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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:
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
aaCentreforClinicalResearchVästmanland,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
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
178
primary care diabetes 13 (2019)176–186Table1–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
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
180
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 ) 176–186Table2–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)
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/mmolorurinaryalbumin20–200g/minor20–300mg/l. f Yesifalbumin/creatinineratio>30mg/mmolorurinaryalbumin20–200g/minor20–300mg/l.
182
primary care diabetes 13 (2019)176–186Fig.1–Resultsoftheexploratoryfactoranalysis(EFA),␦=residual/measurementerror,=factorloading.GPs,general practitioners;HCPs,healthcareprofessionals;NDR,NationalDiabetesRegister;PHCCs,primaryhealthcarecentres;RNs, registerednurses.
primary care diabetes 13 (2019)176–186
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,
stud-184
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 ) 176–186Table3–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.
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
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