Health Care Analytics for Patient Outcomes
In 2022, a NHS hospital, based in Leeds, collaborated with Metical Technologies to develop a predictive analytics model for sepsis.
Sepsis is a potentially life-threatening condition caused by the body’s response to an infection. Early detection and treatment are critical for improving patient outcomes and reducing mortality rates.
The data science team at Metical started by analysing electronic health record data for over 35,000 patients at NHS hospital. They used machine learning algorithms to identify patterns in the data and develop a predictive model for sepsis.
The model analysed patient data in real-time and generated alerts when a patient was at high risk of developing sepsis. The alerts were sent to the hospital’s care teams, who could take appropriate action to prevent the onset of sepsis.
The results of the project were significant. The hospital saw a 20% reduction in mortality rates for patients with sepsis, as well as a 30% reduction in sepsis-related readmissions. The model was also able to identify patients at high risk of sepsis earlier, which allowed for earlier treatment and improved patient outcomes.
In conclusion, health care analytics can be a powerful tool for improving patient outcomes and reducing mortality rates. By analysing electronic health record data and using machine learning algorithms, hospitals can identify high-risk patients and provide personalised care plans. This can lead to improved patient outcomes, as seen in the case study above.