Table 1.
Assumptions and considerations for electronic phenotype implementation by site
| Site | Determination of eGFR | Race Assumption | Personnel Involved | Estimated Time Investment | Challenges/Barriers | Facilitators |
|---|---|---|---|---|---|---|
| Christiana Care | From laboratory (multiple equations) | All patients had a race, and GFR was checked against race | One nephrologist | Total: 223 h | LOINC not used, requiring crosswalk to internal codes | None |
| One information technologist | Communication: 13 | Separate EHRs used for in- and outpatient care during the study period; required matching and merging multiple warehouses and data marts and pulls directly from the EHRs to produce the dataset | ||||
| One student | Data extraction: 79 | |||||
| One resident | Data merging and cleaning: 131 | |||||
| Columbia University | Recalculated from serum creatinine (CKD-EPI) | Assumed nonblack if race not available | One nephrologist | Total: 20 h | LOINC not used, requiring crosswalk to internal codes; however, crosswalk to internal codes existed | Existing clinical data warehouse; eMERGE site with adequate infrastructure and IT support |
| One informaticist | Communication: 5 | |||||
| One research coordinator | Data extraction: 10 | |||||
| Data cleaning: 5 | ||||||
| University of Minnesota | Recalculated from serum creatinine (MDRD) | Assumed nonblack if race not available | One nephrologist | Total: 44 h | eGFR was less available than serum creatinine | Leveraged data extraction completed for an ongoing project |
| One IT person | Communication: 4 | |||||
| Data extraction: 20 | ||||||
| Data cleaning: 20 | ||||||
| UCSF | From laboratory (CKD-EPI) | Assumed nonblack if race not available | One nephrologist | Total: 49 h | LOINC not used; no existing crosswalk to Clarity codes | Leveraged personal relationships |
| One informaticist | Communication: 5 | |||||
| One IT person | Data extraction: 20 | |||||
| One statistician | Data cleaning: 24 | |||||
| University of Utah | From laboratory (multiple equations) | Assumed nonblack if race not available | One informaticist | Total: 40 h | Identifying relevant laboratory codes as LOINC was not universally available | None |
| Communication: 0 | ||||||
| Data extraction: 10 | ||||||
| Data cleaning: 10 | ||||||
| Data analysis: 20 |
LOINC, Logical Observation Identifiers Names and Codes; EHR, electronic health record; CKD-EPI, Chronic Kidney Disease Epidemiology Collaboration; eMERGE, Electronic Medical Records and Genomics; IT, information technology; MDRD, Modification of Diet in Renal Disease; UCSF, University of California, San Francisco.