Achieving EHR Satisfaction in Any Specialty
Impact Report
Insights shared by over 30,000 physicians reveal that EHR satisfaction is highly variable across specialties. For example, pediatrics physicians have an average Net EHR Experience Score (a measurement of overall satisfaction similar to a net promoter score) of 24.0, but other specialties report much lower satisfaction (e.g., cardiology † with a score of 1.6).
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† Pediatrics and cardiology are cited here and in later paragraphs instead of other, more extreme examples due to their larger sample sizes and to avoid overemphasis on potential outliers in Collaborative data.
One critical factor in the difference between specialties’ satisfaction is the quality of initial training. Collaborative data shows a correlation between high physician agreement that initial training prepared them well and high agreement that the EHR has functionality needed for
their specialty.
However, while organizational efforts around training can help mitigate functionality issues, some specialties simply don’t have needed functionality in their EHR, even with great training. One common complaint is that the size or scope of the specialty does not match up with the EHR’s intended user base; for example, one dermatologist described the EHR as “overly bulky for outpatient specialty care.” Another issue is that the EHR does not support specialty-specific clinical workflows; one ophthalmologist said their EHR doesn’t meet the needs of clinicians who “need to be able to document with drawing or images.” Other physicians, notably orthopedists, have concerns with things like specialty-specific templates/order sets, slow response times, or an unintuitive user interface.
To determine how much of the physician EHR experience is reliant on training compared to the product itself, the following charts compare Cerner and Epic users (the two largest customer bases in Collaborative data), showing how training impacts their EHR experience relative to meeting specialty-specific needs.
Compared to Epic users, Cerner users tend to agree less that they have needed specialty-specific functionality, even when controlling for training quality. However, ophthalmology and dermatology stand out for lacking needed functionality regardless of EHR. This highlights EHR vendors’ responsibility to pay special attention to struggling specialties and ensure the EHR includes the functionality these specialties need to succeed.
While these findings may lead some less-satisfied physicians to believe that they can’t succeed with the EHR because of their specialty, trends within specialties debunk this assumption. In many cases, physicians in lower-scoring specialties who have had high-quality training report high overall EHR satisfaction. For example, cardiologists with strong initial EHR training have a Net EHR Experience Score of 58.3, well above the overall physician average. Conversely, physicians in higher-scoring specialties who receive poor training report low satisfaction; poorly trained pediatricians have a Net EHR Experience Score of -21.6.
While cardiology and pediatrics are vastly different specialties and use the EHR in different ways, this analysis
shows they are similarly susceptible to the positive effects of high-quality EHR training and the negative effects
of poor training.
While there is variation in the typical experience of different specialties, no specialty is immune to the effects that high-quality training, strong culture, and personalization can have on EHR satisfaction. The insights in this report show how physicians can rise above their specialty's EHR limitations by learning effective methods of improving their EHR experience, regardless of their specialty.
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This material is copyrighted. Any organization gaining unauthorized access to this report will be liable to compensate KLAS for the full retail price. Please see the KLAS DATA USE POLICY for information regarding use of this report. © 2019 KLAS Research, LLC. All Rights Reserved. NOTE: Performance scores may change significantly when including newly interviewed provider organizations, especially when added to a smaller sample size like in emerging markets with a small number of live clients. The findings presented are not meant to be conclusive data for an entire client base.