Responses

PDF

Comparison of control charts for monitoring clinical performance using binary data
Compose Response

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Statement of Competing Interests

PLEASE NOTE:

  • Responses are moderated before posting and publication is at the absolute discretion of BMJ, however they are not peer-reviewed
  • Once published, you will not have the right to remove or edit your response. Removal or editing of responses is at BMJ's absolute discretion
  • If patients could recognise themselves, or anyone else could recognise a patient from your description, please obtain the patient's written consent to publication and send them to the editorial office before submitting your response [Patient consent forms]
  • By submitting this response you are agreeing to our full [Response terms and requirements]

Vertical Tabs

Other responses

Jump to comment:

  • Published on:
    SPC and Complexity
    • Anthony P Morton, retired medical practitioner/medical statistician Princess Alexandra Hospital Brisbane

    Conventional statistical process control (SPC) has limitations when used with hospital averse event (AE) data. Much data, especially hospital infections like bacteraemias, arise in complex systems.1 These differ from the simple or complicated industrial systems that produce data that are analysed with such success with conventional SPC. AE data arising in complex systems are often nonlinear. Expected values are often unknown. There is often delay in obtaining the AE data e.g. with bacteraemia data – the patient has symptoms, a blood sample is obtained, it is sent to pathology for culture, analysis and reporting and is finally placed in a suitable database then analysed (one of the benefits of conventional SPC is in providing rapid feedback so an industrial process that is going out of control is promptly identified). Most hospital AEs are relatively uncommon and alert staff such as those in Infection Management will frequently detect a change well before a statistical analysis. However, analysis using a time-series chart is still desirable. It can add confirmation to the observations of Infection Management and Quality Improvement staff. A hospital department can summarise its performance with a chart. Management and the public can be informed. A problem is devising control limits about an often non-existent expected value using a linear mean value that may be atypical of much of the data.

    How may this dilemma be overcome? The often changing predicted mean value can...

    Show More
    Conflict of Interest:
    None declared.