Congruency of diabetes care with the Chronic Care Model in different Swiss health care organisations from the patients’ perspective: A cross sectional study

DOI: https://doi.org/10.4414/smw.2014.13992

Anja Frei, Oliver Senn, Felix Huber, Marco Vecellio, Johann Steurer, Katja Woitzek, Thomas Rosemann, Claudia Steurer-Stey

Summary

QUESTIONS UNDER STUDY: Patients with chronic illnesses like diabetes mellitus benefit from care following the concept of the Chronic Care Model. To improve quality and to be responsive to patients’ needs reliable data on patients’ view of care in different healthcare settings are required. We evaluated the congruency of diabetes care with the Chronic Care Model between managed and non-managed care organisations from a patient’s perspective.

METHODS: We compared type 2 diabetes patients from non-managed care with a managed care organisation in Switzerland. We evaluated differences between these settings with the Patient Assessment of Chronic Illness Care 5A questionnaire (PACIC 5A; scale from 1–5) that combines the PACIC and the 5A-approach of physicians’ counselling.

RESULTS: 374 patients completed the PACIC 5A (326 from non-managed care settings, 48 from managed care). The adjusted average PACIC summary score was 3.18 in the non-managed care compared to 3.49 in the managed care sample (p = 0.046). Managed care patients scored significantly higher in the subscales goal setting (2.86 vs 3.29; p = 0.015), advice (3.23 vs 3.64; p = 0.014), assist (2.98 vs 3.44; p = 0.016) and arrange (2.50 vs 2.88; p = 0.049).

CONCLUSIONS: Our data from different health care settings suggest that managed care is recognised by type 2 diabetes patients as care that is more congruent with the Chronic Care Model and offers more intense behavioural counselling and self-management support compared with usual primary care in Switzerland. Future research should evaluate larger, more comparable patient groups.

List of abbreviations

CCM  Chronic Care Model

ACIC  Assessment of Chronic Illness Care

PACIC  Patient Assessment of Chronic Illness Care

Non-MCO  Non-Managed Care Organisation group

MCO  Managed Care Organisation group

CARAT  Chronic Care for Diabetes Study

Introduction

Patients with chronic illnesses like diabetes mellitus benefit from care following the concept of the Chronic Care Model (CCM) [1]. This model is based on six core elements: healthcare organisation, delivery system design, clinical information systems, decision support, community resources and self-management support. Together, these elements are designed to facilitate and produce effective interactions between proactive primary care practice teams and empowered patients with the aim to improve processes and outcomes in chronic illnesses [2].

Few instruments are available to assess to what extent provided care is congruent with the CCM. To enable this, the Assessment of Chronic Illness Care (ACIC) has been developed [3]. This questionnaire is completed by healthcare team members and is particularly useful for helping teams to identify gaps and to improve the care process. The shortcoming of the ACIC is that only the physicians and institutions perspective is assessed and this does not necessarily reflect how patients view the care they receive. To overcome this shortage the Patient Assessment of Chronic Illness Care (PACIC) has been developed to assess congruency of provided health care to the CCM from the patients’ point of view. The original PACIC has been subsequently expanded in the PACIC 5A with the additional assessment to what extent physicians’ counselling reflects the 5A-approach (assess, advise, agree, assist and arrange) [4, 5].

We recently compared the delivery of care for patients with diabetes between managed care, group and single practices in Switzerland by using the ACIC. The managed care practices scored significantly better than the other practices [6]. The aim of this study was to evaluate the patients’ perspective on CCM congruent diabetes care and to assess to what extent physicians’ counselling reflects the 5A-approach between non-managed care and managed care primary practices.

Methods

This study was conducted in a cross sectional study design.

Patient recruitment

Patients from the non-managed care group (non-MCO) participated in the Chronic Care for diabetes study (CARAT) [7, 8]. CARAT challenges the hypothesis that implementing elements of the CCM improves quality of care and outcomes. These elements change the organisation of care via trained practice nurses, who provide information and skills to patients.

Non-managed care group

A total of 30 primary care practices participated in CARAT, 10 were single practices and 20 were group practices from the German speaking part of Switzerland. Eligible patients were identified through the general practitioners’ registry based on lab results and received an invitation letter from the general practitioners with information about the study. Patients were included in consecutive order of attendance in the practice, regardless of the reason for the encounter. The inclusion criteria were adulthood (age >18 years), diagnosis of type 2 diabetes mellitus according to international diagnostic criteria [9] and at least one HbA1c level of ≥7.0% measured within the preceding year. The latter criterion was formulated because the aim of CARAT was to reduce HbA1c values by 0.5% points considering the current recommendations in guidelines (HbA1c = 6.5%) at study onset. Detailed method and design of the CARAT study have been published elsewhere [7].

Managed care group

Patients for the managed care organisation group (MCO) were recruited in consecutive order between February and May 2011 from the mediX group practice in Zurich. Inclusion criteria were adulthood (age >18 years) and diagnosis of type 2 diabetes mellitus according to international diagnostic criteria [9]. The mediX organisation is one of the first managed care organisations in Switzerland, founded in 1998. Coordination of care and a team based patient centred approach is a focus. Information is shared with patients and by providers, supported by electronic health records and collaboration within a multiprofessional team including a diabetes nurse, a nutritionist and another specialist when needed. In addition an internet-based clinical information and decision support system for diabetes patients exists that can be used during consultations. Health professionals have access to mediX guidelines which fulfill the demand of evidence base and are based on national and international guidelines, but are more comprehensive summarising the key elements of management for primary care. The mediX guidelines are independent from any pharmaceutical sponsoring.

Congruence with the Chronic Care Model (CCM) and the 5A counselling approach from the patients’ perspective

Patients’ assessment of provided care was quantified with the Patient Assessment of Chronic Illness Care 5A (PACIC 5A) that combines the assessment of care according to the key elements of the CCM (PACIC) with the patients’ assessment to what extent physicians’ counselling reflects the 5A-approach (assess, advise, agree, assist and arrange) [10, 11]. The “5A” is the recommended approach for behavioural changes according to the US Preventive Services Task Force (USPSTF) [10]. Glasgow et al. first validated the PACIC 5A in a sample of diabetes patients in 30 primary care practices [11]. In the mean time it was validated also for other chronic conditions, and a German version of the PACIC 5A is available [5].

The PACIC 5A captures the time period of the last six months and includes 26 items (the original 20 PACIC items assessing five scale constructs: patient activation, delivery system/practice design, goal setting/tailoring, problem solving/contextual, follow-up/coordination, and six additional items to produce subscales reflecting each of the 5As of behavioural counselling). “Patient activation” assesses to what extent the patient was motivated and supported by the physician to initiate changes. “Delivery system/practice design” assesses if the patient was supported e.g., by booklets and how satisfied the patient was with the organisation of care. “Goal setting/tailoring” assesses to what extent general instructions and suggestions were adapted to the personal situation. “Problem solving/contextual” addresses how the physician dealt with problems, which interfered with achieving predefined goals. Finally, “Follow-up/coordination” addresses how frequently and consistently the whole process was followed-up. The items are scored on a 5–point Likert scale, ranging from 1 (= never) to full accordance (5 = always). The PACIC summary score is the average of items 1–20, the 5A summary score is the average of items 1–4 and 6–26 (the instrument is available online at: http://improvingchroniccare.org/tools/pacic.htm.).

Data collection and data security

The ethics committee of the Canton of Zurich approved the study and provided a “certificate of unobjectability”. After giving informed consent the PACIC 5A questionnaire was handed out to the patients by the physician or the practice nurse with a stamped envelope with the postal address of the study centre. Patients were informed that neither the physicians nor the practice team had any possibility to be informed of their answers. An independent research assistant of the university anonymised the data and entered them directly into SPSS (version 18.0 or higher). All study related data and documents were stored on a protected server of the University of Zurich. Only members of the study team could access the respective files. Intermediate and final reports were stored in the office of the Institute of General Practice at the Zurich University Hospital.

Statistical analyses

Continuous variables are presented as means and standard deviations (±), categorical data as frequencies and percentages. Mean differences between the MCO and non-MCO samples were calculated unadjusted using t-tests for independent samples and using analysis of covariance adjusted for HbA1c, sex, age, years of education, living situation and nationality.

Results

Patient characteristics

In total, 374 patients of whom 57.8% were male with a mean age of 67.8 ± 10.7 years participated in the study. 326 patients were non-MCO study participants, 48 were recruited from the MCO. Table 1 shows patient characteristics for both groups. Non-MCO study participants were younger and had a higher HbA1c level (≥ one HbA1c level of ≥7.0% measured in the preceding year was an inclusion criterion). More patients in this group were still working. The percentage of immigrants was higher in the MCO population. Patients from the two samples did not significantly differ in terms of gender, education, living together with a partner or family (table 1).

Table 1:Patient characteristics between the non-managed care and managed care study samples.
  Non-MCO sample (n = 326) MCO sample (n = 48)
  Mean ± SD or n (%) Mean ± SD or n (%)
Age (years) 67.0 ± 10.6 73.3 ± 10.3
Male gender (n, %) 187 (57.4) 29 (60.4)
HbA1c (%) 7.7 ± 1.3 7.0 ± 0.6
Nationality Swiss (n, %) 291 (91.8) 38 (79.2)
Living together with partner/family (n, %) 246 (78.3) 29 (65.9)
Still working (n, %) 100 (32.2) 6 (13.6)
Education (years) 11.6 (3.2) 10.6 (2.9)

PACIC and 5A scores

The adjusted average PACIC summary score was 3.18 (SE = 0.05) in the non-MCO study sample compared to 3.49 (SE = 0.14) in the MCO sample. This difference was statistically significant (p = 0.046). MCO patients also scored higher than non-MCO participants in the five PACIC subscales with significance for the subscale goal setting.

For the adjusted average 5A summary score as well as for the 5A subscores, again a trend for higher scores in the MCO sample was detectable. Patients treated in MCO compared to the non-MCO study participants reported statistically significant higher values for the advice, assist and arrange subscales (table 2).

We also compared our MCO sample with the PACIC 5A data originally published by Glasgow et al. (2005) [4] including a sample of 363 diabetes type 2 patients. Patients in Glasgow’s study were younger compared to our population (64.1 ± 11.9 vs 67.8 ± 10.7 years) and more patients were female than patients in our samples (52.8% vs. 42.2%). The patients from our MCO sample scored higher in the PACIC summary score and all subscores except for follow-up/coordination, where they scored equally. The majority of the non-MCO population scores in Swiss single and group practices were comparable to the original scores (table 2).

Table 2: Results for PACIC summary score, 5A summary score and PACIC subscales per non-managed care and managed care patients in comparison to the original data.
    Glasgow et al. (2005) (n = 336) Non-MCO sample (n = 326) MCO sample (n = 48) p-value
PACIC summary score Mean (SD)1) 3.2 (0.9) 3.18 (0.85) 3.39 (0.68) 0.072
Mean adj. (SE)2)   3.18 (0.05) 3.49 (0.14) 0.046
Patient activation Mean (SD) 3.6 (1.1) 3.83 (1.13) 3.73 (0.95) 0.519
Mean adj. (SE)   3.83 (0.07) 3.85 (0.19) 0.913
Delivery system Mean (SD) 3.5 (0.9) 3.87 (0.82) 3.98 (0.65) 0.319
Mean adj. (SE)   3.88 (0.05) 4.10 (0.14) 0.123
Goal setting / tailoring Mean (SD) 3.0 (1.0) 2.86 (0.98) 3.19 (0.82) 0.020
Mean adj. (SE)   2.86 (0.06) 3.29 (0.16) 0.015
Problem solving Mean (SD) 3.4 (1.1) 3.26 (1.22) 3.58 (0.88) 0.039
Mean adj. (SE)   3.28 (0.07) 3.62 (0.20) 0.116
Follow-up / coordination Mean (SD) 2.9 (1.0) 2.66 (1.05) 2.87 (0.97) 0.229
Mean adj. (SE)   2.66 (0.06) 2.98 (0.18) 0.094
5A summary score Mean (SD) 3.2 (1.0) 3.09 (0.88) 3.31 (0.71) 0.099
Mean adj. (SE)   3.09 (0.05) 3.41 (0.16) 0.055
Assess Mean (SD) 3.3 (1.0) 3.20 (1.07) 3.36 (0.86) 0.257
Mean adj. (SE)   3.20 (0.06) 3.45 (0.18) 0.184
Agree Mean (SD) 3.4 (1.0) 3.68 (0.96) 3.59 (0.91) 0.563
Mean adj. (SE)   3.68 (0.06) 3.75 (0.16) 0.692
Advise Mean (SD) 3.3 (1.0) 3.22 (0.91) 3.50 (0.80) 0.062
Mean adj. (SE)   3.23 (0.05) 3.64 (0.16) 0.014
Assist Mean (SD) 3.1 (1.0) 2.98 (1.05) 3.42 (0.83) 0.002
Mean adj. (SE)   2.98 (0.06) 3.44 (0.18) 0.016
Arrange Mean (SD) 2.7 (1.0) 2.51 (1.05) 2.78 (1.01) 0.108
Mean adj. (SE)   2.50 (0.06) 2.88 (0.18) 0.049
1) Independent sample t-test between non-MCO and MCO sample 2) Based on analysis of covariance adjusted for HbA1c, sex, age, years of education, living situation, nationality

Strength and limitations

The strength of our study is the objective assessment of the patients’ perspective of diabetes care with a validated instrument that assesses congruence of care with the CCM and the 5A behavioural counselling approach in different primary care settings. However, some important limitations with respect to type and size of study populations, comparability of the populations and generalisability of our results exist. Two major limitations have to be considered and discussed in more detail; firstly, the differences in patients’ characteristics and secondly the relationship between small sample size and small effect size in the MCO group. An inclusion criterion for the non-MCO group was at least one HbA1c level of 7% or higher in the preceding year. This criterion was not applied to the MCO group. Non-MCO patients had higher HbA1c levels, were younger and included a smaller proportion of immigrants compared to MCO patients. Even the PACIC is not likely to be influenced by patients’ cultural background, our analysis was adjusted for these confounders. In addition, patients participating in the CARAT study reflected our sample of “usual” Swiss primary care practices. It is known that patients included in a trial often show better results than patients treated in usual care.

The MCO mediX is one of the first managed care organisations in Switzerland founded in 1998 with focus on gate keeping and coordinated care, on a team based patient centred approach and active quality improvement for people with chronic illnesses. Particularly for the chosen condition diabetes, strategies for coordinated care and an internet-based clinical information and decision aid system exists. It is possible therefore that our results cannot be transferred to patients with diabetes in other managed care organisations. A further limitation is the small sample size of the MCO and that generalisability is limited. The participants in the MCO group were recruited in only one practice compared to 30 practices recruiting participants for the non-MCO group. A small sample is more prone to showing significant effects by chance. However, a small sample size also reduces the power for detecting significant differences between the groups. With a larger MCO sample the differences revealed might therefore have been more striking. In addition, we cannot exclude a selection bias in the recruitment of the MCO sample, since these patients represent only a part of all type 2 diabetes patients treated in the MCO. However, patients from the sample (n = 48) differed only slightly from the population of MCO patients (n = 541) in terms of age (73.3 vs 68 years), gender (32% vs 39.6% women) and mean HbA1c (7.0% vs 7.3%).

In summary, our data from different health care settings suggest that managed care is recognised by type 2 diabetes patients as care that is more congruent with the CCM and that offers more intense behavioural counselling and self-management support compared with usual primary care in Switzerland. Future research should evaluate larger, more comparable patient groups.

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Notes

Funding / potential competing interests: The Chronic Care for diabetes study (patients included from non-managed care organisation group) was supported by grants from the Swiss Academy for Medical Sciences (SAMW), grant number RRMA 8–09, Menarini AG, Switzerland and Margrit and Ruth Stellmacher Stiftung. The funders were neither involved in study design, data collection and/or data analysis nor in manuscript preparation and/or publication decisions. F. Huber is the founder and leader of the mediX group practice. M. Vecellio worked as GP at the mediX group practice and has a special interest in diabetes care. C. Steurer-Stey works at the mediX group practice as lung specialist and does not care for diabetes patients. The other authors declare no competing interests.

Authors’ contribution: Concept/design: Claudia Steurer-Stey, Anja Frei, Oliver Senn, Thomas Rosemann. Data analysis/interpretation, statistics: Anja Frei, Oliver Senn, Claudia Steurer-Stey, Johann Steurer. Data collection: Felix Huber, Marco Vecellio, Katja Woitzek, Claudia Steurer-Stey, Anja Frei. Drafting article: Claudia Steurer-Stey, Anja Frei. Critical revision of article: all authors.