�ݺ�ߣshows by User: SabrinaHsueh1

�ݺ�ߣshows by User: SabrinaHsueh1 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: SabrinaHsueh1 / Mon, 09 Jan 2017 23:18:37 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: SabrinaHsueh1 Amia2016 pghd-panel-v8 /slideshow/amia2016-pghdpanelv8/70839940 amia2016-pghd-panel-v8-170109231837
AMIA 2016 Panel: Transforming Patient-Generated Data for Wellness and Biomedical Research:From Behavioral Sensing to Decision Support AMIA 2016 Didactic Panel Nov 14 15:30 - 17:00 Salon A1 Chair, Discussant Summary & Panel Moderator: Pei-Yun Sabrina Hsueh, PhD Panelists: Susan Peterson, PhD, MPH, Katherine Kim, PhD, MPH, MBA, F. Martin-Sanchez, PhD, FACMI, FACHI, Cagatay Demiralp, PhD ]]>
AMIA 2016 Panel: Transforming Patient-Generated Data for Wellness and Biomedical Research:From Behavioral Sensing to Decision Support AMIA 2016 Didactic Panel Nov 14 15:30 - 17:00 Salon A1 Chair, Discussant Summary & Panel Moderator: Pei-Yun Sabrina Hsueh, PhD Panelists: Susan Peterson, PhD, MPH, Katherine Kim, PhD, MPH, MBA, F. Martin-Sanchez, PhD, FACMI, FACHI, Cagatay Demiralp, PhD ]]> Mon, 09 Jan 2017 23:18:37 GMT /slideshow/amia2016-pghdpanelv8/70839940 SabrinaHsueh1@slideshare.net(SabrinaHsueh1) Amia2016 pghd-panel-v8 SabrinaHsueh1 AMIA 2016 Panel: Transforming Patient-Generated Data for Wellness and Biomedical Research:�From Behavioral Sensing to Decision Support AMIA 2016 Didactic Panel Nov 14 15:30 - 17:00 Salon A1 Chair, Discussant Summary & Panel Moderator: Pei-Yun Sabrina Hsueh, PhD Panelists: Susan Peterson, PhD, MPH, Katherine Kim, PhD, MPH, MBA, F. Martin-Sanchez, PhD, FACMI, FACHI, Cagatay Demiralp, PhD <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/amia2016-pghd-panel-v8-170109231837-thumbnail.jpg?width=120&height=120&fit=bounds" /> AMIA 2016 Panel: Transforming Patient-Generated Data for Wellness and Biomedical Research:�From Behavioral Sensing to Decision Support AMIA 2016 Didactic Panel Nov 14 15:30 - 17:00 Salon A1 Chair, Discussant Summary & Panel Moderator: Pei-Yun Sabrina Hsueh, PhD Panelists: Susan Peterson, PhD, MPH, Katherine Kim, PhD, MPH, MBA, F. Martin-Sanchez, PhD, FACMI, FACHI, Cagatay Demiralp, PhD

Amia2016 pghd-panel-v8 from Pei-Yun Sabrina Hsueh

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0 HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretability for Consumer Informatics /slideshow/hec2016-panel-putting-usergenerated-data-in-action-improving-interpretability-for-consumer-informatics/66067698 hec2016-interpretabilitypanel-public-160915173015
Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center) Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY a IBM T.J. Watson Research Center, USA b Norwegian University of Science and Technology, Norway c Mailman School of Public health, Columbia University, USA d, Department of Biomedical Informatics, University of Washington, USA e Department of Medical Informatics, University of Heidelberg, Germany The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data. ]]>
Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center) Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY a IBM T.J. Watson Research Center, USA b Norwegian University of Science and Technology, Norway c Mailman School of Public health, Columbia University, USA d, Department of Biomedical Informatics, University of Washington, USA e Department of Medical Informatics, University of Heidelberg, Germany The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data. ]]> Thu, 15 Sep 2016 17:30:15 GMT /slideshow/hec2016-panel-putting-usergenerated-data-in-action-improving-interpretability-for-consumer-informatics/66067698 SabrinaHsueh1@slideshare.net(SabrinaHsueh1) HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretability for Consumer Informatics SabrinaHsueh1 Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center) Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY a IBM T.J. Watson Research Center, USA b Norwegian University of Science and Technology, Norway c Mailman School of Public health, Columbia University, USA d, Department of Biomedical Informatics, University of Washington, USA e Department of Medical Informatics, University of Heidelberg, Germany The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/hec2016-interpretabilitypanel-public-160915173015-thumbnail.jpg?width=120&height=120&fit=bounds" /> Chair/Moderator: Pei-Yun Sabrina HSUEH, PhD (IBM T.J. Watson Research Center) Panelists: XinXin ZHU, Bian YANG, Ying-Kuen CHEUNG , Thomas WETTER, and Sanjoy DEY a IBM T.J. Watson Research Center, USA b Norwegian University of Science and Technology, Norway c Mailman School of Public health, Columbia University, USA d, Department of Biomedical Informatics, University of Washington, USA e Department of Medical Informatics, University of Heidelberg, Germany The rise of consumer health awareness and the recent advent of personal health management tools (including mobile and health wearable devices) have contributed to another shift transforming the healthcare landscape. Despite the rise of health consumers, the impact of user-generated health data remains to be validated. In fact, many applications are hinged on the interpretability issues of this sort of data. The aim of this panel is two-fold. First, this panel aims to review the key dimensions in the interpretability, spanning from quality and reliability to information security and trust management. Secondly, since similar issues and methodologies have been proposed in different application areas ranging from clinical decision support to behavioral interventions and clinical trials, the panelists will also discuss both the success stories and the areas that fall short. The opportunities and barriers identified can then serve as guidelines or action items individuals can bring to their organizations to further improve the interpretability of user-generated data.

HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretability for Consumer Informatics from Pei-Yun Sabrina Hsueh

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0 Medinfo2015 workshop-adherence mangement-patient_driven-publicized /slideshow/medinfo2015-workshopadherence-mangementpatientdrivenpublicized/52960801 medinfo2015-workshop-adherencemangementpatientdriven-publicized-150919101607-lva1-app6892
Workshop: Effective Patient Adherence Management by Engaging Enabling Technologies Pei-Yun Sabrina Hsueha, Vimla L. Patelb, Fernando Sanchezc, Marcia Itod,e, Chohreh Partoviana, María V. Giussi Bordonig, Marion Ballf,a a IBM T.J. Watson Research Center, Yorktown Heights, NY, USA b Center for Cognitive Studies in Medicine and Public Health, the New York Academy of Medicine, New York, NY, USA c Health and Biomedical Informatics Center, University of Melbourne, Melbourne, Australia d IBM Brazil Research Lab, Sao Paolo, Brazil e Telehealth/Teledentistry Center, School of Dentistry, University of Sao Paulo, Sao Paulo, Brazil f Johns Hopkins University, Baltimore, MD, USA g Health Informatics Department, Hospital Italiano de Buenos Aires, Argentina. Abstract Effective patient adherence management strategies require better understanding of patient-generated data, including patient-reported data and measurements from devices and sensors, as key to assisting providers in learning more about their patients’needs and enhancing patient centric care. Gaining “meaningful use” of patient-generated data could ultimately lead to improvements in patient safety and outcomes. In this workshop, we review proof of concept studies using technology to assess patient health literacy and self-efficacy with the goal of providing timely intervention, remedy, and improvements in cost and quality of care. In particular, we focus on engagement-enabling technolgoies that can leverage non-clinical information sources and reflect patient activities in the “wild”. We look into barriers to adherence, patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The speakers will address the issues related tothe integration of patient-generated data into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements gathered for the design of next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. ]]>
Workshop: Effective Patient Adherence Management by Engaging Enabling Technologies Pei-Yun Sabrina Hsueha, Vimla L. Patelb, Fernando Sanchezc, Marcia Itod,e, Chohreh Partoviana, María V. Giussi Bordonig, Marion Ballf,a a IBM T.J. Watson Research Center, Yorktown Heights, NY, USA b Center for Cognitive Studies in Medicine and Public Health, the New York Academy of Medicine, New York, NY, USA c Health and Biomedical Informatics Center, University of Melbourne, Melbourne, Australia d IBM Brazil Research Lab, Sao Paolo, Brazil e Telehealth/Teledentistry Center, School of Dentistry, University of Sao Paulo, Sao Paulo, Brazil f Johns Hopkins University, Baltimore, MD, USA g Health Informatics Department, Hospital Italiano de Buenos Aires, Argentina. Abstract Effective patient adherence management strategies require better understanding of patient-generated data, including patient-reported data and measurements from devices and sensors, as key to assisting providers in learning more about their patients’needs and enhancing patient centric care. Gaining “meaningful use” of patient-generated data could ultimately lead to improvements in patient safety and outcomes. In this workshop, we review proof of concept studies using technology to assess patient health literacy and self-efficacy with the goal of providing timely intervention, remedy, and improvements in cost and quality of care. In particular, we focus on engagement-enabling technolgoies that can leverage non-clinical information sources and reflect patient activities in the “wild”. We look into barriers to adherence, patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The speakers will address the issues related tothe integration of patient-generated data into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements gathered for the design of next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. ]]> Sat, 19 Sep 2015 10:16:07 GMT /slideshow/medinfo2015-workshopadherence-mangementpatientdrivenpublicized/52960801 SabrinaHsueh1@slideshare.net(SabrinaHsueh1) Medinfo2015 workshop-adherence mangement-patient_driven-publicized SabrinaHsueh1 Workshop: Effective Patient Adherence Management by Engaging Enabling Technologies Pei-Yun Sabrina Hsueha, Vimla L. Patelb, Fernando Sanchezc, Marcia Itod,e, Chohreh Partoviana, María V. Giussi Bordonig, Marion Ballf,a a IBM T.J. Watson Research Center, Yorktown Heights, NY, USA b Center for Cognitive Studies in Medicine and Public Health, the New York Academy of Medicine, New York, NY, USA c Health and Biomedical Informatics Center, University of Melbourne, Melbourne, Australia d IBM Brazil Research Lab, Sao Paolo, Brazil e Telehealth/Teledentistry Center, School of Dentistry, University of Sao Paulo, Sao Paulo, Brazil f Johns Hopkins University, Baltimore, MD, USA g Health Informatics Department, Hospital Italiano de Buenos Aires, Argentina. Abstract Effective patient adherence management strategies require better understanding of patient-generated data, including patient-reported data and measurements from devices and sensors, as key to assisting providers in learning more about their patients’needs and enhancing patient centric care. Gaining “meaningful use” of patient-generated data could ultimately lead to improvements in patient safety and outcomes. In this workshop, we review proof of concept studies using technology to assess patient health literacy and self-efficacy with the goal of providing timely intervention, remedy, and improvements in cost and quality of care. In particular, we focus on engagement-enabling technolgoies that can leverage non-clinical information sources and reflect patient activities in the “wild”. We look into barriers to adherence, patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The speakers will address the issues related tothe integration of patient-generated data into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements gathered for the design of next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/medinfo2015-workshop-adherencemangementpatientdriven-publicized-150919101607-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> Workshop: Effective Patient Adherence Management by Engaging Enabling Technologies Pei-Yun Sabrina Hsueha, Vimla L. Patelb, Fernando Sanchezc, Marcia Itod,e, Chohreh Partoviana, María V. Giussi Bordonig, Marion Ballf,a a IBM T.J. Watson Research Center, Yorktown Heights, NY, USA b Center for Cognitive Studies in Medicine and Public Health, the New York Academy of Medicine, New York, NY, USA c Health and Biomedical Informatics Center, University of Melbourne, Melbourne, Australia d IBM Brazil Research Lab, Sao Paolo, Brazil e Telehealth/Teledentistry Center, School of Dentistry, University of Sao Paulo, Sao Paulo, Brazil f Johns Hopkins University, Baltimore, MD, USA g Health Informatics Department, Hospital Italiano de Buenos Aires, Argentina. Abstract Effective patient adherence management strategies require better understanding of patient-generated data, including patient-reported data and measurements from devices and sensors, as key to assisting providers in learning more about their patients’needs and enhancing patient centric care. Gaining “meaningful use” of patient-generated data could ultimately lead to improvements in patient safety and outcomes. In this workshop, we review proof of concept studies using technology to assess patient health literacy and self-efficacy with the goal of providing timely intervention, remedy, and improvements in cost and quality of care. In particular, we focus on engagement-enabling technolgoies that can leverage non-clinical information sources and reflect patient activities in the “wild”. We look into barriers to adherence, patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The speakers will address the issues related tothe integration of patient-generated data into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements gathered for the design of next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts.

Medinfo2015 workshop-adherence mangement-patient_driven-publicized from Pei-Yun Sabrina Hsueh

]]> 1253 13 https://cdn.slidesharecdn.com/ss_thumbnails/medinfo2015-workshop-adherencemangementpatientdriven-publicized-150919101607-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post

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0 Mie2015 workshop-adherence engaging-publicized /SabrinaHsueh1/mie2015-workshopadherence-engagingpublicized mie2015-workshop-adherenceengaging-publicized-150919094721-lva1-app6892
MIE Medical Informatics in Europe: European Federation for Medical Informatics (EFMI) annual meeting Worklshop: Addressing Patient Adherence Issues by Engaging Enabling Technologies Chair: Pei-Yun Sabrina Hsueh (IBM T.J. Watson Research Center) Pei-Yun Sabrina HSUEHa, , Marion BALL b,a, Michael MARSCHOLLEKc, Fernando J. MARTIN-SANCHEZd , Chohreh PARTOVIANa, and Vimla PATELe aIBM T.J. Watson Research Center, NY, USA b John Hopkins University, MD, USA c Hannover Medical School, Germany d Melbourne Medical School, Australia e Center for Cognitive Studies in Medicine and Public Health, The New York Academy, USA Abstract One of the well known issues providers have contended with for many years is the issue of patients’ adherence to their care plans and medications outside clinical encounters. In this workshop, we review proof of concept studies using technology at the point of care to assess patient literacy and self-efficacy to provide timely intervention, remedy, and improvements in cost and quality. We focus on patient-generated information, including patient reported data and measurements from devices and sensors, as key to improving patient safety, gaining “meaningful use” data, improving patient centric care, and assisting providers in learning more about their patient needs to improve outcomes. We look into barriers to adherence, basic understanding of the patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The participants will address their findings in the integration of patient-generated information into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements for the next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. ]]>
MIE Medical Informatics in Europe: European Federation for Medical Informatics (EFMI) annual meeting Worklshop: Addressing Patient Adherence Issues by Engaging Enabling Technologies Chair: Pei-Yun Sabrina Hsueh (IBM T.J. Watson Research Center) Pei-Yun Sabrina HSUEHa, , Marion BALL b,a, Michael MARSCHOLLEKc, Fernando J. MARTIN-SANCHEZd , Chohreh PARTOVIANa, and Vimla PATELe aIBM T.J. Watson Research Center, NY, USA b John Hopkins University, MD, USA c Hannover Medical School, Germany d Melbourne Medical School, Australia e Center for Cognitive Studies in Medicine and Public Health, The New York Academy, USA Abstract One of the well known issues providers have contended with for many years is the issue of patients’ adherence to their care plans and medications outside clinical encounters. In this workshop, we review proof of concept studies using technology at the point of care to assess patient literacy and self-efficacy to provide timely intervention, remedy, and improvements in cost and quality. We focus on patient-generated information, including patient reported data and measurements from devices and sensors, as key to improving patient safety, gaining “meaningful use” data, improving patient centric care, and assisting providers in learning more about their patient needs to improve outcomes. We look into barriers to adherence, basic understanding of the patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The participants will address their findings in the integration of patient-generated information into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements for the next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. ]]> Sat, 19 Sep 2015 09:47:21 GMT /SabrinaHsueh1/mie2015-workshopadherence-engagingpublicized SabrinaHsueh1@slideshare.net(SabrinaHsueh1) Mie2015 workshop-adherence engaging-publicized SabrinaHsueh1 MIE Medical Informatics in Europe: European Federation for Medical Informatics (EFMI) annual meeting Worklshop: Addressing Patient Adherence Issues by Engaging Enabling Technologies Chair: Pei-Yun Sabrina Hsueh (IBM T.J. Watson Research Center) Pei-Yun Sabrina HSUEHa, , Marion BALL b,a, Michael MARSCHOLLEKc, Fernando J. MARTIN-SANCHEZd , Chohreh PARTOVIANa, and Vimla PATELe aIBM T.J. Watson Research Center, NY, USA b John Hopkins University, MD, USA c Hannover Medical School, Germany d Melbourne Medical School, Australia e Center for Cognitive Studies in Medicine and Public Health, The New York Academy, USA Abstract One of the well known issues providers have contended with for many years is the issue of patients’ adherence to their care plans and medications outside clinical encounters. In this workshop, we review proof of concept studies using technology at the point of care to assess patient literacy and self-efficacy to provide timely intervention, remedy, and improvements in cost and quality. We focus on patient-generated information, including patient reported data and measurements from devices and sensors, as key to improving patient safety, gaining “meaningful use” data, improving patient centric care, and assisting providers in learning more about their patient needs to improve outcomes. We look into barriers to adherence, basic understanding of the patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The participants will address their findings in the integration of patient-generated information into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements for the next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mie2015-workshop-adherenceengaging-publicized-150919094721-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /> MIE Medical Informatics in Europe: European Federation for Medical Informatics (EFMI) annual meeting Worklshop: Addressing Patient Adherence Issues by Engaging Enabling Technologies Chair: Pei-Yun Sabrina Hsueh (IBM T.J. Watson Research Center) Pei-Yun Sabrina HSUEHa, , Marion BALL b,a, Michael MARSCHOLLEKc, Fernando J. MARTIN-SANCHEZd , Chohreh PARTOVIANa, and Vimla PATELe aIBM T.J. Watson Research Center, NY, USA b John Hopkins University, MD, USA c Hannover Medical School, Germany d Melbourne Medical School, Australia e Center for Cognitive Studies in Medicine and Public Health, The New York Academy, USA Abstract One of the well known issues providers have contended with for many years is the issue of patients’ adherence to their care plans and medications outside clinical encounters. In this workshop, we review proof of concept studies using technology at the point of care to assess patient literacy and self-efficacy to provide timely intervention, remedy, and improvements in cost and quality. We focus on patient-generated information, including patient reported data and measurements from devices and sensors, as key to improving patient safety, gaining “meaningful use” data, improving patient centric care, and assisting providers in learning more about their patient needs to improve outcomes. We look into barriers to adherence, basic understanding of the patients and providers roles in improving adherence, and the use of technology to assist patients in staying on track. The participants will address their findings in the integration of patient-generated information into everyday life and clinical practice and share lessons learned from implementing these designs in practice. This workshop aims to share requirements for the next-generation healthcare systems, especially in areas where the explosive availability of patient-generated data is expected to make impacts.

Mie2015 workshop-adherence engaging-publicized from Pei-Yun Sabrina Hsueh

]]> 416 7 https://cdn.slidesharecdn.com/ss_thumbnails/mie2015-workshop-adherenceengaging-publicized-150919094721-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

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0 Mie2014 workshop: Gap Analysis of Personalized Health Services through Patient-Controlled Devices /slideshow/mie2014-workshopfulldeckshv5mmsvypclean-40317920/40317920 mie2014-workshop-fulldeck-sh-v5mmsvyp-clean-141015145342-conversion-gate01
Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ IBM T.J. Watson Research Center, Yorktown Heights, NY, USA Hannover Medical School, Germany IBM Research Lab in Haifa, Israel IBM Research Lab in Melbourne, Australia Melbourne Medical School, Australia Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management. ]]>
Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ IBM T.J. Watson Research Center, Yorktown Heights, NY, USA Hannover Medical School, Germany IBM Research Lab in Haifa, Israel IBM Research Lab in Melbourne, Australia Melbourne Medical School, Australia Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management. ]]> Wed, 15 Oct 2014 14:53:42 GMT /slideshow/mie2014-workshopfulldeckshv5mmsvypclean-40317920/40317920 SabrinaHsueh1@slideshare.net(SabrinaHsueh1) Mie2014 workshop: Gap Analysis of Personalized Health Services through Patient-Controlled Devices SabrinaHsueh1 Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ IBM T.J. Watson Research Center, Yorktown Heights, NY, USA Hannover Medical School, Germany IBM Research Lab in Haifa, Israel IBM Research Lab in Melbourne, Australia Melbourne Medical School, Australia Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/mie2014-workshop-fulldeck-sh-v5mmsvyp-clean-141015145342-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds" /> Gap Analysis of Insight-Driven Personalized Health Services through Patient-Controlled Devices Pei-Yun Sabrina HSUEH, , Michael MARSCHOLLEK, Yardena PERES, Stefan von CAVALLAR and Fernando J. MARTIN-SANCHEZ IBM T.J. Watson Research Center, Yorktown Heights, NY, USA Hannover Medical School, Germany IBM Research Lab in Haifa, Israel IBM Research Lab in Melbourne, Australia Melbourne Medical School, Australia Mobile computing, wearable and embedded tech entail new and different styles of healthcare data processing, clinical and wellness decision support, and patient engagement schemes. This is especially important to the preventive and disease management scenarios that require better understanding of disease progression previously unable to achieve due to the lack of reliable means to capture granular patient-generated data in non-clinical settings. The new sources of data, when coupled with a framework to integrate analytical insights with feasible service models, enable reliable detection of inflection points, habit formation cycles and assessments of treatment efficacy. Research into data collection, recording, management and analysis of behavioral manisfestations and triggers will help address these challenges in areas spanning from simple fall detection to situations requiring complicated, multi-modal health monitoring such as Alzheimer’s progression and other adherence management cases. Leveraging recent advance in health devices and sensors as well as expertise in healthcare practice and informatics, the proposed workshop will help form a deeper understanding of requirements on patient-controlled devices to address unique healthcare challenges, identify care flow gaps and translate these findings to the design of platforms for patient-controlled devices and a portfolio of potential service models for preventive care and disease management.

Mie2014 workshop: Gap Analysis of Personalized Health Services through Patient-Controlled Devices from Pei-Yun Sabrina Hsueh

]]> 1422 8 https://cdn.slidesharecdn.com/ss_thumbnails/mie2014-workshop-fulldeck-sh-v5mmsvyp-clean-141015145342-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

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0 MEDINFO 2013 Panel on Personalized Healthcare and Adherence: Issues and Challenges /SabrinaHsueh1/medinfo-2013-panel-on-personalized-health medinfo-08222013-final-submitted-130828084830-phpapp02
Venue: The 14th World Congress on Medical and Health Informatics will take place in Copenhagen, Denmark. http://medinfo2013.dk Moderator: Dr. Marion Ball (IBM Research/JHU); Panelists: Dr. Vimla Patel (NYAM), Dr. Bern Shen (Healthcrowd), Dr. Pei-Yun Sabrina Hsueh (IBM Research) Organizer: Dr. Pei-Yun Sabrina Hsueh (phsueh@us.ibm.com) Personalization is key to the delivery of wellness care including preventive measures and disease management regimes, where patients take on increased responsibility for their own health. While personalized care has already taken a giant leap through genomics, it remains a challenge to understand how individual differences play a role in patient adherence and manage recommended changes accordingly. Practical methods of creating and evaluating personalized systems have not been fully established. In particular, the role of data-driven analytics in producing actionable insights for practitioners is unclear, and the use of behavioral data has created additional challenges to the understanding of patient adherence for effective care delivery. The panel will discuss the challenges that face many countries around personalized care from various perspectives. These range from behavioral aspects such as maintaining good practices, cognitive aspects such as how do individuals make decisions in the lights of good evidence, social aspects such as how to engage patients in sustaining adherence behavior, to technological aspects such as how to evaluate individual applicability of data-driven analytics and personalized technological systems. The panel is expected to contribute to the global community by presenting lessons learned from existing pilot designs and a collective list of recommendations for pilot design of personalized services at the conclusion of this panel. ]]>
Venue: The 14th World Congress on Medical and Health Informatics will take place in Copenhagen, Denmark. http://medinfo2013.dk Moderator: Dr. Marion Ball (IBM Research/JHU); Panelists: Dr. Vimla Patel (NYAM), Dr. Bern Shen (Healthcrowd), Dr. Pei-Yun Sabrina Hsueh (IBM Research) Organizer: Dr. Pei-Yun Sabrina Hsueh (phsueh@us.ibm.com) Personalization is key to the delivery of wellness care including preventive measures and disease management regimes, where patients take on increased responsibility for their own health. While personalized care has already taken a giant leap through genomics, it remains a challenge to understand how individual differences play a role in patient adherence and manage recommended changes accordingly. Practical methods of creating and evaluating personalized systems have not been fully established. In particular, the role of data-driven analytics in producing actionable insights for practitioners is unclear, and the use of behavioral data has created additional challenges to the understanding of patient adherence for effective care delivery. The panel will discuss the challenges that face many countries around personalized care from various perspectives. These range from behavioral aspects such as maintaining good practices, cognitive aspects such as how do individuals make decisions in the lights of good evidence, social aspects such as how to engage patients in sustaining adherence behavior, to technological aspects such as how to evaluate individual applicability of data-driven analytics and personalized technological systems. The panel is expected to contribute to the global community by presenting lessons learned from existing pilot designs and a collective list of recommendations for pilot design of personalized services at the conclusion of this panel. ]]> Wed, 28 Aug 2013 08:48:30 GMT /SabrinaHsueh1/medinfo-2013-panel-on-personalized-health SabrinaHsueh1@slideshare.net(SabrinaHsueh1) MEDINFO 2013 Panel on Personalized Healthcare and Adherence: Issues and Challenges SabrinaHsueh1 Venue: The 14th World Congress on Medical and Health Informatics will take place in Copenhagen, Denmark. http://medinfo2013.dk Moderator: Dr. Marion Ball (IBM Research/JHU); Panelists: Dr. Vimla Patel (NYAM), Dr. Bern Shen (Healthcrowd), Dr. Pei-Yun Sabrina Hsueh (IBM Research) Organizer: Dr. Pei-Yun Sabrina Hsueh (phsueh@us.ibm.com) Personalization is key to the delivery of wellness care including preventive measures and disease management regimes, where patients take on increased responsibility for their own health. While personalized care has already taken a giant leap through genomics, it remains a challenge to understand how individual differences play a role in patient adherence and manage recommended changes accordingly. Practical methods of creating and evaluating personalized systems have not been fully established. In particular, the role of data-driven analytics in producing actionable insights for practitioners is unclear, and the use of behavioral data has created additional challenges to the understanding of patient adherence for effective care delivery. The panel will discuss the challenges that face many countries around personalized care from various perspectives. These range from behavioral aspects such as maintaining good practices, cognitive aspects such as how do individuals make decisions in the lights of good evidence, social aspects such as how to engage patients in sustaining adherence behavior, to technological aspects such as how to evaluate individual applicability of data-driven analytics and personalized technological systems. The panel is expected to contribute to the global community by presenting lessons learned from existing pilot designs and a collective list of recommendations for pilot design of personalized services at the conclusion of this panel. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/medinfo-08222013-final-submitted-130828084830-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Venue: The 14th World Congress on Medical and Health Informatics will take place in Copenhagen, Denmark. http://medinfo2013.dk Moderator: Dr. Marion Ball (IBM Research/JHU); Panelists: Dr. Vimla Patel (NYAM), Dr. Bern Shen (Healthcrowd), Dr. Pei-Yun Sabrina Hsueh (IBM Research) Organizer: Dr. Pei-Yun Sabrina Hsueh (phsueh@us.ibm.com) Personalization is key to the delivery of wellness care including preventive measures and disease management regimes, where patients take on increased responsibility for their own health. While personalized care has already taken a giant leap through genomics, it remains a challenge to understand how individual differences play a role in patient adherence and manage recommended changes accordingly. Practical methods of creating and evaluating personalized systems have not been fully established. In particular, the role of data-driven analytics in producing actionable insights for practitioners is unclear, and the use of behavioral data has created additional challenges to the understanding of patient adherence for effective care delivery. The panel will discuss the challenges that face many countries around personalized care from various perspectives. These range from behavioral aspects such as maintaining good practices, cognitive aspects such as how do individuals make decisions in the lights of good evidence, social aspects such as how to engage patients in sustaining adherence behavior, to technological aspects such as how to evaluate individual applicability of data-driven analytics and personalized technological systems. The panel is expected to contribute to the global community by presenting lessons learned from existing pilot designs and a collective list of recommendations for pilot design of personalized services at the conclusion of this panel.

MEDINFO 2013 Panel on Personalized Healthcare and Adherence: Issues and Challenges from Pei-Yun Sabrina Hsueh

]]> 7704 13 https://cdn.slidesharecdn.com/ss_thumbnails/medinfo-08222013-final-submitted-130828084830-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

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0 https://cdn.slidesharecdn.com/profile-photo-SabrinaHsueh1-48x48.jpg?cb=1666305010 I am currently a Research Staff Member and the Medical Informatics PIC chair of the IBM T.J. Research Center, leading the development of evidence-based wellness analytics and personalized services in the Healthcare Transformation Group. Before working for the healthcare software vertical, I worked on natural language processing-related applications such as social media trend analysis and meeting video summarization. My professional goal is to bring my business acumen and years of analytics training on the table to help translate real-world industry problems into services that can be illuminated with analytics and embedded into existing workflow. I am also interested in developing intell... http://researcher.watson.ibm.com/researcher/view.php?person=us-pshsueh https://cdn.slidesharecdn.com/ss_thumbnails/amia2016-pghd-panel-v8-170109231837-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/amia2016-pghdpanelv8/70839940 Amia2016 pghd-panel-v8 https://cdn.slidesharecdn.com/ss_thumbnails/hec2016-interpretabilitypanel-public-160915173015-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/hec2016-panel-putting-usergenerated-data-in-action-improving-interpretability-for-consumer-informatics/66067698 HEC 2016 Panel: Puttin... https://cdn.slidesharecdn.com/ss_thumbnails/medinfo2015-workshop-adherencemangementpatientdriven-publicized-150919101607-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/medinfo2015-workshopadherence-mangementpatientdrivenpublicized/52960801 Medinfo2015 workshop-a...