J R Vest, S N Kasthurirathne, W Ge, J Gutta, O Ben-Assuli, P K Halverson
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Choice of measurement approach for area-level social determinants of health and risk prediction model performance.
Objective: The objective of this paper is to provide empirical guidance by comparing the performance of six different area-level SDoH measurement approaches in predicting patient referral to a social worker and hospital admission after a primary care visit.
Methods: We compared the performance of six area-level SDoH measurement approaches in predicting patient referral to a social worker and hospital admission after a primary care visit using random forest classification algorithm. Data came from 209,605 patient encounters at a federally qualified health center. Models with each area-based measurement approach were compared against the patient-level data only model using area under the curve, sensitivity, specificity, and precision.
Results: Addition of area-level features to patient-level data improved the overall performance of models predicting need for a social worker referral. Entering area-level measures as individual features resulted in highest model performance.
Conclusion: Researchers seeking to include area-level SDoH measures in risk prediction may be able to forego more complex measurement approaches.
期刊介绍：
Informatics for Health & Social Care promotes evidence-based informatics as applied to the domain of health and social care. It showcases informatics research and practice within the many and diverse contexts of care; it takes personal information, both its direct and indirect use, as its central focus.
The scope of the Journal is broad, encompassing both the properties of care information and the life-cycle of associated information systems.
Consideration of the properties of care information will necessarily include the data itself, its representation, structure, and associated processes, as well as the context of its use, highlighting the related communication, computational, cognitive, social and ethical aspects.
Consideration of the life-cycle of care information systems includes full range from requirements, specifications, theoretical models and conceptual design through to sustainable implementations, and the valuation of impacts. Empirical evidence experiences related to implementation are particularly welcome.
Informatics in Health & Social Care seeks to consolidate and add to the core knowledge within the disciplines of Health and Social Care Informatics. The Journal therefore welcomes scientific papers, case studies and literature reviews. Examples of novel approaches are particularly welcome. Articles might, for example, show how care data is collected and transformed into useful and usable information, how informatics research is translated into practice, how specific results can be generalised, or perhaps provide case studies that facilitate learning from experience.
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