Home > ASME Articles > Using Performance Data and Quality Improvement to Enhance Project ECHO Interventions
Rising rates of deaths from opioid overdoses in the U.S. underscore the importance of expanding access to medications to treat opioid use disorder (MOUD), like methadone, buprenorphine, and naloxone.
Barriers to accessing methadone, however, disproportionately impact rural areas, where clinics can be few and far between, and naltrexone use has been limited, due to challenges with getting patients successfully started on the medication. Buprenorphine, on the other hand, has fewer barriers and can be prescribed in the kinds of general medical settings common in rural areas.
That said, the barriers to buprenorphine treatment that do exist can be challenging to overcome, like lack of confidence and inadequate training for prescribers, and a lack of access to experts for guidance and support. Interventions like Project ECHO, which connect providers to subspecialty teams of experts via telemedicine, can enhance staff training and provide that expertise.
Adding performance data collection to inform quality improvement (QI) may improve Project ECHO outcomes, but is that type of data collection and QI doable in these settings?
For this study, part of NIDA Clinical Trials protocol CTN-0103, 18 New Hampshire clinics participating in a Project ECHO were offered a supplemental project exploring the feasibility of performance data collection to inform QI that aimed increase alignment with best practices (ECHO-AMPLIFI). An end-of-project survey was conducted to shed light on clinic staff perceptions of how useful and acceptable they found the program.
Five of the 18 participating clinics joined the training project, four of which served rural communities. All five clinics met the criteria for engagement, as each clinic attended at least one training session, submitted at least one month of performance data, and completed at least one QI initiative.
Performance data measures looked at naloxone overdose reversal device access, practice workflow, and behavioral aspects of OUD management like screening, buprenorphine initiation and retention.
After review of data, clinics implemented several different QI initiatives, including the addition of an ICD-10 diagnostic worksheet in the electronic health record (EHR) system to promote alignment with best practice, development of an entry-to-care workflow designating the clinical team members responsible for specific tasks, or modification of the clinic EHR template for buprenorphine visits to include dates of PDMP queries and naloxone distribution to improve the frequency of naloxone distribution and reduce the time spent on redundant PDMP queries.
Survey results showed that while clinic staff found the training and data collection useful, there were several barriers to collecting that data, including lack of staff time, issues with the functionality of the data collection tools, and challenges with clinic electronic health record systems being unable to document some of the performance metrics.
Though barriers prevented clinics from collecting complete data sets, clinics demonstrated high motivation to make improvements to better align care processes with best practices for buprenorphine treatment. Results of this study suggest that training clinics to monitor their performance and base quality improvement initiatives on that data could improve clinical best practice and, in turn, treatment outcomes for people on MOUD.