Using Routinely Collected Data From the Network of Alcohol and Other Drugs Agencies Database to Evaluate the Impact of <scp>COVID</scp> ‐19 Lockdowns on Trends in Service Delivery in Outpatient Non‐Government Alcohol and Other Drug Treatment Services

BACKGROUND: The COVID-19 pandemic disrupted face-to-face alcohol and other drug (AOD) treatment services and prompted greater use of telehealth. This study measured the impact of COVID-19 on outpatient treatment episodes before, during, and after stay-at-home orders were introduced. METHODS: This observational study used routinely collected data from community-based non-government AOD services in New South Wales (NSW), Australia across 4 years (209 7-day intervals from January 1, 2019-January 2, 2023). Interrupted time-series analyses with seasonal autoregressive integrated moving average (ARIMA) modeling estimated weekly changes in outpatient treatment episodes associated with stay-at-home (lockdown) orders, including (1) commencements, (2) planned cessations, and (3) unplanned cessations. Episode counts were also examined by gender (male, female), age group (< 25 years, 25-59 years, ≥ 60 years), principal drug of concern (alcohol, amphetamines, cannabinoids, opioids, and other), and location (metropolitan and non-metropolitan). RESULTS: There were no significant level or trend changes in the overall number of episode commencements (ARIMA (2,0,0)(1,0,0), lockdown one: β_level = -814.85, p = 0.098; β_slope = 11.14, p = 0.127; lockdown two: β_level = 317.3, p = 0.427; β_slope = -3.47, p = 0.237), planned cessations (ARIMA (1,0,0)(0,0,1), lockdown one: β_level = -142.1, p = 0.66; β_slope = 1.16, p = 0.808; lockdown two: β_level = -199.07, p = 0.432; β_slope = 0.18, p = 0.932), or unplanned cessations (ARIMA (1,0,0), lockdown one: β_level = -92.4, p = 0.717; β_slope = 1.4, p = 0.711; lockdown two: β_level = -121.19, p = 0.563; β_slope = 0.53, p = 0.732) in outpatient non-government AOD services at either lockdown. For subgroups, during lockdown one, commencements per week increased for metropolitan participants (ARIMA (1,0,0) β_level = -725.12, p = 0.024; β_slope = 10.07, p = 0.035) and those with amphetamines (ARIMA(3,0,0)(1,0,0) β_level = -338.44, p = 0.036; β_slope = 4.68, p = 0.05) as their principal drug of concern. CONCLUSIONS: The introduction of COVID-19 lockdown measures did not appear to adversely impact the number of NSW non-government AOD outpatient treatment episodes delivered nor the likelihood of unplanned dropout. Our findings illustrate the likely role of telehealth in sustaining (and for some groups, perhaps temporarily increasing) AOD service provision during the COVID-19 pandemic. This highlights the sector's resilience in sustaining care under challenging circumstances.