Literature DB >> 9382378

Assessing quality using administrative data.

L I Iezzoni1.   

Abstract

Administrative data result from administering health care delivery, enrolling members into health insurance plans, and reimbursing for services. The primary producers of administrative data are the federal government, state governments, and private health care insurers. Although the clinical content of administrative data includes only the demographic characteristics and diagnoses of patients and codes for procedures, these data are often used to evaluate the quality of health care. Administrative data are readily available, are inexpensive to acquire, are computer readable, and typically encompass large populations. They have identified startling practice variations across small geographic areas and-supported research about outcomes of care. Many hospital report cards (which compare patient mortality rates) and physician profiles (which compare resource consumption) are derived from administrative data. However, gaps in clinical information and the billing context compromise the ability to derive valid quality appraisals from administrative data. With some exceptions, administrative data allow limited insight into the quality of processes of care, errors of omission or commission, and the appropriateness of care. In addition, questions about the accuracy and completeness of administrative data abound. Current administrative data are probably most useful as screening tools that highlight areas in which quality should be investigated in greater depth. The growing availability of electronic clinical information will change the nature of administrative data in the future, enhancing opportunities for quality measurement.

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Year:  1997        PMID: 9382378     DOI: 10.7326/0003-4819-127-8_part_2-199710151-00048

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  232 in total

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Review 2.  Methodological hurdles in conducting pharmacoeconomic analyses.

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4.  Risk adjustment using administrative data: impact of a diagnosis-type indicator.

Authors:  W A Ghali; H Quan; R Brant
Journal:  J Gen Intern Med       Date:  2001-08       Impact factor: 5.128

5.  Electronically screening discharge summaries for adverse medical events.

Authors:  Harvey J Murff; Alan J Forster; Josh F Peterson; Julie M Fiskio; Heather L Heiman; David W Bates
Journal:  J Am Med Inform Assoc       Date:  2003-03-28       Impact factor: 4.497

Review 6.  Detecting adverse events using information technology.

Authors:  David W Bates; R Scott Evans; Harvey Murff; Peter D Stetson; Lisa Pizziferri; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2003 Mar-Apr       Impact factor: 4.497

Review 7.  Administrative data based patient safety research: a critical review.

Authors:  C Zhan; M R Miller
Journal:  Qual Saf Health Care       Date:  2003-12

8.  Measuring errors and adverse events in health care.

Authors:  Eric J Thomas; Laura A Petersen
Journal:  J Gen Intern Med       Date:  2003-01       Impact factor: 5.128

9.  Effect of critical access hospital conversion on patient safety.

Authors:  Pengxiang Li; John E Schneider; Marcia M Ward
Journal:  Health Serv Res       Date:  2007-12       Impact factor: 3.402

10.  Effect of widespread restrictions on the use of hospital services during an outbreak of severe acute respiratory syndrome.

Authors:  Michael J Schull; Thérèse A Stukel; Marian J Vermeulen; Merrick Zwarenstein; David A Alter; Douglas G Manuel; Astrid Guttmann; Andreas Laupacis; Brian Schwartz
Journal:  CMAJ       Date:  2007-06-19       Impact factor: 8.262

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