Statistical Methods for Hospital Monitoring with R

428 Pages·2013·3.395 MB·English

by  Anthony Morton, Kerrie L. Mengersen, Geoffrey Playford, Michael Whitby

Statistical Methods for
Hospital Monitoring with R
STATISTICSINPRACTICE
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CRP-Sante´,Luxembourg
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UniversityofGlasgow,UK
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UniversityofMaryland,USA
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NottinghamTrentUniversity,UK
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Statistical Methods for
Hospital Monitoring with R
Anthony Morton
PrincessAlexandraHospital
Brisbane,Australia
Kerrie Mengersen
ScienceandEngineeringFaculty
QueenslandUniversityofTechnology
Brisbane,Australia
Michael Whitby
GreenslopesClinicalSchool
UniversityofQueensland
Brisbane,Australia
Geoffrey Playford
PrincessAlexandraHospital
Brisbane,Australia
Thiseditionfirstpublished2013
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LibraryofCongressCataloging-in-PublicationData
Morton,AnthonyPark,1933–author.
StatisticalmethodsforhospitalmonitoringwithR/AnthonyMorton,KerrieMengersen,GeoffreyPlayford,
MichaelWhitby.
p.;cm.
Includesbibliographicalreferencesandindex.
ISBN978-1-118-59630-2(cloth)
I.Mengersen,KerrieL.,author. II.Playford,Geoffrey,author. III.Whitby,Michael,1950–author. IV.Title.
[DNLM:1.HospitalAdministration. 2.StatisticsasTopic. WX150.1]
RA971
362.11068–dc23
2013008301
AcataloguerecordforthisbookisavailablefromtheBritishLibrary.
ISBN:978-1-118-59630-2
Setin10/12ptTimesbyAptaraInc.,NewDelhi,India.
1 2013
Contents
RLibraries x
RFunctions xi
Preface xvi
Introduction 1
0.1 Overviewandrationaleforthisbook 1
0.1.1 Motivationforthebook 1
0.1.2 WhyR? 2
0.1.3 OtherreadingforR 2
0.2 Whatmethodsarecoveredinthebook? 3
0.3 Structureofthebook 4
0.4 UsingR 5
0.4.1 Enteringdata 6
0.4.2 Dates 8
0.4.3 Exportingdata 10
0.5 Furthernotes 11
0.6 Abriefintroductiontorprogschartsandfigures 11
0.6.1 Whatifthereisnodatecolumn? 18
0.7 Appendixmenus 20
0.7.1 IMenu() 20
0.7.2 CCMenu() 21
1 Introductiontoanalysisofbinaryandproportiondata 24
1.1 Singleproportion,samplesandpopulation 24
1.1.1 Calculatingtheconfidenceinterval 26
1.1.2 Comparisonwithanexpectedrate 27
1.2 Likelihoodratio(Bayesfactor)&supportedrange 29
1.3 Confidenceintervalsforaseriesofproportions 30
1.4 Differencebetweentwoproportions 33
1.4.1 Confidenceintervals 33
1.4.2 Hypothesistest 35
1.4.3 Thetwoproportionsfunction 37
vi CONTENTS
1.5 IntroducingaBayesianapproach 39
1.6 Whenthedataarenotjustoneortwoindependentsamples 39
1.6.1 Morethantwoindependentproportions 40
1.6.2 Example1,yearlydata 40
1.6.3 Example2,hospitaldata 43
1.6.4 Proptestandsmallsamples 47
1.7 Summarisingstratifiedproportiondata 48
1.8 Stratifiedproportiondata,differencesbetweenrates 50
1.8.1 Yearlydata 52
1.8.2 Hospitaldata 54
1.9 Mantel-Haenszel,homogeneityandtrendtests 54
1.9.1 Yearlydata 56
1.9.2 Datastratifiedbyhospital 59
1.10 Stratifiedratesandoverdispersion 63
2 Theanalysisofaggregatedbinarydata 67
2.1 Risk-adjustment 68
2.1.1 Usingstratification 68
2.1.2 Usinglogisticregression 70
2.2 Discriminationandcalibration 71
2.3 Using2005–06data 76
2.3.1 Displayingandanalysingdatafrommultipleinstitutions 77
2.3.2 Tabulations 78
2.3.3 Funnelplotandplotofmultipleconfidenceintervals 83
2.4 WhentheEsarenotfixed 99
2.5 ComplexSurgicalSiteInfections 102
2.5.1 Funnelplotanalysis 102
2.5.2 Shrinkageanalysis 104
2.6 ComplexSSIrisk-adjustmentdiscrimination 106
2.7 Appendix1–Furthertabulationmethods 106
2.8 Appendix2–SMRCIsandtests,furtherscripts.Hospitalexpectedvalues
fromotherhospitalsingroup 109
3 Sequentialbinarydata 116
3.1 CUSUMandrelatedchartsforbinarydata 117
3.2 CumulativeObserved-Expected(O-E)chartandcombinedCUSUM
andO-Echart 120
3.3 CumulativefunnelplotandcombinedCUSUMandfunnelplot 120
3.4 Example 121
3.5 Includingriskadjustment 124
3.6 CUSUMchart 125
3.7 Cumulativeobservedminusexpected(O-E)chart 125
3.8 Funnelplot 127
3.9 Discriminationandcalibrationofriskadjustment 128
3.10 ShewhartPchartandEWMAchart 132
3.11 NoteontheRun-sumchart 135
3.12 TheEWMAchart 135
3.13 Plottingtheexpectedvalues 138
CONTENTS vii
3.14 Usingasplineorgeneralisedadditivemodel(GAM)chart 139
3.15 Whentherearefewtimeperiods 141
3.16 Chartsforquarterlydataanddatawithoutafirstdatecolumn 143
3.17 Chartsforcompositemeasures 146
3.18 Additionaltabulations 146
3.19 Theissueofunder-reporting 151
3.20 NewCUSUMandEWMAcharts,low-ratedata 151
3.20.1 Therisk-adjustedBernoulliCUSUM 153
3.20.2 TheEWMA 156
3.20.3 Quarterlyrates 157
3.21 Intervalsbetweenuncommonbinaryadverseevents 159
3.22 Appendix,proposedEWMAforlowratedata 164
4 Introductiontoanalysisofcountandratedata 168
4.1 Introduction 168
4.2 Rateandcountdata 169
4.3 Singlecountorrate 169
4.3.1 Confidenceinterval 170
4.3.2 Significancetest 171
4.4 Confidencelimitsforcolumnsofcountsandrates 173
4.5 Twoindependentrates 175
4.5.1 Confidenceinterval 175
4.5.2 Hypothesistest 176
4.5.3 Bayesianapproach 177
4.6 Chi-squaredandtrendtestsforcountandratedata 177
4.7 Stratifiedcountandratedata 180
4.7.1 Obtainingasummaryrate 180
4.7.2 Stratifiedcountandratedata,twosetsofrates 181
4.7.3 Indirectstandardisation 182
4.7.4 Directstandardisation 184
4.8 Mantel-Haenszel,homogeneityandtrendtests 187
4.8.1 Fixedeffectsanalysis,stratificationbyyears 187
4.8.2 Randomeffectsanalysis,stratificationbyhospitals 190
4.9 Illustrationofdealingwithoverdispersedrates 193
4.10 Theimportanceofcountdatavariation 196
4.11 Complexsystems,networksandvariation 201
5 Tablesandchartsforaggregatedcountdata 203
5.1 Introduction,data,limitationsofaggregatedcountdataanalysis 203
5.2 ConfidenceintervalsforStaphylococcusaureusbacteraemiaSMRdata 206
5.3 FunnelplotsforStaphylococcusaureusbacteraemiaSMRdata 212
5.4 TabulationsandZ-scores 219
5.5 Moreonoverdispersion,falsediscovery,verysmallexpectedcounts 221
5.5.1 ProposalforBenjamini-Hochbergmodifiedfunnelplot 223
5.6 Bayesianshrinkageplot 227
5.6.1 UsingOpenBUGS 228
5.6.2 UsingempiricalBayesmethods 229
5.7 PerformingfurthertabulationsinR 231
viii CONTENTS
5.8 AdjustinghospitallevelsforMRSAbacteraemia 234
5.9 Bacteraemiariskadjustment 237
6 Sequentialcountandratedata 242
6.1 Groupingdata 243
6.2 Meansandvariances,predictability 243
6.3 Tabulations 244
6.4 Denominators 246
6.5 Shewhart,EWMAandGAMcontrolchartswithoutdenominators 247
6.5.1 Shewhart/EWMAcharts 257
6.6 Shewhart,EWMAandGAMcontrolchartswithdenominators 264
6.6.1 Overdisperseddata 273
6.7 Chartsforquarterlydataanddatawithoutafirstdatecolumn 280
6.8 Whentherearefewtimeperiods 282
6.9 Cross-tabulationinwideformat 286
6.10 UncommoncountdataAEs 291
6.11 Additionalscriptsfortabulationsandcharts 297
6.12 Intervalsbetweenuncommoncountdataevents 300
6.13 Noteoncalculationofnegativebinomialparametersforcontrolcharts
whendenominatorsvary 303
6.13.1 Simpleweightedvariance 303
6.13.2 Linearapproximation(Bissell) 303
6.13.3 ComparisonofsimpleweightedvarianceandBissell’slinear
approximation 304
7 MiscellaneousAEs 307
7.1 MROprevalence 308
7.2 Antibioticusage 315
7.3 Spuriousproportions,somebloodculturedata 316
7.4 RIDITcharts,ECGdata 321
7.5 Numericaldata–theatreutilisation 326
7.6 Lengthofstay(LOS)data 329
7.7 Changepoint 339
7.8 Assessingagreement 346
7.8.1 Numericaldataagreement 348
7.9 Makingdecisions(decisionanalysis) 350
7.10 Investigatingoutbreaks,furtheranalysisofstratifieddata 352
7.10.1 Reviewingstratifieddataanalysis 355
7.10.2 Outbreakinvestigationexample 361
8 Hospitalsafetyandadverseeventprevention 374
8.1 Introduction 374
8.2 Anoverviewofhospitalqualityimprovement,fivepillars 375
8.2.1 TheCustomer,thefirstpillar 375
8.2.2 ThePractitioner,thesecondpillar 375
8.2.3 TheSystem,thethirdandmainpillar 375
CONTENTS ix
8.3 Medicalerror 376
8.3.1 Backgroundofmedicalerror(Vincent,Taylor-Adams&
Vincent) 376
8.4 Improvingthesystem 377
8.4.1 Evidence-basedsystems 377
8.4.2 Theroleofbundlesandchecklists 377
8.5 Error-proofingsystems 379
8.6 Disciplineandaccountability 379
8.7 Limitationsofimposingquality 380
8.8 Performanceandpredictablevariation 380
8.9 Thekeystoagoodsystem 381
8.10 Analysingandimplementingevidence-basedsystems 381
8.11 Theroleofpatient-carestaff 382
8.12 Theroleofcentralauthority 382
8.13 Changemanagement,thefourthpillar 383
8.14 Feedbackloops,thefifthpillar 383
8.15 ImplementationoftheQualityImprovementProcess 384
8.15.1 Implementation 384
8.15.2 Obtainingdata 386
8.15.3 SpecialissueswithQIstudies 386
8.16 Thehospitalasanetwork 389
References 391
Index 399
R Libraries
arm gee PropCIs
bmem geepack psy
chron hglm qAnalyst
Epi Kendall qcc
epibasix lme4 rmeta
epicalc MASS spc
epiR meta splines
epitools mgcv surveillance
exactci MKmisc tseries