These days you cannot have a comprehensive discussion about the U.S. healthcare system without mentioning the opioid crisis — and chances are you don’t have to look beyond your family and friends to find someone who has been affected by it.
The Centers for Disease Control and Prevention reports that in 2016, there were more than 63,600 overdose deaths in the United States, and just over 42,200 (approximately 67 percent) were related to opioids. The epidemic has even moved Congress to take a bipartisan approach to the issue. In June 2018, the House of Representatives passed the most expansive opioid-related package to date, which combines 58 bills into a new bill titled the Substance Use-Disorder Prevention that Promotes Opioid Recovery and Treatment (SUPPORT) for Patients and Communities Act. On Sept. 17, the Senate passed the bill with changes.
The SUPPORT bill, in addition to $4 billion in funding from the Centers for Medicare & Medicaid Services for opioid addiction and recovery, is a good start. But much of the substance of the SUPPORT bill and Congress’s other efforts focuses primarily on treatment options, with only a minor emphasis on the value of identifying the risk of opioid misuse before addiction occurs.
While ensuring access to good treatment programs and facilities throughout the country, healthcare stakeholders should complement these efforts by leveraging data and technology to identify and address the risks of opioid misuse before addiction occurs. A comprehensive approach to managing the risk of opioid misuse at all phases of the addiction cycle will be the key to realizing a material improvement in opioid-related abuse and deaths.
Identifying High-Risk Patients
Leveraging data will be essential to identifying the potential for opioid misuse before it occurs or early in the addiction cycle. Identifying risks upstream in the patient care cycle can be facilitated by analyzing demographics, claims, medical records, and other data sources to identify potential social and medical determinants for opioid dependency, such as gender, age, injury, current prescriptions, and coexisting medical conditions.
Individuals identified as being at high risk for opioid misuse can be enrolled in an education program or in specialized care management to help ensure they are aware of and adhere to safe prescription medication usage. Data on social and medical determinants also can be combined with actual claims data (e.g., number of refills, overlapping controlled substances, number of prescribers, dosages exceeding morphine equivalents, duration of the prescription) to identify patients at risk of or dealing with opioid addiction.
Interventions that can help stave off opioid misuse by high-risk patients include:
- Monitoring after hospital discharge to improve treatment adherence and emergency room avoidance
- Chronic-condition and pain management programs
- Preventive care and screenings for early detection
- Medication adherence programs
Screening for Fraud and Abuse
Data also can be harnessed to identify cases of potential fraud or abusive appropriation or disbursement of opioids.
On the patient side, claims data can reveal instances of doctor shopping (where patients access opioid subscriptions from several prescribers, all of whom are unaware of the other providers that are treating the patient). A report by the Office of the Inspector General of the U.S. Department of Health and Human Services cited an example in which a Medicare enrollee received 73 prescriptions for opioids from 11 prescribers, filled at 20 different pharmacies, over the course of a year. While this example is extreme, identifying patients who obtain opioids from multiple prescribers can be a risk indicator that warrants patient outreach, education, and care management early in the patient’s opioid-access cycle.
Claims data also can be used to identify abuses by prescribers and pharmacies, whether intentional or inadvertent. Indicators of potential opioid distribution abuse include outliers relative to benchmarks in opioid dose levels and volumes, by pharmacy and provider.
Aggregating medical and pharmacy claims data also can reveal pharmacy-provider relationships that may have aberrant opioid distribution patterns, as well as practitioners who inappropriately prescribe or disperse drugs without a medical examination. Addressing instances of prescribing and disbursement abuse through provider education (in the case of inadvertent abuse) or legal action (in the case of fraud) will help reduce inappropriate opioid access that leads to addiction.
To identify certain aberrant prescribing and patient behaviors related to opioids, some states have implemented prescription drug monitoring programs (PDMPs), which are electronic databases that track controlled-substance prescriptions within a state. The programs can be useful in identifying drug-seeking behaviors such as doctor shopping, but they also have limitations — including the need for providers to check the database before prescribing, which may not always occur. Additionally, pharmacies enter dispensing data at various intervals, so the database may not have the most current information available.
Still, PDMPs will play a role in fighting the epidemic, especially if supplemented by broader analytical tools that examine other risk variables: comorbid and chronic conditions, social determinants, and the relationships between providers, prescribers, pharmacies, and patients.
An Issue that Hits Home
Coupled with ongoing efforts to improve access to effective treatment programs, data-driven initiatives that identify opioid misuse risk and that address risk factors and causes will be essential to achieve a meaningful reduction in opioid-related overdose and death rates. The statistics are grim, but this is not an insurmountable task. Other deadly conditions, such as smallpox and polio, were mitigated by medical technology and sound policy.
I lost my son to the opioid epidemic. Although it is too late for my family, I look forward to the day when no one else has to suffer such a loss.
Editor’s Note: A version of this post originally appeared in HFMA’s Leadership E-newsletter and has been published here with permission from HFMA Learning Solutions, Inc., a subsidiary of the Healthcare Financial Management Association.