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Topics
- Access to Care (1)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 20 of 20 Research Studies DisplayedMagoc T, Allen KS, McDonnell C
Generalizability and portability of natural language processing system to extract individual social risk factors.
The purpose of this study was to validate the portability and generalizability of a Natural Language Processing (NLP) method to extract individual social factors from clinical notes. More than 6 million notes were processed at the receiving site by the NLP model. The study found that approximately 13,000 and 19,000 were categorized as positive for financial insecurity and housing instability, respectively. The NLP model reflected excellent performance on the validation dataset with all measures over 0.87 for both social factors.
AHRQ-funded; HS028636.
Citation: Magoc T, Allen KS, McDonnell C .
Generalizability and portability of natural language processing system to extract individual social risk factors.
Int J Med Inform 2023 Sep; 177:105115. doi: 10.1016/j.ijmedinf.2023.105115..
Keywords: Social Determinants of Health, Electronic Health Records (EHRs), Health Information Technology (HIT)
Mehta S, Lyles CR, Rubinsky AD
Social determinants of health documentation in structured and unstructured clinical data of patients with diabetes: comparative analysis.
It is not clear how accurately Electronic health records (HER) data reflect patients' lived experience of social determinants of health (SDOH). The process of manually reviewing clinical notes to retrieve SDOH information is not feasible. The purpose of this study was to apply two tools, PatientExploreR and Electronic Medical Record Search Engine (EMERSE), to identify SDOH mappings for structured and unstructured patient data. The researchers included 4,283 adult patients receiving primary care for diabetes at UCSF. The study results revealed that SDOH may be more significant in the lives of patients with diabetes than is evident from structured data recorded on EHRs. When researchers applied EMERSE NLP rules, additional information was uncovered from patient clinical notes on problems related to social connections isolation, employment, financial insecurity, housing insecurity, food insecurity, education, and stress.
AHRQ-funded; HS026383.
Citation: Mehta S, Lyles CR, Rubinsky AD .
Social determinants of health documentation in structured and unstructured clinical data of patients with diabetes: comparative analysis.
JMIR Med Inform 2023 Aug 22; 11:e46159. doi: 10.2196/46159..
Keywords: Social Determinants of Health, Diabetes, Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT)
Linfield GH, Patel S, Ko HJ
Evaluating the comparability of patient-level social risk data extracted from electronic health records: a systematic scoping review.
This study’s objective was to evaluate how and from where social risk data are extracted from electronic health records (EHRs) for research purposes, and how observed differences may impact study generalizability. A systematic scoping review was conducted of peer-reviewed literature that used patient-level EHR data to assess 1 ± 6 social risk domains: housing, transportation, food, utilities, safety, social support/isolation. The authors found 111 of 9022 identified articles met inclusion criteria. By domain, martial/partner status was most often included, predominantly defined by marital partner status, and extracted from structured sociodemographic data. Structured housing data was extracted most from billing codes and screening tools. Across domains, data were predominantly sourced from structured fields (n = 89/111) versus unstructured free text (n = 32/111).
AHRQ-funded; HS026383.
Citation: Linfield GH, Patel S, Ko HJ .
Evaluating the comparability of patient-level social risk data extracted from electronic health records: a systematic scoping review.
Health Informatics J 2023 Jul-Sep; 29(3):14604582231200300. doi: 10.1177/14604582231200300..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Social Determinants of Health, Risk
Steeves-Reece AL, Davis MM, Hiebert Larson J
Patients' willingness to accept social needs navigation after in-person versus remote screening.
The authors conducted a cross-sectional study in order to assess possible adverse effects of screening patients remotely on patient engagement and interest in accepting social needs navigation. Participants were Medicare and Medicaid beneficiaries in the Oregon Accountable Health Communities (AHC) model. The results indicated that over 70% of participants were willing to accept help with social needs; neither the mode of screening nor interaction term were significantly associated with willingness to accept navigation assistance. The authors concluded remote screening may not adversely affect patient willingness to accept health care-based navigation for social needs.
AHRQ-funded; HS027707.
Citation: Steeves-Reece AL, Davis MM, Hiebert Larson J .
Patients' willingness to accept social needs navigation after in-person versus remote screening.
J Am Board Fam Med 2023 Apr 3;36(2):229-39. doi: 10.3122/jabfm.2022.220259R1.
Keywords: Telehealth, Screening, Health Information Technology (HIT), Social Determinants of Health
Harle CA, Wu W, Vest JR
Accuracy of electronic health record food insecurity, housing instability, and financial strain screening in adult primary care.
The objective of this study was to assess the accuracy of electronic health record–based multidomain screening questionnaires on social risk factors. Researchers used single-domain questionnaires on individual factors such as food insecurity, housing instability, and financial strain as external standards.
AHRQ-funded; HS028636.
Citation: Harle CA, Wu W, Vest JR .
Accuracy of electronic health record food insecurity, housing instability, and financial strain screening in adult primary care.
JAMA 2023 Feb 7; 329(5):423-24. doi: 10.1001/jama.2022.23631..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Screening, Social Determinants of Health
Burgermaster M, Rodriguez VA
Psychosocial-behavioral phenotyping: a novel precision health approach to modeling behavioral, psychological, and social determinants of health using machine learning.
The purpose of this study was to demonstrate a novel application of machine learning for psychosocial-behavioral phenotyping, which includes the identification of subgroups with similar combinations of psychosocial characteristics. The researchers conducted a secondary analysis of psychosocial and behavioral data from a community cohort (n = 5,883). The study found 20 psychosocial-behavioral phenotypes. Each phenotype suggested different contextual considerations for intervention design. The researchers concluded that psychosocial-behavioral phenotypes can identify possible targets of intervention.
AHRQ-funded; HS019853.
Citation: Burgermaster M, Rodriguez VA .
Psychosocial-behavioral phenotyping: a novel precision health approach to modeling behavioral, psychological, and social determinants of health using machine learning.
Ann Behav Med 2022 Nov 18;56(12):1258-71. doi: 10.1093/abm/kaac012..
Keywords: Social Determinants of Health, Health Information Technology (HIT), Research Methodologies
Wang M, Pantell MS, Gottlieb LM
Documentation and review of social determinants of health data in the EHR: measures and associated insights.
Electronic Health Records (EHRs) increasingly include designated fields to capture social determinants of health (SDOH). The investigators developed measures to characterize their use, and use of other SDOH data types, to optimize SDOH data integration. The investigators concluded for their institution, measures revealed substantial variation across data types, suggesting the need to engage in efforts such as EHR-user education and targeted workflow integration. They also concluded that measures revealed opportunities to optimize SDOH data documentation and review.
AHRQ-funded; HS026383.
Citation: Wang M, Pantell MS, Gottlieb LM .
Documentation and review of social determinants of health data in the EHR: measures and associated insights.
J Am Med Inform Assoc 2021 Nov 25;28(12):2608-16. doi: 10.1093/jamia/ocab194..
Keywords: Social Determinants of Health, Electronic Health Records (EHRs), Health Information Technology (HIT)
Fiori KP, Heller CG, Flattau A
Scaling-up social needs screening in practice: a retrospective, cross-sectional analysis of data from electronic health records from Bronx county, New York, USA.
This study describes a health system’s experience from 2018 to 2020 to scale social needs of screening of patients within a large urban primary care ambulatory network. This program took place at an academic medical center within an ambulatory network of 18 primary care practices located in the Bronx, New York. The study used electronic health records of 244,764 patients who had a clinical visit from April 2018 to 2019. The authors organized measures using the RE-AIM framework domains of reach and adoption to ascertain the number of patients who were screened and the number of providers who adopted screening. A total of 53,093 patients were screened for social needs, representing 21.7% of the patients seen. Almost one-fifth (19.6%) of patients reported at least one unmet social need, varying by both practice location and specialty within practices. Slightly more than half (51.8%) of providers screened at least one patient.
AHRQ-funded; HS026396.
Citation: Fiori KP, Heller CG, Flattau A .
Scaling-up social needs screening in practice: a retrospective, cross-sectional analysis of data from electronic health records from Bronx county, New York, USA.
BMJ Open 2021 Sep 29;11(9):e053633. doi: 10.1136/bmjopen-2021-053633..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Screening, Social Determinants of Health
Pantell MS, Adler-Milstein J, Wang MD
A call for social informatics.
This article discusses the emergence of a new subfield of health informatics, focused on the application of information technologies to capture and apply social data in conjunction with health data to advance individual and population health. Many professional organizations have endorsed screening for social determinants of health (SDOH), and the US Office of the National Coordinator for Health Information Technology has recommended increased capacity of health information technology to integrate and support use of SDOH in clinical settings.
AHRQ-funded; HS026383.
Citation: Pantell MS, Adler-Milstein J, Wang MD .
A call for social informatics.
J Am Med Inform Assoc 2020 Nov;27(11):1798-801. doi: 10.1093/jamia/ocaa175..
Keywords: Health Information Technology (HIT), Social Determinants of Health
Roberts ET, Mehrotra A
Assessment of disparities in digital access among Medicare beneficiaries and implications for telemedicine.
In this study, the investigators examined disparities in digital access (ie, access at home to technology that enables video telemedicine visits) among Medicare beneficiaries by socioeconomic and demographic characteristics. The investigators concluded that the proportion of beneficiaries who lacked digital access was higher among those with low socioeconomic status, those 85 years or older, and in communities of color.
AHRQ-funded; HS026727.
Citation: Roberts ET, Mehrotra A .
Assessment of disparities in digital access among Medicare beneficiaries and implications for telemedicine.
JAMA Intern Med 2020 Oct;180(10):1386-89. doi: 10.1001/jamainternmed.2020.2666..
Keywords: Elderly, Medicare, Telehealth, Health Information Technology (HIT), Disparities, Access to Care, Social Determinants of Health, Low-Income, Racial and Ethnic Minorities
Cohen DJ, Wyte-Lake T, Dorr DA
Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs.
The authors sought to identify the unmet information needs of clinical teams delivering care to patients with complex medical, social, and economic needs, and to propose principles for redesigning electronic health records (EHR) to address these needs. They concluded that developing EHR tools that are simple, accessible, easy to use, and able to be updated by a range of professionals is critical. They recommended that the identified information needs and design principles inform developers and implementers working in community health centers and other settings where complex patients receive care.
AHRQ-funded; HS023324.
Citation: Cohen DJ, Wyte-Lake T, Dorr DA .
Unmet information needs of clinical teams delivering care to complex patients and design strategies to address those needs.
J Am Med Inform Assoc 2020 May;27(5):690-99. doi: 10.1093/jamia/ocaa010..
Keywords: Healthcare Delivery, Teams, Electronic Health Records (EHRs), Health Information Technology (HIT), Social Determinants of Health, Community-Based Practice, Primary Care
De 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
Cottrell EK, Gold R, Likumahuwa S
Using health information technology to bring social determinants of health into primary care: a conceptual framework to guide research.
The investigators recently proposed a conceptual framework to illustrate how health information technology can be used to bring social determinants of health information into primary care. In this paper, they describe how they are putting this conceptual model into practice within the OCHIN network of community health centers by highlighting examples of ongoing research, identifying knowledge gaps, and outlining a roadmap of future research to move the field forward.
Citation: Cottrell EK, Gold R, Likumahuwa S .
Using health information technology to bring social determinants of health into primary care: a conceptual framework to guide research.
AHRQ-funded; 233201500020I..
Keywords: Health Information Technology (HIT), Primary Care, Research Methodologies, Social Determinants of Health
Graetz I, Huang J, Brand RJ
Bridging the digital divide: mobile access to personal health records among patients with diabetes.
The authors examined personal health record (PHR) use through a computer-based Web browser or mobile device. They found that mobile-ready PHRs may increase access among patients facing a digital divide in computer use, disproportionately reaching racial/ethnic minorities and lower socioeconomic status patients. They recommend continued efforts to increase equitable access to PHRs among patients with chronic conditions.
AHRQ-funded; HS015280.
Citation: Graetz I, Huang J, Brand RJ .
Bridging the digital divide: mobile access to personal health records among patients with diabetes.
Am J Manag Care 2018 Jan;24(1):43-48..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diabetes, Racial and Ethnic Minorities, Social Determinants of Health
Perez SL, Kravitz RL, Bell RA
Characterizing internet health information seeking strategies by socioeconomic status: a mixed methods approach.
The authors investigated how the Internet is used to obtain health-related information and how individuals with differing socioeconomic resources navigate it when presented with a health decision. Their findings suggest that individuals with different levels of socioeconomic status vary in the heuristics and search patterns they rely upon to direct their searches and that the influence and use of credible information in the process of making a decision is associated with education and prior experiences with healthcare services.
AHRQ-funded; HS022236.
Citation: Perez SL, Kravitz RL, Bell RA .
Characterizing internet health information seeking strategies by socioeconomic status: a mixed methods approach.
BMC Med Inform Decis Mak 2016 Aug 9;16:107. doi: 10.1186/s12911-016-0344-x.
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Keywords: Education: Patient and Caregiver, Health Information Technology (HIT), Social Determinants of Health, Web-Based
Ancker JS, Hafeez B, Kaushal R
Socioeconomic disparities in adoption of personal health records over time.
The authors sought to track personal health record (PHR) adoption and differences by sociodemographic group over time. Using data from the Empire State Poll, they found that during a 4-year period in which federal policies incentivized medical organizations to give medical record access to patients through PHRs and electronic portals, rates of PHR use increased rapidly in all sociodemographic groups, but with a digital divide remaining, linked to Hispanic ethnicity and lower income.
AHRQ-funded; HS021531.
Citation: Ancker JS, Hafeez B, Kaushal R .
Socioeconomic disparities in adoption of personal health records over time.
Am J Manag Care 2016 Aug;22(8):539-40.
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Keywords: Disparities, Electronic Health Records (EHRs), Health Information Technology (HIT), Racial and Ethnic Minorities, Social Determinants of Health
Heisler M, Choi H, Palmisano G
Comparison of community health worker-led diabetes medication decision-making support for low-income Latino and African American adults with diabetes using e-health tools versus print materials: a randomized, controlled trial.
This study compared outcomes between community health worker (CHW) use of a tailored, interactive, Web-based, tablet computer-delivered tool specifically developed for the study and use of printed educational materials. In a population of low-income Latino and African American adults with diabetes and relatively low levels of formal education, participants in both CHW-led interventions reported mostly similar improvements in outcomes over 3 months.
AHRQ-funded; HS019256
Citation: Heisler M, Choi H, Palmisano G .
Comparison of community health worker-led diabetes medication decision-making support for low-income Latino and African American adults with diabetes using e-health tools versus print materials: a randomized, controlled trial.
Ann Intern Med. 2014 Nov 18;161(10 Suppl):S13-22. doi: 10.7326/m13-3012..
Keywords: Health Information Technology (HIT), Diabetes, Decision Making, Outcomes, Social Determinants of Health