Literature DB >> 11838300

Using control charts to assess performance measurement data.

Kwan Lee1, Christine McGreevey.   

Abstract

BACKGROUND: In 1997 the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) announced the ORYX initiative, which integrates outcomes and other performance measurement data into the accreditation process. JCAHO uses control and comparison charts to identify performance trends and patterns that are provided to JCAHO surveyors in advance of the organization's survey. During its survey, the health care organization (HCO) is asked to explain its rationale for its selection of performance measures, how the ORYX data have been analyzed and used to improve performance, and the outcomes of these activities. WHAT DO CONTROL CHARTS DO? Control charts indicate whether an HCO's process is in statistical control (that is, stable insofar as only common cause variation exists) or out of statistical control (that is, unstable insofar as special cause variation exists). With the presence of special cause variation, the HCO should not make any change in its processes until the special cause is identified and eliminated. CHOOSING THE CORRECT CONTROL CHART: An HCO can use many different control charts. Selecting the correct control chart type for the type of data collected makes interpretation more sensitive for detecting special cause variation. The ORYX measures are calculated as proportions (rates), ratios, and means (continuous variables data, such as average length of stay), and this information forms the basis for selecting the correct type of control chart. In addition, the average rate (especially for rare event measures) and the average number of cases need to be considered when selecting the control chart type for small population measures.

Entities:  

Mesh:

Year:  2002        PMID: 11838300     DOI: 10.1016/s1070-3241(02)28009-8

Source DB:  PubMed          Journal:  Jt Comm J Qual Improv        ISSN: 1070-3241


  5 in total

1.  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
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2.  Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?

Authors:  I Scott; D Youlden; M Coory
Journal:  Qual Saf Health Care       Date:  2004-02

3.  Reduction of paediatric head CT utilisation at a rural general hospital emergency department.

Authors:  Jeffrey Paul Louie; Joseph Alfano; Thuy Nguyen-Tran; Hai Nguyen-Tran; Ryan Shanley; Tara Holm; Ronald A Furnival
Journal:  BMJ Qual Saf       Date:  2020-02-28       Impact factor: 7.035

4.  Targets without tolerances: improper evaluation of medical personnel.

Authors:  Robert S Butler; Douglas Johnston; Michael W Kattan
Journal:  Ann Transl Med       Date:  2018-04

5.  A Quality Improvement Intervention to Inform Scale-Up of Integrated HIV-TB Services: Lessons Learned From KwaZulu-Natal, South Africa.

Authors:  Santhanalakshmi Gengiah; Kogieleum Naidoo; Regina Mlobeli; Maureen F Tshabalala; Andrew J Nunn; Nesri Padayatchi; Nonhlanhla Yende-Zuma; Myra Taylor; Pierre M Barker; Marian Loveday
Journal:  Glob Health Sci Pract       Date:  2021-09-30
  5 in total

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