Using routinely available electronic health record data elements to develop and validate a digital divide risk score
Data files
Mar 26, 2025 version files 80.22 KB
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DD_datashare.csv
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README.md
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Abstract
Background: Digital health (patient portals, remote monitoring devices, video visits) is a routine part of healthcare, though the digital divide may affect access.
Objective: To test and validate an electronic health record (EHR) screening tool to identify patients at risk of the digital divide.
Materials and Methods: We conducted a retrospective EHR data extraction and cross-sectional survey of participants within one healthcare system. We identified 4 potential digital divide markers from the EHR: 1) mobile phone number, 2) email address, 3) active patient portal, and 4) >2 patient portal logins in the last year. We mailed surveys to patients at higher risk (missing all four markers), intermediate risk (missing 1-3 markers) or lower risk (missing no markers). Combining EHR and survey data, we summarized the markers into risk scores and evaluated its association with patients’ report of lack of Internet access. Then, we assessed the association of EHR markers and eHealth Literacy Scale survey outcomes.
Results: 249 patients (39.4%) completed the survey (53% > 65 years, 51% female, 50% minority race, 55% rural/small town residents, 46% private insurance, 45% Medicare). Individually, the four EHR markers had high sensitivity (range 81-95%) and specificity (range 65-79%) compared with survey responses. The EHR-marker-based score (high, intermediate, low risk) predicted absence of Internet access (ROC c-statistic = 0.77). Mean digital health literacy scores significantly decreased as EHR-marker digital divide risk increased (p<0.001).
Conclusion: Using these markers, healthcare systems could target interventions and implementation strategies to support equitable patient access to digital health.
[Access this dataset on Dryad](Dataset DOI link)
This dataset contains deidentified survey and electronic health record (EHR)-derived data used in the study of the Digital Divide—examining disparities in technology access and usage related to healthcare. It includes variables related to demographics, technology use, digital health engagement, and social determinants of health. The results of the study indicate that 4 easily obtained EHR markers have high sensitivity and specificity in predicting a person’s risk for the digital divide.
Description of the data and file structure
The dataset consists of one excel file with deidentified data.
Item | Source | Description |
---|---|---|
dd_study_id | assigned | Unique person identifier (deidentified) |
p1_ddrisk | EHR | derived Risk for the digital divide (based off 4 identifiers; if all 4 are positive then High Risk; if 0 are positive then Low Risk else Mid Risk |
p1_sex | EHR | derived Sex |
p1_agegroup | EHR | derived Age group |
p1_race | EHR | derived Race |
p1_area | EHR | derived Area based on RUCA 2010 |
p1_insurance | EHR | derived Financial class |
USES_EMAIL | survey | Goes online to access internet or send/receive email |
RCV_TEXT | survey | Receives text messages (weekly or daily) |
SEND_TEXT | survey | Sends text messages (weekly or daily) |
CELL_INTERNET | survey | Uses cell to access the internet |
TECH_HEALTH | survey | Uses technology for accessing healthcare information |
FRIENDS_INTERNET | survey | Family and friends help with internet for health information |
eHEALS | survey | eHEALS Score Sum of 8 questions |
dd_education | survey | Education Status |
dd_employment_a | survey | Full Time |
dd_employmentb | survey | Part Time |
dd_employmentc | survey | Unemployed |
dd_employmentd | survey | Retired |
dd_employmente | survey | Disabled |
dd_employmentf | survey | Student |
dd_employment__g | survey | Stay at home parent |
dd_financialsecurity | survey | Currently, is your income enough to meet your basic needs for food, housing, clothing, and medical care? |
dd_housingsecurity_12m | survey | How often in the past 12 months would you say you were worried or stressed about having enough money to pay rent/mortgage? |
dd_housingsituation | survey | What is your living situation today? |
dd_foodsecurity_12m | survey | In the past 12 months, you worried that your food would run out before you got money to buy m |
dd_transportsecurity_12m | survey | In the past 12 months, has lack of reliable transportation kept you from medical appointments, meetings, work, or from getting things needed for daily living? |
dd_cellphoneuse | survey | Do you have a cell ? |
dd_have_email | survey | Do you have an email? |
dd_ehr_access_offered | survey | Have you been offered access to your online medical records? |
dd_ehr_access_12m | survey | Have you accessed your online medical records in the last 12 months? |
EHR_EMAIL | EHR | Email Address found in the EHR (Digital Divide Indicator 1; Positive if email is listed in EHR) |
EHR_CELL | EHR | Cell listed in the EHR (Digital Divide Indicator 2; Positive if cell is listed in EHR) |
EHR_PORTAL | EHR | Patient portal listed in the EHR (Digital Divide Indicator 3; Positive if patient portal is activated) |
EHR_LOGINS | EHR | Total portal logins in the last year |
EHR_ACTIVE | EHR | Is user active in the portal (Digital Divide Indicator 4; Positive if EHR_LOGINS>2) |
*Note: Blank cells denote missing data.
Sharing/Access information
We suggest reading the associated publication “Using routinely available electronic health record data elements to develop and validate a digital divide risk score”
https://doi.org/10.1093/jamiaopen/ooaf004
For questions about this dataset, email Dr. Thomas Houston (tkhouston@wakehealth.edu) or Dr. Jaime Faro (jaime.faro@umass.edu)
Links to other publicly accessible locations of the data:
- NA
Data was derived from the following sources:
- Atrium Health Wake Forest Baptist’s version of Epic Clarity (EHR data)
- Digital divide survey (survey data)