Emergency Room Readmissions: A Case Study

784 Words4 Pages
A few examples

1) Preventing Heart Attacks: Pacemakers can take real-time metrics in patients and _ag a patient if they show symptoms to have a heart attack. A physician can see this alert and notify the patient to go to the hospital for care to prevent this life threatening event.

2) Predicting Hospital Readmissions: Hospitals could generate analytical models to better predict emergency room admissions before they happen to improve care and reduce costs.

3) Detecting Patients’ Risk of Suicide: Analyze patients, who were hospitalized for mental health problems, and identify the most prevalent factors that lead to suicide. Clinicians can then identify and monitor high-risk individuals [7].

How firms are using predictive analytics to improve Health Care

1) Google uses unlikely data sources to predict in semi-real time where the flu and dengue are. Google has a team of data scientists and collaborates with teams of epidemiologists from all over the world to parse the search streams in order to detect in real time where the flu and dengue are. In the case of the flu, there is
…show more content…
Providence Health Plan has created a simple financial model to determine which patients will be enrolled in a care management program. Providence Health Plan’s disease management programs include congestive heart failure, coronary artery disease, diabetes, management, chronic obstructive pulmonary disease (COPD), and asthma. On a per-disease basis, the institution is able to assess risk based on the amount of money spent in an ambulatory or hospital setting. While the algorithm is crude, this use case shows once again how choosing simple data to operate on sometimes can yield important results. As care teams collaborate with data scientists, working toward simple and elegant solutions is often sufficient when more complex data mining is not possible
Get Access