Table 3.
Reporting EHR VA Retrospective Data Considerations
| Phase/Element | Considerations and Recommendations |
|---|---|
| Study design | |
| Outcome definition | • Define VA outcome (e.g., best VA in the better-eye, change of best VA in the worse-eye, change in both eye VA) • Determine VA outcome unit (e.g., line versus letter count, logMAR, visual impairment categories) • Consider defining a minimum clinically important difference threshold |
| EHR VA elements | • Determine VA data fields that are relevant to the research question (e.g., best documented versus best corrected, see Table 1 for examples of available VA data fields) • Understand the implication of VA chart type (e.g., Snellen, ETDRS) on reporting and system capabilities • Plan for handling of the documentation of letter count and narrative detail |
| Nonquantifiable VA parameters | • Plan for managing observations (e.g., CF, HM, LP, NLP) as VA data - Observation (e.g., CF, HM, LP, NLP, prosthetic) entries and others should be analyzed separately from VA line measures or logMAR units when reporting VA change scores |
| EHR data extraction | |
| VA fields | • Identify available and relevant VA fields for data extraction - Assess for multiple entries in a single data field - Determine need for letter count extraction field (e.g., “+2”, “−1”) |
| Other relevant parameters | • Consider unique system and platform encounter parameters: department, subspecialty, location, provider, etc. • EHR system parameters: available VA fields, VA data entry method (e.g., free-text, drop-down menu) |
| Data quality assessment and analysis | |
| Completeness | • Identify the absence of VA data element(s) • Consider implications on cross-sectional and longitudinal analyses |
| Data dictionary conformance and plausibility | • Apply a data dictionary (VA values and observations) that is consistent with internal formatting constraints or standards until external standards are established • Plan for management of VA data documented at atypical or nonstandard test distances • Plan for manual review to assess plausibility in cases where data values may not meet the conformance standard |
| Change of VA | • Calculations of VA changes should consider eye- versus person-level reporting (completeness or missing data may impact usable data and analysis) • Plan for management of VA change in measures at floor (e.g., CF, HM) or ceiling of the estimate (e.g., 20/25) |
| Reporting | |
| VA outcome | • Outcome definition |
| VA fields examined | • Number of VA fields, entries per field examined • Content and description of VA fields analyzed (e.g., pinhole, refraction, near VA) |
| VA entry means | • Means of VA measure entries available: free text, drop-down menu, etc. • Documentation practices (if known) |
| Data quality | • Number of unique VA entries as a percentage of total entries • Completeness: number and percentage of entries with absent VA data • Definitions and percentage of usable (meeting conformance and plausibility standards) and unusable data (e.g., overall, by subspecialty, by provider, etc.) |
| VA coding | • Management of letter count, entries with test distance that do not convert to data dictionary, observations, narrative information, and implausible entries |
CF = counting fingers; EHR = electronic health record; HM = hand motion; logMAR = logarithmic minimum angle of resolution; LP = light perception; NLP = no light perception; VA = visual acuity.