Predicting hospital readmissions and underlying risk factors of Lung Cancer with Machine Learning
Readmission after pulmonary lobectomy is a frequent challenge for hospitals, healthcare plans, and insurance providers. Readmission is a condition when a patient is admitted to a hospital for any reason within 30 days of discharge from their hospital. Re-occurring problems and readmissions have been a major issue in the healthcare system. Readmissions are often costly; however, their findings can be incredibly beneficial for both the public and healthcare industries. With this in consideration, to improve Americans’ healthcare, Hospital Readmissions Reduction Program (HRRP) was brought in motion by the Centers for Medicare & Medicaid Services (CMS). This program penalizes hospitals with excessive readmissions.
Allwyn is developing a machine learning based approach to reduce readmissions by recommending data-driven preventive actions prior to a lobectomy procedure. This approach can be used by various organizations such as hospitals or healthcare companies to take proactive measures and circumvent readmissions by predicting:
- The probability of a patient’s readmission
- Underlying risk factors
We will be sharing the challenges with Data Exploration and Engineering, followed by our Strategy and its impact. Follow us on LinkedIn as we share our approach in the coming weeks.