Understanding tinnitus clinical care in the Veterans Health Administration and Department of Defense: Overview of survey results

Abstract: Purpose: In 2021, the Veterans Health Administration (VHA) and Department of Defense (DOD) Tinnitus Working Group conducted a survey of DOD and VHA clinicians to evaluate clinical services provided for tinnitus. Method: The online survey included a mix of multiple-choice and open-ended questions. Respondents included VHA and DOD health care providers in audiology, otolaryngology, mental health, and primary care, as well as DOD hearing conservation technicians. Quantitative and qualitative methods were used to analyze the data. Results: A total of 669 providers responded to this combined survey. Results indicated that compared to DOD and VHA providers in other fields, audiologists tended to be more confident and more aware of their role in tinnitus management. In terms of confidence and scope of practice, DOD mental health care providers were the group least familiar with tinnitus care. Other results explored herein include barriers to tinnitus care, facilitators for progressive tinnitus management programs, interventions and patient materials offered, new patient materials wanted, and respondents' preferred information sources and training methods. Conclusion: Survey results indicated that more directed education and support are needed to increase DOD and VHA clinicians' awareness of the need for tinnitus services and their roles in providing that care.

Read the full article
Report a problem with this article

Related articles

  • More for Researchers

    Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data

    Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.

    Mental Health Peer reviewed