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Optimizing Medication Management Workflows in Your EHR

November 21, 2023

Colin Banas, M.D., M.H.A.

Optimizing Medication Management Workflows in Your EHR

When every patient requires medication reconciliation at hospital admission and discharge, and it’s been a quality measure of The Joint Commission for nearly 20 years, why is the medication history in your electronic health record (EHR) still full of so many holes? And why is med rec still a “med wreck?”

Some key factors contribute to this broken process. The first is incomplete data. I recall the early days of EHRs, when there was no interoperability of data outside the four walls of my organization. I was in my residency when clinicians gained access to the “external Rx history,” which was a watershed moment in digital care that finally provided some data around the patients’ prescription fills.

Unfortunately, I soon learned that this medication data is never complete. The standard external data feed pulls prescription information into the EHR from payers’ pharmacy benefit managers (PBMs), financial transactions, and pharmacies. Today, there are still pharmacies or PBMs that aren’t connected to the standard feed. On top of that, financial transaction data for prescriptions almost always lacks instructions, also known as “sigs,” on how the patient is supposed to take the medication. This means the data feed is missing entire prescriptions and often lacks visibility into how the medication was intended to be used.

The second factor is incoming data that uses terminology that’s different from the nomenclature your EHR uses. This causes information to arrive in a free-text block rather than structured in discrete fields, which prevents its immediate use for tasks such as triggering critical safety alerts like potential drug interactions.

Clinicians try to fill these gaps by making phone calls to additional sources, such as local pharmacies, family members, or other members of the clinical team. Of course, they also turn to the data source sitting in front of them: the patient. Unfortunately, we all know how difficult it is to remember every medication we take, let alone the dosage, frequency, and intent. Add the stress of an emergency setting or the burden of illness, and it’s even harder for patients to remember and recite these details. These data gaps result in delayed care and contribute to staff stress and burnout.

On the chance a patient does accurately communicate his or her medication history, the clinician must then manually enter it into the patient record, a time-consuming process that’s prone to human error. I’ve accidentally typed an 11 instead of a 1 into an EHR, and I doubt I’m alone in that kind of mistake. In this era of digital transformation, can’t technology help us do better?

To overcome these roadblocks and reduce the risk of adverse drug events (ADEs) and hospital readmissions, it’s essential to enhance medication management workflows by giving your clinicians a robust source of medication history data and an automated process to optimize that data when it’s imported into your EHR.

 

Tips for Automating Medication Workflows

Start by adding more data so your clinicians don’t have to spend valuable time hunting for up-to-date patient information or manually entering data. It’s possible to enhance the standard medication feed by pulling in more prescribing data from healthcare providers, independent pharmacies, hosted insurer and payer records, and health information exchanges. In other words, have technology help you cast a wider net for those medication records.

Once you have access to more information, you still need to break down the interoperability barriers that prevent a clean import of medication history data into your EHR. Clinical-grade AI can normalize prescription nomenclature standards and instructions (sigs) into the terms your system uses and safely infer missing data based on context. AI can also translate national drug codes between different databases and populate free text into discrete fields in your EHR. With AI handling tedious tasks and avoiding the risk of keyboard errors, clinicians can spend more time on patient care. If necessary, at any point, the AI will flag issues that need staff input, acting as your clinical co-pilot in medication safety.

You can also leverage your EHR to speed medication reconciliation for high-risk patients. As health systems face increasing pressure to reconcile medications for the most medically complex patients at admission, EHRs can help automate the process of prioritizing patients by age, high-risk medications, or other factors.

 

Intelligent Automation Optimizes Native EHR Workflows—and Patient Care

Many health systems are optimizing their medication history data feed with more complete patient information and adding AI to native EHR workflows to automatically fill data gaps. Here are two examples:

Cone Health, a North Carolina-based health system with more than 100 care locations and nearly 2,500 beds, wanted to optimize its medication history process to enhance patient safety and workflow efficiency. Pharmacy technicians had access to an external medication history source within their Epic EHR, but information was often missing. As a result, they needed to call pharmacies to gather and confirm a patient’s medication list, then enter it manually.

The health system now uses a solution that provides a more complete source of medication history and properly translates the incoming records. Today, they receive data for 93% of patients and 98% of high-risk patients over age 65. Clinical-grade AI translates and optimizes that data, then populates it into the appropriate fields to make it available in the clinical workflow, so technicians can spend less time manually gathering and entering this information.

Michigan-based Covenant HealthCare gathers comprehensive medication history data from multiple sources (including local and independent pharmacies) to supplement the standard data feed. Clinical-grade AI then cleans the data, translates sigs into preferred language, and imports the information into discrete fields in its Epic EHR. Covenant reduced medication errors by 89% and improved productivity by 33%, resulting in a $309,000 savings in labor costs in the ED pharmacy, plus $6.7 million in annual savings from avoided errors.

With optimizations like these, your EHR can become an indispensable part of your medication-related processes, relieving burden from your clinicians and reducing the risk of errors that could harm patients. And “med wreck” can become a distant memory.


About Colin Banas, M.D., M.H.A.
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Colin Banas, M.D., M.H.A. is Chief Medical Officer of DrFirst, and former Internal Medicine Hospitalist and former Chief Medical Information Officer for VCU Health System in Richmond, Virginia.