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Abstracts From The 2022 Health Care Systems Research Network (Hcsrn) Annual Conference Jul 2022

Abstracts From The 2022 Health Care Systems Research Network (Hcsrn) Annual Conference

Journal of Patient-Centered Research and Reviews

The Health Care Systems Research Network (HCSRN) is comprised of 20 health systems with embedded research units. The network’s annual conference serves as a forum for research teams from member institutions to disseminate scientific findings, explore new collaborations, and share insights about conducting research in real-world care delivery settings. Abstracts accepted for presentation at HCSRN 2022 are published in this supplement of Journal of Patient-Centered Research and Reviews, the official journal of HCSRN’s annual conference proceedings.


Association Of Lung Cancer With Pneumonia And Chlamydia Pneumoniae Infection, Johnny Zakhour Md, Daniel Muller, Alex Glynn, Jose Bordon Oct 2021

Association Of Lung Cancer With Pneumonia And Chlamydia Pneumoniae Infection, Johnny Zakhour Md, Daniel Muller, Alex Glynn, Jose Bordon

The University of Louisville Journal of Respiratory Infections

Introduction: The degree of association and type of causal versus non-causal relationship between pneumonia and lung cancer (LC) are evolving discussions. We reviewed English publications on the degree of association between pneumonia and subsequent LC.

Methods: We searched the PubMed database using key words for pneumonia, LC, and chlamydia infection. We selected peer-reviewed studies of patients with pneumonia and LC. Case reports and other literature reviews were excluded from this review.

Results: Five studies examined the incidence and/or risk of LC for a total of 415,750 patients, and four studies examined cases with Chlamydia pneumoniae chronic infection at the time …


Abstracts From The 26th Annual Health Care Systems Research Network Conference, April 8–10, 2020 Apr 2020

Abstracts From The 26th Annual Health Care Systems Research Network Conference, April 8–10, 2020

Journal of Patient-Centered Research and Reviews

The Health Care Systems Research Network (HCSRN) is made up of community-based care delivery systems with a shared mission to improve health and health care through research. The network’s annual conference serves as a forum for attendees to disseminate study findings, stimulate collaborations, and share insights about conducting research in real-world care settings. Although this year’s live conference was cancelled to help slow the spread of COVID-19, the oral and poster abstracts accepted for presentation at HCSRN 2020 are published in this open access supplement to Volume 7, Issue 1 of the Journal of Patient-Centered Research and Reviews, the …


Utilizing Digital Health To Collect Electronic Patient-Reported Outcomes In Prostate Cancer: Single-Arm Pilot Trial, Christine Tran, Ms, Adam Dicker, Md, Phd, Benjamin Leiby, Phd, Eric Gressen, Md, Noelle Williams, Md, Heather Jim, Phd Mar 2020

Utilizing Digital Health To Collect Electronic Patient-Reported Outcomes In Prostate Cancer: Single-Arm Pilot Trial, Christine Tran, Ms, Adam Dicker, Md, Phd, Benjamin Leiby, Phd, Eric Gressen, Md, Noelle Williams, Md, Heather Jim, Phd

Kimmel Cancer Center Faculty Papers

Background: Measuring patient-reported outcomes (PROs) requires an individual’s perspective on their symptoms, functional status, and quality of life. Digital health enables remote electronic PRO (ePRO) assessments as a clinical decision support tool to facilitate meaningful provider interactions and personalized treatment.

Objective: This study explored the feasibility and acceptability of collecting ePROs using validated health-related quality of life (HRQoL) questionnaires for prostate cancer.

Methods: Using Apple ResearchKit software, the Strength Through Insight app was created with content from validated HRQoL tools 26-item Expanded Prostate Cancer Index Composite (EPIC) or EPIC for Clinical Practice and 8-item Functional Assessment of Cancer Therapy Advanced …


Abstracts From The 24th Annual Health Care Systems Research Network Conference, April 11–13, 2018, Minneapolis, Minnesota Apr 2018

Abstracts From The 24th Annual Health Care Systems Research Network Conference, April 11–13, 2018, Minneapolis, Minnesota

Journal of Patient-Centered Research and Reviews

Founded in 1994, the Health Care Systems Research Network (HCSRN) is a consortium of 18 research centers that are housed in community-based health systems. The organization's annual conference serves as a venue for research teams to disseminate scientific findings, stimulate new collaborations, and share insights about conducting research in real-world care-delivery settings. Abstracts accepted for presentation at HCSRN 2018 are published within this supplement of the Journal of Patient-Centered Research and Reviews.


Abstracts From The 23rd Annual Health Care Systems Research Network Conference, March 21–23, 2017, San Diego, California Aug 2017

Abstracts From The 23rd Annual Health Care Systems Research Network Conference, March 21–23, 2017, San Diego, California

Journal of Patient-Centered Research and Reviews

This proceedings supplement includes selected abstracts presented at the 23rd annual conference of the Health Care Systems Research Network (HCSRN), held March 21–23, 2017, in San Diego, California. Formerly called the HMO Research Network, HCSRN aims to improve individual and population health through research that connects the resources and capabilities of its member health care systems.


Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi Feb 2013

Data Mining The Functional Characterizations Of Proteins To Predict Their Cancer-Relatedness, Peter Revesz, Christopher Assi

School of Computing: Faculty Publications

This paper considers two types of protein data. First, data about protein function described in a number of ways, such as, GO terms and PFAM families. Second, data about whether individual proteins are experimentally associated with cancer by an anomalous elevation or lowering of their expressions within cancerous cells. We combine these two types of protein data and test whether the first type of data, that is, the functional descriptors, can predict the second type of data, that is, cancer-relatedness. By using data mining and machine learning, we derive a classifier algorithm that using only GO term and PFAM family …