Innovation Science and Implementation - Page 3 of 12 - Duke Institute for Health Innovation

With its mission in mind, DIHI strives to implement each of its innovations to positively impact clinical care in the real world. DIHI has designed, led, and measured impact for numerous innovation implementations. Moreover, DIHI applies its evolving methodologies into the design and implementation of each new innovation, thereby increasing the speed to deliver value and expanding the potential for achievable transformative innovation.

doctor and patient reviewing an X-ray of the patient's shoulder

Using AI for Surgery Pre-Authorization

Identifying and outlining documentation for surgery pre-authorizations.

a university building in the background, with a small lake and palm trees in the foreground

World Health AI Partnership

Focused on capacity building, best practice diffusion, and AI solution scaling between Duke Health and Aga Khan University in Kirachi, Pakistan.

Automating Behavioral Health Evaluation in Primary Care

Automating follow up to a positive BH screen in 6-11 year old patients within primary care by distributing, collecting and scoring ADHD, Depression and Anxiety questionnaires directly within the EHR.

EASY Telehealth Care: Optimizing telehealth in rheumatology

Enable rheumatology providers to identify patients who could be seen by telehealth rather than in-person at their next follow-up appointment.

Automated Post-Hospitalization Track for Patients Discharged on Outpatient Parenteral Antimicrobial Therapy (OPAT)

Implement a real-time OPAT patient dashboard to facilitate earlier hospital discharge and automate the process of early post-discharge follow-up.

patient with lower back pain being seen by a nurse

Using Machine Learning to Appropriately Triage Patients with Low Back Pain (LBP)

Develop and validate a machine learning algorithm capable of predicting patient need for spinal surgery or non-operative management utilizing elements from the electronic health record.

abstract technological image depicting data science

Automating CMS Quality Measure Curation

Optimize the process and enhance the efficiency of quality measure reporting to removes unnecessary burden from clinical staff.

nurse talking with patient getting ready to perform a pulmonary function test

Machine Learning for Interpreting PFTs: Improving operational efficiency of pulmonary medicine

Automating PFT interpretation

patient talking with their treatment team

Automated Patient Care Assignment: Accelerating every-day operational efficiency

Optimize patient placement and individual team member assignment