Key Highlights
- Completing EHR training does not ensure proficiency as a clinician in the real world.
- Task completion, workflow accuracy, and efficiency are used to gag proficiency.
- Clinicians can practice EHR workflows safely with the use of realistic, role-based simulation.
- Proficiency can be maintained after go-live with ongoing training and in-app support.
Introduction
A clinician can complete all the EHR training modules that have been allocated to them, pass the test, and obtain a completion certificate, but still struggle with the system for the rest of the week.
They might be 100% trained but not be proficient in practice. This distinction is becoming more and more crucial for health systems. Participation in EHR training is measured by completion. EHR proficiency tests one’s skill. Leaders are informed who has finished the curriculum. The other shows how effectively clinicians are able to carry out the workflows necessary for their jobs. Furthermore, there is much more to the gap in healthcare than just productivity.
It may have an impact on clinician burnout, workload, workflow dependability, and the capacity to provide care without unnecessary interference. According to the National Academy of Medicine, physicians who received inadequate EHR training were 3.5 times more likely to claim that their EHR did not allow them to provide high-quality treatment. Additionally, it cites protected training time, education tailored to roles and specializations, and improved metrics for efficient EHR use as critical priorities.
The positive aspect is that health systems are not restricted to inquiring about the confidence of clinicians. The EHR generates data that can be used to assess proficiency. A much better image of what clinicians can truly accomplish can be obtained from vendor analytics, event logs, workflow metrics, after-hours activities, and proven proficiency.
Why is EHR Training Completion not Equate to Proficiency?
Completing training is a must. Health systems must be aware of whether practitioners attended the required education, whether it was provided, and whether the learning criteria were fulfilled. When completion is seen as the ultimate indicator of success, the issue arises.
The issue arises when success is determined solely by completion. You can learn that a doctor has completed a documentation module from a completion report. It can’t tell you if the doctor can effectively record a visit. It can demonstrate that a nurse has finished order entry training. It can’t tell you if the nurse can carry out the workflow with assurance during a hectic shift.
It can verify that a clinician witnessed an outcomes review demonstration. It cannot determine whether they are able to locate, analyze, and act upon the relevant information without needless searching. Hence, it is better to think of completion as a training activity indicator rather than a competency metric.
The Healthcare Issue of Training Being Designed Around Software
The fact that many EHR programs are still built around what the software can do rather than what a specific physician needs to accomplish is one reason completion might be deceptive. The distinction is important.
Although they may operate in the same EHR, emergency physicians, surgeons, hospitalists, primary care physicians, and nurses use it differently. They have diverse patient volumes, order patterns, workflows, documentation needs, and priorities. However, they might all receive essentially the same tour of the system via a generic curriculum.
This strategy provides a well-known result: although physicians are more knowledgeable about the EHR, they may not be more adept at utilizing it in the course of their real work.
When training becomes a checkbox for onboarding
The success of EHR training is also influenced by how a company presents it. The standards are quite different. According to the second method, health systems must specify what proficiency entails, set expectations according to job and expertise, then evaluate if those expectations are being fulfilled. That is more in line with the approach taken to other clinical competences.
What Is the True Meaning of EHR Proficiency?
A clinician’s level of proficiency cannot be fully expressed by a single number. Rather, proficiency should be seen as a blend of aptitude, efficiency, accuracy, workflow performance, and system usage. This implies that being proficient involves more than just knowing the location of a feature.
A clinician might be aware of the existence of an order set. Knowing when and how to use it correctly is a sign of proficiency. They might be aware of the existence of a macro or SmartPhrase. Being proficient entails properly integrating it into routine documentation.
They might be able to locate an outcome. The ability to obtain and act upon pertinent information within the anticipated workflow is what is meant by proficiency. The core of the problem is this distinction between knowing and doing.
Completion vs. proficiency
EHR training completion | EHR proficiency |
Modules completed | Clinical workflows successfully performed |
Hours of training | Efficient use of the EHR |
Attendance | Use of relevant efficiency tools |
Quiz scores | Appropriate use of order sets and personalization |
Certificate or sign-off | Documentation and task timeliness |
Curriculum percentage | After-hours EHR activity |
Training participation | Demonstrated competency |
The Health Systems' Current Data
The fact that health systems frequently already have a large amount of the required data makes evaluating EHR performance one of the most helpful components. Interactions with the system are documented by the EHR. These interactions can be combined into useful metrics using vendor analytics. When combined, these data sources can identify trends that a training-completion report is unable to.
1. Vendor competency and efficiency analytics
One example of this strategy is the Signal platform from Epic. Among Epic’s vendor-defined metrics are an efficiency meter that takes into account EHR time in relation to workload and a Proficiency Score that represents the utilization of particular EHR capabilities.
These metrics have been shown to be useful for assessing the effects of focused EHR education. According to a study, family medicine residents’ performance increased as a result of a structured EHR training program, even if the efficiency metric under investigation did not significantly improve. It’s a crucial distinction.
Efficiency and proficiency are connected, but they are not the same. It is possible for a clinician to improve their use of the EHR’s tools without instantly increasing their overall speed. On the other hand, a clinician who relies on ineffective or inconsistent methods could appear quick. The metric requires background.
2. EHR event logs data
EHRs produce comprehensive event data behind the visible interface. Health systems can look at metrics like these, depending on the system and how the company sets up its analytics:
- Time spent using EHR
- Spending time on specific tasks
- Using particular tools
- Activity related to documentation
- Use after hours
- Workflow completion
- Keystrokes or clicks related to specific duties
- Volume of messages and processing time
Clinical informatics teams now have a huge potential. Organizations can evaluate what clinicians claim to know with what their actual EHR conduct reveals, rather than depending just on surveys or self-reported confidence.
3. Pajama time
Pajama time is one of the few EHR metrics that best capture the human aspect of the issue. The phrase refers to EHR work that is done after regular clinical hours, such as charting, documentation, messaging, and other chores that extend into the evenings, weekends, or other personal time.
Pajama time should not be viewed as a straightforward “bad clinician” metric. A high figure may indicate organizational procedures, workload, staffing, scheduling, documentation needs, or demands unique to a certain profession.
However, it remains a useful indication. The National Academy of Medicine suggests monitoring PJ time as part of attempts to comprehend EHR-related burden and clinical well-being, whereas research has connected after-hours EHR use with physician fatigue.
4. Timeline Importance
Efficiency is more than just finishing things fast. When a work is finished might be as significant in the medical field. Thus, health systems can look at metrics like:
- Visit closure
- Note signing
- Order completion
- Required cosignatures
- Results review
- In-basket response time
These assessments offer an additional level of competence. Effective proficiency is not always demonstrated by a practitioner who can swiftly traverse an EHR but frequently leaves crucial documentation unfinished. Maximum speed is not the objective. Within the workflow, it is dependable performance.
An Improved Method for Assessing EHR Proficiency
Replacing completion metrics is not the best strategy. The purpose is to place them appropriately. Consider the three layers of the measurement model.
Layer 1: Has the clinician finished the course?
The conventional completion measure is this one. It attests to involvement.
Layer 2: Is the clinician able to show the workflow?
The competency measure is this. It attests to the clinician’s ability to carry out crucial duties accurately and on their own.
Layer 3: How does that ability affect the behavior of an EHR in real time?
Operational data is useful in this situation. Workflow completion, after-hours activity, proficiency and efficiency indicators, and other EHR-derived metrics can all be examined by health institutions.
When combined, these three layers paint a far more powerful picture than when used separately. Exposure is indicated by completion. Capability is revealed through demonstration. Behavior is revealed via live system data. This paradigm is far more helpful in determining whether EHR training is producing the desired results.
How EHR Proficiency can Be Developed by Health Systems?
The gap is found through measurement. Closing it is the next step.
1. Define competence according to job role
A generic list of EHR features is not a good place to start. Start working on the project. What skills are essential for a primary care physician? What must an emergency nurse consistently do? These prerequisites may develop into competency standards unique to a given role.
Because training is based on the work that doctors really do, this makes EHR training best practices much more applicable.
2. Practice workflows rather than just features
Clinicians may learn that a specific function exists through a feature-based curriculum. They are required to employ the function in context using a workflow-based curriculum.
For instance:
Examine pertinent data > open the patient record > document > place orders > examine the results > and end the visit.
Compared to a series of disjointed software presentations, the sequence is far closer to actual clinical work. Clinicians can also make mistakes during hands-on practice, but the consequences are still confined to a training setting.
3. Make training ongoing
After go-live, training shouldn’t stop. To pinpoint areas for focused optimization, use workflow and proficiency data. Personalized training can increase EHR-related knowledge and performance and lower some metrics of after-hours use, according to research on targeted EHR optimization. When the data indicates that only specific workflows or user groups require assistance, do not retrain everyone.
4. Provide a secure setting for clinicians
Directly using clinical protocols in manufacturing has a clear drawback:
Real patient data is stored in the production system.
Clinicians must have practical opportunities to practice without putting patients at needless risk or disclosing private health information. Simulation becomes especially helpful in this situation.
Without testing on actual patient information, a realistic simulated EHR environment enables doctors to repeat workflows, make mistakes, get feedback, and gain confidence. Additionally, rather than waiting until the first actual patient interaction, it offers a chance to evaluate proficiency prior to go-live.
The Future of Digital Transformation in Healthcare through Simulation
This is where the broader issue of digital transformation in healthcare is related to EHR competency. The deployment of technology is a common indicator of its implementation. Deployment, however, is not adoption. Furthermore, adoption does not equate to competence. Even if an EHR is effectively implemented in a health system, doctors may still have trouble understanding its workflows months later. For this reason, in the healthcare industry, training, adoption, competency, and change management must all be taken into account.
Competency models are subject to the same rule. Competency-based approaches outline the necessary skills, offer practice opportunities, evaluate performance, and gradually reinforce those skills rather than viewing learning as an event.
Healthcare frameworks like the ADKAR model acknowledge that successful change cannot be achieved solely through knowledge. In order to maintain the new behavior, people also need to be able to use that information and receive reinforcement. That distinction is especially crucial for EHR adoption. It is not necessary to show clinicians where a button is. They must have faith in their ability to complete their tasks.
Assima's Potential to Develop Measurable EHR Proficiency
A more competency-focused approach can be supported in this situation by a systems training platform. Healthcare organizations can construct realistic software practice environments with Assima’s object-based simulation technique, allowing physicians to practice the necessary workflows without depending on real-time patient records.
Learning pathways based on roles and specializations can help better match practice to the work that physicians actually do. Organizations can determine where learners require more assistance by using competency gates and step-level analytics, which can offer proof of demonstrated performance. This is particularly helpful prior to go-live, when clinicians require practical experience but shouldn’t be learning by making mistakes in a live setting.
Additionally, Assima does not need to replace the analytics built within the EHR. The two have distinct functions. The two have distinct functions. Health organizations can learn how clinicians are utilizing the live EHR with the use of vendor analytics like Epic Signal. Organizations can develop and evaluate the competency that first facilitates effective use with the aid of simulation. Simulation information may be updated as systems and procedures change, and Assima In-App Search can offer contextual support when doctors require assistance during the workflow after it goes live.
Conclusion
Completion rates have been used for years to evaluate EHR training programs. Completion is still important. It serves as the starting point. However, it should not be confused with competence. Use it as a starting point to measure the actual capabilities of clinicians. In the end, professionals’ completion of EHR training is not what makes it valuable.
It is that when patient care depends on the system, they may use it with assurance, effectiveness, and appropriateness. Completion reveals who was present. Proficiency indicates who is capable of doing the task. And it’s the difference in healthcare that needs to be measured.
Frequently Asked Questions
Let’s Answer Some of Your Questions.
EHR training completion confirms a clinician attended and finished a course. EHR proficiency confirms they can actually perform clinical workflows — documenting a visit, placing orders, reviewing results — accurately and efficiently in the live system. Completion is a participation metric; proficiency is a capability metric, and the two often diverge.
Through three layers: whether the clinician completed training, whether they can demonstrate the workflow unassisted, and how that shows up in live EHR data. The behavioural layer draws on vendor analytics (such as Epic Signal), event logs, workflow-completion timing, and after-hours (“pajama time”) activity — combined with scenario-based assessments rather than attendance alone.
No. A clinician can finish every assigned module, pass the quiz, and earn a certificate while still struggling to document a visit or run an order set confidently during a busy shift. Completion shows exposure to training; it does not prove the clinician can execute the workflows their role requires.
Pajama time is EHR work — charting, documentation, messaging — done after clinical hours, spilling into evenings and weekends. It’s a useful proficiency and burden indicator, though a high figure can also reflect workload, staffing, or documentation requirements rather than skill alone. The National Academy of Medicine recommends tracking it as part of understanding EHR-related clinician burden.
Epic Signal provides vendor-defined metrics, including an efficiency meter (EHR time relative to workload) and a Proficiency Score reflecting use of specific EHR capabilities. It’s valuable for seeing how clinicians use the live system, but efficiency and proficiency aren’t identical — a clinician can use the right tools without being fast, or appear fast while relying on inefficient workarounds. Signal works best alongside demonstrated-competency assessment.
Define competency by clinical role, give clinicians hands-on practice of their real workflows in a safe simulated EHR (not the live system), assess whether they can complete key workflows correctly, and reinforce with targeted refresher training and in-app guidance as systems and workflows change. Proficiency has to be maintained over time, not achieved once at go-live.
