Predict Hospital Acquired Conditions

Healthcare Clinical Improve Health Outcomes Executive Summary
Bolster prevention procedures even by predicting which patients are likely to develop HACs.
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Business Problem

Hospital acquired conditions (HAC) are medical complications that a patient did not have at the time of their hospital admission, that develop over the course of their stay..There are 14 categories of HACs that range from surgical site infection to traumatic falls. Every year, the latter alone impacts 700 thousand to 1 million people in the United States, causing fractures or bleeding that lead to increasing amounts of healthcare utilization. In 2016, the Centers for Medicare & Medicaid Services (CMS) reported there were 48,771 avoidable HAC cases that resulted in 3,219 deaths and excess costs of over $2 billion. As part of its HAC reduction program, the CMS holds back about $350 million worth of reimbursements every year from hospitals that record high amounts of HACs. However poor health outcomes and nagging costs associated with HACs are preventable, and about 70% of reported HACs come from negligent injuries that can be avoided with proactive care.

Intelligent Solution

Many dimensions of care influence a given provider’s capacity to prevent patients from acquiring an HAC. The medical community has created extensive guidelines backed by research to help prevent each individual HAC from negatively impacting the lives of patients. For example, falls can be prevented by ensuring floor surfaces are dry and patients are within reach of personal possessions, and infections can be prevented through the use of ultraviolet techniques to clean rooms.

AI can be used to help bolster prevention procedures even further by enabling clinicians to predict exactly which patients are likely to develop HACs based on: patient diagnosis, medical history, and other predicted variables such as length of stay. Further, AI is able to provide clinicians with propensity scores that can be used to predict how likely each patient is to develop a specific category of HAC, and with the leading statistical factors contributing to that patient’s score. Your clinicians will augment the care they provide and will be able to prevent patients from acquiring HACs by implementing additional counteractive measures for those at risk. AI will not only help you save patient lives, but it will also ensure you capture the full breadth of reimbursements, enabling you to invest further into the community you work and care for.

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