RESUMO
Background: Inappropriate medication use is common around the world, particularly among older patients, and, despite potentially being preventable, often leads to adverse clinical and economic outcomes. However, there is a dearth of information regarding this prominent issue in China. Objectives: To evaluate the extent to which the physician can correctly identify potentially inappropriate medication (PIM) in older patients and to understand physicians' attitudes towards improving PIM knowledge. Methods: An online, cross-sectional survey was conducted anonymously among practicing physicians in China from November through December 2020. Knowledge of PIM was accessed using seven clinical vignettes covering a wide variety of therapeutic areas. Source of information and perceived barriers regarding PIM were also evaluated. We performed the ordinary least square regression analysis to understand the potential factors related to physicians' knowledge of PIM. Results: A total of 597 study participants were included in the analysis. More than half of them had never heard of any screening tool for PIMs (n = 328, 54.9%) and the most frequently acknowledged tool was the China PIM Criteria (n = 259, 43.4%). For the seven clinical vignettes testing physicians' knowledge on the medications that should be generally avoided in older patients, the mean score was 2.91 points out of 7 (SD: 1.32), with the median score of three points (IQR: 2-4). Only one-third of the respondents were feeling confident when prescribing for older patients (n = 255, 35.08%). Package inserts have been used as the major source of PIM information (always, n = 177, 29.65%; frequently, n = 286, 47.91%). Perceived barriers to appropriate prescribing include polypharmacy (n = 460, 77.05%), lack of formal education on prescribing for the older patients (n = 428, 71.69%). Conclusion: In this online survey evaluating physicians' ability to detect PIM for older patients, approximately 40% of PIM were recognized, suggesting an insufficient level of knowledge about appropriate prescribing.
RESUMO
BACKGROUND: As a computerized drug-drug interaction (DDI) alert system has not been widely implemented in China, health care providers are relying on mobile health (mHealth) apps as references for checking drug information, including DDIs. OBJECTIVE: The main objective of this study was to evaluate the quality and content of mHealth apps supporting DDI checking in Chinese app stores. METHODS: A systematic review was carried out in November 2020 to identify mHealth apps providing DDI checking in both Chinese iOS and Android platforms. We extracted the apps' general information (including the developer, operating system, costs, release date, size, number of downloads, and average rating), scientific or clinical basis, and accountability, based on a multidimensional framework for evaluation of apps. The quality of mHealth apps was evaluated by using the Mobile App Rating Scale (MARS). Descriptive statistics, including numbers and percentages, were calculated to describe the characteristics of the apps. For each app selected for evaluation, the section-specific MARS scores were calculated by taking the arithmetic mean, while the overall MARS score was described as the arithmetic mean of the section scores. In addition, the Cohen kappa (κ) statistic was used to evaluate the interrater agreement. RESULTS: A total of 7 apps met the selection criteria, and only 3 included citations. The average rating score for Android apps was 3.5, with a minimum of 1.0 and a maximum of 4.9, while the average rating score for iOS apps was 4.7, with a minimum of 4.2 and a maximum of 4.9. The mean MARS score was 3.69 out of 5 (95% CI 3.34-4.04), with the lowest score of 1.96 for Medication Guidelines and the highest score of 4.27 for MCDEX mobile. The greatest variation was observed in the information section, which ranged from 1.41 to 4.60. The functionality section showed the highest mean score of 4.05 (95% CI 3.71-4.40), whereas the engagement section resulted in the lowest average score of 3.16 (95% CI 2.81-3.51). For the information quality section, which was the focus of this analysis, the average score was 3.42, with the MCDEX mobile app having the highest score of 4.6 and the Medication Guidelines app having the lowest score of 1.9. For the overall MARS score, the Cohen interrater κ was 0.354 (95% CI 0.236-0.473), the Fleiss κ was 0.353 (95% CI, 0.234-0.472), and the Krippendorff α was 0.356 (95% CI 0.237-0.475). CONCLUSIONS: This study systematically reviewed the mHealth apps in China with a DDI check feature. The majority of investigated apps demonstrated high quality with accurate and comprehensive information on DDIs. However, a few of the apps that had a massive number of downloads in the Chinese market provided incorrect information. Given these apps might be used by health care providers for checking potential DDIs, this creates a substantial threat to patient safety.
