Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study.

Background: Recently, internet hospitals have been emerging in China, saving patients time and money during the COVID-19 pandemic. In addition, pharmacy services that link doctors and patients are becoming essential in improving patient satisfaction. However, the existing internet hospital pharmacy service mode relies primarily on manual operations, making it cumbersome, inefficient, and high-risk. Objective: To establish an internet hospital pharmacy service mode based on artificial intelligence (AI) and provide new insights into pharmacy services in internet hospitals during the COVID-19 pandemic. Methods: An AI-based internet hospital pharmacy service mode was established. Initially, prescription rules were formulated and embedded into the internet hospital system to review the prescriptions using AI. Then, the "medicine pick-up code," which is a Quick Response (QR) code that represents a specific offline self-pick-up order, was created. Patients or volunteers could pick up medications at an offline hospital or drugstore by scanning the QR code through the window and wait for the dispensing machine or pharmacist to dispense the drugs. Moreover, the medication consultation function was also operational. Results: The established internet pharmacy service mode had four major functional segments: online drug catalog search, prescription preview by AI, drug dispensing and distribution, and AI-based medication consultation response. The qualified rate of AI preview was 83.65%. Among the 16.35% inappropriate prescriptions, 49% were accepted and modified by physicians proactively and 51.00% were passed after pharmacists intervened. The "offline self-pick-up" mode was preferred by 86% of the patients for collecting their medication in the internet hospital, which made the QR code to be fully applied. A total of 426 medication consultants were served, and 48.83% of them consulted outside working hours. The most frequently asked questions during consultations were about the internet hospital dispensing process, followed by disease diagnosis, and patient education. Therefore, an AI-based medication consultation was proposed to respond immediately when pharmacists were unavailable. Conclusion: The established AI-based internet hospital pharmacy service mode could provide references for pharmacy departments during the COVID-19 pandemic. The significance of this study lies in ensuring safe/rational use of medicines and raising pharmacists' working efficiency.

Survey about the use of clarithromycin in an ENT outpatient department of a tertiary hospital.

We undertook this survey about the use of clarithromycin in the Ear, Nose, and Throat (ENT) Outpatient Department of Fudan University Hospital to understand its utilization patterns and rational use. A survey of prescriptions given to outpatients was carried out, and detailed information of the patients, including age, sex, diagnosis, combined medication, and other information, was recorded in Excel spreadsheets. The rationale for each prescription was evaluated retrospectively. Based on our analysis, 82.5% of the clarithromycin prescriptions were for the treatment of rhinosinusitis. It was found that the parameters for the diagnosis of this condition were surprisingly broad and should have been more specific. In addition, the clarithromycin dosage regimen varied in clinical practice. For chronic rhinosinusitis, the duration of treatment was between 8 and 16 days, which was not sufficient. Moreover, clarithromycin was prescribed along with considerable numbers of pharmacotherapeutic anti-allergic drugs. Our survey indicated that improvements in the quality of clarithromycin prescriptions in otolaryngology outpatients should be made. Furthermore, the importance of medical education to patients should be emphasized. In addition, the interaction between clarithromycin and other anti-allergic drugs requires further investigation.

The effects of medication education and behavioral intervention on Chinese patients with epilepsy.

OBJECTIVES: The objectives of this study were to evaluate the effects of medication education and behavioral intervention on Chinese patients with epilepsy and to compare the difference between them. METHODS: A total of 109 patients with epilepsy who did not to take their antiepileptic drugs (AEDs) more than once were randomly assigned to two intervention groups: the medication education group (group I) and the medication education with behavioral intervention group (group II). Group I was initially provided with medication education in the form of oral education and written materials, and this education was reinforced by monthly calls from the pharmacist over the next six months. The behavioral intervention provided to group II consisted of a modified medication schedule which was based on cue-dose training therapy. The outcomes that were evaluated both in the beginning and in the end of the study included adherence, which was measured using the four-item Morisky Medication Adherence Scale (MMAS-4), the number of seizures, knowledge of AEDs, and the number of patients who missed a dose of their AEDs. Differences within and between the groups were analyzed. RESULTS: After intervention, the adherence and knowledge of AEDs increased greatly in all patients, and the number of patients who had seizures or missed AEDs decreased. However, no significant differences were observed between groups I and II. The observed changes were (group I vs group II, p value) increased adherence: 62.3% vs 64.3%, 0.827; increased knowledge of AEDs: 88.7% vs 80.4%, 0.231; and improved seizure control: 64.2% vs 64.3%, 0.988. In addition, the percentage of patients who forgot to take their AEDs decreased to 45.0% from more than 70%, and 44.9% of these patients took the missed AEDs as soon as they remembered. DISCUSSION: These findings clearly demonstrate that medication education and reinforced telephone calls from pharmacists can help to increase adherence to AEDs, the knowledge of patients regarding AEDs, and seizure control. However, the inclusion of a behavioral strategy that was easy to administer and use in this program did not lead to any significant effects on improving adherence. The results indicate that pharmacists can play an important role in improving the effects of medication regimens, but further research is required to identify strategies for improving adherence to behavioral theory.

Validation of Chinese version of the Morisky medication adherence scale in patients with epilepsy.

PURPOSE: This study aimed to validate a Chinese version of the Morisky Medication Adherence Scale (MMAS-8) in patients with epilepsy. The relationships between adherence, seizure frequency, and adverse effects were assessed using this method. METHODS: Data from patients diagnosed with epilepsy at the Department of Neurology of Huashan Hospital were collected between January and June 2013. To validate the MMAS-8, internal consistency, test-retest reliability, and factor analysis were calculated. Relationships between adherence, seizure frequency, and adverse effects were assessed using Pearson's correlation. RESULTS: One hundred and eleven patients were recruited. The MMAS-8 had moderate internal consistency (Cronbach's α=0.556) and good test-retest reliability (intraclass correlation coefficient=0.729). The MMAS-8 adherence rate was 79.2%. MMAS-8 adherence was negatively correlated with seizure frequency and adverse effects (r = -0.708, p<0.001; r = -0.484, p<0.001). CONCLUSION: The MMAS-8 scale can be used as a tool to assess medication adherence in Chinese patients with epilepsy. Better seizure control and lower rates of adverse effects were significantly correlated with higher adherence scores.

Self-reported adherence in patients with epilepsy who missed their medications and reasons for nonadherence in China.

OBJECTIVES: The objectives of this study were: (1) to evaluate self-reported adherence in adult patients with epilepsy in China who had missed taking their antiepileptic drugs (AEDs) at least once and (2) to determine why patients were not adherent to their medication to employ interventions targeted at barriers to adherence. METHODS: A questionnaire was used to collect the patients' demographic data, disease information, and reasons for why the patients did not take their AEDs. Adherence was also included as measured using a four-item Morisky questionnaire (Morisky-4 questionnaire). RESULTS: Of the 131 patients, 4.6%, 70.2%, and 25.2% showed high, medium, and low adherence, respectively. The reasons for nonadherence included forgetfulness (54.2%), being seizure-free for a period (48.9%), and fear of adverse drug effects (27.5%). CONCLUSIONS: Medium adherence was the predominant nonadherence pattern, and forgetfulness, being seizure-free for a period, and fear of adverse effects were the primary reasons for nonadherence to AEDs. To overcome barriers to nonadherence, it is essential to use tools that are sensitive to reasons for nonadherence.