A Preliminary Clinical Audit of Elective Hip and Knee ... stuart-smith and... · Dr Karen Stuart-Smith. Consultant Anaesthetist North Wales NHS Trust. Career interest in research

Copyright © 2008, SAS Institute Inc. All rights reserved. 1

Copyright © 2008, SAS Institute Inc. All rights reserved.

A Preliminary Clinical Audit of Elective Hip and Knee Replacements

Improving Performance in Healthcare Through Statistical Techniques

21st May 2009

Karen Stuart-Smith

Ian Cox


Agenda

  Introduction

  The Audit Context

  Preliminary Findings: 1.  Patient Demographics 2.  Prevalence of Pre-Operative Conditions 3.  Longitudinal Patient Data 4.  What is Associated with Length of Stay? 5.  Scenario Planning and Risk Assessment

  Future Audits and Next Steps



Introduction

  Dr Karen Stuart-Smith. Consultant Anaesthetist North Wales NHS Trust. Career interest in research and clinical audit. Special interest in orthopaedic surgery.

  Dr Ian Cox. Marketing Manager, JMP Division, SAS Institute.   Purpose of presentation is to demonstrate the power of

descriptive, analytical and predictive approaches in clinical audit, with a view to improving patient care and delivering value for money.


The Audit Context

  North Wales NHS Trust is an amalgamation of Glan Clwyd Hospital in Denbighshire and Maelor Hospital in Wrexham.

  Abergele Hospital is a part of Glan Clwyd. It is a stand alone former TB hospital situated outside the town of Abergele and 6 miles from the main hospital.

  Previously Abergele housed several clinical specialities including urology and day case surgery, and some years ago also had onsite laboratory facilities.



The Audit Context (continued)   All clinical services have now been withdrawn from Abergele with the

exception of elective orthopaedic surgery.   No laboratory facilities on site.   Major elective surgery is being carried out on elderly patients in an

isolated environment. Medical and nursing skill mix variable.   Close attention has to be paid to the type of patient being operated on

at Abergele, with sicker patients being operated on at the main hospital site (Glan Clwyd).

  Resources are being stretched.   No audit tools currently available to identify problems in the patient

pathway, maximise care in an isolated environment, or predict who would benefit from a higher level of post-operative care (HDU, ITU).


National Context

  No evidence-based guidelines available nationally for the management of patients undergoing major joint replacement surgery.

  No national database and no opportunity to identify problem areas.

  No nationally agreed outcome measures.   No way therefore to move management forward in a DGH

setting.



Specifics of this Audit   Conducted in 2005.   Data originally collected prospectively by an orthopaedic staff doctor on

my behalf.   171 patients undergoing orthopaedic surgery at Abergele over about

three months.   Data collected began at preoperative assessment and continued to

discharge.   Included: pre-operative co-morbidities, demographics, type of

anaesthesia and surgery, perioperative fluids (including blood), pre and post-operative Hb, intra and post-operative blood pressure, post-operative complications and length of stay.


Specifics of this Audit (continued)   Original data collection contained to many yes/no questions (result of

constraints on audit facilities at local hospital)   Notes of all patients included in original audit were recalled and specific

numerical data obtained.   Took a further 18 months. Data collected by anaesthetic registrars and

one of the Sisters in the orthopaedic ward.   No statistical software available on site to analyse large body of data   Eventually contacted by Ian Cox from JMP after initial website contact.



The Demographics   Total 171 patients   Gender: 113 female, 58 male   Overall age: mean 69.5, s.e.m. 0.70. Range 44-92 years, median 70   Age/gender split: females mean 69 years, s.e.m. 0.9, males 70.4, s.e.m. 1.17   Overall BMI: mean 29.4, s.e.m. 0.43, median 29, range 19-48

BMI/gender split: male mean 28.64, s.e.m. 0.63: female mean 29.8, s.e.m. 0.55   Total number of operations: total hips (THR) 86, total knees (TKR) 85

Gender/op split: female 58 THRs (51.3% of all female ops), 55 TKRs (48.7% of all female ops). Male: 28 THRs (48.3% of all male ops) , 30 TKRs (51.7% of all male ops).

  Age vs. operation: THRs: mean age 68, s.e.m. 0.93. TKRs mean age 70.3, s.e.m. 1.05

  BMI vs. operation: THRs: mean 68.5, s.e.m. 0.61. TKRs mean 30.3, s.e.m. 0.58


Visual Six Sigma - Process

Frame Problem Collect Data Uncover

Relationships

Model Relationships

Utilize Knowledge

Revise Knowledge

“Statistics as Detective” or EDA

“Statistics as Judge” or CDA



Visual Six Sigma - Strategies

1.  Use dynamic visualization to literally “see” the sources of variation in your data.

2.  Use exploratory data analysis techniques to identify key drivers and models, especially for situations with many variables.

3.  Use confirmatory statistical methods only when the conclusions are not obvious.


Preliminary Findings

“Live” commentary and demonstration.

Every set of data is unique, so we need to disambiguate the requirements and capabilities of the enabling software from the narrative and findings that arise from a specific set of data.

Slides 13 to 24 are included post-facto simply as a reminder of what was shown in the meeting.



Confidentiality: Easily Control Who has Access To What


Confidentiality: Easily Control Who has Access To What

Use ‘Master Data Management’ and only

expose sensitive data and computation to those that

need to know



1: Demographic Variables – Easily “See” What’s in the Data

What are the characteristics of

those with high BMI?


2: Which Demographic is Associated with Operation (Type)?

Some evidence for BMI (but not Gender or Age)



2: Which Demographic is Associated with Operation (Type)?

Make understandable predictions (irrespective of modelling approach)


2: Pre-Operative Conditions

Further investigate interesting subsets

by selecting in graphs



2: Factors Associated with Pre-Op Hypotension

Joint effect of BMI and Age on Pre-Op HTN


3: Longitudinal Patient Data Plot many variables and

dynamically filter by patient or covariate to

see multivariate groups and outliers



4: What is Associated with Length of Stay?

The Graph Builder builds graphs

similarly to the way an Excel pivot table builds tabulations


4: What is Associated with Length of Stay?

The key determinant is the age of the

patient



5: Scenario Planning and Risk Assessment

Screen for active factors in a

regression model if the data is not too

sparse


5: Scenario Planning and Risk Assessment

Perform ‘stochastic optimisation’ in an intuitive graphical environment to investigate the

impact of change on outcomes



Future Audits and Next Steps Significant changes have been made to the way elective orthopaedic patients are managed at Abergele: only ASA 1 and 2 now operated on, Hb now measured at 24 hours post-op, major joint patents catheterised to improve fluid balance. A new audit looking at three months of patient data from the summer of 2008 is now in progress using same template. Will be possible to detect changes in patient demographics, management, etc and their impact on length of stay, post-op complications, etc. A special emphasis will be placed on assessing the management of blood loss and fluid replacement.

A similar audit of fractured neck of femur patients, using the same template, is currently being analysed.


Potential use of JMP as a National Clinical Audit Tool

  Novel approach to data handling allows patient factors which affect defined outcomes (eg length of stay, mortality) to be identified easily.

  Intra-operative as well as postoperative factors can be assessed for their effect on outcome.

  Can be made surgeon (and anaesthetist, etc) specific.   Impact of a change in practice can easily be quantified-an important

part of closing the audit loop.   Potential predictive power that can be applied at preoperative

assessment to anticipate level of post-operative care required in an individual patient.

  Secure password-protected handling of patient data.


Copyright © 2008, SAS Institute Inc. All rights reserved. Copyright © 2008, SAS Institute Inc. All rights reserved.

Documents

A Preliminary Clinical Audit of Elective Hip and Knee ... stuart-smith and... · Dr Karen Stuart-Smith. Consultant Anaesthetist North Wales NHS Trust. Career interest in research