If you work with or use healthcare data, you probably have a negative reaction to the word “silos.” That’s because while the industry has spent decades working toward interoperability, much of our data remains “siloed” in incompatible systems.
But in agriculture, silos are an efficient part of the infrastructure, built to receive, store, and supply produce. They may look like they are standing alone, isolated from their environment, but silos are an integral component in a complex system designed to distribute large volumes of food as efficiently as possible.
So, what we have in healthcare aren’t really data silos. They are deeply dug pits, broad swaths of unstructured and poorly maintained information that requires healthcare workers to shovel data from one pit to another despite the systemic burdens of doing so. Consider that on average it takes a care team 20 minutes to collect, validate, and document a patient’s medication history. Then, it takes another six minutes per patient to call pharmacies, other providers, and the patient’s family to confirm that information.1
Why Should We Care About Medication Data?
Every year up to 9,000 people in the United States die due to medication errors and up to 7 million patients are injured as a result of erroneously prescribed drugs, incorrectly dispensed drugs, or avoidable drug-drug interactions. All told, the U.S. spends more than $40 billion annually to care for those affected by medication-associated errors.2
The solution to redressing a considerable portion of these errors lies in providing access to reliable data, either by refining and transmitting existing information or by improving the process of capturing data at the point of care.
Where Does Data Get Stuck?
When a patient picks up a prescription, that simple act is the culmination of a complex, fractured process that touches almost every stakeholder in healthcare delivery and payment. Each of the actions below is necessary to ensure the right patient picks up the right drug at the right time with the right instructions on how to adhere to the prescribed medication therapy. When data gets stuck anywhere in the process, patients can experience delays in treatment or errors related to incomplete or incorrect medication information.
- Clinicians and care teams collect the patient’s medication history at the point of care and capture that data in the electronic health record (EHR) system, then generate the prescription, transmit it to the pharmacy, and transmit a payment claim to the insurance company.
- Pharmacists and pharmacies receive and review the patient’s prescription, then generate a record of the medication to dispense to the patient, the insurance carrier or pharmacy benefits manager (PBM), and the prescribing clinician.
- Insurance carriers and PBMs receive payment claims from clinicians and pharmacies and generate a record of claims that were paid.
- Patients maintain medication lists and share medication history and potential allergies with the care team.
When you consider all the steps involved, perhaps it’s no surprise that medication errors are a glaring example of systemic failure in the current healthcare environment.
Transforming Data Pits Into Flowing Streams
Fortunately, we are seeing technologies emerge that can streamline the process and protect patient safety. DrFirst’s SmartSuite℠ of AI-powered solutions codifies prescriptions and reconciles medication histories when exchanged between EHR systems, payers, and pharmacies. The result: Physicians, nurses, pharmacists, and other clinicians can access complete patient medication data that can trigger critical safety checks like drug interaction notifications or allergy alerts without having to manually enter all that data. For large-scale data migrations, SmartProcessor℠ solves data fidelity issues between disparate systems and formats, resulting in complete, clean, and consumable medication data for the receiving system and end users.
As the healthcare industry grapples with the massive volume of patient data that’s been created and collected over decades, there is a pressing need for new tools like these to make this vital information usable by EHRs and other systems. To get to the point where medication data flows seamlessly between each stakeholder and is delivered in a usable form to the patient and their care team members, we need to transform the quagmire of data pits into a system of effective data streams.
- The Downstream Effects of Fractured Medication Data, DrFirst, https://go.drfirst.com/hubfs/Partners/IG-Downstream-Effects-PARTNERS-Gen.pdf
- Tariq RA, Vashisht R, Sinha A, et al. Medication Dispensing Errors and Prevention. [Updated 2021 Nov 14]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan. https://www.ncbi.nlm.nih.gov/books/NBK519065/