The use of model constructs to design collaborative health information technologies: A case study to support child development

Sean P Mikles; Hyewon Suh; Julie A Kientz; Anne M Turner

doi:10.1016/j.jbi.2018.09.003

The use of model constructs to design collaborative health information technologies: A case study to support child development

J Biomed Inform. 2018 Oct:86:167-174. doi: 10.1016/j.jbi.2018.09.003. Epub 2018 Sep 5.

Authors

Sean P Mikles¹, Hyewon Suh², Julie A Kientz², Anne M Turner³

Affiliations

¹ Biomedical Informatics and Medical Education, University of Washington, Box 357240, 1959 NE Pacific Street, Seattle, WA 98195, USA. Electronic address: smikles@uw.edu.
² Human Centered Design & Engineering, University of Washington, 428 Sieg Hall, Box 352315, 1959 NE Pacific Street, Seattle, WA 98195, USA.
³ Biomedical Informatics and Medical Education, University of Washington, Box 357240, 1959 NE Pacific Street, Seattle, WA 98195, USA; Department of Health Services, University of Washington, Magnuson Health Sciences Center, Room H-680, Box 357660, 1959 NE Pacific Street, Seattle, WA 98195, USA.

Abstract

Objective: Health information technology could provide valuable support for inter-professional collaboration to address complex health issues, but current HIT systems do not adequately support such collaboration. Existing theoretical research on supporting collaborative work can help inform the design of collaborative HIT systems. Using the example of supporting collaboration between child development service providers, we describe a deductive approach that leverages concepts from the literature and analyzes qualitative user-needs data to aid in collaborative system design.

Materials and methods: We use the Collaboration Space Model to guide the deductive qualitative analysis of interviews focused on the use of information technology to support child development. We deductively analyzed 44 interviews from two separate research initiatives and included data from a wide range of stakeholder groups including parents and various service providers. We summarized the deductively coded interview excerpts using quantitative and qualitative methods.

Results: The deductive analysis method provided a rich set of design data, highlighting heterogeneity in work processes, barriers to adequate communication, and gaps in stakeholder knowledge in supporting child development work.

Discussion: Deductive qualitative analysis considering constructs from a literature-based model provided useful, actionable data to aid in design. Design implications underscore functions needed to adequately share data across many stakeholders. More work is needed to validate our design implications and to better understand the situations where specific system features would be most useful.

Conclusions: Deductive analysis considering model constructs provides a useful approach to designing collaborative HIT systems, allowing designers to consider both empirical user data and existing knowledge from the literature. This method has the potential to improve designs for collaborative HIT systems.

Keywords: Child development; Collaborative work; Interdisciplinary communication; Public health informatics; Qualitative research; Software design.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Access to Information
Algorithms
Child
Child Development*
Child, Preschool
Communication
Cooperative Behavior
Data Collection / methods
Delivery of Health Care
Early Intervention, Educational
Electronic Health Records*
Humans
Mass Screening / methods
Medical Informatics / methods*
Pediatrics / organization & administration
Primary Health Care / organization & administration
Qualitative Research
Software
Washington

Grants and funding

T15 LM007442/LM/NLM NIH HHS/United States