Design of a clinical balance tool for fall risk assessments: A development and usability study - Jennifer Hornung Garvin; Virginia M. Yazzie; Natalie A. Katsuyama; Truman Rudloff; Lise C. Worthen-Chaudhari; Ajit M. W. Chaudhari (PLoS ONE, 2025)
Background Falls are a significant source of early morbidity and mortality in the aging population, yet clinical changes that lead to increased fall risks often escape early identification and intervention. A device to measure postural control would facilitate evidence-based fall risk assessment. Objectives Our objectives were to iteratively develop a prototype quantitative posture instrument (QuPI) to replace the weight scale and to assess barriers and facilitators of its implementation in a clinical setting. Methods We undertook an iterative formative evaluation and usability study of QuPI prototypes in primary care, medical oncology, sports medicine, cardiology, and endocrinology outpatient clinics. Clinicians evaluated an initial QuPI prototype and completed a semi-structured interview to determine critical functionality, inform design, and assess usability. The QuPI was then modified according to the results, and a new prototype was tested and evaluated. Results Eighteen clinicians participated in both rounds of interviews. Clinicians who participated (referred to as participants) reported willingness to use the QuPI with all patients during the first round of interviews and stated they would replace their current weight scale with the modified QuPI during the second round of interviews. Participants identified design elements that were both facilitators and barriers to use. Usability scores for both prototypes were excellent. Despite several national guidelines for fall risk assessments, lack of consistent use of guidelines by care teams was found to be a barrier to effective fall risk assessments. Conclusion The QuPI provides a new method for quantifying fall risks with good user acceptance, usability, and clinical feasibility without disrupting workflow. The QuPI supplemented and facilitated the use of standard algorithms for fall risk assessment. Greater education of the entire care team regarding evidence-based fall risk assessment will promote adherence to guidelines and fall prevention.