National Healthcare Quality and Disparities Report
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- Cancer (1)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 5 of 5 Research Studies DisplayedSenft N, Abrams J, Katz
eHealth activity among African American and white cancer survivors: a new application of theory.
eHealth is a promising resource for cancer survivors and may contribute to reducing racial disparities in cancer survivorship. This research applied the Unified Theory of Acceptance and Use of Technology (UTAUT) to examine eHealth activity among African American (AfAm) and White cancer survivors.
AHRQ-funded; HS022955.
Citation: Senft N, Abrams J, Katz .
eHealth activity among African American and white cancer survivors: a new application of theory.
Health Commun 2020 Mar;35(3):350-55. doi: 10.1080/10410236.2018.1563031..
Keywords: Racial and Ethnic Minorities, Cancer, Disparities, Health Status, Telehealth, Health Information Technology (HIT)
Angraal S, Mortazavi BJ, Gupta A
Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction.
This study developed models to predict the risk of death and hospitalization in patients with heart failure (HF) with preserved ejection fraction (HFpEF). Data was used from the TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist) clinical trial. Five methods: logistic regression with a forward selection of variables; logistic regression with a lasso regularization for variable selection; random forest (RF); gradient descent boosting; and support vector machine, were used to train models for assessing risks of mortality and HF hospitalization through 3 years of follow-up and were validated using 5-fold cross-validation. RF was found to be the best performing model for predicting mortality and HF hospitalization. Blood urea nitrogen levels, body mass index, and Kansas City Cardiomyopathy Questionnaire (KCCQ) subscale scores were strongly associated with mortality, while hemoglobin level, blood urea nitrogen, time since previous HF hospitalization, and KCCQ scores were the most significant predictors of HF hospitalization.
AHRQ-funded; HS023000.
Citation: Angraal S, Mortazavi BJ, Gupta A .
Machine learning prediction of mortality and hospitalization in heart failure with preserved ejection fraction.
JACC Heart Fail 2020 Jan;8(1):12-21. doi: 10.1016/j.jchf.2019.06.013..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Mortality, Hospitalization, Risk, Health Status, Health Information Technology (HIT)
Baik D, Reading M, Jia H
Measuring health status and symptom burden using a web-based mHealth application in patients with heart failure.
This cross-sectional study was conducted at an urban academic medical center to measure health status and symptom burdens of heart failure patients using a mHealth application called mi.Symptoms. Patients were diverse, with a mean age of 58.7, and were 37% women, 36% Black, and 36% Hispanic/Latino. Almost half were classified as New York Heart Association class III, and 44% reported not having enough income to make ends meet. Health status was measured with the Kansas City cardiomyopathy questionnaire clinical summary score. Predictors of better health status included higher physical function and ability to participate in social functions and activities. Predictors of poorer health status was New York Heart Association class IV status and dyspnea.
AHRQ-funded; HS021816.
Citation: Baik D, Reading M, Jia H .
Measuring health status and symptom burden using a web-based mHealth application in patients with heart failure.
Eur J Cardiovasc Nurs 2019 Apr;18(4):325-31. doi: 10.1177/1474515119825704..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Health Status, Telehealth, Health Information Technology (HIT)
Hartzler AL, Osterhage K, Demiris G
Understanding views on everyday use of personal health information: insights from community dwelling older adults.
As a first step in formulating the role of personal health information management (PHIM) in healthy aging, researchers explored the perspectives of older adults on health and health information used in their everyday lives. Participants expressed wellness from a position of personal strength by focusing on wellness activities for staying healthy through: (1) personal health practices, (2) social network support, and (3) residential community engagement.
AHRQ-funded; HS022106.
Citation: Hartzler AL, Osterhage K, Demiris G .
Understanding views on everyday use of personal health information: insights from community dwelling older adults.
Inform Health Soc Care 2017 Sep;43(3):1-14. doi: 10.1080/17538157.2017.1297815.
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Keywords: Elderly, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient and Family Engagement, Health Status
Rantz MJ, Skubic M, Popescu M
A new paradigm of technology-enabled 'vital signs' for early detection of health change for older adults.
The purpose of this article is threefold: (1) discuss research behind the technology-enabled ‘vital signs’ for early detection of health change that the Eldertech Research team has conducted, (2) discuss clinical implications for mainstream adoption and use of these vital signs for early interventions to help older adults, their families, and healthcare providers, and (3) present some obstacles to overcome for mainstream adoption.
AHRQ-funded; HS018477.
Citation: Rantz MJ, Skubic M, Popescu M .
A new paradigm of technology-enabled 'vital signs' for early detection of health change for older adults.
Gerontology 2015;61(3):281-90. doi: 10.1159/000366518..
Keywords: Elderly, Health Status, Patient Safety, Health Information Technology (HIT)