Mathew J Reeves
Biographic Data
| ID | 5535823 |
|---|---|
| NAME | Mathew J Reeves |
| GIVEN NAMES | Mathew J |
| FAMILY NAME | Reeves |
| SIGNATURE | REEVES M J |
| AFFILIATIONS | Michigan State University |
| ORCID | 0000-0002-8019-6343 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 11 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The Effect of Rural Versus Urban Residence on Risk of Unplanned Readmission and Death in Older Veterans Discharged From VA Hospitals
Engaging Stakeholders in Co-Developing the Michigan Stroke Transitions Trial (MISTT) Website Intervention
Community-engaged UCD is critical to creating patient-centered technology-based post-stroke TC interventions
Opening Pandora’s Box
BACKGROUND: Measuring the effectiveness of transitional care interventions has historically relied on health care utilization as the primary outcome. Although the Care Transitions Measure was the first outcome measure specifically developed for transitional care, its applicability beyond the hospital-to-home transition is limited. There is a need for patient-centered outcome measures (PCOMs) to be developed for transitional care settings (ie, TC-…
Heart Disease and Stroke Statistics—2018 Update
Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter. Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in …
Heart Disease and Stroke Statistics—2017 Update
Health Information Exchange Organizations and Their Support for Research
Federal investment spurred health information exchange organization (HIO) development and maturation to provide third-party approaches to electronic health information exchange across disparate electronic health record (EHR) systems. By creating opportunities for data aggregation across multiple medical institutions, HIOs also spur research. Using data from a 2015 national web-based survey of HIOs (N = 64), we identified HIOs supporting or not su…
Heart Disease and Stroke Statistics—2016 Update
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics related to heart disease, stroke, and other cardiovascular and metabolic diseases and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update represents a critical resource for the lay pu…
Heart Disease and Stroke Statistics—2015 Update
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics related to heart disease, stroke, and other cardiovascular and metabolic diseases and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update represents a critical resource for the lay pu…
In Response
Institute for Clinical Evaluative Sciences Toronto, ON, Canada †Department of Epidemiology and Biostatistics, Michigan State University East Lansing, MI Supported by an operating grant from the Canadian Institutes of Health Research (CIHR). P.C.A. is also supported in part by a Career Investigator Award from the Heart and Stroke Foundation. The authors declare no conflict of interest
The Relationship Between the C-Statistic of a Risk-adjustment Model and the Accuracy of Hospital Report Cards
BACKGROUND: Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adju…
Temporal and Regional Trends in the Prevalence of Healthy Lifestyle Characteristics
Objectives. We examined temporal and regional trends in the prevalence of health lifestyles in the United States. Methods. We used 1994 to 2007 data from the Behavioral Risk Factor Surveillance System to assess 4 healthy lifestyle characteristics: having a healthy weight, not smoking, consuming fruits and vegetables, and engaging in physical activity. The concurrent presence of all 4 characteristics was defined as a healthy overall lifestyle. We …
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Temporal and Regional Trends in the Prevalence of Healthy Lifestyle Characteristics
Objectives. We examined temporal and regional trends in the prevalence of health lifestyles in the United States. Methods. We used 1994 to 2007 data from the Behavioral Risk Factor Surveillance System to assess 4 healthy lifestyle characteristics: having a healthy weight, not smoking, consuming fruits and vegetables, and engaging in physical activity. The concurrent presence of all 4 characteristics was defined as a healthy overall lifestyle. We …
In Response
Institute for Clinical Evaluative Sciences Toronto, ON, Canada †Department of Epidemiology and Biostatistics, Michigan State University East Lansing, MI Supported by an operating grant from the Canadian Institutes of Health Research (CIHR). P.C.A. is also supported in part by a Career Investigator Award from the Heart and Stroke Foundation. The authors declare no conflict of interest
The Relationship Between the C-Statistic of a Risk-adjustment Model and the Accuracy of Hospital Report Cards
BACKGROUND: Hospital report cards, in which outcomes following the provision of medical or surgical care are compared across health care providers, are being published with increasing frequency. Essential to the production of these reports is risk-adjustment, which allows investigators to account for differences in the distribution of patient illness severity across different hospitals. Logistic regression models are frequently used for risk adju…
Heart Disease and Stroke Statistics—2015 Update
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics related to heart disease, stroke, and other cardiovascular and metabolic diseases and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update represents a critical resource for the lay pu…
Heart Disease and Stroke Statistics—2016 Update
Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together the most up-to-date statistics related to heart disease, stroke, and other cardiovascular and metabolic diseases and presents them in its Heart Disease and Stroke Statistical Update. The Statistical Update represents a critical resource for the lay pu…
Heart Disease and Stroke Statistics—2017 Update
Health Information Exchange Organizations and Their Support for Research
Federal investment spurred health information exchange organization (HIO) development and maturation to provide third-party approaches to electronic health information exchange across disparate electronic health record (EHR) systems. By creating opportunities for data aggregation across multiple medical institutions, HIOs also spur research. Using data from a 2015 national web-based survey of HIOs (N = 64), we identified HIOs supporting or not su…
Heart Disease and Stroke Statistics—2018 Update
Each chapter listed in the Table of Contents (see next page) is a hyperlink to that chapter. The reader clicks the chapter name to access that chapter. Each chapter listed here is a hyperlink. Click on the chapter name to be taken to that chapter. Each year, the American Heart Association (AHA), in conjunction with the Centers for Disease Control and Prevention, the National Institutes of Health, and other government agencies, brings together in …
Opening Pandora’s Box
BACKGROUND: Measuring the effectiveness of transitional care interventions has historically relied on health care utilization as the primary outcome. Although the Care Transitions Measure was the first outcome measure specifically developed for transitional care, its applicability beyond the hospital-to-home transition is limited. There is a need for patient-centered outcome measures (PCOMs) to be developed for transitional care settings (ie, TC-…
Engaging Stakeholders in Co-Developing the Michigan Stroke Transitions Trial (MISTT) Website Intervention
Community-engaged UCD is critical to creating patient-centered technology-based post-stroke TC interventions
The Effect of Rural Versus Urban Residence on Risk of Unplanned Readmission and Death in Older Veterans Discharged From VA Hospitals
Medicine (8 works) · Blood Pressure and Hypertension Studies (4 works) · Internal Medicine (4 works) · Disease (3 works) · Gerontology (3 works) · MEDLINE (3 works) · Stroke (engine) (3 works) · Cardiology (2 works) · Cardiovascular Function and Risk Factors (2 works) · Cardiovascular Health and Disease Prevention (2 works)