National Journal of Community Medicine (Dec 2023)
Evaluating Usability of IRAIVI Pregnancy Prediction Model Using System Usability Scale
Abstract
Background: Barriers to utilize maternal healthcare services amongst pregnant women at community level differs substantial variation among slums and urban areas which is essential to recognize and resolve these issues within framework of district-level policy planning. IRAIVI pregnancy prediction model is developed to enhance optimal utilization of maternal healthcare services. The study was conducted to evaluate usability of IRAIVI using System Usability Scale amongst healthcare workforce. Methods: This model was developed with a set of predictors based on data collected during baseline and follow up visits from currently pregnant women as per study protocol. For evaluating efficiency of this model, System Usability Scale (SUS) was adopted and shared with 25 randomly selected experts in the field of public health. The questionnaire was shared via google form and responses recorded on Likert’s scale were then analysed using SPSS. Results: IRAIVI model's usability assessed using SUS found to be user-friendly, best learning curve, adaptable to new system and highly acceptance by healthcare workforce. The SUS score averaging at 84 demonstrates favourable usability of the model. Conclusion: This model has capability to accentuate maternal health services which in-turn can contribute for better ANC services in resource-constrained settings. Additionally, future opportunities can be explored through field studies in different settings.
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