Susan Loveland

Datos Biográficos

ID5534192
NOMBRESusan Loveland
NOMBRESSusan
APELLIDOLoveland
FIRMALOVELAND S
AFILIACIONESBoston University
VERIFICADONo
TOTAL DE OBRAS11
TOTAL DE CITAS0
TOTAL COMO AUTOR11
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2001
AÑO MÁS RECIENTE DE PUBLICACIÓN2013
ÍNDICE H0

  • Examining the Impact of the AHRQ Patient Safety Indicators (PSIs) on the Veterans Health Administration

    Amy K Rosen, Susan Loveland et al.ARTICLEMedical Care2013Referencias: 19

    BACKGROUND: By focusing primarily on outcomes in the inpatient setting one may overlook serious adverse events that may occur after discharge (eg, readmissions, mortality) as well as opportunities for improving outpatient care. OBJECTIVE: Our overall objective was to examine whether experiencing an Agency for Healthcare Research and Quality Patient Safety Indicator (PSI) event in an index medical or surgical hospitalization increased the likeliho…

  • Validating the Patient Safety Indicators in the Veterans Health Administration

    Amy K Rosen, Kamal M F Itani et al.ARTICLEMedical Care2012Referencias: 19

    BACKGROUND: The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) use administrative data to detect potentially preventable in-hospital adverse events. However, few studies have determined how accurately the PSIs identify true safety events. OBJECTIVES: We examined the criterion validity, specifically the positive predictive value (PPV), of 12 selected PSIs using clinical data abstracted from the Veterans Health A…

  • Comparison of In-Hospital Versus 30-Day Mortality Assessments for Selected Medical Conditions

    Ann M Borzecki, Cindy L Christiansen et al.ARTICLEMedical Care2010Referencias: 8

    BACKGROUND: In-hospital mortality measures such as the Agency for Healthcare Research and Quality (AHRQ) Inpatient Quality Indicators (IQIs) are easily derived using hospital discharge abstracts and publicly available software. However, hospital assessments based on a 30-day postadmission interval might be more accurate given potential differences in facility discharge practices. OBJECTIVES: To compare in-hospital and 30-day mortality rates for 6…

  • Trends in the Inpatient Quality Indicators

    Ann M Borzecki, Cindy L Christiansen et al.ARTICLEMedical Care2010Referencias: 25

    BACKGROUND: The Agency for Healthcare Research and Quality Inpatient Quality Indicators (IQIs), which include in-hospital mortality and utilization rates, have received little attention in the Veterans Health Administration (VA), despite extensive private sector use for quality improvement. OBJECTIVES: We examined the following: the feasibility of applying the IQIs to VA data; temporal trends in national VA IQI rates; temporal and regional IQI tr…

  • Effects of Resident Duty Hour Reform on Surgical and Procedural Patient Safety Indicators Among Hospitalized Veterans Health Administration and Medicare Patients

    Amy K Rosen, Susan Loveland et al.ARTICLEMedical Care2009Referencias: 29

    OBJECTIVE: Improving patient safety was a strong motivation behind duty hour regulations implemented by Accreditation Council for Graduate Medical Education on July 1, 2003. We investigated whether rates of patient safety indicators (PSIs) changed after these reforms. RESEARCH DESIGN: Observational study of patients admitted to Veterans Health Administration (VA) (N = 826,047) and Medicare (N = 13,367,273) acute-care hospitals from July 1, 2000 t…

  • Development and Validation of a Psychiatric Case-Mix System

    Kevin L Sloan, Maria E Montez-Rath et al.ARTICLEMedical Care2006Referencias: 30

    BACKGROUND: Although difficulties in applying risk-adjustment measures to mental health populations are increasingly evident, a model designed specifically for patients with psychiatric disorders has never been developed. OBJECTIVE: Our objective was to develop and validate a case-mix classification system, the "PsyCMS," for predicting concurrent and future mental health (MH) and substance abuse (SA) healthcare costs and utilization. SUBJECTS: Su…

  • Tracking Rates of Patient Safety Indicators Over Time

    Amy K Rosen, Shibei Zhao et al.ARTICLEMedical Care2006Referencias: 21

    BACKGROUND: The Patient Safety Indicators (PSIs), developed by the Agency for Healthcare Research and Quality, are useful screening tools for highlighting areas in which quality should be further investigated and providing useful benchmarks for tracking progress. OBJECTIVES: Our objectives were to: 1) provide a descriptive analysis of the incidence of PSI events from 2001 to 2004 in the Veterans Health Administration (VA); 2) examine trends in na…

  • Evaluating the Patient Safety Indicators

    Amy K Rosen, Peter Rivard et al.ARTICLEMedical Care2005Referencias: 19

    BACKGROUND: The Patient Safety Indicators (PSIs), an administrative data-based tool developed by the Agency for Healthcare Research and Quality, are increasingly being used to screen for potential in-hospital patient safety problems. Although the Veterans Health Administration (VA) is a national leader in patient safety, accurate information on the epidemiology of patient safety events in the VA is still unavailable. OBJECTIVES: Our objectives we…

  • Predicting Costs of Care Using a Pharmacy-Based Measure Risk Adjustment in a Veteran Population

    Anne E Sales, Chuan-Fen Liu et al.ARTICLEMedical Care2003Referencias: 9

    BACKGROUND: Although most widely used risk adjustment systems use diagnosis data to classify patients, there is growing interest in risk adjustment based on computerized pharmacy data. The Veterans Health Administration (VHA) is an ideal environment in which to test the efficacy of a pharmacy-based approach. OBJECTIVE: To examine the ability of RxRisk-V to predict concurrent and prospective costs of care in VHA and compare the performance of RxRi…

  • Applying Diagnostic Cost Groups to Examine the Disease Burden of VA Facilities

    Amy K Rosen, Susan Loveland et al.ARTICLEMedical Care2003Referencias: 16

    OBJECTIVES: To compare the disease burden of Veterans Health Administration (VA) patients at six study sites with all other VA patients and the Medicare population. DESIGN: A 60% random sample of all VA veteran patients during federal fiscal year 1997 was obtained from administrative databases. A split-sample technique provided a 40% sample (n = 1,046,803) for development and a 20% sample (n = 524,461) for validation. We selected the six study si…

  • Evaluating Diagnosis-Based Case-Mix Measures

    Amy K Rosen, Susan Loveland et al.ARTICLEMedical Care2001Referencias: 17

    BACKGROUND: Diagnosis-based case-mix measures are increasingly used for provider profiling, resource allocation, and capitation rate setting. Measures developed in one setting may not adequately capture the disease burden in other settings. OBJECTIVES: To examine the feasibility of adapting two such measures, Adjusted Clinical Groups (ACGs) and Diagnostic Cost Groups (DCGs), to the Department of Veterans Affairs (VA) population. RESEARCH DESIGN: …