From smartphone to EHR: a case report on integrating patient-generated health data
Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects...
Saved in:
Published in | NPJ digital medicine Vol. 1; no. 1; p. 23 |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
20.06.2018
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
ISSN | 2398-6352 2398-6352 |
DOI | 10.1038/s41746-018-0030-8 |
Cover
Abstract | Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions.
mHealth: Smartphone app syncs with health record to improve asthma care
Patients with asthma who record inhaler usage and lung function scores with a smartphone app and transmit the data to an electronic health record (EHR) can get timelier care and prescription adjustments from their doctors. A team led by Yvonne Chan and Nicholas Genes from the Icahn School of Medicine at Mount Sinai in New York, NY, USA explored the feasibility of having patients self-report health data on an iPhone app called Asthma Health and then share the information with their pulmonologists via an EHR patient portal app. Four patients took part in the study, but only two really engaged in the platform. Those patients submitted multiple measures of peak expiratory flow rate per week. In one instance, the measure triggered a pulmonologist to call the patient and prescribe new allergy medications. |
---|---|
AbstractList | Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions.
Patients with asthma who record inhaler usage and lung function scores with a smartphone app and transmit the data to an electronic health record (EHR) can get timelier care and prescription adjustments from their doctors. A team led by Yvonne Chan and Nicholas Genes from the Icahn School of Medicine at Mount Sinai in New York, NY, USA explored the feasibility of having patients self-report health data on an iPhone app called Asthma Health and then share the information with their pulmonologists via an EHR patient portal app. Four patients took part in the study, but only two really engaged in the platform. Those patients submitted multiple measures of peak expiratory flow rate per week. In one instance, the measure triggered a pulmonologist to call the patient and prescribe new allergy medications. Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions. Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions.mHealth: Smartphone app syncs with health record to improve asthma carePatients with asthma who record inhaler usage and lung function scores with a smartphone app and transmit the data to an electronic health record (EHR) can get timelier care and prescription adjustments from their doctors. A team led by Yvonne Chan and Nicholas Genes from the Icahn School of Medicine at Mount Sinai in New York, NY, USA explored the feasibility of having patients self-report health data on an iPhone app called Asthma Health and then share the information with their pulmonologists via an EHR patient portal app. Four patients took part in the study, but only two really engaged in the platform. Those patients submitted multiple measures of peak expiratory flow rate per week. In one instance, the measure triggered a pulmonologist to call the patient and prescribe new allergy medications. Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness-if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple's ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic's EHR. For users who had installed and activated Epic's patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions.Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness-if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple's ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic's EHR. For users who had installed and activated Epic's patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions. Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions to prevent acute exacerbations of chronic illness—if data are seen and shared by care teams. This case report describes the technical aspects of integrating data from a popular smartphone platform to a commonly used EHR vendor and explores the challenges and potential of this approach for disease management. Consented subjects using the Asthma Health app (built on Apple’s ResearchKit platform) were able to share data on inhaler usage and peak expiratory flow rate (PEFR) with a local pulmonologist who ordered this data on Epic’s EHR. For users who had installed and activated Epic’s patient portal (MyChart) on their iPhone and enabled sharing of health data between apps via HealthKit, the pulmonologist could review PGHD and, if necessary, make recommendations. Four patients agreed to share data with their pulmonologist, though only two patients submitted more than one data point across the 4.5-month trial period. One of these patients submitted 101 PEFR readings across 65 days; another submitted 24 PEFR and inhaler usage readings across 66 days. PEFR for both patients fell within predefined physiologic parameters, except once where a low threshold notification was sent to the pulmonologist, who responded with a telephone discussion and new e-prescription to address symptoms. This research describes the technical considerations and implementation challenges of using commonly available frameworks for sharing PGHD, for the purpose of remote monitoring to support timely care interventions. mHealth: Smartphone app syncs with health record to improve asthma care Patients with asthma who record inhaler usage and lung function scores with a smartphone app and transmit the data to an electronic health record (EHR) can get timelier care and prescription adjustments from their doctors. A team led by Yvonne Chan and Nicholas Genes from the Icahn School of Medicine at Mount Sinai in New York, NY, USA explored the feasibility of having patients self-report health data on an iPhone app called Asthma Health and then share the information with their pulmonologists via an EHR patient portal app. Four patients took part in the study, but only two really engaged in the platform. Those patients submitted multiple measures of peak expiratory flow rate per week. In one instance, the measure triggered a pulmonologist to call the patient and prescribe new allergy medications. |
ArticleNumber | 23 |
Author | Violante, Samantha Schadt, Eric E. Chan, Yu-Feng Yvonne Cetrangol, Christine Rogers, Linda Genes, Nicholas |
Author_xml | – sequence: 1 givenname: Nicholas surname: Genes fullname: Genes, Nicholas organization: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai – sequence: 2 givenname: Samantha surname: Violante fullname: Violante, Samantha organization: Sema4, a Mount Sinai Venture – sequence: 3 givenname: Christine surname: Cetrangol fullname: Cetrangol, Christine organization: Epic Applications, Information Technology Department, Mount Sinai Health System – sequence: 4 givenname: Linda surname: Rogers fullname: Rogers, Linda organization: Mount Sinai – National Jewish Health Respiratory Institute – sequence: 5 givenname: Eric E. surname: Schadt fullname: Schadt, Eric E. email: eric.schadt@sema4genomics.com organization: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , Sema4, a Mount Sinai Venture – sequence: 6 givenname: Yu-Feng Yvonne surname: Chan fullname: Chan, Yu-Feng Yvonne email: yu-fengyvonne.chan@mssm.edu organization: Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai , Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, Center for Digital Health, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31304305$$D View this record in MEDLINE/PubMed |
BookMark | eNp9UU1r3TAQFCWh-Wh-QC9F0EsvbleflnsolJA0hUAgtGch22s_Bz_JlfQC_ffVy0vSNNCcVmhndmZ3jsieDx4JecvgIwNhPiXJaqkrYKYCEFCZV-SQi8ZUWii-9-R9QE5SugEADtI0Ur8mB4IJkALUIbk-j2FN09rFvKyKAM2Bnl1cf6aOdi4hjbiEmGnwdPIZx-jy5Ee6lII-VyN6LF_Y0xW6Oa9o77J7Q_YHNyc8ua_H5Of52Y_Ti-ry6tv306-XVadB50poVw-84b1hSvJe1KyVYhgc1B1ojW0nxMBZ26qe1YNBZK2ToIRoauhboaU4Jl92c5dNu8a-K4aim-0Sp7LNbxvcZP_t-Gllx3BrtVLAGlUGfLgfEMOvDaZs11PqcJ6dx7BJlnNVvHFzp_X-GfQmbKIv61muyjW1gYYX1Lunjh6tPJy7ANgO0MWQUsThEcLAblO1u1RtSdVuU7WmcOpnnG7K5f5hu9Q0v8jkO2YqKn7E-Nf0_0l_AB_QtNw |
CitedBy_id | crossref_primary_10_1093_jamia_ocaa036 crossref_primary_10_1097_HCO_0000000000000891 crossref_primary_10_1177_20552076221112152 crossref_primary_10_1093_jamia_ocaa177 crossref_primary_10_1016_j_annemergmed_2021_08_002 crossref_primary_10_2196_29155 crossref_primary_10_3389_fdgth_2023_1289373 crossref_primary_10_1038_s41746_020_0236_4 crossref_primary_10_2196_57801 crossref_primary_10_1109_JBHI_2023_3271580 crossref_primary_10_1093_jamiaopen_ooz036 crossref_primary_10_1016_j_amjmed_2022_10_006 crossref_primary_10_1177_0890117120919366 crossref_primary_10_2196_35917 crossref_primary_10_3390_informatics11010002 crossref_primary_10_1007_s40279_019_01084_y crossref_primary_10_2196_43214 crossref_primary_10_1055_s_0041_1732424 crossref_primary_10_1016_j_jbi_2020_103639 crossref_primary_10_1371_journal_pdig_0000511 crossref_primary_10_1016_j_telpol_2021_102285 crossref_primary_10_1016_j_eswa_2024_124398 crossref_primary_10_1186_s12911_021_01560_4 crossref_primary_10_1055_s_0041_1730284 crossref_primary_10_1097_ICO_0000000000002500 crossref_primary_10_1097_SAP_0000000000003179 crossref_primary_10_1055_s_0040_1718755 crossref_primary_10_1093_jamiaopen_ooae109 crossref_primary_10_1055_s_0042_1758737 crossref_primary_10_1200_JCO_20_00721 crossref_primary_10_2196_16444 crossref_primary_10_2196_31048 crossref_primary_10_1080_02770903_2021_1955378 crossref_primary_10_1371_journal_pone_0286210 crossref_primary_10_1109_JTEHM_2021_3058841 crossref_primary_10_2196_12861 crossref_primary_10_1089_tmj_2020_0427 crossref_primary_10_2196_25413 crossref_primary_10_1126_scitranslmed_abd7865 crossref_primary_10_2196_51955 crossref_primary_10_1093_jamiaopen_ooaa052 crossref_primary_10_1016_j_copbio_2019_03_004 crossref_primary_10_1016_j_iot_2020_100166 crossref_primary_10_1093_jamia_ocae138 crossref_primary_10_1177_20552076241277481 crossref_primary_10_1016_j_alit_2020_06_001 |
Cites_doi | 10.1093/jamia/ocv206 10.1016/j.molonc.2014.08.006 10.1152/ajpregu.00349.2016 10.1089/tmj.2015.0106 10.1016/j.amjmed.2016.07.029 10.2196/jmir.5094 10.1097/HCO.0000000000000350 10.1093/jamia/ocv118 10.1371/journal.pone.0152722 10.1097/ACM.0000000000001205 10.1089/tmj.2013.0282 10.1177/1932296815622453 10.1038/nbt.3826 10.1001/jama.2014.2564 |
ContentType | Journal Article |
Copyright | The Author(s) 2018 The Author(s) 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
Copyright_xml | – notice: The Author(s) 2018 – notice: The Author(s) 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
DBID | C6C AAYXX CITATION NPM 3V. 7RV 7X7 7XB 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR CCPQU DWQXO FYUFA GHDGH K9. KB0 M0S NAPCQ PHGZM PHGZT PIMPY PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM |
DOI | 10.1038/s41746-018-0030-8 |
DatabaseName | Springer Nature OA Free Journals CrossRef PubMed ProQuest Central (Corporate) ProQuest Nursing & Allied Health Database ProQuest Health & Medical Collection ProQuest Central (purchase pre-March 2016) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central ProQuest Central Essentials ProQuest Central ProQuest One ProQuest Central Korea Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Health & Medical Complete (Alumni) Nursing & Allied Health Database (Alumni Edition) ProQuest Health & Medical Collection Nursing & Allied Health Premium ProQuest Central Premium ProQuest One Academic (New) Access via ProQuest (Open Access) ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef PubMed Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing ProQuest Central China ProQuest Central Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea ProQuest Central (New) ProQuest One Academic Eastern Edition ProQuest Nursing & Allied Health Source ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) Nursing & Allied Health Premium ProQuest Health & Medical Complete ProQuest One Academic UKI Edition ProQuest Nursing & Allied Health Source (Alumni) ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
DatabaseTitleList | CrossRef Publicly Available Content Database MEDLINE - Academic PubMed |
Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 2398-6352 |
ExternalDocumentID | PMC6550195 31304305 10_1038_s41746_018_0030_8 |
Genre | Journal Article |
GroupedDBID | 0R~ 53G 7RV 7X7 ACGFS ADBBV ALIPV ALMA_UNASSIGNED_HOLDINGS AOIJS BCNDV C6C EBS GROUPED_DOAJ HYE M~E NAO NO~ OK1 PGMZT RNT RPM AAYXX CITATION 8FI 8FJ AAJSJ ABUWG ACSMW AFKRA AJTQC BENPR CCPQU EBLON EIHBH EJD FYUFA HMCUK NAPCQ NPM PIMPY SNYQT UKHRP 3V. 7XB 8FK AARCD AASML AZQEC DWQXO K9. PHGZM PHGZT PKEHL PPXIY PQEST PQQKQ PQUKI PRINS 7X8 5PM |
ID | FETCH-LOGICAL-c606t-36a7f292d81542d371b43ffa07c066ebc33f21bb5d17f8ee1ba40533970db3643 |
IEDL.DBID | C6C |
ISSN | 2398-6352 |
IngestDate | Thu Aug 21 13:21:43 EDT 2025 Thu Sep 04 23:39:54 EDT 2025 Wed Aug 13 11:16:57 EDT 2025 Thu Jan 02 23:01:39 EST 2025 Tue Jul 01 01:09:39 EDT 2025 Thu Apr 24 22:55:09 EDT 2025 Fri Feb 21 02:39:51 EST 2025 |
IsDoiOpenAccess | true |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 1 |
Keywords | Information technology Data integration Predictive markers |
Language | English |
License | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c606t-36a7f292d81542d371b43ffa07c066ebc33f21bb5d17f8ee1ba40533970db3643 |
Notes | ObjectType-Case Study-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-4 ObjectType-Report-1 ObjectType-Article-3 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
OpenAccessLink | https://www.nature.com/articles/s41746-018-0030-8 |
PMID | 31304305 |
PQID | 2531368092 |
PQPubID | 5061815 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_6550195 proquest_miscellaneous_2258152864 proquest_journals_2531368092 pubmed_primary_31304305 crossref_primary_10_1038_s41746_018_0030_8 crossref_citationtrail_10_1038_s41746_018_0030_8 springer_journals_10_1038_s41746_018_0030_8 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2018-06-20 |
PublicationDateYYYYMMDD | 2018-06-20 |
PublicationDate_xml | – month: 06 year: 2018 text: 2018-06-20 day: 20 |
PublicationDecade | 2010 |
PublicationPlace | London |
PublicationPlace_xml | – name: London – name: England |
PublicationTitle | NPJ digital medicine |
PublicationTitleAbbrev | npj Digital Med |
PublicationTitleAlternate | NPJ Digit Med |
PublicationYear | 2018 |
Publisher | Nature Publishing Group UK Nature Publishing Group |
Publisher_xml | – name: Nature Publishing Group UK – name: Nature Publishing Group |
References | Bietz, Bloss (CR9) 2016; 23 Dorsey (CR10) 2017; 92 Pfiffner, Pinyol, Natter, Mandl (CR13) 2016; 11 Wood, Bennett, Basch (CR19) 2015; 9 Chan (CR14) 2017; 35 Wright, Hall Brown, Collier, Sandberg (CR7) 2017; 312 CR18 CR17 Heintzman (CR4) 2016; 10 CR12 CR11 North, Chaudhry (CR15) 2016; 22 CR21 CR20 Powell, Landman, Bates (CR8) 2014; 311 Garabelli, Stavrakis., Po (CR2) 2017; 32 Garde, Dehkordi, Wensley, Ansermino, Dumont (CR6) 2015; 2015 Milani, Lavie, Bober, Milani, Ventura (CR3) 2017; 130 Kim (CR1) 2014; 20 Kumar, Goren, Stark, Wall, Longhurst (CR5) 2016; 23 Gay, Leijdekkers (CR16) 2015; 17 P Garabelli (30_CR2) 2017; 32 RB Kumar (30_CR5) 2016; 23 ER Dorsey (30_CR10) 2017; 92 MJ Bietz (30_CR9) 2016; 23 F North (30_CR15) 2016; 22 V Gay (30_CR16) 2015; 17 J Kim (30_CR1) 2014; 20 PB Pfiffner (30_CR13) 2016; 11 A Garde (30_CR6) 2015; 2015 YF Chan (30_CR14) 2017; 35 RV Milani (30_CR3) 2017; 130 WA Wood (30_CR19) 2015; 9 30_CR20 30_CR21 30_CR11 AC Powell (30_CR8) 2014; 311 30_CR12 30_CR17 30_CR18 SP Wright (30_CR7) 2017; 312 ND Heintzman (30_CR4) 2016; 10 |
References_xml | – ident: CR21 – volume: 23 start-page: 532 year: 2016 end-page: 537 ident: CR5 article-title: Automated integration of continuous glucose monitor data in the electronic health record using consumer technology publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocv206 – volume: 9 start-page: 1018 year: 2015 end-page: 1024 ident: CR19 article-title: Emerging uses of patient generated health data in clinical research publication-title: Mol. Oncol. doi: 10.1016/j.molonc.2014.08.006 – ident: CR18 – volume: 312 start-page: R358 year: 2017 end-page: R367 ident: CR7 article-title: How consumer physical activity monitors could transform human physiology research publication-title: Am. J. Physiol. Integr. Comp. Physiol. doi: 10.1152/ajpregu.00349.2016 – volume: 22 start-page: 608 year: 2016 end-page: 613 ident: CR15 article-title: Apple HealthKit and Health app: patient uptake and barriers in primary care publication-title: Telemed. J. E Health doi: 10.1089/tmj.2015.0106 – volume: 130 start-page: 14 year: 2017 end-page: 20 ident: CR3 article-title: Improving hypertension control and patient engagement using digital tools publication-title: Am. J. Med. doi: 10.1016/j.amjmed.2016.07.029 – volume: 17 year: 2015 ident: CR16 article-title: Bringing health and fitness data together for connected health care: mobile apps as enablers of interoperability publication-title: J. Med. Internet Res. doi: 10.2196/jmir.5094 – ident: CR12 – ident: CR17 – volume: 32 start-page: 53 year: 2017 end-page: 57 ident: CR2 article-title: Smartphone-based arrhythmia monitoring publication-title: Curr. Opin. Cardiol. doi: 10.1097/HCO.0000000000000350 – volume: 23 start-page: e42 year: 2016 end-page: e48 ident: CR9 article-title: Opportunities and challenges in the use of personal health data for health research publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocv118 – volume: 11 year: 2016 ident: CR13 article-title: C3-PRO: connecting ResearchKit to the Health System using i2b2 and FHIR publication-title: PLoS ONE doi: 10.1371/journal.pone.0152722 – ident: CR11 – volume: 92 start-page: 157 year: 2017 end-page: 160 ident: CR10 article-title: The use of smartphones for health research publication-title: Acad. Med. doi: 10.1097/ACM.0000000000001205 – volume: 20 start-page: 552 year: 2014 end-page: 558 ident: CR1 article-title: Analysis of health consumers’ behavior using self-tracker for activity, sleep, and diet publication-title: Telemed. J. E Health doi: 10.1089/tmj.2013.0282 – volume: 10 start-page: 25 year: 2016 end-page: 41 ident: CR4 article-title: A digital ecosystem of diabetes data and technology publication-title: J. Diabetes Sci. Technol. doi: 10.1177/1932296815622453 – volume: 35 start-page: 354 year: 2017 end-page: 362 ident: CR14 article-title: The asthma mobile health study, a large scale clinical study using ResearchKit publication-title: Nat. Biotech. doi: 10.1038/nbt.3826 – volume: 311 start-page: 1851 year: 2014 end-page: 1852 ident: CR8 article-title: In search of a few good apps publication-title: JAMA doi: 10.1001/jama.2014.2564 – volume: 2015 start-page: 7692 year: 2015 end-page: 7695 ident: CR6 article-title: Pulse oximetry recorded from the Phone Oximeter for detection of obstructive sleep apnea events with and without oxygen desaturation in children publication-title: Conf. Proc. IEEE Eng. Med Biol. Soc. – ident: CR20 – volume: 23 start-page: 532 year: 2016 ident: 30_CR5 publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocv206 – volume: 9 start-page: 1018 year: 2015 ident: 30_CR19 publication-title: Mol. Oncol. doi: 10.1016/j.molonc.2014.08.006 – volume: 92 start-page: 157 year: 2017 ident: 30_CR10 publication-title: Acad. Med. doi: 10.1097/ACM.0000000000001205 – volume: 311 start-page: 1851 year: 2014 ident: 30_CR8 publication-title: JAMA doi: 10.1001/jama.2014.2564 – volume: 23 start-page: e42 year: 2016 ident: 30_CR9 publication-title: J. Am. Med. Inform. Assoc. doi: 10.1093/jamia/ocv118 – volume: 10 start-page: 25 year: 2016 ident: 30_CR4 publication-title: J. Diabetes Sci. Technol. doi: 10.1177/1932296815622453 – ident: 30_CR11 – ident: 30_CR12 – volume: 22 start-page: 608 year: 2016 ident: 30_CR15 publication-title: Telemed. J. E Health doi: 10.1089/tmj.2015.0106 – volume: 20 start-page: 552 year: 2014 ident: 30_CR1 publication-title: Telemed. J. E Health doi: 10.1089/tmj.2013.0282 – volume: 312 start-page: R358 year: 2017 ident: 30_CR7 publication-title: Am. J. Physiol. Integr. Comp. Physiol. doi: 10.1152/ajpregu.00349.2016 – volume: 2015 start-page: 7692 year: 2015 ident: 30_CR6 publication-title: Conf. Proc. IEEE Eng. Med Biol. Soc. – volume: 35 start-page: 354 year: 2017 ident: 30_CR14 publication-title: Nat. Biotech. doi: 10.1038/nbt.3826 – volume: 17 year: 2015 ident: 30_CR16 publication-title: J. Med. Internet Res. doi: 10.2196/jmir.5094 – ident: 30_CR21 – ident: 30_CR20 – ident: 30_CR17 – volume: 32 start-page: 53 year: 2017 ident: 30_CR2 publication-title: Curr. Opin. Cardiol. doi: 10.1097/HCO.0000000000000350 – ident: 30_CR18 – volume: 11 year: 2016 ident: 30_CR13 publication-title: PLoS ONE doi: 10.1371/journal.pone.0152722 – volume: 130 start-page: 14 year: 2017 ident: 30_CR3 publication-title: Am. J. Med. doi: 10.1016/j.amjmed.2016.07.029 |
SSID | ssj0002048946 |
Score | 2.3276012 |
Snippet | Patient-generated health data (PGHD), collected from mobile apps and devices, represents an opportunity for remote patient monitoring and timely interventions... |
SourceID | pubmedcentral proquest pubmed crossref springer |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 23 |
SubjectTerms | 631/114/2401 639/705/258 692/53/2423 Asthma Biomedicine Biotechnology Case reports Digital technology Electronic health records Health informatics Inhalers Medicine Medicine & Public Health Patients Smartphones Telemedicine Web portals |
SummonAdditionalLinks | – databaseName: ProQuest Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1LSx0xFD5YhdKNaF-OWkmhq5bgTB6TxI1I8XIp2IVUuLthJpO0BZ1R7_X_e5LJjNxKXSchj_Ml-ZJz8gXgC2c1t44p6oSVVDSC01oXnErjpCiC5lgT3jtf_CznV-LHQi7ShdsyhVWOa2JcqNvehjvyY4Zg4aXODTu9vaPh16jgXU1faLyCrShdhnhWCzXdsQRRWiPK0ZnJ9fFSIAMPR2hNA7ypXt-OnnHM56GS__hL4zY024HtxB_J2WDwXdhw3Vt4fZE85O_gcnbf35DlDSIiRJ07surJ-fzyhNTE4oZFBh8B6TsyCkVgNSSpq9LfUYQaSSgZ3keSEED6Hq5m57--z2n6N4FaPI6sKC9r5ZlhrUZ-xFquCjSB93WuLBIM11jOPSuaRraF8tq5oqlFeJJrVN42HCnKB9jssIV7QEwtPRMlt1x6JFbWSGOE1wK3Pe9yqzPIx-GrbBIVD39bXFfRuc11NYx4hSMeZEjzCot8nYrcDooaL2U-HG1Spcm1rJ6gkMHnKRmnRfB11J3rHzAPk9h7pkuRwcfBhFNtWDoqnWWg1ow7ZQiS2-sp3d8_UXq7xAMdAi2DbyMMnpr1307sv9yJA3jDIiBLXLIOYXN1_-A-IdNZNUcRzo9REPmE priority: 102 providerName: ProQuest |
Title | From smartphone to EHR: a case report on integrating patient-generated health data |
URI | https://link.springer.com/article/10.1038/s41746-018-0030-8 https://www.ncbi.nlm.nih.gov/pubmed/31304305 https://www.proquest.com/docview/2531368092 https://www.proquest.com/docview/2258152864 https://pubmed.ncbi.nlm.nih.gov/PMC6550195 |
Volume | 1 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1ZaxsxEB5yQOlLSM84SY0KfWoR3dWtvCXGxgQSimnAb8uuLLWFZh1i5_9npD2CaxrIs2bQNZK-0Yw-AXzhrOTOM029cJKKSnBampxTab0UeeQcq-J756trNb0Rl3M534G8ewuTkvYTpWXaprvssO8rgdA5-r6GRrukZhf2Dbp10ahHatRfq0QeWitUF7_kZltz8wTagpXb2ZH_hEjTyTM5hIMWMpLzppFvYMfXb-HVVRsUfwezyf3ylqxusRcx0dyT9ZKMp7MzUhKHZxRpwgJkWZOOGwKrIS2hKv2VeKcRd5LmSSSJOaPv4WYy_jma0varBOrQA1lTrkodmGULg5CILbjOcdRDKDPtEFP4ynEeWF5VcpHrYLzPq1LEV7hWZ4uKIyr5AHs1tvAIiC1lYEJxx2VALOWstFYEI_CkCz5zZgBZN3yFa3nE43cWf4sUz-amaEa8wBGPzKNZgSpfe5W7hkTjOeHTbk6Kdj2tCoZbBVcms2wAn_tiXAkxvFHWfvmAMkxi75lRYgAfmynsa0PtRG42AL0xub1AZNneLKn__E5s2wp9uNyi5rfODJ6a9d9OHL9I-gRes2SfCjetU9hb3z_4T4h11tUQdvVcD2H_Ynz9YzZMtj5M9waPnkH6VA |
linkProvider | Springer Nature |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1ZT9wwEB7RRWp5QfRkgbau1L60skh8JDYSQj12tRR2Va1A4i1NHLutVBJgF1X9U_xGxrnQFpU3nmPH9hyescfzDcBbzlJuLIupFUZSkQlOUxVyKrWVIvSYY5nPdx5PotGx-HoiT5bgqs2F8c8q2z2x2qjz0vg78m2GwsIjFWi2d3ZOfdUoH11tS2jUYnFg__7BI9tsd_8L8vcdY8PB0ecRbaoKUIPO-pzyKI0d0yxX6D2wnMchTtC5NIgNml-bGc4dC7NM5mHslLVhlgqfsKrjIM84GnD87wNYFj6jtQfLnwaTb9PuVsfD4GoRteFTrrZnAn1-f2hX1CsUVYsG8JZXe_tx5j8R2srwDddgtfFYycdaxB7Dki2ewMNxE5N_CtPhRXlKZqcog_6duyXzkgxG0x2SEoMmktRRCVIWpIWmwGFIg-dKf1Sw1-j2kjojk_gnq8_g-F5o-hx6Bc5wHYhOpWMi4oZLhzQ2WmotnBJoaJ0NjOpD0JIvMQ2Mua-m8TupwulcJTXFE6S4Bz4NEuzyvutyVmN43NV4q-VJ0qjzLLkRvj686T6jIvroSlrY8hLbMImrZyoSfXhRs7AbDXtX2Gp9iBeY2zXwIN-LX4pfPyuw7wiPkKHGnh9aMbiZ1n8XsXH3Il7Do9HR-DA53J8cbMIKq4Qzwg1zC3rzi0v7Ev2sefaqEW4C3-9bn64BLfk3JA |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3dTxQxEJ-ckFx8IYggJygl8UlS3e3Xtr4Z5HKKEHPhEt42u90WTWCPcMf_77T7Yc6LJjxvJ22n086vOzO_ArzjrODWsYw6YSUVpeC00Cmn0jgp0sA5VoZ654tLNZmJb9fyegCyq4WJSfuR0jIe01122MeFQOgc7r6aBruk-sN95Z_Bps4QcYcYrTrtf60ELlojVBfD5HpdetULrUHL9QzJv8Kk0fuMt2GrhY3kczPQFzBw9Q4ML9rA-EuYjh_md2RxhzMJyeaOLOfkbDL9RApi0U-RJjRA5jXp-CGwG9KSqtKbyD2N2JM0ZZEk5I3uwmx8dnU6oe1zCdTiLWRJuSoyzwyrNMIiVvEsRc17XySZRVzhSsu5Z2lZyirNvHYuLQsRKnFNllQlR2SyBxs1jnAfiCmkZ0Jxy6VHPGWNNEZ4LdDbeZdYPYKkU19uWy7x8KTFbR5j2lznjcZz1HhgH01yFHnfi9w3RBr_a3zYrUne7qlFzvC44Eonho3guP-MuyGEOIrazR-xDZM4e6aVGMGrZgn73lA6EpyNIFtZ3L5BYNpe_VL_-hkZtxXe41KDkiedGfwZ1j8n8fpJrY9g-OPLOP_-9fL8AJ6zaKoKz7BD2Fg-PLo3CH2W5dto6L8BpgL63w |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=From+smartphone+to+EHR%3A+a+case+report+on+integrating+patient-generated+health+data&rft.jtitle=NPJ+digital+medicine&rft.au=Genes%2C+Nicholas&rft.au=Violante%2C+Samantha&rft.au=Cetrangol%2C+Christine&rft.au=Rogers%2C+Linda&rft.date=2018-06-20&rft.pub=Nature+Publishing+Group+UK&rft.eissn=2398-6352&rft.volume=1&rft.issue=1&rft_id=info:doi/10.1038%2Fs41746-018-0030-8&rft.externalDocID=10_1038_s41746_018_0030_8 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2398-6352&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2398-6352&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2398-6352&client=summon |