Healthcare providers across the world are confronting the growing opioid epidemic within their communities and patient populations. In the United States, drug overdose deaths numbered more than 100,000 during the 12-month period ending in April 2021, a 28.5% increase from the prior year, according to the Center for Disease Control. It’s estimated 75,673 of those overdose deaths were opioid related.
To address the opioid epidemic, we must equip clinicians with tools that provide a comprehensive picture of a patient’s care history so they can make informed risk assessments and care decisions. To achieve this, healthcare leaders must prioritize interoperability by taking advantage of the health information exchanges in place and relentlessly focusing on optimizing data usability.
A comprehensive view of a patient’s health history, combined with the right analytics, intuitive workflows and enhanced processes, can offer clinicians key insights into appropriate opioid prescribing and effective pain management options.
Electronic health records (EHRs) are foundational in providing clinicians with the information and insights needed to make informed care decisions.
For example, many EHRs can integrate controlled substance prescribing insights from state prescription drug monitoring programs (PDMPs) into the workflow. A comprehensive view of a patient’s opioid-related risk, including prescription history and refill frequency, past prescribers, and dispensing pharmacies can help identify opioid use disorder and abuse.
Alternatively, this visibility helps prescribers recognize patients who are opioid naïve (those who aren’t taking opioids daily) and consider that factor when determining the best pain management plan. Integration directly into the EHR reduces the burden of navigating to multiple screens and a separate log-in page. Integration into the EHR also enables health systems to meet state regulatory requirements and provide necessary reporting to track PDMP usage.
EHRs can also aggregate information beyond what’s available in state PDMPs, creating a longitudinal patient record that provides clinicians with visibility into the care a patient received across the continuum. Integrating that information into the clinical workflow provides visibility to past problems and diagnoses. Other clinical information available from outside records, including labs and medications, further round out the prescriber’s understanding of a patient’s health history.
Electronic prescribing for controlled substances (EPCS) is another tactic to support safe prescribing. Where PDMPs provide visibility to medication dispensed, EPCS documents a prescription being written. Built into EHR workflows, this process enables providers to securely communicate with pharmacies. EPCS contributes to a comprehensive view of the patient’s record by discretely documenting prescriptions into the chart.
To infuse transparency and accountability into prescribing for controlled substances, EPCS will soon be required by federal regulation. The Centers for Medicare and Medicaid Services (CMS) established an enforcement date for the beginning of 2023. As of January 1, 2022, 30 U.S. states – including many states with the highest rates of drug-related death – have chosen to enact legislation addressing EPCS in advance of the federal mandate. Several states have reported a decline in drug-related deaths following the regulation.
For organizations that don’t fall under mandates yet, CMS is encouraging timely adoption of electronic workflows to ensure that controlled substance prescriptions are documented discretely in the EHR.
In addition to providing a longitudinal view of the patient record, EHRs provide clinical decision support (CDS) to help caregivers make better informed treatment decisions. CDS functionality includes the ability to:
EHRs can guide providers using medications to treat opioid use disorders.
While the PDMP surfaces patient data to support providers and pharmacists nearly in real-time, analytic insights from EPCS into provider behaviors can help leaders manage opioid-related workflows. Information gleaned from analysis of prescribing and PDMP usage can identify the need for:
Making providers aware of their prescribing patterns compared to their peers has shown to change behavior. A joint white paper from EHRA and ECRI outlines actionable measures healthcare organizations can take to reduce risk by addressing prescribing behavior.
Though we’ve made strides over the past several years, opportunities to advance opioid-related care with technology still exist.
Patient matching can be challenging when state PDMPs contain duplicates, potentially impacting the accuracy of the data and the provider’s ability to view it.
Many state PDMPs do not allow hospitals to store controlled substance prescribing data in the EHR discretely; therefore, hospitals rely on integration through health information exchanges to push prior diagnoses and problems, home medications and current prescriptions into the EHR.
Data usability is another concern. When outside records are pulled into the native workflow, they’re often disorganized. This burdens providers with a manual reconciliation process before they can glean useful information and insights from the patient’s health history. Industry leaders are advancing technology to alleviate this burden.
Additionally, PDMP data is limited to prescription data, which doesn’t always provide a full picture of a patient’s opioid use if they’ve turned to other resources to manage pain. As caregivers, we need to do more than simply not prescribe opioids. We need to put in place robust screening processes to help identify patients who may turn to increasingly deadly non-prescription alternatives, according to the CDC. In tandem, we need to equip providers with the tools and programs to offer alternative pain management solutions and opioid use disorder treatment to patients identified as high risk.
On a positive note, advancements in machine-learning technology offer promise. Interoperability offers access to a richer set of patient information, which EHRs can leverage through machine-learning algorithms to empower caregivers to deliver better patient outcomes. Healthcare information technology companies can use machine-learning models to identify a patient’s risk of future opioid-related harm.
Machine-learning based predictive models are considered a new diagnostic or lab test. Instead of taking a blood sample or asking a patient what their symptoms are, they take a patient’s history and make an educated guess regarding risk based on information in the EHR. The goal is to help caregivers make confident decisions at the point of care to reduce future risk of complications.
Though EHRs provide clinicians with insights into provide optimal patient care amid the opioid epidemic, we must not overlook the importance of governance in maximizing the impact of technology. Healthcare organizations that have had success mitigating the opioid crisis developed comprehensive approaches that include:
The opioid crisis is a society-wide problem requiring creative solutions from all sectors, including government, social services and the public. Technology available today can support prescribers in managing safe prescribing of opioids at the point of care and prevent fraud and abuse. We must make these technologies widely available and useful to clinicians so they can continue to provide healing support to their patients.
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