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Validation of an instrument for the assessment of patient-centred care among patients with multimorbidity in the primary care setting: the 36-item patient-centred primary care instrument

BMC Family Practice volume 19, Article number: 143 (2018) Cite this article

Abstract

Background

Validated instruments are needed to assess the delivery of patient-centred care (PCC) to patients with multimorbidity in the primary care setting. Eight dimensions of PCC have been identified: respect for patients’ preferences, access to care, emotional support, information and education, involvement of family and friends, continuity and secure transition between health care settings, physical comfort, and coordination of care. The main objective of this study was to validate an instrument for the assessment of PCC among patients with multimorbidity in the primary care setting: the 36-item patient-centred primary care (PCPC) instrument.

Methods

We included patients with multimorbidity from seven health care practices in the region of Tilburg, the Netherlands. All patients enrolled in at least two chronic care programmes (involving diagnosis of and treatment for combinations of diabetes, asthma and/or chronic obstructive pulmonary disease, cardiovascular diseases and conditions, and age-related frailty) were selected from the practices’ data registries and included as eligible participants. A total of 216 patients with multimorbidity filled in the study questionnaire (55% response rate). We tested the instrument using structural equation modelling, and examined its validity and reliability.

Results

Confirmatory factor analyses revealed good indices of fit and overall internal consistency, as represented by Cronbach’s alpha values. All eight dimensions of PCC were related positively to satisfaction with care (all p ≤ 0.001). Patients with multimorbidity who experienced joint decision making and responsibility taking in the primary care setting also had significantly higher scores for all eight PCC dimensions, indicating the instrument’s construct validity.

Conclusions

We conclude that the psychometric properties of the 36-item PCPC instrument are good. Based on these results the PCPC instrument seems a promising tool for the assessment of PCC among patients with multimorbidity in the primary care setting.

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Background

The number of people with chronic diseases is increasing at an astonishing rate, making millions of patients reliant on primary care systems. As a consequence, such systems throughout the world are struggling to find the best way to deal with large numbers of chronically ill patients while keeping costs low and quality high [1]. Patients with multimorbidity are known to report even worse well-being and health outcomes than do individuals with single chronic conditions [2]. Furthermore, they are more likely to be hospitalised and are at greater risk of premature death than are patients with single chronic diseases [3, 4]. The prevalence of multimorbidity in Europe is currently about 65% among people aged ≥60 years and 85% among those aged ≥85 years [5,6,7]. Thus, 50 million people in Europe have at least two chronic diseases, and this number is expected to grow as populations age.

Providing optimal care for older patients with (multiple) chronic diseases is actually among the greatest challenges of the healthcare spectrum today [8]. Health professionals clearly express the concern that they often missed the opportunity to engage with multimorbidity patients as true partners in their care and really help them to manage their conditions at home. This situation represents a missed opportunity, as the outpatient primary care setting is precisely the context identified as most appropriate to effectively deal with ageing populations [6,7,8]. The complexity of many chronic diseases and frailty profiles that come with multimorbidity demands Patient Centred Care (PCC), such that multimorbidity patients are equipped with the information and skills necessary to act as co-producers or co-creators of their care and where abilities to maintain overall well-being are optimised [7,8,9]. Such care supports active involvement of patients in the design of new care models and in decision making about individual treatment options. Decisions need to be based on personal preferences, needs and circumstances of each patient in every aspect of their live beyond physical health and clinical outcomes only [9,10,11,12,13].

The Harvard School of Medicine collaborated with the Picker Institute to conduct a very comprehensive study of the constituents of PCC [14, 15]. These researchers identified the following eight dimensions of PCC: respect for patients’ values, preferences and expressed needs, provision of information and education, access to care, emotional support to relieve fear and anxiety, involvement of family and friends, continuity and secure transition between health care settings, physical comfort, and coordination of care [14,15,16]. A consultation of additional PCC literature [17,18,19,20,21] revealed no additional aspect or dimension of PCC. Table 1 provides detailed descriptions of the eight PCC dimensions in general [14,15,16,17,18,19,20,21] and describes them for patients with multimorbidity receiving primary care in particular as derived from the literature [22,23,24,25].

Table 1 The eight dimensions of patient-centred care in the primary care setting for patients with multimorbidity
Full size table

In a systematic review, Rathert and colleagues [16] showed that organisations which perform well in multiple PCC dimensions report better organisational and patient outcomes (e.g. improved care processes, clinical outcomes, cost reduction). For example, care that is well coordinated, easily accessible, providing physical comfort and attending patients’ emotional needs is known to increase patients’ satisfaction with care as well as improve joint decision making and responsibility taking [16, 26,27,28,29]. Organisations implementing interventions falling into several PCC dimensions reported better outcomes than did those aiming to improve single PCC dimensions, indicating that a constellation of interventions in multiple PCC dimensions leads to better outcomes [16].

Although we have considerable evidence for the benefits of investing in the improvement of the eight PCC dimensions [14,15,16] to achieve better organisational and patient outcomes, we lack instruments and research investigating the effects of these eight dimensions, especially among patients with multimorbidity in the primary care setting. A broader understanding of patients’ experiences with these PCC aspects is important as they could help to improve the organisation and provision of care for this population, which is expected to lead to better outcomes (e.g. improved satisfaction with care, enhanced self-management abilities and well-being) [16, 22,23,24,25]. The measurement of levels of PCC among patients with multimorbidity is the first step. Therefore, the main objective of this study is to validate an instrument for the assessment of PCC among patients with multimorbidity in the primary care setting: the 36-item patient-centred primary care (PCPC) instrument. Based on earlier research we expected that investment in the eight dimensions of PCC would be associated positively with satisfaction with care [16]. In addition, we expected that the occurrence of joint decision making and responsibility taking, as perceived by patients with multimorbidity, would align with their experiences with PCC.

Methods

We included adult patients with multimorbidity from seven health care practices in the region of Tilburg, the Netherlands. All patients enrolled in at least two chronic care programs (involving diagnosis of and treatment for combinations of diabetes, asthma and/or chronic obstructive pulmonary disease, cardiovascular diseases and conditions, and age-related frailty) were selected from the data registries of the practices and included as eligible participants. All adult patients with at least two registered chronic conditions (n = 413) were eligible to participate. No additional inclusion criterion was applied. Exclusion criteria were too ill to participate and no longer a patient of the health care practices under study. First, these selected patients received questionnaires at home via post. Three weeks later, reminder notices were sent to non-respondents. Another three weeks later, second reminder notices with duplicates of the questionnaire were sent. Finally, when telephone numbers were available, we called non-respondents to ask them to fill in the questionnaire. Nineteen respondents appeared not eligible to participate due to incorrect addresses (n = 5), recent moves (n = 2), death (n = 4), admission to a hospice or nursing home due to terminal illness (n = 2), poor cognitive function preventing questionnaire filling (n = 2), recent stroke (n = 1), and poor eyesight (n = 3). Of the remaining 394 patients a total of 216 patients with multimorbidity filled in the questionnaire. Thus, the final response rate was 55%.

The medical ethics committee of Erasmus Medical Centre, Rotterdam, the Netherlands determined that the rules stipulated in the Medical Research Involving Human Subjects Act did not apply to this study (protocol no. MEC-2018-021). Written informed consent to participate in the study was obtained from all participants.

Measures

Patient-centred primary care

The eight dimensions of PCC identified by the Picker Institute were used as a framework for the development of an instrument to assess PCC in the primary care setting for patients with multimorbidity. The development of the patient-centred primary care (PCPC) instrument also builts on our earlier work [30,31,32], in which we investigated the eight dimensions of PCC in hospital and long-term care settings, as well as adjusting them based on literature describing primary care for patients with multimorbidity (e.g. [22,23,24,25]) and consulting experts in the primary care setting when it comes to care for patients with multimorbidity (i.e., general practitioners, practice nurses, and patients with multimorbidity, who were consulted on item adjustment, removal, and addition). General practitioners (n = 4) and practice nurses (n = 3) known for delivering high levels of PCC in the area of Tilburg and patients dealing with multimorbidity (n = 3) for several years were selected as experts. First, they received the questionnaire via mail. All experts commented on the items via mail followed by a telephone meeting. Both authors discussed the comments and suggestions, which led to an adjusted version we send back to the experts. This was followed by another telephone meeting (with a selection of experts) and a personal meeting (with a patient expert) after which we reached agreement on a final set of 36 items, with responses structured by a five-point scale ranging from 1 (totally disagree) to 5 (totally agree).

Satisfaction with care

We used an adjusted version of the Satisfaction with inpatient Stroke Care (SASC) scale to assess satisfaction with care. Although the 8-item SASC was originally developed for use among stroke patients, it investigates experiences with care in general, not those related specifically to stroke care. Therefore, the SASC has been used widely in various patient populations to assess general satisfaction with care (e.g. [33,34,35,36]). The items were adjusted slightly for the primary care setting (e.g. ‘The doctors have done everything they can to make me well again’ was changed into ‘The staff has done everything they can to make me well again’), with removal of irrelevant or overlapping items (e.g. the hospitalization process went smoothly and I have been treated with kindness and respect by the staff at the hospital), resulting in a final set of 6 items: ‘I have received all the information I want about the causes and nature of my illness(es)’, ‘The staff has done everything they can to make me well again’, ‘I am satisfied with the type of treatment they have given me (e. g. physiotherapy, occupational therapy)’, ‘I have had enough therapy (e.g. physiotherapy, occupational therapy)’, ‘I am happy about the effect treatments had on my disease progression’, and ‘I am satisfied with the treatment provided by the general practitioner who I visit’. Responses are structured by a four-point scale ranging from 1 (strongly disagree) to 4 (strongly agree), with higher mean scores indicating greater satisfaction. In this study among patients with multimorbidity, the Cronbach’s alpha value for this adjusted 6-item instrument was 0.89, indicating good reliability.

Joint decision making and responsibility taking: Relational co-production of care

The 7-item relational co-production instrument was used to assess joint decision making and responsibility taking, as perceived by patients with multimorbidity [10, 37, 38]. Relational co-production refers to joint decision making and responsibility taking achieved through open communication, co-operation, and respect for each other, with negotiation of treatment options to accomplish mutually defined goals. Gittell (e.g. [39,40,41,42]) identified this concept as “relational coordination” when talking about the quality of relationships and communication among professionals and “relational coordination” if it concerns the quality of relationships and communication between patients and their health care professionals. High-quality relationships reinforce high-quality communication, encouraging professionals and patients with multimorbidity to listen to each other and to take account of the impacts of their actions on those engaged in different parts of the process, thereby helping them to react to new information in a co-ordinated way [43]. This questionnaire measures four aspects of communication (frequent, timely, accurate, and problem-solving) and three aspects of relationships (based on shared knowledge, goals, and mutual respect) between professionals and patients with multimorbidity. Responses are structured by a five-point Likert scale ranging from 1 (never) to 5 (always). This instrument has proven to be reliable and valid (based on structural and content validity, internal consistency and interrater agreement) in assessing the quality of communication and relationships [44, 45]. Higher mean scores indicate better realisation of joint decision making and responsibility taking, with scores ≥4 considered to represent success and scores < 4 considered to represent the lack of success perceived by patients with multimorbidity [46]. In this study, the Cronbach’s alpha value for this instrument was 0.87, indicating good reliability.

Analysis

To validate the 36-item PCPC instrument, we first used descriptive statistics to characterise the study population with regard to age, gender, marital status, educational level, and experiences with primary care delivery (the eight dimensions of PCC and satisfaction with care). Second, we calculated the mean, standard deviation, number of missing responses, and lambda value for each PCPC item. Third, we used LISREL to conduct confirmatory factor analyses and verify the factor structure of the instrument. Fourth, we assessed model fit using the following cut-off criteria of Hu and Bentler [47]:

  • standardised root mean square residual (SRMR) < 0.08,

  • root mean square error of approximation (RMSEA) < 0.06, and

  • comparative fit index (CFI) > 0.95.

Fifth, we used Cronbach’s alpha values to assess the internal consistency of the subscales and examined inter-correlations to verify conceptual relatedness among (sub)scales. Finally, we assessed the construct validity of the instrument overall and its eight dimensions by analysing associations with satisfaction with care. In addition, we examined whether scores for the eight dimensions of PCC were higher among patients who perceived the successful establishment of joint decision making and responsibility taking with their health care professionals than among those who perceived a lack of success.

Results

The mean age of the patients was 74.46 ± 10.64 (range 47–94) years (Table 2). Of the respondents, 40.9% were male, 43.2% were single, and 40% had lower educational levels.

Table 2 Characteristics of patients with multimorbidity in the study sample and their experiences with care
Full size table

PCPC item characteristics

Table 3 displays statistics for the 36 PCPC items. Item non-response rates ranged from 1 to 8%. Respondents gave considerable numbers of not-applicable responses in the family and friends dimension (about 100 per item), continuity and transition (n = 36–54), and coordination of care (item 14, n = 38; item 13, n = 24) dimensions. In addition, 61 respondents rated item 23 in the emotional support dimension as not applicable, and 19 and 58 respondents rated items 8 and 9, respectively, in the physical comfort dimension as not applicable.

Table 3 Characteristics of responses to the 36 patient-centred care items (n = 216)
Full size table

All items had loadings on the intended factors > 0.50.

Model fit

The model showed good fit, meeting cut-off criteria (CFI = 0.987, SRMR = 0.079, RMSEA = 0.0548).

Internal consistency and inter-correlations

Internal consistency values for the PCPC subscales ranged from 0.72 (physical comfort) to 0.92 (family and friends; Table 4). The internal consistency value for the overall instrument was 0.89. All (sub)scales were correlated significantly and positively (all p ≤ 0.001), indicating that they were conceptually related.

Table 4 Scale characteristics and (inter-)correlations of the 36-item patient-centred primary care instrument
Full size table

Construct validity

All eight dimensions of PCC were related positively to satisfaction with care (all p ≤ 0.001), indicating construct validity (Table 5). In addition, scores in all dimensions were higher among patients with multimorbidity who experienced joint decision making and responsibility taking (Table 6).

Table 5 Correlations of patient-centred care dimension scores with satisfaction with care
Full size table
Table 6 Relationships between joint decision making and responsibility taking (relational co-production of care) and patient-centred care
Full size table

Discussion

This study clearly showed that the 36-item PCPC instrument is valid and reliable for the assessment of PCC among patients with multimorbidity in the primary care setting. Given that multimorbidity is becoming the leading threat to population health and the greatest challenge for primary care systems worldwide, such an instrument can help to improve levels of patient centredness for this vulnerable population. Findings from several countries indicate that the prevalence of chronic diseases and multimorbidity is especially high in the primary care setting [8, 48,49,50,51]. Primary care providers are currently not equipped to deal with the complexities of ageing populations [51]. Health professionals clearly express the concern that they often missed the opportunity to engage chronically ill older patients as true partners in their care and really help them to manage their conditions at home. Identification of levels of patient centredness according to patients with multimorbidity provides insight in how well organizations are doing regarding the eight dimensions of PCC and helps identify the areas which need improvement (the dimensions with lower scores). Confirmatory factor analyses revealed good indices of fit for the instrument. As indicated by the high reliability coefficient, the scale showed good internal consistency. We found support for construct validity through significant positive correlations between PCPC scores and satisfaction with care. These findings are in line with earlier research showing positive associations between the eight dimensions of PCC and satisfaction with care [16]. This research also showed that patients with multimorbidity who perceived joint decision making and responsibility taking with their health care professionals also reported higher levels of all eight dimensions of PCC.

Several psychometric properties of the PCPC instrument could not be evaluated in this study and thus remain undefined. They include the instrument’s responsiveness, sensitivity to change, predictive value (e.g. clinical outcomes), relationship to other PCC instruments, and different modes of administration. Secondly, we included patients enrolled in at least two chronic care programmes (involving diagnosis of and treatment for combinations of diabetes, asthma and/or chronic obstructive pulmonary disease, cardiovascular diseases and conditions, and age-related frailty). Given that these patients were enrolled in at least 2 or more chronic care programmes we were able to identify and select them from the data registries of the health care practices. As a consequence patients who are dealing with a chronic illness other than diabetes, asthma and/or chronic obstructive pulmonary disease, cardiovascular diseases and conditions, and age-related frailty (which are the most prevalent chronic conditions) were not included. Further research is needed to assess the validity of this instrument among patients with (a combination of) other chronic illnesses as well as the general patient population in the primary care setting. Thirdly, some items had high numbers of ‘non-applicable’ responses. Although these aspects may not be applicable to all patients with multimorbidity in the primary care setting (e.g., emotional support and attention paid to fatigue and insomnia is only needed for those who struggle in these areas and transition of care is only relevant for those who are referred to another health care professional), if they are applicable they are crucial for their outcomes [22,23,24]. Fourthly, while after four iterative rounds we reached agreement on a final set of 36 items, we did not use a formal consensus method. Fifthly, while the original SASC to assess satisfaction with care has been validated among patients in the hospital we slightly adjusted the instrument to assess satisfaction with care among patients with multimorbidity in the primary care setting (e.g. replacing ‘doctor’ with ‘staff’). Although the Cronbach’s alpha (0.89) shows the instrument is reliable in this setting this adjusted 6-item SASC has not been formally validated yet. This may have limited testing concurrent construct validity of the PCC instrument. Finally, we tested the Dutch version of the 36-item PCPC instrument; we recommend testing of the English version in other countries to ensure international validity using adequate translation procedures such as forward-translations and back-translations recommended by the World Health Organisation [52].

Conclusion

We conclude that the psychometric properties of the 36-item PCPC instrument are good. Based on these results the PCPC instrument seems a promising tool for the assessment of PCC among patients with multimorbidity in the primary care setting.

Abbreviations

CFI:

Comparative fit index

PCC:

Patient-centred care

PCPC instrument:

Patient-centred primary care instrument

RMSEA:

Root mean square error of approximation

SASC:

Satisfaction with inpatient stroke care

SD:

Standard deviation

SRMR:

Standardised root mean square residual

References

  1. World Health Organization. People-centred and integrated health services: an overview of the evidence. Interim report. Geneva: World Health Organization; 2015.

    Google Scholar 

  2. Fortin M, Lapointe L, Hudon C, Vanasse A, Ntetu AL, Maltais D. Multimorbidity and quality of life in primary care: a systematic review. Health Qual Life Outcomes. 2004;2:51.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Vogeli C, Shields AE, Lee TA, Gibson TB, Marder WD, Weiss KB, et al. Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs. J Gen Intern Med. 2007;22(Suppl 3):391–5.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Menotti A, Mulder I, Nissinen A, Giampaoli S, Feskens EJ, Kromhout D. Prevalence of morbidity and multimorbidity in elderly male populations and their impact on 10-year all-cause mortality: the FINE study (Finland, Italy, Netherlands, elderly). J Clin Epidemiol. 2001;54:680–6.

    Article  PubMed  CAS  Google Scholar 

  5. van Oostrom SH, Picavet HS, van Gelder BM, Lemmens LC, Hoeymans N, van Dijk CE, et al. Multimorbidity and comorbidity in the Dutch population: data from general practices. BMC Public Health. 2012;12:715.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Glynn LG, Valderas JM, Healy P, Burke E, Newell J, Gillespie P, et al. The prevalence of multimorbidity in primary care and its effect on health care utilization and cost. Fam Pract. 2011;28:516–23.

    Article  PubMed  Google Scholar 

  7. Fortin M, Bravo G, Hudon C, Lapointe L, Almirall J, Dubois MF, et al. Relationship between multimorbidity and health-related quality of life of patients in primary care. Qual Life Res. 2006;15:83–91.

    Article  PubMed  Google Scholar 

  8. Osborn R, Moulds D, Squires D, Doty MM, Anderson C. International survey of older adults finds shortcomings in access, coordination, and patient-centered care. Health Aff. 2014;33(12):2247–55.

    Article  Google Scholar 

  9. Wagner EH, Bennett SM, Austin BT, Greene SM, Schaefer JK, Von Korff M. Finding common ground: patient-centeredness and evidence-based chronic illness care. J Altern Complement Med. 2005;11:S7–15.

    Article  PubMed  Google Scholar 

  10. Cramm JM, Nieboer AP. Longitudinal study to identify the influence of quality of chronic care delivery on productive interactions between patients and (teams of) healthcare professionals within disease management programs. BMJ Open. 2014;4:e005914.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Cramm JM, Nieboer AP. Is “disease management” the answer to our problems? No! Population health management and (disease) prevention require “management of overall well-being”. BMC Health Serv Res. 2016;16:500.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Cramm JM, Nieboer AP. Chronically ill patients’ self-management abilities to maintain overall well-being: what is needed to take the next step in the primary care setting? BMC Fam Pract. 2015;16:123.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cramm JM, Nieboer AP. Disease management: the need for a focus on broader self-management abilities and quality of life. Population Health Management. 2015;18(4):246–55.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Gerteis M, Edgman-Levitan S, Daley J, Delbanco TL. Through the patient’s eyes: understanding and promoting patient-centered care. San Francisco: Jossey-Bass; 1993.

    Google Scholar 

  15. Gerteis M, Edgman-Levitan S, Walker JD, Stokes DM, Cleary PD, Delbanco TL. What patients really want. Health Manage Q. 1993;15(3):2–6.

    PubMed  CAS  Google Scholar 

  16. Rathert C, Wyrwich M, Boren S. Patient-centered care and outcomes: a systematic review of the literature. Med Care Res Rev. 2013;70(4):351–79.

    Article  PubMed  Google Scholar 

  17. Bechtel C, Ness DL. If you build it, will they come? Designing truly patient-centered health care. Health Aff (Millwood). 2010;29(5):914–20.

    Article  Google Scholar 

  18. Berwick DM. (2009). What patient-centered should mean: confessions of an extremist. Health Aff. 2009;28:555–65.

    Article  Google Scholar 

  19. Greene SM, Tuzzio L, Cherkin D. A framework for making patient-centered care front and center. Perm J. 2012;16(3):49–53.

    PubMed  PubMed Central  Google Scholar 

  20. Kitson A, Marshall A, Bassett K, Zeitz K. What are the core elements of patient-centred care? A narrative review and synthesis of the literature from health policy, medicine and nursing. J Adv Nurs. 2013;69(1):4–15.

    Article  PubMed  Google Scholar 

  21. Mead N, Bower P. Patient-centredness: a conceptual framework and review of the empirical literature. Soc Sci Med. 2000;51(7):1087–110.

    Article  PubMed  CAS  Google Scholar 

  22. Duguay C, Gallagher F, Fortin M. The experience of adults with multimorbidity: a qualitative study. J Comorbidity. 2014;4:11–21.

    Article  Google Scholar 

  23. Sturmberg JP, Botelho RJ, Kissling B. Integrated multimorbidity management in primary care: why, what, how, and how to? Journal of Comorbidity. 2016;6(2):114–9.

    Article  PubMed  PubMed Central  Google Scholar 

  24. AGS (American Geriatrics Society) Expert Panel on the Care of Older Adults with Multimorbidity. Patient-centered Care for Older Adults with multiple chronic conditions: a stepwise approach from the American Geriatrics Society. J Am Geriatr Soc. 2012;60(10):1957–68.

    Article  Google Scholar 

  25. Kim DH, Rich MW. Patient-centred care of older adults with cardiovascular disease and multiple chronic conditions. Can J Cardiol. 2016;30:1097–107.

    Article  Google Scholar 

  26. Delaney LJ. Patient-centred care as an approach to improving health care in Australia. Collegian. 2018;25(1):119–23.

    Article  Google Scholar 

  27. Ekman I, Wolf A, Olsson L, Taft C, Dudas K, Schaufelberger M, Swedberg K. Effects of person-centred care in patients with chronic heart failure: the PCC-HF study. Eur Heart J. 2012;33:1112–9.

    Article  PubMed  Google Scholar 

  28. Kinmonth AL, Woodcock A, Griffin S, Spiegal N, Campbell MJ. Randomised controlled trial of patient centred care of diabetes in general practice: impact on current wellbeing and future disease risk. The diabetes care from diagnosis research team. BMJ. 1998;317:1202–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Wolf D, Lehman L, Quinlin R, Rosenzweig M, Friede S, Zullo T, Hoffman L. Can nurses impact patient outcomes using a patient-centered care model? J Nurs Adm. 2008;38(12):532–40.

    Article  PubMed  Google Scholar 

  30. Cramm JM, Leensvaart L, Berghout MA, van Exel J. Exploring views on what is important for patient-centred care in end-stage renal disease using Q methodology. BMC Nephrol. 2015;16:74.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Berghout MA, Leensvaart L, van Exel J, Cramm JM. (2015). Healthcare professionals’ views on patient-centered care in hospitals. BMC Health Serv Res. 2015;15:385.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Cramm JM, Nieboer AP. Validation of an instrument to assess the delivery of patient-centred care to people with intellectual disabilities as perceived by professionals. BMC Health Serv Res. 2017;17:472.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Baumann C, Rat AC, Mainard D, Cuny C, Guillemin F. Importance of patient satisfaction with care in predicting osteoarthritis-specific health-related quality of life one year after total joint arthroplasty. Qual Life Res. 2011;20(10):1581–8.

    Article  PubMed  Google Scholar 

  34. Brédart A, Robertson C, Razavi D, Batel-Copel L, Larsson G, Lichosik D, et al. Patients’ satisfaction ratings and their desire for care improvement across oncology settings from France, Italy, Poland and Sweden. Psychooncology. 2003;12(1):68–77.

    Article  PubMed  Google Scholar 

  35. Pöder U, Von Essen L. Perceptions of support among Swedish parents of children on cancer treatment: a prospective, longitudinal study. Eur J Cancer Care (Engl). 2009;18(4):350–7.

    Article  Google Scholar 

  36. Von Essen L, Larsson G, Oberg K, Sjödén PO. ‘Satisfaction with care’: associations with health-related quality of life and psychosocial function among Swedish patients with endocrine gastrointestinal tumours. Eur J Cancer Care (Engl). 2002;11(2):91–9.

    Article  CAS  Google Scholar 

  37. Gittell JH, Douglass A. Relational bureaucracy: structuring reciprocal relationships into roles. Acad Manag Rev. 2012;37:709–33.

    Article  Google Scholar 

  38. Van der Meer L, Nieboer AP, Finkenflügel HJM, Cramm JM. The importance of person-centred care and co-creation of care for the well-being and job satisfaction of professionals working with people with intellectual disabilities. Scandinavian J of Caring Sci. 2017; https://doi.org/10.1111/scs.12431.

  39. Gittell JH. Organizing work to support relational coordination. Internat J Human Resource Management. 2000;11:517–39.

    Article  Google Scholar 

  40. Gittell JH. Coordinating mechanisms in care provider groups: relational coordination as a mediator and input uncertainty as a moderator of performance effects. Management Sci. 2002;48(11):1408–26.

    Article  Google Scholar 

  41. Gittell JH, Fairfield K, Bierbaum B, Jackson R, Kelly M, Laskin R, Lipson S, Siliski J, Thornhill T, Zuckerman J. Impact of relational coordination on quality of care, postoperative pain and functioning, and length of stay: a nine-hospital study of surgical patients. Med Care. 2000;38(8):807–19.

    Article  PubMed  CAS  Google Scholar 

  42. Weinberg DB, Gittell JH, Lusenhop RW, Kautz CM, Wright J. Beyond our walls: impact of patient and provider coordination across the continuum on outcomes for surgical patients. Health Serv Res. 2007;42(1):7–24.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Gittell JH. Relationships between service providers and their impact on customers. J Serv Res. 2002;4:299–311.

    Article  Google Scholar 

  44. Gittell JH, Seidner R, Wimbush J. A relational model of how high-performance work systems work. OrganizationScience. 2010;21(2):490–506.

    Google Scholar 

  45. Valentine MA, Nembhard IG, Edmondson AC. Measuring teamwork in health care settings. A review of survey instruments. Med Care. 2015;53(4):e16–30.

  46. Relational Coordination Analytics Inc. Overview and analysis: relational coordination data (memo). Cambridge: Relational Coordination Analytics Inc; 2016.

  47. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Modeling. 1999;6:1–55.

    Article  Google Scholar 

  48. Fortin M, Stewart M, Poitras ME, Almirall J, Maddocks H. A systematic review of prevalence studies on multimorbidity: toward a more uniform methodology. Ann Fam Med. 2012;10:142–51.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Schneider KM, O’Donnell BE, Dean D. Prevalence of multiple chronic conditions in the United States’ Medicare population. Health Qual Life Outcomes. 2009;7:82.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380:37–43.

    Article  PubMed  Google Scholar 

  51. Korownyk C, et al. Competing demands and opportunities in primary care. Can Fam Physician. 2017;63(9):664–8.

    PubMed  PubMed Central  Google Scholar 

  52. WHO: Process of translation and adaptation of instruments http://www.who.int/substance_abuse/research_tools/translation/en/. Accessed 27 May 2018.

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Acknowledgements

The authors thank all patients for taking the time to fill in the questionnaires.

Funding

We received funding from CZ and VGZ (Dutch health care insurance companies). They provided funding for this study only, the results are based on the findings of the research only.

Availability of data and materials

The data and surveys used are available upon request.

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Authors and Affiliations

  1. Erasmus School of Health Policy & Management, Erasmus University, Rotterdam, The Netherlands

    Jane Murray Cramm & Anna Petra Nieboer

Authors
  1. Jane Murray Cramm
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  2. Anna Petra Nieboer
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Contributions

JC and AN drafted the design for data collection. JC was involved in subject recruitment and data collection, AN performed the statistical analysis, and JC and AN interpreted the data. JC and AN drafted the manuscript and contributed equally to its refinement. Both authors have read and approved the final version.

Corresponding author

Correspondence to Jane Murray Cramm.

Ethics declarations

Ethics approval and consent to participate

The medical ethics committee of Erasmus Medical Centre, Rotterdam, the Netherlands determined that the rules stipulated in the Medical Research Involving Human Subjects Act did not apply to this study (protocol no. MEC-2018-021). Written informed consent to participate in the study was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interest.

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Cramm, J.M., Nieboer, A.P. Validation of an instrument for the assessment of patient-centred care among patients with multimorbidity in the primary care setting: the 36-item patient-centred primary care instrument. BMC Fam Pract 19, 143 (2018). https://doi.org/10.1186/s12875-018-0832-4

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  • DOI: https://doi.org/10.1186/s12875-018-0832-4

Keywords

BMC Primary Care

ISSN: 2731-4553

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