![Week 3: Lab
statistics multi-part question and need an explanation and answer to help me learn.
Part 1:
Your instructor will provide you with a scholarly article. The article will contain at least one
graph and/or table. Please reach out to your instructor if you do not receive the article by
Monday of Week 3.
Part 2:
Title your paper: “Review of [Name of Article]”
State the Author:
Summarize the article in one paragraph:
Post a screenshot of the article's frequency table and/or graph.
Example:
Frequency Distribution -OR- Graph
Answer the following questions about your table or graph.
What type of study is used in the article (quantitative or qualitative)?
Explain how you came to that conclusion.
What type of graph or table did you choose for your lab (bar graph, histogram, stem & leaf
plot, etc.)?
What characteristics make it this type (you should bring in material that you learned in the
course)?
Describe the data displayed in your frequency distribution or graph (consider class size,
class width, total frequency, list of frequencies, class consistency, explanatory variables,
response variables, shapes of distributions, etc.)
Draw a conclusion about the data from the graph or frequency distribution in the context of
the article.
How else might this data have been displayed?
Discuss the pros and cons of 2 other presentation options, such as tables or different
graphical displays.
Why do you think those two other presentation options (i.e., tables or different graphs)
were not used in this article?
Give the full APA reference of the article you are using for this lab.
Be sure your name is on the Word document, save it, and then submit it under
"Assignments" and "Week 3: Lab".](https://image.slidesharecdn.com/weeklab-230314043558-0042f292/85/Week-Lab-pdf-1-320.jpg)
![Week 3 Lab Assignment
Name:________________________ Instructor Name: _______________
Please use this template to help answer the questions listed in the lab instructions. The
“parts” below refer to the parts listed in the lab instructions. Type your answers and post
your screenshots in the spaces given below. Then, save this document with your name and
submit it inside the course room.
Part 1. Read the assigned article.
Please reach out to your instructor if you did not receive the assigned article for the term by
Monday of Week 3.
Part 2. Analyze the article.
Title: Review of [Type out name of Article]
Author(s): [Type out names of Author(s) of the Article]
Summarize the article in one paragraph:
Post a screenshot of a graph/chart from the article that you will analyze:
Analysis
(Answer the following questions thoroughly in complete sentences)
What type of study is used in the article (quantitative or qualitative)? Explain how you came
to that conclusion.
What type of graph or table did you choose for your lab (bar graph, histogram, stem & leaf
plot, etc.)? What characteristics make it this type (you should bring in material that you
learned in the course)?
Describe the data displayed in your frequency distribution or graph (consider class size,
class width, total frequency, list of frequencies, class consistency, explanatory variables,
response variables, shapes of distributions, etc.)
Draw a conclusion about the data from the graph or frequency distribution in context of the
article.
How else might this data have been displayed (Pick two different graphs that could have
been used to display the same data as your selected graph/table)?
Discuss pros and cons of 2 other presentation options, such as tables or different graphical
displays.
Explain how these graphs would be structured to display the data in the article. Why don’t
you think those two graphs were not used in this article?
Give the full APA reference of the article you are using for this lab.
Be sure your name is on the Word document, save it, and then submit it. In the assignment
module, click “start assignment” and then “upload file” and “submit assignment”.
EvidenceRelatingHealthCareProviderBurnoutandQualityofCareASystematicReviewandMeta
-
analysisDanielS.Tawfik,MD,MS;AnnetteScheid,MD;JochenProfit,MD,MPH;TaitShanafelt,MD;
MickeyTrockel,MD,PhD;KathrynC.Adair,PhD;J.BryanSexton,PhD;andJohnP.A.Ioannidis,MD,D
ScBackground:Whetherhealthcareproviderburnoutcontrib-
utestolowerqualityofpatientcareisunclear.Purpose:Toestimatetheoverallrelationshipbetwee](https://image.slidesharecdn.com/weeklab-230314043558-0042f292/85/Week-Lab-pdf-2-320.jpg)
![rex-cesssignificance(33)byidentifyingthestudypopula-
tionwiththehighestprecision(1/SE)amongthosewiththelowestriskofbias(studiesusingafully
validatedburnoutinventorywithanobjectivequalitymetric).Wethencalculatedthepowerofalls
tudiestodetecttheeffectsizeofthisstudyandcomparedtheobservedversusexpectednumberofst
udieswithstatisticallysig-nificantresultsbyusingpairedttests.Next,westrati-
fiedexcesssignificancetestingbyoutcomecategory.Becausesmallstudiesmaycarryincreasedris
kofbias,weperformedtheEggertesttolookforsmall-
studyeffects(34).Weregressedstandardnormaldevi-
ate(Hedgesg/SE)onprecision(1/SE)byusingrobustSEsduetoclusteringofeffectsizesatthestud
ypopu-lationlevel.WeusedStata15.0(StataCorp)forallanalyses.Alltestswere2-
sided.Forsummaryeffects,weconsidered2differentthresholdsofstatisticalsignificance,P<0.05
0andthenewlyproposedP<0.005(35,36).Wemadenofurthercorrectionsformultipletesting.Th
isstudywasperformedinaccordancewiththeinstitutionalreviewboardrequirementsofStanfor
dUniversityandwasclassifiedasresearchnotinvolvinghumansubjects.RoleoftheFundingSourc
eThefundershadnoroleinstudydesign,datacol-
lection,analysis,interpretation,orwritingofthereport.Figure1.Evidencesearchandselection.Ar
ticles identified in MEDLINEand PsyclNFO (n = 6715)Articles identified in Web ofScience (n
= 3116)Articles identified inEMBASE (n = 3871)Duplicate publications (n =
1999)Titles/abstracts screened (n = 11 703)Not relevant (n = 11 390)Selected for full-text
review (n = 313)Bibliographic reviews (n = 3)Included in final analysis (n = 123)Excluded
(n = 193) No burnout predictor: 123 No quality outcome: 46 Review/repeat population:
16 Not quantitative: 7 Not health care providers:
1BurnoutandQualityofCareREVIEWAnnals.orgAnnalsofInternalMedicine•Vol.171No.8•15Oc
tober2019557
RESULTSThesearchidentified11703citations.Screeningresultedin313potentiallyeligiblepubl
icationsre-trievedinfulltext—120ofwhichwereincluded—
plus3additionalpublicationsidentifiedbybibliographyre-
view(Figure1).Overall,weincluded123publicationsfrom1994through2019(37–
159),encompassing142distinctstudypopulations,asdetailedinSupplementTable4(availableat
Annals.org).Themediansamplesizewas376(interquartilerange,129to1417).The142studypop
ulationsincludedphysicians(n=71[50%]),nurses(n=84[59%]),andotherproviders(n=18[13
%])foratotalof241553healthcareproviderseval-
uated.Qualitymetricscoveredinpatients(n=122[86%]);outpatients(n=62[44%]);andadult(n
=134[94%]),pediatric(n=93[65%]),medical(n=135[95%]),andsurgical(n=89[63%])patients
.Only4studiesexplicitlyspecifiedaprimaryoutcome.Sixstud-
iesdidnotprovidesufficientdatatoderiveaneffectsizefromtheoriginalpublicationbutprovided
usableFigure2.Summaryofallincludedburnout–
qualitymetriccombinations,showingfrequencyofeffectsizereporting(count)andvalueofsumm
aryeffectsize(Hedgesg).Burnout MetricBurnoutEmotional exhaustionDepersonalizationLow
personal accomplishmentBurnoutEmotional exhaustionDepersonalizationLow personal
accomplishmentQuality MetricQuality and safetyOutcomesErrorsCommunicationBest
practices302515Count1075312.01.51.00.5–0.5–1.0–2.0–1.50Hedges g20Inappropriate
laboratory testsInappropriate timing of dischargeSuboptimal patient care](https://image.slidesharecdn.com/weeklab-230314043558-0042f292/85/Week-Lab-pdf-7-320.jpg)
![P<0.050threshold.WhentheP<0.005thresholdwasused,therespectivenumberswere18(39%),
1(2%),and27(59%).Resultsaresum-
marizedinTable1,andprimaryeffectsizesfromallincludedstudiesareshowninSupplementFigu
re2(availableatAnnals.org).Resultsweresimilarwhensecondaryeffectsizeswereincluded.Ofth
e114distinctburnout–qualitymet-
riccombinations,58(51%)hadstatisticallysignificantsummaryeffectsgreaterthan0,6(5%)had
statisticallysignificanteffectslessthan0,and50(44%)showednodifferenceattheP<0.050thresh
old.WhentheP<0.005thresholdwasused,therespectivenumberswere47(41%),6(5%),and61(
54%).Resultsfromallburnout–qualitymetriccombinationsareshowninSup-
plementFigure3(availableatAnnals.org).Ourfindingsweresimilarwhenlimitedtostudiesexplic
itlyusingstandardburnoutdefinitions,buttheobservedrela-
tionshipswereattenuatedwhenlimitedtoindepen-
dentorobjectivequalitymetrics,asshowninTable1.Themostprecisestudywithlowriskofbias(1
43)reportedasmalleffectsize(Hedgesg=0.26,analo-
goustoanoddsratioof1.5to1.6).Usingthisestimate,theIoannidistestfoundanexcessofobserved
versuspredictedstatisticallysignificantstudies(73%observedvs.62%predictedatthe0.050sig
nificancethreshold,P=0.011)(Table2).Whenstratifiedbyqualitymetriccategory,anexcessofsta
tisticallysignificantstudieswasseeninthecategoriesofbestpracticesandqualityandsafety.Resul
tsweresimilarfortheP<0.005threshold.TheEggertestdidnotshowsmall-studyeffects(inter-
cept,1.32[95%CI,3.48to0.85]),indicatingthatsmallerstudiesdidnotsystematicallyoverestimat
eeffectsizes(Figure3).AfunnelplotrelatingeffectsizetoSEisshowninSupplementFigure4(avail
ableatAnnals.org).DISCUSSIONThisoverviewextendspreviousworkinthefieldbyincludingaco
mprehensiveevaluationforreportingbi-asesinthehealthcareproviderburnoutliterature,en-
compassing145publishedstudypopulationsthatquantifiedtherelationbetweenburnoutandqu
alityofcareover25yearsfor241553healthcareprofession-
als.Mostoftheevidencesuggestsarelationshipbe-
tweenproviderburnoutandimpairedqualityofcare,consistentwithrecentreviewsofvariousdi
mensions(7–10,22).Althoughtheeffectsizesinthepublishedliter-
aturearemodestlystrong,ourfindingofexcesssignif-
icanceimpliesthatthetruemagnitudemaybesmallerthanreported,andthestudiesthatattempte
dtolowertheriskofbiasdemonstratefewersignificantassocia-
tionsthanthefullevidencebase.Thatonly4studiesTable1.NumberandDirectionofSummaryEffe
ctSizesforEachCombinationofBurnoutandQualityMetric*CriteriaforInclusionBurnout–
QualityCombinations,n†P<0.050Threshold,n(%)P<0.005Threshold,n(%)Hedgesg>0‡Hedge
sg<0§NoEffectHedgesg>0‡Hedgesg<0§NoEffectPrimaryeffectsonly4624(52)1(2)21(46)18(
39)1(2)27(59)Primaryandsecondaryeffects11458(51)6(5)50(44)47(41)6(5)61(54)Standa
rdburnoutdefinitions2415(62)1(4)8(33)14(58)1(4)9(38)Independent/objectivequalitymet
rics4814(29)2(4)32(67)9(19)2(4)37(77)*SummaryeffectsizesobtainedviaempiricalBayesm
eta-analysis.†Numberofdistinctburnout–
qualitycombinationsrepresented.‡Indicatesburnoutrelatedtopoor-
qualitycare.§Indicatesburnoutrelatedtohigh-
qualitycare.Notsignificantlydifferentfrom0atthespecifiedPvaluethreshold.BurnoutandQualit
yofCareREVIEWAnnals.orgAnnalsofInternalMedicine•Vol.171No.8•15October2019559](https://image.slidesharecdn.com/weeklab-230314043558-0042f292/85/Week-Lab-pdf-9-320.jpg)
![gorousstud-iesexist,andtheeffectsizemaybesmallerthanreport-ed—
andmaybeparticularlysmallerforobjectivequalitymeasures.Whethercurtailingburnoutimpro
vesqualityofcare,orwhetherimprovingqualityofcarereducesburnout,isnotyetknown,andadeq
uatelypoweredanddesignedrandomizedtrials(91,166,167)willbeindispensableinansweringt
hesequestions.FromStanfordUniversitySchoolofMedicine,Stanford,Cali-
fornia(D.S.T.,T.S.,M.T.);BrighamandWomen'sHospitalandHarvardMedicalSchool,Boston,Mas
sachusetts(A.S.);Stan-
fordUniversitySchoolofMedicine,Stanford,California,andCaliforniaPerinatalQualityCareColla
borative,PaloAlto,Cal-ifornia(J.P.);DukeUniversitySchoolofMedicine,DukeUni-
versityHealthSystem,andDukePatientSafetyCenter,Dur-
ham,NorthCarolina(K.C.A.,J.B.S.);andStanfordUniversitySchoolofMedicine,StanfordUniversit
ySchoolofHumanitiesandSciences,andMeta-ResearchInnovationCenteratStan-
ford(METRICS),Stanford,California(J.P.I.).Note:Theleadauthorhadfullaccesstoalldatainthestu
dyandaffirmsthatthemanuscriptisanhonest,accurate,andtransparentaccountofthestudy;that
noimportantaspectsofthestudyhavebeenomitted;andthatanydiscrepanciesfromthestudyaso
riginallyplannedhavebeenexplained.FinancialSupport:BytheStanfordMaternalandChildHealt
hResearchInstitute.Disclosures:Dr.TawfikreportsgrantsfromStanfordMaternalandChildHeal
thResearchInstituteduringtheconductofthestudy.Dr.ProfitreportsgrantsfromtheEuniceKenn
edyShriverNationalInstituteofChildHealthandHumanDevelop-
mentduringtheconductofthestudyandhasreceivedhon-
orariaforspeakingatscientificmeetingsonthetopicofburn-
out.Dr.SextonreportsgrantsfromtheNationalInstitutesofHealthduringtheconductofthestudy.
Authorsnotnamedherehavedisclosednoconflictsofinterest.Disclosurescanalsobeviewedatw
ww.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M19-
1152.ReproducibleResearchStatement:Studyprotocol,statisticalcode,anddataset:Availablefr
omDr.Tawfik(e-
mail,dtawfik@stanford.edu).CorrespondingAuthor:DanielS.Tawfik,MD,MS,770WelchRoad,S
uite435,PaloAlto,CA94304;e-
mail,dtawfik@stanford.edu.Currentauthoraddressesandauthorcontributionsareavail-
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STheAnnalsInformationforAuthorssectionisavailableatwww.annals.org/aim/pages/authors
.Allmanuscriptsmustbesubmittedelectronicallyus-
ingthemanuscriptsubmissionoptionatAnnals.org.BurnoutandQualityofCareREVIEWAnnals.o
rgAnnalsofInternalMedicine•Vol.171No.8•15October2019567
CurrentAuthorAddresses:Dr.Tawfik:770WelchRoad,Suite435,PaloAlto,CA94304.Dr.Scheid:O
fficeBL341G,221LongwoodAvenue,Boston,MA02115.Dr.Profit:1265WelchRoad,MSOBx1C07
,Stanford,CA94305.Dr.Shanafelt:300PasteurDrive,RoomH3215,Stanford,CA94305.Dr.Trocke
l:401QuarryRoad,Room2303,Stanford,CA94305.Drs.AdairandSexton:3100TowerBoulevard,
Suite300,Dur-
ham,NC27707.Dr.Ioannidis:1265WelchRoad,MSOBx306,Stanford,CA94305.AuthorContribut
ions:Conceptionanddesign:D.S.Tawfik,J.P.A.Ioannidis.Analysisandinterpretationofthedata:D.
S.Tawfik,J.Profit,T.Shanafelt.Draftingofthearticle:D.S.Tawfik,T.Shanafelt,J.P.A.Ioannidis.Critic
alrevisionforimportantintellectualcontent:D.S.Tawfik,A.Scheid,T.Shanafelt,M.Trockel,J.B.Sex
ton,J.P.A.Ioannidis.Finalapprovalofthearticle:D.S.Tawfik,A.Scheid,J.Profit,T.Shanafelt,M.Troc
kel,K.C.Adair,J.B.Sexton,J.P.A.Ioannidis.Provisionofstudymaterialsorpatients:D.S.Tawfik.Stati
sticalexpertise:D.S.Tawfik.Obtainingoffunding:D.S.Tawfik.Administrative,technical,orlogistic
support:D.S.Tawfik,A.Scheid,J.B.Sexton.Collectionandassemblyofdata:D.S.Tawfik,A.Scheid,K.
C.Adair.Annals.orgAnnalsofInternalMedicine•Vol.171No.8•15October2019
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Week Lab.pdf
- 1. Week 3: Lab statistics multi-part question and need an explanation and answer to help me learn. Part 1: Your instructor will provide you with a scholarly article. The article will contain at least one graph and/or table. Please reach out to your instructor if you do not receive the article by Monday of Week 3. Part 2: Title your paper: “Review of [Name of Article]” State the Author: Summarize the article in one paragraph: Post a screenshot of the article's frequency table and/or graph. Example: Frequency Distribution -OR- Graph Answer the following questions about your table or graph. What type of study is used in the article (quantitative or qualitative)? Explain how you came to that conclusion. What type of graph or table did you choose for your lab (bar graph, histogram, stem & leaf plot, etc.)? What characteristics make it this type (you should bring in material that you learned in the course)? Describe the data displayed in your frequency distribution or graph (consider class size, class width, total frequency, list of frequencies, class consistency, explanatory variables, response variables, shapes of distributions, etc.) Draw a conclusion about the data from the graph or frequency distribution in the context of the article. How else might this data have been displayed? Discuss the pros and cons of 2 other presentation options, such as tables or different graphical displays. Why do you think those two other presentation options (i.e., tables or different graphs) were not used in this article? Give the full APA reference of the article you are using for this lab. Be sure your name is on the Word document, save it, and then submit it under "Assignments" and "Week 3: Lab".
- 2. Week 3 Lab Assignment Name:________________________ Instructor Name: _______________ Please use this template to help answer the questions listed in the lab instructions. The “parts” below refer to the parts listed in the lab instructions. Type your answers and post your screenshots in the spaces given below. Then, save this document with your name and submit it inside the course room. Part 1. Read the assigned article. Please reach out to your instructor if you did not receive the assigned article for the term by Monday of Week 3. Part 2. Analyze the article. Title: Review of [Type out name of Article] Author(s): [Type out names of Author(s) of the Article] Summarize the article in one paragraph: Post a screenshot of a graph/chart from the article that you will analyze: Analysis (Answer the following questions thoroughly in complete sentences) What type of study is used in the article (quantitative or qualitative)? Explain how you came to that conclusion. What type of graph or table did you choose for your lab (bar graph, histogram, stem & leaf plot, etc.)? What characteristics make it this type (you should bring in material that you learned in the course)? Describe the data displayed in your frequency distribution or graph (consider class size, class width, total frequency, list of frequencies, class consistency, explanatory variables, response variables, shapes of distributions, etc.) Draw a conclusion about the data from the graph or frequency distribution in context of the article. How else might this data have been displayed (Pick two different graphs that could have been used to display the same data as your selected graph/table)? Discuss pros and cons of 2 other presentation options, such as tables or different graphical displays. Explain how these graphs would be structured to display the data in the article. Why don’t you think those two graphs were not used in this article? Give the full APA reference of the article you are using for this lab. Be sure your name is on the Word document, save it, and then submit it. In the assignment module, click “start assignment” and then “upload file” and “submit assignment”. EvidenceRelatingHealthCareProviderBurnoutandQualityofCareASystematicReviewandMeta - analysisDanielS.Tawfik,MD,MS;AnnetteScheid,MD;JochenProfit,MD,MPH;TaitShanafelt,MD; MickeyTrockel,MD,PhD;KathrynC.Adair,PhD;J.BryanSexton,PhD;andJohnP.A.Ioannidis,MD,D ScBackground:Whetherhealthcareproviderburnoutcontrib- utestolowerqualityofpatientcareisunclear.Purpose:Toestimatetheoverallrelationshipbetwee
- 7. rex-cesssignificance(33)byidentifyingthestudypopula- tionwiththehighestprecision(1/SE)amongthosewiththelowestriskofbias(studiesusingafully validatedburnoutinventorywithanobjectivequalitymetric).Wethencalculatedthepowerofalls tudiestodetecttheeffectsizeofthisstudyandcomparedtheobservedversusexpectednumberofst udieswithstatisticallysig-nificantresultsbyusingpairedttests.Next,westrati- fiedexcesssignificancetestingbyoutcomecategory.Becausesmallstudiesmaycarryincreasedris kofbias,weperformedtheEggertesttolookforsmall- studyeffects(34).Weregressedstandardnormaldevi- ate(Hedgesg/SE)onprecision(1/SE)byusingrobustSEsduetoclusteringofeffectsizesatthestud ypopu-lationlevel.WeusedStata15.0(StataCorp)forallanalyses.Alltestswere2- sided.Forsummaryeffects,weconsidered2differentthresholdsofstatisticalsignificance,P<0.05 0andthenewlyproposedP<0.005(35,36).Wemadenofurthercorrectionsformultipletesting.Th isstudywasperformedinaccordancewiththeinstitutionalreviewboardrequirementsofStanfor dUniversityandwasclassifiedasresearchnotinvolvinghumansubjects.RoleoftheFundingSourc eThefundershadnoroleinstudydesign,datacol- lection,analysis,interpretation,orwritingofthereport.Figure1.Evidencesearchandselection.Ar ticles identified in MEDLINEand PsyclNFO (n = 6715)Articles identified in Web ofScience (n = 3116)Articles identified inEMBASE (n = 3871)Duplicate publications (n = 1999)Titles/abstracts screened (n = 11 703)Not relevant (n = 11 390)Selected for full-text review (n = 313)Bibliographic reviews (n = 3)Included in final analysis (n = 123)Excluded (n = 193) No burnout predictor: 123 No quality outcome: 46 Review/repeat population: 16 Not quantitative: 7 Not health care providers: 1BurnoutandQualityofCareREVIEWAnnals.orgAnnalsofInternalMedicine•Vol.171No.8•15Oc tober2019557 RESULTSThesearchidentified11703citations.Screeningresultedin313potentiallyeligiblepubl icationsre-trievedinfulltext—120ofwhichwereincluded— plus3additionalpublicationsidentifiedbybibliographyre- view(Figure1).Overall,weincluded123publicationsfrom1994through2019(37– 159),encompassing142distinctstudypopulations,asdetailedinSupplementTable4(availableat Annals.org).Themediansamplesizewas376(interquartilerange,129to1417).The142studypop ulationsincludedphysicians(n=71[50%]),nurses(n=84[59%]),andotherproviders(n=18[13 %])foratotalof241553healthcareproviderseval- uated.Qualitymetricscoveredinpatients(n=122[86%]);outpatients(n=62[44%]);andadult(n =134[94%]),pediatric(n=93[65%]),medical(n=135[95%]),andsurgical(n=89[63%])patients .Only4studiesexplicitlyspecifiedaprimaryoutcome.Sixstud- iesdidnotprovidesufficientdatatoderiveaneffectsizefromtheoriginalpublicationbutprovided usableFigure2.Summaryofallincludedburnout– qualitymetriccombinations,showingfrequencyofeffectsizereporting(count)andvalueofsumm aryeffectsize(Hedgesg).Burnout MetricBurnoutEmotional exhaustionDepersonalizationLow personal accomplishmentBurnoutEmotional exhaustionDepersonalizationLow personal accomplishmentQuality MetricQuality and safetyOutcomesErrorsCommunicationBest practices302515Count1075312.01.51.00.5–0.5–1.0–2.0–1.50Hedges g20Inappropriate laboratory testsInappropriate timing of dischargeSuboptimal patient care
- 8. practicesInappropriate use of patient restraintsPoor adherence to infection controlInappropriate antibiotic prescribingLack of close monitoringLow best practice scoreNeglect of workPoor adherence to management guidelinesPoor communicationLow patient enablement scoreForgetting to convey informationLow attention to patient impactLow physcian empathy scoreNot fully discussing treatment optionsPoor handoff qualityShort consultation lengthSelf-reported medical errorsSelf-reported medication errorsSelf-reported treatment/medication errorsMedical error scoreObserved medical errorsAccident propensityDiagnosis delayDiagnostic errorsObserved medication errorsSelf- reported impairmentAdverse eventsHealth care–associated infectionsPatient fallsLength of stayUrinary tract infectionsMortalityPoor pain controlHIV viral load suppressionMorbidityPosthospitalization recovery timeLow quality of careLow patient safety scoreLow safety climate scoreLow quality during most recent shiftLow work unit safety gradePoor patient care quality scoreMalpractice allegationsLow individual safety gradeLow safety perceptionsNear-miss reportingProlonged emergency department visitREVIEWBurnoutandQualityofCare558AnnalsofInternalMedicine•Vol.171No.8•15Octob er2019Annals.org datapublishedinasubsequentreview(39,66,69,107,115,117).Oneresearchgroupreportedresu ltsfromasinglestudypopulationin2publications;thefirstpub- lishedeffectwasconsideredprimary,withresultsfromthelaterpublicationconsideredsecondar yeffects(112,160).Overallburnout,emotionalexhaustion,anddeper- sonalizationweretheprimarypredictorsfor56,75,and11studypopulations,respectively,froma varietyofsur- veyinstruments,asoutlinedinSupplementTable5(availableatAnnals.org).The50distinctqualit ymetricsincluded10bestpractices,8communication,10med- icalerrors,10patientoutcomes,and12qualityandsafetymeasures(26measuredproviderpercep tionofquality,15usedindependentorobjectivemeasuresofquality,and9includedbothtypesofas sessments).AsillustratedinFigure2,38(33%)ofthe114dis-tinctburnout– qualitycombinationswerereported3ormoretimes.Themostfrequentlyreportedeffectre- latedemotionalexhaustiontolowqualityofcare(n=41),withmostofthereportedeffectsizesinthe qualityandsafetyandmedicalerrorscategories.Althoughall5categoriesofoutcomeshadestimat esmorefre- quentlyrelatingburnoutinthedirectionofpoorqualityofcare(denotedinredinFigure2),7ofthe1 6esti- matespointingintheoppositedirectionwerefoundinthecommunicationcategory.Resultsweres imilarwhenlimitedtoprimary(orfirst- listed,whenprimarywasnotspecified)effectsizesonly(SupplementFigure1,avail- ableatAnnals.org).Meta-analysescombiningburnoutandqualitymet- ricswithinqualitycategoriesrevealedI2valuesof93.4%to98.8%,indicatingextremelyhighheter ogene-ity;therefore,summaryeffectsareprovidedonlyatthelevelofthe114distinctburnout– qualitycombinations,46ofwhichincludedprimaryeffectsizes.Meta- analysesofthese46combinationsrevealed24(52%)withastatisticallysignificantsummaryeffec tgreaterthan0(burnoutrelatedtopoorqualityofcare),1(2%)withstatisticallysignificantsumma ryeffectslessthan0(burnoutrelatedtohighqualityofcare),and21(46%)withnodifferenceatthe
- 12. e.Rather,wereportfrequenciesofsignificantsummaryeffectsizeswithinburnout– qualitymetriccombinationstoprovideaquantitativeframeworkforinterpretationwhileacknow ledgingthatadistributionoftrueeffectsizesisexpectedinthisfield-wideassessment,incon- trasttoatraditionalmeta-analysis(163).Weavoidedscoringqualityassessmentsofthein- cludedstudies,choosinginsteadtoanalyzekeyaspectsofstudyquality,assuggestedbythepropos edreport-ingguidelinesformeta-analysesofobservationalstud- ies(16).Judgingthequalityofmostlycross- sectionalobservationalstudiesisnotoriouslydifficult,andnowidelyacceptedtoolsexist.Salyersa ndcolleagues(9)createda10-itemtooltoassessqualityaspectsin82burnoutandquality-of- carestudiesanddidnotidentifyanyrelationshipbetweenstudyqualityscoreandeffectsize.Ourfin dingscarryseveralimportantimplicationsforfutureinterventiontrialsandobservationalstudies .Forinterventiontrials,thepotentialforexaggeratedpublishedeffectsshouldbeconsideredinpo wercalcu-lationstolowertheriskforfalse- negativeresults(typeIIerror).Inaddition,futurestudiesshouldattempttore- ducetheriskofreportingbiases.Standardizationandconsensusoncoreoutcomesmaybeusefulfo rfuturestudiesifappropriatetargetscanbeidentified(164).Suchstandardizationmayimproveco mparabilityamongstudies,facilitatingtraditionalmeta-analysises- timatesoftherelevanteffectsizes.Someoutcomes,suchasself- reportedmedicalerrors,lowqualityofcare,andlowpatientsafetyscore,areparticularlyprev- alentintheliterature,suggestingthatresearchersal- readyconsidertheseoutcomeseitherimportantorfea- sibletomeasure.However,ifcoreoutcomesaretobewidelyaccepted,theymustbebothimportant andfea- sibletomeasure.Thus,inadditiontothis“popularvote”approach,expertconsensusisneededtocu rateanappropriatelistofcoreoutcomesforthisfield.Otheroutcomeevaluationsmightthenbedisc ouragedunlessauniquejustificationispresent.Studyregistrationmayfurtherreducetheriskofst udypublicationbiasandincreasetransparencyofun- publishedstudies.Byregisteringastudypubliclyatitsoutset,researcherscanreducethelikelihoo dthatastudywasconceivedandconductedbutremainsun- Figure3.Standardnormaldeviate(Hedgesg/SE)inrelationtoprecision(1/SE).Standard Normal DeviateRobustSEParameterEstimate–3.48 to 0.850.33 to 0.751.100.100.23<0.001– 1.320.54InterceptSlopeP Value95% CIPrecision95% CIFitted values002020– 20404060608080BurnoutandQualityofCareREVIEWAnnals.orgAnnalsofInternalMedicine•V ol.171No.8•15October2019561 publishedbecauseofundesirableorlacklusterresults(165).Inasimilarmanner,protocolprespec ificationmayreducetheriskforselectiveoutcomeandselectiveanalysisreportingwithinpublishe dstudies,allowingeasieridentificationofanyposthocanalyses.Publishedanalysesthatdeviatefr omtheprespecifiedprotocolwouldrequirejustificationfromtheauthors,andthisapproachwoul dalertthereadersthatthoseresultsmaybemoresusceptibletobias.Currently,thesemechanisms areusedrarelyinanyfieldofmedicineoutsideclinicaltrials,buttheycouldbecomewidelyad- optedwithsufficientadvocacybyresearchers,publish- ers,funders,andotherstakeholders.Inconclusion,burnoutamonghealthcareprovid- ersisfrequentlyassociatedwithreducedqualityofcareinthepublishedliterature.However,fewri