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Statistical Report on Diagnoses of C. difficile and Deaths among Patients with C. difficile

Statistical Report on Diagnoses of C. difficile and Deaths among Patients with C. difficile. Chris Robertson Strathclyde University Health Protection Scotland. Outline. Aims and Methods Diagnoses of C. difficile Comparison of wards and periods Testing for C. difficile

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Statistical Report on Diagnoses of C. difficile and Deaths among Patients with C. difficile

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  1. Statistical Report on Diagnoses of C. difficile and Deaths among Patients with C. difficile Chris Robertson Strathclyde University Health Protection Scotland

  2. Outline • Aims and Methods • Diagnoses of C. difficile • Comparison of wards and periods • Testing for C. difficile • Where and when was testing taking place • Rates of new diagnoses per 1000 occupied bed days • Comparison of wards and periods • Funnel plots to compare wards • Death Rates among patients with C. difficile • All cause deaths and deaths where C. difficileis a contributory cause • Control Charts • Were the number of cases per week typical • Potential Outbreak Analysis* • Number of cases in a ward at the same time * • Trends in C. difficilereports over time * * At request of Vale of Leven Inquiry Team

  3. Aims and Methods Aims • Investigate pattern of Diagnoses of C. difficileand the extent to which the pattern varies over wards and time • Investigate pattern of Testing for C. difficileand the extent to which the pattern varies over wards and time • Investigate pattern of Deaths and report on the extent to which the pattern varies over the wards and period

  4. Aims and Methods Methods • The rate of occurrence of events or the proportion of patients with an event, which require the use of an appropriate denominator. • In some instance the denominator will be • the number of patients with C. Difficile, • the number tested for C. Difficile, • the number of occupied bed days. • The latter denominator is required for comparison of wards as the wards are of different sizes.

  5. Aims and Methods Methods • Analysis of rates is based upon the Poisson distribution • Assessed using standard methods • residual plots and index of dispersion test • Comparison of proportions • Fisher’s exact test and exact binomial confidence intervals • Time to event analysis • Cox regression

  6. Aims and Methods Study Period • 3 periods of particular interest: • January to June 2007, • July to November 2007 and • December 2007 to June 2008 • The latter period is the period most under scrutiny • January to June 2007 is the period which is most directly comparable (temporally) to the main study period

  7. New diagnoses of C. difficile Distribution of new diagnoses ofC. difficile over time and ward • Generally the ward of sample collection is the same the same ward that the result is returned to but not always • Due to patient movement • Admissions • Transfers from and to another hospital • 2 views • By ward the sample was collected from • By ward the positive result was returned to • Descriptive analysis of where in the hospital C. difficilewas present

  8. New diagnoses of C. difficile New and Repeat Infections

  9. New diagnoses of C. difficile All New Diagnoses of C. difficileby ward of diagnosis Black spots are the first positive test; green dots are a presumed new infection in a patient previously positive for C. difficile. Diagnoses from RAH, WIG, Home or community are excluded

  10. New diagnoses of C. difficile All New Diagnoses of C. difficileby ward of sample collection Black spots are the first positive test; green dots are a presumed new infection in a patient previously positive for C. difficile. Diagnoses from RAH, WIG, Home or community are excluded

  11. New diagnoses of C. difficile Summary – New Diagnoses • C. difficileis present throughout the whole period from January 2007 to June 2008, • Especially in Wards 6, 14 and 15. • This presentation does not take into account ward size or occupancy. • Little difference between results presented by ward of sample collection and ward result reported to and most subsequent analysis is based upon ward of report

  12. Testing for C. difficile Testing for C. Difficile by ward and time • The aim of this section is to see if testing is spread throughout all the wards or is localised to a few wards or a specific period • Examples from 3 wards

  13. Testing for C. difficile Positive Continuation: Previous positive result may have been in another ward Positive Subsequent: Previous first diagnosis may have been in another ward

  14. Testing for C. difficile

  15. Testing for C. difficile Summary: testing for C. difficile throughout the whole period in virtually all wards but especially in 14, 3, 5, 6, F and CCU/HDU Even in wards with few cases

  16. Testing for C. difficile Summary • Testing throughout the whole period in virtually all wards but especially in • 14, 3, 5, 6, F and CCU/HDU. • This presentation does not take into account ward size or occupancy • 6, 14 and 15 with 19, 22 and 23 beds occupied on average; • 3, 5, F, Fruin are smaller at 17, 14, 15, 12 beds • CCU/HDU at 9 beds.

  17. Rates of C. Difficile per 1000 occupied bed days Rates of C. difficile • Rates per 100 occupied bed days so that comparisons of wards and periods are referred to a common baseline • Aim • Is there any evidence that the rate of new diagnoses varies • over period • over ward

  18. Rates of C. Difficile per 1000 occupied bed days Rates of new C. difficile infections per month Ja7 is January 2007, Ja8 January 2008. Occupied beds days data is not available for every day and imputed values are used when necessary. The horizontal dotted blue line is the average rate of new infections per week in the hospital over the whole study period. The vertical green dotted lines separate the time axis into the three periods.

  19. Rates of C. Difficile per 1000 occupied bed days C Difficile Rates by Ward No significant difference between the two periods, Jan to May 2007 and Dec-Jun 2008, p = 0.59 Significant differences between the wards, p < 0.0001 The dot is the rate and the horizontal line represents the 95% confidence interval for the rate. The rates are derived from a Poisson regression model adjusting for ward and period (Jan to Jun 2007 and Dec 2007 to June 2008)

  20. Rates of C. Difficile per 1000 occupied bed days Summary – Rates • Ward F has two clear peaks in April/May 2007 and January/February 2008. • The double peak is also visible in ward 3 while the 2008 peak is visible in ward 6. • The April 2007 peak can be identified in ward CCU(4)/HDU. • Wards 5, 14 and 15 have fairly constant rates • Rate of C. difficile infections varies among the three periods, p = 0.010. • The rates in the period Jul to Nov 2007 are 45% (95% CI 10%, 67%) lower than those in the first period (Jan to Jun 2007). • No difference in rates between Jan to Jun 2007 and Dec 2007 to June 2008

  21. Funnel Plots of Rates of C. Difficile Funnel Plots • Funnel plots show the anticipated variation in the rates of new infections among the wards. • Aim of this section is to see if there is evidence that the rates of diagnoses of C. difficile in a ward are higher or lower than the average in the hospital taking into account • the natural variation you would expect by chance, and • the size of the wards as measured by occupied bed days.

  22. Funnel Plots of Rates of C. Difficile Monitoring Funnel Plots – what variations should you expect if the rate is the same in all wards Bed Occupancy increased? – one month extra observation time in latter period No cases in Fruin Jan 2007-June 2007

  23. Funnel Plots of Rates of C. Difficile Summary Funnel Plots • In the first two periods there is no evidence that any ward has substantially higher rates of C. difficilewith regard to the others, • though ward 15 and Fruin have lower rates in the first period. • In the last period December 2007 to June 2008, • Ward 6 has higher rates than the others, • ward 5 and Fruin have lower, • and all are outside the 95% funnel plot limits for the size of the ward. • Assuming that the Poisson model is valid this suggests that there may be more variability among the wards than could reasonably be attributed to chance (at the 95% confidence limits).

  24. Death Rates Deaths • Is there evidence that the rate of death among patients who were diagnosed with C. difficile vary • over ward, and • over period.

  25. Death Rates All Cause Deaths • There are 130 C. difficile patients and for 80 there is a record of death. • Death Rate is 61.5% (95% CI 52.6%, 69.9%) • percentage of patients who had C. Difficile who died • Of the 80 patients who died, • 25% died within 6 days of the confirmed diagnosis being reported to the ward, • 50% within 17 days, • 75% within 2 months and • 90% within 4 months. • Three patients died on the day of report and 7 died before the report came back to the ward (1 with a 3 day gap, and 3 with gaps of 2 days, 3 with gaps of 1 day) – the sample was collected while the patients was alive but the patient died before the laboratory reported.

  26. Death Rates Percentages of Patients with C. difficile who died by Ward There is a great deal of variation – some wards had few C Difficile patients, but no statistically significant differences, p=0.14

  27. Death Rates Percentages of Patients with C. difficile who died by Period No statistically significant differences, p=0.73

  28. Death Rates Percentages of Patients with C. difficile dying within 30 days by Ward There is a great deal of variation – some wards had few C Difficile patients, but no statistically significant differences, p=0.75

  29. Death Rates Percentages of Patients with C. difficile dying within 30 days by Period No statistically significant differences, p=0.45

  30. Death Rates Cause of Death of the 60 patients who had a diagnosis of a new infection of C. difficile between December 1st, 2007 and 30th June 2008 No evidence that having C. difficile as a contributory cause of death is related to the ward of collection of the sample, p=0.31, or ward of diagnosis, p = 0.29.

  31. Death Rates Summary - Deaths • There is no evidence that the percentage of C. difficile patients who died varied over period or ward. • There is no evidence that percentage of C. difficile patients who died with C. Difficile is a contributory cause varied over ward in the period December 2007 to June 2008. • Analysis takes into account, age and gender and time to death from first diagnosis but does not adjust for co morbidity of patient • The relatively small sample size and large number of wards make it difficult to detect differences unless they were very large.

  32. Control Charts Control Charts for new infections • In this section the use of elementary control charts on the weekly new notifications of C. difficile infections per ward is investigated. • The aim is to see if or when there would have been statistical evidence suggesting that there were an exceptionally large number of C. difficile cases in the hospital i.e. exploratory. • The study period is divided into two separate periods • Jan-Nov 2007 and Dec 2007 to Jun 2008. • The main focus is the period Dec 2007 to Jun 2008 and data from the earlier period is used to set the baseline control limits.

  33. Control Charts Control Charts Dec 2007-Jun 2008 The mean number of new diagnoses of C. difficile in patients residing in the hospital from the period Jan to Nov 2007 is used to construct the control chart – 1.69 per week. In the period Dec 2007 to Jun 2008 there are two instances where the statistical process control methods signal - the week beginning 21 January 2008 and the week beginning 28 April 2008

  34. Control Charts Control Charts - Summary • Using the period January 2007 to November 2007 to set the baseline, there is evidence of 2 periods of a large number of new diagnoses of C. difficile in the hospital than would be expected by chance • Conclusions unchanged when using the period January to June 2007 as baseline • Analysis is retrospective and does not reflect the situation which would have been observed as the data evolved prospectively

  35. Potential Outbreaks Potential Outbreaks of C. difficile • During the period Jan 2007 to June 2008 guidelines for defining the occurrence of an outbreak existed. • Aim of this investigation is to see if there were any dates when an outbreak may have occurred. • Investigation carried out at the request of the Vale of Leven Hospital Inquiry team

  36. Potential Outbreaks Potential outbreaks NHS Greater Glasgow and Clyde Control of Infection Committee Policy. Outbreak Policy for outbreaks in healthcare premises. Effective from July, 2006; Review Date July 2010; Replaces previously issued outbreak policies

  37. Potential Outbreaks Re - creation of C. difficileburden in hospital - Assumptions • A patient with C. difficilehas it for 7 days (range 3-10) following any positive test, not just the first positive test. • Movement of patients between wards and transfers out and death taken into account • Analysis is fraught with difficulties because of the lack of absolute certainty in the data. • Although the ward to which the diagnosis was reported is known there is no guarantee that the patient remained in the same ward for the subsequent 7 days if there is no mention of death, discharge, transfer out to another hospital or movement to another ward. • analysis is the weakest and the one which is most sensitive to the data quality.

  38. Potential Outbreaks Example Patient Trajectories Day 1 2 3 4 5 6 7 8 9 10 11 Ward A Same ward for all 7 days – No subsequent positive test Ward A Same ward - subsequent positive test on day 3 Ward A Same ward - Died or transferred out on day 4 Denotes patient with C. difficile diagnosis on ward

  39. Potential Outbreaks Example Patient Trajectories Day 1 2 3 4 5 6 7 8 9 10 11 Ward A Ward B Moved ward day 3 - No subsequent positive test Ward A Ward B Moved ward day 3 - subsequent positive test day 7, died day 10, moved back to original ward day 10

  40. Potential Outbreaks Example Ward Trajectories Day 1 2 3 4 5 6 7 8 9 10 11 Patient A Moved ward day 3, returned day 6 Patient B Patient died on 5th day post diagnosis Number of Positive patients in ward 1 1 2 1 1 2 2 0 0 0 0

  41. Potential Outbreaks Estimated numbers of C. difficilePatients in the hospital per day Seldom is there a period with no C. difficile cases in the hospital, 29% of the whole period

  42. Potential Outbreaks Potential Outbreaks in the wards A black spot corresponds to an occasion when there are 2 patients with C. Difficile in the ward on the same date; A red spot corresponds to 3 or more patients. No episodes were observed in the wards not listed in the graphs.

  43. Potential Outbreaks Potential outbreaks in the wards3 day period after positive test A black spot corresponds to an occasion when there are 2 patients with C. Difficile in the ward on the same date; A red spot corresponds to 3 or more patients. No episodes were observed in the wards not listed in the graphs.

  44. Potential Outbreaks Outbreak - Summary • Analysis sensitive to assumptions and data quality • Evidence of instances where potential outbreaks are possible even with most favourable conditions (1 day post diagnosis) • Both in the January to June 2007 and in the December 2007 – June 2008 period

  45. Time Trends Comparison with C. difficile cases prior to 2007 • Investigation carried out at the request of the Vale of Leven Hospital Inquiry team • This investigation is likely to be subject to ascertainment bias due to • Introduction of mandatory reporting of C. difficile cases from September 2006 onwards • More detailed investigation of hospital and laboratory data in the period January 2007 – June 2008

  46. Time Trends New Reports of C. difficile from 2003 to June 2008 • Data were collected as part of a police investigation and were typed into a spreadsheet from the Vale of Leven infection control team records. • Potentially useful for describing the historical trends in the numbers of cases of C. difficilein the Vale of Leven Hospital prior to the period under investigation in this report. • Comparisons of the early with cases from 2007 onwards must always bear in mind that mandatory reporting of all cases of C. difficilein patients over 65 was established as from 1st September 2006. • With mandatory reporting came • a national case definition, • rules for case finding and definitions; • reporting practices prior to September 2006 may not be comparable with reporting practices after this period.

  47. Time Trends New Reports of C. difficile from 2003 to June 2008 • In the period 2003-2006 there were on average 2.3 new patients with C. difficileper year • some evidence of an increasing trend, p = 0.042 • rates increasing by 19.7% (95% CI 0.7%, 42.3%) per year. • In the three periods which were wholly after the introduction of mandatory reporting for C. difficileamong those aged 65 or over there was a big increase in the rates of new patients per month, p < 0.0001, adjusting for trend

  48. Time Trends Summary – 2003-June 2008 • It is not easy to interpret the increase in rates as mandatory reporting was introduced in September 2006 • part of the increase may be due to changes in reporting and ascertainment practices. • Part of the increase may also be associated with a continuation of the increasing trend from 2003 to 2006.

  49. Summary Summary - Data • There are data issues. • There were rather a large number of data corrections and this leads to a reduction in confidence in the data. • Some of the problems will stem from data recording issues in case notes and missing information in cases notes. • The database in the legal office was not set up for a rigorous analysis as much information was contained within the same text entry field. • Patient movement data may not be complete • Not absolutely certain that the database for the trend analysis had all cases of C. difficile, • testing regime may have been different 2007 onwards

  50. Summary Summary C. Difficile Cases • C. Difficile is present throughout the whole period from January 2007 to June 2008 notably in in Wards 6, 14 and 15. • Using data from Jan – Jun 2007 and Dec 2007-Jun 2008 • there are higher rates of new C. Difficile infections in wards 6 and F, • no differences in the rates between the two periods. • The funnel plot analysis suggested that in the last period December 2007 to June 2008 the level of variation among the wards was greater that anticipated: • Ward 6 had higher rates of new C. Difficile infections than the other wards and ward 5 had lower rates.

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