Research Article: Development and psychometric testing of the clinical networks engagement tool

Date Published: March 28, 2017

Publisher: Public Library of Science

Author(s): Jill M. Norris, Kent G. Hecker, Leora Rabatach, Tom W. Noseworthy, Deborah E. White, Jacobus P. van Wouwe.

http://doi.org/10.1371/journal.pone.0174056

Abstract

Clinical networks are being used widely to facilitate large system transformation in healthcare, by engagement of stakeholders throughout the health system. However, there are no available instruments that measure engagement in these networks.

The study purpose was to develop and assess the measurement properties of a multiprofessional tool to measure engagement in clinical network initiatives. Based on components of the International Association of Public Participation Spectrum and expert panel review, we developed 40 items for testing. The draft instrument was distributed to 1,668 network stakeholders across different governance levels (leaders, members, support, frontline stakeholders) in 9 strategic clinical networks in Alberta (January to July 2014). With data from 424 completed surveys (25.4% response rate), descriptive statistics, exploratory and confirmatory factor analysis, Pearson correlations, linear regression, multivariate analysis, and Cronbach alpha were conducted to assess reliability and validity of the scores.

Sixteen items were retained in the instrument. Exploratory factor analysis indicated a four-factor solution and accounted for 85.7% of the total variance in engagement with clinical network initiatives: global engagement, inform (provided with information), involve (worked together to address concerns), and empower (given final decision-making authority). All subscales demonstrated acceptable reliability (Cronbach alpha 0.87 to 0.99). Both the confirmatory factor analysis and regression analysis confirmed that inform, involve, and empower were all significant predictors of global engagement, with involve as the strongest predictor. Leaders had higher mean scores than frontline stakeholders, while members and support staff did not differ in mean scores.

This study provided foundational evidence for the use of this tool for assessing engagement in clinical networks. Further work is necessary to evaluate engagement in broader network functions and activities; to assess barriers and facilitators of engagement; and, to elucidate how the maturity of networks and other factors influence engagement.

Partial Text

Large-scale transformation in healthcare requires engaging stakeholders across the health system.[1–4]. Engagement has been described as the active involvement of stakeholders in maintaining and enhancing the performance of their organisation.[2,3] Evidence suggests that when healthcare professionals are engaged in their health system, organizations benefit from reductions in mortality, adverse drug events, errors, and infection rates,[5–8] as well as enhanced quality of care and patient experience.[7,9,10] Findings from a large-scale study in the NHS indicated that trusts with higher staff engagement exhibit better financial performance.[7] Alongside this growing evidence for the link between engagement and performance, there have been a number of advances in physician[3,6,11,12] and patient engagement in healthcare,[13–15] Efforts to engage the spectrum professionals and stakeholders who design and carry out quality improvement initiatives, however—a process outlined within numerous healthcare improvement models.[16–22]—have often been met with limited success.[23–25]

The objective of this study was to create a brief, multiprofessional tool to measure engagement in SCN initiatives, and establish evidence for reliability and construct validity of the tool. We created items based on the IAP2 spectrum of engagement[36] and included the input of experts and clinicians. From 16 items, four distinct subscales were established through the EFA and CFA: (1) global engagement, (2) inform, (3) involve, and (4) empower; all of the subscales demonstrated acceptable reliability. Inform, involve, and empower were all significant predictors of global engagement, but both the CFA and regression analysis demonstrated that involve was the strongest predictor. Leaders exhibited significantly higher scores across all scales than stakeholders, while members and support staff did not differ in their scores. In sum, we have established preliminary psychometric evidence of this engagement tool for use with SCNs.

To conclude, this clinical networks engagement tool demonstrates preliminary evidence of construct validity and reliability. In further work, we propose to assess engagement in broader network activities beyond that of discrete projects, as well as evaluating the factors that influence engagement and how the maturity of networks factors into engagement.

 

Source:

http://doi.org/10.1371/journal.pone.0174056

 

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