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Circ Cardiovasc Qual Outcomes. 2017 Mar;10(3). pii: e003326. doi: 10.1161/CIRCOUTCOMES.116.003326.

Smartphone-Based Geofencing to Ascertain Hospitalizations.

Author information

1
From the Division of Cardiology (K.T.N., J.E.O., M.N., R.A.G., C.M., A.H.F., C.M., L.B., M.A.C., G.M.M) and Department of Epidemiology and Biostatistics (M.J.P.), University of California, San Francisco; Ginger.io, San Francisco, CA (L.K., S.M.).
2
From the Division of Cardiology (K.T.N., J.E.O., M.N., R.A.G., C.M., A.H.F., C.M., L.B., M.A.C., G.M.M) and Department of Epidemiology and Biostatistics (M.J.P.), University of California, San Francisco; Ginger.io, San Francisco, CA (L.K., S.M.). marcusg@medicine.ucsf.edu.

Abstract

BACKGROUND:

Ascertainment of hospitalizations is critical to assess quality of care and the effectiveness and adverse effects of various therapies. Smartphones, mobile geolocators that are ubiquitous, have not been leveraged to ascertain hospitalizations. Therefore, we evaluated the use of smartphone-based geofencing to track hospitalizations.

METHODS AND RESULTS:

Participants aged ≥18 years installed a mobile application programmed to geofence all hospitals using global positioning systems and cell phone tower triangulation and to trigger a smartphone-based questionnaire when located in a hospital for ≥4 hours. An in-person study included consecutive consenting patients scheduled for electrophysiology and cardiac catheterization procedures. A remote arm invited Health eHeart Study participants who consented and engaged with the study via the internet only. The accuracy of application-detected hospitalizations was confirmed by medical record review as the reference standard. Of 22 eligible in-person patients, 17 hospitalizations were detected (sensitivity 77%; 95% confidence interval, 55%-92%). The length of stay according to the application was positively correlated with the length of stay ascertained via the electronic medical record (r=0.53; P=0.03). In the remote arm, the application was downloaded by 3443 participants residing in all 50 US states; 243 hospital visits at 119 different hospitals were detected through the application. The positive predictive value for an application-reported hospitalization was 65% (95% confidence interval, 57%-72%).

CONCLUSIONS:

Mobile application-based ascertainment of hospitalizations can be achieved with modest accuracy. This first proof of concept may ultimately be applicable to geofencing other types of prespecified locations to facilitate healthcare research and patient care.

KEYWORDS:

fast food; hospitalization; internet; pharmacies; smartphone

PMID:
28325751
PMCID:
PMC5363280
DOI:
10.1161/CIRCOUTCOMES.116.003326
[Indexed for MEDLINE]
Free PMC Article

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