9 keys for optimizing EHR use at the point of care
Crucial best practices for getting the most value out of an electronic records system.
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9 essential steps in maximizing return on an EHR
As more organizations have installed electronic health records systems, they’re now looking for ways to derive value from them. That starts at the very beginning of the implementation process, according to a paper on best practices developed by the National Learning Consortium, which represents the collective experiences and knowledge of work done under the programs of the Office of the National Coordinator for Health Information Technology.
From the start, an organization should engage all stakeholders in system selection and implementation, especially getting them involved in the configuration of data entry templates, clinician decision support and how the system will be rolled out. While staff will be trained, optimizing use of the EHR starts before training and continues after training and go-live to ensure effective use of the system. Here are nine strategies to consider.
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1. Map the workflows and process as they are being performed today
Compare current use with the improved workflow and processes intended to be performed. Discuss with user what issues they are seeing and have them identify ways to adopt the new workflow and processes or revise it to perform better.
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2. Directly observe how individuals use the EHR
Any number of factors can cause issues, many of which can be corrected with additional training or slight modifications of existing computer skills, redesign of a template or adding data capture aids such as copy and paste, favorites lists or larger font sizes.
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3. Consider the physical environment
When implementing barcode medication administration record systems, nurses may believe they are walking more and physicians may complain they have to wait on someone to stop using the computer so they can get on and enter orders. Review the layout of nurse stations and determine if more stations or portable devices are necessary.
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4. Practice actual use of systems
Role-play with individuals to make them comfortable with changes in how work is performed in front of a patient while using the computer. Use your test environment to play the role of various types of patients, such as those who are hard of hearing or have nosy relatives, or those who may be concerned about the privacy and security of their information. However, most patients simply won’t care that a computer is being used.
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5. Script how to introduce the EHR to patients
You may need to take a bit of time and explain the need to focus on documentation during the visit. Most patients won't mind.
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Clinicians may complain they are expected to collect and record more data in the EHR than when they were charting on paper. The EHR may be asking for data that are rarely needed, and changing these data elements from required to optional may be necessary. Evaluate all uses of the data, such as how a data element affects the performance of a clinical decision support rule or is required for claims processing.
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7. Evaluate if alternative data sources can reduce data input
If a patient has been treated since the EHR was adopted, trace if certain data could flow from a previous visit. Common information such as gender, birth date, family history, past medical history, allergies and other data that rarely changes should not have to be collected again.
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8. Supply value for the data collected
Data collection can seem meaningless if clinicians required to enter data see no apparent purpose. Your organization may have improved disease prevention by collecting data on whether patients have had certain vaccinations, colorectal cancer screening or mammography. But if many patients say the procedures have been performed elsewhere, physicians may question the value of collecting this data. Clinicians should be involved in deciding what data to collect and then shown aggregate results. If results show little value, fine tune practices to be more pertinent which could require modifying the EHR.
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Continue to work on issues identified and on identifying other issues. Even when all appears to be working well, new issues may arise or old issues resurface. Occasionally ask users if the data entry seems to be going smoothly.
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