<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Zhang J</submitter><funding>Swiss National Science Foundation</funding><pagination>e11896</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6315242</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>6(12)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Mobile health (mHealth) technologies have the potential to bring health care closer to people with otherwise limited access to adequate health care. However, physiological monitoring using mobile medical sensors is not yet widely used as adding biomedical sensors to mHealth projects inherently introduces new challenges. Thus far, no methodology exists to systematically evaluate these implementation challenges and identify the related risks.&lt;h4>Objective&lt;/h4>This study aimed to facilitate the implementation of mHealth initiatives with mobile physiological sensing in constrained health systems by developing a methodology to systematically evaluate potential challenges and implementation risks.&lt;h4>Methods&lt;/h4>We performed a quantitative analysis of physiological data obtain</pubmed_abstract><journal>JMIR mHealth and uHealth</journal><pubmed_title>Data Integrity-Based Methodology and Checklist for Identifying Implementation Risks of Physiological Sensing in Mobile Health Projects: Quantitative and Qualitative Analysis.</pubmed_title><pmcid>PMC6315242</pmcid><funding_grant_id>150640</funding_grant_id><pubmed_authors>Hartinger SM</pubmed_authors><pubmed_authors>Zhang J</pubmed_authors><pubmed_authors>Tushaus L</pubmed_authors><pubmed_authors>Mausezahl D</pubmed_authors><pubmed_authors>Moreo M</pubmed_authors><pubmed_authors>Verastegui H</pubmed_authors><pubmed_authors>Karlen W</pubmed_authors><pubmed_authors>Nuno Martinez N</pubmed_authors></additional><is_claimable>false</is_claimable><name>Data Integrity-Based Methodology and Checklist for Identifying Implementation Risks of Physiological Sensing in Mobile Health Projects: Quantitative and Qualitative Analysis.</name><description>&lt;h4>Background&lt;/h4>Mobile health (mHealth) technologies have the potential to bring health care closer to people with otherwise limited access to adequate health care. However, physiological monitoring using mobile medical sensors is not yet widely used as adding biomedical sensors to mHealth projects inherently introduces new challenges. Thus far, no methodology exists to systematically evaluate these implementation challenges and identify the related risks.&lt;h4>Objective&lt;/h4>This study aimed to facilitate the implementation of mHealth initiatives with mobile physiological sensing in constrained health systems by developing a methodology to systematically evaluate potential challenges and implementation risks.&lt;h4>Methods&lt;/h4>We performed a quantitative analysis of physiological data obtain</description><dates><release>2018-01-01T00:00:00Z</release><publication>2018 Dec</publication><modification>2025-04-06T23:38:10.093Z</modification><creation>2019-03-26T22:40:55Z</creation></dates><accession>S-EPMC6315242</accession><cross_references><pubmed>30552079</pubmed><doi>10.2196/11896</doi></cross_references></HashMap>