Using administrative data to screen hospitals for high complication rates.
about
Using computerized data to identify adverse drug events in outpatients.Nurse staffing and postsurgical adverse events: an analysis of administrative data from a sample of U.S. hospitals, 1990-1996Administrative data based patient safety research: a critical review.Measuring hospital quality: can medicare data substitute for all-payer data?Validity of selected AHRQ patient safety indicators based on VA National Surgical Quality Improvement Program data.Prolonged hospital stay and the resident duty hour rules of 2003Using Medicare claims data to assess provider quality for CABG surgery: does it work well enough?Conditional Length of StayHospital ownership and preventable adverse events.Confidential clinician-reported surveillance of adverse events among medical inpatients.Discrepancies between explicit and implicit review: physician and nurse assessments of complications and quality.Electronically screening discharge summaries for adverse medical events.Association of hospital participation in a quality reporting program with surgical outcomes and expenditures for Medicare beneficiariesRisk Factors for Nonroutine Discharge in Patients Undergoing Spinal Fusion for Intervertebral Disc Disorders.How safe is primary knee replacement surgery? Perioperative complication rates in Northern Illinois, 1993-1999.Tree-structured risk stratification of in-hospital mortality after percutaneous coronary intervention for acute myocardial infarction: a report from the New York State percutaneous coronary intervention database.A Nationwide Analysis of Pelvic Ring Fractures: Incidence and Trends in Treatment, Length of Stay, and Mortality.Ranking hospitals by the quality of care for medical conditions: the role of complications.Identifying complications and low provider adherence to normative practices using administrative dataHospital organisation and outcomes.Anticipating the effects of accountable care organizations for inpatient surgery.Enabling claims-based decision support through non-interruptive capture of admission diagnoses and provider billing codes.An integer programming model to limit hospital selection in studies with repeated sampling.Development of the individualised Comparative Effectiveness of Models Optimizing Patient Safety and Resident Education (iCOMPARE) trial: a protocol summary of a national cluster-randomised trial of resident duty hour policies in internal medicine
P2860
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P2860
Using administrative data to screen hospitals for high complication rates.
description
1994 nî lūn-bûn
@nan
1994年の論文
@ja
1994年論文
@yue
1994年論文
@zh-hant
1994年論文
@zh-hk
1994年論文
@zh-mo
1994年論文
@zh-tw
1994年论文
@wuu
1994年论文
@zh
1994年论文
@zh-cn
name
Using administrative data to screen hospitals for high complication rates.
@en
type
label
Using administrative data to screen hospitals for high complication rates.
@en
prefLabel
Using administrative data to screen hospitals for high complication rates.
@en
P2093
P1433
P1476
Using administrative data to screen hospitals for high complication rates.
@en
P2093
Coffman GA
Iezzoni LI
P577
1994-01-01T00:00:00Z