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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 8 of 8 Research Studies DisplayedWang S, Hanneman P, Xu C
Critical Care Recovery Center: a model of agile implementation in intensive care unit (ICU) survivors.
As many as 70% of intensive care unit (ICU) survivors suffer from long-term physical, cognitive, and psychological impairments known as post-intensive care syndrome (PICS). In this study, the investigators described how the first ICU survivor clinic in the United States, the Critical Care Recovery Center (CCRC), was designed to address PICS using the principles of Agile Implementation (AI).
AHRQ-funded; HS024384.
Citation: Wang S, Hanneman P, Xu C .
Critical Care Recovery Center: a model of agile implementation in intensive care unit (ICU) survivors.
Int Psychogeriatr 2020 Dec;32(12):1409-18. doi: 10.1017/s1041610219000553..
Keywords: Intensive Care Unit (ICU), Critical Care, Health Status, Caregiving
Sonik RA, Coleman-Jensen A, Parish SL
Household food insufficiency, health status and emergency healthcare utilisation among children with and without special healthcare needs.
The purpose of this study was to compare exposure to household food insufficiency and the relationship between household food insufficiency and both health status and emergency healthcare utilization among children with and without special healthcare needs (SHCN). The investigators concluded that compared with other children, children with SHCN have an elevated risk of exposure to household food insufficiency and experiencing greater reductions in health status when exposed.
AHRQ-funded; HS026317.
Citation: Sonik RA, Coleman-Jensen A, Parish SL .
Household food insufficiency, health status and emergency healthcare utilisation among children with and without special healthcare needs.
Public Health Nutr 2020 Dec;23(17):3204-10. doi: 10.1017/s1368980020000361..
Keywords: Children/Adolescents, Nutrition, Health Status, Emergency Department, Public Health
Odlum M, Moise N, Kronish IM
Trends in poor health indicators among Black and Hispanic middle-aged and older adults in the United States, 1999-2018.
This study used records extracted from the Behavioral Risk Factor Surveillance System to determine which health indicators have improved or became worse among Black and Hispanic middle-aged (45 and older) adults compared to Whites from 1999 to 2018. This data is required by the Minority Health and Health Disparities Research and Education Act of 2000. A sample included of 4,856,326 participants, of them 60.9% women, mean age 60.4. During the last 20 years, Black adults showed an overall decrease showing improvement in uninsured status and physical inactivity while showing an overall increase in hypertension, diabetes, asthma, and stroke, and also the same increases and decreases in the Black-White gap. Hispanic adults showed improvement in physical inactivity and perceived poor health, while they showed overall deterioration in hypertension and diabetes. The Hispanic-White gap improved in coronary heart disease, stroke, kidney disease, asthma, arthritis, depression and physical inactivity while it increased for diabetes, hypertension, and uninsured status.
AHRQ-funded; HS025198.
Citation: Odlum M, Moise N, Kronish IM .
Trends in poor health indicators among Black and Hispanic middle-aged and older adults in the United States, 1999-2018.
JAMA Netw Open 2020 Nov 2;3(11):e2025134. doi: 10.1001/jamanetworkopen.2020.25134..
Keywords: Elderly, Racial and Ethnic Minorities, Disparities, Health Status, Health Insurance, Diabetes, Blood Pressure, Chronic Conditions
Johnson J, Rodriguez MA, Al Snih S
Life-space mobility in the elderly: current perspectives.
The authors conducted a narrative review: a) to provide a summary of the articles that have assessed validation of the University of Alabama at Birmingham Life-Space Assessment instrument, the most widely used instrument to assess life-space mobility (LSM) in older adults; and b) to provide a summary of the research articles that have examined LSM as independent or outcome variable. They found that the identified studies showed that LSM instruments can accurately predict morbidity, mortality, and healthcare use.
AHRQ-funded; HS026122.
Citation: Johnson J, Rodriguez MA, Al Snih S .
Life-space mobility in the elderly: current perspectives.
Clin Interv Aging 2020;15:1665-74. doi: 10.2147/cia.S196944..
Keywords: Elderly, Health Status
Kulhawy-Wibe SC, Zell J, Michaud K
Systematic review and appraisal of the cross-cultural validity of functional status assessment measures in rheumatoid arthritis.
Researchers conducted a systematic review and appraisal of the cross-cultural adaptation and cross-cultural validity of the Health Assessment Questionnaire and its derivatives, and of the more recent Patient-Reported Outcomes Measurement Information System (PROMIS) functional status assessment measures (FSAMs) in rheumatoid arthritis. They concluded that their review highlighted a paucity of data on the cross-cultural validity of FSAMs and the mostly poor- or fair-quality methods by which they were translated and adapted.
AHRQ-funded; HS025638.
Citation: Kulhawy-Wibe SC, Zell J, Michaud K .
Systematic review and appraisal of the cross-cultural validity of functional status assessment measures in rheumatoid arthritis.
Arthritis Care Res 2020 Jun;72(6):798-805. doi: 10.1002/acr.23904..
Keywords: Arthritis, Cultural Competence, Health Status
Rundell SD, Resnik L, Heagerty PJ
Comparing the performance of comorbidity indices in predicting functional status, health-related quality of life, and total health care use in older adults with back pain.
The purpose of this prospective cohort study was to determine how well the functional comorbidity index (FCI) predicted outcomes in older adults with back pain compared to Quan's modification of the Charlson comorbidity index (Quan-Charlson comorbidity index) and the Elixhauser comorbidity index. The investigators concluded that all indices performed similarly in predicting outcomes. The authors indicated that there is still a need to develop better function-based risk-adjustment models that improve prediction of functional outcomes versus standard comorbidity indices.
AHRQ-funded; HS019222; HS022972.
Citation: Rundell SD, Resnik L, Heagerty PJ .
Comparing the performance of comorbidity indices in predicting functional status, health-related quality of life, and total health care use in older adults with back pain.
J Orthop Sports Phys Ther 2020 Mar;50(3):143-48. doi: 10.2519/jospt.2020.8764..
Keywords: Elderly, Back Health and Pain, Pain, Chronic Conditions, Quality of Life, Healthcare Utilization, Health Status
Senft 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)