Assessment of variation in the Alberta Context Tool: the contribution of unit level contextual factors and specialty in Canadian pediatric acute care settings

Carole A Estabrooks, Janet E Squires, Alison M Hutchinson, Shannon Scott, Greta G Cummings, Sung Hyun Kang, William K Midodzi, Bonnie Stevens, Carole A Estabrooks, Janet E Squires, Alison M Hutchinson, Shannon Scott, Greta G Cummings, Sung Hyun Kang, William K Midodzi, Bonnie Stevens

Abstract

Background: There are few validated measures of organizational context and none that we located are parsimonious and address modifiable characteristics of context. The Alberta Context Tool (ACT) was developed to meet this need. The instrument assesses 8 dimensions of context, which comprise 10 concepts. The purpose of this paper is to report evidence to further the validity argument for ACT. The specific objectives of this paper are to: (1) examine the extent to which the 10 ACT concepts discriminate between patient care units and (2) identify variables that significantly contribute to between-unit variation for each of the 10 concepts.

Methods: 859 professional nurses (844 valid responses) working in medical, surgical and critical care units of 8 Canadian pediatric hospitals completed the ACT. A random intercept, fixed effects hierarchical linear modeling (HLM) strategy was used to quantify and explain variance in the 10 ACT concepts to establish the ACT's ability to discriminate between units. We ran 40 models (a series of 4 models for each of the 10 concepts) in which we systematically assessed the unique contribution (i.e., error variance reduction) of different variables to between-unit variation. First, we constructed a null model in which we quantified the variance overall, in each of the concepts. Then we controlled for the contribution of individual level variables (Model 1). In Model 2, we assessed the contribution of practice specialty (medical, surgical, critical care) to variation since it was central to construction of the sampling frame for the study. Finally, we assessed the contribution of additional unit level variables (Model 3).

Results: The null model (unadjusted baseline HLM model) established that there was significant variation between units in each of the 10 ACT concepts (i.e., discrimination between units). When we controlled for individual characteristics, significant variation in the 10 concepts remained. Assessment of the contribution of specialty to between-unit variation enabled us to explain more variance (1.19% to 16.73%) in 6 of the 10 ACT concepts. Finally, when we assessed the unique contribution of the unit level variables available to us, we were able to explain additional variance (15.91% to 73.25%) in 7 of the 10 ACT concepts.

Conclusion: The findings reported here represent the third published argument for validity of the ACT and adds to the evidence supporting its use to discriminate patient care units by all 10 contextual factors. We found evidence of relationships between a variety of individual and unit-level variables that explained much of this between-unit variation for each of the 10 ACT concepts. Future research will include examination of the relationships between the ACT's contextual factors and research utilization by nurses and ultimately the relationships between context, research utilization, and outcomes for patients.

Figures

Figure 1
Figure 1
Caterpillar Plot for each ACT Variable (Model 1, N = 32 Units).

References

    1. Dopson S, Fitzgerald L, (eds.) Knowledge to Action: Evidence-Based Health Care in Context. Oxford: Oxford University Press; 2005.
    1. Scott-Findlay S, Golden-Biddle K. Understanding how organizational culture shapes research use. J Nurs Adm. 2005;35(7-8):359–365.
    1. Stetler C. Role of the organization in translating research into evidence-based practice. Outcome Manag. 2003;7(3):97–105.
    1. Estabrooks CA, Scott S, Squires JE, Stevens B, O'Brien-Pallas L, Watt-Watson J, Profetto-McGrath J, McGilton K, Golden-Biddle K, Lander J. et al.Patterns of research utilization on patient care units. Implement Sci. 2008;3:31. doi: 10.1186/1748-5908-3-31.
    1. Scott SD, Estabrooks CA, Allen M, Pollock C. A context of uncertainty: how context shapes nurses' research utilization behaviors. Qual Health Res. 2008;18(3):347–357. doi: 10.1177/1049732307313354.
    1. Titler M. Translation science and context. Research and Theory for Nursing Practice: An International Journal. 2010;24(1):35–55. doi: 10.1891/1541-6577.24.1.35.
    1. Woods N, Magyary D. Translational research: Why nursing's interdisciplinary collaboration is essential. Research and Theory for Nursing Practice: An International Journal. 2010;24(1):9–24. doi: 10.1891/1541-6577.24.1.9.
    1. Redfern S, Christian S. Achieving change in health care practice. J Eval Clin Pract. 2003;9(2):225–238. doi: 10.1046/j.1365-2753.2003.00373.x.
    1. Titler MG. Methods in translation science. Worldviews Evid Based Nurs. 2004;Q1:38–48.
    1. McCormack B, McCarthy G, Wright J, Coffey A. Development and testing of the Context Assessment Index (CAI) Worldviews Evid Based Nurs. 2009;6(1):27–35. doi: 10.1111/j.1741-6787.2008.00130.x.
    1. Wallin L. Knowledge translation and implementation research in nursing. Int J Nurs Stud. 2009;46:576–587. doi: 10.1016/j.ijnurstu.2008.05.006.
    1. Kitson A, Harvey G, McCormack B. Enabling the implementation of evidence based practice: A conceptual framework. Qual Health Care. 1998;7(3):149–158. doi: 10.1136/qshc.7.3.149.
    1. Grol R, Berwick D, Wensing M. On the trail of quality and safety in health care. BMJ. 2008;336(7635):74–76. doi: 10.1136/.
    1. Grol R, Grimshaw J. From best evidence to best practice: Effective implementation of change in patients' care. Lancet. 2003;362(9391):1225–1230. doi: 10.1016/S0140-6736(03)14546-1.
    1. Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovation in service organizations: Systematic review and recommendations. Milbank Q. 2004;82(4):581–629. doi: 10.1111/j.0887-378X.2004.00325.x.
    1. Fleuren M, Wiefferink K, Paulussen T. Determinants of innovation within health care organizations: Literature review and Delphi study. Int J Qual Health Care. 2004;16(2):107–123. doi: 10.1093/intqhc/mzh030.
    1. McCormack B, Kitson A, Harvey G, Rycroft-Malone J, Titchen A, Seers K. Getting evidence into practice: The meaning of 'context'. J Adv Nurs. 2002;38(1):94–104. doi: 10.1046/j.1365-2648.2002.02150.x.
    1. Estabrooks C, Squires J, Cummings G, Birdsell J, Norton P. Development and assessment of the Alberta Context Tool. BMC HSR. 2009;9:234.
    1. Estabrooks C, Squires J, Hayduk L, Cummings G, Norton P. Advancing the argument for validity of the Alberta Context Tool with healthcare aides in residential long-term care. BMC MRM. 2011;11:107.
    1. American Educational Research Association; American Psychological Association; National Council on Measurement in Education. Standards for Educational and Psychological Testing. Washington, D.C.: American Educational Research Association; 1999.
    1. Nelson E, Batalden P, Huber T, Mohr J, Godfrey M, Headrick L, Wasson J. Microsystems in health care: Part 1. Learning from high performing front-line clinical units. J Qual Improv. 2002;28:472–493.
    1. Disch J. Clinical Microsystems: The building blocks of patient safety. Creative Nursing. 2006;3:13–14.
    1. Godfrey M, Nelson E, Wasson J, Mohr J, Batalden P. Microsystems in healthcare: Part 3. Planning patient-centered services. Joint Commission Journal on Quality and Safety. 2003;29(4):159–170.
    1. Goldschmidt K, Gordin P. A model of nursing care Microsystems for a large neonatal intensive care unit. Advances in Neonatal Care. 2006;6(2):81–87. doi: 10.1016/j.adnc.2006.01.003.
    1. Wasson J, Godfrey M, Nelson E, Mohr J, Batalden P. Microsystems in healthcare: Part 4. Planning patient centered care. Joint Commission Journal on Quality and Safety. 2003;29(5):227–237.
    1. Sales A, Sharp N, Li Y-F, Lowy E, Greiner G, Liu C-F, Alt-White A, Rick C, Sochalski J, Mitchell P. et al.The association between nursing factors and patient mortality in the Veterans Health Administration: The view from the nursing unit level. Medical Care. 2008;46(9):938–945. doi: 10.1097/MLR.0b013e3181791a0a.
    1. Nelson E, Godfrey M, Batalden P, Berry S, Bothe A, McKinley K, Melin C, Meuthing S, Moore G, Wasson J. et al.Clinical Microsystems, Part 1. The building blocks of health systems. The Joint Commission Journal on Quality and Patient Safety. 2008;34(7):367–378.
    1. Glick WH. Conceptualizing and measuring organizational and psychological climate: Pitfalls in multilevel research. Academy of Management Review. 1985;10(3):601–616.
    1. James LR. Aggregation bias in estimates of perceptual agreement. J Appl Psychol. 1982;67(2):219–229.
    1. Bliese PD. In: Multilevel Theory, Research and Methods in Organizations: Foundations, Extensions and New Directions. Klein KJ, Kozlowski SWJ, editor. San Francisco: Jossey-Bass; 2000. Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis; pp. 349–381.
    1. Vogus TJ, Sutcliffe KM. The Safety Organizing Scale: Development and validation of a behavioral measure of safety culture in hospital nursing units. Med Care. 2007;45(1):46–54. doi: 10.1097/01.mlr.0000244635.61178.7a.
    1. Rosenthal R, Rosnow RL. Essentials of Behavioural Research: Methods and Data Analysis. 2. New York: McGraw Hill; 1991.
    1. Keppel G. Design and Analysis: A Researcher's Handbook. Englewood Cliffs, New Jersey: Prentice-Hall; 1991.
    1. Estabrooks CA, Midodzi WK, Cummings GG, Ricker KL, Giovannetti P. The impact of hospital nursing characteristics on 30-day mortality. Nurs Res. 2005;54(2):74–84.
    1. Estabrooks CA, Midodzi WK, Cummings GG, Wallin L. Predicting research use in nursing organizations: a multilevel analysis. Nurs Res. 2007;56(4 Suppl):S7–S23.
    1. Bartko J. On various intraclass correlation reliability coefficients. Psychol Bull. 1976;83:762–765.
    1. McGraw K, Wong S. Forming inferences about some intraclass correlation coefficients. Psychological Methods. 1996;1:30–46.
    1. Shrout PE, Fleiss JL. Intraclass correlations: Uses in assessing rater reliability. Psychol Bull. 1979;2:420–428.
    1. Bryk A, Raudenbush S. In: Hierarchical Liner Models: Applications and Data Analysis Methods. 2, editor. Thousand Oaks, CA: Sage; 2002.
    1. Adewale AJ, Hayduk L, Estabrooks CA, Cummings GG, Midodzi WK, Derksen L. Understanding hierarchical linear models: Applications in nursing research. Nursing Research. 2007;56(4 Supplement 1):S40–S46.
    1. Maslach C, Jackson SE, Leiter MP. In: Maslach Burnout Inventory. 3, editor. Palo Alto, CA: Consulting Psychologists Press; 1996.
    1. Rostila I, Suominen T, Asikainen P, Green P. Differentiation of organizational climate and culture in public health and social services in Finland. J Pub Health. 2011;19:39–47.
    1. Glisson C, Landsverk J, Schoenwald S, Kielleher K, Hoagwook K, Mayberg S, Green P. Assessing the Organizational Social Context (OSC) of Mental Health Services: Implications for Implementation Research and Practice. Administration and Policy in Mental Health. 2008;35(1):98–113. doi: 10.1007/s10488-007-0148-5.
    1. Batalden P, Nelson E, Edwards W, Godfrey M, Mohr J. Developing small clinical units to attain peak performance. Joint Commission Journal on Quality and Safety. 2003;29(11):575–585.
    1. French B, Thomas L, Baker P, Burton C, Pennington L, Roddham H. What can management theories offer evidence-based practice: A comparative analysis of measurement tools for organizational context. Implement Sci. 2009;4:28. doi: 10.1186/1748-5908-4-28.
    1. Clarke H. A.B.C. Survey. Vancouver: Registered Nurses Association of British Columbia; 1991.
    1. Foundation CHSR. Is research working for you? A self assessment tool and discussion guide for health services management and policy organizations. Ottawa: Canadian Health Services Research Foundation; 2005.
    1. Watson B, Clarke C, Swallow V, Forster S. Exploratory factor analysis of the research and development culture index among qualified nurses. Journal of Clinical Nursing. 2005;14:1042–1047. doi: 10.1111/j.1365-2702.2005.01214.x.
    1. Mallidou A, Cummings G, Esatbrooks C, Giovannetti P. Nurse specialty subcultures and patient outcomes in acute care hospitals: A multiple-group structural equation modelling. Int J Nurs Stud. 2011;48(1):81–93. doi: 10.1016/j.ijnurstu.2010.06.002.
    1. Rogers EM. In: Diffusion of Innovations. 4, editor. New York: The Free Press; 1995.

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