The objective of this review is to evaluate and compare the measurement properties of instruments that measure collaboration within healthcare settings, specifically those which have been psychometrically tested and validated.
More specifically, the objectives are to:
- Identify studies reporting the measurement properties of instruments that measure collaboration within healthcare settings that are populated with a complex mix of participant types
- Identify the measurement properties assessed by each study
- Evaluate the reports on methodological quality and rate them
- Compare instruments by synthesizing the results of the evaluation.
It has been stated that the idea of teamwork and collaboration in the healthcare setting (HCS) is intuitively appealing.1 However, research and general experience indicate that the achievement of teamwork and collaboration is modest in the majority of HCSs2 with the perception and experience of collaboration often varying between professionals working in the same setting.3
The term team is difficult to define as a universal entity. In the literature several terms are used to label types of teams within HCS such as multidisciplinary, interdisciplinary and inter-professional.4 These terms commonly target the health professional groups within the HCS and are not inclusive of the patients themselves, their friends and family or other types of non-professional groups involved in the care of the patient. For this reason we will focus on the participants within HCSs and not exclusively on inter-professional teams. Any real HCS is likely to be populated with various types of participants including orderlies, receptionists, chaplains, clerical staff, administrators and volunteers who may all contribute to a patient's care. The impetus to consider others in the HCS such as the patients and their families redefines the boundaries of the inter-professional team.
Concepts like shared decision making,5 involving patients in safe care approaches to inter-professional practice,6 patient and family involvement in quality improvement processes,7 and the World Health Organization's8 call for patient and family inclusion in collaborative healthcare all reflect a growing awareness of the need to understand and collaborate with others within the HCS. Therefore, collaboration in the HCS is best considered to be broader than the “professional” groups (i.e. nurses, physicians and pharmacists, etc.).
A review of the existing research and discourse on collaborative teamwork in healthcare suggests that the presence of collaboration can result in improving patient outcomes and enhancing team members' overall levels of satisfaction.9,10 For example, patient safety in relation to drug prescription improves when nurses and pharmacists collaborate.11 Routinely, different professional groups work in teams, for example, in surgery where the surgeons, anesthetist and nurses, etc. work as a team to achieve specific goals. However, can this teamwork be considered collaborative?
The term/concept “collaboration” is often used in literature and adopts various meanings depending on the author's viewpoint and the context or environment in which the team operates. Barbara Gray12 defined collaboration as the process of joint decision making by interdependent stakeholders involved in solving a specific problem. Gray suggested that collaborative decision making involves stakeholders resolving differences, joint ownership of the decisions reached and collective responsibility. In an editorial published in 2000 titled, “What's so great about collaboration? We need more evidence and less rhetoric”, Zwarenstein and Reeves13 highlighted the need for more research to justify the application of collaboration in inter-professional healthcare practice. The interest of this current review is the tools used to measure collaboration.
A current search of literature indicates a significant research effort into the outcomes of collaborative healthcare. A deficiency in the collaborative care research is to associate positive patient outcomes as a result of collaborative care.14–19 However, without an empirical measurement the observed outcome may be due to a multiplicity of variables. In a Cochrane systematic review, Zwarenstein, Goldman and Reeves9 identified five randomized controlled trials of Inter-Professional Collaboration (IPC) interventions and concluded IPC was effective in improving healthcare outcomes. Only one study cited in the review attempted to evaluate team collaboration by comparing the measured outcomes of videoconferencing and audio-conferencing.20 The review authors stated “… we know little about the processes of collaboration and how it contributes to changes in healthcare processes and patient outcomes”.9(p. 8) The authors suggested that there was a need for “…future research… [to] …focus on the conceptualizations and [validation of] measurement [criteria] of collaboration”.9(p. 9)
A number of theoretical models of collaboration have evolved within the broader framework of human behavior that assist in understanding the group behavior of collaboration.21 Relevant to the healthcare and social care settings are three theoretical models that attempt to define and conceptualize collaboration: Sullivan,22 DÁmour21 and Bronstein.23 Theorization and conceptualization assists in the identification of the key determinants of successful collaboration24 and in turn, the measurement of collaboration.
According to Orchard et al.,25 Sullivan's model is based on the “…critical attributes of collaboration…” coordination (includes achieving mutual goals by working together), cooperation (contribution of views and valuing those of other team members), shared decision making (planning care in consultation with all, including the patient and their families) and partnership (creating effective working relationships).
DÁmour's model21 is based on the outcome of a synthesis of 17 papers regarding collaboration. The attributes of collaboration identified in this model include sharing (responsibility, decision making, healthcare philosophy, values, data, planning and interventions), partnership (collegial relationship that involves open communication, mutual respect and trust; valuing the contribution of others and common goals), interdependency (mutual dependence = the whole is greater than the sum of its parts) and power (symmetry in power relationships).
Bronstein's model23 includes the collaborative attributes of interdependence, newly created professional activities (new activity and services not achieved without collaboration), flexibility (the deliberate occurrence of role blurring), collective ownership of goals (shared responsibility in the process of reaching goals) and reflection on process (attention to the process of working together).
In addition to models and attributes of collaboration, the factors that promote or impede collaboration need to be considered when attempting to measure collaboration. A 2005 review of literature resulted in the identification of three determinants of successful collaboration: systematic determinants, organizational determinants and interactional determinants.24 Each of these determinants is dependent on a multiplicity of factors. For example, the systematic determinant is influenced by social, cultural, professional and education systems. The organizational determinant is impacted by an organization's structure, philosophy, administration, resources and coordination mechanisms, and the interactional determinant is influenced by peoples' willingness to collaborate, trust, communicate and mutual respect.24
Research into healthcare team collaboration has relied upon the adaptation of existing instruments to measure collaboration. These instruments are not specific to inter-professional teams and few have been validated psychometrically. Orchard et al. suggested that instruments which allow “…teams to assess collaborative relationships are needed”.25(p. 59) Thannhauser, Russell-Mayhew and Scott26 evaluated 23 instruments measuring inter-professional education and collaboration. This evaluation included development of psychometric properties, validity and reliability data, general utility of the measure, sample description and questionnaire design, which are also important criteria for this review.
Instruments such as the Index of Interdisciplinary Collaboration(IIC)23 and its modified formats (Modified Index of Interdisciplinary Collaboration-MIIC) have demonstrated a capacity to measure and differentiate variances in the perception of collaboration within a hospice setting27–30 and to measure collaboration in expanded school mental health programs.31 Other instruments such as the Inter-professional Socialization and Valuing Scale32 the Assessment of Inter-professional Team Collaboration Scale (AITCS),25 the Care Process Self-Evaluation Tool (CPSET),33 the Doctor's Opinion on Collaboration (DOC)34 and others also exist; however no systematic reviews have been conducted to evaluate these tools.
For the purpose of improving patient safety, improved collaboration between people within any HCS needs to be facilitated. For example, Dougherty and Larsen35 reviewed measurement instruments for nurse-physician collaboration and recommended collaboration as a key communication strategy to minimize errors and increase patient safety. Healthcare policy makers and administrators are increasingly promoting collaborative teamwork as a key foundation of effective and efficient healthcare. Given the acclaimed role that collaboration plays in improving patient safety and health outcomes, it is important to determine effective ways to measure collaboration in the HCS. Research outcomes are invalid if there is an assumption that collaboration has occurred without an associated measurement using a validated instrument. The purpose of this review is to identify which of the available instruments are valid and reliable measurements of collaboration in the HCS populated by a complex mix of participant types.
Types of participants
Participants may be any healthcare professionals, the patient or any other non-professional who contributes to a patient's care. The term participant type means the designation of any one participant, for example, “nurse”, “social worker” or “administrator”. More than two participant types is mandatory. Diversity of participant types includes the diversity observed between medical doctors, for example, oncologist, radiologist or general practitioner.
Focus of this review
The focus of this review will be the validity and reliability of instruments used to measure collaboration within healthcare settings.
Types of outcomes
The outcome of interest is validation and interpretability of the instrument being assessed that includes content validity (including face validity), construct validity (structural, criterion/concurrent, hypothesis testing) and reliability (internal consistency, test-retest). Interpretability is characterized by statistics such as mean and standard deviation which can be translated to a qualitative meaning.
Types of studies
The types of studies considered for inclusion will be validation studies, but quantitative study designs such as randomized controlled trials, controlled trials and case studies are also eligible for inclusion. Studies that are Interprofessional Education (IPE) focused, published as an abstract only, patient self-reporting only or not about care delivery are also excluded.
The search strategy aims to find both published and unpublished studies. A three-step search strategy will be utilized in this review. An initial limited search of MEDLINE and CINAHL will be undertaken followed by an analysis of the text words contained in the title and abstract, and of the index terms used to describe the article. A second search using all identified keywords and index terms will then be undertaken across all included databases. Thirdly, the reference list of all identified reports and articles will be searched for additional studies. Studies published in English will be considered for inclusion in this review. Studies published anytime in the past will be considered for inclusion in this review.
The databases to be searched include:
Cochrane Central Register of Controlled Trials
MD Consult Australia
Psychology and Behavioural Sciences Collection
Informit Health Databases
Web of Science
The search for unpublished studies will include:
EThOS (Electronic Thesis Online Service), Index to Theses, and ProQuest Dissertations and Theses
Initial keywords to be used will be:
collaborat*; collaboration, collaborate, collaborative
multidisciplinary OR transdisciplinary OR interdisciplinary OR multiprofessional OR inter-professional
health*; health, healthcare
measure*; measure, measured, measurement
sensitiv*; sensitive, sensitivity
valid*; valid, validity, validation
reliab*; reliable, reliability
Assessment of methodological quality
Studies retrieved that meet the inclusion criteria will be assessed for methodological quality by two independent appraisers using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) Checklist (www.cosmin.nl) (Appendix I) prior to inclusion in the review. Any disagreements that arise between the appraisers will be resolved through discussion, or with a third reviewer. Currently there is no Joanna Briggs Institute (JBI) appraisal tool that focuses on measurement properties of instruments.
Data will be extracted from papers included in the review using the COSMIN data extraction tool (Appendix I). The reviewers intend to create an Excel spreadsheet of the COSMIN checklist with a four point rating scale, which will be used to record appraisal results and sample characteristics for each measurement property. The data extracted will include specific details about the study quality relating to validity, reliability, interpretability statistics, the sample characteristics (generalizability), study methods and objectives, and outcomes of significance to the review question and objectives.
Effect sizes associated with internal consistency and inter-rater reliability (such as Cronbach's alpha, Cohen's kappa inter-rater scores and/or Kendall's tau) will be reported. If statistical pooling is not possible, the findings will be presented in narrative form including tables and figures to aid in data presentation where appropriate.
Conflicts of interest
There are no conflicts of interest.
2. Sicotte C, D'Amour D, Moreault M-P. Interdisciplinary collaboration within Quebec community health care centres. Soc Sci Med. 2002;55(6):991-1003.
3. Nathanson BH, Henneman EA, Blonaisz ER, Doubleday ND, Lusardi P, Jodka PG. How much teamwork exists between nurses and junior doctors in the intensive care unit? J Adv Nurs. 2011;67(8):1817-23.
4. Chamberlain-Salaun J, Mills J, Usher K. Terminology used to describe health care teams: an integrative review of the literature. J Multidiscip Healthc. 2013;6:65-74.
5. Kon AA. The shared decision-making continuum. JAMA. 2010;304(8):903-4.
6. Howe A. Can the patient be on our team? An operational approach to patient involvement in interprofessional approaches to safe care. J Interprof Care. 2006;20(5):527-34.
7. Robertson S, Pryde K, Evans K. Patient involvement in quality improvement: is it time we let children, young people and families take the lead? Arch Dis Child Educ Pract Ed. 2014 Feb;99(1):23-7.
8. World Health Organisation. Framework for action on interprofessional education and collaborative practice: World Health Organisation; 2010. Report No.: WHO/HRH/HPN/10.3.
9. Zwarenstein M, Goldman J, Reeves S. Interprofessional collaboration: effects of practice-based interventions on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2009;3(CD000072):1-31.
10. Chung B, Dopheide JA, Gregerson P. Psychiatric pharmacist and primary care collaboration at a skid-row safety-net clinic. J Natl Med Assoc. 2011 Jul;103(7):567-74.
11. Feldman LS, Costa LL, Feroli ER, Jr., Nelson T, Poe SS, Frick KD, et al. Nurse-pharmacist collaboration on medication reconciliation prevents potential harm. J Hosp Med. 2012 May-Jun;7(5):396-401.
12. Gray B. Collaborating; finding common ground for multiparty problems. San Francisco: Jossey-Bass; 1989.
13. Zwarenstein M, Reeves S. What's so great about collaboration?: we need more evidence and less rhetoric. BMJ. 2000;320(7241):1022.
14. Vera M, Perez-Pedrogo C, Huertas SE, Reyes-Rabanillo ML, Juarbe D, Huertas A, et al. Collaborative care for depressed patients with chronic medical conditions: a randomized trial in Puerto Rico. Psychiatr Serv. 2010 Feb;61(2):144-50.
15. Van Leeuwen Williams E, Unutzer J, Lee S, Noel PH. Collaborative depression care for the old-old: findings from the IMPACT trial. Am J Geriatr Psychiatry. 2009 Dec;17(12):1040-9.
16. van der Voort TY, van Meijel B, Goossens PJ, Renes J, Beekman AT, Kupka RW. Collaborative care for patients with bipolar disorder: a randomised controlled trial. BMC Psychiatry. 2011;11:133.
17. Rollman BL, Belnap BH. The Bypassing the Blues trial: collaborative care for post-CABG depression and implications for future research. Cleve Clin J Med. 2011 Aug;78 Suppl 1:S4-12.
18. Muntingh AD, van der Feltz-Cornelis CM, van Marwijk HW, Spinhoven P, Assendelft WJ, de Waal MW, et al. Collaborative stepped care for anxiety disorders in primary care: aims and design of a randomized controlled trial. BMC Health Serv Res. 2009;9:159.
19. Johnson JA, Al Sayah F, Wozniak L, Rees S, Soprovich A, Chik CL, et al. Controlled trial of a collaborative primary care team model for patients with diabetes and depression: rationale and design for a comprehensive evaluation. BMC Health Serv Res. 2012;12:258.
20. Wilson SF, Marks R, Collins N, Warner B, Frick L. Benefits of multidisciplinary case conferencing using audiovisual compared with telephone communication: a randomized controlled trial. J Telemed Telecare. 2004;10(6):351-4.
21. D'Amour D, Ferrada-Videla M, San Martin Rodriguez L, Beaulieu M. The conceptual basis for interprofessional collaboration: core concepts and theoretical frameworks. J Interprof Care. 2005;19(S1):116-31.
22. Sullivan TJ. Collaboration: A Health Care Imperative. New York, NY: McGraw-Hill; 1998.
23. Bronstein LR. Instrument development. Index of interdisciplinary collaboration. Soc Work Res. 2002;26(2):113-22.
24. San Martín-Rodríguez L, Beaulieu M, D'Amour D, Ferrada-Videla M. The determinants of successful collaboration: a review of theoretical and empirical studies. J Interprof Care. 2005;19:132-47.
25. Orchard CA, King GA, Khalili H, Bezzina MB. Assessment of Interprofessional Team Collaboration Scale (AITCS): development and testing of the instrument. J Contin Educ Health Prof. 2012 Winter;32(1):58-67.
26. Thannhauser J, Russell-Mayhew S, Scott C. Measures of interprofessional education and collaboration. J Interprof Care. 2010;24(4):336-49.
27. Wittenberg-Lyles EM, Parker Oliver D. The power of interdisciplinary collaboration in hospice. Prog Palliat Care. 2007;15(1):6-12.
28. Wittenberg-Lyles E, Parker Oliver D, Demiris G, Regehr K. Interdisciplinary collaboration in hospice team meetings. J Interprof Care. 2010;24(3):264-73.
29. Oliver DP, Wittenberg-Lyles EM, Day M. Measuring interdisciplinary perceptions of collaboration on hospice teams. Am J Hosp Palliat Care. [Empirical Study; Quantitative Study]. 2007 Feb-Mar;24(1):49-53.
30. Oliver DP, Wittenberg-Lyles EM, Day M. Variances in perceptions of interdisciplinary collaboration by hospice staff. J Palliat Care. 2006 Winter;22(4):275-80.
31. Mellin EA, Bronstein L, Anderson-Butcher D, Amorose AJ, Ball A, Green J. Measuring interprofessional team collaboration in expanded school mental health: Model refinement and scale development. J Interprof Care. 2010 Sep;24(5):514-23.
32. King G, Shaw L, Orchard CA, Miller S. The interprofessional socialization and valuing scale: a tool for evaluating the shift toward collaborative care approaches in health care settings. Work. 2010;35(1):77-85.
33. Seys D, Deneckere S, Sermeus W, Van Gerven E, Panella M, Bruyneel L, et al. The Care Process Self-Evaluation Tool: a valid and reliable instrument for measuring care process organization of health care teams. BMC Health Serv Res. 2013;13:325.
34. Berendsen AJ, Benneker WH, Groenier KH, Schuling J, Grol RP, Meyboom-de Jong B. DOC questionnaire: measuring how GPs and medical specialists rate collaboration. Int J Health Care Qual Assur. 2010;23(5):516-26.
35. Dougherty M, Larson E. A review of instruments measuring nurse-physician collaboration. J Nurs Adm. 2005;35(5):244-53.
Appendix I: Appraisal instruments and data extraction tools
The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments
The COSMIN checklist (COnsensus-based Standards for the selection of health status Measurement INstruments) is provided below in its published format (www.cosmin.nl). For the purpose of this review the COSMIN checklist with the four-point scale will be used to assess the methodological quality of the studies. The COSMIN checklist will be used as prescribed (see COSMIN Checklist Manual; www.cosmin.nl), with the option of minor modifications in the process as required by the types of studies retrieved for review.
The COSMIN checklist was developed for evaluating measurement instruments of health related patient reported outcomes (HR-PROs). The use of the COSMIN checklist in this review is valid because the criteria for what constitutes good measurement properties for HR-PROs are equivalent for collaboration measurement instruments.