This document provides an overview of the global mHealth landscape and the Johns Hopkins mHealth initiatives. It discusses how mobile technologies can be leveraged to collect health data, connect individuals, compress time to intervention, and create opportunities to improve health outcomes. The document outlines several mHealth projects in Bangladesh aiming to improve maternal and child health through tools like mobile phone reminders, vaccination registries, and community health worker systems. It emphasizes the need for rigorous evaluation of mHealth initiatives to generate evidence on effectiveness and ensure technologies improve health.
Towards an Environmental Health Sciences Ontology:CHEAR to HHEAR and BeyondDeborah McGuinness
The National Institute of Environmental Health Sciences (NIEHS) supported a Children's Health Exposure Analysis Repository(CHEAR) program that needed to integrate data across exposure science and health. We led the data science effort of this program and design the CHEAR ontology to support data integration and to leverage a wide range of existing ontologies and vocabularies. We are refactoring the ontology to support human health (instead of just aiming to support child health, and broadening support a broad range of environmental health sciences applications.
Support Dementia: using wearable assistive technology and analysing real-time data (Fehmida Mohamedali and Nasser Matoorian)
Interactive Technologies and Games (ITAG) Conference 2016
Health, Disability and EducationDates: Wednesday 26 October 2016 - Thursday 27 October 2016 Location: The Council House, NG1 2DT
Towards a successful implementation of game mechanics (gamification) in e-hea...Maged N. Kamel Boulos
Cite as: Kamel Boulos MN. Towards a successful implementation of game mechanics (gamification) in e-health interventions (updated: 09//2015). In: Baptista TM, Kamel Boulos MN, Rodrigues FM, Rocha A. E-Health, psychology and medicine: the future of a close cooperation (invited symposium). In: Proceedings of the 14th European Congress of Psychology, Milan, Italy, 7-10 July 2015. URL: http://www.ecp2015.it/scientific-program/invited-symposia/ - WebCite cache: http://www.webcitation.org/6YIHINbi0
Towards an Environmental Health Sciences Ontology:CHEAR to HHEAR and BeyondDeborah McGuinness
The National Institute of Environmental Health Sciences (NIEHS) supported a Children's Health Exposure Analysis Repository(CHEAR) program that needed to integrate data across exposure science and health. We led the data science effort of this program and design the CHEAR ontology to support data integration and to leverage a wide range of existing ontologies and vocabularies. We are refactoring the ontology to support human health (instead of just aiming to support child health, and broadening support a broad range of environmental health sciences applications.
Support Dementia: using wearable assistive technology and analysing real-time data (Fehmida Mohamedali and Nasser Matoorian)
Interactive Technologies and Games (ITAG) Conference 2016
Health, Disability and EducationDates: Wednesday 26 October 2016 - Thursday 27 October 2016 Location: The Council House, NG1 2DT
Towards a successful implementation of game mechanics (gamification) in e-hea...Maged N. Kamel Boulos
Cite as: Kamel Boulos MN. Towards a successful implementation of game mechanics (gamification) in e-health interventions (updated: 09//2015). In: Baptista TM, Kamel Boulos MN, Rodrigues FM, Rocha A. E-Health, psychology and medicine: the future of a close cooperation (invited symposium). In: Proceedings of the 14th European Congress of Psychology, Milan, Italy, 7-10 July 2015. URL: http://www.ecp2015.it/scientific-program/invited-symposia/ - WebCite cache: http://www.webcitation.org/6YIHINbi0
Predictive Analytics and Machine Learning for Healthcare - DiabetesDr Purnendu Sekhar Das
Machine Learning on clinical datasets to predict the risk of chronic disease conditions like Type 2 Diabetes mellitus beforehand; as well as predicting outcomes like hospital readmission using EMR RWE data.
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Advances in information and communication technologies have led to the emergence of Internet of Things
(IoT). In the modern health care environment, the usage of IoT technologies brings convenience to physicians and
patients since they are applied to various medical areas (such as real-time monitoring, patient information and healthcare
management). The body sensor network (BSN) technology is one of the core technologies of IoT developments in
healthcare system, where a patient can be monitored using a collection of tiny-powered and lightweight wireless sensor
nodes
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
Computer Patient Interviewing & Pilot Medical Assessment #ICASM2015ICASM2015
Slides to accompany talk given by Dr Richard Sills on Wednesday 23rd September 2015 at the 63rd International Congress of Aviation and Space Medicine, held at Oxford University (UK).
http://icasm2015.org/
For more information on Instant Medical History and adding Computer Patient Interviewing to Pilot Medical Assessments please visit MedicalHistory.com and contact Richard Sills at rosills1@gmail.com
HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretabi...Pei-Yun Sabrina Hsueh
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.
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
'인공지능은 의료를 어떻게 혁신하는가' 주제의 2017년 11월 버전입니다.
'How Artificial Intelligence would Innovate the medicine of the future'
최윤섭 소장 (최윤섭 디지털 헬스케어 연구소)
Yoon Sup Choi, PhD (Director/Founder, Digital Healthcare Institute)
yoonsup.choi@gmail.com
For mHealth to work it needs to be disruptive. This presentation, from Mobile Monday's mHealth event in Amsterdam, looks at how wireless technology will enable it, and explores the myths, barriers, business models and alternative approaches.
Predictive Analytics and Machine Learning for Healthcare - DiabetesDr Purnendu Sekhar Das
Machine Learning on clinical datasets to predict the risk of chronic disease conditions like Type 2 Diabetes mellitus beforehand; as well as predicting outcomes like hospital readmission using EMR RWE data.
Augmented Personalized Health: using AI techniques on semantically integrated...Amit Sheth
Keynote @ 2018 AAAI Joint Workshop on Health Intelligence (W3PHIAI 2018), 2 February 2018, New Orleans, LA [Video: https://youtu.be/GujvoWRa0O8]
Related article: https://ieeexplore.ieee.org/document/8355891/
Abstract
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease-focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-population physical-cyber-social big data-driven. While the ability to create and capture data is already here, the upcoming innovations will be in converting this big data into smart data through contextual and personalized processing such that patients and clinicians can make better decisions and take timely actions for augmented personalized health. In this talk, we will discuss how use of AI techniques on semantically integrated patient-generated health data (PGHD), environmental data, clinical data, and public social data is exploited to achieve a range of augmented health management strategies that include self-monitoring, self-appraisal, self-management, intervention, and Disease Progression Tracking and Prediction. We will review examples and outcomes from a number of applications, some involving patient evaluations, including asthma in children, bariatric surgery/obesity, mental health/depression, that are part of the Kno.e.sis kHealth personalized digital health initiative.
Background: Background: http://bit.ly/k-APH, http://bit.ly/kAsthma, http://j.mp/PARCtalk
Advances in information and communication technologies have led to the emergence of Internet of Things
(IoT). In the modern health care environment, the usage of IoT technologies brings convenience to physicians and
patients since they are applied to various medical areas (such as real-time monitoring, patient information and healthcare
management). The body sensor network (BSN) technology is one of the core technologies of IoT developments in
healthcare system, where a patient can be monitored using a collection of tiny-powered and lightweight wireless sensor
nodes
Wide adoption of smartphones and availability of low-cost sensors has resulted in seamless and continuous monitoring of physiology, environment, and public health notifications. However, personalized digital health and patient empowerment can become a reality only if the complex multisensory and multimodal data is processed within the patient context. Contextual processing of patient data along with personalized medical knowledge can lead to actionable information for better and timely decisions. We present a system called kHealth capable of aggregating multisensory and multimodal data from sensors (passive sensing) and answers to questionnaire (active sensing) from patients with asthma. We present our preliminary data analysis comprising data collected from real patients highlighting the challenges in deploying such an application. The results show strong promise to derive actionable information using a combination of physiological indicators from active and passive sensors that can help doctors determine more precisely the cause, severity, and control level of asthma. Information synthesized from kHealth can be used to alert patients and caregivers for seeking timely clinical assistance to better manage asthma and improve their quality of life.
Paper: http://www.knoesis.org/library/resource.php?id=2153
Citation:
Pramod Anantharam, Tanvi Banerjee, Amit Sheth, Krishnaprasad Thirunarayan, Surendra Marupudi, Vaikunth Sridharan, Shalini G. Forbis, Knowledge-driven Personalized Contextual mHealth Service for Asthma Management in Children , IEEE 4th International Conference on Mobile Services, June 27 - July 2, 2015, New York, USA.
Computer Patient Interviewing & Pilot Medical Assessment #ICASM2015ICASM2015
Slides to accompany talk given by Dr Richard Sills on Wednesday 23rd September 2015 at the 63rd International Congress of Aviation and Space Medicine, held at Oxford University (UK).
http://icasm2015.org/
For more information on Instant Medical History and adding Computer Patient Interviewing to Pilot Medical Assessments please visit MedicalHistory.com and contact Richard Sills at rosills1@gmail.com
HEC 2016 Panel: Putting User-Generated Data in Action: Improving Interpretabi...Pei-Yun Sabrina Hsueh
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.
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
'인공지능은 의료를 어떻게 혁신하는가' 주제의 2017년 11월 버전입니다.
'How Artificial Intelligence would Innovate the medicine of the future'
최윤섭 소장 (최윤섭 디지털 헬스케어 연구소)
Yoon Sup Choi, PhD (Director/Founder, Digital Healthcare Institute)
yoonsup.choi@gmail.com
For mHealth to work it needs to be disruptive. This presentation, from Mobile Monday's mHealth event in Amsterdam, looks at how wireless technology will enable it, and explores the myths, barriers, business models and alternative approaches.
This slide deck is comprised of lectures delivered at Nova Southeastern University Colleges of Medicine (MI) and Pharmacy (PHA) in the following courses:
MI 6410 Consumer Health Informatics and Web 2.0 in Healthcare
PHA 5203 Consumer Health Informatics and Web 2.0 in Healthcare
Non Invasive Health Monitoring with mHealthBart Collet
mHealth Trends and examples of non invasive mobile health devices, organisations and services.
Made as preparation for MoMoAMS #14 about mHealth, Jan 25th 2010, Amsterdam
How Wearables will transform the EHR (Electronic Disease Record), slide deck for presentation by David Doherty (@mHealth) at Wearables Europe, London, 28 May 2015.
Learn more about Monty C. M. Metzger at http://blog.monty.de/keynote-speaker
Contact me at monty (at) aheadoftime (dot) de
Mobile Health (mHealth)
What are the key trends in mHealth? What are the best example and cases of mHealth today?
What role will the mobile phone play for the health, pharma and medicine industry? And what can your cell phone do for your personal health?
The Anotated bilography should look like this Social1) S.docxmattinsonjanel
The Anotated bilography should look like this:
Social:
1) Strachan, Juliet, and Vincent Pavie-Latour. "Food for Thought." International Journal of Market Research 50.01 (2008): 13-27. Print. Since a long time, people argued wither to concentrate advertisements on children and youth. Children an Youth are our society while the advertisement is one of the important tool to make marketing. We have to care about our generations and not to stop making business. Here is an article supporting my idea.
2) Gbadamosi, Ayantunji, Robert E. Hinson, Eddy K. Tukamushaba, and Irene Ingunjiri. "Children’s Attitudinal Reactions to TV Advertisements." International Journal of Market Research 54.4 (2012): 543+. Print. It's a study has been done on African Children to figure how they behave and thier reactions. The study provede that kids have point in thier mantelaty they can analysis and get feedback from them.Its case of study helps me in certain way.
3)
4)
5)
Economics:
1)
2)
3)
4)
5)
Politics:
1)
Quinlan, Mark. "Thousands Could Lose Internet Access July 9 Due to Virus." CNBC News (2012): n. pag. CBCnews. CBC/Radio Canada, 04 July 2012. Web. 05 Aug. 2014. Lot of information about internet and how to secure our children from the abusers. It helps me in statistics and ways to be awareness and useful methods to use.
2)
Messmer, Ellen. "The Worst Data Breach Incidents of 2012 – So Far." The Worst Data Breach Incidents of 2012 – So Far. N.p., 18 June 2012. Web. 30 July 2014. Its related to my article by the statistics it has.
3)
Author is trying to explain how can we afford the safe environment to Internet to kids with all support ways to improve the kids' skills. In Europe, governments are supporting the childhood privacy in more secure sites. "Particular attention will be paid to soft law adopted in the UK and in France." Its such an awesome source taking about law in our case of study.
4)
5)
http://web.a.ebscohost.com.ezproxy.library.ewu.edu/ehost/detail/detail?sid=13c127bb-2ef4-4388-bde6-190c2cd83e35%40sessionmgr4004&vid=2&hid=4214&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#db=bth&AN=37362616
http://web.a.ebscohost.com.ezproxy.library.ewu.edu/ehost/detail/detail?sid=84b2632c-da79-4031-8c5a-a932a345513b%40sessionmgr4004&vid=0&hid=4214&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#db=bth&AN=78072523
http://web.a.ebscohost.com.ezproxy.library.ewu.edu/ehost/detail/detail?sid=be241d5d-6c48-4a67-8550-87ee54dc1e6f%40sessionmgr4001&vid=0&hid=4214&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#db=bth&AN=96330681
http://web.a.ebscohost.com.ezproxy.library.ewu.edu/ehost/detail/detail?vid=8&sid=a5068c93-d46a-4f6c-ae99-dfe9e542cf0d%40sessionmgr4001&hid=4214&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#db=bth&AN=27996445
He used the following resources: (you may use the first one and what you see as it works well with the essay)
Some sorces and links that needed in the annotated bibliography
In Defense of Data (2013) ‘Data Breach tre ...
디지털 헬스케어 기반의 능동적, 선제적 보험
수동적, 사후적 대응에서 능동적, 선제적 관리로의 변화
- 디지털 헬스케어 기반의 가입자 데이터의 측정
- 데이터 분석을 통한 가입자 관리: 질병 위험군 분류, 계리
- 질병 관리 및 치료에 대한 능동적 개입: 관리 방안 및 인센티브
How to implement digital medicine in the futureYoon Sup Choi
by Yoon Sup Choi, PhD
yoonsup.choi@gmail.com
Professor, SAHIST, Sungkyunkwan University
Director, Digital Healthcare Institute
Managing Partner, Digital Healthcare Partners
March 2024 - Top 10 Read Articles in Computer Networks & CommunicationsIJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
An intelligent approach to take care of mother and baby healthIJECEIAES
This is the era of technology and is widely used in every sector. In Bangladesh the use of technology is increasing day by day in many sectors. Health sector is one of them. This research is designed and developed to help the pregnant women to get weekly information on development and conditions of their health and the growing child inside their womb. This system will notify expectant mothers automatically about their health checkup date and time. It provides general and special health information to the expectant mothers. It is designed with user friendly interface so that an expectant mother can use this system very effectively. This system allows a unique secure login system and provides a unique suggestion to the expectant mothers.This system is very user friendly and useful.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Labrique global health v4
1.
2.
3. Alain B. Labrique, PhD, MHS, MS
Director
JHU Global mHealth Initiative (JHU-GmI)
Associate Professor
Program in Global Disease Epidemiology and Control
Dept. of International Health & Dept. of Epidemiology (jt)
Johns Hopkins Bloomberg School of Public Health
JHU School of Nursing
JHU School of Medicine (Health Informatics)
9. Untethered, yet connected:
Diverse applications of ubiquitous
wireless and mobile technologies
designed to improve and
enhance health research, health services
delivery and health outcomes
mHealth
10. mHealth:The Four C’s
Harnessing ubiquitous information
and communication technology to
collect data, connect individuals to
each other and to information,
compress time and create
opportunities to intervene.
11. Global “mHealth” is a complex, diverse
development space, and is not homogenous.
14. “JiVitA” Maternal and Child Health Research Project
(WWW.JIVITA.ORG)
Public Health, Maternal and Child Health
and Nutrition Efficacy Research
to
Improve Health and Save Lives in
Bangladesh, South Asia and Globally.
19. Rural families use mobile phones
during severe pregnancy crises
N=11,451 (2007-2010)
Source: Labrique, mHealth Summit, Washington DC, 2011
20. 168,231 Woman Survey –
Gaibandha, Bangladesh
(January-March 2012)
• 71% Households own phones
• 20% Used a phone in past 30 days for
emergency health purpose
• Phone owners 2.8 times more likely to
use phone for health call
• ONLY 23% Electricity in home!
Labrique et al., Unpublished data, mHealth Summit 2012
21. 0
.2.4.6.8
1
2008 2009 2010 2011 2012
Year
Lowest Quartile WI (n=17,176) Low Quartile WI (n=19,789)
High Quartile WI (n=6,472) Highest Quartile WI (n=1,032)
Mobile Phone Ownership by WI over Time
Household Mobile Phone Ownership over time in rural
Bangladesh, by “Wealth Index” (n=44,469)
Labrique, Tran et al, 2013 (in press)
ProportionofHHreporting“MobilePhoneOwnership”
22. Challenges in averting neonatal mortality –
being at the right place, at the right time…
•1st Day – 50% of deaths
•1st Week – 75% of deaths
Source: Lawn JE et al Lancet 2005, Based on analysis of 47 DHS datasets (1995-2003), 10,048 neonatal deaths)
“Hot Zone”
25. Tremendous time and effort is invested in manual
data collection, aggregation and reporting.
Example: Bangladesh
CHW’s 19 ledgers contain 473
unique data fields.
Only 60 fields are unique,
required for a digital system
to process the same
information.
37. Emerging “Lessons”
• User-centered / User-engaged design
• Extensive formative research & workflow mapping
• Iterative technical deployment and stabilization
• Early government and community engagement
• Mixed-methods evaluation
• Plan for technical failures / build-in system
redundancy
• “Control” systems to prevent & monitor misuse
39. PROVIDER
HEALTH
SYSTEM
PATIENT
Access to information
Behavior change
Activity Monitoring
Self-reported Data
Workflow management
Decision Support
Surveillance and Tracking
Remuneration / Incentives
Workforce monitoring
Real-time Data Streams
Supply-chain management
40.
41. Providing families access to
timely information
“If you have any
bleeding during this
month, seek medical
attention right away”
Expectant women/
new mothers sign
up for service
Users receive
health-related
messages weekly
“Freemium” model to
drive coverage
“Your baby needs an
immunization this week
to stay healthy:
Available free at all
EPI clinics”
50. Healthcare Worker
Communication and Training
• Data collection and
communication tools
• Multimedia courses and lectures
• mLearning on Demand
• Interactive Quizzes
www.emocha.org
58. New frontiers!
Remote, Point-of-care Diagnostic tools
Breslauer D., et al. 2009 Mobile Phone Based Clinical Microscopy for Global Health Applications. PLoS ONE 4(7): e6320
59.
60. Mobile-based Flow Cytometry
Ozcan Research Group (Nano-Bio Photonics / UCLA): Optical imaging techniques for point-of-care diagnostics
Hongying Zhu , Serhan O. Isikman , Onur Mudanyali , Alon Greenbaum and Aydogan Ozcan Lab Chip, 2012, Advance Article
70. The Bellagio eHealth
Evaluation Declaration 2011
“Rigorous evaluation of
e- & m-Health is necessary to
generate useful evidence and
promote the appropriate
integration of technologies to
improve health and reduce
inequalities.”
71. Bellagio Call to Action 2011
If used improperly, eHealth may divert
valuable resources and even cause
harm… implementation must be
guided by evidence…
72. “mHealth tools and interventions must be backed up
by rigorous scientific development, evaluation, and
evidence generation to enhance meaningful
innovation and best practices, and to validate tools
and methods for health professionals, consumers,
payers, governments, and industry.”
73.
74.
75. Why “Evidence” ?
1. Health investments in global health are driven
by more than market forces
2. Limited resources = Need for stringent, cost-
effectiveness based planning
3. Two decades of Emphasis on EBD !
4. Donors: Increased transparency / scrutiny
5. Population-side demand for improved quality
6. e-Health / ICT induced political fatigue
79. “Maturity” of the mHealth Project
AmountofInformation(RED)
Threshold of “Information”
Stability Functionality Useability Efficacy Effectiveness
Methodology
Systems Engineering Qualitative Quantitative Mixed Q/Q / M&E
“Evidence” Across The mHealth Maturity Lifecycle
OF
WHAT ?
MEASURED
HOW ?
80. mHealth Technical Evidence Review Group for RMNCH
“m-TERG”
“Providing governments and implementing agencies
objective, evidence-based guidance for the
selection and scale of mHealth strategies
across the reproductive, maternal,
newborn and child health continuum”
85. What is the problem we’re trying to solve ?
AVAILABILITY
4.2.1 Supplyof
commodities
4.2.2 Supplyof
services
4.2.3 Supplyof
equipment
4.2.4 Diversityof
treatment
options
INFORMATION
4.1.1 Lack of
population
enumeration
4.1.2 Delayed
reportingof
events
4.1.3 Quality/
unreliabilityof
data
4.1.4
Communication
roadblocks
4.1.5 Accessto
informationor
data
COST
4.7.1 Expenses
relatedto
commodity
production
4.7.2 Expenses
relatedto
commodity
supply
4.7.3 Expenses
relatedto
commodity
disbursement
4.7.4 Expenses
relatedtoservice
delivery
4.7.5 Client-side
expenses
UTILIZATION
4.5.4 Lossto
follow up
4.5.1 Demandfor
services
4.5.2 Geographic
inaccessibility
4.5.3 Low
adherenceto
treatments
ACCEPTABILITY
4.4.3 Stigma
4.4.1Alignment
withlocal norms
4.4.2Addressing
individual beliefs
andpractices
EFFICIENCY
4.6.1 Workflow
management
4.6.2 Effective
resource
allocation
4.6.5 Timeliness
of care
4.6.3 Unnecessary
referrals/
transportation
4.6.4 Planning
andcoordination
QUALITY
4.3.1 Qualityof
care
4.3.3 Qualityof
Commodity
4.3.4 Health
worker
motivation
4.3.2 Health
worker
competence
4.3.6 Supportive
supervision
4.3.5 Continuity
of care
86. mHealth Strategy Intermediate Outcome Outcome / Impact
Provider Competence,
Accountability,
Effectiveness.
Client Knowledge
and Self-Efficacy
Improved
Health Outcomes
Improved
Quality
of Care
Improved
Health
Behaviors
Disease Surveillance
Electronic Medical Records
Remote Monitoring
Logistics monitoring and tracking
Decision Support Systems
Point-of-care Diagnostics
Appointment Scheduling
Client reporting of quality / performance
On-Demand Training / Assessment
Client Education
On-demand Information / Helplines
Supply Chain Integrity
Accuracy of Information
Continuity of Care
Affordability of Care
Financing (Banking, Insurance)
Enhanced Counseling
Improved
Efficiency /
Coverage
Vital Statistics Reporting
Improved
Population
Health
Real-time Data Access / PHRCLIENTPROVIDERHEALTHSYSTEM
Remote Consultation
Improved Dem. / Hlth. Data
Appropriate Resource Alloc.
Policy Adjustments
Workflow Management Systems
Responsive
Health System
89. Why a mHealth and ICT
Framework for RMNCH?
•Allows focus on health systems strategy of the
mHealth innovation, not just the technology.
•Provides projects with a communication tool when
talking with different stakeholders, including
governments about what mHealth offers.
•Allows identification of uniqueness, commonalities
and gaps across multiple mHealth projects through
the use of a consistent and health systems-focused
vocabulary.
91. RMNCH Continuum:
Known Interventions
mHealth Strategy: …overcoming
these constraints:
Touching these
“actors” in the
system:
Labrique, Mehl, Vasudevan et al. 2013 (MS in Review)
93. Step 2: Develop repositories of
m-evidence and m-activities
Help to identify, collate and grade the
quality of information on mHealth
strategies
94. What do we know ? What has been tried ?
mHealthEvidence.org / mHealthKnowledge.org
95. Helping to Consolidate efforts Globally
And other partners…
MREGISTRY.ORG
A Global mHealth Project Registry
96. Step 3: Facilitate the review and
synthesis of evidence
Help to understand when sufficient
information exists to recommend
mHealth as part of the standard of care
104. Evidence Prioritization Summary
mHealth strategies likely to demonstrate:
• improved client access to information
• enhanced traditional methods of counseling and BCC
• bolstered client adherence to medication, and attendance to
scheduled appointments
• shortened turnaround time for performance data submission
• improved workforce scheduling, monitoring and accountability
• improved workforce training and continued education
• supported caregivers through decision support tools
• strengthened commodities supply chains and reduce risk of
stockouts
• created shorter feedback loops for systemic response
“mHealth Extends REACH, Creates CONVENIENCE, Shortens INFORMATION lag,
and Facilitates TARGETTED CARE when and where its needed.”
mTERG
105. Where can we have the most impact ?
Mehl G, Labrique AB. Science Sept. 2014.
106. An Ecosystem of mTools for
Cross-Sectoral Development exists!
“m” – spans Health, Agriculture, Education,
Politics, Finance, Data Collection
107. Eras of mHealth
I
Innovation and Experimentation
II
Discordant Proliferation
III
Scrutiny and Consolidation
IV
Integration and Scale
108.
109. Degree to which the mHealth strategy changes the status quo
INCREMENTAL CHANGE DISRUPTIVE INNOVATION
DIFFICULTYOFSCALING
COMPLEXITYOFENGAGEDECOSYSTEM
INSTITUTIONAL/HEALTHSYSTEMINERTIA
110. Challenges
- Tentative funding for pilots and
demonstrations, limited investment in
scale
- Rapidly growing, complex ecosystem
with new non-health actors
- Duplicative efforts, lack of
interoperability
- Siloes of innovation, without clear
pathways to integration
- Economic evaluations of mHealth
interventions are lacking
111. • For scale-up / Mainstreaming of mHealth, we need to:
• …Reach BEYOND the “converted”
Speak the language of HEALTH decision-makers
• …STOP taking shortcuts – measuring attributable
impact or cost is not an afterthought, an inexpensive
or easy task.
• …SUPPORT a high threshold of information quality,
establishing new methods where appropriate, but
aligning claims with data.
116. Draw inspiration from Botswana and Bangladesh to Brussels and Baltimore to
understand what is m…… POSSIBLE
Thank you.
http://tinyurl.com/mpossible-video
119. Follow a robust process
USERS
•Identify Users
•Define Target Population
ROLES
•Define Roles
•Map Workflow / Scheduling rules
DATA
•Map Data “Universe”
•Deconstruct data elements
OPTIMIZE
•Assess Data Efficiency
•Identify opportunities for Optimization
DESIGN
•End User Engagement
•User-Acceptability / Functionality
BUILD
•Program, Deploy, Test
•Evaluate
120. UN IWG mHealth Catalytic Grantee Projects
mehlg@who.int