Outpatients’ perceptions of collaboration across clinics and health literacy among patients with diabetes and at least one comorbidity: A hospital-level cross-sectional study

Abstract

Background: Patients with multiple chronic conditions often face fragmented care and inconsistent information, increasing their risk of serious health issues. Their perceived collaboration across clinics may be shaped by difficulties in accessing and using information for informed decision-making. This study explored the association between patient-perceived collaboration across clinics and health literacy among outpatients with diabetes and at least one comorbidity at the hospital level.

Methods: This cross-sectional study at the outpatient clinic at Steno Diabetes Center Aarhus included all patients with diabetes and at least one comorbidity who were simultaneously receiving treatment at another outpatient clinic within the hospital. The association between patient-perceived extensive collaboration across clinics (exposure) and patient health literacy (outcome) was assessed using four selected scales and regression models. Results were presented as both unadjusted and adjusted, accounting for potential confounders.

Results: A total of 3,435 outpatients received a survey, with 1,655 responses. Of these, 686 reported receiving cross-clinic treatment. Among the 552 respondents who answered the exposure-related question, 44.7% perceived extensive collaboration across clinics, while 55.3% perceived limited collaboration. Statistically significant differences were found in three out of four health literacy scales, with those who perceived limited collaboration scoring lower in areas related to managing their health and engaging with healthcare providers.

Conclusion: The findings suggest that outpatients with comorbidities and perceived poor clinic collaboration may have low health literacy, highlighting the need to address this in their treatment and communication with healthcare providers. Future research is needed to determine whether limited perception arises from personal challenges, elements of the treatment process, or relational and organizational issues across clinics, in order to improve the perception of collaboration and clinical outcomes.

Keywords

diabetes collaboration health literacy patient-reported outcomes multimorbidity

Introduction

The growing number of individuals with multiple chronic conditions presents a significant global health challenge.¹ Effectively managing the complex needs of these patients requires strong collaboration in multimorbidity care. Without proper care coordination, there is a heightened risk of fragmented care, which undermines patient safety through poor integration, high treatment burdens, and inadequate communication among healthcare professionals.^2,3 As a result, many patients feel lost within the healthcare system,³ which can severely impact patients’ health-related quality of life and treatment outcomes.^4,5

Diabetes is one of the most prevalent chronic conditions associated with multimorbidity,^6,7 leading to various organisational and personal health-related issues. These include increased healthcare utilization and costs,⁸ higher mortality rates,⁹ greater burden of disease,¹⁰ increased treatment burden,¹¹ fragmented care,¹² and decreased health-related quality of life.⁴ Multimorbidity is associated with declining health literacy, as evidence indicates that health literacy decreases with the number of chronic conditions.^13,14 Health literacy reflects the knowledge and confidence required for individuals to improve their health and living conditions and is essential for empowering individuals to engage in their healthcare.^15,16 In this context, collaboration across outpatient clinics seems particularly important for those with lower health literacy.¹⁷

Despite the limited knowledge regarding collaboration across outpatient clinics within the diabetes population and its specific settings,^18–21 it is crucial to explore whether individuals’ experiences of collaboration are related to health literacy. Understanding this relationship could significantly impact overall health outcomes and the effectiveness of care delivery. This study represents one of the first efforts to suggest that collaboration across outpatient clinics may influence the health literacy of patients receiving care. This study aimed to explore the association between outpatients’ perceived collaboration across hospital clinics for individuals with multiple conditions and health literacy.

Methods

Study context

In this study, data were collected from a prior initiative at Steno Diabetes Center Aarhus, Aarhus University Hospital, which aimed to develop and test multidisciplinary team meetings. These meetings brought together patients and hospital specialists to address treatment-related challenges across clinics. In Q1 2023, a survey was distributed via e-Boks, a secure Danish communication platform, to 3,435 adults affiliated with the diabetes clinic, excluding 296 individuals who participated in a pilot test of the questionnaire and 377 who did not have an e-Boks account. Survey data were also linked to the Central Denmark Region’s data warehouse to calculate the Charlson Comorbidity Index.²² The warehouse contains information from clinical electronic health records and operational databases, capturing patient-specific data such as demographics, medical history, diagnoses, treatments, and outcomes.²³

Current study

Study design and population

In this cross-sectional study, a subpopulation of adult outpatients with diabetes and at least one comorbidity was selected based on survey responses from Steno Diabetes Center Aarhus, indicating they received treatment at both the diabetes clinic and other clinics within Aarhus University Hospital.

Exposure

Exposure was classified as either extensive or limited collaboration across outpatient clinics, based on the survey question regarding participants’ perceptions: ‘To what extent do you feel that the diabetes clinic and other clinics at the hospital collaborate on your treatment?’ Participants could respond with: 1) To a very great extent, 2) To a great extent, 3) To some extent, 4) To a small extent, 5) Not at all, or 6) Do not know. These response categories were dichotomously classified into: 1) Extensive collaboration across clinics (options 1 and 2), and 2) Limited collaboration across clinics (options 3, 4, and 5). Response option 6 was excluded.

Outcomes

The outcome measured was health literacy, defined as the ability to find, understand, and use information and services to make informed health decisions. The questionnaire included 4 out of 9 scales from the validated Health Literacy Questionnaire (HLQ),^24,25 all of which were chosen specifically for their relevance in assessing person-related factors that could shape patients’ perceptions of collaboration across clinics. These were Scale 2 ‘Having sufficient information to manage my health’, Scale 5 ‘Appraisal of health information’, Scale 6 ‘Actively engage with healthcare providers’, and Scale 9 ‘Understanding health information well enough to know what to do’. Each represents an outcome of the study and with a range between 1 (lowest ability) and 4 or 5 (highest ability).²⁵

Covariates and data sources

The covariates were identified as potential confounders based on insights from the literature and data obtained from distributed questionnaires. These included sociodemographic factors such as sex, age, educational level, occupational status, cohabitation status, treatment burden, well-being , and the Charlson Comorbidity Index.^13,14,20,26 The Danish version of the Multimorbidity Treatment Burden Questionnaire (MTBQ) was used to assess respondents’ treatment burden.²⁷ The MTBQ is a validated questionnaire comprising ten questions that cover various aspects of treatment burden, including medication use, healthcare appointments, lifestyle changes, self-monitoring, and reliance on others such as family and friends.^27,28 Responses were scored as follows: ‘does not apply’ and ‘not difficult’ as 0, ‘a little difficult’ as 1, ‘quite difficult’ as 2, ‘very difficult’ as 3, and ‘extremely difficult’ as 4. Patients with more than 50% missing responses were excluded. The average score for each participant was calculated from answered questions and multiplied by 25 to yield a global MTBQ score (0-100). Treatment burden was categorized into four levels: no burden (score 0), low burden (score <10), medium burden (score 10-22), and high burden (score >22).^27,28 The WHO-5 Well-Being Index (WHO-5) was used to measure respondents’ subjective well-being.²⁹ WHO-5 is a brief questionnaire consisting of five questions. Responses were assigned the following scores: ‘always’ as 5, ‘most of the time’ as 4, ‘slightly more than half the time’ as 3, ‘slightly less than half the time’ as 2, ‘a little of the time’ as 1, and ‘never’ as 0. To calculate the total score, all selected values were summed and then multiplied by 4, yielding a score between 0 and 100. A higher score reflects better well-being, while a score of 50 or below indicates a risk for stress or depression.²⁹ According to a systematic review, the WHO-5 has demonstrated validity as an outcome measure in clinical studies and has been successfully applied across various research fields.²⁹ The Charlson Comorbidity Index (CCI), classifies the severity of multimorbidity by summing the assigned weights of all comorbid conditions recorded in a patient’s medical records over the past five years, prior to the distribution of our questionnaire. Higher scores indicate more severe conditions and, consequently, a worse prognosis.²² CCI is a valid method for estimating the mortality risk associated with multimorbidity.²² The groupings of the individual covariates are shown in Table 1.

Table 1.

Description of the study population grouped by patients’ perceived extensive and limited collaboration across outpatient clinics.

	Total		Extensive collaboration		Limited collaboration		P-value
	N=552		N=247		N=305
	n	(%)	n	(%)	n	(%)
Age	63.0	(13.7)^a	64.6	(12.5)^a	61.8	(14.5)^a	0.020
Sex
Male	335	(60.7)	167	(67.6)	168	(55.1)	0.003
Female	217	(39.3)	80	(32.4)	137	(44.9)	0.003
Education level
None, short courses and other	136	(24.6)	75	(30.4)	61	(20.0)	0.006
Skilled worker	214	(38.8)	98	(39.7)	116	(38.0)
Higher education (until 4 years)	113	(20.5)	42	(17.0)	71	(23.3)
Higher education (more than 4 years)	80	(14.5)	27	(10.9)	53	(17.4)
Missing	9	(1.9)	5	(2.0)	4	(1.3)
Cohabitation status
Yes	346	(62.7)	159	(64.4)	187	(61.3)	0.616
No	177	(32.1)	74	(30.0)	103	(33.8)
Missing	29	(5.3)	14	(5.7)	15	(4.9)
Occupation status
Full time	106	(19.2)	46	(18.6)	60	(19.7)	0.127
Part time	72	(13.0)	24	(9.7)	48	(15.7)
Retirement	336	(60.9)	157	(63.6)	179	(58.7)
Unemployed or other	37	(6.7)	20	(8.1)	17	(5.6)
Missing	1	(0.2)	-		1	(0.3)
Diabetes type
Type 1 diabetes	282	(51.1)	113	(45.7)	169	(55.4)	0.024
Type 2 diabetes	270	(48.9)	134	(54.3)	136	(44.6)	0.024
Treatment burden
No one	68	(12.3)	49	(19.8)	19	(6.2)	0.000
Low	122	(22.1)	63	(25.5)	59	(19.3)
Medium	168	(30.4)	75	(30.4)	93	(30.5)
High	188	(34.1)	57	(23.1)	131	(43.0)
Missing	6	(1.1)	3	(1.2)	3	(1.0)
Charlson comorbidity index
None	105	(19.0)	43	(17.4)	62	(20.3)	0.185
1-2	152	(27.5)	59	(23.9)	93	(30.5)
3-4	167	(30.3)	81	(32.8)	86	(28.2)
≥5	128	(23.2)	64	(25.9)	64	(21.0)
Well-being	63^a	(18.2)	69.0	(16.9)^a	57.7	(17.6)^a	0.000

^aNote: Mean (Standard Deviation).

Statistical methods

Descriptive statistical analysis was used to present patient characteristics and the distribution between patient-perceived extensive and limited collaboration across clinics. Categorical variables were presented as proportions, and numerical variables as means. Chi-square tests and t-tests were used to assess differences between the two groups. Four linear regression models were conducted to investigate the association between patient-perceived collaboration across clinics (exposure) and each of the four health literacy scales (outcomes). Patients with missing responses to the exposure questions or ‘do not know’ answers were excluded. For the outcome, sum scores for each health literacy scale were calculated as the mean of the item scores and standardized to a range of 1 (lowest ability) to 4 or 5 (highest ability). If more than two items were missing, the participant’s score was marked as missing, in accordance with the Danish HLQ validation coding rules.²⁵ Adjusted analyses were conducted with the following potential confounders: sex, age, educational level, cohabitation status and CCI.

We examined effect modification by adding interaction terms to our regression models and subsequently tested their statistical significance by use of Wald tests. In the adjusted analyses, the total number varied between the unadjusted and adjusted models due to the exclusion of missing data for potential confounding variables, allowing for complete-case analyses.³⁰ The statistical significance level was set at p < 0.05. Model controls for each linear regression were conducted and accepted. All statistical analyses were performed using Stata Statistical Software: Release 18. College Station, TX: StataCorp LLC.

Results

Out of 3,435 adults who received the questionnaire, the response rate was 48.2% (n=1,655). Among the respondents, 41.5% (n=686) reporting cross-clinic contacts for non-diabetes conditions at the same hospital (Figure 1). Of these, 94 were excluded for missing responses to the exposure questions, and 40 more for answering ‘do not know’. Ultimately, the final study population consisted of 552 respondents.

Figure 1.

Flowchart of study population.

Non-responder analysis

A total of 51.8% (n=1,780) of the participants who received the questionnaire did not respond, making it impossible to determine how many had cross-clinical contact, which was an inclusion criterion for this study. As a result, a non-responder analysis could not be conducted. Additionally, 134 out of the 686 patients who responded to the questionnaire were excluded: 94 for missing responses and 40 for answering ‘do not know’ to the exposure question. An analysis of the 134 excluded respondents revealed that those excluded were often females, living alone, working full-time, and with Type 1 diabetes, and had fewer chronic conditions compared to those included (shown in Appendix A). Notably, 31.3% of excluded patients had no chronic conditions other than diabetes, suggesting that collaboration across clinics may be less relevant, while 33.6% had 1-2 additional chronic conditions (shown in Appendix A).

Description of the study population

The study population consisted of 552 participants, of whom 44.7% (n=247) perceived extensive collaboration across clinics, while 55.3% (n=305) perceived limited collaboration (Table 1). Patients who perceived limited collaboration were younger, predominantly female, and had higher education levels (Table 1). They were more likely to live alone, be employed, and experience a higher prevalence of Type 1 diabetes and treatment burden, while reporting fewer chronic conditions and poorer well-being compared to patients who perceived extensive collaboration (Table 1).

Association models

Table 2 shows that, for three out of four health literacy scales, patients who perceived limited collaboration had a statistically significantly lower health literacy score compared to those who perceived extensive collaboration. Prior to the adjusted analyses, the variables controlled for were assessed as potential effect modifiers in each scale, with sex identified as a potential effect modifier for scale 6. The crude effects were −0.501 (95% CI: −0.643; −0.361), and the effect of sex on this association was −0.766 (95% CI: −0.997; −0.535).

Table 2.

Crude and adjusted coefficients for the health literacy score at scales 2, 5, 6, and 9 in patients’ perceived limited and extensive collaboration across clinics.

	Association model
	Mean health literacy score (SD)	Unadjusted		Adjusted
	Mean health literacy score (SD)	Coeff. (95% CI)	P-value	Coeff. (95% CI)	P-value
Scale 2 Perceived sufficiency of information to manage health
Limited collaboration	2.931 (0.59)	−0.199 (−0.302; −0.096)^a	0.000	−0.210 (−0.318; −0.102)^b,c	0.000
Extensive collaboration	3.130 (0.60)	Reference	-	Reference	-
Scale 5 Appraisal of health information
Limited collaboration	2.706 (0.60)	−0.076 (−0.182; 0.029)^d	0.156	−0.106 (−0.215; 0.003)^c,e	0.056
Extensive collaboration	2.783 (0.61)	Reference	-	Reference	-
Scale 6 Ability to actively engage with healthcare providers
Limited collaboration	3.564 (0.85)	−0.501 (−0.643; −0.361)^f	0.000	−0.503 (−0.652; −0.354)^c,g	0.000
Extensive collaboration	4.066 (0.77)	Reference	-	Reference	-
Scale 9 Understanding health information well enough to know what to do
Limited collaboration	3.759 (0.70)	−0.184 (−0.309; −0,059)^d	0.004	−0.269 (−0.398; −0.140)^c,e	0.000
Extensive collaboration	3.942 (0.73)	Reference	-	Reference	-

Note. SD=Standard Deviation, CI=Confidence Interval.

^aN=525.

^bN=490.

^cAdjusted for sex, age, education level, cohabitation status, and CCI.

^dN=515.

^eN=480.

^fN=516.

^gN=481.

Discussion

This study aimed to explore the association between outpatients’ perceived collaboration across clinics and patient health literacy. Significant differences were found in three out of four health literacy scores, with outpatients perceiving limited collaboration across clinics scoring lower in managing their health, engaging with healthcare providers, and understanding health information compared to those perceiving extensive collaboration.

More than half of the respondents in our study perceived limited collaboration across clinics, which may reflect the varying levels of biomedical knowledge patients bring into the healthcare setting, based on their past experiences or how well their expectations are met.³¹ In this context, inadequate health literacy could also play a significant role, as it affects the use of health services, impacts patient satisfaction, and hinders the physician-patient relationship, a crucial barrier to effective healthcare delivery and quality outcomes.^32,33 Although our study did not examine health outcomes across clinics, this highlights the need for further research to identify relevant, actionable solutions. Other studies have reported patients’ perspectives on collaboration, including healthcare providers’ perceived lack of knowledge about their condition, insufficient holistic care and support, poor care management, and inadequate communication between healthcare providers.^34–36 Moreover, patients have perceived the importance of being actively involved in their care and having their treatment systematically coordinated with accurate information and clear instructions.^36,37 This, however, can be particularly challenging for patients with low health literacy, especially when complex treatment needs involve multiple clinics. Overall, health literacy may influence patients’ perception of a lack of collaboration across clinics, though it does not rule out the possibility of poor collaboration in reality. In this context, effective communication from healthcare providers becomes crucial, and several studies have proposed strategies to improve communication and health outcomes for patients with low health literacy.^38,39 Additionally, it cannot be ruled out that the large proportion of patients who perceived limited collaboration in our study may stem from the challenge of assessing, through our exposure question, whether collaboration is necessary, as care across multiple clinics does not always require it. Therefore, a more precisely formulated question could be proposed to better capture the nuances of collaboration in such contexts, potentially leading to more accurate results.

The significance of our results warrants discussion, as our findings reveal that the mean health literacy scores for patients perceived extensive and limited collaboration are above average on the four scales used in this study.²⁵ This is particularly notable given that ten to twenty percent of the Danish population struggles with key health literacy dimensions, such as understanding health information well enough to act on it and actively engaging with healthcare providers.⁴⁰ Nonetheless, our results are intriguing, as some patients with lower health literacy scores still perceive extensive collaboration, a factor not explored in this study. This suggests that health literacy alone is insufficient to guide initiatives aimed at improving patients’ experiences of collaboration across clinics. Our findings on differences in patient characteristics between those who perceived extensive and limited collaboration may hint at a profile to focus on; however, this result stands alone due to the lack of a clearly defined patient profile in the literature, making it difficult to discuss our findings. A complement to health literacy scores could be a patient-centred approach to uncover what individual patients have based their responses on when perceiving limited collaboration.⁴¹ This approach would help identify the specific factors influencing their views and allow for more targeted interventions to address any barriers to effective collaboration.

Strengths and limitations

A strength of this study is that all adult outpatients affiliated with Steno Diabetes Center Aarhus were invited to participate using e-Boks to distribute the questionnaire and reminders. The response rate is slightly below the reported average for online surveys, which stands at 44.1%.⁴² A limitation of this distribution method is that patients not registered with e-Boks may face physical or mental challenges that hinder its use, or they may be older individuals with low digital literacy⁴³ that could bias our results. Moreover, a non-responders’ analysis could not be conducted due to missing data, which is a limitation of this study, as it prevents us from assessing participation bias. Such bias may be present, as some individuals are reported to face barriers to participation, including language difficulties, physical limitations, or mental health issues.⁴⁴ Additionally, those with the lowest health literacy are more likely to refrain from participating.⁴⁵

The exhaustiveness of the exposure question was assessed by interviewing individual outpatients in the diabetes clinic. In this study, the exposure question, ‘To what extent do you feel that the diabetes clinic and other clinics at the hospital collaborate on your treatment?’ may be unclear, as it could refer to both administrative collaboration between clinics and professional collaboration between specialists. Since the study uses existing data, we can only critically assess how patients understood the question, which may affect the results. However, the response categories for exposure did not appear to be exclusive, as ‘not relevant’ was not an option. Furthermore, the lack of information about the type of collaboration respondents based their answers on complicates our understanding of the sources of limited collaboration and hinders the development of initiatives to address it. The dichotomous grouping of exposure was implemented based on methods used in previous studies.⁴⁶ The combination of the four selected HL scales has been a strength of the study, as covering functional, communicative, and critical health literacy provides a more nuanced picture of health literacy.²⁴ Although the strategy for calculating HL sum scores resulted in varying totals in the unadjusted analyses, potentially introducing bias, the minimal missing data on each covariate led to few excluded cases in our complete-case strategy, thereby minimizing potential bias overall.^30,46

Conclusion

The findings suggest that outpatients with multiple chronic conditions who perceived limited collaboration across clinics may have low health literacy, highlighting the need to address this in their treatment and communication with healthcare providers. Future research is needed to explore whether limited experience stems from personal challenges, aspects of the treatment process, or relational and organizational issues across clinics, with the goal of improving collaboration experience and clinical outcomes.

Footnotes

Acknowledgements

Thank you to everyone who participated in the survey; your insights were essential in making this important work possible.

ORCID iDs

Mikkel Aagaard

Charlotte Gjørup Pedersen

Statements and declarations

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The project has received funding from the Novo Nordisk Foundation, grant number NNF20SA0035556.

Conflicting interests

The author(s) declare no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

All data underlying this research will be made available on reasonable request to the authors. *

Appendix

Appendix A. Analysis of excluded patients who did not respond to the exposure question compared to those who did.

	Study population		Excluded^a		P-value
	N=552		N=134
	n	(%)	n	(%)
Age	63.0^b	(13.7)^b	60.7^b	(16.5)^b	0.135
Sex
Male	335	(60.7)	63	(47.0)	0.004
Female	217	(39.3)	71	(53.0)	0.004
Education level
None, short courses and other	136	(24.6)	37	(27.6)	0.229
Skilled worker	214	(38.8)	48	(35.8)
Higher education (until 4 years)	113	(20.5)	22	(16.4)
Higher education (more than 4 years)	80	(14.5)	21	(15.7)
Missing	9	(1.6)	6	(4.5)
Cohabitation status
Yes	346	(62.7)	34	(25.4)	<0.001
No	177	(32.1)	91	(67.9)
Missing	29	(5.3)	9	(6.7)
Occupation status
Full time	106	(19.2)	33	(24.6)	0.007
Part time	72	(13.0)	17	(12.7)
Retirement	336	(60.9)	72	(53.7)
Unemployed or other	37	(6.7)	8	(6.0)
Missing	1	(0.2)	4	(3.0)
Diabetes type
Type 1 diabetes	282	(51.0)	75	(56.0)	<0.001
Type 2 diabetes	270	(49.0)	56	(41.8)
Missing			3	(2.2)
Charlson comorbility index
None	105	(19.0)	42	(31.3)	<0.001
1-2	152	(27.5)	45	(33.6)
3-4	167	(30.3)	23	(17.2)
>5	128	(23.2)	24	(17.9)

^aExcluded Due to Missing Response on Exposure Question.

^bMean (Standard Deviation).

Note. Categorical variables were presented as proportions, and numerical variables as means. Chi-square tests and t-tests were used to assess differences between the two groups.

References

Tinajero

Malik

. An Update on the Epidemiology of Type 2 Diabetes: A Global Perspective. Endocrinol Metab Clin North Am 2021; 50(3): 337–355.

Mercer

Furler

Moffat

, et al. Multimorbidity: technical series on safer primary care: World Health Organization, 2016.

Schiøtz

Høst

Frølich

. Involving patients with multimorbidity in service planning: perspectives on continuity and care coordination. Journal of comorbidity 2016; 6(2): 95–102.

Fortin

Lapointe

Hudon

, et al. Multimorbidity and quality of life in primary care: a systematic review. Health and quality of life outcomes 2004; 2(1): 51.

Prior

Vestergaard

Vedsted

, et al. Healthcare fragmentation, multimorbidity, potentially inappropriate medication, and mortality: a Danish nationwide cohort study. BMC medicine 2023; 21(1): 305.

Zhang

Padhi

Wei

, et al. Community prevalence and dyad disease pattern of multimorbidity in China and India: a systematic review. BMJ global health 2022; 7(9): e008880.

Prados-Torres

Calderón-Larrañaga

Hancco-Saavedra

, et al. Multimorbidity patterns: a systematic review. Journal of clinical epidemiology 2014; 67(3): 254–266.

Glynn

Valderas

Healy

, et al. The prevalence of multimorbidity in primary care and its effect on health care utilization and cost. Family practice 2011; 28(5): 516–523.

Lee

Shields

Vogeli

, et al. Mortality rate in veterans with multiple chronic conditions. Journal of general internal medicine : JGIM 2007; 22(S3): 403–407.

10.

Rosbach

Andersen

. Patient-experienced burden of treatment in patients with multimorbidity - A systematic review of qualitative data. PloS one 2017; 12(6): e0179916.

11.

Friis

Lasgaard

Pedersen

, et al. Health literacy, multimorbidity, and patient-perceived treatment burden in individuals with cardiovascular disease. A Danish population-based study. Patient education and counseling 2019; 102(10): 1932–1938.

12.

Ivd

Snoeijs

Melchiorre

, et al. Innovating care for people with multiple chronic conditions in Europe. NIVEL, 2015.

13.

Friis

Lasgaard

Osborne

, et al. Gaps in understanding health and engagement with healthcare providers across common long-term conditions: a population survey of health literacy in 29 473 Danish citizens. BMJ open 2016; 6(1): e009627.

14.

Pedersen

Aaby

Friis

, et al. Multimorbidity and health literacy: A population-based survey among 28,627 Danish adults. Scandinavian journal of public health 2023; 51(2): 165–172.

15.

Nutbeam

Kickbusch

. Advancing health literacy: a global challenge for the 21st century. Health promotion international 2000; 15(3): 183–184.

16.

Nutbeam

DON

. Health literacy as a public health goal: a challenge for contemporary health education and communication strategies into the 21st century. Health promotion international 2000; 15(3): 259–267.

17.

Stømer

Wahl

Gøransson

, et al. Exploring health literacy in patients with chronic kidney disease: a qualitative study. BMC nephrology 2020; 21(1): 314.

18.

Mora-Pinzon

Chrischilles

Greenlee

, et al. Variation in coordination of care reported by breast cancer patients according to health literacy. Supportive care in cancer 2019; 27(3): 857–865.

19.

Lim

Huang

Shepherd

, et al. Health literacy and cancer care coordination in Chinese migrant patients and their carers: A cross-sectional survey. Psycho-oncology (Chichester, England) 2019; 28(5): 1048–1055.

20.

MacLeod

Musich

Gulyas

, et al. The impact of inadequate health literacy on patient satisfaction, healthcare utilization, and expenditures among older adults. Geriatric nursing (New York) 2017; 38(4): 334–341.

21.

Hawley

Janz

Lillie

, et al. Perceptions of care coordination in a population-based sample of diverse breast cancer patients. Patient education and counseling 2010; 81(S1): S34–S40.

22.

Charlson

Pompei

Ales

, et al. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of chronic diseases 1987; 40(5): 373–383.

23.

Bager-Elsborg

JR.

Description of the BI Data Warehouse for reserarch purposes in Cental Denmark Region. 2023. [Available from]: https://www.rm.dk/contentassets/7b6dcaf5c7554c139b4ec054822bc4cf/reference-til-forskning.pdf

24.

Osborne

Batterham

Elsworth

, et al. The grounded psychometric development and initial validation of the Health Literacy Questionnaire (HLQ). BMC public health 2013; 13(1): 658.

25.

Maindal

Kayser

Norgaard

, et al. Cultural adaptation and validation of the Health Literacy Questionnaire (HLQ): robust nine-dimension Danish language confirmatory factor model. SpringerPlus 2016; 5(1): 1232.

26.

Balbale

Etingen

Malhiot

, et al. Perceptions of Chronic Illness Care Among Veterans With Multiple Chronic Conditions. Military medicine 2016; 181(5): 439–444.

27.

Pedersen

Duncan

Lasgaard

, et al. Danish validation of the Multimorbidity Treatment Burden Questionnaire (MTBQ) and findings from a population health survey: a mixed-methods study. BMJ open 2022; 12(1): e055276.

28.

Duncan

Murphy

Man

M-S

, et al. Development and validation of the Multimorbidity Treatment Burden Questionnaire (MTBQ). BMJ open 2018; 8(4): e019413.

29.

Topp

Østergaard

Søndergaard

, et al. The WHO-5 Well-being index: A systematic review of the literature. Psychotherapy and psychosomatics 2015; 84(3): 167–176.

30.

Pedersen

Mikkelsen

Cronin-Fenton

, et al. Missing data and multiple imputation in clinical epidemiological research. Clinical epidemiology 2017: 157–166.

31.

Weinman

. Doctor–patient interaction: psychosocial aspects. 2001.

32.

Rasu

Bawa

Suminski

, et al. Health Literacy Impact on National Healthcare Utilization and Expenditure. Int J Health Policy Manag 2015; 4(11): 747–755.

33.

Kripalani

Jacobson

Mugalla

, et al. Health literacy and the quality of physician-patient communication during hospitalization. J Hosp Med 2010; 5(5): 269–275.

34.

van der Aa

van den Broeke

Stronks

, et al. Patients with multimorbidity and their experiences with the healthcare process: a scoping review. J Comorb 2017; 7(1): 11–21.

35.

Head

Forster

Harsin

, et al. Identifying sources of patient dissatisfaction when seeking care for a chronic and complex disease. Patient Experience Journal 2023; 10(2): 94–102.

36.

Gilchrist Miss

Kholvadia

Dr A

. Patients’ Perceptions of Interprofessional Collaboration: A Scoping Review. Patient Experience Journal 2024; 11(1): 154–172.

37.

Beaudin

Lammers

Pedroja

. Patient Perceptions of Coordinated Care: The Importance of Organized Communication in Hospitals. Journal for healthcare quality 1999; 21(5): 18–23.

38.

Muscat

Shepherd

Nutbeam

, et al. Health Literacy and Shared Decision-making: Exploring the Relationship to Enable Meaningful Patient Engagement in Healthcare. J Gen Intern Med 2021; 36(2): 521–524.

39.

Richter

Jansen

Bongaerts

, et al. Communication of benefits and harms in shared decision making with patients with limited health literacy: A systematic review of risk communication strategies. Patient Educ Couns 2023; 116: 107944.

40.

Friis

Osborne

, et al. National indicators of health literacy: ability to understand health information and to engage actively with healthcare providers - a population-based survey among Danish adults. BMC Public Health 2014; 14: 1095.

41.

Grover

Fitzpatrick

Azim

, et al. Defining and implementing patient-centered care: An umbrella review. Patient Educ Couns 2022; 105(7): 1679–1688.

42.

M-J

Zhao

Fils-Aime

. Response rates of online surveys in published research: A meta-analysis. Computers in Human Behavior Reports 2022; 7: 100206.

43.

Mancino

. Digital literacy in the EU: An overview: European data. 2023. [Available from]: https://data.europa.eu/en/publications/datastories/digital-literacy-eu-overview

44.

Gayet-Ageron

Agoritsas

Schiesari

, et al.

Barriers to participation in a patient satisfaction survey: who are we missing?

PLoS One 2011; 6(10): e26852.

45.

Svendsen

Bak

Sørensen

, et al. Associations of health literacy with socioeconomic position, health risk behavior, and health status: a large national population-based survey among Danish adults. BMC Public Health 2020; 20(1): 565.

46.

Mirzaei

Carter

Patanwala

, et al. Missing data in surveys: Key concepts, approaches, and applications. Research in social and administrative pharmacy 2022; 18(2): 2308–2316.

47.

World Medical Association . WMA Declaration of Helsinki - Ethical Principles for Medical Research Involving Human Subjects. WMA, 2022. [Available from]: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/