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Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston 2016 University of Massachusetts Medical School

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston

Stephenie C. Lemon

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based ...


Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston 2016 University of Massachusetts Medical School

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston

Kathleen M. Mazor

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based ...


Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston 2016 University of Massachusetts Medical School

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston

Sarah L. Cutrona

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based ...


Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston 2016 University of Massachusetts Medical School

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring For Health Behavior Change Into The 21st Century, Rajani S. Sadasivam, Sarah L. Cutrona, Rebecca L. Kinney, Benjamin M. Marlin, Kathleen M. Mazor, Stephenie C. Lemon, Thomas K. Houston

Rajani S. Sadasivam

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based ...


Cardiomems™ In Lvad Patients: A Case Series, Maya Guglin, Bennet George, Sarah Branam, Amanda Hart 2016 Gill Heart Institute, University of Kentucky

Cardiomems™ In Lvad Patients: A Case Series, Maya Guglin, Bennet George, Sarah Branam, Amanda Hart

The VAD Journal

Patients with a left ventricular assist device (LVAD) commonly encounter issues with volume status post-implant. Volume overload can result from incomplete compensation of left ventricular failure or from right ventricular failure. The CardioMEMS™ intracardiac hemodynamic monitoring device is an area of growing interest regarding the management of chronic congestive heart failure, however, its utility has not been serially investigated in patients with an LVAD. We present a case series of patients with ventricular assist devices care for at our institution in which the CardioMEMS™ device aided in the management of volume status and pump performance.


A Harmonized Data Quality Assessment Terminology And Framework For The Secondary Use Of Electronic Health Record Data, Michael G. Kahn, Tiffany J. Callahan, Juliana Barnard, Alan E. Bauck, Jeff Brown, Bruce N. Davidson, Hossein Estiri, Carsten Goerg, Erin Holve, Steven G. Johnson, Siaw-Teng Liaw, Marianne Hamilton-Lopez, Daniella Meeker, Toan C. Ong, Patrick Ryan, Ning Shang, Nicole G. Weiskopf, Chunhua Weng, Meredith N. Zozus, Lisa Schilling 2016 University of Colorado Anschutz Medical Campus

A Harmonized Data Quality Assessment Terminology And Framework For The Secondary Use Of Electronic Health Record Data, Michael G. Kahn, Tiffany J. Callahan, Juliana Barnard, Alan E. Bauck, Jeff Brown, Bruce N. Davidson, Hossein Estiri, Carsten Goerg, Erin Holve, Steven G. Johnson, Siaw-Teng Liaw, Marianne Hamilton-Lopez, Daniella Meeker, Toan C. Ong, Patrick Ryan, Ning Shang, Nicole G. Weiskopf, Chunhua Weng, Meredith N. Zozus, Lisa Schilling

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Objective: Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths and limitations of electronic health record (EHR) data for operational analytics, quality improvement, and research. Existing published DQ terms were harmonized to a comprehensive unified terminology with definitions and examples and organized into a conceptual framework to support a common approach to defining whether EHR data is ‘fit’ for specific uses.

Materials and Methods: DQ publications, informatics and analytics experts, managers of established DQ programs, and operational manuals from several mature EHR-based research networks were reviewed to identify potential DQ terms ...


A Qualitative Review Of Differential Diagnosis Generators, William Bond MD, MS, Linda M. Schwartz MDE, AHIP, CM, Kevin R. Weaver DO, Donald Levick MD, MBA, Michael Guliano MD, MEd, MHPE, Mark L. Graber MD 2016 Lehigh Valley Health Network, University of South Florida

A Qualitative Review Of Differential Diagnosis Generators, William Bond Md, Ms, Linda M. Schwartz Mde, Ahip, Cm, Kevin R. Weaver Do, Donald Levick Md, Mba, Michael Guliano Md, Med, Mhpe, Mark L. Graber Md

Kevin Weaver, D.O., FACOEP

No abstract provided.


A Randomized Controlled Trial Of A Videoconferencing Smoking Cessation Intervention For Korean American Women: Preliminary Findings, Sun S. Kim, Somporn Sitthisongkram, Kunsook Bernstein, Hua (Julia) Fang, Won S. Choi, Douglas M. Ziedonis 2016 University of Massachusetts Boston

A Randomized Controlled Trial Of A Videoconferencing Smoking Cessation Intervention For Korean American Women: Preliminary Findings, Sun S. Kim, Somporn Sitthisongkram, Kunsook Bernstein, Hua (Julia) Fang, Won S. Choi, Douglas M. Ziedonis

Quantitative Health Sciences Publications and Presentations

Introduction: Korean women are reluctant to pursue in-person smoking cessation treatment due to stigma attached to women smokers and prefer treatment such as telephone and online smoking cessation programs that they can access secretively at home. However, there is some evidence that face-to-face interaction is the most helpful intervention component for them to quit smoking.

Methods: This study is a pilot clinical trial that examined the acceptability and feasibility of a videoconferencing smoking cessation intervention for Korean American women and compared its preliminary efficacy with a telephone-based intervention. Women of Korean ethnicity were recruited nationwide in the United States and ...


Creating A Better World With Information And Communication Technologies: Health Equity, Sajda Qureshi 2016 University of Nebraska at Omaha

Creating A Better World With Information And Communication Technologies: Health Equity, Sajda Qureshi

Sajda Qureshi

When news broke on 23rd July 2014, that a case of the deadly virus Ebola had been confirmed in Lagos, home to about 21 million people and a major transportation hub, the World held its breath. If not contained, this virus could spread quickly killing a multitude of people around the World. By 15th October, cases of Ebola had been recorded around the World: Liberia reported 4249 cases with 2458 deaths, Sierra Leone reported 3252 cases with 1183 deaths, Guinea 1472 cases with 843 deaths, Nigeria reported 20 cases with 8 deaths, the USA reported 3 cases and 1 death ...


Are We Making A Better World With Information And Communication Technology For Development (Ict4d) Research? Findings From The Field And Theory Building, Sajda Qureshi 2016 University of Nebraska at Omaha

Are We Making A Better World With Information And Communication Technology For Development (Ict4d) Research? Findings From The Field And Theory Building, Sajda Qureshi

Sajda Qureshi

As Information and Communication Technologies (ICTs) continue to penetrate people’s lives the world over, there is a sense that understanding the role of ICTs in the context of development needs to be conceptualized theoretically while making empirical contributions that add to what we know (Avgerou, 2008; Davison, 2012; Sein and Harindranath, 2004; Sahay and Walsham, 1995). Other scholars have pointed to the importance of this research for the field of Information Systems (ISs) in offering broader contributions. Avgerou (2008) suggests that in the era of globalization such research offers contributions in ISs beyond “organizational organizational and national boundaries and ...


Advancing Population Health: New Models And The Role Of Research. An Overview Of The 22nd Annual Health Care Systems Research Network Conference, Robert T. Greenlee, Lois E. Lamerato, Sarah M. Greene 2016 Marshfield Clinic Research Foundation

Advancing Population Health: New Models And The Role Of Research. An Overview Of The 22nd Annual Health Care Systems Research Network Conference, Robert T. Greenlee, Lois E. Lamerato, Sarah M. Greene

Journal of Patient-Centered Research and Reviews

The Health Care Systems Research Network (HCSRN; formerly HMO Research Network) held its annual conference in Atlanta, Georgia, in April 2016. A consortium of research organizations affiliated with 20 large health care delivery systems, the HCSRN met for the 22nd consecutive year to report on scientific achievements, develop and share skills and best practices, and promote new research collaborations. The 2016 conference, with a theme of “Advancing Population Health: New Models and the Role of Research,” was co-hosted on behalf of HCSRN by Marshfield Clinic Research Foundation and Henry Ford Health System’s Public Health Sciences Department. The 350 ...


Abstracts From The 22nd Annual Health Care Systems Research Network Conference, April 13–16, 2016, Atlanta, Georgia, 2016 Aurora Health Care

Abstracts From The 22nd Annual Health Care Systems Research Network Conference, April 13–16, 2016, Atlanta, Georgia

Journal of Patient-Centered Research and Reviews

This proceedings supplement includes selected abstracts presented at the 22nd annual conference of the Health Care Systems Research Network (HCSRN), held April 1316, 2016, in Atlanta, Georgia. The HCSRN connects the resources and capabilities of research departments from its member health care systems. Collectively, the organization represents more than 1,900 scientists and research staff from an array of disciplines such as epidemiology, economics, disparities, outcomes and quality assessment, trials and genomics.


Telehealth At Jefferson: The Future Of Medicine, Danica Stone 2016 Jefferson University Hospitals

Telehealth At Jefferson: The Future Of Medicine, Danica Stone

Population Health Matters (Formerly Health Policy Newsletter)

No abstract provided.


Using Machine Learning And Natural Language Processing Algorithms To Automate The Evaluation Of Clinical Decision Support In Electronic Medical Record Systems, Donald A. Szlosek, Jonathan M. Ferretti 2016 University of Southern Maine

Using Machine Learning And Natural Language Processing Algorithms To Automate The Evaluation Of Clinical Decision Support In Electronic Medical Record Systems, Donald A. Szlosek, Jonathan M. Ferretti

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: As the number of clinical decision support systems incorporated into electronic medical records increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. Here we use machine learning and natural language processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an electronic medical record system and compare it against manual evaluation.

Methods: Modeled after the electronic medical record system EPIC at Maine Medical Center, we developed a dummy dataset containing physician notes in free text for 3621 artificial patients ...


Using A Patient Portal To Transmit Patient Reported Health Information Into The Electronic Record: Workflow Implications And User Experience, Barbara Sorondo, Amy Allen, Janet Bayleran, Stacy Doore, Samreen Fathima, Iyad Sabbagh, Lori Newcomb 2016 Eastern Maine Medical Center

Using A Patient Portal To Transmit Patient Reported Health Information Into The Electronic Record: Workflow Implications And User Experience, Barbara Sorondo, Amy Allen, Janet Bayleran, Stacy Doore, Samreen Fathima, Iyad Sabbagh, Lori Newcomb

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: This project implemented an integrated patient self-reported screening tool in a patient portal and assessed clinical workflow and user experience in primary care practices.

Methods: An electronic health risk assessment based on the CMS Annual Wellness Visit (AWV) was developed to integrate self-reported health information into the patient’s electronic health record (EHR). Patients enrolled in care coordination tested the implementation. The evaluation plan included quantitative and qualitative measures of patient adoption, provider adoption, workflow impact, financial impact, and technology impact.

Findings: Seventy-two patients completed the sample AWV, and 80% of the questionnaires had clinical findings that required provider ...


Health Information System Implementation In A Complex Acute Care Environment: A Sociotechnical Analysis, Maximillian D. Besworth 2016 The University of Western Ontario

Health Information System Implementation In A Complex Acute Care Environment: A Sociotechnical Analysis, Maximillian D. Besworth

Electronic Thesis and Dissertation Repository

With the increase of information systems in health care, there is a growing need to better understand factors that contribute to the implementation and use of such technology. This secondary analysis explored the implementation of a health information system in a large acute care hospital from the perspective of hospital leadership and the health information system developers. The purpose of this study was to: (a) explore a group of interprofessional leaders’ perceptions of social and technical factors which impacted an HIS implementation within an acute care hospital organization; and, (b) uncover how the various social and technical forces contributed to ...


Framework For Deploying A Virtualized Computing Environment For Collaborative And Secure Data Analytics, Adrian Meyer, Laura Green, Ciearro Faulk, Stephen Galla, Anne-Marie Meyer 2016 UNC Lineberger Comprehensive Cancer Center

Framework For Deploying A Virtualized Computing Environment For Collaborative And Secure Data Analytics, Adrian Meyer, Laura Green, Ciearro Faulk, Stephen Galla, Anne-Marie Meyer

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information.

Framework: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures. It outlines 6 core components: Security, Ease of Access, Performance, Cost, Tools, and Training.

Conclusion: A platform ...


What Causes Care Coordination Problems? A Case For Microanalysis, Wayne Zachary, Russell Charles Maulitz, Drew A. Zachary 2016 Starship Health Technologies, LLC

What Causes Care Coordination Problems? A Case For Microanalysis, Wayne Zachary, Russell Charles Maulitz, Drew A. Zachary

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: Care coordination (CC) is an important fulcrum for pursuing a range of health care goals. Current research and policy analyses have focused on aggregated data rather than on understanding what happens within individual cases. At the case level, CC emerges as a complex network of communications among providers over time, crossing and recrossing many organizational boundaries. Micro-level analysis is needed to understand where and how CC fails, as well as to identify best practices and root causes of problems.

Coordination Process Diagramming: Coordination Process Diagramming (CPD) is a new framework for representing and analyzing CC arcs at the micro ...


Collecting, Integrating, And Disseminating Patient-Reported Outcomes For Research In A Learning Healthcare System, Christopher A. Harle, Gloria Lipori, Robert W. Hurley 2016 Indiana University Richard M. Fairbanks School of Public Health

Collecting, Integrating, And Disseminating Patient-Reported Outcomes For Research In A Learning Healthcare System, Christopher A. Harle, Gloria Lipori, Robert W. Hurley

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: Advances in health policy, research, and information technology have converged to increase the electronic collection and use of patient-reported outcomes (PROs). Therefore, it is important to share lessons learned in implementing PROs in research information systems.

Case Description: The purpose of this case study is to describe a novel information system for electronic PROs and lessons learned in implementing that system to support research in an academic health center. The system incorporates freely available and commercial software and involves clinical and research workflows that support the collection, transformation, and research use of PRO data. The software and processes that ...


A Framework To Support The Sharing And Re-Use Of Computable Phenotype Definitions Across Health Care Delivery And Clinical Research Applications, Rachel Richesson, Michelle Smerek, C. Blake Cameron 2016 Duke University School of Nursing

A Framework To Support The Sharing And Re-Use Of Computable Phenotype Definitions Across Health Care Delivery And Clinical Research Applications, Rachel Richesson, Michelle Smerek, C. Blake Cameron

eGEMs (Generating Evidence & Methods to improve patient outcomes)

Introduction: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups.

Method: Drawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we ...


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