Literature DB >> 10475396

Measuring for improvement: from Toyota to thoracic surgery.

J M Levett1, R G Carey.   

Abstract

BACKGROUND: Measuring quality has become a high priority in the era of managed care. Nevertheless, it can be counterproductive to use the same methods for measuring improvement in surgical procedures and processes as we use for measurement in basic research. Techniques of statistical process control have been used for many years to measure process improvement in industry and are now being applied to health care.
METHODS: Examples of using statistical process control charts to monitor coronary artery bypass grafting mortality, intensive care unit admission time, and length of stay are reviewed.
RESULTS: The major advantage of using control chart methodology is that it allows one to determine whether the process being evaluated is in fact stable and to detect when significant or special cause variation occurs.
CONCLUSIONS: Summary statistics currently provided to purchasers of care and regulatory agencies do not ensure that the processes being evaluated are stable. We need to look at data over time with statistically validated methods such as control charts to better monitor our processes of care and thereby provide accurate statistics.

Mesh:

Year:  1999        PMID: 10475396     DOI: 10.1016/s0003-4975(99)00547-0

Source DB:  PubMed          Journal:  Ann Thorac Surg        ISSN: 0003-4975            Impact factor:   4.330


  6 in total

Review 1.  Application of statistical process control in healthcare improvement: systematic review.

Authors:  Johan Thor; Jonas Lundberg; Jakob Ask; Jesper Olsson; Cheryl Carli; Karin Pukk Härenstam; Mats Brommels
Journal:  Qual Saf Health Care       Date:  2007-10

2.  Performance of statistical process control methods for regional surgical site infection surveillance: a 10-year multicentre pilot study.

Authors:  Arthur W Baker; Salah Haridy; Joseph Salem; Iulian Ilieş; Awatef O Ergai; Aven Samareh; Nicholas Andrianas; James C Benneyan; Daniel J Sexton; Deverick J Anderson
Journal:  BMJ Qual Saf       Date:  2017-11-24       Impact factor: 7.035

3.  Control charts for chronic disease surveillance: testing algorithm sensitivity to changes in data coding.

Authors:  Naomi C Hamm; Depeng Jiang; Ruth Ann Marrie; Pourang Irani; Lisa M Lix
Journal:  BMC Public Health       Date:  2022-02-28       Impact factor: 3.295

4.  Using the Laney p' Control Chart for Monitoring COVID-19 Cases in Jordan.

Authors:  Mazen Arafah
Journal:  J Healthc Eng       Date:  2022-09-19       Impact factor: 3.822

5.  Unpacking the key components of a programme to improve the timeliness of hip-fracture care: a mixed-methods case study.

Authors:  Pamela Mazzocato; Maria Unbeck; Mattias Elg; Olof Gustaf Sköldenberg; Johan Thor
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2015-11-09       Impact factor: 2.953

6.  Early recognition and response to increases in surgical site infections using optimized statistical process control charts-the Early 2RIS Trial: a multicenter cluster randomized controlled trial with stepped wedge design.

Authors:  Deverick J Anderson; Iulian Ilieş; Katherine Foy; Nicole Nehls; James C Benneyan; Yuliya Lokhnygina; Arthur W Baker
Journal:  Trials       Date:  2020-10-28       Impact factor: 2.279

  6 in total

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