Mobile apps for detecting falsified and substandard drugs: A systematic review

被引:5
|
作者
Ciapponi, Agustin [1 ,2 ]
Donato, Manuel [1 ,2 ]
Gulmezoglu, A. Metin [3 ]
Alconada, Tomas [1 ,2 ]
Bardach, Ariel [2 ]
机构
[1] Consejo Nacl Invest Cient & Tecn, Inst Efectividad Clin & Sanitaria IECS, Buenos Aires, DF, Argentina
[2] Consejo Nacl Invest Cient & Tecn, IECS, Ctr & Invest Epidemiol & Salud Publ CIESP, Buenos Aires, DF, Argentina
[3] WHO, Dept Reprod Hlth & Res, UNDP UNFPA UNICEF WHO World Bank Special Programm, Geneva, Switzerland
来源
PLOS ONE | 2021年 / 16卷 / 02期
关键词
INTERVENTIONS; COMBAT;
D O I
10.1371/journal.pone.0246061
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The use of substandard and counterfeit medicines (SCM) leads to significant health and economic consequences, like treatment failure, rise of antimicrobial resistance, extra expenditures of individuals or households and serious adverse drug reactions including death. Our objective was to systematically search, identify and compare relevant available mobile applications (apps) for smartphones and tablets, which use could potentially affect clinical and public health outcomes. We carried out a systematic review of the literature in January 2020, including major medical databases, and app stores. We used the validated Mobile App Rating Scale (MARS) to assess the quality of apps, (1 worst score, 3 acceptable score, and 5 best score). We planned to evaluate the accuracy of the mobile apps to detect SCM. We retrieved 335 references through medical databases and 42 from Apple, Google stores and Google Scholar. We finally included two studies of the medical database, 25 apps (eight from the App Store, eight from Google Play, eight from both stores, and one from Google Scholar), and 16 websites. We only found one report on the accuracy of a mobile apps detecting SCMs. Most apps use the imprint, color or shape for pill identification, and only a few offer pill detection through photographs or bar code. The MARS mean score for the apps was 3.17 (acceptable), with a maximum of 4.9 and a minimum of 1.1. The 'functionality' dimension resulted in the highest mean score (3.4), while the 'engagement' and 'information' dimensions showed the lowest one (3.0). In conclusion, we found a remarkable evidence gap about the accuracy of mobile apps in detecting SCMs. However, mobile apps could potentially be useful to screen for SCM by assessing the physical characteristics of pills, although this should still be assessed in properly designed research studies.
引用
收藏
页数:13
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