Smokefree policy and medication dispensing for people in prison: interrupted time series analysis

Abstract

Abstract Background Previous evaluations of smokefree prison policies have suggested improvements in self-rated health and some smoking-related symptoms. No studies to date have investigated impacts on medication use as proxy measures of objective ill-health or as indicators of potential negative unintended consequences. These is limited evidence to date on these important outcomes. Methods We obtained from NHS National Services Scotland aggregate data on medication items dispensed in prisons, based on individual named patient medication records, and from the Scottish Prison Service data on the prison population, for the period Jan 2013-Nov 2019. Items of interest comprised those for smoking cessation (varenicline and buproprion); nicotine replacement; specific smoking-related health conditions (glyceryl trinitrate; inhaled bronchodilators and steroids; antibiotics; chloramphenicol eye drops; and proton pump inhibitors and H2 receptor antagonists), and potential unintended mental health consequences (anti-depressants). We also included a set of negative controls for which dispensing was not expected to be affected by the new smokefree policy (anticonvulsants, excluding pregabalin and gabapentin). Analyses were undertaken using AutoRegressive Integrated Moving Average (ARIMA) time series methods, with the dates of the policy's announcement and of implementation included as pre-specified breakpoints. Results The results of ARIMA modelling of medication dispensing are confidential until May 2020 due to their sensitivity and will be available to present at WCPH 2020. Conclusions The use of routinely available dispensing data as an indicator of objective health impacts and potential negative unintended consequences provides novel insights into the effectiveness of smokefree prison policies. Results will be of interest to international jurisdictions considering such policies and to those seeking to harness the potential of administrative data for natural experiments.