Medium, Message, Panopticon: The Electronic Health Record in Residency Education
Bibliographic record
Abstract
Within a single generation, medical records and record keeping have switched from paper to electronic media. Physician workflows have changed to accommodate a wide range of new e-health systems, including electronic health records (EHRs), hospital information systems, and picture archiving and communication systems. These technologies now pervade much of contemporary clinical practice, mediating the information flow in and around the provision of patient care. Many champion the benefits of e-health, such as greater efficiency and better use of data.1 Many also criticize its shortcomings, such as increased costs, interference with patient communication, and systemic data errors.2 The debate continues apace.One key impact of the move to e-health systems has been a shift of responsibility and effort regarding the creation and management of patient health data. In a systematic review of the utility of electronic patient records (EPRs), Greenhalgh and colleagues observed that “even though secondary work (audit, research, billing) may be made more efficient by the EPR, primary clinical work may be made less efficient . . . creating accurate and complete clinical records requires the sacrifice of time and effort by frontline clinical and administrative staff [which is] justified by more benefits for efficient business processes (eg, billing), governance, and research.”3 It may be surprising to the uninitiated that patients and physicians are not necessarily the main beneficiaries of e-health systems. This, in turn, raises many questions about the ethics and effects of these technologies on residency education.The article by Chen et al4 in this issue of the Journal of Graduate Medical Education reports the findings of a study that used the log data generated by first-year internal medicine residents' mouse clicks and keystrokes using the institutional EHR. The research showed that the average time spent on the system was approximately 7 hours per day in July, which fell to 5 hours per day by January. The authors hypothesized that this was due to the residents' increased competence and confidence in using the EHR system, even though their study did not explore whether this was actually the case.Thus, we have a detailed profile of resident interactions with an EHR over time, but little information on the residents' experiences of using the system. We also know little about how trainees' use of the EHR relates to their clinical training. It is notable that, although residents in the study received training on how to operate the EHR at the start of the year, there was no mention of any subsequent teaching or professional development around EHR use. Indeed, based on the information available, it would seem that the EHR was a nonnegotiable part of the work flow of the residents in this study, rather than part of the formal curriculum. Competencies related to the use of e-health would therefore seem to be a part of the informal or hidden curricula, rather than something explicitly linked to trainees' professional development. That these residents spent a major part of their days using the EHR system, and that this activity was not—as far as we can tell—explicitly related to their training, raises further questions regarding the balance between service and training and who benefits (or should benefit) from this activity. To paraphrase Marshall McLuhan, it seems that the EHR medium is very much a message but one to which we are perhaps paying too little attention.5As much as we might question the relevance of using an EHR for residency training, there is another, perhaps larger, issue: the use of syntactic log data to monitor how health professionals use EHRs and other e-health technologies. Tracking and monitoring are key aspects of Internet technologies,6 and Chen et al have illustrated this power by using the logs of individual residents' clicks and keystrokes to make inferences about their behaviors and the value of those behaviors.4 It should be noted that Chen et al are not the only researchers to use log data to make inferences about clinical behaviors;7 there seems to be a growing acceptance of this approach. Most clinical activities are ephemeral (unless captured on video), and their value depends on whether and how they were observed, as well as on their outcomes. The use of e-health systems is a radical departure from this, as every single user action is recorded for future analysis and interpretation. An EHR is therefore a panopticon: a system that allows the few to observe the many, without the latter being aware that they are being observed.There are many potentially beneficial uses of panoptic technologies, such as preventing errors and flagging suboptimal practices. But there are also less desirable uses, such as obliging users to change their behaviors to conform to institutional norms based on factors such as cost or time rather than optimal patient care. This is further complicated by clinicians' awareness that they are being observed and tracked. This may lead them to change their behaviors using these systems to portray themselves in a more favorable light. While one might hope that this oversight would lead to clinical quality improvement, it is just as likely to be a syntactic response: users who game the system also tend to distance themselves from the moral and ethical consequences of their actions. If unaddressed, these issues will only add to the informal and hidden curricula of e-health in residency education.How residents are being prepared for practice in an e-health mediated world is an important question, perhaps one of the most important questions facing us today. Larger studies are required to explore these issues more thoroughly. For instance, we need to compare and contrast residents' qualitative experiences and their quantitative use of EHRs across multiple programs to begin to appreciate the impact e-health is having on residency education as a whole. More importantly, we need to be paying a lot more attention to the intersections between e-health and the professional development of tomorrow's physicians. If, as it seems, e-health is changing the ecology of residency training, then we need to be a lot better informed and prepared to deal with its consequences.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.017 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".