Indiana University-Purdue University Indianapolis (IUPUI) / Unmet social needs pose significant risk to both patients and healthcare organizations by increasing morbidity, mortality, utilization, and costs. Health care delivery organizations are increasingly employing social workers to address social needs, given the growing number of policies mandating them to identify and address their patients’ social needs. However, social workers largely document their activities using unstructured or semi-structured textual descriptions, which may not provide information that is useful for modeling, decision-making, and evaluation. Therefore, without the ability to convert these social work documentations into usable information, the utility of these textual descriptions may be limited. While manual reviews are costly, time-consuming, and require technical skills, text mining algorithms such as natural language processing (NLP) and machine learning (ML) offer cheap and scalable solutions to extracting meaningful information from large text data. Moreover, the ability to extract information on social needs and social work interventions from free-text data within electronic health records (EHR) offers the opportunity to comprehensively evaluate the outcomes specific social work interventions. However, the use of text mining tools to convert these text data into usable information has not been well explored. Furthermore, only few studies sought to comprehensively investigate the outcomes of specific social work interventions in a safety-net population. To investigate the role of social workers in addressing patients’ social needs, this dissertation: 1) utilizes NLP, to extract and categorize the social needs that lead to
referral to social workers, and market basket analysis (MBA), to investigate the co-occurrence of these social needs; 2) applies NLP, ML, and deep learning techniques to extract and categorize the interventions instituted by social workers to address patients’ social needs; and 3) measures the effects of receiving a specific social work intervention type on healthcare utilization outcomes.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/25986 |
| Date | 04 1900 |
| Creators | Bako, Abdulaziz Tijjani |
| Contributors | Vest, Joshua R., Blackburn, Justin, Walter-McCabe, Heather, Kasthurirathne, Suranga, Menachemi, Nir |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
Page generated in 0.0019 seconds