Short answer

Prioritize features that foster collaboration and shared understanding between patients, clinicians, and caregivers within the design of clinical decision support tools.

Field: Human Factors
Source: BMC Medical Informatics and Decision Making (2020)
Method: Grounded Theory Approach
Evidence: Strong effect

mHealth clinical decision support systems should be designed to actively facilitate shared decision-making between clinicians, patients, and caregivers, rather than solely relying on algorithmic outputs. This human factors research insight is drawn from a 2020 study published in BMC Medical Informatics and Decision Making. Using Grounded theory approach, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Prioritize features that foster collaboration and shared understanding between patients, clinicians, and caregivers within the design of clinical decision support tools.

Study

Human FactorsHigh ImpactStrong effect

Shared Decision-Making in mHealth Systems Enhances Patient-Clinician Collaboration

BMC Medical Informatics and Decision Making · 2020

Key Findings

01Enabling shared decision-making between clinician, patient, and carer is a core principle for mHealth design.
02Flexibility in the system is crucial to accommodate variations in diagnostic and treatment approaches among clinicians.
03Integration of information from multiple sources is a key functional requirement.
04The patient-clinician relationship is central to clinical decision-making, and theoretical modeling of human judgment is more relevant than purely algorithm-based approaches.

Application

Design takeaway

Prioritize features that foster collaboration and shared understanding between patients, clinicians, and caregivers within the design of clinical decision support tools.

How to apply

When designing any health-related technology, consider how it will impact and support the communication and decision-making processes among all involved parties, not just the end-user clinician.

Project actions

01Consider the different roles and perspectives of all users (patient, caregiver, clinician) in your design.
02Think about how your design can support communication and shared understanding.
03Explore how to make your design flexible enough to fit different user needs and contexts.

Method & Evidence

AimHow can mHealth clinical decision support systems be designed to effectively support shared decision-making between clinicians, patients, and caregivers in the context of Parkinson's disease management?

MethodGrounded Theory Approach

ProcedureThe study employed a grounded theory approach to understand user needs and inform the design of an mHealth clinical decision support system for Parkinson's disease. This involved gathering data to develop theoretical principles for mHealth design.

ContextHealthcare technology design, specifically mHealth for chronic disease management (Parkinson's disease).

Variables

IV["Design features supporting shared decision-making","System flexibility","Information integration capabilities"]

DV["Effectiveness of shared decision-making","Patient-clinician collaboration","User satisfaction"]

CV["Specific disease context (Parkinson's)","User roles (clinician, patient, caregiver)","Theoretical grounding of design principles"]

Strengths & Limitations

Strengths

+Grounded theory approach provides a user-centered foundation for design.
+Focus on theoretical principles offers transferable insights beyond a specific technology.

Limitations

The study's focus on theoretical principles means practical usability and effectiveness in real-world scenarios may vary. The specific context of Parkinson's disease might limit direct applicability to other conditions.

Reliability & validity

The reliability of the findings would depend on the rigor of the grounded theory data collection and analysis. Validity is enhanced by the theoretical grounding and focus on user needs, but the lack of direct system testing might limit external validity.

Think critically

To what extent can technology truly 'enable' shared decision-making, or does it risk over-simplifying or even undermining the nuanced human interactions involved?

Design Principles

"Design for collaborative intelligence, where technology augments human judgment and facilitates shared decision-making."

Effective design of health technologies requires understanding the complex human interactions involved in healthcare. By prioritizing shared decision-making, designers can create tools that support, rather than dictate, the collaborative process, leading to more personalized and effective care.

What This Means for Your Design

When you make a health app for doctors and patients, make sure it helps them talk to each other and make decisions together, instead of just telling them what to do.

How to use in your project

1.Use this research to justify the importance of user collaboration and shared decision-making in your design process.
2.Refer to the principles of shared decision-making and theoretical modeling of human judgment when discussing your design choices.

Add to My Project

Quick Cite

Paragraph starter

This design project acknowledges the critical role of shared decision-making in effective healthcare, drawing upon research that highlights the importance of facilitating collaboration between clinicians, patients, and caregivers. By prioritizing features that support this dynamic, as advocated by Timotijević et al. (2020), the design aims to enhance the patient-clinician relationship and integrate diverse information sources, moving beyond purely algorithmic approaches to decision support.

Source

BMC Medical Informatics and Decision Making

Designing a mHealth clinical decision support system for Parkinson’s disease: a theoretically grounded user needs approach

journal · 2020

View source

Questions About This Research

What does the research say about shared decision-making in mhealth systems enhances patient-clinician collaboration?: Prioritize features that foster collaboration and shared understanding between patients, clinicians, and caregivers within the design of clinical decision support tools. Evidence: BMC Medical Informatics and Decision Making (2020).
Why does "Shared Decision-Making in mHealth Systems Enhances Patient-Clinician Collaboration" matter for design?: Effective design of health technologies requires understanding the complex human interactions involved in healthcare. By prioritizing shared decision-making, designers can create tools that support, rather than dictate, the collaborative process, leading to more personalized and effective care.
How can designers apply this research?: Prioritize features that foster collaboration and shared understanding between patients, clinicians, and caregivers within the design of clinical decision support tools.
What were the main findings?: Enabling shared decision-making between clinician, patient, and carer is a core principle for mHealth design.. Flexibility in the system is crucial to accommodate variations in diagnostic and treatment approaches among clinicians.. Integration of information from multiple sources is a key functional requirement.. The patient-clinician relationship is central to clinical decision-making, and theoretical modeling of human judgment is more relevant than purely algorithm-based approaches.
What research method was used?: Grounded Theory Approach.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2020 journal from BMC Medical Informatics and Decision Making.
What should I do differently in my next project?: When designing any health-related technology, consider how it will impact and support the communication and decision-making processes among all involved parties, not just the end-user clinician.
What are the limitations?: The findings are specific to Parkinson's disease and may not be directly generalizable to all chronic conditions or healthcare settings. The study focused on theoretical principles, and the practical implementation and testing of the designed system were not detailed.