Implementation of the ChronicCare Model in Small MedicalPractices Improves CardiovascularRisk but Not Glycemic Control

OBJECTIVE

To test whether the implementation of elements of the Chronic CareModel (CCM)via a specially trained practice nurse leads to an improved cardiovascular riskprofile among type 2 diabetes patients.

RESEARCH DESIGN AND METHODS

This cluster randomized controlled trial with primary care physicians as the unit ofrandomization was conducted in the German part of Switzerland. Three hundredtwenty-six type 2 diabetes patients (age >18 years; at least one glycosylatedhemoglobin [HbA1c] level of ‡7.0% [53 mmol/mol] in the preceding year) from 30primary care practices participated. The intervention included implementation ofCCM elements and involvement of practice nurses in the care of type 2 diabetespatients. Primary outcomewas HbA1c levels. The secondary outcomes were bloodpressure (BP), LDL cholesterol, accordance with CCM (assessed by PatientAssessment of Chronic Illness Care [PACIC] questionnaire), and quality of life(assessed by the 36-item short-form health survey [SF-36]).

RESULTS

After 1 year, HbA1c levels decreased significantly in both groups with no significantdifference between groups (20.05% [20.60 mmol/mol]; P = 0.708). Among in-tervention group patients, systolic BP (23.63; P = 0.050), diastolic BP (24.01;P < 0.001), LDL cholesterol (20.21; P = 0.033), and PACIC subscores (P < 0.001 to0.048) significantly improved compared with control group patients. Nodifferences between groups were shown in the SF-36 subscales.

CONCLUSIONS

A chronic care approach according to the CCM and involving practice nurses indiabetes care improved the cardiovascular risk profile and is experienced bypatients as a better structured care. Our study showed that care according to theCCM can be implemented even in small primary care practices, which still rep-resent the usual structure in most European health care systems.Diabetes Care 2014;37:1039–1047 | DOI: 10.2337/dc13-1429

1Institute of General Practice and Health ServicesResearch, University of Zurich, Zurich,Switzerland2Institute of Social and Preventive Medicine,University of Zurich, Zurich, Switzerland3Horten Centre for Patient-Oriented Research,University of Zurich, Zurich, Switzerland

Corresponding author: Anja Frei, anja.frei@ifspm.uzh.ch.

Received 17 June 2013 and accepted 3 December2013.

Clinical trial reg. no. ISRCTN05947538, www.isrctn.org.

This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc13-1429/-/DC1.

© 2014 by the American Diabetes Association.See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

Anja Frei,1,2 Oliver Senn,1 Corinne Chmiel,1

Josiane Reissner,1 Ulrike Held,3 and

Thomas Rosemann1

Diabetes Care Volume 37, April 2014 1039

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Chronic diseases and multiplemorbidities have shown an increasingprevalence in most industrializedcountries, including Switzerland (1).Among these chronic diseases, diabetesis one of the most prevalent ones (2).The Chronic CareModel (CCM) has beendeveloped as an evidence-basedapproach for the care of chronically illpatients. A central element of the CCMis the team-centered care approach,which facilitates and produces effectiveinteractions between proactive primarycare practice teams, and empowerspatients with the aim to improveprocesses and outcomes in patientswith chronic illnesses (3,4).

In contrast to the United States,experiences in European countries withthe CCM approach are rare. ManyEuropean health care systems, forexample in Germany, Austria,Switzerland, France, Italy, and Spain, arephysician-centered and do not involvepractice nurses or other nonphysicianprofessions in care. Advocates for healthcare among the politicians in thesecountries are very interested in team-based approaches, especially in the careof chronically ill patients, since, on theone hand, the number of these patientsis increasing and, on the other hand, ashortage of primary care physicians (PCPs)exists in most of these countries (5).

Regarding the care for diabetespatients, the optimal cardiovascular riskprofile is one of the most importanttargets for health expectancy andquality of life (6). The aim of this studywas to investigate whether a team-based approach according to the CCM,which included the involvement of apractice nurse in the care for type 2diabetes patients results in an improvedcardiovascular risk profile after 1 year,namely, glycosylated hemoglobin(HbA1c), blood pressure (BP), and LDLcholesterol. Additionally, we examinedwhether the intervention resulted in animproved quality of life for the patientsand improved patients’ perspective ofthe provided care.

RESEARCH DESIGN AND METHODS

This study was a cluster randomizedcontrolled trial with PCPs as the unit ofrandomization. Detailed informationabout design and methods (7) and the

baseline characteristics of the studypatients (8) was published previously.The study protocol has been approvedby the ethics committee of the Kantonof Zurich and received an unrestrictedpositive vote on 25 January 2010.

Recruitment of ParticipantsEligible criteria for PCPs were that theyparticipated in routine primary care ofunselected patients. If they wereworking in a non–single-handedpractice, it was required that patientswere clearly allocated to individualPCPs. About 800 randomly selectedPCPs from the eastern part ofSwitzerland were invited to aninformation meeting on the study.Additionally, the project was presentedin several quality-circle meetings in thePCPs’ networks.

Eligible patients were identified throughthe PCP registry, based on laboratoryresults, and received an invitation letterby the PCPs with information about thestudy. Patients were included inconsecutive order of attendance in thepractice, regardless of the reason for theencounter. The inclusion criteria wereadulthood (age .18 years), diagnosis oftype 2 diabetes according to internationaldiagnostic criteria (9), and at least oneHbA1c level of$7.0% (53 mmol/mol)measured within the preceding year.The latter criterion was formulatedbecause the aim of the study was toreduce HbA1c values by 0.5%, consideringthe current recommendations inguidelines (HbA1c 6.5% [48 mmol/mol])at study onset (10). Exclusion criteriawere insufficient language skills to readand understand informed consent,patient information, and questionnaires;practice contact for emergencies only(i.e., no continuous patient-doctorrelationship); and a life expectancyof ,6 months.

InterventionThe intervention aimed at providingteam care according to the CCM.To perform CCM-based care, a teamapproach involving the practice nurse isrequired. Usual care in Switzerland isfocused on the PCP and the PCP-patientrelationship, based on good clinicalpractice. As in most European countries,practice nurses in Switzerland arecurrently only marginally involved in the

care for patients, and their education isless focused on medical issues,addressing mainly administrativematters. We established theintervention based on the results of aqualitative prestudy concerning theimplementation of CCM elements, theinvolvement of practice nurses (11), andpreliminary results of a systematicreview conducted by our research groupassessing effective interventions inprimary care to improve care fordiabetes patients (12).

Intervention on Cluster Level (Provider of

Health Care)

Practice nurses of the interventiongroup were trained right afterrandomization in a 6-day educationalcourse “Treatment of long termpatientsdmodule diabetes,” organizedby the union of Swiss practice nurses(13). The course provided medicalknowledge for the treatment ofdiabetes patients and generalcommunication skills, and it empoweredpractice nurses for their role in a teamproviding structured care for chronicallyill patients. The practice nurses alsolearned how to perform visits andfollow-up consultations by means of amonitoring tool developed for the study(described below) (14).

In addition, PCPs and practice nursesfrom the intervention groupparticipated in two 4-h interactiveworkshops. The first workshop wasscheduled right after randomization andaddressed the implementation of theteam approach in practice andevidenced-based therapy of diabetes.The second workshop took place after 6study months, and covered professionalexchange between practice nurses andPCPs regarding implementationexperience and management ofcardiovascular risk factors.

Intervention on Practice Level (Patients)

The intervention on the practice levelmaintained that practice nurses beinvolved in the care of type 2 diabetespatients. Practice nurses plannedindependent consultations withpatients. The monitoring tool guidedthem through the consultations, andprovided the opportunity to recordrelevant parameters and assistance forself-management support in order tohelp the patient in selecting

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appropriate, concrete behavioral goals,in developing plans for reaching thosegoals, and in evaluating the progressand adequacy of those plans. Themonitoring tool addressed clinicalparameters (e.g., HbA1c, BP, and LDLcholesterol levels), examinations (e.g.,food control, neurological tests, andeye examinations), adherence toprescribed drugs, self-care goals, andother recommendations. The clinicalaim of the tool was to ensure thattreatment recommendations werefollowed. The assessed parameterswere classified regarding their clinicalurgency and importance into a trafficlight scheme (green, amber, and red),and the practice nurses forwardedthe tool to the PCPs. So the PCPsobtained an immediate overview onthe current situation of the patients.We recommended practice nurseconsultations every 4 months, butfrequency could be adaptedaccording to the clinical situation ofthe patient (14).

Overall, the intervention included theimplementation of the following CCMelements: organization of health careand delivery system design (withinvolvement of the practice nurse);clinical information systems (using theCARAT [Chronic Care for Diabetes] studymonitoring tool); decision support (withguideline-based instructions on the tool,and requiring the availability of adiabetes specialist at University HospitalZurich); and self-management support(provided by the practice nurse). Moredetailed information is provided in thestudy protocol (7).

Outcome MeasuresThe primary study outcome was theHbA1c level. Secondary clinicaloutcomes were the cardiovascular riskfactors systolic and diastolic BP and LDLcholesterol level. Clinical parameterswere assessed by the practice teamusing point-of-care laboratory analysisand/or analysis by externallaboratories. Patient-reportedsecondary outcomes were accordancewith the CCM from patients’perspective measured by the PatientAssessment of Chronic Illness Carequestionnaire (PACIC) (15,16) and thegeneric health-related quality of lifeassessed by the SF-36 (17).

Sample SizeWe aimed at inducing a reduction of0.5% in the HbA1c level for theintervention group patients. Since noepidemiological data regarding HbA1clevel from the Swiss primary care settingwas available at the time of studyprotocol development, we assumed,based on previous German data (18) andon our inclusion criteria (HbA1c $7.0%[53 mmol/mol]), a mean HbA1c of 7.7%(61 mmol/mol) at baseline assessmenttime. In accordance with data from theDIG (Diabetes in Germany) study (19)and the ACCORD (Action to ControlCardiovascular Risk in Diabetes) trial(20), we assumed an SD of 1.2% (13mmol/mol) and, based on our previousstudies and on data available from thewebsite of the University of Aberdeen(21), an intraclass correlation coefficient(ICC) of 0.04 for the primary outcomeHbA1c. We aimed at 80% power; thesignificance level was set to 0.05. Weperformed the sample size calculationwith the Cluster Randomization SampleSize Calculator, version 1.02, of theUniversity of Aberdeen. Based on ourassumptions and definitions, the samplesize calculation resulted in theinclusion of 12 patients and 11practices in each arm. Considering ahigher drop-out rate in clusterrandomized trials since the dropout ofone cluster leads to the loss of allpatients in a cluster, we assumed adrop-out rate of 20%, resulting in 14practices in each arm and 28 practices,including 12 patients, in total (22–24).

RandomizationThe PCPs who agreed to participate inthe study were alphabetically orderedby their family names in a list withnumbers from 1 to 30. An independentresearch assistant, who was notinvolved in the study and was blind tothe identity of the PCPs, randomlyallocated by statistical computersoftware SPSS (version 18.0) 15 letters Aand 15 letters B to numbers 1–30 and tothe corresponding PCPs, respectively.The assignment of the letters A and B toeither the intervention or control groupwas randomly conducted by a secondresearch assistant who drew blinded aticket with the letters A or B and a ticketwith the group allocation interventionor control group from an envelope.

We informed all PCPs about the groupallocation after the inclusion of patientsand baseline assessments to minimizeselection bias. We did not constraincluster randomization by anystratification.

Statistical MethodsBaseline characteristics of PCPs andpatients according to intervention andcontrol group are presented as themeans and SDs for continuous variables,and frequencies and percentages forcategorical data.

Analyses were conducted by intention-to-treat. Missing follow-up data ofpatients who dropped out weresubstituted by baseline assessment data(last observation carried forward). Forthe primary outcome, HbA1c level andclinical outcomes systolic BP, diastolicBP, LDL cholesterol level, and SF-36results, we analyzed the mean (95% CI)differences in changes over timebetween groups using t tests forindependent samples. ICCs werecalculated for the primary and clinicalsecondary outcomes to assess apotential clustering effect. To assess theindependent effect of the treatmentgroup, we additionally conductedmultilevel regression analyses with thePCP as the cluster level considering thechanges over time in the primary andclinical secondary outcomes aspredictor variables, and potentiallyconfounding variables as determinants(patient’s sex and age, smoking status,BMI, number of comorbidities, numberof visits during the study year, totalnumber of drugs, treatment ofcorrespondent medication [antidiabetictherapy for HbA1c, antihypertensivetherapy for BP, lipid-lowering therapyfor LDL cholesterol], and changes incorrespondent medication during thestudy year). Mean differences over timeof the PACIC subscales were calculatedusing the nonparametricMann-WhitneyU test, since the PACIC subscales areordinally scaled and the scores were notnormal distributed. The significancelevel was set at 0.05. Statistical analyseswere performed using Stata version12.0 (StataCorp, 2010).

RESULTS

A total of 30 PCPs from the German-speaking part of Switzerland who

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recruited 326 type 2 diabetes patientsparticipated in the study. Recruitmentof PCPs took place between November2009 and February 2010, and therecruitment of patients and baselineassessment took place between Januaryand April 2010. PCPs were informedabout their allocated group after theyfinished patient inclusion. Theintervention ran from April 2010 untilMay 2011, and follow-up assessmentswere conducted 1 year after baselineassessments. Figure 1 shows the flow ofPCPs and patients through the study. Intotal, 23 patients (7%) were lost tofollow-up.

PCP and patient demographic andclinical characteristics are presentedin Table 1. PCPs from both groupswere comparable, except that morecontrol group than intervention groupPCPs worked in single-handedpractices.

Table 2 shows the primary, secondary,and additional clinical outcomes. Atbaseline, intervention group patientshad a mean HbA1c level of 7.8%(62 mmol/mol), a mean systolic BP of

140 mmHg, a mean diastolic BP of 83mmHg, and amean LDL cholesterol levelof 2.8 mmol/L. For control grouppatients, the mean HbA1c level was 7.6%(59 mmol/mol), mean systolic BP was138 mmHg, mean diastolic BP was 79mmHg, and mean LDL cholesterol level2.5 mmol/L. At follow-up, theintervention and control groups did notdiffer significantly in the mean changeover time of the primary outcome HbA1clevel, but the HbA1c level improvedsignificantly in both groups, as follows:20.27% (23.4 mmol/mol; P = 0.033) inthe intervention; and 20.22% (22.9mmol/mol; P = 0.002) in the controlgroup. Statistically significantdifferences could be observed in themean changes over time between theintervention and control groups for thesecondary clinical outcomes systolic BP,diastolic BP, and LDL cholesterol level. Indetail, the systolic BP, diastolic BP, andLDL cholesterol level of the interventiongroup patients improved over time,whereas the corresponding levels of thecontrol group patients remainedapproximately the same. There was no

evidence for a statistically significantclustering effect. Estimated effectsbased on multilevel regression analyseswere of the same magnitude; however,changes in LDL cholesterol levels nolonger reached the level of significance(Supplementary Table 1).

Descriptive results with regard to healthcare utilization, further clinicaloutcomes, and medications arepresented comprehensively inSupplementary Table 2. Briefly, themean number of visits to generalpractices during the last year increasedin both groups (from 8.3 to 9.6 in theintervention group; from 7.9 to 8.4 inthe control group). However, the meandifference in change between groupswas not statistically significant (1.07;P = 0.155). In terms of changes inmedications (categorized as change/nochange) from baseline to follow-up, nosignificant differences could bedetected regarding antidiabetic therapy(x2 = 0.03, P = 0.862), antihypertensivetherapy (x2 = 2.63, P = 0.105), andlipid-lowering therapy (x2 = 0.57,P = 0.449).

Figure 1—Flow diagram of recruitment and follow-up of PCPs and patients.

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Regarding the patient-reportedsecondary outcomes, we foundstatistically significant differences inchanges over time between interventionand control group patients in all PACICsubscales and in the PACIC summaryscore, showing improved levels forintervention group patients and mostlyunchanged scores for control grouppatients at follow-up (Table 3). For allscores of the SF-36 subscales, we did notfind statistically significant differences inchanges between the two groups overtime.

CONCLUSIONS

In our study, a chronic care approachperformed according to the CCM andinvolving the practice nurse in diabetes

care improved the cardiovascular riskprofile of patients with type 2 diabetes.Patients experienced the changes in thecare provided as having a betterstructure, which is reflected in theincreased PACIC scores. Furthermore,our results showed that CCM care canbe implemented even ininexperienced small primary carepractices, which still represent themost common situation in manyEuropean health care systems.

After 1 year of intervention, the primaryoutcome HbA1c level slightly improvedin both groups of our study withoutshowing a significant differencebetween the intervention and controlgroups. Several reasons might accountfor that. First of all, the PCPs could not

be blinded; they knew that they hadparticipated in a diabetes trial thatmight also have increased the attentiontoward the HbA1c level in the controlgroup. Furthermore, the HbA1c levelswere already quite good in mostpatients at baseline, especially whentaking into account that therecommendations for HbA1c targetlevels changed during the study period.Current guidelines recommend lessstrict targets, especially for olderpatients, a group that constituted mostof the patients in our sample (6,10).Additionally, most of the patients in oursample had multiple morbidities, whichalso might have kept PCPs away fromvery rigorous HbA1c target levels.Overall, it can be concluded that theHbA1c level was satisfactory in mostpatients, and only a small amount ofroom remained for improvementwithout increasing the risk ofhypoglycemia for many of these oldpatients with multiple morbidities(20,25). Interestingly, on the one hand,previous studies found similar resultswith no significant difference in HbA1cdecrease between the two groups (26),and on the other hand also a decline inHbA1c levels only in the CCM group (27)after the implementation of CCMelements.

Our hypothesis that the nonsignificanceof the HbA1c level was caused by thestudy participation effect is supportedby the finding that BP, which was notmentioned as being a primary study aim,improved significantly only in theintervention group. PCPs and practicenurses from the intervention groupwere sensitized to the management ofcardiovascular risk factors, which was atopic in the educational courses andworkshops. Furthermore, theintervention-monitoring tool guided thepractice nurse through a systematicmonitoring of the BP. Nevertheless, themean BP values at the end of the studyperiod indicate that there is still roomfor improvement, at least for the meansystolic BP, which did not fulfill currentrecommendations (6) and was slightlyhigher compared with other samples(28,29). The same effect occurred in theLDL cholesterol levels. LDL cholesterollevel was also defined as a treatmentaim in the intervention-monitoring tool

Table 1—Baseline characteristics of intervention and control group at cluster(PCPs) and individual (type 2 diabetes patients) levels

CharacteristicsIntervention

group (n = 162)Control group

(n = 164)

PCP factors at baselinePCPs, n 15 15Age, mean (SD), years 50.0 (6.9) 51.5 (7.6)Men 13 (87) 14 (93)Organization of PCPs’ practicesSingle-handed practice 3 (20) 7 (47)Group practice (.1 PCP) 12 (80) 8 (53)Member of a PCP network 10 (67) 7 (47)

Patient factors at baselineAge, mean (SD), years 65.7 (10.4) 68.3 (10.6)Men 88 (54) 99 (60)Living together with partner/family (n = 314) 125 (79) 121 (78)Education, mean (SD), years (n = 312) 11.6 (3.2) 11.7 (3.1)Smoking (patient reported)Current smoker 22 (14) 14 (9)Former smoker 63 (39) 66 (40)Never smoker 73 (45) 76 (46)Missing 4 (2) 8 (5)

BMI, mean (SD) 30.5 (5.3) 30.7 (5.9)Antidiabetic therapyNone 4 (2) 8 (5)Only oral 108 (67) 100 (61)Only insulin 11 (7) 15 (9)Combined (insulin and oral) 36 (22) 41 (25)Missing 3 (2) d

Diabetes duration, mean (SD), years (n = 322) 9.5 (7.4) 10.3 (7.8)No comorbidities, mean (SD) 2.5 (1.6) 2.9 (1.5)No drugs, mean (SD) (n = 321) 4.6 (2.2) 4.9 (2.0)No consultations in last year, mean (SD) (n = 325) 8.3 (6.8) 7.9 (5.2)PHQ-9 summary score, mean (SD) (n = 302) 5.1 (4.7) 5.3 (4.8)Compliance (assessed by PCPs)Very good 47 (29) 62 (38)Rather good 80 (50) 69 (42)Rather and very bad 33 (20) 33 (20)Missing 2 (1) d

Values are numbers (percentages), unless stated otherwise. PHQ-9, Patient HealthQuestionnaire short form.

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and was discussed as an importanttarget in the interactive workshop forPCPs and practice nurses. Our datashowed some medical treatmentintensification regarding LDL cholesterollevel as well as BP, but whether theimprovements are due to theintensification or caused by an increasedadherence by the patients can finally notbe determined.

Interestingly, according to theimprovements in BP and LDL cholesterollevels, patients’ experiences of providedcare also changed. All PACIC subscalesshowed significantly higher scores overtime in the intervention group. Obviously,patients experienced the changes or thedifferences in provided care that areassociated with the CCM. This effect wasnot observed for control group patients,despite the improvement in their HbA1clevels over time.

We could not observe significantchanges over time for generic health-related quality of life (HRQL), which wasassessed by the SF-36. The SF-36 isprobably the most common HRQLinstrument, but it is not very specific.Although the intervention resulted inimprovements in clinical parametersand perception of the provided care,patients’ general HRQL status was notaffected. This finding emphasizes theimportance of disease-specific HRQLassessments to detect the concretechanges of intervention. However, thescores of the eight SF-36 domainsremained remarkably constant overtime in both the intervention andcontrol groups. This result supports thehigh test-retest reliability of theinstrument in general.

Improving diabetes care is obviously achallenging goal, which may not beachieved by simple approachestargeting single aims only. A recentstudy (30) with similar methodologyassessed, for instance, the effect of peersupport for patients with type 2diabetes but could not show significantdifferences between groups in theimprovement of the cardiovascular riskfactors. In another study (31), patientswith newly diagnosed type 2 diabetesreceived a 6-h structured groupeducational intervention, but nosignificant differences in the change in

Table

2—Primary

outcome,clinicalse

condary

outcomes,

andadditionalch

aracteristicsatbas

elineandfollow-u

pin

type2diabetespatients

per

alloca

tedgro

up

Outcomes

Participan

ts,n

(baseline/follow-up)

Outcomeat

baseline

Outcomeat

follow-up

ICC

Difference

inchan

gebetweengroups,

mean(95%

CI)*

Pvalue†

Interven

tion

Control

Interven

tion

Control

Interven

tion

Control

Prim

aryoutcome

HbA1c(%

)16

2/14

716

4/15

67.8(1.5)

7.6(1.1)

7.6(1.2)

7.3(1.0)

,0.00

120.05(2

0.34to

0.23

)0.70

8HbA1c(m

mol/mol)

162/14

716

4/15

662

(16)

59(12)

59(13)

56(10)

,0.00

120.60(2

3.72to

2.52

)0.70

7

Secondaryoutcomes

Systolic

BP(m

mHg)

162/14

516

4/15

514

0.3

(18.4)

137.8

(16.8)

136.4(17.5)

137.5

(16.9)

0.019

23.63(2

7.26to

0.00

)0.05

0Diastolic

BP(m

mHg)

162/14

416

4/15

583

.1(10.4)

78.7

(10.2)

79.6

(9.9)

79.2

(11.2)

,0.00

124.01

(26.23

to21.78)

,0.001

LDLcholesterol(mmol/L)

159/14

616

4/15

42.8(1.1)

2.5(1.1)

2.7(1.0)

2.6(1.0)

0.040

20.21

(20.39

to20.02)

0.03

3

Additionalcharacteristics

BMI(kg/m

2)

162/14

616

4/15

430

.5(5.3)

30.7

(5.9)

30.0

(4.9)

30.8

(5.8)

20.24(2

0.62to

0.14

)0.21

3HDLcholesterol(mmol/L)

161/14

716

4/15

61.2(0.3)

1.3(0.4)

1.2(0.3)

1.3(0.5)

20.05(2

0.13to

0.02

)0.18

2Totalcholesterol(mmol/L)

162/14

716

3/15

65.0(1.2)

4.7(1.1)

4.9(1.1)

4.7(1.1)

20.08(2

0.28to

0.13

)0.46

9Waist/hip

ratio

Male‡

87/79

91/84

1.02

(0.08)

1.01(0.07)

1.01(0.06)

1.00

(0.06)

0.01

(20.01

to0.03)

0.37

2Female‡

74/66

62/60

0.92

(0.06)

0.93(0.09)

0.92(0.06)

0.94

(0.11)

20.01(2

0.03to

0.02

)0.52

1Cap

illaryfastingblood

glucose

(mmol/L)

162/14

516

4/15

48.4(2.5)

7.7(2.2)

7.9(2.0)

7.3(1.9)

20.14(2

0.69to

0.41

)0.61

2

Values

aremean(SD),unless

otherwisestated

.*Valueinterpretableinrelationto

interven

tiongroup:a

negativevalueindicates

greaternegativechange,andapositive

valuegreaterpositive

chan

geinthe

interven

tiongroupcompared

withcontrolsubjects.†ttestforindep

enden

tsamples.‡Waist

circumference

(cm)/hip

circumference

(cm).

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HbA1c, BP, or LDL cholesterol levelbetween the control and interventiongroups could be shown after 12 months.On the other hand, a recent review (32)assessing the effects of the CCM ondiabetes patients in the United Statesfound that the CCM is effective inimproving the health of people whohave diabetes and are in primary care.The authors emphasized in their reviewthat no single component of the CCMwas found to be crucial for improvedoutcomes; incorporating multiplecomponents together in the sameintervention can help facilitate betterCCM implementation (32). Shojaniaet al. (33) concluded in 2004 thatmultifaceted interventions to improvethe quality of diabetes care have agreater chance of success than single-faceted interventions; this finding hasbeen confirmed by several otherreviews addressing diabetes care butalso other chronic diseases (34,35).The CCM obviously represents such amultifaceted intervention, but,surprisingly, many trials do not reflect itscore elements (12).

A strength of this trial is that it is a studywithin a real-life setting, reflecting thesituation as it occurs in most Europeancountries, with small inexperiencedpractices, regarding such approachesand a nonexistent culture of involvingpractice nurses in the care. Therefore,our results are not only importantregarding the disease-specificoutcomes; they also prove that the CCMapproach can be implemented withacceptable effort in daily primary care.The CCM has shown positive effects inseveral chronic diseases including

diabetes (26,27,36–38), but evidenceregarding implementation in small,often single-handed primary carepractices, which is the most commontype of practice in many Europeancountries, is still rare (39).

This is a pragmatic cluster randomizedcontrolled trial. Some limitations shouldbe acknowledged. First of all, due to thestudy design, it was not possible to blindPCPs and practice nurses to groupallocation, which might have influencedthe results or might have led to a morepronounced effect of the intervention.Second, we scheduled follow-upassessments 1 year after baselineassessments and the onset of theimplementation of the intervention,respectively. We first planned follow-upassessments after 2 study years toobtain a longer implementation periodas the basis of our analyses. But manyPCPs who were allocated to the controlgroup also wanted to implement theteam approach after the end of thestudy, so we could not let them wait foranother year. Finally, cluster effectsmight influence such trials. We haveadjusted our power calculation to thisbut also calculated the ICC of the clinicalvariables. However, it has to bementioned that a small cluster effectoccurred only regarding the LDLcholesterol level; interestingly, HbA1cand BP levels showed no clusteringat all.

A chronic care approach conductedaccording to the CCM and involvingpractice nurses in diabetes careimproved the cardiovascular risk profileand was experienced by patients as abetter structured form of care. Our

study showed that care according to theCCM can be implemented even in smallprimary care practices, which stillrepresent the usual structure for care inmost European health care systems.

Acknowledgments. The authors thank theprimary care physicians, practice nurses, andtype 2 diabetes patients who made this studypossible with their enthusiastic participation.

Funding. This study was supported by grantsfrom the Swiss Academy of Medical Sciences(grants RRMA 8-09 and RRMA 13/10) and fromthe Margrit und Ruth Stellmacher Foundation.

Duality of Interest. This study was supportedby a grant from A. Menarini AG, Switzerland. Noother potential conflicts of interest relevant tothis article were reported.

The writing of the report and the decision tosubmit the article for publication were entirelyindependent of the funders. The study fundershad no input into the study design or analysis, orthe interpretation of data.

Author Contributions. A.F. contributed to theconception and design of the study, organizeddata collection and data management,organized the recruitment of primary carephysicians, conducted statistical analyses,organized and conducted the interactiveworkshops with the primary care physicians andpractice nurses, and wrote the first draft of themanuscript. O.S. contributed to the conceptionand design of the study, provided clinical input,developed the traffic light scheme, conductedstatistical analyses, and contributed to theinterpretation of the data. C.C. contributed tothe conception and design of the study,organized data collection and management,provided clinical input, developed the trafficlight scheme, organized and conducted theinteractive workshops with the primary carephysicians and practice nurses, and contributedto the interpretation of the data. J.R. organizedthe data collection and management, andorganized and conducted the interactiveworkshops with the primary care physicians andpractice nurses. U.H. contributed to theconception and design of the study, provided

Table 3—Patient-reported secondary outcome PACIC: scores at baseline and follow-up in type 2 diabetes patientsper allocated group

PACIC

Participants at baseline/follow-up, n Outcome at baseline Outcome at follow-up

P value*Intervention Control Intervention Control Intervention Control

Summary score† 148/129 142/135 3.1 (0.9) 3.2 (0.8) 3.3 (0.8) 3.2 (1.0) 0.001

Patient activation 153/135 153/139 3.8 (1.1) 3.9 (1.2) 3.9 (1.1) 3.9 (1.2) 0.032

Delivery system 148/131 147/140 3.8 (0.9) 3.9 (0.8) 3.9 (0.9) 3.7 (0.9) ,0.001

Goal setting 147/131 148/137 2.8 (0.9) 2.9 (1.0) 3.1 (1.0) 2.9 (1.1) 0.003

Problem solving 149/131 146/135 3.1 (1.3) 3.4 (1.2) 3.4 (1.2) 3.4 (1.2) 0.016

Follow-up 146/129 142/137 2.6 (1.0) 2.7 (1.1) 2.7 (1.0) 2.6 (1.2) 0.048

Values are mean (SD), unless otherwise stated. *Nonparametric Mann-Whitney U test. †One missing value was allowed and was replaced by themean value of the remaining items.

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statistical input, and contributed to theinterpretation of the data. T.R. contributed tothe conception and design of the study,provided clinical input, developed the trafficlight scheme, organized the recruitment ofprimary care physicians, organized andconducted the interactive workshops with theprimary care physicians and practice nurses,conducted statistical analyses, and contributedto the interpretation of the data. All authorscontributed to successive drafts of themanuscript, and read and approved the finalversion of the manuscript. A.F. is the guarantorof this work and, as such, had full access to allthe data in the study and takes responsibility forthe integrity of the data and the accuracy of thedata analysis.

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