Skip to main content
Download PDF

Patient Assessment Chronic Illness Care (PACIC) and its associations with quality of life among Swiss patients with systemic sclerosis: a mixed methods study

Orphanet Journal of Rare Diseases volume 18, Article number: 7 (2023) Cite this article

Abstract

Background

The Chronic Care Model (CCM) is a longstanding and widely adopted model guiding chronic illness management. Little is known about how CCM elements are implemented in rare disease care or how patients’ care experiences relate to health-related quality of life (HRQoL). We engaged patients living with systemic sclerosis (SSc) to assess current care according to the CCM from the patient perspective and their HRQoL.

Methods

We employed an explanatory sequential mixed methods design. First, we conducted a cross-sectional quantitative survey (n = 101) using the Patient Assessment of Chronic Illness Care (PACIC) and Systemic Sclerosis Quality of Life (SScQoL) questionnaires. Next, we used data from individual patient interviews (n = 4) and one patient focus group (n = 4) to further explore care experiences of people living with SSc with a focus on the PACIC dimensions.

Results

The mean overall PACIC score was 3.0/5.0 (95% CI 2.8–3.2, n = 100), indicating care was ‘never’ to ‘generally not’ aligned with the CCM. Lowest PACIC subscale scores related to ‘goal setting/tailoring’ (mean = 2.5, 95% CI 2.2–2.7) and ‘problem solving/contextual counselling’ (mean = 2.9, 95% CI 2.7–3.2). No significant correlations were identified between the mean PACIC and SScQoL scores. Interviews revealed patients frequently encounter major shortcomings in care including ‘experiencing organized care with limited participation’, ‘not knowing which strategies are effective or harmful’ and ‘feeling left alone with disease and psychosocial consequences’. Patients often responded to challenges by ‘dealing with the illness in tailored measure’, ‘taking over complex coordination of care’ and ‘relying on an accessible and trustworthy team’.

Conclusions

The low PACIC mean overall score is comparable to findings in patients with common chronic diseases. Key elements of the CCM have yet to be systematically implemented in Swiss SSc management. Identified gaps in care related to lack of shared decision-making, goal-setting and individual counselling-aspects that are essential for supporting patient self-management skills. Furthermore, there appears to be a lack of complex care coordination tailored to individual patient needs.

Background

Systemic sclerosis (SSc) is a rare multisystemic, autoimmune connective‐tissue disease characterized by a chronic and frequently progressive disease course. Approximately 20 in 100,000 adults are affected [1, 2]. Variability in disease severity, progression, and organ involvement challenge timely diagnosis and effective disease management contributing to high mortality [1, 3]. Approximately 75% of patients develop organ involvement within the first five years of diagnosis and early manifestations including skin fibrosis (75%), gastrointestinal symptoms (71%), lung involvement (65%), digital ulcers (34%) and cardiac involvement (32%) [3]. Except for haematopoietic stem cell transplantation for patients with rapidly progressive dcSSc and a high risk of organ failure in an early disease stage, treatments modifying the overall disease course are currently not available [4, 5]. Thus, medical management must be tailored to individual organ sequelae and disease progression, i.e., regular multidisciplinary consultations to identify organ involvement early as well as pharmacological and non-pharmacological interventions to decrease/slow disease progression and reduce organ damage [4].

At the same time, interventions should focus on improving health-related quality of life (HRQoL) of people living with SSc [6]. Over the disease trajectory, patients experience multiple physical and psychosocial problems including fatigue, hand stiffness, Raynaud’s phenomenon, digital ulcers, shortness of breath, pain, gastrointestinal symptoms, work disability, depression, anxiety (e.g., fear of disease progression), and dissatisfaction with body image [6,7,8,9,10]. Numerous studies report severely impaired physical and psychological HRQoL in SSc [10,11,12,13]. Importantly, the heterogeneous disease presentation and the symptom burden of patients living with SSc necessitate a chronic care approach including competent, coordinated, multidisciplinary collaboration as well as self-management support targeting individual patient needs [14,15,16,17]. However, prevailing models of SSc care mainly focus on acute health problems and often lack an integrated approach that addresses the complex care needs of patients [18, 19].

The Chronic Care Model (CCM) is a longstanding and widely adopted model that includes electronic health (eHealth) approaches to guide chronic illness management [19,20,21]. The model aims to improve health outcomes through effective and productive interactions between prepared, proactive practice teams and informed, activated patients. The CCM focuses on the six core elements: community resources, health system, self-management support, delivery-system design (e.g., continuity of care), decision support, and clinical information systems. A significant body of literature supports that incorporating CCM elements (e.g. self-management support, clinical decision support) into care is associated with better clinical outcomes including reduced health service use, fewer emergency department visits and lower healthcare costs [22,23,24]. The Patient Assessment of Chronic Illness Care (PACIC) is a validated tool to assess implementation of the CCM from the patient perspective [25]. Notably, several studies have shown that perceived level of chronic illness management (as measured by the PACIC) is positively correlated with patient outcomes [26,27,28]. For example, in diabetes, higher PACIC scores are associated with improved markers of glycemic control, self-management activities, physical activity and diminished distress [29, 30]. In transplant patients, higher perceived levels of chronic illness management are positively associated with treatment satisfaction and trust in the transplantation team [31].

In the rare disease space, few care models incorporate elements of the CCM [32,33,34]. On average, rare disease patients reported PACIC score of 2.5 (on a 5-point Likert scale ranging from 1 = ‘never’ to 5 = ‘always’), suggesting poorer healthcare experiences compared to reports in patients with common chronic conditions (range 1.7–4.2/5.0) [26, 35,36,37]. In relation to SSc, the association between healthcare provision and rare disease patient outcomes (e.g., HRQoL) has remained unexplored. However, the PACIC is a disease-agnostic instrument that may not address specific challenges of rare disease care (e.g., lack of treatment options and specialized healthcare) or specific patient needs regarding heterogeneity/severity of SSc. Accordingly, SSc patient experiences of chronic care in relation to the PACIC dimensions may demand further inquiry using qualitative methods.

To date, there is paucity of evidence on how CCM elements are implemented in SSc management and how patients’ care experiences relate to HRQoL. The MANagement Of Systemic Sclerosis (MANOSS) project aims to fill existing gaps in SSc care by developing an eHealth-enhanced rare disease chronic care model for SSc patients in Switzerland [38]. As part of the MANOSS project, this mixed methods study aimed to describe the current state of SSc chronic illness care and HRQoL from the patient perspective to inform the development of an integrated model of care for SSc. The quantitative phase evaluated the level of chronic care across the five dimensions measured by the PACIC scale and quality of life measured by the Systemic Sclerosis Quality of Life Questionnaire (SScQoL). The subsequent qualitative phase aimed to explain care experiences of people living with SSc with a focus on the PACIC dimensions.

Methods

Study design

The study employed an explanatory, sequential, mixed methods design [38, 39]. Briefly, we first conducted a quantitative cross-sectional survey of Swiss SSc patients (see Fig. 1). Quantitative analyses informed subsequent qualitative interviews. For qualitative interviews, we used a purposefully selected sub-sample of patients based on the maximum variation of PACIC/HRQoL score to better understand and explain quantitative findings. Ethical approval was obtained for the overall MANOSS project by the responsible Swiss ethics committee (EKNZ 2018‐01206).

Fig. 1
figure 1

Study diagram for the explanatory, sequential mixed methods design

Full size image

Quantitative data collection and analysis

Sample and setting

For the quantitative survey, we recruited a convenience sample of 101 adult patients (> 18 years) spanning a range of SSc disease severity and experiences. We recruited German- and French-speaking participants from all Swiss University Hospitals, rheumatology outpatient clinics, and the Swiss scleroderma patients’ association (www.sclerodermie.ch) [38].

Variables and measurement

Patients participating in the MANOSS cross-sectional survey (March–August 2019) completed three survey instruments (paper or web-based format) [38]. We used the validated 20-item PACIC instrument to measure care alignment with CCM. The PACIC includes five subscales addressing specific domains: (1) patient activation; (2) delivery system design/decision support; (3) goal setting/tailoring; (4) problem solving/contextual counselling; and (5) follow-up/coordination [25]. Patients rated care received from their healthcare team (e.g., physicians, nurses, physiotherapists, occupational therapists, social workers) during the past 6-months using a 5-point Likert scale (1 = ‘never’ to 5 = ‘always’). Total and subscale scores (i.e., summed items completed within that scale) are averaged across items. The 20-item PACIC demonstrates reasonable validity and reliability, including high internal consistency (α = 0.93), in patients with chronic conditions across many languages and countries when using a single-dimension structure [25, 37, 40]. However, several studies have revealed high inter-correlations between PACIC subscales and ‘lack of fit’ using the 5-dimension structure—suggesting that subscales may not always be appropriate [37, 40, 41]. Because PACIC has not been used in the context of SSc, we used the Mokken model to test the construct validity of the PACIC scale and its subscales [42]. Additional details on our validation of the PACIC-15 for SSc are provided in Additional file 1.

We used the revised German and French 29-item Systemic Sclerosis Quality of Life (SScQoL) questionnaire to measure HRQoL [43, 44]. The revised German SScQoL employs a 4-point response structure (‘Always’, ‘Usually’, ‘Sometimes’, ‘Never’) and is a valid, reliable measure [44]. The response structure of the French version was adapted according to the German version to ensure interoperable responses for the MANOSS survey (German: α = 0.97, French: α = 0.91) [44, 45]. To calculate the overall SScQoL sum score, responses are dichotomized (‘Always’ = 1, ‘Usually’ = 1, ‘Sometimes’ = 1, ‘Never’ = 0) and summed. Higher values indicate lower HRQoL [44].

We assessed self-reported comorbidities using the 12‐item Self‐Administered Comorbidity Questionnaire (SCQ) that is moderately to strongly correlated with a standard medical record-based comorbidity measure (i.e., Charlson Index) [46]. Patients with SSc often struggle to distinguish between disease-related organ involvement and comorbidities unrelated to SSc. Thus, we used the SCQ to comprehensively assess self-reported comorbidity (i.e., co-occurring diseases in an individual) [47, 48]. Participants provided sociodemographic data (sex, age, education, employment status), disease information (subset: lSSc, dSSc, Overlap syndrome or unknown) and disease duration.

Quantitative data analysis

Quantitative data are reported using descriptive statistics (frequencies/percentages or means/medians with 95% confidence intervals and interquartile ranges) (R, Version 3.6.3, and DescTools-package) [49]. To compare PACIC-15 mean scores between groups (e.g., sex, age groups, education, comorbidities), we computed standardized mean differences (SMD)—which are identical to Cohen’s d (tableone-package for R) [50]. Compared to p values, SMD is more appropriate for calculating effect size estimates in small, uneven datasets—such as the ones analysed in this study [51]. A SMD ≥ 0.2, ≥ 0.5 and ≥ 0.8 depict small, medium and large differences between groups respectively. We calculated 95% confidence intervals (CIs) for means to facilitate comparison between ratings. Differences between groups were defined as means with distinct, non-overlapping CIs. Correlation analysis (pearson’s r) was computed to calculate associations between PACIC and SScQoL levels and visualized using the corrplot-package in R [52].

Qualitative data collection and analysis

Sample and setting

To further explore the association between HRQoL and perception of chronic care, we used data from individual patient interviews (n = 4) and one patient focus group (n = 4), that were conducted within the larger qualitative MANOSS study (i.e., n = 14 individual interview and n = 17 focus group participants). Individual interview participants were purposefully selected from the quantitative MANOSS study sample according to patients’ PACIC and SScQoL scores (Table 1). For the focus group, we contacted patients with experience living with SSc (i.e., disease duration > 10 years) from the Swiss Scleroderma Association and the quantitative study sample. Participant background/profession (i.e., medical, scientific) was identified in the discussion round of the study.

Table 1 Interview subsample (n = 4) selected according to SScQoL and PACIC mean values
Full size table

Data collection

Semi-structured individual interviews were conducted in German, French or English and were conducted (30–90 min in duration) either on-site or via telephone (due to COVID-19 pandemic restrictions) [38]. Open-ended interview questions (e.g., How do you experience your care? What would the best possible care look like for you?) were drawn from the CCM and patient’s narratives [20, 38]. The complete interview guide is published in the MANOSS study protocol [38]. Interviews were recorded and transcribed verbatim.

Focus group participants (n = 4) were engaged using an interview guide with open-ended prompts to discuss our quantitative study results (i.e., What is important/surprising? What fits your experience? What contradicts your own experience? What are important aspects that should be taken into account when improving chronic care for patients?). Subsequently, primary care needs and problem areas for care were discussed from a patient perspective. Due to the COVID-19 pandemic, the focus group was conducted using an online video conferencing (Zoom) and recorded with participant consent.

Qualitative data analysis

We used a reflexive thematic analysis approach described by Braun and Clarke [53, 54]. Briefly, investigators started analysis of interview transcripts by (1) familiarizing themselves with the data (i.e., reading and discussing first impression, main issues from patient perspective), (2) coding the data and developing first patterns of shared meaning across all interviews (i.e., inductive, but not theory free) and (3) constructing patterns/themes to explain PACIC dimensions. Finally, themes were refined and named based on original data (i.e., quotes, codes).

Mixed methods data integration

The quantitative data informed the structure of the qualitative study. Subsequently, the qualitative data were used to explain the quantitative findings. Importantly, the mixed methods approach provides deeper insight for model development than either method in isolation [39]. We present our quantitative results first, followed by a joint display including key quantitative findings and qualitative in-depth themes for each PACIC dimension and data integration at the level of discussion.

Results

Participants’ characteristics

In total, 101 patients (median age = 60 yrs., IQR: 50–68) with a median disease duration of 8 years (IQR: 5–15) completed the survey (Table 2). Approximately half of patients (52/101, 51.5%) reported having more than two comorbidities. In total, 8 patients (interview: n = 4, focus group: n = 4) participated in the qualitative study. All four focus group participants were active members of a patient organization and three had a medical and/or scientific background, one participant had a rare rheumatic disease other than SSc since childhood.

Table 2 Patient characteristics of quantitative and qualitative study phases
Full size table

Patient Assessment of Chronic Illness Care (PACIC) and its associations with patient characteristics, comorbidities and quality of life (HRQoL)

The distribution of all PACIC-15 scales in the overall, the German and the French-speaking MANOSS sample (n = 101) is presented in Table 3. Single item values are presented in Table 4 (i.e., joint display of quantitative and qualitative findings). The mean overall PACIC-15 score was relatively low (\({\overline{x}}\) = 3.0, 95% CI 2.8–3.2, n = 100) indicating that care was ‘never’ to ‘generally not’ perceived as aligned with the CCM. Lowest PACIC-15 mean subscale scores related to ‘goal setting/tailoring’ (\({\overline{x}}\) = 2.5, 95% CI 2.2–2.7, n = 99), followed by ‘problem solving/contextual counselling’ (\({\overline{x}}\) = 2.9, 95% CI 2.7–3.2, n = 99). The single PACIC-15 items with the lowest ratings were: ‘given a copy of my treatment plan’ (\({\overline{x}}\) = 2.0, 95% CI1.7–2.3, n = 97) and ‘helped to plan ahead so I could take care of my condition(s) even in hard times’ (\({\overline{x}}\) = 2.5, 95% CI 2.2–2.8, n = 98).

Table 3 Distribution of the 15-item PACIC scale
Full size table
Table 4 Joint display of key quantitative findings for each PACIC subscale and interrelated qualitative theme
Full size table

Overall, patient characteristics were not associated with individual (mean) PACIC-15 scores. Considering comorbidities, only self-report of lung problems showed a significant difference in mean PACIC-15 scores (Table 5). However, patients ≤ 65 years (\({\overline{x}}\) = 3.1 vs. 2.7; SMD = 0.41, n = 95) and males (\({\overline{x}}\) = 3.3 vs. 3.0; SMD = 0.33, n = 97) reported higher mean PACIC scores. Patients trended towards lower mean PACIC scores early in the disease trajectory (i.e., within two years of diagnosis) (\({\overline{x}}\) = 2.9 vs. 3.1; SMD = 0.15, n = 95) and in subgroup with diffuse cutaneous systemic sclerosis (dcSSc) (\({\overline{x}}\) = 2.9 vs. 3.2; SMD = 0.26, n = 67). Interestingly, patients with lung (\({\overline{x}}\) = 3.4 vs. 2.8; SMD = 0.61, n = 100) and gastrointestinal (GI) problems (\({\overline{x}}\) = 3.2 vs. 2.9; SMD = 0.29, n = 100) reported higher PACIC levels than those without pulmonary/GI comorbidities. Patients with musculoskeletal complaints reported lower PACIC scores (back pain: \({\overline{x}}\) = 2.9 vs. 3.2; SMD = 0.31, n = 97; osteoarthritis: \({\overline{x}}\) = 2.8 vs. 3.1; SMD = 0.30, n = 98). Further, patients with more than two self-reported comorbidities reported lower PACIC levels (\({\overline{x}}\) = 2.8 vs. 3.0; SMD = 0.28, n = 100).

Table 5 Univariate analyses of patient characteristics and comorbidities in relation to the mean PACIC-15 score (n = 101)
Full size table

No significant correlations (pearson’s r) were identified between the mean PACIC-15 and SScQoL scores (neither total score nor sub-dimensions) (see Additional file 2).

Association of HRQoL and patient characteristics/comorbidities

The overall mean SScQoL score was 18.3 (95% CI 16.7–19.9). Patients from German-speaking Switzerland tended to have better SScQoL outcomes (\({\overline{x}}\) = 17.4 vs. 21.4; SMD = 0.56), particularly in ‘emotional’ (\({\overline{x}}\) = 7.5 vs. 9.9; SMD = 0.71) and ‘sleep’ (\({\overline{x}}\) = 1.2 vs. 1.7; SMD = 0.61) dimensions. Younger patients (≤ 65 years) tended to report poorer HRQoL (\({\overline{x}}\) = 19.0 vs. 16.6; SMD = 0.30) (Table 6).

Table 6 Distribution of the 29-item SScQoL scales
Full size table

Notably, HRQoL was strongly associated with self-reported comorbidities but no other patient characteristics (Table 7). Neither sex, marital status nor disease subset/duration were associated with SScQoL mean score. Patients ≤ 65 years old (\({\overline{x}}\) = 19.0 vs. 16.6; SMD = 0.30, n = 95) and with compulsory or no education (\({\overline{x}}\) = 20.3 vs. 18.0; SMD = 0.30, n = 99) tended to exhibit lower HRQol (i.e., higher SScQoL scores). The number of patient self-reported comorbidities had a deleterious influence on SScQoL. Patients reporting more than two comorbidities (51.5%, n = 52) had lower HRQoL—as evidenced by significantly higher SScQoL score (\({\overline{x}}\) = 22.3 vs. 14.3; SMD = 1.15, n = 100). Similar findings were observed in individuals reporting depression (\({\overline{x}}\) = 24.3 vs. 17.4; SMD = 1.10, n = 99), gastrointestinal problems (\({\overline{x}}\) = 21.2 vs. 14.3; SMD = 0.94, n = 100) and osteoarthritis (\({\overline{x}}\) = 21.3 vs. 16.4; SMD = 0.64, n = 98).

Table 7 Univariate analyses of patient characteristics/comorbidities in relation to mean SScQoL score (n = 101)
Full size table

Qualitative findings

The quantitative findings informed the structure of the qualitative data description—presented in a joint display (see Table 4). More concrete, patient experiences with the current chronic care approach are described in six themes illustrated with patient quotes. Whereas always two qualitative themes are mapped to the PACIC dimensions: (1) ‘experiencing organized care with limited participation’ and (2) ‘dealing with the illness in tailored measure’ (belonging to ‘patient activation’ and ‘delivery system design/decision support’); (3) ‘not knowing which strategies are effective or harmful’ and (4) ‘feeling left alone with disease and psychosocial consequences’ (belonging to ‘goal setting/tailoring’ and ‘problem solving/contextual counselling’); (5) ‘taking over complex coordination of care’ and (6) ‘relying on an accessible and trustworthy team’ (belonging to ‘follow-up/coordination’). In respect to Table 4, the reader is advised to start with the dimension definition, then the overview of the quantitative results followed by the qualitative results to better understand the patient experience.

Discussion

In this investigation of SSc care, we found relatively low PACIC values overall. Patients identified the greatest deficits in the areas of ‘goal setting/tailoring’ and ‘problem solving/contextual counselling’. These observations are further supported by the qualitative findings that revealed significant need for SSc self-management support and care coordination, both key elements of CCM.

The low PACIC mean overall score of 3.0/5.0 (95% CI 2.8–3.2) in our study is comparable to findings in patients with common chronic diseases [26, 30, 36]. However, direct comparison of PACIC scores should be done with caution as slightly different version have been used across studies. A 2018 meta-analysis of 34 studies from 13 countries (> 25,000 patients with diabetes) [36] identified a pooled score of 3.0 (95% CI 2.8–3.2). Interestingly, a survey conducted by EURORDIS (a European alliance of 970 rare disease patient organisations from 74 countries) used the abbreviated 11-item PACIC [55] and found patients report a better chronic care experience (\({\overline{x}}\) = 3.4 vs. 2.6) when treated in centres belonging to a European Reference Network (ERN)—highlighting the critical role for access to expert care for rare diseases.

Notably, we did not find an association between PACIC scores and HRQoL. However, mean SScQoL scores were significantly associated with a number of self-reported comorbidities (depression, gastrointestinal problems and osteoarthritis). Such findings are in line with studies of common chronic conditions, in which PACIC scores were marginally correlated with HRQoL (r = 0.15 and 0.23) [26, 28, 56]. Our observation is explained by qualitative investigation that revealed a number of factors influencing patient ratings of care (i.e., gratitude, faith, loyalty, luck, equity, engagement with the system) [57]. Interestingly, patients with lung problems reported higher PACIC levels than those without pulmonary complications. It is plausible that patients’ evaluation of care may depend on their perceived level of influence and engagement with the healthcare system—rather than HRQoL per se.

Nevertheless, PACIC dimensions can inform development or improvement of integrated models of SSc care [27]. In the present study, PACIC scores indicate shortcomings in ‘goal setting/tailoring’ and ‘problem solving/contextual counselling’. The patient-identified gaps in care pose significant barriers to effective self-management. Indeed, the described qualitative themes ‘not knowing which strategies are effective or harmful’ and ‘feeling left alone with disease and psychosocial consequences’ highlight the quantitative findings. Our observations are similar to studies in common chronic conditions that identified the same PACIC dimensions had the lowest mean values [26, 28]. Similarly, prior qualitative work in SSc, found that patients often lack guidance and effective strategies for independent self-management—particularly in relation to disease and psychosocial consequences [58,59,60]. Indeed, a systematic review of 26 qualitative studies in SSc identified that patients often feel ‘alone and misunderstood’ (i.e., fearful avoidance of fellow patients, invisible suffering) despite having the opportunity to meet other patients in support groups [60]. Comparisons at the item level reveal similarities with European patients with other rare diseases [55]. Swiss SSc patients in the present study were—similar to rare disease patients in Europe—rarely helped to plan ahead for self-management in challenging times (\({\overline{x}}\) = 2.5 for both groups) or connected with disease-specific patient support groups (\({\overline{x}}\) = 2.3 and 2.1 respectively) [55]. Importantly, patients in our study noted limitations of traditional peer support groups. The present findings underscore and expand on previously identified gaps in care for patients with SSc and emphasize the importance of eliciting patient-defined goals/outcomes, developing self-management programmes and re-envisioning traditional on-site peer support groups [16, 59,60,61,62]. When implementing integrated care, patients and professionals should agree on a joint treatment plan including individualized goals targeting the primary SSc manifestations and consequences. Importantly, patients need to understand the essential elements for their individual disease self-management and require tailored education across the specialities involved in care. Therefore, it is important to foster provider skills and implement programs supporting psychological and self-management support to enable patients to self-manage their condition on a day-to-day basis [55].

Like Desmedt et al. [26] and Stuber et al. [35], we observed relatively high PACIC scores in the dimensions ‘patient activation’ and ‘delivery system design/decision support’—suggesting that patient with SSc generally feel involved in care decisions. Compared to European rare disease patients, Swiss SSc patients are more likely to ‘receive treatment choices to think about’ (\({\overline{x}}\) = 3.2 vs. 2.8) and consider their care as ‘well organized’ (\({\overline{x}}\) = 3.9 vs. 3.5) [55]. Congruently, interviews revealed that patients who had regular medical follow-up perceived their care as ‘super organised’ despite a persistent fear of receiving negative results. However, the qualitative theme ‘experiencing organized care with limited participation’—suggests that patients did not feel involved in medical consultations and that decisions were primarily provider-driven. Moreover, the theme ‘dealing with the illness in tailored measure’ describes the importance of protecting patients from feeling overwhelmed in confronting SSc—a finding that adds to prior qualitative SSc research [60]. Our qualitative inquiry reflects the importance of soliciting patient input and involving patients in decision-making as well as arranging care to extend and reinforce office-based consultations. Thus, improving healthcare provider competencies in shared decision-making is a key target for effectively implementing integrated SSc care [63, 64]. Stocker et al. [17] highlighted the need for patient decision aids to foster more patient-focused communication and support high quality decisions that are both informed and aligned with patient needs, values and preferences. Furthermore, our study revealed that patients may feel strained by too much, untimely or frightening information and may therefore refuse certain tests, examinations or interventions. To overcome such barriers, timely access to specialized care (e.g., virtual expert consultations, cross-border healthcare, knowledge assets produced by centres of expertise) warrant consideration [55].

With regard to the PACIC dimension ‘follow-up/coordination’, we identified major gaps in the complex care coordination of SSc (i.e., discontinuity and lack of follow-up). Among Swiss SSc patients in this study, patients were more likely to reported receiving feedback and explanations about specialist visits and examinations compared to European rare disease patients (\({\overline{x}}\) = 3.6 vs. 2.5) [55]. However, qualitative interviews with experienced patients revealed that patients often assume responsibility for complex care coordination themselves. The theme ‘taking over complex coordination of care’ underscored the difficulty patients experience coordinating their own care. Similar to European rare disease patients, Swiss SSc patients rarely had contact with their healthcare provider after a visit, potentially explained by suboptimal provider reimbursement for outpatient services in the Swiss health system [65]. Moreover, patients may be receiving care in centres/practices that lack expertise in this rare disease [55]. Importantly, rare disease patients who were treated in centres belonging to a European Reference Network (ERN) reported higher satisfaction with regard to ‘being contacted after a visit’ (\({\overline{x}}\) = 2.8 vs. 2.1). Congruently, our interview participants described ‘relying on an accessible and trustworthy team’ as a central theme relating to finding trusted, reliable professionals and peers for ongoing care and support. Several studies have revealed similar gaps in SSc care delivery (i.e., lack of structured multidisciplinary collaboration, inadequately organized follow-up, poor patient-provider relationships [17, 59, 66,67,68]. Despite the positive impact the chronic care model has demonstrated on disease outcomes, rare disease care models rarely test multi-component interventions (e.g., patient education, patient-held medical records, specialist nurse-led care) in providing coordinated, ongoing, complex care [32, 69] and infrequently incorporate community-based resources [70, 71]. In diabetes and cancer, chronic care implementation has long utilized specialized nurses and peers for support, case-management and counselling to improve patient-centredness, satisfaction with care and clinical outcomes [72,73,74,75]. Additionally, capacity building within health systems may be needed for a more flexible approach to planning consultations (e.g., self-referrals for lab tests and consultations) as well as co-management by patients and professionals (e.g., personal health records) to improve patient access, promote empowerment and reduce travel requirements [15, 76, 77].

In summary, comprehensive SSc care demands a systematic approach that addresses physical and mental health concerns as well as social consequences/inequities throughout the disease course. A collaborative approach between patients and providers is paramount with shared responsibility for decision-making and goal setting to arrive at a joint treatment plan. Additionally, tailored therapeutic education is an essential component of comprehensive, holistic SSc care. In regard to care delivery and follow-up/coordination important targets include improving provider skills (e.g., decision-making, self-management support) and novel modes of care (e.g., decision aids, virtual consultations, specialized nurses, peer-to-peer support, self-referrals, personal health records) may help create a more person-centered approach to SSc care.

Relative strengths of this study include the comprehensive assessment of patient experiences and needs for SSc chronic illness care using both quantitative and qualitative data from patients spanning a range of disease experience (i.e., newly diagnosed until long diseases duration). The study also has a number of limitations. First, the sample size is relatively limited, yet 101 patients included in the quantitative survey is a sizeable cohort for a rare disease [78]. Similarly, the qualitative sample used to contextualise the PACIC data was small. The purposeful selection of these participants ensured us to depict the variable disease trajectory of SSc. However, experience with a new diagnosis may be underrepresented because all participants in the qualitative part had two or more years of disease experience. In addition, the PACIC has not been formally validated for SSc. The PACIC has been used in rare disease populations [55]—yet it is unclear how well this generic instrument assesses the challenges specific to rare disease care (e.g. lack of treatment options and specialized healthcare professionals) and disease-specific patient needs. Prior research in common chronic diseases suggest that the single PACIC score is an appropriate measure of global chronic care—yet it is difficult to distinguish between the five PACIC dimensions [41, 79]. Unlike previous validation studies using confirmatory factor analysis, we applied Mokken Scale Analysis that relates to nonparametric Item Response Theory (IRT) models and is more appropriate for non-normally distributed data [42, 80]. Our validation revealed five items of the PACIC-20 dimensions not fitting our data. After excluding these problematic items, H coefficients were found to be strong for the global (0.52) and subscales (0.69, 0.70) suggesting a robust unidimensional scale (see Additional file 1). However, from a clinical perspective, excluding these items may be controversial—as considering scalability coefficients alone may yield an incomplete picture [42]. Indeed, patient care experiences with regard to peer support (e.g., item 10), follow-up (e.g., item 17) and referral to HPs (e.g., item 18) would be important for quality assessment of SSc and rare disease care in general.

Conclusions

In summary, re-envisioning current SSc care practices and incorporating components of the Chronic Care Model (CCM) offer opportunities to improve chronic disease management of SSc patients in Switzerland. Our findings suggest that shared decision-making, goal-setting and tailored counselling are needed to better support patients to develop self-management skills. New models of care must focus on coordinating the complex care (including ongoing follow-up), and facilitating patients and professionals in sharing a leadership role to improve patient-centredness, satisfaction with care and clinical outcomes. Establishing more flexible approaches to scheduling consultations and fostering co-management by patients and professionals merits attention (e.g., specialized nurse-led case management and peer-to-peer counselling). Future research would be needed to receive a valid and reliable measure for the assessment of chronic illness care in rare diseases as SSc. Additional investigation may focus on comparing and contrasting centres providing care for people living with SSc and other rare (rheumatic) diseases to discern the key elements of chronic illness management for these populations.

Availability of data and materials

The datasets generated and/or analysed during this study are included in this published article or can be made available from the corresponding author on reasonable request.

References

  1. Allanore Y, Simms R, Distler O, Trojanowska M, Pope J, Denton CP, et al. Systemic sclerosis. Nat Rev Dis Primers. 2015;1:15002.

    Article  Google Scholar 

  2. Bairkdar M, Rossides M, Westerlind H, Hesselstrand R, Arkema EV, Holmqvist M. Incidence and prevalence of systemic sclerosis globally: a comprehensive systematic review and meta-analysis. Rheumatology. 2021;60(7):3121–33.

    Article  Google Scholar 

  3. Jaeger VK, Wirz EG, Allanore Y, Rossbach P, Riemekasten G, Hachulla E, et al. Incidences and risk factors of organ manifestations in the early course of systemic sclerosis: a longitudinal EUSTAR study. PLoS ONE. 2016;11(10):e0163894.

    Article  Google Scholar 

  4. Kowal-Bielecka O, Fransen J, Avouac J, Becker M, Kulak A, Allanore Y, et al. Update of EULAR recommendations for the treatment of systemic sclerosis. Ann Rheum Dis. 2017;76(8):1327–39.

    Article  Google Scholar 

  5. Walker UA, Saketkoo LA, Distler O. Haematopoietic stem cell transplantation in systemic sclerosis. RMD Open. 2018;4(1):e000533.

    Article  Google Scholar 

  6. Kwakkenbos L, Delisle VC, Fox RS, Gholizadeh S, Jewett LR, Levis B, et al. Psychosocial aspects of scleroderma. Rheum Dis Clin N Am. 2015;41(3):519–28.

    Article  Google Scholar 

  7. Bassel M, Hudson M, Taillefer SS, Schieir O, Baron M, Thombs BD. Frequency and impact of symptoms experienced by patients with systemic sclerosis: results from a Canadian National Survey. Rheumatology (Oxford). 2011;50(4):762–7.

    Article  Google Scholar 

  8. Hudson M, Thombs BD, Steele R, Watterson R, Taillefer S, Baron M, et al. Clinical correlates of quality of life in systemic sclerosis measured with the World Health Organization Disability Assessment Schedule II. Arthritis Rheum. 2008;59(2):279–84.

    Article  Google Scholar 

  9. Decuman S, Smith V, Verhaeghe S, Deschepper E, Vermeiren F, De Keyser F. Work participation and work transition in patients with systemic sclerosis: a cross-sectional study. Rheumatology (Oxford). 2012;51(2):297–304.

    Article  Google Scholar 

  10. Sierakowska M, Doroszkiewicz H, Sierakowska J, Olesinska M, Grabowska-Jodkowska A, Brzosko M, et al. Factors associated with quality of life in systemic sclerosis: a cross-sectional study. Qual Life Res. 2019;28(12):3347–54.

    Article  Google Scholar 

  11. Frantz C, Avouac J, Distler O, Amrouche F, Godard D, Kennedy AT, et al. Impaired quality of life in systemic sclerosis and patient perception of the disease: a large international survey. Semin Arthritis Rheum. 2016;46(1):115–23.

    Article  Google Scholar 

  12. van Leeuwen NM, Ciaffi J, Liem SIE, Huizinga TWJ, de Vries-Bouwstra JK. Health-related quality of life in patients with systemic sclerosis: evolution over time and main determinants. Rheumatology (Oxford). 2021;60(8):3646–55.

    Article  Google Scholar 

  13. Park EH, Strand V, Oh YJ, Song YW, Lee EB. Health-related quality of life in systemic sclerosis compared with other rheumatic diseases: a cross-sectional study. Arthritis Res Ther. 2019;21(1):61.

    Article  CAS  Google Scholar 

  14. Willems LM, Kwakkenbos L, Bode C, van den Hoogen FH, van den Ende CH. Health care use and patients’ perceptions on quality of care in systemic sclerosis. Clin Exp Rheumatol. 2013;31(2 Suppl 76):64–70.

    Google Scholar 

  15. Spierings J, van den Ende C, Schriemer R, de Pundert L, Moens HB, van Laar J, et al. Optimal care for systemic sclerosis patients: recommendations from a patient-centered and multidisciplinary mixed-method study and working conference. Clin Rheumatol. 2019;38(4):1007–15.

    Article  Google Scholar 

  16. Spierings J, van Rhijn-Brouwer FCC, de Bresser CJM, Mosterman PTM, Pieterse AH, Vonk MC, et al. Treatment decision-making in diffuse cutaneous systemic sclerosis: a patient’s perspective. Rheumatology (Oxford). 2020;59(8):2052–61.

    Article  CAS  Google Scholar 

  17. Stocker JK, Vonk MC, van den Hoogen FHJ, Nijhuis-van der Sanden MWG, Spierings J, Staal JB, et al. Room for improvement in non-pharmacological systemic sclerosis care? A cross-sectional online survey of 650 patients. BMC Rheumatol. 2020;4:43.

    Article  Google Scholar 

  18. Bodenheimer T, Lorig K, Holman H, Grumbach K. Patient self-management of chronic disease in primary care. JAMA. 2002;288(19):2469–75.

    Article  Google Scholar 

  19. Gee PM, Greenwood DA, Paterniti DA, Ward D, Miller LM. The eHealth Enhanced Chronic Care Model: a theory derivation approach. J Med Internet Res. 2015;17(4):e86.

    Article  Google Scholar 

  20. Wagner EH. Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract. 1998;1(1):2–4.

    CAS  Google Scholar 

  21. Davy C, Bleasel J, Liu H, Tchan M, Ponniah S, Brown A. Effectiveness of chronic care models: opportunities for improving healthcare practice and health outcomes: a systematic review. BMC Health Serv Res. 2015;15:194.

    Article  Google Scholar 

  22. Brand CA, Ackerman IN, Tropea J. Chronic disease management: improving care for people with osteoarthritis. Best Pract Res Clin Rheumatol. 2014;28(1):119–42.

    Article  Google Scholar 

  23. Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the chronic care model in the new millennium. Health Aff (Millwood). 2009;28(1):75–85.

    Article  Google Scholar 

  24. Stellefson M, Dipnarine K, Stopka C. The chronic care model and diabetes management in US primary care settings: a systematic review. Prev Chronic Dis. 2013;10:E26.

    Article  Google Scholar 

  25. Glasgow RE, Wagner EH, Schaefer J, Mahoney LD, Reid RJ, Greene SM. Development and validation of the Patient Assessment of Chronic Illness Care (PACIC). Med Care. 2005;43(5):436–44.

    Article  Google Scholar 

  26. Desmedt M, Vertriest S, Petrovic M, Bergs J, Vrijhoef H, Dessers E, et al. Seen through the patients’ eyes: quality of chronic illness care. Fam Pract. 2018;35(4):446–51.

    Article  Google Scholar 

  27. Schmittdiel J, Mosen DM, Glasgow RE, Hibbard J, Remmers C, Bellows J. Patient Assessment of Chronic Illness Care (PACIC) and improved patient-centered outcomes for chronic conditions. J Gen Intern Med. 2008;23(1):77–80.

    Article  Google Scholar 

  28. Malliarou M, Desikou C, Lahana E, Kotrotsiou S, Paralikas T, Nikolentzos A, et al. Diabetic patient assessment of chronic illness care using PACIC. BMC Health Serv Res. 2020;20(1):543.

    Article  Google Scholar 

  29. Glasgow RE, Whitesides H, Nelson CC, King DK. Use of the Patient Assessment of Chronic Illness Care (PACIC) with diabetic patients: relationship to patient characteristics, receipt of care, and self-management. Diabetes Care. 2005;28(11):2655–61.

    Article  Google Scholar 

  30. Bo A, Jensen NH, Bro F, Nicolaisen SK, Maindal HT. Higher patient assessed quality of chronic care is associated with lower diabetes distress among adults with early-onset type 2 diabetes: cross-sectional survey results from the Danish DD2-study. Prim Care Diabetes. 2020;14(5):522–8.

    Article  Google Scholar 

  31. Iglesias K, De Geest S, Berben L, Dobbels F, Denhaerynk K, Russell LC, et al. Validation of the patient assessment of chronic illness care (PACIC) short form scale in heart transplant recipients: the international cross-sectional bright study. BMC Health Serv Res. 2020;20(1):160.

    Article  Google Scholar 

  32. Burton J, Murphy E, Riley P. Primary immunodeficiency disease: a model for case management of chronic diseases. Prof Case Manag. 2010;15(1):5–10 (2-4; quiz 5-6).

    Article  Google Scholar 

  33. Pericleous M, Kelly C, Ala A, De Lusignan S. The role of the chronic care model in promoting the management of the patient with rare liver disease. Expert Rev Gastroenterol Hepatol. 2018;12(8):829–41.

    Article  CAS  Google Scholar 

  34. Pai M, Key NS, Skinner M, Curtis R, Feinstein M, Kessler C, et al. NHF-McMaster guideline on care models for haemophilia management. Haemophilia. 2016;22(Suppl 3):6–16.

    Article  Google Scholar 

  35. Stuber KJ, Langweiler M, Mior S, McCarthy PW. A pilot study assessing patient-centred care in patients with chronic health conditions attending chiropractic practice. Complement Ther Med. 2018;39:1–7.

    Article  Google Scholar 

  36. Arditi C, Iglesias K, Peytremann-Bridevaux I. The use of the Patient Assessment of Chronic Illness Care (PACIC) instrument in diabetes care: a systematic review and meta-analysis. Int J Qual Health Care. 2018;30(10):743–50.

    Article  Google Scholar 

  37. Rick J, Rowe K, Hann M, Sibbald B, Reeves D, Roland M, et al. Psychometric properties of the Patient Assessment Of Chronic Illness Care measure: acceptability, reliability and validity in United Kingdom patients with long-term conditions. BMC Health Serv Res. 2012;12:293.

    Article  Google Scholar 

  38. Kocher A, Simon M, Dwyer AA, Villiger PM, Kunzler-Heule P, De Geest S, et al. Developing a rare disease chronic care model: management of systemic sclerosis (MANOSS) study protocol. J Adv Nurs. 2019;75(12):3774–91.

    Article  Google Scholar 

  39. Creswell JW, Plano Clark VL. Designing and conducting mixed methods research, 2nd. edition. Thousand Oaks: Sage Publications; 2011.

    Google Scholar 

  40. Gugiu C, Coryn CL, Applegate B. Structure and measurement properties of the Patient Assessment of Chronic Illness Care instrument. J Eval Clin Pract. 2010;16(3):509–16.

    Google Scholar 

  41. Iglesias K, Burnand B, Peytremann-Bridevaux I. PACIC Instrument: disentangling dimensions using published validation models. Int J Qual Health Care. 2014;26(3):250–60.

    Article  CAS  Google Scholar 

  42. Sijtsma K, van der Ark LA. A tutorial on how to do a Mokken scale analysis on your test and questionnaire data. Br J Math Stat Psychol. 2017;70(1):137–58.

    Article  Google Scholar 

  43. Ndosi M, Alcacer-Pitarch B, Allanore Y, Del Galdo F, Frerix M, Garcia-Diaz S, et al. Common measure of quality of life for people with systemic sclerosis across seven European countries: a cross-sectional study. Ann Rheum Dis. 2018;77(7):1032–8.

    Article  Google Scholar 

  44. Kocher A, Ndosi M, Denhaerynck K, Simon M, Dwyer AA, Distler O, et al. A rare disease patient-reported outcome measure: revision and validation of the German version of the Systemic Sclerosis Quality of Life Questionnaire (SScQoL) using the Rasch model. Orphanet J Rare Dis. 2021;16(1):356.

    Article  Google Scholar 

  45. Kocher A, Ndosi M, Hoeper K, Simon M, Nicca D. Revision and validation of the German version of the systemic sclerosis quality of life questionnaire (Sscqol) with Mokken scale analysis. Ann Rheumatic Dis. 2020;79:550–1.

    Article  Google Scholar 

  46. Sangha O, Stucki G, Liang MH, Fossel AH, Katz JN. The self-administered comorbidity questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum. 2003;49(2):156–63.

    Article  Google Scholar 

  47. Hudson M, Bernatsky S, Taillefer S, Fortin PR, Wither J, Baron M, et al. Patients with systemic autoimmune diseases could not distinguish comorbidities from their index disease. J Clin Epidemiol. 2008;61(7):654–62.

    Article  Google Scholar 

  48. Spagnolo P, Cordier JF, Cottin V. Connective tissue diseases, multimorbidity and the ageing lung. Eur Respir J. 2016;47(5):1535–58.

    Article  Google Scholar 

  49. Signorell A. DescTools: tools for descriptive statistics. R package version 0.99.41. https://cran.r-project.org/package=DescTools. Accessed 14 May 2021.

  50. Yoshida K, Bartel A. tableone: create 'Table 1' to describe baseline characteristics with or without propensity score weights. R package version 0.12.0. https://CRAN.R-project.org/package=tableone. Accessed 14 May 2021.

  51. Faraone SV. Interpreting estimates of treatment effects: implications for managed care. Pharm Ther. 2008;33(12):700–11.

    Google Scholar 

  52. Wei T, Simko V. R package 'corrplot': visualization of a correlation matrix (Version 0.90)2021. https://cran.r-project.org/web/packages/corrplot/corrplot.pdf.

  53. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3(2):77–101.

    Article  Google Scholar 

  54. Braun V, Clarke V, Hayfield N, Terry G. Thematic analysis. In: Liamputtong P, editor. Handbook of research methods in health social sciences. Singapore: Springer; 2019. p. 843–60.

    Chapter  Google Scholar 

  55. EURORDIS. Improve our experience of health care! Key findings from a survey on patients' and carers' experience of medical care for their rare diseases 2021. https://download2.eurordis.org/rbv/HCARE/HCARE_FS_long.pdf.

  56. Boland MR, Kruis AL, Huygens SA, Tsiachristas A, Assendelft WJ, Gussekloo J, et al. Exploring the variation in implementation of a COPD disease management programme and its impact on health outcomes: a post hoc analysis of the RECODE cluster randomised trial. NPJ Prim Care Respir Med. 2015;25:15071.

    Article  Google Scholar 

  57. Staniszewska SH, Henderson L. Patients’ evaluations of the quality of care: influencing factors and the importance of engagement. J Adv Nurs. 2005;49(5):530–7.

    Article  Google Scholar 

  58. Kocher A, Adler S, Spichiger E. Skin and mucosa care in systemic sclerosis–patients’ and family caregivers’ experiences and expectations of a specific education programme: a qualitative study. Musculoskelet Care. 2013;11(3):168–78.

    Article  Google Scholar 

  59. Mouthon L, Alami S, Boisard AS, Chaigne B, Hachulla E, Poiraudeau S. Patients’ views and needs about systemic sclerosis and its management: a qualitative interview study. BMC Musculoskelet Disord. 2017;18(1):230.

    Article  Google Scholar 

  60. Nakayama A, Tunnicliffe DJ, Thakkar V, Singh-Grewal D, O’Neill S, Craig JC, et al. Patients’ perspectives and experiences living with systemic sclerosis: a systematic review and thematic synthesis of qualitative studies. J Rheumatol. 2016;43(7):1363–75.

    Article  Google Scholar 

  61. Robson JC, Shepherd M, Harper L, Ndosi M, Austin K, Flurey C, et al. Psychological and self-management support for people with vasculitis or connective tissue diseases: UK health professionals’ perspectives. Rheumatol Adv Pract. 2020;4(2):rkaa016.

    Article  Google Scholar 

  62. Kwakkenbos L, Carboni-Jimenez A, Carrier ME, Pepin M, Pelaez S, Malcarne VL, et al. Reasons for not participating in scleroderma patient support groups: a comparison of results from the North American and European scleroderma support group surveys. Disabil Rehabil. 2019;43:1279–86.

    Article  Google Scholar 

  63. Joseph-Williams N, Lloyd A, Edwards A, Stobbart L, Tomson D, Macphail S, et al. Implementing shared decision making in the NHS: lessons from the MAGIC programme. BMJ. 2017;357:j1744.

    Article  Google Scholar 

  64. Muscat DM, Morony S, Trevena L, Hayen A, Shepherd HL, Smith SK, et al. Skills for shared decision-making: evaluation of a health literacy program for consumers with lower literacy levels. Health Lit Res Pract. 2019;3(3 Suppl):S58–74.

    Google Scholar 

  65. De Pietro C, Camenzind P, Sturny I, Crivelli L, Edwards-Garavoglia S, Spranger A, et al. Switzerland: health system review. Health Syst Transit. 2015;17(4):1–288.

    Google Scholar 

  66. Schouffoer AA, Zirkzee EJ, Henquet SM, Caljouw MA, Steup-Beekman GM, van Laar JM, et al. Needs and preferences regarding health care delivery as perceived by patients with systemic sclerosis. Clin Rheumatol. 2011;30(6):815–24.

    Article  Google Scholar 

  67. Spierings J, van den Ende CHM, Schriemer RM, Bernelot Moens HJ, van der Bijl EA, Bonte-Mineur F, et al. How do patients with systemic sclerosis experience currently provided healthcare and how should we measure its quality? Rheumatology (Oxford). 2020;59(6):1226–32.

    Article  Google Scholar 

  68. Stocker JK, Vonk MC, van den Hoogen FHJ, Nijhuis-van der Sanden MWG, Spierings J, Staal JB, et al. Opening the black box of non-pharmacological care in systemic sclerosis: a cross-sectional online survey of Dutch health professionals. Rheumatol Int. 2020;41:1299–310.

    Article  Google Scholar 

  69. Spijk-de Jonge MJ, Weijers JM, Teerenstra S, Elwyn G, van de Laar MA, van Riel PL, et al. Patient involvement in rheumatoid arthritis care to improve disease activity-based management in daily practice: a randomized controlled trial. Patient Educ Couns. 2021;105:1244–53.

    Article  Google Scholar 

  70. Doyle M. Peer support and mentorship in a us rare disease community: findings from the cystinosis in emerging adulthood study. Patient. 2015;8(1):65–73.

    Article  Google Scholar 

  71. Badiu C, Bonomi M, Borshchevsky I, Cools M, Craen M, et al. Developing and evaluating rare disease educational materials co-created by expert clinicians and patients: the paradigm of congenital hypogonadotropic hypogonadism. Orphanet J Rare Dis. 2017;12(1):57.

    Article  Google Scholar 

  72. Frei A, Senn O, Chmiel C, Reissner J, Held U, Rosemann T. Implementation of the chronic care model in small medical practices improves cardiovascular risk but not glycemic control. Diabetes Care. 2014;37(4):1039–47.

    Article  Google Scholar 

  73. Scherz N, Bachmann-Mettler I, Chmiel C, Senn O, Boss N, Bardheci K, et al. Case management to increase quality of life after cancer treatment: a randomized controlled trial. BMC Cancer. 2017;17(1):1–8.

    Article  Google Scholar 

  74. Chmiel C, Giewer I, Frei A, Rosemann T. Four-year long-term follow-up of diabetes patients after implementation of the Chronic Care Model in primary care: a cross-sectional study. Swiss Med Wkly. 2017. https://doi.org/10.4414/smw.2017.14522.

    Article  Google Scholar 

  75. White S, Foster R, Marks J, Morshead R, Goldsmith L, Barlow S, et al. The effectiveness of one-to-one peer support in mental health services: a systematic review and meta-analysis. BMC Psychiatry. 2020. https://doi.org/10.1186/s12888-020-02923-3.

    Article  Google Scholar 

  76. Granstrom E, Wannheden C, Brommels M, Hvitfeldt H, Nystrom ME. Digital tools as promoters for person-centered care practices in chronic care? Healthcare professionals’ experiences from rheumatology care. BMC Health Serv Res. 2020;20(1):1108.

    Article  Google Scholar 

  77. Speerin R, Slater H, Li L, Moore K, Chan M, Dreinhofer K, et al. Moving from evidence to practice: Models of care for the prevention and management of musculoskeletal conditions. Best Pract Res Clin Rheumatol. 2014;28(3):479–515.

    Article  Google Scholar 

  78. Dwyer AA, Quinton R, Morin D, Pitteloud N. Identifying the unmet health needs of patients with congenital hypogonadotropic hypogonadism using a web-based needs assessment: implications for online interventions and peer-to-peer support. Orphanet J Rare Dis. 2014;9:83.

    Article  Google Scholar 

  79. Spicer J, Budge C, Carryer J. Taking the PACIC back to basics: the structure of the Patient Assessment of Chronic Illness Care. J Eval Clin Pract. 2012;18(2):307–12.

    Article  Google Scholar 

  80. Muncer SJ, Speak B. Mokken scale analysis and confirmatory factor analysis of the Health of the Nation Outcome Scales. Personal Individ Differ. 2016;94:272–6.

    Article  Google Scholar 

Download references

Acknowledgements

We wish to thank the participating patients and the Swiss Scleroderma patient association for their generosity and collaboration. Special thanks to Ms. Sabine Herzig for her valuable support during the questionnaire data collection.

Funding

This publication is part of the Swiss MANagement Of Systemic Sclerosis (MANOSS) study and received funding from the Swiss Nursing Science Foundation and the Swiss League Against Rheumatism.

Author information

Authors and Affiliations

  1. Department Public Health (DPH), Institute of Nursing Science (INS), Faculty of Medicine, University of Basel, Bernoullistrasse 28, 4056, Basel, Switzerland

    Agnes Kocher, Michael Simon, Catherine Blatter, Jasmina Bogdanovic, Patrizia Künzler-Heule & Dunja Nicca

  2. Department of Rheumatology and Immunology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

    Agnes Kocher

  3. Department of Nursing, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland

    Michael Simon

  4. Boston College, Connell School of Nursing, Chestnut Hill, MA, USA

    Andrew A. Dwyer

  5. Center for Nursing Research, Massachusetts General Hospital Munn, Boston, MA, USA

    Andrew A. Dwyer

  6. Department of Gastroenterology/Hepatology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland

    Patrizia Künzler-Heule

  7. Department of Nursing, Cantonal Hospital St. Gallen, St. Gallen, Switzerland

    Patrizia Künzler-Heule

  8. Medical Center Monbijou, 3011, Bern, Switzerland

    Peter M. Villiger

  9. Service of Rheumatology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland

    Diana Dan

  10. Department of Rheumatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland

    Oliver Distler

  11. Department of Rheumatology, University Hospital Basel, Basel, Switzerland

    Ulrich A. Walker

  12. Department of Global and Public Health, Institute for Epidemiology, Biostatistics and Prevention, University of Zurich, Zurich, Switzerland

    Dunja Nicca

Authors
  1. Agnes Kocher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael Simon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrew A. Dwyer
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Catherine Blatter
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jasmina Bogdanovic
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Patrizia Künzler-Heule
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Peter M. Villiger
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Diana Dan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Oliver Distler
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ulrich A. Walker
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Dunja Nicca
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AK, MS, AAD, PMV and DN conceived and designed the work. AK, JB, PMV, DD, OD and UAW acquired the data of the first study phase, and AK, MS, CB, JB, PKH, and DN analyzed it. AK, PKH, JB and DN acquired and analyzed the data of the second study phase. AK, MS, CB, JB, PKH and DN contributed to interpreting the data and drafting the manuscript. All authors revised the subsequent drafts critically for important intellectual content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Agnes Kocher.

Ethics declarations

Ethics approval and consent to participate

The Swiss MANagement Of Systemic Sclerosis (MANOSS) cross-sectional study was reviewed and approved by the responsible Swiss ethics committee in September 2018 (EKNZ 2018‐01206). Patient information forms and informed consent documents complied with the Swiss ethics committee’s templates. All participants received a written explanation of the purpose of the study, the voluntary nature of their participation and the use of their contributions.

Consent for publication

Not applicable.

Competing interests

AK has a consultancy relationship with and/or has received research funding from Boehringer Ingelheim, Pfizer, Swiss Nursing Science Foundation, Swiss League Against Rheumatism, and University of Basel. She is an unpaid member of the EULAR recommendations for non-pharmacological management of autoimmune connective tissue diseases task force. AAD is an Associate Professor of Nursing at Boston College whose research focuses on developing more person-centered approaches to care. He receives funding from Boston College and the U.S. National Institutes of Health (U.S.A.) and receives funding to cover travel expenses for his faculty participation in a Swiss rare diseases summer school. Dr. Dwyer has no competing interests to declare. OD has/had consultancy relationship with and/or has received research funding from and/or has served as a speaker for the following companies in the area of potential treatments for systemic sclerosis and its complications in the last three calendar years: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, 4P Science, Galapagos, Glenmark, Horizon, Inventiva, Janssen, Kymera, Lupin, Medscape, Miltenyi Biotec, Mitsubishi Tanabe, MSD, Novartis, Prometheus, Redxpharna, Roivant, Sanofi and Topadur. Patent issued “mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143). Research Grants: Kymera, Mitsubishi Tanabe. MS, CB, JB, PKH, PM, DD, UAW, and DN declare they have no financial and non-financial interests that are directly or indirectly related to this work.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1

. Table 1a. Mokken scale analysis of global scale. Table 1b. Mokken scale analysis of subscales. Table 2a. Mokken scale analysis of global scale. Table 2b. Mokken scale analysis of subscales

Additional file 2

. Correlation matrix (pearson’s r) of mean PACIC-15 and SScQoL scores.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kocher, A., Simon, M., Dwyer, A.A. et al. Patient Assessment Chronic Illness Care (PACIC) and its associations with quality of life among Swiss patients with systemic sclerosis: a mixed methods study. Orphanet J Rare Dis 18, 7 (2023). https://doi.org/10.1186/s13023-022-02604-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13023-022-02604-2

Keywords

  • Health-related quality of life
  • Health services research
  • Nursing
  • Outcome and process assessment
  • Patient-centered care
  • Patient-reported outcome measures
  • Rare diseases
  • Rheumatology
  • Scleroderma
  • Systemic sclerosis

Orphanet Journal of Rare Diseases

ISSN: 1750-1172