Human-centered Design of a Health Recommender System for Orthopaedic Shoulder Treatment

TL;DR

This paper describes the development of a health recommender system for orthopaedic shoulder treatment using a human-centered design approach to support shared decision-making between doctors and patients.

Contribution

The novel contribution is the application of human-centered design to create a usable and useful health recommender system prototype for orthopaedic treatment decisions.

Findings

The I-C-IT prototype achieved a high usability score of 88.75 on the standard system usability scale.

90% of orthopaedic surgeons agreed that I-C-IT would help them make data-informed decisions with patients.

The HCD process resulted in 14 data visualization elements and key design principles for health recommender systems.

Abstract

Rich data on diverse patients and their treatments and outcomes within Electronic Health Record (EHR) systems can be used to generate real world evidence. A health recommender system (HRS) framework can be applied to a decision support system application to generate data summaries for similar patients during the clinical encounter to assist physicians and patients in making evidence-based shared treatment decisions.

A human-centered design (HCD) process was used to develop a HRS for treatment decision support in orthopaedic medicine, the Informatics Consult for Individualized Treatment (I-C-IT). We also evaluate the usability and utility of the system from the physician’s perspective, focusing on elements of utility and shared decision-making in orthopaedic medicine.

The HCD process for I-C-IT included 6 steps across three phases of analysis, design, and evaluation. A team of informaticians and comparative effectiveness researchers directly engaged with orthopaedic surgeon subject matter experts in a collaborative I-C-IT prototype design process. Ten orthopaedic surgeons participated in a mixed methods evaluation of the I-C-IT prototype that was produced.

The HCD process resulted in a prototype system, I-C-IT, with 14 data visualization elements and a set of design principles crucial for HRS for decision support. The overall standard system usability scale (SUS) score for the I-C-IT Webapp prototype was 88.75 indicating high usability. In addition, utility questions addressing shared decision-making found that 90% of orthopaedic surgeon respondents either strongly agreed or agreed that I-C-IT would help them make data informed decisions with their patients.

The HCD process produced an HRS prototype that is capable of supporting orthopaedic surgeons and patients in their information needs during clinical encounters. Future research should focus on refining I-C-IT by incorporating patient feedback in future iterative cycles of system design and evaluation.

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