PDUC Registry Audit and Quality Improvement

Robert A. Baker PhD CCP(Aust)

Received Research and Travel Support from the Terumo Corporation and Cellplex Pty Ltd.The Perfusion Downunder Meeting is sponsored by Cellplex Pty Ltd. Disclosures

In Brief!What is the PDUC?Where we are at!A look at benchmarksAuditQuality Improvement

What is the Perfusion Downunder Collaboration?

Mission Statement

To foster and grow high quality research in the perfusion sciences by the establishment and maintenance of a prospective data set on cardiac surgical procedures performed in centres throughout Australia and New Zealand.

5444 procedures from six Australian and New Zealand cardiac centers in the period March 2007 to March 2010

Male (74%)Female (26%)Age by Sex

Risk Factors

Procedure types

Morbidity

30 Day Mortality

maximum glucose >10 mmol/l during CPBmaximum arterial line temperature >37C during CPBblood gas management outside of pCO2 range 35 to 45 mmHgNADIR Haemoglobin < 70 g/LQuality Indicators

Developing Benchmark in Perfusion?

Defining benchmarking?Concept of using a structured method of quality measurement and improvementProcess of measuring performance using one or more specific indicators to compare activity with others

What is benchmarking?Important tool for quality improvementIdentification of leaders in the field Involves measuring and analysing process-of-care indicators Integral if we want to move from performance measurement to performance improvement

What are benchmarks?Benchmark characteristics;Represent a measurable level of performance Should be demonstrably attainable Based on objective criteria and must incorporate what is reliably and validly measured

Weissman et al 1999 J Eval Clin Pract 5;269-281

Data Collection5444 procedures from six Australian and New Zealand cardiac centers in the period March 2007 to March 2010BenchmarkingCABG / Valve / Valve/graft3973 casesSubset of variables selected to facilitate comparison with the most recently published ASCTS database data

Methods - BenchmarksChosen Four QI to investigate;

maximum blood glucose pCO2 managementminimum haemoglobin arterial outlet temperature > 37oC

Achievable Benchmark of CarePremise is to base assessment of performance on actual performance cf subjective what should/could be doneBenchmarksMeasurable level of excellenceAttainable Selection of high performers should be structured and reproducibleAll high performers should contributeSmall numbers should not dominateChange with continuous improvementWeissman et al 1999 J Eval Clin Pract 5;269-281

MainMaintenance of EuglycemiaThe clinical team should maintain perioperative blood glucose concentration within an institutions normal clinical range in all patients, including non diabetic subjects. (Class 1, Level B)

Maximum Blood Glucose During Bypass

Maximum Blood Glucose During Bypass

Glucose benchmark calculation

ABC denominator = 3958 (15 cases with missing data)

10% subset = 395 eligible procedures.

Since 1st rank site has >395 eligible procedures,

Benchmark = 20%

Incidence of DiabetesPreop Glucose

Sigrid TubleFlinders Medical CentreAdelaide, South Australia

Reliable InformationPreserve Confidence

AccuracyCompleteness

Plan the evaluation/auditDevelop audit guidelinesImplementation of audit processEvaluate the quality (i.e. accuracy and completeness) of dataIdentify discrepancies and their causeRecommend quality assurance procedures

Participating centres/periodFlinders Private Hospital/2008 (FPH)Flinders Medical Centre/2008 (FMC)Ashford Hospital/2009 (AH)Sample10% of casesEligibility criteriaProcedures with cardiopulmonary bypass:Valve Coronary artery bypass graftValve/graftSource documentsCase notesPerfusion reportsLocal data collection forms Local electronic databases Unavailable source documentsIntensive care unit charts

Number of variables: 57 (out of 260)Relevance of the variables:Cardiac risk models (e.g. AusScore, Euroscore)OutcomesPerfusion DownunderData missing and not entered in > 20% (Data Quality Reports October 2009)

n = 57 variables

Category (n)VariableCategory (n)VariableCategory (n)VariableDemographic (5)AgeNYHALength hospital staySexInfarct septal ruptureLength postop stayWeightPerfusion (9)Procedure dateDischarge statusHeightCPB Time30 day mortalityEthnicityCross-clamp timeDeath locationClinical (15)Chronic pulm diseaseCP induction tempCause of deathExtracard arteriopathyPreop glucoseNew comaNeuro dysfunctionFinal naso tempNew renal failurePrev cardiac surgeryACT baselineDischarge dateActive endocarditisACT finalPostop max creatCritical preop stateCreat > 200 mol/ LIABPUnstable anginaProcedure (4)Procedure typeReturn to theatreEstimated LV functionCABGICU blood loss 4 hrsRecent MIMitral valve repairICU bloodUrgency Outcomes (24)DeathICU plateletPulmonary hypertensionStrokeICU FFPHyperchol EncephalopathyPostop MI EFVentilation timeReturn to ICUCHFICU stayPostop dialysis

Perfusionists = 5Surgeons = 5Eligible cases = 635Audit sample size = 63Cases/centre = 13 FPH, 31 FMC, 19 AHCompleted audit = 60 (3 unavailable for AH)

n = 3,420 data

(57 variables 60 cases)

Systematic errorsData transfer and calculation (e.g. postop dialysis and ventilation time)Unclear or ambiguous data definitions (e.g. mitral valve type)Random errorsTranscription & incompleteness of data source (e.g. ICU time, mortality 30-day)Lack of adherence to data definitions (e.g. CABG type, creatinine levels)

Ensure good data definitions (clear & unambiguous)Periodic training of database personnel Reduce frequency of Incompleteness, Non-adherence to data definitions, Inter-observer variabilityComprehensive documentation of data collection guidelinesHigh quality data collection forms Routine data monitoring programme (independent auditor or data managers)

*PDU QUALITY CONTROL INITIATIVECarmel Fenton; YiYi Huang; Nick Carr

Royal Hobart HospitalHobart, Tasmania, Australia

Statistics: Michael Long

*RHH FOCUS ON TRANSFUSION RATES

*RHH QUALITY INDICATORPROBLEM:

PDU indicator for Hb at 7 g/dl

RHH indicator for blood transfusion trigger is Hb of 6 g/dl

Change in PDU Quality Indicator criteria to include Hb

*GOALSDecrease the number of patients with min Hb on CPB

*PDU QUALITY CONTROL INITIATIVE

*P < 0.01

Retrograde Autologous Priming of the Cardiopulmonary Bypass Circuit: A Quality Improvement Initiative and Prospective Clinical Audit.Richard NewlandOn behalf of the Flinders Cardiac Surgery Team

Flinders Medical CentreAdelaide, South Australia

*Good afternoonPresent the first evaluation of the data quality in the PDUC DatabaseFocus on the role of data quality assurance towards a high quality clinical databasesFirst of all, why do we need quality and to evaluate it?**Quality is what we need in a clinical database**Quality in data means**X is what I am going to present to you today**Considerations during planning of auditOrganisers were interviewed to gain insight and understanding of the data collection processGuidelines were developed fully considering the aims of the auditThere are 7 current participating centresUse of a pre-programmed random case selector queryLocal electronic database used as source for data entered first in database.

**Choosing problematic variables is expected to bias the outcome of the audit but it is important to identify the causes of the missing and not entered data.From here onwards, when I discuss data that are not entered, data actively not entered by the database personnel, this can be because they are unavailable or has not been doneVariables selected that were relevant to cardiac surgery risk models (AusScore, EuroScore and the Society of Thoracic Surgeons 30-day operative mortality and morbidity risk models) and based on missing and not entered data from October 2009 PDUC Database Data Quality Reports

****Notify participating centres (1-2 weeks prior to audit)

**Based on the number of data pointsAccurate and completeInaccurate3.2% total missing, small % cannot be validated2.2% total not entered, small % cannot be validatedLocal database, considerable2% cannot be validated at all**Present the rates, focus on accuracy and completenessNumber of variables accurate and completeBased on number of cases out of the 60 audited, presented here in %> 75 % 42 variables7 variables < 25% - Cardioplegia induction temperature, final nasopharyngeal temperature, location of mortality, postoperative maximum creatinine, intraoperative use of IABP, ICU blood loss 4 hrs, cause of mortality

**Rate are based on % cases per participating centreDifferent data management system per centreMajority < 25% of cases with inaccurate dataPostop maximum creatinine specific for FMC, mainly due to difference in units (same for AH), some not the highest value postopMost inaccuracy are due to coding errors!FMC ventilation time (included from intubation) and ICU time (transcription error)FPH Length of days date difference calculation issueAH Pre-op creatinine (units), ventilation time (transciption errors for 31%), CABG type (lack of adherence to data definition)**Routine data monitoring by data managers, by choosing a simple variable to audit.***Thought Id better clear up any misconceptions about where Hobart, Tasmania is**At the time as a unit we were focusing on decreasing our Transfusion rate which had been steadily increasing.As a perfusion group all we could do was to do as much as possible to limit the hemodilution effect of CPB.We had done all the usual things such as minimising the circuit as much as possible; encouraging the surgeons to cut as much out of the A-V loop as possible & on selected cases retrograde autologous priming.**As haemodilution was the area we were targeting we obviously chose the perfusion quality indicator Hb