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http://www.diva-portal.org

This is the published version of a paper published in Primary Care Diabetes.

Citation for the original published paper (version of record):

Husdal, R., Thors Adolfsson, E., Leksell, J., Eliasson, B., Jansson, S. et al. (2019)

Associations between quality of work features in primary health care and glycaemic

control in people with Type 2 diabetes mellitus: a nationwide survey

Primary Care Diabetes, 13(2): 176-186

https://doi.org/10.1016/j.pcd.2018.11.005

Access to the published version may require subscription.

N.B. When citing this work, cite the original published paper.

Permanent link to this version:

(2)

primary care diabetes 13 (2019)176–186

ContentslistsavailableatScienceDirect

Primary

Care

Diabetes

journal homepage:http://www.elsevier.com/locate/pcd

Original

research

Associations

between

quality

of

work

features

in

primary

health

care

and

glycaemic

control

in

people

with

Type

2

diabetes

mellitus:

A

nationwide

survey

Rebecka

Husdal

a,b,

,

Eva

Thors

Adolfsson

a

,

Janeth

Leksell

b,c

,

Björn

Eliasson

d

,

Stefan

Jansson

e

,

Lars

Jerdén

c,f

,

Jan

Stålhammar

g

,

Lars

Steen

h

,

Thorne

Wallman

g,i

,

Ann-Marie

Svensson

j

,

Andreas

Rosenblad

a

aCentreforClinicalResearchVästmanland,UppsalaUniversity,Västerås,Sweden

bDepartmentofMedicalSciences,ClinicalDiabetologyandMetabolism,UppsalaUniversity,Uppsala,Sweden cSchoolofEducation,HealthandSocialStudies,DalarnaUniversity,Falun,Sweden

dDepartmentofMedicine,SahlgrenskaUniversityHospital,Gothenburg,Sweden

eSchoolofMedicalSciences,UniversityHealthCareResearchCentre,ÖrebroUniversity,Örebro,Sweden fCentreforClinicalResearchDalarna,UppsalaUniversity,Falun,Sweden

gDepartmentofPublicHealthandCaringSciences,FamilyMedicineandPreventiveMedicineSection,Uppsala

University,Uppsala,Sweden

hDrugandTherapeuticsCommittee,SörmlandCountyCouncil,Eskilstuna,Sweden iCentreforClinicalResearchSörmland,UppsalaUniversity,Eskilstuna,Sweden jNationalDiabetesRegister,CentreofRegisters,Gothenburg,Sweden

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received23August2018

Receivedinrevisedform

2November2018

Accepted15November2018

Availableonline10December2018

Keywords:

Diabetesmellitus

Type2

a

b

s

t

r

a

c

t

Aims: To describe and analyse the associations betweenprimary health care centres’

(PHCCs’)qualityofwork(QOW)andindividualHbA1clevelsinpeoplewithType2diabetes

mellitus(T2DM).

Methods:Thiscross-sectionalstudyinvitedall1152SwedishPHCCstoanswera

question-naireaddressingQOWconditions.Clinical,socio-economicandcomorbiditydatafor230,958

peoplewithT2DMwerelinkedtodataonQOWconditionsfor846(73.4%)PHCCs.

Results: Of the participants, 56% had controlled (≤52mmol/mol), 31.9% intermediate

(53–69mmol/mol),and12.1%uncontrolled(≥70mmol/mol)HbA1c.Anexplanatoryfactor

analysisidentifiedsevenQOWfeatures. The featureshaving a call-recallsystem,

hav-ingindividualizedtreatmentplans, PHCCs’resultsalwayson theagenda,andhaving a

Abbreviations:CI,confidenceinterval;EFA,exploratoryfactoranalysis;GEE,generalizedestimatingequations;GP,generalpractitioner;

NDR,NationalDiabetesRegister;OHA,oralhypoglycaemicagents;PHC,primaryhealthcare;PHCC,primaryhealthcarecentre;RN,

registerednurse;SALAR,SwedishAssociationofLocalAuthoritiesandRegions;QOW,qualityofwork;Swed–QOP,SwedishNationalSurvey

oftheQualityandOrganisationofDiabetesCareinPrimaryHealthcare;T2DM,Type2diabetesmellitus;WTE,wholetimeequivalent.

Correspondingauthorat:CentreforClinicalResearch,VästmanlandHospitalVästerås,SE-72189Västerås,Sweden.

E-mailaddress:rebecka.husdal@regionvastmanland.se(R.Husdal).

https://doi.org/10.1016/j.pcd.2018.11.005

1751-9918/©2018TheAuthors.PublishedbyElsevierLtdonbehalfofPrimaryCareDiabetesEurope.Thisisanopenaccessarticleunder

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primary care diabetes 13 (2019)176–186

177

Nationalsurvey

Primaryhealthcare

Qualityofhealthcare

follow-upstrategycombinedwithtakingresponsibilityofoutcomes/resultswereassociated

withlowerHbA1clevelsinthecontrolledgroup(allp<0.05).Forpeoplewithintermediate

oruncontrolledHbA1c,havingindividualizedtreatmentplanswastheonlyQOWfeature

thatwassignificantlyassociatedwithalowerHbA1clevel(p<0.05).

Conclusions: This nationwide study adds important knowledge regarding associations

betweenQOWinreallifeclinicalpracticeandHbA1clevels.PHCCs’QOWmaymainlyonly

benefitpeoplewithcontrolledHbA1candmoreeffectiveQOWstrategiesare neededto

supportpeoplewithuncontrolledHbA1c.

©2018TheAuthors.PublishedbyElsevierLtdonbehalfofPrimaryCareDiabetesEurope.

ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.

org/licenses/by-nc-nd/4.0/).

1.

Introduction

Type2diabetesmellitus(T2DM)isanimportantpublichealth

problemworldwide.Inmanycountries,peoplewithT2DMare

treatedintheprimaryhealthcare(PHC)system.ThePHC

sys-temisbeingoutstrippedbytheincreasedburdenofT2DMand

itscomplications,resultinginamajorpublichealthissue[1].

Thequalityofwork(QOW)inprimarydiabetescarefor

peo-plewithT2DMisessentialforpostponingthedevelopmentof

diabetes-relatedcomplications[2].PeoplewithT2DMwhohas

poorglycaemiccontrol(HbA1c≥53mmol/mol)isatincreased

riskofcomplications[3].Despitethepresenceofguidelines

fordiabetes care[2,4], the QOW is suboptimal and differs

bothwithinandbetweencountries[5,6].ImprovingtheQOW

requiresefforts suchasworkingwithpreventionstrategies

forreducingdiabetes-relatedcomplications[7],usingnational

registriesforreceivingtailoredfeedbackonclinicaloutcomes

[8],andprovidingindividualizedtreatment[9,10].

Swedenisoneoftheleadingcountriesintermsofprimary

diabetes care, and the Swedish National DiabetesRegister

(NDR)isthelargestdiabetesregisterglobally[11].A

qualita-tivestudybytheSwedishAssociationofLocalAuthoritiesand

Regions(SALAR)identifiedsevensuccessfactorsinSwedish

primary diabetes care,which were associatedwith county

councils/regionshavinggoodperformanceregardingHbA1c

levelinpeoplewithT2DM:(i)focusonpatients’targets;(ii)

tar-getedinitiativesforpatientswithpooroutcomes;(iii)PHCCs’

resultsarealwaysontheagendaformanagementand

health-careprofessionals(HCPs);(iv)interpretationofnewknowledge

andclearexpectations;(v)follow-upandfeedbackonresults;

(vi)long-termimprovementinitiativesfordiabetescare;and

(vii)ownershipofresultsandfocusonprevention[12].This

qualitative study examined HbA1c levels at an aggregated

regionallevel,anditremainsunclearwhetherthesefactors

areimportantatanindividuallevel.Thestudycarriedoutby

SALARhashadgreatimpactonSwedishprimarydiabetescare

andgiventhattheorganizationofprimarydiabetescareis

costly,therearereasonstostudytheseeffectsofactionswith

differentapproaches. Further,although ameta-analysis by

Triccoetal.[13]foundthatqualityimprovement(QI)strategies

areessentialforimprovingHbA1clevelsandinterventions

tar-getingHCPsseemstobevaluableforpeoplewithpoorbaseline

HbA1c,themainchallengeistoaddressthecombinationof

strategieswhichpeoplewithT2DMwillbenefitthemostfrom.

Moreinformationonreallifeclinicalpracticeisalsoneededto

fullyunderstandthebenefitsofQOWinPHCforpeoplewith

T2DM.Thus,theaimofthepresentstudywastodescribeand

analysetheassociationsbetweenPHCCs’QOWandindividual

HbA1clevelsinpeoplewithT2DM.

2.

Methods

This cross-sectional study was based on data collected by

PHCCsinall 21 Swedish countycouncils/regionsusing the

SwedishNationalSurveyoftheQualityandOrganizationof

DiabetesCare inPrimary Healthcare(Swed–QOP)

question-naire. Individual clinical data on people with T2DM were

obtainedfromtheNDR.Informationonsocio-economic

con-ditions and comorbidities were retrieved bylinkage to the

LongitudinalDatabaseforHealthInsuranceandLabor

Mar-ketStudies(LISA)andtheSwedishNationalPatientRegister

(NPR).TheUppsalaRegionalEthicalReviewBoardapproved

thestudy(Dnr:2013/376).

2.1. Setting

In 2013, Sweden had a population of 9.6 million people,

ofwhom >400,000 were estimatedto haveT2DM [14]. The

Swedish PHC system is tax-funded and organized into 21

separategeographicallybasedcountycouncils/regions,which

cooperatenationallythroughtheSALAR[15].

2.2. Studypopulation

AllSwedishPHCCsinoperationin2013wereinvitedto

partic-ipateinthisstudy.Intotal,880(76.4%)of1152eligiblePHCCs

completedtheSwed–QOPquestionnaire.Individual-leveldata

from2013werecollectedfor290,808peoplewithT2DMwho

attendedthesePHCCsandwereregisteredintheNDR.Tobe

eligibletoparticipate,peoplewererequiredtobe≥18years.

Thefinalsamplecomprised846PHCCswith230,958people

withT2DM.SupplementaryFig.S1givesadetailedoverview

oftheinclusionprocess.

2.3. Datacollection

TheSwed–QOPquestionnairewasansweredbyeachPHCC’s

manager. It containedquestions about the PHCC’s

charac-teristicsandwasconstructedbasedonitemsfromprevious

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178

primary care diabetes 13 (2019)176–186

Table1–ThequestionsfromtheSwedishNationalSurveyoftheQualityandOrganizationofDiabetesCareinPrimary Healthcare(Swed–QOP)questionnaireanddescriptivestatisticsofprimaryhealthcarecentres’(PHCCs’)background characteristicsandqualityofworkconditions(n=846).

Typeofvariable VariablefromtheSwed–QOPquestionnaire Valuea Missingb

n(%)

Backgroundcharacteristics ListsizeofthePHCCs,mean(SD) 8461(4196) 2(0.2)

NumberoflistedpeoplewithT2DM,mean(SD) 354(199) 1(0.1)

WTEGPs/500peoplewithT2DM,mean(SD) 7.1(4.5) 3(0.4)

WTERNs/500peoplewithT2DMassignedfordiabetescare,mean(SD) 0.8(0.4) 19(2.2)

Diabetes-responsibleGPs 611(72.2) 0(0.0)

NumberofRNswithdiabetes–specificeducation,mean(SD) 1.7(0.9) 0(0.0)

Diabetes-specificeducationforRNs(ECTScredits),mean(SD) 15.0(8.9) 0(0.0)

PedagogicaleducationforRNs(ECTScredits),mean(SD) 4.1(6.5) 0(0.0)

LengthofregularvisitstoGPs,mean(SD) 28(8.3) 6(0.7)

LengthofregularvisitstoRNs,mean(SD) 46(9.0) 7(0.8)

Diabetesteam,n(%) 473(56.3) 6(0.7)

Groupeducationprogram,n(%) 203(24.0) 0(0.0)

RegistrationsystemforrevisitstoGP,n(%) 662(80.2) 21(2.5)

RegistrationsystemforrevisitstoRN,n(%) 732(89.1) 24(2.8)

RNs’participationinsettingtreatmenttargetsforHbA1c,n(%) 595(70.7) 4(0.5)

GPs’participationinsettingtreatmenttargetsforHbA1c,n(%) 701(83.3) 4(0.5)

PeoplewithT2DM’participationinsettingtreatmenttargetsforHbA1c,n(%) 256(30.4) 4(0.5)

Qualityofworkc Call-recallsystemtoGPsbasedonpatient’sneeds(Q1a),n(%) 269(32.3) 14(1.7)d

Call-recallsystemtoRNsbasedonpatients’needs(Q1b),n(%) 428(52.1) 25(3.0)d

Goal-orienteddrugtherapybasedoncleartreatmentstages(Q2a),n(%) 573(73.5) 66(7.8)

Clearstrategywithinterventionstargetedpeoplewithpooroutcomes(Q2b),n(%) 562(71.3) 58(6.8)

CommonmeetingsregardingdiabetesguidelinesforallHCPs(Q3a),n(%) 342(41.0) 12(1.4)

FrequentdialoguebetweenPHCCmanagementandHCPaboutPHCC’sresults(Q3b),n(%) 475(57.7) 23(2.7)

TheHCPisinformedaboutPHCC’sresults(Q3c),n(%) 446(60.2) 105(12.7)

PHCCsreporthavingregionalguidelinesfordiabetescare,n(%) 831(98.2) 15(1.8)e

Easytoaccess(Q4a),n(%) 665(80.0) 0(0.0)

Easytounderstand(Q4b),n(%) 559(67.3) 0(0.0)

Withclearrecommendations(Q4c),n(%) 504(60.6) 0(0.0)

Well-entrenchedinthecountycouncil/region(Q4d),n(%) 442(86.0) 332(39.2)

Countycouncil/regioncontinuouslyreportsresultsfromNDRtoPHCCs(Q5a),n(%) 590(70.5) 9(1.1)

Countycouncil/regionusesNDR-resultsforqualityofdialogue(Q5b),n(%) 524(62.9) 13(1.5)

Countycouncil/regioninternallyreportsNDRresultsconcerningallPHCCs(Q5c),n(%) 472(56.6) 12(1.4)

Cultureoffollowingguidelines(Q6a),n(%) 795(98.5) 39(4.6)

Focusingonpreventionofdiabetescomplications(Q6b),n(%) 761(94.9) 44(5.2)

Follow-upstrategyofoutcomes/results(Q7a),n(%) 799(96.5) 18(2.1)

Responsibilityofqualityandresultsforpeoplewithdiabetes(Q7b),n(%) 769(96.6) 50(5.9)

Havingdiabetes-responsibleRNs(Q:excluded) 822(97.2) 0(0.0)

Politicalpriorityofdiabetescare(Q:excluded) 395(48.6) 34(4.0)

Havingconductedqualityimprovementworkduringseveralyears(Q:excluded) 565(73.6) 78(9.2)

ECTS,EuropeanCreditsTransferAccumulationSystem;GP,generalpractitioner;HCP,healthcareprofessional;NDR,NationalDiabetesRegister;

RN,registerednurse;T2DM,Type2diabetesmellitus;WTE,whole-timeequivalent.

a PercentagesarebasedonPHCCswithvalidvalues.

b PercentagesarebasedonallPHCCsincludedinthestudy,i.e.,n=846.

c (Q#)referstothequestionpresentedinFig.1describingtheresultofqualityofworkfeatures.

d PercentagesarebasedonPHCCsreportinghavingacall–recallsystem(n=832).

e PercentagesarebasedonPHCCsreportinghavingregionalguidelines(n=831).

careintheUnitedKingdom[17,18].Forthepresentstudy,21

questionsaddressingQOWconditions,whichwerebasedon

componentsconstitutingSALAR’ssevensuccessfactors[12],

wereaddedtotheSwed–QOPquestionnaireafterhavingbeen

validatedusingfacevalidity.Detailsaboutthedatacollection

oftheSwed–QOPquestionnaire[19]andreliabilitytestingof

thequestionnaire[20]havebeenpublishedelsewhere.Table1

givesanoverviewoftheSwed–QOPquestionsincludedinthe

presentstudy.

Swed–QOPquestionnairedataforeachPHCCwerelinkedto

individual-levelclinicaldataintheNDRusingaunique

iden-tificationnumber(theSwedishHealthCareAddressRegister

IdentityNumber).Individual-leveldatafromother registers

werelinkedusingeachindividual’suniqueSwedishPersonal

IdentificationNumber.

2.4. Datasources

TheNDRincludes>350,000(90%)peoplewhohavebeen

diag-nosedwithT2DMandaretreatedintheSwedishPHCsystem.

Theregisterisusedinclinicalpracticetoassistinthe

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primary care diabetes 13 (2019)176–186

179

individual-level informationregardingriskfactors,

medica-tion,and complications. Clinical data are reportedatleast

onceayearfrommedicalcheck-upsbygeneralpractitioners

(GPs)orregisterednurses(RNs).Individualclinicaldataare

reportedcontinuouslyeitheronlineorbyelectronic

transmis-sionsfrommedicalcharts[22].Eachpatientprovidesinformed

consent[21].TheT2DMdiagnosiswasbasedontheclinical

assessmentbyaphysician.Clinical datafrom the NDR for

people withT2DM aged≥18 years reported tothe registry

during2013wereobtainedforalleligiblePHCCs.HbA1cwas

definedinmillimolespermole(mmol/mol)accordingtothe

InternationalFederationofClinicalChemistryandLaboratory

Medicine[23].

Additional individual-level data on socioeconomic

sta-tus and comorbidities were retrieved to address potential

biases. Socio-economic data were collected by linking the

individual clinical level data from the NDR with the LISA

maintainedbyStatisticsSweden.TheLISAprovided

informa-tion onindividual country ofbirth,maritalstatus, income,

highesteducationallevel,andoccupationalstatus[24].Also,

individual-level datafrom the NDR werelinked todataon

comorbidities, obtained from the NPR maintained by the

SwedishNationalBoardofHealthandWelfare.TheNPR

con-tainsindividual-leveldataonprimaryandsecondarymedical

diagnoses from inpatientand outpatient visits atSwedish

hospitals.Thediagnosesareclassifiedaccordingtothe

Inter-national Statistical Classification of Diseases and Related

HealthProblems,10threvision(ICD-10)[25].Eachparticipant’s

medicalhistorywasretrievedfortheyears2012and2013,and

wascategorizedintothemaindiagnosticgroupsofthe

ICD-10classificationsystem.Detailsaboutthecodingprocedure

havebeenpublishedelsewhere[19].Table2givesdetailsabout

thevariablesobtainedfromtheNDR,LISANPR.Comorbidities

relevanttodiabetesarepresentedinTable2,whileallICD-10

diagnosesaregiveninSupplementaryTableS1.

2.5. Statisticalanalyses

Categoricalvariables are presentedasfrequenciesand

per-centages,n(%),whilecontinuousvariablesaregivenasmeans

andstandarddeviations(SDs).Theanswerstothe21

ques-tionscoveringQOWconditionsweredichotomizedas0(“No”)

or1(“Yes”),with“Donotknow”codedasmissing.The21QOW

questionsarelistedinTable1.

To explore the underlying factor structure of the QOW

questions,andthusexplaintheobservedassociationsamong

the 21questions measured atthe PHCClevel, an

explana-toryfactoranalysis(EFA)wasperformedforthe846PHCCs

includedinthestudy.Thefactorextractionformingthebasis

oftheEFAwasperformedusingprincipalcomponentanalysis

(PCA),withfactorsbeingabovethethresholdofeigenvalue=1

deemedprovidingmeaningfulinformationforthe

interpreta-tionoftheEFAresults.Basedonthisrule,sevenfactorswere

identified.

Toobtainaneasilyinterpretablefactorsolution,by

mini-mizingthenumberofQOWquestionsthathadhighloadings

forafactor,avarimaxrotationwithKaisernormalizationwas

performedforthefactorsextractedthroughthePCAmethod.

Following this,QOWquestions thatstill lackedhigh factor

loadings, and thus were deemedto haveambiguous

inter-pretations,wereexcludedusingastep-wiseprocedure.Ina

firststep,thequestion“politicalpriorityofdiabetescare”was

excluded,sincetheabsolutevalueofitshighestfactorloading

was<0.4.Inasecondstep,thetwoquestions“having

diabetes-responsibleRNs”and“havingconductedqualityimprovement

workduringseveralyears”wereexcluded,sincetheabsolute

valuesoftheirhighestfactorloadingwere<0.6whiletheydid

notfitintotheinterpretationoftheotherquestionswith

load-ings>0.6forthesamefactor.Forthesetwosteps,aniterative

procedure wasused wherebythe extractionsand rotations

were re-estimated until a satisfactory resultwas obtained.

Thisprocessledtotheretentionof18questionsformingseven

factors with 2–4 questions each, thus constitutingthe EFA

solution usedinthepresent study.Thesevenfactorswere

interpretedasidentifyingthefollowingsevenQOWfeatures:

(1)call–recallsystem;(2)individualizedtreatmentplans; (3)

PHCCs’ resultsalways on the agenda;(4) characteristics of

regionalguidelines;(5)follow-upandfeedback;(6)cultureand

prevention;and(7)strategiesandresponsibility(Fig.1).

FromtheobtainedEFAsolution,sevenEFAfactoranalysis

scoreswerecalculatedforeachPHCC,basedoncoefficients

estimatedusingtheAnderson–Rubinmethod(factorloadings

varyingbetween0.681and0.867).Inthepresentstudy,these

EFAfactoranalysisscoresarethusestimatesofthedegreeof

presenceofeachQOWfeatureataPHCC.

Totakeaccountofthehierarchicaldependencestructure

of the data, inwhich people with T2DM attend the same

PHCCandPHCCsbelongtothesamecountycouncil/region,

theassociationsbetweenthedegreeofpresenceofPHCC-level

QOWfeaturesandtheindividual-levelHbA1c(mmol/mol)

val-ues were analysed using generalized estimating equations

(GEE)linearregressionmodelsutilizinganindependent

struc-tureworkingcorrelationmatrix.Inallanalyses,theEFAfactor

analysisscoreswereusedinthecalculationsasestimatesof

theQOWfeatures.TwoseparateGEElinearregressionmodels

wereused,withthesevenQOWfeaturesbeingtheexplanatory

variables ofmaininterest:(i)anunadjusted model,

includ-ingonlythesevenQOWfeatures,and(ii)anadjustedmodel,

whichincluded,inadditiontothesevenQOWfeatures,the

individual-leveldemographic,socio-economic,lifestyle,

clin-ical,andcomorbidityvariablesdescribedinTable1aswellas

thePHCC-levelbackgroundcharacteristicsdescribedinTable2

andSupplementaryTableS1.

Allregressionanalyseswereperformedstratifiedonthree

categories ofHbA1clevel: controlled(≤52mmol/mol);

inter-mediate(53–69mmol/mol);anduncontrolled(≥70mmol/mol).

Thesedataarepresentedusingtheslopecoefficientsˇwith

accompanying95%confidenceintervals(CIs).Testsof

differ-ence betweenˇ valuesforthe controlledand uncontrolled

groupswereperformedusinganormalapproximationZtest

procedure. Missing NDR data were imputedusing the last

observation carried forward method, utilizing valid values

fromthesameyear.

All statistical analyses were performed using IBM SPSS

Statistics24,exceptfortestsofdifferencebetweenˇwhich

were calculated manually using Microsoft Excel. For all

statisticaltests,two-sidedp-value<0.05wereconsidered

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p r i m a r y c a r e d i a b e t e s 1 3 ( 2 0 1 9 ) 176–186

Table2–ParticipantcharacteristicsaccordingtothethreeHbA1clevelgroups(n=230,958).

Typeofvariable Variable Controlled Intermediate Uncontrolled Missinga

(n=124,671) (n=70,928) (n=26,947) n(%)

Demographics Age(years),mean(SD) 68.1(11.5) 68.8(11.6) 66.1(12.9) 0(0.0)

Men,n(%) 69430(55.7) 40,699(57.4) 15,844(58.8) 0(0.0)

Durationofdiabetes(years),mean(SD) 7.1(6.6) 10.9(8.0) 12.4(8.5) 21,528(9.3)

Clinical Systolicbloodpressure(mmHg),mean(SD) 134.2(15.4) 135.5(15.7) 136.0(16.5) 11,979(5.2)

Diastolicbloodpressure(mmHg),mean(SD) 76.1(9.6) 76.0(9.7) 76.9(10.3) 12,130(5.3)

Bodymassindex(kg/m2),mean(SD) 29.4(5.2) 30.1(5.3) 31.2(5.8) 30,305(13.1)

Totalcholesterol(mmol/l),mean(SD) 4.7(1.1) 4.6(1.1) 4.8(1.2) 61,771(26.7)

Triglycerides(mmol/l),mean(SD) 1.7(1.0) 1.9(1.2) 2.3(1.9) 83,328(36.1)

High-densitylipoprotein(mmol/l),mean(SD) 1.3(0.4) 1.2(0.4) 1.2(0.4) 78,019(34.0)

Low-densitylipoprotein(mmol/l),mean(SD)b 2.6(0.9) 2.5(0.9) 2.6(1.0) 77,102(33.4)

Estimatedglomerularfiltrationrate(eGFR)<60(ml/min),n(%)c 16,240(15.0) 11,740(19.1) 4569(19.8) 35,680(15.4) Risk/presenceoffootcomplications,n(%) 19,619(19.7) 14,303(25.0) 6159(29.8) 48,839(21.1)

Diabetesretinopathy,n(%) 18,772(20.5) 18,697(33.8) 8809(43.9) 59,938(15.4) Microalbuminuria,n(%)e 13,660(16.1) 10,678(22.6) 5247(31.3) 80,468(34.8) Macroalbuminuria,n(%)f 4593(5.6) 4119(9.1) 2305(14.5) 87,075(37.7) Antihypertensivedrugs,n(%) 94,409(79.0) 54,951(80.7) 19,848(76.9) 10,155(4.1) Lipid-loweringdrugs,n(%) 72,921(61.2) 44,697(65.8) 16,247(63.2) 10,925(4.7) Glucose-loweringtreatment,n(%) 1457(0.6) Diet 40,439(32.6) 6460(9.2) 1490(5.6) OHA 65,370(52.7) 34,531(48.9) 8294(30.9) Insulin 7264(5.9) 10,977(15.6) 6190(23.1) OHA+insulin 9716(7.8) 17,057(24.2) 9952(37.1) Othermedications 1184(1.0) 1527(2.2) 880(3.3) Lifestyle Smoker,n(%) 14,946(13.7) 8432(13.7) 3925(17.4) 33,591(14.5) Physicalactivity,n(%) 50,352(21.8)

Neverorlessthanonceperweek 23,960(23.9) 17,596(30.8) 8492(40.9)

1–2times/week 19,507(19.5) 11,864(20.7) 4406(21.2)

3–5times/week 24,319(24.3) 12,279(21.5) 3515(16.9)

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p r i m a r y c a r e d i a b e t e s 1 3 ( 2 0 1 9 ) 176–186

181

Socio-economics BorninSweden,n(%) 102,293(82.1) 56,963(80.4) 20,419(75.9) 228(0.0)

Maritalstatus,n(%) 228(0.0)

Single 18,120(14.5) 10,412(14.7) 5223(19.4)

Married/registeredpartner 66,798(53.6) 36,527(51.5) 12,245(45.5)

Divorced 21,389(17.2) 12,316(17.4) 5419(20.1)

Widowed 18,279(14.7) 11,607(16.4) 4031(15.0)

Incomeperyear,n(%) 101(0.0)

<120,000SEK 23,598(18.9) 14,484(20.4) 6264(23.3) 120,000≤SEK<145000 23,219(18.6) 14,439(20.4) 5812(21.6) 145,000≤SEK<175000 24,254(19.5) 14,210(20.0) 5042(18.7) 175,000≤SEK<250000 27,223(21.8) 14,577(20.6) 5332(19.8) ≥250,000 26,348(21.1) 13,193(18.6) 4482(16.6) Educationallevel,n(%) 4397(1.9) ≤9years(compulsory) 46,891(38.2) 29,190(42.0) 11,088(42.3) 10–12years 52,865(43.1) 29,455(42.4) 11,442(43.6) College/university 22,954(18.7) 10,834(15.6) 3691(14.1) Occupationalstatus,n(%) 228(0.0) Working 33,508(26.9) 18,302(25.8) 7441(27.6)

Notworkingaged<65years 15,466(12.4) 9131(12.9) 5518(20.5)

Notworkingaged≥65years 75,612(60.7) 43,429(61.3) 13,959(51.9)

Comorbidityd Neoplasms(ICD10;C00–D48),n(%) 16,415(13.2) 9224(13.0) 3033(11.3) 0(0.0)

Eyeandadnexa,(ICD10;H00–H59),n(%) 27,427(22.0) 17,796(25.1) 7223(26.8) 0(0.0) Circulatorysystem(ICD10;I00–I99),n(%) 39,113(31.4) 24,379(34.4) 10,085(37.4) 0(0.0) OHA,Oralhypoglycaemicagents;SEK,Swedishkrona.

Note:Controlled,≤52mmol/mol;intermediate,53–69mmol/mol;uncontrolled,≥70mmol/mol. a Percentagesarebasedonallpeopleincludedinthestudy,i.e.,n=230,958.

b Primarilybasedonlow-densitylipoproteinlevel(LDL)reportedtotheNDRandsecondaryifmissing;theLDLwascalculatedbasedontheFriedewaldformula. cCalculatedbasedontheModificationofDietinRenalDiseaseform.

dOthercomorbiditiesarereportedassupplementarydata(TableS1).

e Yesiftwoofthreetestswithin1yearwerepositive,i.e.,albumin/creatinineratio3–30mg/mmolorurinaryalbumin20–200␮g/minor20–300mg/l. f Yesifalbumin/creatinineratio>30mg/mmolorurinaryalbumin20–200␮g/minor20–300mg/l.

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primary care diabetes 13 (2019)176–186

Fig.1–Resultsoftheexploratoryfactoranalysis(EFA),=residual/measurementerror,=factorloading.GPs,general practitioners;HCPs,healthcareprofessionals;NDR,NationalDiabetesRegister;PHCCs,primaryhealthcarecentres;RNs, registerednurses.

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183

3.

Results

Background characteristics and QOW features of the 846

PHCCsaregiveninTable1.ThePHCCsreportedamean(SD)

listsizeof8461(4196)patients,354(199)ofwhomhadT2DM.

Nursingpersonnelassignedfordiabetes careatthe PHCCs

madeupamean(SD)of0.8(0.41)whole-timeequivalent(WTE)

RNsforevery500peoplewithT2DM.

Table 2shows the characteristics of the 230,958 people

withT2DM,groupedaccordingtothethreeHbA1ccategories.

Morethanhalf (56.0%)ofthe participantshad acontrolled

HbA1c level, about one-third (31.9%) an intermediate, and

aboutone-tenth(12.1%)anuncontrolledHbA1clevel.People

withuncontrolled HbA1c were slightlyyounger, mean (SD)

age66(12.9)years,weremoreoftenmales(58.8%),andhad

alongerdiabetesduration,mean(SD)12.4(8.5)years.

Regard-lessofHbA1clevel,mostofthepeopleweremarried/hada

registered partner,and mosthad 10–12years ofschooling.

Complicationssuchaspresenceofmicroalbuminuria(31.3%)

ormacroalbuminuria(14.5%)weremorecommoninthegroup

withuncontrolledHbA1c.

3.1. QOWfeaturesatthePHCCs

AsshowninTable1,alowpercentageofPHCCsreported

hav-ingacall–recallsystembasedonpatients’needstoRNs(52.1%)

andGPs(32.3%).However,morePHCCsrecognizedthe

impor-tanceofhavingagoal-orienteddrugtherapytreatmentplan

(73.5%)andaclearstrategyforpeoplewithpooroutcomes

(71.3%).IncorporatingtheHCPsintotheQOWprocessseemed

tobelessprioritized:only342(41.0%)PHCCshadcommon

meetingsaboutguidelines,475(57.7%)hadadialoguebetween

PHCCmanagementandHCPs,and446(60.2%)informedthe

HCPsabouttheirPHCC’sresults.However,almostallreported

takingresponsibilityforqualityandresults(96.6%)andhaving

acultureoffollowingguidelines(98.5%).

3.2. AssociationbetweenQOWfeaturesand individualHbA1clevels

TheassociationsbetweenQOWfeaturesandindividualHbA1c

levels are shown in Table 3, separately for the controlled,

intermediate, and uncontrolled groups. After adjusting for

confoundingvariables,anincreasedpresenceoffourofthe

seven QOW features was significantly associated with a

lowerHbA1clevelforpeoplewithacontrolledHbA1clevel.

TheseQOWfeatures(expressedasthechangeinHbA1cper

SD of the QOW feature)were: call–recall system (factor 1;

−0.054mmol/mol; p<0.001); Individualized treatment

(Fac-tor2;−0.053mmol/mol;p<0.001);PHCCsresultsalwayson

theagenda(Factor3;−0.088mmol/mol;p<0.001);and

Strate-giesandresponsibility(Factor7;−0.046mmol/mol;p<0.003).

TheQOWfeatureCultureand prevention(factor6)wasnot

significantlyassociatedwithindividualHbA1c levelsinthe

unadjustedmodel.However,afteradjustingforconfounding

variables,anincreasedpresenceofthisfeaturewasassociated

withincreasedHbA1clevelsinpeoplewithacontrolledHbA1c

level(0.043mmol/mol;p=0.005).

For people with anintermediate or uncontrolled HbA1c

level, the increased presence of Individualized treatment

(Factor 2) was the only QOW feature that was

signif-icantly associated with a lower individual HbA1c level

(−0.053mmol/mol; p=0.001and−0.197mmol/mol; p=0.014,

respectively). When testing for differences between the

uncontrolled and controlled HbA1c level groups regarding

associations between QOW features and individual HbA1c

level, onlythefeaturePHCCs’resultsalwaysontheagenda

(factor3)differedsignificantlybetweenthetwogroups;the

slope coefficientˇwaslower forthecontrolledgroupthan

for the uncontrolled group(ˇ=0.172mmol/mol; p=0.042).

Comparing PHCCsamongthe top 2.5%(i.e.,having≥2SDs

on all QOW features) with those among the bottom 2.5%

(i.e., having≤2 SDs onall QOW features)showed that the

HbA1clevelwouldbe1.136mmol/mollowerinthecontrolled

group,0.212mmol/mollowerintheintermediategroup,and

0.788mmol/mollowerintheuncontrolledgroup.

4.

Discussion

Thecurrentstudyfoundagreaternumberofsignificant

asso-ciations between QOWfeatures and HbA1clevel in people

withcontrolledHbA1cthan inpeople withintermediate or

uncontrolledHbA1c.Thiscontrastswithaprevious

system-aticreviewandmeta-analysis[13],whereQOWstrategieswere

reportedtohavethelargesteffectamongpeoplewith

inter-mediate/uncontrolledHbA1c.Theseconflictingresultsmaybe

explainedbylimitationsofthepresentcross-sectionalstudy

design and/or reflecting the need of more evidence-based

QOWstrategiestosupportpeoplewithuncontrolledHbA1c.

Surprisingly,eventhoughalmostallPHCCsworkedwiththe

questionsaddressedintheQOWfeaturesCultureand

preven-tion(Factor6)andStrategiesandresponsibility(Factor7),no

significantassociationswerefoundforpeopleinthe

interme-diateoruncontrolledgroup.Thismayreflectthat,eventhough

PHCCsmanagershaveaninterestinpursuingthesequestions,

their organizationexperiences challenges whentranslating

thisinto clinicalpractice,especiallyforpeoplewith

uncon-trolledHbA1c[26].

The unexpected association between having more of

the QOWfeature Cultureand prevention(Factor6) and an

increasedHbA1c levelinthose withcontrolledHbA1c may

reflectreversecausation.Notably,theQOWfeatureFollowup

andfeedback(Factor5)wasnotsignificantlyassociatedwith

lowerHbA1clevels.UsingtheNDRprovidestheopportunity

forPHCCstogetaccesstoasystematicdocumentation,make

comparisons,andcomeupwithideasforimprovements[8].

Certainly,identifyingassociationscouldbechallengingwhen

theutilizationoftheNDR isunclear.Theobserved

associa-tionbetweentheQOWfeatureIndividualizedtreatmentplans

(Factor2)andlowerHbA1clevelsinpeoplewith

intermedi-ate/uncontrolledHbA1cconfirmstheimportanceofproviding

individualizedcare[9].

Systematic reviews[27–29] have foundlimited evidence

for associations between the organisation ofdiabetes care

and glycaemic control, which may be explained by poor

methodological quality of the included studies. Moreover,

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p r i m a r y c a r e d i a b e t e s 1 3 ( 2 0 1 9 ) 176–186

Table3–Resultsofthegeneralizedestimatingequationslinearregressionmodelsoftheassociationsbetweenqualityofwork(QOW)featuresandindividualHbA1c level,separatelyforeachHbA1clevel.Significantdifferencesaregiveninbold.

QOWfeature Controlled

(n=104,647at788PHCCs) Intermediate (n=61,078at788PHCCs) Uncontrolled (n=22,849at783PHCCs) Diff.uncontrolledvs controlled

ˇ(95%CI) pvalue ˇ(95%CI) pvalue ˇ(95%CI) pvalue Diffˇ pvalue

Unadjusted

1.Call–recallsystem −0.042(−0.072;−0.013) 0.005 −0.005(−0.042;0.032) 0.805 0.025(−0.130;0.180) 0.754 0.067 0.238

2.Individualizedtreatment −0.055(−0.085;−0.025) <0.001 −0.042(−0.079;−0.005) 0.027 −0.107(−0.260;0.047) 0.174 −0.052 0.290 3.Resultsalwaysontheagenda −0.129(−0.159;−0.099) <0.001 −0.014(−0.052;0.024) 0.476 0.166(0.007;0.325) 0.040 0.295 0.001

4.Regionalguidelines −0.029(−0.058;0.001) 0.054 −0.014(−0.051;0.022) 0.439 −0.125(−0.282;0.032) 0.118 −0.096 0.155

5.Follow-upandfeedback −0.008(−0.021;0.038) 0.571 0.035(−0.002;0.072) 0.063 −0.043(−0.194;0.109) 0.582 −0.051 0.290

6.Cultureandprevention 0.011(−0.020;0.041) 0.497 −0.017(−0.055;0.021) 0.374 −0.109(−0.269;0.052) 0.186 −0.119 0.111

7.Strategiesandresponsibility −0.051(−0.083;−0.019) 0.002 −0.012(−0.051;0.026) 0.529 0.111(−0.050;0.271) 0.177 0.162 0.050 Adjusteda

1.Call–recallsystem −0.054(−0.083;−0.025) <0.001 −0.009(−0.046;0.028) 0.641 −0.004(−0.160;0.152) 0.964 0.050 0.298 2.Individualizedtreatment −0.053(−0.083;−0.023) <0.001 −0.053(−0.091;−0.014) 0.007 −0.197(−0.355;−0.040) 0.014 −0.144 0.065 3.Resultsalwaysontheagenda −0.088(−0.119;−0.057) <0.001 −0.017(−0.057;0.022) 0.391 0.085(−0.080;0.249) 0.312 0.172 0.042 4.Regionalguidelines −0.015(−0.044;0.014) 0.313 −0.009(−0.046;0.028) 0.640 −0.091(−0.251;0.068) 0.262 −0.077 0.213 5.Follow-upandfeedback −0.014(−0.042;0.014) 0.339 0.036(0.000;0.073) 0.052 −0.056(−0.206;0.095) 0.470 −0.042 0.323 6.Cultureandprevention 0.043(0.013;0.073) 0.005 0.003(−0.035;0.041) 0.881 −0.098(−0.258;0.062) 0.231 −0.140 0.074 7.Strategiesandresponsibility −0.046(−0.077;−0.015) 0.003 0.007(−0.032;0.046) 0.724 0.109(−0.054;0.272) 0.190 0.156 0.058 Diff.,Difference;HCP,healthcareprofessional;PHCC,primaryhealthcarecentre;NDR,NationalDiabetesRegister.

Note:Controlled,≤52mmol/mol;intermediate,53–69mmol/mol;uncontrolled,≥70mmol/mol.QOWfeatures:1.Call–recallsystem;2.individualizedtreatment;3.PHCCs’resultsalwaysontheagenda; 4.characteristicsofregionalguidelines;5.follow-upandfeedback;6.cultureandprevention;7.strategiesandresponsibility.

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primary care diabetes 13 (2019)176–186

185

ieswithdiverseparticipantcharacteristics,studysettings,and

reportedoutcomes[30].Theorganizationofprimarydiabetes

carehasnosingleuniversalpathwaythatcanbeappliedin

allsettings[6].However,thisstudyaddsimportantknowledge

abouttheeffectsofQOWfeatureswithinoneofthemost

com-prehensivePHCsystemsinEurope,whichmaybeusefulfor

benchmarkingbetweencountries.

To some extent, the findings of the present study are

consistent withSALAR’s sevensuccess factors in terms of

identifyingorganizationalfeaturesasimportanttotheability

ofHCPs toprovideadiabetescareofgoodqualityfor

peo-plewithT2DM[12].Cautionmust,however,betakenwhen

comparingthepresentstudyand SALAR’squalitativestudy

becauseofthedifferentmethodologicalapproaches.Despite

the limitations inthe methodology and restricted

general-izabilityoftheresults,SALAR’squalitativestudyhashad a

large-scale impact on Swedish primary diabetes care. The

sevenQOWfeaturesaddressedinthe currentstudyshould

beseenascomplementaryinformationtoSALAR’squalitative

benchmarkingstudy,makingitpossibleforpolicymakersto

betterunderstandthemeaningofsuccessfactorsinprimary

diabetescare.

Limitationsofthepresentstudyincludethecross-sectional

design,making it impossible tostudy causal relationships.

Usingself-reportedquestionnaires,althoughfacilitatingthe

collectionofthislargeamountofdata,increasedtheriskthat

respondents embellished answers or misinterpreted

ques-tions. To reduce this kind of bias, PHCC managers were

encouragedtoanswer the questionnairetogether withGPs

andRNshavingdirectcontactwiththepatients.Thereisalso

ariskofselectionbiassincewell-functioningPHCCsmayhave

beenmoreinclinedtocompletethequestionnaire.However,

thisissofarthefirstSwedishlarge-scalenationalsurveyto

describeandanalysetheassociationsbetweenPHCCs’QOW

and HbA1c level in people with T2DM. The large sample

sizeof people withT2DM and PHCCsincreases the ability

togeneralizetheresultsintheSwedish PHCsetting.Using

well-administratedregisterscoveringindividual-leveldataon

clinicalriskfactors,socio-economics,andcomorbiditiesmade

itpossibletoadjustforallknownimportantconfounders.

Inconclusion,havingindividualizedtreatmentplanswas

the only QOW feature that was significantly associated

with lower HbA1c levels in all groups. The greatest effect

wasfoundforpeople withuncontrolled HbA1c.Inaddition

to previous research assessing the effectiveness on QOW

improvements based on randomized controlled trials, this

nationwideobservationalstudypointstotheimportanceof

examiningassociationsbetweenQOWinreallifeclinical

prac-ticeandHbA1clevelsinpeoplewithT2DM.Todate,theQOW

carriedoutatSwedishPHCCsmayonlybenefitpeoplewith

good glycaemiccontrol(HbA1c≤52mmol/mol). More

effec-tiveQOWstrategiesarethusneededtosupportpeoplewith

uncontrolledHbA1c.

Funding

Thisworkwassupportedbygrantsfrom:theUppsala–Örebro

RegionalResearchCouncil[grant:numberRFR-480801,

RFR-550891,RFR-640711]andRegionVästmanland[grantnumber

LTV-398181,LTV-472371,LTV-552001,LTV-644151].The

fund-ingsourceshadnoroleinthestudydesign,datacollection,

dataanalysis,datainterpretation,orwritingofthereport.

Conflicts

of

interest

Theauthorsstatethattheyhavenoconflictofinterest.

Acknowledgements

Theauthorsaregratefultoalloftheparticipatingclinicians

involved in the data collection as well as the staff at the

NDR.Wealsothankthecontactpeopleinthecounty

coun-cils/regionsfortheirsupportandallPHCCsthatparticipated

inthepresentstudy.

Appendix

A.

Supplementary

data

Supplementary data associated with this article can be

found, in the online version, at https://doi.org/10.1016/

j.pcd.2018.11.005.

r

e

f

e

r

e

n

c

e

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Figure

Table 1 – The questions from the Swedish National Survey of the Quality and Organization of Diabetes Care in Primary Healthcare (Swed–QOP) questionnaire and descriptive statistics of primary health care centres’ (PHCCs’) background characteristics and qual
Table 2 – Participant characteristics according to the three HbA1c level groups (n = 230,958).
Fig. 1 – Results of the exploratory factor analysis (EFA), ␦ = residual/measurement error, ␭ = factor loading
Table 3 – Results of the generalized estimating equations linear regression models of the associations between quality of work (QOW) features and individual HbA1c level, separately for each HbA1c level

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