An electronic health record (EHR) log analysis shows limited clinician engagement with unsolicited genetic test results

Abstract

How clinicians utilize medically actionable genomic information, displayed in the electronic health record (EHR), in medical decision-making remains unknown. Participating sites of the Electronic Medical Records and Genomics (eMERGE) Network have invested resources into EHR integration efforts to enable the display of genetic testing data across heterogeneous EHR systems. To assess clinicians’ engagement with unsolicited EHR-integrated genetic test results of eMERGE participants within a large tertiary care academic medical center, we analyzed automatically generated EHR access log data. We found that clinicians viewed only 1% of all the eMERGE genetic test results integrated in the EHR. Using a cluster analysis, we also identified different user traits associated with varying degrees of engagement with the EHR-integrated genomic data. These data contribute important empirical knowledge about clinicians limited and brief engagements with unsolicited EHR-integrated genetic test results of eMERGE participants. Appreciation for user-specific roles provide additional context for why certain users were more or less engaged with the unsolicited results. This study highlights opportunities to use EHR log data as a performance metric to more precisely inform ongoing EHR-integration efforts and decisions about the allocation of informatics resources in genomic research.

Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures

“… 75 , 93 , 94 , 113 Only one of the experimental studies was a randomized controlled trial. 75 Across both observational and experimental studies, 41 articles compared EHR use across different groups of users including comparisons by specialty (14 studies), 4 , 7 , 25 , 29 , 31 , 36 , 42 , 48 , 51 , 58 , 59 , 85 , 105 , 115 clinical role (12), 24 , 26 , 33 , 37 , 46 , 65 , 76 , 95 , 99 , 106 , 108 , 115 gender (8), 19 , 34 , 47 , 49 , 66 , 68 , 70 , 106 year in residency (8), 31 , 32 , 35 , 39 , 52 , 56 , 57 , 95 organization (3), 24 , 44 , 75 and country (1). 27 Vendor-measure studies were more likely than investigator-measure studies to make such comparisons of EHR use by user group (65% vs 25...…”

“…While 70 articles measured a duration of time, 2–4 , 6 , 7 , 19 , 24–62 , 66–73 , 76 , 77 , 79–81 , 83 , 92–96 , 98 , 102 , 108 , 109 , 111 , 119 12 of these measured a duration between 2 specific points in time (e.g., duration of an appointment, or shift), 60 , 68 , 76 , 80 , 81 , 83 , 92–94 , 96 , 102 , 111 leaving 58 articles which measured a duration of active EHR use. 2–4 , 6 , 7 , 19 , 24–59 , 61 , 62 , 66 , 67 , 69–73 , 77 , 79 , 95 , 98 , 108 , 109 , 119 Of these 58 articles, 34 described (or referenced an article that described) how active use was defined. 3 , 4 , 19 , 24–29 , 31 , 32 , 35 , 39 , <...…”

“… 2–4 , 6 , 7 , 19 , 24–59 , 61 , 62 , 66 , 67 , 69–73 , 77 , 79 , 95 , 98 , 108 , 109 , 119 Of these 58 articles, 34 described (or referenced an article that described) how active use was defined. 3 , 4 , 19 , 24–29 , 31 , 32 , 35 , 39 , 41 , 42 , 44 , 47 , 48 , 52 , 53 , 55–58 , 62 , 66 , 69 , 72 , 73 , 77 , 79 , 95 , 98 , 108 There was no difference in reporting between vendor-measure or investigator-measure studies (59% vs 60% of relevant articles, P = 1.000), but there were differences in method. The vendor-measure studies all used Epic’s 5-s threshold to identify periods of inactivity or Cerner’s method of defining active use as either actions occurring less than 45 seconds apart or performing more than 15 keystrokes, 3 mouse clicks, or 1700 pixels of mouse movement in a minute.…”

Incomplete Penetrance of Population-Based Genetic Screening Results in Electronic Health Record

“…Reservations regarding insurance discrimination and the social impact the findings might have for the patient play a role as well, although we note that only one person in the results herein asked to have no mention of the finding in the medical record. Additionally, physicians may not pay attention to unsolicited genetic results within EHRs (eMERGE ( Gottesman et al, 2013 ; Williams et al, 2019 ; Nestor et al, 2021 )) and it may be unclear to healthcare personnel who is responsible for positive genetic testing results ( Pet et al, 2019 ). Ours was not a usability study and we cannot attribute the relative weight of the factors that may contribute to the observed poor documentation.…”

“…Failing to document findings in the PL could result in a loss of knowledge regarding the patients’ at-risk status for years to come. However, as Nestor et al (2021) showed, even documented findings can often be ignored. This highlights the need for continued outreach to T1pos participants and especially their healthcare providers on follow-up steps and documentation that needs to be taken to effectively manage disease risk and to ensure optimal outcomes of PbGS.…”