Monitoring Platelet Issues - a novel approach CUSUM. Clive Hyam Blood Stocks Management Scheme London

Similar documents
GAMINGRE 8/1/ of 7

REPORT ON LABOUR FORECASTING FOR CONSTRUCTION

Computing & Telecommunications Services Monthly Report January CaTS Help Desk. Wright State University (937)

Computing & Telecommunications Services

Time Series Analysis

FEB DASHBOARD FEB JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

Technical note on seasonal adjustment for M0

Mr. XYZ. Stock Market Trading and Investment Astrology Report. Report Duration: 12 months. Type: Both Stocks and Option. Date: Apr 12, 2011

Long-term Water Quality Monitoring in Estero Bay

Section II: Assessing Chart Performance. (Jim Benneyan)

SPECIMEN. Date Morning/Afternoon. A Level Geography H481/01 Physical systems Sample Question Paper. Time allowed: 1 hour 30 minutes PMT

Technical note on seasonal adjustment for Capital goods imports

Salem Economic Outlook

SYSTEM BRIEF DAILY SUMMARY

YACT (Yet Another Climate Tool)? The SPI Explorer

In Centre, Online Classroom Live and Online Classroom Programme Prices

Chiang Rai Province CC Threat overview AAS1109 Mekong ARCC

WHEN IS IT EVER GOING TO RAIN? Table of Average Annual Rainfall and Rainfall For Selected Arizona Cities

CIMA Professional 2018

SYSTEM BRIEF DAILY SUMMARY

Annual Average NYMEX Strip Comparison 7/03/2017

CIMA Professional 2018

The science of learning from data.

Jayalath Ekanayake Jonas Tappolet Harald Gall Abraham Bernstein. Time variance and defect prediction in software projects: additional figures

Record date Payment date PID element Non-PID element. 08 Sep Oct p p. 01 Dec Jan p 9.85p

CIMA Professional

CIMA Professional

Monthly Trading Report July 2018

Improve Forecasts: Use Defect Signals

DEPARTMENT OF THE ARMY MILITARY SURFACE DEPLOYMENT AND DISTRIBUTION COMMAND (SDDC) 1 SOLDIER WAY SCOTT AFB, IL 62225

Average 175, , , , , , ,046 YTD Total 1,098,649 1,509,593 1,868,795 1,418, ,169 1,977,225 2,065,321

Average 175, , , , , , ,940 YTD Total 944,460 1,284,944 1,635,177 1,183, ,954 1,744,134 1,565,640

Mountain View Community Shuttle Monthly Operations Report

Statistical Models for Rainfall with Applications to Index Insura

Determine the trend for time series data

On Efficient Memory-Type Control Charts for Monitoring out of Control Signals in a Process Using Diabetic Data

Monthly Trading Report Trading Date: Dec Monthly Trading Report December 2017

Jackson County 2018 Weather Data 67 Years of Weather Data Recorded at the UF/IFAS Marianna North Florida Research and Education Center

Scarborough Tide Gauge

Your World is not Red or Green. Good Practice in Data Display and Dashboard Design

Pre-Calc Chapter 1 Sample Test. D) slope: 3 4

Jackson County 2013 Weather Data

ACCA Interactive Timetable

How are adding integers and subtracting integers related? Work with a partner. Use integer counters to find 4 2. Remove 2 positive counters.

TILT, DAYLIGHT AND SEASONS WORKSHEET

ACCA Interactive Timetable & Fees

Dates and Prices ICAEW - Manchester In Centre Programme Prices

Climatography of the United States No

GTR # VLTs GTR/VLT/Day %Δ:

Seasonal Hydrometeorological Ensemble Prediction System: Forecast of Irrigation Potentials in Denmark

Where Was Mars At Your Birth?

Lecture Prepared By: Mohammad Kamrul Arefin Lecturer, School of Business, North South University

Sections 01, 02, & 04 (Bressoud and Ehren) 9 October, 2015

CHAPTER 2 SOLUTIONS. Given: 333 houses; AWWA household average demand. a. The AWWA average household water use is 1,320 L/d

ACCA Interactive Timetable & Fees

Florida Courts E-Filing Authority Board. Service Desk Report March 2019

P7.7 A CLIMATOLOGICAL STUDY OF CLOUD TO GROUND LIGHTNING STRIKES IN THE VICINITY OF KENNEDY SPACE CENTER, FLORIDA

Calculations Equation of Time. EQUATION OF TIME = apparent solar time - mean solar time

ENGINE SERIAL NUMBERS

CAVE CLIMATE COMPARISON ACTIVITY BETWEEN THE SURFACE AND THE CAVERN

DESC Technical Workgroup. CWV Optimisation Production Phase Results. 17 th November 2014

WindPRO version Dec 2005 Printed/Page 11/04/2008 1:54 PM / 1. Meteo data report, height: 66.0 Feet

What is the difference between Weather and Climate?

UWM Field Station meteorological data

Smoothed Prediction of the Onset of Tree Stem Radius Increase Based on Temperature Patterns

Climatography of the United States No

Climatography of the United States No

KING EDWARD POINT OBSERVATORY MAGNETIC DATA

KING EDWARD POINT OBSERVATORY MAGNETIC DATA

CIMA Dates and Prices Online Classroom Live September August 2016

KING EDWARD POINT OBSERVATORY MAGNETIC DATA

ACCA Interactive Timetable & Fees

UNCLASSIFIED. Environment, Safety and Health (ESH) Report

Bootstrapping Australian inbound tourism

Science Standard 1: Students analyze monthly precipitation and temperature records, displayed in bar charts, collected in metric units (mm).

Supplementary appendix

Climatography of the United States No

Climatography of the United States No

Climatography of the United States No

Climatography of the United States No

Climatography of the United States No

ACCA Interactive Timetable

Climatography of the United States No

Climatography of the United States No

Climatography of the United States No

Climatography of the United States No

Safety effects of lower speed limits during winter months

Lesson Adaptation Activity: Analyzing and Interpreting Data

In this activity, students will compare weather data from to determine if there is a warming trend in their community.

ACCA Interactive Timetable

Sluggish Economy Puts Pinch on Manufacturing Technology Orders

TEMPERATURE AND PRECIPITATION CHANGES IN TÂRGU- MURES (ROMANIA) FROM PERIOD

2.1 Inductive Reasoning Ojectives: I CAN use patterns to make conjectures. I CAN disprove geometric conjectures using counterexamples.

Meteo data report, height: 20.0 m. Name of meteo object: Ugashik

Climatography of the United States No

Climatography of the United States No

Introduction to Forecasting

ACCA Interactive Timetable & Fees

Climatography of the United States No

Climatography of the United States No

Transcription:

Monitoring Platelet Issues - a novel approach CUSUM Clive Hyam Blood Stocks Management Scheme London

Overview of Presentation What s driving the need to better understand platelet issues Potential tools that could be used to monitor platelet issues Selection & Explanation of CUSUM

Why Monitor Platelet Issues? Need to ensure that there is a sufficiency of supply. Prevent shortages. Understand if any increased demand is across all hospitals / areas or polarised within certain types of hospital / specific areas. You can t successfully solve a problem unless you firstly fully understand it.

Platelet Demand in England & N. Wales 290 280 270 Prediction for /13 280,000 8.3% Issues 000 260 250 240 4.0% 3.7% 230 220 0.5% 3.7% 210 2006/07 2007/08 2008/09 2009/10 2010/11 /12

Background In order to monitor platelet issues, a method is required that can identify whether any variation is due to chance or whether there is evidence of a significant change in the mean number of issues. Where the significant change can be demonstrated objectively.

Where to Start We started with experts Dave Collett and Elinor Curnow from statistics and clinical audit within NHSBT. Showed that platelet issue data was well represented by a normal distribution. Considered 3 different SPC (statistical process control) methods, (X bar) charts, Scan Statistic charts and CUSUM charts

Process Various scenarios were tried, to determine how many months before the sample statistic triggered. In each case this was repeated 10,000 times and the ARL (average run length) calculated. ARL was used to compare how quickly each method detected a change.

Outcome & Recommendations CUSUM charts generally detect change more quickly than either charts or scan statistic charts. CUSUM charts can signal at the first observation, whereas charts and scan statistic charts will only signal after a number of observations. The use of CUSUM charts was therefore recommended.

Next Steps Looked into developing a tool based on CUSUM charts that could be piloted by the hospitals belonging to East of England RTC During and after pilot gather feedback from users as to the usefulness of the tools provided.

CUSUM Charts Two charts are provided Observed Tabular CUSUM Expected O-E The O-E chart plots the cumulative difference between observed and expected platelet issues and is useful for observing changes over time. To identify statistically significant changes the tabular CUSUM chart is used to complement the O-E chart. A signal occurs when the tabular CUSUM exceeds a predefined limit (5 SD)

Important Point The O-E chart is a useful tool for observing performance over time. A downward trend in the O-E chart indicates lower than expected platelet issues whereas an upward trend indicates higher than expected issues. i.e. CUSUM effectively monitors both increases and decreases.

O-E CUSUM Chart East of England RTC The data contained in the chart represents the last 36 months worth of platelet issues to hospitals that make up the RTC. The first 24 months form a baseline average against which each of the most recent 12 months is compared. The results of these calculations are then graphed.

O-E CUSUM Chart East of England RTC East of England RTC (All) Observed - Expected CUSUM O-E CUSUM Observed - Expected CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month

O-E CUSUM Chart East of England RTC Chart displays a trend, rather than absolute numbers over time. Hence no scale on the Y axis Simplistic interpretation would be that platelet issues to the hospitals that make up the RTC are increasing month on month over time

Tabular CUSUM East of England RTC To determine when a significant increase in platelet issues has occurred the tabular CUSUM is used. The Tabular CUSUM imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular CUSUM is reset.

Tabular CUSUM East of England RTC East of England RTC (All) Tabular CUSUM Chart Limit Tabular Cusum Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month

Tabular CUSUM East of England RTC Tabular CUSUM chart shows an increase and a trigger in May Tabular CUSUM resets After trigger line trending upwards but more slowly than before

Proposed CUSUM BSMS Tool (All) Average PLT Issues per month in preceding 24 months = 1618 O-E CUSUM O-E CUSUM Tabular CUSUM Chart Limit Positive Tabular Cusum O - E CUSUM Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month Issue Month Issue Month Issues Oct 1678 Nov 1747 Dec 1885 Jan 1975 Feb 1807 Mar 1922 Apr 1703 May 1835 Jun 1825 Jul 1811 Aug 1738 Sep 1723 CUSUM is a sequential analysis technique typically used for monitoring change detection. The data contained relates to the last 36 months of platelet issues from NHSBT, months 1 to 24 form a baseline average which is displayed at the top just under the hospital name. Months 25 to 36 raw issues are shown in the table to left. The O-E Cusum is the sum of the observed - the expected issues for each of the most recent 12 months graphed. The Tabular Cusum imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular cusum is reset. A number of trigger points within the 12 month period indicates that platelet issues are showing 'statistical out of control' increases. Email To Platelets

Is that the end of the story?? Well not quite. We have looked at data for the RTC but are these trends reflected in all hospitals that make up the RTC??

P250 : Addenbrooke's Hospital Average PLT Issues per month in preceding 24 months = 443 O-E CUSUM O-E CUSUM Tabular CUSUM Chart Limit Positive Tabular Cusum O - E C U SU M Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month Issue Month Issue Month Issues Oct 422 Nov 446 Dec 450 Jan 597 Feb 438 Mar 459 Apr 422 May 414 Jun 439 Jul 409 Aug 439 Sep 476 CUSUM is a sequential analysis technique typically used for monitoring change detection. The data contained relates to the last 36 months of platelet issues from NHSBT, months 1 to 24 form a baseline average which is displayed at the top just under the hospital name. Months 25 to 36 raw issues are shown in the table to left. The O-E Cusum is the sum of the observed - the expected issues for each of the most recent 12 months graphed. The Tabular Cusum imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular cusum is reset. A number of trigger points within the 12 month period indicates that platelet issues are showing 'statistical out of control' increases. Email To katherine.philpott@addenbrookes.nhs.uk

P637 : Watford General Hospital Average PLT Issues per month in preceding 24 months = 84 O-E CUSUM O-E CUSUM Tabular CUSUM Chart Limit Positive Tabular Cusum O - E CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month Issue Month Issue Month Issues Oct 58 Nov 77 Dec 50 Jan 77 Feb 82 Mar 117 Apr 94 May 88 Jun 105 Jul 121 Aug 72 Sep 75 CUSUM is a sequential analysis technique typically used for monitoring change detection. The data contained relates to the last 36 months of platelet issues from NHSBT, months 1 to 24 form a baseline average which is displayed at the top just under the hospital name. Months 25 to 36 raw issues are shown in the table to left. The O-E Cusum is the sum of the observed - the expected issues for each of the most recent 12 months graphed. The Tabular Cusum imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular cusum is reset. A number of trigger points within the 12 month period indicates that platelet issues are showing 'statistical out of control' increases. Email To john.taylor@whht.nhs.uk

P255 : Norfolk and Norwich University Hospital Average PLT Issues per month in preceding 24 months = 79 O-E CUSUM O-E CUSUM Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Chart Limit Positive Tabular Cusum O - E CUSUM Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Issue Month Issue Month Issue Month Issues Oct 72 Nov 60 Dec 72 Jan 56 Feb 53 Mar 79 Apr 56 May 74 Jun 89 Jul 79 Aug 92 Sep 51 CUSUM is a sequential analysis technique typically used for monitoring change detection. The data contained relates to the last 36 months of platelet issues from NHSBT, months 1 to 24 form a baseline average which is displayed at the top just under the hospital name. Months 25 to 36 raw issues are shown in the table to left. The O-E Cusum is the sum of the observed - the expected issues for each of the most recent 12 months graphed. The Tabular Cusum imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular cusum is reset. A number of trigger points within the 12 month period indicates that platelet issues are showing 'statistical out of control' increases. Email To deborah.asher@nnuh.nhs.uk

P256 : Papworth Hospital Average PLT Issues per month in preceding 24 months = 124 O-E CUSUM O-E CUSUM Tabular CUSUM Chart Limit Positive Tabular Cusum O - E CUSU M Tabular CUSUM Oct Nov Dec Jan Feb Mar Apr Issue Month May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr Issue Month May Jun Jul Aug Sep Issue Month Issues Oct 187 Nov 184 Dec 201 Jan 187 Feb 192 Mar 251 Apr 171 May 198 Jun 228 Jul 217 Aug 232 Sep 179 CUSUM is a sequential analysis technique typically used for monitoring change detection. The data contained relates to the last 36 months of platelet issues from NHSBT, months 1 to 24 form a baseline average which is displayed at the top just under the hospital name. Months 25 to 36 raw issues are shown in the table to left. The O-E Cusum is the sum of the observed - the expected issues for each of the most recent 12 months graphed. The Tabular Cusum imposes a 'chart limit' which is calculated at 5 standard deviations above the two year average, should this 'chart limit' be exceeded a trigger point is recorded i.e. data line above 'chart limit' and the tabular cusum is reset. A number of trigger points within the 12 month period indicates that platelet issues are showing 'statistical out of control' increases. Email To martin.pooley@papworth.nhs.uk

Next Steps Pilot with the hospitals of the East of England RTC, reports to be sent via email on a monthly basis. Feedback required via a short survey monkey at the beginning and towards the end of the pilot to gauge users opinions and how they may have changed over time.

Acknowledgements Clive Hyam - BSMS Data Analyst Catrina Hall - BSMS Research Analyst Elinor Curnow - NHSBT Senior Statistician

Thank you for your attention Any Questions