# Comparative Analysis of Prescriptions and Pharmacy Services in Internet-Based Psychiatric Hospital During and After the COVID-19 Pandemic: Retrospective Cross-Sectional Observational Study

## TL;DR

This study analyzed prescription and pharmacy service trends in an online psychiatric hospital during and after the pandemic, finding changes in patient demographics and drug prescriptions.

## Contribution

The study introduces a novel combination of descriptive and analytic statistical methods to evaluate internet-based psychiatric hospital services during the pandemic.

## Key findings

- Prescription numbers increased significantly during the pandemic phase but not in the postpandemic phase.
- Female patients and young adults aged 18-40 were the majority in both pandemic and postpandemic phases.
- Audit times for prescriptions were faster during the pandemic compared to the postpandemic period.

## Abstract

The COVID-19 pandemic has significantly accelerated the development of internet-based hospitals and telepharmacy services. However, their characteristics and evolving trends remain unclear.

This study aimed to assess the associations between distinct pandemic phases and the number of prescriptions, patients’ demographic characteristics, drug and disease distribution patterns, and pharmacy service indicators in our internet-based psychiatric hospital.

In this retrospective cross-sectional observational study, we conducted a full-sample census of prescriptions issued in the internet-based psychiatric hospital of the Affiliated Brain Hospital of Guangzhou Medical University during November 2020-December 2023. Cancelled, pending, and test prescriptions were excluded, and no sampling procedure was used. The research timespan was divided into pandemic and postpandemic phases, and trends of prescriptions were evaluated using interrupted time series analysis. Outcome measures, including patients’ sex and age, diagnosed disease, drug type, pharmacist audit time, and audit outcome, were analyzed using the bootstrap method, Pearson chi-square analysis, and multinomial logistic regression.

The segmented regression model revealed significant positive correlation between months and number of prescriptions during pandemic phase (F1,16=6.96; P=.02), whereas no significant correlation was detected in postpandemic phase (F1,10=2.77; P=.13). Descriptive analysis with bootstrap method revealed that female population were the majority in the pandemic phase (7297/11,812, 61.78%; 95% CI 60.91%-62.70%) and the postpandemic phase (3520/5518, 63.79%; 95% CI 62.58%-65.18%). Young adults aged 18-40 years were the predominant population in the pandemic phase (5606/11,812, 47.46%; 95% CI 46.63%-48.39%) and postpandemic phase (2657/5518, 48.15%; 95% CI 46.79%-49.37%). Depressive disorder and quetiapine were the most frequently diagnosed disease and prescribed drug in both pandemic phases, respectively. The majority of prescriptions were audited within 5 minutes during the pandemic phase (5999/11,812, 50.79%; 95% CI 49.89%-51.65%), while most prescriptions were audited within 1-12 hours in the postpandemic phase (2031/5518, 36.81%; 95% CI 35.61%-37.95%). Pearson chi-square analysis and multinomial logistic regression indicated that variables positively correlated with pandemic phases included female (P=.01; odds ratio [OR] 1.09, 95% CI 1.02-1.17), aged ≤17 years (P<.001; OR 2.20, 95% CI 1.90-2.54), aged 18-40 years (P<.001; OR 1.59, 95% CI 1.38-1.83), audit time between 12 and 24 hours (P=.02; OR 6.26, 95% CI 1.38-28.49), and approved outcome (P=.03; OR 3.97, 95% CI 1.19-13.26). The audit time ≤5 minutes (P=.049; OR 0.22, 95% CI 0.05-0.99) was negatively correlated with the pandemic phases.

This study innovatively applied descriptive and analytic statistical methods to evaluate the associations between different pandemic phases and the prescriptions and pharmacy services in an internet-based psychiatric hospital. This study addressed limitations of existing research through a larger sample size, longer research timespan, and analytic statistical methods. This study demonstrated early warning indicators and replicable analytic methods for other medical institutions and offered implications in optimizing the efficiency of pharmacy services.