RQ MassMEDIC CAPA On CAPA Webinar v2€¦ · § Indications that your CAPA system may be feeling a...

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CAPA ON CAPA “We should work on our process, not the outcome of our processes”

Transcript of RQ MassMEDIC CAPA On CAPA Webinar v2€¦ · § Indications that your CAPA system may be feeling a...

Page 1: RQ MassMEDIC CAPA On CAPA Webinar v2€¦ · § Indications that your CAPA system may be feeling a little under the weather: § CAPA metrics are inadequate for management understanding

C A P A O N C A P A

“We s h o u l d w o r k o n o u r p r o c e s s , n o t t h e o u t c om e o f o u r p r o c e s s e s ”

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A B O U T R & Q

RegulatoryandQualitySolutions(R&Q)providesindustry-leadingregulatoryandqualityengineeringservicesthroughouttheentireproductlifecycle.

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A B O U T T O D A Y ’ S S P E A K E R

§ 25+yearsofdomesticandinternationalexperience

§ Previous:Covidien,BostonScientific,BARD

§ VPQuality- Maintained20+manufacturingplantsworldwide

PaulRobinson,SeniorDirectorofRegionalOperations,R&Q

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A G E N D A

§ Why?§ Realworld

§ Readyforanaudit?WhatdoestheFDAlookfor?§ CAPAregulations/requirements

§ 820.100

§ CAPAsystem§ Feeders§ Datatrending/evaluation/alerts§ CAPAprocess

§ Riskmanagement§ Systemmanagement

§ TheCAPA§ Rootcauseanalysis§ Statisticaltools§ ELCD– Engineering,Logic,CommonSense,andDiscipline!

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W H Y ?

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W H Y ?

§ Realworld§ FDAaudit§ 80/20rule– everheardofthat?

§ Remember:CAPAisnot anassignmentorproject.Itisasystem.§ CAPAhasbeencalledthe”immunesystem”oftheQualityManagementSystem.Itmustworkforyourorganizationtorepairorimproveitselfproperly.

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TimeforaCheckup?

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W H Y ?

§ IndicationsthatyourCAPAsystemmaybefeelingalittleundertheweather:§ CAPAmetricsareinadequateformanagementunderstandingandcontrol;toomany,toofew,tooconfusing

§ CAPAprojectsarenotprogressing§ Thereisaveryweak“CAPAculture”§ Yourorganizationseemstohavetoomany CAPAprojectsortheyarelanguishing

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We’lldiscusswhattodoina

fewslides

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W H Y ?

§ Realworld?§ Managedcorrectly,it’sanopportunityforimprovement

§ Reportingproblems§ Proactivelyaddressingproblems§ Closedloopsystem

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Don’tbeafraid!

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W H Y E L S E ?

§ Regulationsrequireit!§ 21CodeofFederalRegulations(CFR)820.100“Eachmanufacturershall establishandmaintainproceduresforimplementingcorrectiveandpreventiveaction.”

§ ISO13485:2003,8.5.2,8.5.3“Theorganizationshall identifyandimplementanychangesnecessarytoensureandmaintainthecontinuedsuitabilityandeffectivenessofthequalitymanagementsystemthroughtheuseofthequalitypolicy,qualityobjectives,auditresults,analysisofdata,correctiveandpreventiveactionsandmanagementreview.”

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Evenifnotrequired,itisstillsmarttodo.Ishouldknow,I’m

anowl!We’rewickedsmaht!

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C A P A S Y S T E M

F e e d e r s

D a t a T r e n d i n g / E v a l u a t i o n /A l e r t s

C A PA P r o c e s s

S y s t e m M a n a g em e n t

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Onemoretime.Itisnotanassignment

oraproject.ItisaSYSTEM!

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T H E F E E D E R S

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CAPASystem!

ManagementReview

Audits

Complaints/MDRs

Non-ConformingMaterial

EnvironmentalMonitoring

SupplierQuality

Scrap

Re-work

Allfeedersareequal,somemoreequalthanothers!

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D A T A T R E N D I N G / E V A L U A T I O N / A L E R T S

§ How?§ Tables§ Runcharts§ SPC§ Paretoanalysis§ Audits§ Complaints§ Etc.

§ What’simportanttomonitorwithinyourfeedersystem?§ Howyouaregoingtoevaluate;andwhatareyouralert/actionlimits?

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Feeder Owner Metric ReportingFrequency

Method Alert Limit

Scrap Operations % Scrap Monthly SPC SPC Rules

Audits Quality % Schedule Monthly Limit >95%

Howyoudoin?

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C A P A P R O C E S S ( R I S K - B A S E D A P P R O A C H )

InitiateCorrectiveActionRequest

1.NoAction 2.Correction 3.CAPA

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C A P A P R O C E S S

1. ProblemStatement

2. Feeder/Source/Alert3. ProductsAffected

4. ProcessesAffected

5. Departments/FunctionsAffected

6. EventDescription/Summary

7. InitialRiskAssessment(withRationaleandDocumentation)8. InitialFrequencyAssessmentwithrationaleanddocumentation

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InitiateCorrectiveActionRequest

Seerisk-baseddecisionmatrixexamplenextslide

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P R O C E D U R E

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RISK BASED ESCALATION

FREQUENCYProbability is so

remote Unlikely probability Occasional

probability Moderate probability

High probability

1 2 3 4 5

PRO

DUCT

AND

/OR

BUSI

NESS

RIS

K

Negligible Patient Risk

Business Performance Risk 1 NO ACTION REQUIRED

NO ACTION REQUIRED CORRECTION CORRECTION CORRECTION

Minor Patient Risk

Internal Compliance Risk 2 NO ACTION REQUIRED CORRECTION CORRECTION CAPA CAPA

Moderate Patient Risk

Documentation Compliance Risk 3 CORRECTION CORRECTION CAPA CAPA CAPA

Severe Patient Risk

Quality System Compliance Risk 4 CAPA CAPA CAPA CAPA CAPA

Catastrophic Patient Risk

Regulatory Approval/Warning Risk 5 CAPA CAPA CAPA CAPA CAPA

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C A P A P R O C E S S

1. OK,butprovidesolidrationale…

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NoActionRequired

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C A P A P R O C E S S

1. Contain

2. Correctanddispose

3. Verify

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Correction

Timetolean?TimetoClean!

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C A P A P R O C E S S

1. Correction1. Contain2. Dispose3. Verify

2. Investigation

3. Solutionverification/validation

4. Implementation

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CAPA

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S Y S T E M M A N A G E M E N T

§ Managementreview

§ CAPAboard

§ Qualityreports

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ItwouldnotbeincorrecttoassumethattheCAPAsystemisoneof,ifnot,THEmostimportantcomponentsofaQualitySystem,SOMONITORitshealthandeffectivenessandTAKEACTIONasneeded!- PAULROBINSON

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T H E C A P A

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

1. Correction1. Contain2. Dispose3. Verify

2. Investigation

3. Solutionverification/validation

4. Implementation

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Thereisno

MagicWand!

E.L.CS.D!

Ok,I’mdone…

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ Avoiding…

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ORPROBLEMPARETO

Isolvedthisone,I’mdone!

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ Investigation

1. Problemdescription1. ”What’syourproblem?”

2. Backgroundinformation1. “HowdidIgethere?”

3. Sourceinvestigation1. “Iknowit’sinheresomewhere.”

4. Miningtools1. Dig,dig,dig

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§ Implementation

1. Verification/validation!

2. Verification/validation!

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

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DeterminingProbabilities Theprobabilityofaneventisthenumberofoutcomesthattheeventoccursdividedbythenumberofpossibleoutcomes.Forexampletheprobabilityofgettinga“heads”ontheflipofacoinis½or.5(heads/heads+tails).Thistoolcanbeusedindeterminingcomplaintrates,defectlevels,non-conformances,etc.

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ MeasurementSystemAnalysis§ Overallvariationcomingfromaproductorprocessismadeupofthevariationinherent

intheproductorprocessitselfandanaddedcomponentofvariationcomingfromthemeasurementsystem.

§ Measurementsystemvariabilitycanbebrokendownintotwocomponents,repeatabilityandreproducibility.Repeatabilityisthebuiltinvariationofameasurementsystemandiscalculatedusingrepeatedmeasurementsmadeofthesamevariableunderidenticalconditions.Reproducibilityresultswhendifferentconditionsareimposedonmeasurements(differentoperators,setupmethods,environment,etc.)

§ ThemetricsoftencalculatedaretheGaugeR&R(repeatabilityandreproducibility)andtheP/Tratio.TheR&Rrepresentstheproportionoftheoverallvariationcomingfromyourmeasurementsystem.TheP/Tratioistheamountofyourspecificationtakenupbymeasurementsystemvariationalone.

§ Beforedoinganyanalysis,itiscrucialtohavecapablemeasurementsystems.ValuesforR&Rshouldbelessthan30%.ValuesforP/Tratioshouldbelessthan15%.Note-therequiredvaluescanbechangedbasedonrisk.

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ Processanalysis§ Shape§ Spread§ Centraltendency§ Temporalelement§ Capability

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Processanalysiscanbedonebylookingatvariouselementsofdatadistribution.

Shape- Reviewingtheshapeofadistributioncanhelpidentifycertainfactsaboutaprocess.Isitskewedtoonesizeoranother?Doyouhaveabi-modeldistribution(potentialoftwosamplepopulations?)Isitnormal?Flat?

Spread- Howvariableisyourprocess?Oftendefinedbythestandarddeviation(squarerootofvariance)orinsomecasestherange(differenceofthehighpointversesthelowpoint- sensitivetooutliers)

CentralTendency- Thecenterofthedistribution.

TemporalElement:Howdoestheprocesschangeovertime?Typicallyrunchartsareeffectivewaystomeasurehowaprocesschangesovertime.

Capability:Severaltermsareusedtodefinecapability.

Cp istheshortterm/limiteddatacapabilityofyourproductorprocessinmeetingtherangeofyourspecification.Itistheratioofyourshorttermvariationdividedbythewidthofyourspecificationrange.Ifbarelycapable,thatratiowillbe1.0.Iflessthan1.0,yourprocessisnotcapable.Itdoesnottakeintoaccountadistributiondeviatingfromcenterspecification.

Cpk istheshort/termlimiteddatacapabilityofyourproductorprocess.Itdoestakeintoconsiderationanydeviationfromcenter.Cpk’s barelycapablehaveavalueof1.0.Ifaprocessorproductislessthan1.0,itisconsiderednotcapable.

Pp isthelongtermprocessperformanceindicator.Itistheratioofyourlongtermprocessvariationdividedbythewidthofyourspecification.Itdoesnotconsiderdeviationfromthecenterofthespecification

Ppk isthelongtermcapabilityofyourproductorprocess.Itdoestakeintoconsiderationanydeviationfromcenter.Ppks barelycapablehaveavalueof1.0.Ifaprocessorproductislessthan1.0,itisconsiderednotcapable.

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ Relationships§ Scatterplots§ Boxplots§ Paretocharts§ Piecharts

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ScatterPlots- ThedataisdisplayedasacollectionofpointsonanXYchart.Eachhasthevalueofonevariabledeterminingthepositiononthehorizontalaxisandthevalueoftheothervariabledeterminingthepositionontheverticalaxis.ThedisplayenablesanunderstandingoftherelationshipbetweentheXandYvariableinadditiontothestrengthofthatsignal.

BoxPlots- isastandardizedwayofdisplayingthedistributionofdatabasedonthefivenumbersummary:minimum,firstquartile,median,thirdquartile,andmaximum.Itisaconvenienttooltodisplaythespreadandshapeofadistribution.

ParetoCharts- atypeofchartthatcontainsbothbarsandalinegraph,whereindividualvaluesarerepresentedindescendingorderbybars,andthecumulativetotalisrepresentedbytheline.Thischartisveryeffectiveinidentifyingthetopcontributorstoaconditions.RemembertheParetoprinciple:“80percentoftheproblemscomefrom20percentofthesources”

PieCharts- aconvenientchartwhichclearlydemonstratestheproportionofsourcesrelativetoasignal.

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R O O T C A U S E A N A L Y S I S & S T A T I S T I C A L T O O L S

§ Relationships§ XYdiagram§ Correlation§ Regression§ Hypothesistesting§ ANOVA

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XYdiagram- Thisisaveryusefuldiagramdemonstratingtherelationshipofaninput(theXaxis)toanoutput(theYaxis)

Correlation- isameasureofthedegreeofassociationbetweentwoquantitativevariables.Thevaluerangesfrom1(averystrongpositiverelationship,0(norelationship),to-1(averystrongnegativecorrelation)Thisisveryusefulindeterminingifchangeswithparticularvariablepotentiallyinfluences,causeschanges(oristheacorrelation?)withanothervariable.

Regression allowsyoutoquantifytherelationshipbetweenoneormany“input”variablesagainstanother“output”variable.ThestrengthofthatrelationshipismeasuredbyatermknownasR-squared.ThevalueofR-square(describedasafractionorapercentage)istheestimateoftherelationshipthatcanbeexplainedbythemathematicalmodel/regression.ForexampleifaregressioniscalculatedandcomesupwithanR-squaredvalueof.89or89%,thenyouwouldsaythatthe89%ofthechangesinoutputvariableYcanbeexplainedbytheassociatedinputvariablesinthemodel.Regressionequationsareveryhelpfulinmaking“output”estimatesusingdifferentvaluesofpotential“input”settings.

Hypothesistesting- isapowerfultoolusedininferentialstatisticsordecisionmaking.Itisusedtoprojectaninferencewithacertainprobability,therelationshipoftwosamplesorpopulations.Forexample,afinalstatementwouldbe“with95%confidence,wecanstatethatthereappearstobenosignificantstatisticaldifferencebetweenthetwosamples”Note:Itdoesnotsaythattheyarethesame,itjustsaysthatthereisarelativeconfidenceinsayingwedon’tseeasignal.

ANOVA- isananalysissimilartoaHypothesistesthoweverwithanANOVA,youaremakinganinferencecomparingmultiplesamplesorpopulation.Ultimately,youwillbeabletoinfer:“with95%confidence,wecannotstatethatallofthesesamplesisstatisticallyequaltotheothers”(oneormoreislikelydifferent)

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Q U E S T I O N S

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T H A N K Y O U !

F o r m o r e i n f o r m a t i o n a n d t o …

D O W N L O A D W H I T E P A P E R S A N D C A S E S T U D I E S

S U B S C R I B E T O R & Q ’ S B L O G

B E G I N A C O N V E R S A T I O N

v i s i t

f a c e b o o k . c o m / r a n d q

t w i t t e r . c o m / R Q E x p e r t s

l n k e d . i n / r q t e a m

i n s t a g r a m . c o m / r q c a r e e r s


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