Background
The rising prevalence of chronic diseases such as type 2 diabetes, worldwide, puts increasing pressure on health systems and especially on primary health care. New models of service delivery focusing on patient-centered and coordinated care have been initiated aiming at improving the quality of care for persons with chronic illnesses, which is a political priority in many countries [
1] and endorsed by the WHO [
2]. The influential Chronic Care Model (CCM) [
3] provides a promising framework to enhance evidence-based chronic care [
4]. It describes a patient-centered care approach that is also planned and proactive population-based, and thus different from a reactive acute-oriented care. The evidence concerning the potential of the model, or components of it, to improve care processes, outcomes of care and health care resource use is growing [
1,
5] and the model has been proposed as an effective framework in primary care for improving quality of diabetes care [
6‐
8]. The principles of the CCM have been included in disease management programs in different countries, for example, the USA, Canada, England and Australia [
1] and, accordingly, in different health-care systems.
In evaluating the public health impact of new frameworks – like the CCM – in health care, adequate instruments, that is, measures of quality that are reliable and valid, are needed [
9]. Moreover, instruments covering the patient perspective to quality of care are crucial [
10‐
12]. The Patient Assessment of Chronic Illness Care (PACIC) has been designed to assess quality of care for patients with a chronic illness [
13]. It measures the different dimensions of the CCM from the perspective of the patient, focusing on self-management support – including collaborative goal setting, problem solving and follow-up – as well as planned proactive care.
The PACIC scale was developed and validated by Glasgow et al. in the USA for patients with a variety of chronic diseases [
13] and for patients with diabetes type 2 [
14]. It has been translated and validated into Dutch, Spanish, Danish, French, Spanish [
9,
15‐
17] and German (PACIC-5a) [
18]. The psychometric performance of the English scale has been studied also outside USA: in Australia and the UK [
12,
19]. In a study comparing different generic instruments, the PACIC was evaluated being among the most promising as regards patients’ experience of quality of integrated care [
11].
The Finnish Ministry of Social Affairs and Health proposes implementation of the CCM in primary healthcare centers [
20], and as a Finnish validated version of the PACIC scale was not available and earlier studies have suggested the need for validating the scale when adapting it to different healthcare systems, the aim of our study was to evaluate the psychometric properties of the Finnish translation of the PACIC, in a large register-based sample of patients with type 2 diabetes, in terms of reliability and validity.
Results
Responses were received from 2866 respondents (response rate 56%). The mean age of respondents was 63.4 (SD 7.8), 55.9% were male and 40.2% had a higher professional educational level. The mean duration of diabetes type 2 was 8.3 years (SD 6.0). Of the respondents, 2511 (87.6%) responded to all 20 PACIC items, and 93.5% to at least 17, and these 2681 respondents were included in the study sample. In this sample, the mean age was 63.2 (SD 7.7), 55.8% were male, 41% had a higher professional educational level and the mean duration of diabetes was 8.3 years (SD 5.9), thus being quite comparable with the whole sample. Municipal primary healthcare centers were the main provider of diabetes care for 77% of respondents; 18% received their care through occupational healthcare services and 4% through private healthcare centers. The majority (75%) used oral diabetes medication. Demographic and clinical data on the study sample as well as the whole sample, in order to discern possible differences, are provided in Table
1.
Table 1
Demographic and clinical data
Gender |
Male | 55.8 | 55.9 |
Age | 63.2 (7.7) | 63.4 (7.8) |
Age |
27 to 54 | 13.0 | 12.7 |
55 to 64 | 38.7 | 37.9 |
65 to 75 | 48.3 | 49.4 |
Professional education | | |
Upper secondary education (vocational school) or less | 59.0 | 59.8 |
Higher education (college, polytechnic, university) | 41.0 | 40.2 |
Marital status |
Single | 9.6 | 9.8 |
Married/cohabiting | 67.0 | 66.5 |
Widowed/divorced | 23.4 | 23.7 |
Duration of diabetes |
1–3 years | 19.7 | 19.5 |
4–10 years | 53.1 | 52.9 |
More than 10 years | 27.3 | 27.6 |
Medicationa |
Oral drugs only | 74.6 | 74.7 |
Oral drugs + insulin/insulin only | 24.1 | 24.1 |
Other (e.g. GLP-1 analog) | 1.3 | 1.2 |
Service provider responsible for care of diabetesb | |
Municipal healthcare center | 77.2 | 77.6 |
Occupational healthcare service | 18.4 | 18.2 |
Private healthcare center | 4.4 | 4.3 |
Perceived autonomy support (HCCQ) | range 1–5 | 3.5 (1.2) | 3.6 (1.2) |
Perceived competence | range 1–5 | 4.2 (0.9) | 4.2 (0.9) |
Diabetes empowerment | range 1–5 | 4.0 (0.7) | 4.0 (0.7) |
Self-reported health |
Poor | 50.7 | 50.7 |
Good | 26.6 | 26.4 |
Very good | 22.7 | 22.9 |
Continuity of care |
Regular physician (yes) | 74.3 | 74.5 |
Regular nurse (yes) | 51.5 | 51.5 |
The item response on the PACIC scale was high with only small numbers of missing values (0.5–1.1%), also in the whole sample (4–6%; Table
2). Floor effects on the subscales were 5.7–24.9%, over 20% for two of the subscales (
problem solving and
follow-up/coordination), whereas ceiling effects were low (0.3–5.3%). On the total PACIC scale, floor and ceiling effects were low (2.8/0.1); when having a stricter lower and upper limit of < 1.5 and > 4.5, the effects were 17.8 and 0.9 (Table
3).
Table 2
Missing values on PACIC itemsa
1. Asked for my ideas when we made a treatment plan | 0.8 | 4.7 |
2. Given choices about treatment to think about | 0.8 | 5.3 |
3. Asked to talk about any problems with my medicines or their effects | 0.3 | 4.5 |
4. Given a written list of things I should do to improve my health | 0.7 | 5.0 |
5. Satisfied that my care was well organized | 0.7 | 4.2 |
6. Shown how what I did to take care of my illness influenced my condition | 0.3 | 4.0 |
7. Asked to talk about my goals in caring for my illness | 0.2 | 4.4 |
8. Helped to set specific goals to improve my eating or exercise | 0.5 | 5.0 |
9. Given a copy of my treatment plan | 0.7 | 5.4 |
10. Encouraged to go to a specific group or class to help me cope with my chronic illness | 0.2 | 5.0 |
11. Asked questions, either directly or on a survey, about my health habits | 0.3 | 4.7 |
12. Sure that my doctor or nurse thought about my values and my traditions when they recommended treatments to me | 1.1 | 6.0 |
13. Helped to make a treatment plan that I could carry out in my daily life | 0.4 | 5.3 |
14. Helped to plan ahead so I could take care of my illness even in hard times | 0.7 | 6.0 |
15. Asked how my chronic illness affects my life | 0.3 | 5.4 |
16. Contacted after a visit to see how things were going | 0.2 | 5.1 |
17. Encouraged to attend programs in the community that could help me | 0.3 | 5.4 |
18. Referred to a dietician, health educator, or counselor | 0.4 | 5.4 |
19. Told how my visits with other types of doctors, like an eye doctor or surgeon, helped my treatment | 0.2 | 4.8 |
20. Asked how my visits with other doctors were going | 0.3 | 5.2 |
Table 3
Descriptive data on subscales and complete PACIC scale (Study sample; n = 2681)
Patient activation (3 items; no missing items allowed) | 1.5 | 17.2/4.7 | 2.54 (1.21) | 2.3 | 1.7–3.3 |
Delivery system design/decision support (3 items; no missing items allowed) | 1.5 | 5.7/5.3 | 3.12 (1.06) | 3.3 | 2.3–4.0 |
Goal setting/tailoring (5 items; 1 missing item allowed) | 0 | 12.7/0.6 | 2.25 (0.93) | 2.2 | 1.4–2.8 |
Problem solving/contextual (4 items; 1 missing item allowed) | 0.4 | 20.2/2.6 | 2.29 (1.10) | 2.0 | 1.3–3.0 |
Follow up/coordination (5 items; 1 missing item allowed) | 0.1 | 24.9/0.3 | 1.79 (0.76) | 1.6 | 1.2–2.2 |
PACIC total score (20 items; 3 missing items allowed) | 0.1 | 2.8/0.1 (17.8/0.9b) | 2.32 (0.84) | 2.3 | 1.7–2.9 |
The mean total PACIC score was 2.32 (SD 0.84) and the median 2.3, with an IQR of 1.7–2.9. The total PACIC scale showed a reasonable distribution and approached normal distribution; however, it was moderately skewed (skewness 0.530, kurtosis − 0.248). The subscale means ranged from 3.12 (1.06) for
delivery system design/decision support to 1.79 (0.76) for
follow-up/coordination (Table
3).
Alpha reliabilities were acceptable to excellent, and as follows: total PACIC scale 0.94 (20 items), patient activation 0.85 (3 items), delivery system design/decision support 0.74 (3 items), goal setting/tailoring 0.80 (5 items), problem solving/contextual 0.86 (4 items) and follow-up/coordination 0.74 (5 items).
The inter-correlation (Spearman’s rho) between the subscales was moderate to high, being highest between the problem-solving and goal-setting scales (0.78) and goal-setting and decision-support scales (0.71), whereas the follow-up scale was the least correlated with the other scales, and lowest with the patient-activation scale (0.51). The goal-setting (0.91) and problem-solving (0.90) scales correlated the highest with the total PACIC scale and the follow-up scale the least (0.76).
The subgroup analysis showed differences in total PACIC scores according to gender, age, marital status, medication, duration of disease and service provider (Table
4). However, the strengths of these associations were modest. As concerns patients’ demographic characteristics, age had the strongest association (Spearman’s rho − 0.12) with the total PACIC score, and among clinical characteristics, the strongest association was found between service provider and PACIC (0.14).
Table 4
Results for PACIC by demographic and clinical characteristics (Study sample; n = 2681)
Gender |
Men | 2.36 (0.84) | 0.001 | − 0.07 | 0.000 |
Women | 2.26 (0.84) | | | |
Age |
27–54 | 2.49 (0.89) | 0.000a | −0.12 | 0.000 |
55–64 | 2.40 (0.87) | | | |
65–75 | 2.21 (0.84) | | | |
Professional education |
Upper secondary education or less | 2.31 (0.84) | 0.90 | 0.01 | 0.806 |
Higher education | 2.32 (0.84) | | | |
Marital status |
Single | 2.42 (0.87) | 0.000 | −0.10 | 0.000 |
Married/cohabiting | 2.34 (0.84) | | | |
Widowed/divorced | 2.16 (0.80) | | | |
Duration of diabetes |
≤ 3 years | 2.41 (0.85) | 0.028 | − 0.05 | 0.011 |
4–10 years | 2.32 (0.85) | | | |
> 10 years | 2.27 (0.83) | | | |
Medication |
Oral drugs only | 2.29 (0.83) | 0.001 | 0.06 | 0.002 |
Oral drugs + insulin/insulin only/other | 2.41 (0.86) | | | |
Service provider responsible for care |
Municipal healthcare | 2.25 (0.82) | 0.000b | 0.14 | 0.000 |
Occupational or private healthcare | 2.54 (0.89) | | | |
Principal component analysis (PCA) identified a two-factor solution, which explained 53% of the variance. When allowing for a third factor (which almost reached the extraction criterion: Eigenvalue > 1), 58% of the variance was explained (Table
5). In the two-factor solution, Factor 1 is ‘shared decision making and self-care support’ and Factor 2 ‘planned care and social support’, whereas in the three-factor solution, Factor 1 is ‘shared decision making and satisfaction’, Factor 2 ‘coordinated care and social support’, and Factor 3 ‘personal goal-setting and problem-solving’. When performing a PCA separately for patients receiving care in municipal healthcare centers and those receiving care in occupational or private healthcare services (data not shown), an identical three-factor solution as in Table
5 was identified among patients in municipal healthcare centers (only the loading values were different) and nearly an identical two-factor solution among patients in occupational or private healthcare services (only one item, no. 4, loaded differently).
Table 5
Factor loadings of the PACIC items using Oblimin rotationc (Study sample; n = 2681)
Patient activation |
1. Asked for my ideas when we made a treatment plan |
0.86
| |
0.74
| | |
2. Given choices about treatment to think about |
0.73
| |
0.63
| | |
3. Asked to talk about any problems with my medicines or their effects |
0.76
| |
0.73
| | |
Delivery system design/Decision support |
4. Given a written list of things I should do to improve my health | 0.43 | | | |
−0.63
|
5. Satisfied that my care was well organized |
0.82
| |
0.81
| | |
6. Shown how what I did to take care of my illness influenced my condition |
0.85
| |
0.70
| | |
Goal setting/Tailoring |
7. Asked to talk about my goals in caring for my illness |
0.74
| |
0.50
| | −0.44 |
8. Helped to set specific goals to improve my eating or exercise |
0.57
| | | |
−0.61
|
9. Given a copy of my treatment plan | | 0.45 | | |
−0.70
|
10. Encouraged to go to a specific group or class to help me cope with my chronic illness | |
0.78
| |
0.55
| −0.41 |
11. Asked questions, either directly or on a survey, about my health habits |
0.57
| | 0.37 | | −0.41 |
Problem solving/Contextual |
12. Sure that my doctor or nurse thought about my values and my traditions when they recommended treatments to me |
0.73
| |
0.64
| | |
13. Helped to make a treatment plan that I could carry out in my daily life |
0.51
| 0.39 | | |
−0.64
|
14. Helped to plan ahead so I could take care of my illness even in hard times | 0.35 |
0.55
| | |
−0.60
|
15. Asked how my chronic illness affects my life | 0.43 | 0.44 | | | −0.39 |
Follow-up/Coordination |
16. Contacted after a visit to see how things were going | |
0.66
| |
0.62
| |
17. Encouraged to attend programs in the community that could help me | |
0.83
| |
0.68
| |
18. Referred to a dietician, health educator, or counselor | |
0.59
| |
0.62
| |
19. Told how my visits with other types of doctors, like an eye doctor or surgeon, helped my treatment | 0.39 | 0.33 | 0.46 |
0.50
| |
20. Asked how my visits with other doctors were going | |
0.61
| |
0.74
| |
As regards convergent and construct validity, PACIC total scores correlated well with perceived autonomy supportiveness (Spearman’s rho 0.58) and significantly also with the outcome variables, and among these, most strongly with the Diabetes empowerment scale (0.24; Table
6). The correlations with the two other outcome variables – perceived competence and self-reported health – were 0.19 respective 0.15. Continuity of care, that is, having a regular physician and/or having a regular nurse, was associated with higher PACIC scores, 2.41/2.05 (yes/no;
p < 0.001) and 2.47/2.14 (yes/no;
p < 0.001), respectively, and the strength of the associations were 0.19 and 0.20.
Table 6
Associations (Spearman’s rho) between PACIC and health care quality and outcome measures (Study sample; n = 2681)
Perceived autonomy support (HCCQ) | 0.58*** |
Continuity of care (no/yes) |
Regular physician | 0.19*** |
Regular nurse | 0.20*** |
Perceived competence | 0.19*** |
Diabetes empowerment | 0.24*** |
Self-reported health (poor/good) | 0.15*** |
Discussion
Quality improvement in healthcare services, especially in primary health care – in order to answer the challenge of a rising prevalence of chronic conditions within the population – is a focus for health policy makers in many countries. International quality improvement models and measures ensure possibilities to learn from each other, both concerning strengths and weaknesses of quality improvement efforts. To be able to track changes in standards of care, as well as to assess the effectiveness of interventions, good measures are needed [
12]. As concerns patients with chronic conditions, their evaluation of care quality and improvements in care quality are important, meaning that measures that assess specifically patients’ perceptions are crucial. In this study, we have assessed the validity and reliability of a Finnish translation of the internationally validated PACIC scale, as well as its utility, in the Finnish healthcare system.
In summary, our findings showed that the translated PACIC scale had a reasonably good validity and reliability among patients with type 2 diabetes in the Finnish primary care setting. The study had a satisfactory response rate and the majority (88%) of respondents answered all PACIC items, indicating good face validity. The validation analyses, moreover, showed that scores on the total scale were reasonably well distributed and the internal consistency was excellent. Two of the five predetermined subscales had problems with floor effects, but all these five subscales had acceptable to excellent internal consistency. In terms of construct validity, the translated PACIC scale, as hypothesized, had significant associations with care quality, i.e., perceived autonomy supportiveness – indicating convergent validity – and continuity of care, as well as outcome measures. The PCA, however, revealed a two- or three-factor structure in the current Finnish healthcare context, instead of the proposed five-dimensional.
In the majority of earlier studies, the five dimension structure of the PACIC scale has not been confirmed. Studies in different populations and healthcare systems have suggested also one-, two- and four-dimensional structures [
17,
19,
30‐
33]. Differences in the PACIC scale structure in different studies have been attributed to methodological differences, but also to real differences between healthcare systems and samples of patients [
17]. Spicer and colleagues [
21] have raised the issue whether the PACIC scale is a formative rather than a reflective measure, and thus questioned the suitability of factor analysis and internal reliability estimates. Cramm and Nieboer [
34], based on their findings in a follow-up study, however, argue that the scale can be regarded a reflective measure. Fan et al. [
33] suggest that a universally applicable factorial structure might not exist. In our study, we found different factorial structures among patients receiving care by different healthcare providers. This might suggest differences in care structures and processes, or, alternatively, as suggested by Fan et al. [
33], different priorities as concerns chronic disease care among the patients. Some earlier studies have raised questions about the utility of the PACIC subscales, and propose the use of the PACIC total score as an overall experience of chronic illness care [
14,
30,
33,
35]. Primary care personnel’s perceptions of implementation of the CCM components seem to be only weakly, though for the most part consistently, associated with patients’ perceptions of CCM (PACIC and its subscales) [
36]. More research is needed to determine the degree to which PACIC and possibly the subscales are related to patient outcomes. Moreover, comparing the relative contribution of the predetermined subscales in this regard with the contribution of subscales derived from exploratory factor analysis in the patient population of interest could be worthwhile.
Although the five dimension factorial structure was not established, the predetermined subscales, as well as the total PACIC scale, had good internal consistencies: Cronbach’s alpha being 0.94 for the total scale, and varying from 0.74 to 0.86 for the subscales, thus confirming the results of the original English version [
13]. As in our data, the subscales
delivery system design/decision support and/or
follow-up/coordination have had the lowest internal consistencies in earlier validation studies as well [
12,
13,
15,
18,
31], suggesting that this does not reflect the translation process nor the Finnish primary healthcare context [
12].
The mean scores on the total PACIC scale and the subscales were relatively low in our sample and comparable with the scores in patients with type 2 diabetes in Denmark [
37] and patients with long-term conditions in UK [
12]; in general, lower than those reported elsewhere. Consistent with earlier studies [
12,
13], especially
follow-up/coordination activities were rated low, showing problems with floor effects, as did also the
problem solving subscale in our study. According to Glasgow and colleagues [
13], these two subscales, as well as the
goal setting scale, form the core of modern chronic care, but are seldom present in the absence of specific quality improvement efforts. Although there have been care quality improvement initiatives in primary healthcare in Finland, there were still ongoing development work to implement, specifically, the Chronic Care Model at the time when the questionnaires in this study were answered, and only in selected healthcare centers. This might explain the low scores and floor effects on the two subscales. Also, when comparing different studies it has to be kept in mind that there are two main versions of the scale. In our study, as in the original study [
13], the PACIC scale is rated from ‘almost never’ to ‘almost always’; the other main version applied, extends from ‘never’ to ‘always’. Moreover, as commented earlier [
12], the clinical significance of differences in scores is not known.
The subgroup analysis revealed significant associations between PACIC scores and demographic (gender, age, marital status) as well as clinical (duration of disease, medication, service provider) characteristics; only education was not significantly associated. However, these associations were weak (≤ 0.14) and, thus, it is possible that the statistical significance reflects the larger sample size in our study. Nevertheless, earlier findings are inconsistent, also regarding direction of associations. Accordingly, it is unclear whether the scale functions differently in different subgroups and countries or whether there are differences in care quality or expectations. It has to be kept in mind that the findings we report are from unadjusted bivariate analysis, as has mostly been the case also in earlier validation studies.
As regards convergent validity, the PACIC score was – as hypothesized and consistent with earlier studies [
12] – associated with perceived autonomy support, an established measure of quality of chronic care [
24]. Moreover, the findings showed the hypothesized relationships with continuity of care and outcome measures, thus confirming the construct validity of the PACIC scale, as well as of its Finnish translation. As there has recently been calls for revisions of the PACIC scale because of changes in chronic illness care during the last decade, for example, technological advances [
35], we suggest that another way forward might be to complement the PACIC scale with other quality indicators.
Our findings are limited by the cross-sectional nature of the study, meaning that we were not able to assess all aspects of validity and reliability of the PACIC questionnaire. Thus, we did not assess reproducibility (test-retest reliability) or responsiveness. Moreover, we did not interview patients to explore their views on, and understanding of, the translated PACIC scale and its items, though the questionnaire, including the PACIC scale, was tested in a pilot study with possibilities for patients to add comments. Still, the study has a number of strengths, including a large register-based sample of patients with type 2 diabetes, receiving care in different healthcare settings.