Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis
Objective The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors.Method...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMJ Publishing Group
2017-12-01
|
| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/7/12/e018280.full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832540932686217216 |
|---|---|
| author | Livia Faes Lucas M Bachmann Martin K Schmid Michael A Thiel Rahel Buechi Nicolas S Bodmer Oliver Job Kenny R Lienhard |
| author_facet | Livia Faes Lucas M Bachmann Martin K Schmid Michael A Thiel Rahel Buechi Nicolas S Bodmer Oliver Job Kenny R Lienhard |
| author_sort | Livia Faes |
| collection | DOAJ |
| description | Objective The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors.Methods Systematic Review—MEDLINE, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until 15 December 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used inbuilt sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the reporting quality with the ’STAndards for the Reporting of Diagnostic accuracy studies' (STARD) statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarised.Results We screened 3296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % CI 0.56 to 0.94) and 0.89 (95 %CI 0.70 to 0.97) for specificity.Conclusions The diagnostic evidence of available health apps on Apple’s and Google’s app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.PROSPERO registration number 42016033049. |
| format | Article |
| id | doaj-art-ecf4ce7aa2f54671bc3fd9babad7eebc |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2017-12-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-ecf4ce7aa2f54671bc3fd9babad7eebc2025-02-04T12:00:17ZengBMJ Publishing GroupBMJ Open2044-60552017-12-0171210.1136/bmjopen-2017-018280Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysisLivia Faes0Lucas M Bachmann1Martin K Schmid2Michael A Thiel3Rahel Buechi4Nicolas S Bodmer5Oliver Job6Kenny R Lienhard72 Eye Clinic of the Cantonal Hospital of Lucerne, Lucerne, Switzerland2 Medignition Inc., Research Consultants, Zurich, SwitzerlandEye Clinic, Luzerner Kantonsspital, Luzern, SwitzerlandEye Clinic, Luzerner Kantonsspital, Luzern, Switzerland1 Eye Clinic, Cantonal Hospital of Lucerne, Lucerne, Switzerlanddoctoral student1 Eye Clinic, Cantonal Hospital of Lucerne, Lucerne, Switzerland3 Department of Information Systems, Faculty of Business and Economics, University of Lausanne, Lausanne, SwitzerlandObjective The number of mobile applications addressing health topics is increasing. Whether these apps underwent scientific evaluation is unclear. We comprehensively assessed papers investigating the diagnostic value of available diagnostic health applications using inbuilt smartphone sensors.Methods Systematic Review—MEDLINE, Scopus, Web of Science inclusive Medical Informatics and Business Source Premier (by citation of reference) were searched from inception until 15 December 2016. Checking of reference lists of review articles and of included articles complemented electronic searches. We included all studies investigating a health application that used inbuilt sensors of a smartphone for diagnosis of disease. The methodological quality of 11 studies used in an exploratory meta-analysis was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the reporting quality with the ’STAndards for the Reporting of Diagnostic accuracy studies' (STARD) statement. Sensitivity and specificity of studies reporting two-by-two tables were calculated and summarised.Results We screened 3296 references for eligibility. Eleven studies, most of them assessing melanoma screening apps, reported 17 two-by-two tables. Quality assessment revealed high risk of bias in all studies. Included papers studied 1048 subjects (758 with the target conditions and 290 healthy volunteers). Overall, the summary estimate for sensitivity was 0.82 (95 % CI 0.56 to 0.94) and 0.89 (95 %CI 0.70 to 0.97) for specificity.Conclusions The diagnostic evidence of available health apps on Apple’s and Google’s app stores is scarce. Consumers and healthcare professionals should be aware of this when using or recommending them.PROSPERO registration number 42016033049.https://bmjopen.bmj.com/content/7/12/e018280.full |
| spellingShingle | Livia Faes Lucas M Bachmann Martin K Schmid Michael A Thiel Rahel Buechi Nicolas S Bodmer Oliver Job Kenny R Lienhard Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis BMJ Open |
| title | Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis |
| title_full | Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis |
| title_fullStr | Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis |
| title_full_unstemmed | Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis |
| title_short | Evidence assessing the diagnostic performance of medical smartphone apps: a systematic review and exploratory meta-analysis |
| title_sort | evidence assessing the diagnostic performance of medical smartphone apps a systematic review and exploratory meta analysis |
| url | https://bmjopen.bmj.com/content/7/12/e018280.full |
| work_keys_str_mv | AT liviafaes evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT lucasmbachmann evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT martinkschmid evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT michaelathiel evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT rahelbuechi evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT nicolassbodmer evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT oliverjob evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis AT kennyrlienhard evidenceassessingthediagnosticperformanceofmedicalsmartphoneappsasystematicreviewandexploratorymetaanalysis |