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. 2021 Nov 29;23(11):e26123.
doi: 10.2196/26123.

Examination of a Canada-Wide Collaboration Platform for Order Sets: Retrospective Analysis

Arshia Pedram Javidan  1   2 , Allan Brand  3 , Andrew Cameron  4 , Tommaso D'Ovidio  3 , Martin Persaud  3 , Kirsten Lewis  3 , Chris O'Connor  5
Affiliations

Examination of a Canada-Wide Collaboration Platform for Order Sets: Retrospective Analysis

Arshia Pedram Javidan et al. J Med Internet Res. .

Abstract

Background: Knowledge translation and dissemination are some of the main challenges that affect evidence-based medicine. Web 2.0 platforms promote the sharing and collaborative development of content. Executable knowledge tools, such as order sets, are a knowledge translation tool whose localization is critical to its effectiveness but a challenge for organizations to develop independently.

Objective: This paper describes a Web 2.0 resource, referred to as the collaborative network (TCN), for order set development designed to share executable knowledge (order sets). This paper also analyzes the scope of its use, describes its use through network analysis, and examines the provision and use of order sets in the platform by organizational size.

Methods: Data were collected from Think Research's TxConnect platform. We measured interorganization sharing across Canadian hospitals using descriptive statistics. A weighted chi-square analysis was used to evaluate institutional size to share volumes based on institution size, with post hoc Cramer V score to measure the strength of association.

Results: TCN consisted of 12,495 order sets across 683 diagnoses or processes. Between January 2010 and March 2015, a total of 131 health care organizations representing 360 hospitals in Canada downloaded order sets 105,496 times. Order sets related to acute coronary syndrome, analgesia, and venous thromboembolism were most commonly shared. COVID-19 order sets were among the most actively shared, adjusting for order set lifetime. A weighted chi-square analysis showed nonrandom downloading behavior (P<.001), with medium-sized institutions downloading content from larger institutions acting as the most significant driver of this variance (chi-gram=124.70).

Conclusions: In this paper, we have described and analyzed a Web 2.0 platform for the sharing of order set content with significant network activity. The robust use of TCN to access customized order sets reflects its value as a resource for health care organizations when they develop or update their own order sets.

Keywords: Web 2.0; evidence-based medicine; health informatics; knowledge translation; order sets.

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Conflict of interest statement

Conflicts of Interest: APJ has no conflicts of interest to declare. AB, AC, TD, MP, and CO were previously employed by Think Research, the source of the database used in this study. KL is currently employed by Think Research. None of the authors received any financial incentive for any of their contributions to this study. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Figures

Figure 1
Figure 1
Contribution and access activity on the collaborative network, simplified using a model with only 2 organizations.
Figure 2
Figure 2
Data selection criteria and associated number of resources for the final data set.
Figure 3
Figure 3
Network diagram showing total collaborative network for downloads of order sets during the study period by hospital size. Node color represents hospital size (gray=small; teal=medium; purple=large; loyal blue=group). Node size is representative of the source size of the institution (ie, popularity of that site’s content). Edge color and width represent sink hospital size and the relative number of downloads (ie, thicker=more unique downloads of content). Arrows point from source hospital to sink hospital.
Figure 4
Figure 4
Network graph of order set downloads for order sets corresponding to COVID-19. Node color represents hospital size (gray=small; teal=medium; purple=large; loyal blue=group). Node size is representative of the source size of the institution (ie, popularity of that site’s content for this particular order set). Edge color and width represent sink hospital size and the relative number of downloads (ie, thicker=more unique downloads of content). Arrows point from source hospital to sink hospital.
See this image and copyright information in PMC

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