Literature DB >> 1790324

Acquired conditions: an improvement to hospital discharge abstracts.

J M Naessens1, M D Brennan, C J Boberg, P C Amadio, P J Karver, R O Podratz.   

Abstract

Selected secondary diagnoses (e.g. pulmonary embolism) may provide an efficient and inexpensive source of data for quality assurance (QA) monitoring if their absence at admission were known. In June 1990 we modified our hospital abstracting methods to classify each diagnosis into categories: (1) present on admission, (2) acquired during hospitalization, or (3) uncertain. Our experience has confirmed the identification and elimination from QA reports of the majority of pre-existing secondary diagnoses. Examples of secondary diagnosis codes acquired or uncertain were acute myocardial infarction 48%, pneumonias 25%, pulmonary emoboli 54% and cerebral vascular accident/hemorrhage 35%. Abstracting time has increased less than 2 min per discharge. A reabstraction study showed 87% agreement (kappa = 0.733, p less than 0.001) between initial collection and blinded reabstraction. The separation of secondary diagnoses into preexisting or acquired can: (1) be reliably undertaken by discharge abstracters; (2) be efficient in adding minimal time; and (3) enhance the validity and usefulness of data and increase physician acceptance.

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Year:  1991        PMID: 1790324     DOI: 10.1093/intqhc/3.4.257

Source DB:  PubMed          Journal:  Qual Assur Health Care        ISSN: 1040-6166


  5 in total

1.  Screening algorithms to assess the accuracy of present-on-admission coding.

Authors:  Michael Pine; Donald E Fry; Barbara Jones; Roger Meimban
Journal:  Perspect Health Inf Manag       Date:  2009-02-11

2.  Evaluating implementation of a rapid response team: considering alternative outcome measures.

Authors:  James P Moriarty; Nicola E Schiebel; Matthew G Johnson; Jeffrey B Jensen; Sean M Caples; Bruce W Morlan; Jeanne M Huddleston; Marianne Huebner; James M Naessens
Journal:  Int J Qual Health Care       Date:  2014-01-08       Impact factor: 2.038

3.  Complications, comorbidities, and mortality: improving classification and prediction.

Authors:  L L Roos; L Stranc; R C James; J Li
Journal:  Health Serv Res       Date:  1997-06       Impact factor: 3.402

4.  Development of a validation algorithm for 'present on admission' flagging.

Authors:  Terri J Jackson; Jude L Michel; Rosemary Roberts; Jennie Shepheard; Diana Cheng; Julie Rust; Catherine Perry
Journal:  BMC Med Inform Decis Mak       Date:  2009-12-01       Impact factor: 2.796

5.  Use of routine hospital morbidity data together with weight and height of patients to predict in-hospital complications following total joint replacement.

Authors:  George Mnatzaganian; Philip Ryan; Paul E Norman; David C Davidson; Janet E Hiller
Journal:  BMC Health Serv Res       Date:  2012-11-01       Impact factor: 2.655

  5 in total

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