
Enhanced Decision Support for Periop Care
Challenges related to hospital access, staffing constraints, and patient-related factors require a refined risk prediction model to enable risk-mitigation strategies earlier in the process.
The Living Lab showcases DIHI’s approach to catalyze innovations in health and healthcare. As they evolve from pilot implementations into sustainable solutions, projects become part of the “living lab” of evaluation and iterative innovation to build upon the knowledge gained through the testing of new clinical workflows and use cases.

Challenges related to hospital access, staffing constraints, and patient-related factors require a refined risk prediction model to enable risk-mitigation strategies earlier in the process.

A model to aid actionable mild to moderate TBI triage decisions in the ER.

Estimates the pre-test probability of bacteremia and post-test probability of blood culture results in hospitalized patients for EHR-based clinical decision support.

Placing patient-specific 3D images in the Neurosurgeon’s field of view using augmented reality and advanced imaging to increase precision for epilepsy surgery.

Guiding appropriate specialty consultation and delivering tailored patient educational content.

A population health solution for NAFLD with an ultimate goal to optimize health care resources by improving access for high risk patients and minimizing unnecessary referrals.

Improving dermatology access, care delivery and cost via machine learning assisted risk stratification.

A machine learning risk stratification model to improve recognition and management of high risk PE while also reducing hospital utilization for low risk patients.

Identify high risk mortality inpatients to provide them with a Transition of Care Toolkit to help with advance care planning.