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Cited by 6Electronic Health Records SystemsMedical Coding and Health InformationNursing Diagnosis and Documentation

The relationship between perceptions of electronic health record usability and clinical importance of social and environmental determinants of health on provider documentation

Open access
Sood, Natasha, Stetter, Christy, Kunselman, Allen, Jasani, Sona·2024·PLOS Digital Health
DOI 10.1371/journal.pdig.0000428PMC PMC10783763
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Abstract

Social and environmental determinants of health (SEDH) data in the electronic health record (EHR) can be inaccurate and incomplete. Providers are in a unique position to impact this issue as they both obtain and enter this data, however, the variability in screening and documentation practices currently limits the ability to mobilize SEDH data for secondary uses. This study explores whether providers’ perceptions of clinical importance of SEDH or EHR usability influenced data entry by analyzing two relationships: (1) provider charting behavior and clinical consideration of SEDH and (2) provider charting behavior and ease of EHR use in charting. We performed a cross-sectional study using an 11-question electronic survey to assess self-reported practices related to clinical consideration of SEDH elements, EHR usability and SEDH documentation of all staff physicians, identified using administrative listserves, at Penn State Health Hershey Medical Center during September to October 2021. A total of 201 physicians responded to and completed the survey out of a possible 2,478 identified staff physicians (8.1% response rate). A five-point Likert scale from “never” to “always” assessed charting behavior and clinical consideration. Responses were dichotomized as consistent/inconsistent and vital/not vital respectively. EHR usability was assessed as “yes” or “no” responses. Fisher’s exact tests assessed the relationship between charting behavior and clinical consideration and to compare charting practices between different SEDHs. Cumulative measures were constructed for consistent charting and ease of charting. A generalized linear mixed model (GLMM) compared SDH and EDH with respect to each cumulative measure and was quantified using odds ratios (OR) and 95% confidence intervals (CI). Our results show that provider documentation frequency of an SEDH is associated with perceived clinical utility as well as ease of charting and that providers were more likely to consistently chart on SDH versus EDH. Nuances in these relationships did exist with one notable example comparing the results of smoking (SDH) to infectious disease outbreaks (EDH). Despite similar percentages of physicians reporting that both smoking and infectious disease outbreaks are vital to care, differences in charting consistency and ease of charting between these two were seen. Taken as a whole, our results suggest that SEDH quality optimization efforts cannot consider physician perceptions and EHR usability as siloed entities and that EHR design should not be the only target for intervention. The associations found in this study provide a starting point to understand the complexity in how clinical utility and EHR usability influence charting consistency of each SEDH element, however, further research is needed to understand how these relationships intersect at various levels in the SEDH data optimization process.

AI snapshot

Written from the paper’s full text.

TL;DR

In a cross-sectional survey of 201 physicians at Penn State Health Hershey Medical Center, self-reported SEDH charting frequency was associated with perceived clinical importance and, for some elements, ease of EHR charting. Providers were much more likely to consistently chart social determinants of health (SDH) than environmental determinants of health (EDH).

Key findings

  • Of 2,478 identified staff physicians, 201 completed the survey (8.1% response rate); 84% were attendings and 63% practiced both inpatient and outpatient medicine.
  • Smoking was the only SDH consistently charted by at least half of physicians (78%); 9 of 13 SDHs were considered vital by at least half, with smoking highest at 87%. For EDHs, infectious disease outbreaks were most consistently charted (31%) and most often considered vital (80%), but only 16.4% reported it was easy to chart.
  • Perceived clinical importance was significantly associated with consistent charting for all 13 SDHs, but ease of charting was significantly associated only for childcare, employment, insurance, smoking, and refugee status. For EDHs, perceived importance was significantly associated with charting only for infectious disease outbreaks and access to basic appliances; ease of charting was significant only for infectious disease outbreaks.
  • The odds of consistently charting at least 1 SDH were 14 times the odds of charting at least 1 EDH (OR = 14.8, 95% CI 8.8–24.9, p < .001); the odds of easily charting at least 1 SDH were 10 times the odds of easily charting at least 1 EDH (OR = 10.8, 95% CI 6.7–17.5, p < .001).

Methods

  • Cross-sectional electronic survey of all staff physicians at Penn State Health Hershey Medical Center during September–October 2021, distributed anonymously via administrative listservs; 201 of 2,478 physicians completed the 11-question REDCap survey.
  • Charting behavior and clinical consideration were assessed on a five-point Likert scale and dichotomized as consistent/inconsistent and vital/not vital; EHR usability was assessed as yes/no for whether the EHR made documenting each SEDH element easy.
  • Fisher’s exact tests assessed relationships between charting behavior and clinical consideration, and cumulative measures were compared for SDH versus EDH using a generalized linear mixed model with a binary distribution, logit link, fixed type effect, and random physician effect; results reported as odds ratios and 95% confidence intervals.

Limitations

  • The authors report a low overall response rate of 8%, possible non-response bias, and inability to stratify analyses by medical specialty; they also note the study was conducted at a single academic medical center, limiting generalizability.
  • The authors state they could not correlate physician responses with health system-level SEDH data quality or patient outcomes because of low structured documentation modalities and inability to use natural language processing analytics.
  • Evident from the text: charting behavior was self-reported rather than extracted from actual EHR documentation, and the cross-sectional design cannot establish causality; the survey also occurred during the COVID-19 pandemic, which the authors suggest may have influenced participation and documentation perceptions.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1371/journal.pdig.0000428

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

21 of 53 cited sources checked · 10 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    SEDH data in the electronic health record can be inaccurate and incomplete.

    “Social and environmental determinants of health (SEDH) data in the electronic health record (EHR) can be inaccurate and incomplete.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [28] LA Cook, 2021, The quality of social determinants data in the electronic health record: a systematic review, J Am Med Inform Assoc source
  • Premisecitation

    The usability of EHR data is generally poor.

    “consistent with the notion that the usability of EHR data is generally poor [29,30].”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [29] N Wiebe, 2019, Evaluation of interventions to improve inpatient hospital documentation within electronic health records: a systematic review, J Am Med Inform Assoc source
    • cites [30] AA Dhavle, 2016, Analysis of Prescribers’ Notes in Electronic Prescriptions in Ambulatory Practice, JAMA Intern Med source

      The paper’s discussion (section labeled “Downloaded From,” page not specified) calls for better EHR and e-prescribing interface design to reduce inappropriate use of free-text prescription notes. That supports a specific usability concern, but the study does not establish that EHR data are generally poor in usability. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • Premisecitation

    Inaccuracy and incompleteness have been identified with determinants of health data.

    “issues including inaccuracy and incompleteness have been identified with determinants of health data [28]”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [28] LA Cook, 2021, The quality of social determinants data in the electronic health record: a systematic review, J Am Med Inform Assoc source
  • Premisecitation

    Those who care for vulnerable populations or routinely use social care services are more likely to engage with EHR determinants data.

    “those who care for vulnerable populations or routinely use social care services are more likely to engage with EHR determinants data [34].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [34] BE Iott, 2022, Physician awareness of social determinants of health documentation capability in the electronic health record, J Am Med Inform Assoc source

      The Results report greater awareness of EHR social-determinants documentation capability among physicians at community health centers, and the Discussion says physicians frequently involved in screening and social care may be more aware. The paper measures awareness, however, not whether these physicians are more likely to engage with or use EHR determinants data; it also presents the link to frequent social care work as a possibility. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Premisecitation

    Negative EHR user experiences in general may result in partial data capture.

    “negative EHR user experiences in general may result in partial data capture [29,32,33].”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [29] N Wiebe, 2019, Evaluation of interventions to improve inpatient hospital documentation within electronic health records: a systematic review, J Am Med Inform Assoc source
    • cites [32] AJ Johnson, 2009, Cohort study of structured reporting compared with conventional dictation, Radiology source
    • cites [33] C Lanier, 2018, What factors influence the use of electronic health records during the first 10 minutes of the clinical encounter?, Int J Gen Med source

      The Introduction (page not available) says physicians more readily accept EHRs after positive experiences, and the Discussion says EHR use can vary with expectations and experiences. Neither passage establishes that negative user experiences result in partial data capture; the study measured EHR use during encounters, not completeness of captured data. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. 18
  • May combine two claims. 13

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Structured data entry can facilitate data use and exchange.

    “Structured data entry can facilitate data use and exchange [13]”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [13] TK Fraze, 2019, Prevalence of Screening for Food Insecurity, Housing Instability, Utility Needs, Transportation Needs, and Interpersonal Violence by US Physician Practices and Hospitals, JAMA Netw Open source

      The Discussion (page unavailable in our copy) says new diagnostic codes could let physicians and hospitals document patients’ social needs so payers can refer patients to resources. This supports a specific example of coded information being used across organizations, but the paper does not address the broader claim about structured data entry facilitating data use and exchange. (LLM, conf=0.72)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Systematic screening and documentation of health determinants can directly impact patient care and research efforts.

    “Systematic screening and documentation of health determinants can directly impact patient care [1–8] and research efforts [1,5].”
    Quote in the paperSubstantial claim2 of 8 sources checked
    • cites [1] BG Patra, 2021, Extracting social determinants of health from electronic health records using natural language processing: a systematic review, J Am Med Inform Assoc source
    • cites [2] M Chen, 2020, Social determinants of health in electronic health records and their impact on analysis and risk prediction: A systematic review, J Am Med Inform Assoc source
    • cites [3] Committee on Integrating Primary Care and Public Health; Board on Population Health and Public Health Practice; Institute of Medicine. Primary Care and Public Health: Exploring Integration to Improve Population Health. Washington (DC): National Academies Press (US); 2012 Mar 28.

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [4] Centers for Disease Control and Prevention. Social Determinants of Health at CDC [Internet]. Atlanta,GA. Centers for Disease Control and Prevention; 2020 [updated 2022]. https://www.cdc.gov/about/sdoh/index.html.

      Not checked in the free run.

    • cites [5] EK Cottrell, 2019, Variation in Electronic Health Record Documentation of Social Determinants of Health Across a National Network of Community Health Centers, Am J Prev Med source
    • cites [6] JR Vest, 2019, Prediction of emergency department revisits using area-level social determinants of health measures and health information exchange information, Int J Med Inform source
    • cites [7] JR Vest, 2019, Impact of Risk Stratification on Referrals and Uptake of Wraparound Services That Address Social Determinants: A Stepped Wedged Trial, Am J Prev Med source
    • cites [8] DJ Feller, 2018, Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment, J Acquir Immune Defic Syndr source

      The Results and Discussion (pages not provided) show that documented social and behavioral risk factors improved an HIV risk-prediction model, supporting a benefit for research. The Conclusion proposes using predictive analytics to improve HIV screening, but describes an anticipated clinical benefit, not a demonstrated direct impact on patient care. The paper does not assess systematic screening and documentation of health determinants generally. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Only 15.6% of physician practices and 24.4% of hospitals perform comprehensive health determinants screening.

    “only 15.6% of physician practices and 24.4% of hospitals performing comprehensive health determinants screening per The National Survey of Healthcare Organizations and Systems Responses (2017–2018) [13].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [13] TK Fraze, 2019, Prevalence of Screening for Food Insecurity, Housing Instability, Utility Needs, Transportation Needs, and Interpersonal Violence by US Physician Practices and Hospitals, JAMA Netw Open source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation

    This finding is congruent with SEDH data quality issues noted in the literature.

    “This finding is congruent with SEDH data quality issues noted in the literature [28–30].”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites [28] LA Cook, 2021, The quality of social determinants data in the electronic health record: a systematic review, J Am Med Inform Assoc source
    • cites [29] N Wiebe, 2019, Evaluation of interventions to improve inpatient hospital documentation within electronic health records: a systematic review, J Am Med Inform Assoc source
    • cites [30] AA Dhavle, 2016, Analysis of Prescribers’ Notes in Electronic Prescriptions in Ambulatory Practice, JAMA Intern Med source

      The Abstract reports data-quality problems in electronic prescriptions: inappropriate free-text content and patient directions that conflict with structured fields. That supports the general point that electronic health data can have quality issues, but our copy does not identify these findings as SEDH-specific. (LLM, conf=0.78)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    In general, respondents reported that SDHs were difficult to chart in the EHR; smoking and insurance were reported as easy to chart by 59% and 47% of physicians respectively, and rates for the other 11 SDHs were less than 30%.

    “In general, respondents reported that SDHs were difficult to chart in the EHR. Smoking and insurance were reported as easy to chart by 59% and 47% of physicians respectively; rates for the other 11 SDHs were less than 30% (Fig 1).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • May combine two claims.

    Findingown data

    Of the 13 SDHs assessed, 9 were reported as vital to patient care by at least half of physicians, with smoking reported by the highest percentage (87%).

    “Of the 13 SDHs assessed, 9 were reported as vital to their patient care by at least half of physicians with the SDH of smoking reported by the highest percentage of physicians (87%) (Fig 1.).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • May combine two claims.

    Findingown data

    Of the 7 EDHs assessed, infectious disease outbreaks was consistently charted on by the most physicians (31%), which was far less than that for the SDH of smoking (78%).

    “Of the 7 EDHs assessed in the survey, the EDH of infectious disease outbreaks was consistently charted on by the most physicians (31%) (Fig 2). This, however, was far less than that for the SDH of smoking (78%).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • May combine two claims.

    Findingown data

    Of the 7 EDHs assessed, 3 were reported as vital to patient care by at least half of physicians; infectious disease had the highest percentage (80%), followed by access to basic appliances (59%) and household pollution (59%).

    “Of the 7 EDHs assessed, 3 were reported as vital to patient care by at least half of physicians (Fig 2). Infectious disease had the highest percentage of physicians who perceived this EDH as vital to patient care (80%) followed by access to basic appliances (59%) and household pollution (59%).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • May combine two claims.

    Findingown data

    The EDH of infectious disease outbreaks was reported as easy to chart by only 16.4% of physicians; rates for the other 6 EDHs were all less than 10%.

    “The EDH of infectious disease outbreaks was reported as easy to chart by only 16.4% of physicians; rates for the other 6 EDHs were all less than 10% (Fig 2).”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • May combine two claims.

    Findingown data

    Despite similar percentages of physicians reporting that both smoking and infectious disease outbreaks are vital to care, differences in charting consistency and ease of charting between these two were seen.

    “Despite similar percentages of physicians reporting that both smoking and infectious disease outbreaks are vital to care, differences in charting consistency and ease of charting between these two were seen.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The GLMM used a random physician effect to account for correlation between the SDH and EDH responses per physician.

    “The GLMM used a binary distribution with a logit link and consisted of a fixed type effect (SDH vs. EDH) and random physician effect to account for correlation between the SDH and EDH responses per physician.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Whether data quality issues are related to incomplete entry, incomplete capture or a lack of universal guidelines is unclear from the existing literature.

    “Whether data quality issues are related to incomplete entry, incomplete capture or a lack of universal guidelines is unclear from the existing literature.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Data quality relies on accuracy and completeness.

    “Data quality relies on accuracy and completeness [27]”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [27] B Ehsani-Moghaddam, 2021, Data quality in healthcare: A report of practical experience with the Canadian Primary Care Sentinel Surveillance Network data, Health Inf Manag source

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Premisenone given

    SEDH data quality and mobilization depends on collection and storage, two tasks performed by providers whose engagement with SEDH data may be modifiable.

    “SEDH data quality and mobilization depends on collection and storage, two tasks performed by providers whose engagement with SEDH data may be modifiable.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductreasoning

    The study relied on self-reported charting behavior because routine structured data entry of SEDH elements was limited at the study institution and to not exclude any possible provider SEDH documentation modality.

    “We relied on self-reported charting behavior because routine structured data entry of SEDH elements was limited at the study institution and because we did not want to exclude any possible provider SEDH documentation modality.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Study design and conductnone given

    Systematized use of electronic screening forms, such as PRAPARE, was not a standardized practice at the study institution.

    “Systematized use of electronic screening forms, such as PRAPARE, was not a standardized practice at the study institution”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The study was approved by the Institutional Review Board as exempt.

    “The Institutional Review Board (IRB) at the study institution granted exempt status for this research (#STUDY00018033).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Study design and conductreasoning

    Regardless of possible variation in documentation method, a physician would have been able to use their same chosen method to chart on all SEDHs.

    “Regardless of this possible variation (using structured data entry or an unstructured form like a clinical note) a physician would have been able to use their same chosen method to chart on all SEDHs.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Provider SEDH documentation may vary between different physicians.

    “and provider SEDH documentation may vary between different physicians.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The survey was distributed by non-study team administrative personnel to ensure anonymous participation.

    “Non-study team administrative personnel in these offices distributed the survey electronically using staff physician institutional email addresses via these administrative listservs to ensure anonymous participation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Structured data entry may negatively impact clinical workflows.

    “Structured data entry may negatively impact clinical workflows [31]”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [31] RA Bush, 2017, Structured Data Entry in the Electronic Medical Record: Perspectives of Pediatric Specialty Physicians and Surgeons, J Med Syst source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    The associations found in this study provide a starting point to understand the complexity in how clinical utility and EHR usability influence charting consistency of each SEDH element.

    “The associations found in this study provide a starting point to understand the complexity in how clinical utility and EHR usability influence charting consistency of each SEDH element”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: Self-reported charting behavior accurately reflects actual documentation behavior.
    • Rests on an assumption: The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.
    • Rests on an assumption: The 201 respondents are representative of all staff physicians at the study institution.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    A total of 2,478 staff physicians were identified, and 201 participants completed the survey (8.1% response rate) and were included in the analysis.

    “A total of 2,478 staff physicians (1,800 attending physicians and 678 residents/fellows) were identified using an administrative listserv at the study institution during the project timeframe. Of this total, 201 participants completed the survey (8.1% response rate) and were included in the analysis.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationown data

    Our results provide a starting point to understand how clinical utility and EHR usability influence physician documentation practices for each individual SEDH element.

    “Our results provide a starting point to understand how clinical utility and EHR usability influence physician documentation practices for each individual SEDH element.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Provider documentation frequency of an SEDH is associated with clinical utility as well as ease of charting.

    “In conclusion, our study results show that provider documentation frequency of an SEDH is associated with clinical utility as well as ease of charting”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    The study had a low overall response rate of 8%, which could lead to non-response bias.

    “We had a low overall response rate of 8% which could lead to non-response bias.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    The self-reported data in our study allowed us to assess for all possible types of charting behaviors and not only rely on discrete elements from structured data entry.

    “One advantage of the self-reported data in our study, however, was that we were able to assess for all possible types of charting behaviors and not only rely on discrete elements from structured data entry.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    Physician responses seen in our study corroborated patterns seen in the literature.

    “Furthermore, physician responses seen in our study corroborated patterns seen in the literature.”
    Quote in the paperNot a substantial claim
28 of 28

  • The paper relies on this without support.

    Self-reported charting behavior accurately reflects actual documentation behavior.

    “We relied on self-reported charting behavior because routine structured data entry of SEDH elements was limited at the study institution and because we did not want to exclude any possible provider SEDH documentation modality.”

  • The paper relies on this without support.

    The 11-question survey validly measures clinical consideration, EHR usability, and charting behavior.

    “A five-point Likert scale from “never” to “always” was used to assess participant charting behavior and clinical consideration as specifically related to the participant’s own clinical practice. EHR usability was assessed by asking participants to answer “yes” or “no” to whether the EHR makes documenting each SEDH element easy.”

  • The paper relies on this without support.

    The 201 respondents are representative of all staff physicians at the study institution.

    “Of this total, 201 participants completed the survey (8.1% response rate) and were included in the analysis.”

  • The paper relies on this without support.

    The process for charting on smoking would have been the same as for any other SDH or EDH for a particular provider.

    “the process for charting on smoking would have been the same as for any other SDH or EDH for a particular provider.”

  • The paper relies on this without support.

    Assessing for smoking status is deeply entrenched across all levels of medical training.

    “Assessing for smoking status is deeply entrenched across all levels of medical training”

  • The paper relies on this without support.

    Inconsistent and incomplete acquisition affects the quality and use of SEDH data.

    “Inconsistent and incomplete acquisition affects the quality and use of SEDH data”
6 of 6

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • SDH importance range excludes the reported 40% value

    Minor

    The discussion gives 43% as the lowest percentage considering an SDH vital, but the results report 40% for access to guns in the household.

  • Emergency Medicine omitted from infectious-disease charting exceptions

    Minor

    The results identify Emergency Medicine as having exactly half its physicians chart on infectious disease outbreaks. The discussion nevertheless says every department except Psychiatry and Pathology had less than half charting on it.

  • Conflicting statements about food security's ease-of-charting association

    Minor

    The results list only five SDHs with a significant association between ease of charting and consistent charting, excluding food security. The discussion says the association was significant for every SDH except seven others, which includes food security among the significant SDHs.

3 of 3

Cites

Flagged first, then by citations

Research works printed but not linked: 4

  1. Committee on Integrating Primary Care and Public Health; Board on Population Health and Public Health Practice; Institute of Medicine. Primary Care and Public Health: Exploring Integration to Improve Population Health. Washington (DC): National Academies Press (US); 2012 Mar 28.
  2. O’Reilly K. How to improve screening for social determinants of health [Internet]. Chicago,IL. American Medical Association; 2019 [cited 2019 Oct 4]. https://www.ama-assn.org/delivering-care/patient-support-advocacy/how-improve-screening-social-determinants-health.
  3. Robeznieks A. New ICD-10 codes will help physicians tackle social barriers to care [Internet]. Chicago,IL. American Medical Association; 2019 [cited 2019 Apr 2]. https://www.ama-assn.org/practice-management/digital/new-icd-10-codes-will-help-physicians-tackle-social-barriers-care.
  4. C Thomas-Henkel, 2017, Screening for Social Determinants of Health in Populations with Complex Needs: Implementation Considerations

Cited by

Still being checked.

Related

Authors
Sood, N., Stetter, C., Kunselman, A., & Jasani, S.
Affiliations
  • Pennsylvania State University (US)
  • Yale University (US)
Corresponding author
Jasani, Sona
ORCID
Venue
PLOS Digital Health
Publisher
Public Library of Science (PLoS)
Published
2024-01-11
Volume
3
Issue
1
Pages
e0000428
ISSN
2767-3170 (ISSN-L)
DOI
10.1371/journal.pdig.0000428
PMC
PMC10783763
OpenAlex
W4390755860
Semantic Scholar
c80eccc799af48543245bf2b0178863731cbe275
Cited by
6
References
27
Citations by year
2026: 2 · 2025: 3 · 2024: 1
FWCI
1.85
Type
journal article
Language
en
Open access
Licence
Locations
  • PLOS Digital Health (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • University of Pennsylvania
  • Pennsylvania State University
  • Penn State College of Medicine
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
  • Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
Keywords
electronic health records, EHR usability, clinical documentation, infectious disease outbreaks, data entry, secondary use of health data, EHR design, physician perceptions, health data quality, health workforce data, health insurance data, health care costs

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-28.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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