Feasibility of a Novel COVID-19 Telehealth Care Management Program Among Individuals Receiving Treatment for Opioid Use Disorder: Analysis of a Pilot Program
Bibliographic record
Abstract
BACKGROUND: The emergence of COVID-19 exacerbated the existing epidemic of opioid use disorder (OUD) across the United States due to the disruption of in-person treatment and support services. Increased use of technology including telehealth and the development of new partnerships may facilitate coordinated treatment interventions that comprehensively address the health and well-being of individuals with OUD. OBJECTIVE: The analysis of this pilot program aimed to determine the feasibility of delivering a COVID-19 telehealth care management program using SMS text messages for patients receiving OUD treatment. METHODS: Eligible individuals were identified from a statewide opioid treatment program (OTP) network. Those who screened positive for COVID-19 symptoms were invited to connect to care management through a secure SMS text message that was compliant with Health Insurance Portability and Accountability Act standards. Care management monitoring for COVID-19 was provided for a period of up to 14 days. Monitoring services consisted of daily SMS text messages from the care manager inquiring about the participant's physical health in relation to COVID-19 symptoms by confirming their temperature, if the participant was feeling worse since the prior day, and if the participant was experiencing symptoms such as coughing or shortness of breath. If COVID-19 symptoms worsened during this observation period, the care manager was instructed to refer participants to the hospital for acute care services. The feasibility of the telehealth care management intervention was assessed by the rates of adoption in terms of program enrollment, engagement as measured by the number of SMS text message responses per participant, and retention in terms of the number of days participants remained in the program. RESULTS: Between January and April 2021, OTP staff members referred 21 patients with COVID-19 symptoms, and 18 (82%) agreed to be contacted by a care manager. Participants ranged in age from 27 to 65 years and primarily identified as female (n=12, 67%) and White (n=15, 83%). The majority of participants were Medicaid recipients (n=14, 78%). There were no statistically significant differences in the demographic characteristics between those enrolled and not enrolled in the program. A total of 12 (67%) patients were enrolled in the program, with 2 (11%) opting out of SMS text message communication and choosing instead to speak with a care manager verbally by telephone. The remaining 10 participants answered a median of 7 (IQR 4-10) SMS text messages and were enrolled in the program for a median of 9 (IQR 7.5-12) days. No participants were referred for acute care services or hospitalized during program enrollment. CONCLUSIONS: These results demonstrate the feasibility of a novel telehealth intervention to monitor COVID-19 symptoms among OTP patients in treatment for OUD. Further research is needed to determine the applicability of this intervention to monitor patients with comorbid chronic conditions in addition to the acceptability among patients and providers using the SMS text messaging modality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".