Automated identification of health apps' medical specialties and promoters from the store webpages

The aim of this study was to develop automated methods, based on text analytics, for extracting information from the apps' webpages on the app stores and identify relevant apps' features such as the medical specialty and promoter. In this preliminary study, we classified a sample of more than 66000 apps from the US iTunes store into 18 medical specialties and seven types of promoters. Of the ∼66000 apps analyzed over 18 specialties, we found that 24.1% were relevant to Nutrition, 23.9% to General Medicine, and 15.7% to Pharmacology, whereas less than 1.5% of apps were relevant to specialties such as Rheumatology, Radiology, Diabetes, Respiratory, Vision, and Sleep Healthcare. The analysis of promoters showed that Manufacturers and Software Houses and Independent Developers promoted 99% of apps combined, whereas promoters in the healthcare and science areas (e.g., Government Services, Healthcare Providers, or Scientific and Educational Organizations) still play a minor role. This study highlighted interesting trends and open opportunities in the field of health apps and suggested that the proposed approach might be a basis for future developments of support tools for informed, aware selection and adoption of health apps by patients and healthcare professionals.