK, Dambrun K, Cowburn S .
Variation in electronic health record documentation of social determinants of health across a national network of community health centers.
Am J Prev Med 2019 Dec;57(6 Suppl 1):S65-s73. doi: 10.1016/j.amepre.2019.07.014..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Social Determinants of Health
Trinacty CM, LaWall E, Ashton M
Adding social determinants in the electronic health record in clinical care in Hawai'i: supporting community-clinical linkages in patient care.
Given its distinctive history, culture, and location, Hawai'i has unique social factors impacting population health. Local health systems are striving to address these issues to meet their patients' health needs. Yet the evidence on precisely how health care systems and communities may work together to achieve these goals are limited both generally and specifically in the Hawai'i context. This article described real-world efforts by 3 local health care delivery systems that integrated the identification of social needs into clinical care using the electronic health record (EHR).
AHRQ-funded; HS023185.
Citation: Trinacty CM, LaWall E, Ashton M .
Adding social determinants in the electronic health record in clinical care in Hawai'i: supporting community-clinical linkages in patient care.
Hawaii J Med Public Health 2019 Jun;78(6 Suppl 1):46-51..
Keywords: Social Determinants of Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Community-Based Practice, Healthcare Delivery, Vulnerable Populations
Bucher BT, Shi J, Pettit RJ
Determination of marital status of patients from structured and unstructured electronic healthcare data.
This paper describes a robust method to determine the marital status of patients, which is included as a Social Determinant of Health and considered a key driver of health care utilization. A robust method to determine marital status using structured and unstructured electronic healthcare data was developed using data from a single US academic institution. A natural language processing (NLP) pipeline was developed and validated. Performance was compared against two baseline methods: a machine learning n-gram model and structured data from the electronic health record. Overall the NLP engine had excellent to superior performance compared with the other models.
AHRQ-funded; HS025776.
Citation: Bucher BT, Shi J, Pettit RJ .
Determination of marital status of patients from structured and unstructured electronic healthcare data.
AMIA Annu Symp Proc 2020 Mar 4;2019:267-74..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Social Determinants of Health, Healthcare Utilization