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Orgs Push Digital Medicine, EHR Tool to Advance Digestive Health

Four major healthcare research facilities are teaming up to develop a digestive health toolkit using digital medicine to implement into the EHR.

UC Davis Health has joined forces with Mount Sinai, Cleveland Clinic, and Northwestern to design a digestive health digital medicine toolkit and implement it into the EHR.

Funded by a National Institutes of Health (NIH) grant, the four healthcare institutions aim to develop the Inflammatory Bowel Disease (IBD) Digital Therapeutics Toolkit to generate electronic patient-reported outcomes (ePROs) through scientific evidence and digital medicine.

During the pandemic, telehealth and digital monitoring became more prevalent for providing care for various chronic diseases. According to HHS, Medicare fee-for-service in-person visits for primary care fell quickly in mid-March. Then, telehealth accounted for nearly half of Medicare primary care visits in April.

Although telehealth and digital medicine use became more widespread in 2020, implementing these digital tools into the EHR remained a challenge. The four research groups said it could be difficult to implement the IBD tool into the EHR without disrupting the workflow.

“Our hypothesis is that medical homes supported by a unified EHR-connected platform and automated IBD-specific digital interventions will translate to a sustainable improvement in population health outcomes,” Ashish Atreja, CIO and chief digital health officer at UC Davis Health, and co-principal investigator of the NIH grant, said in a statement.

“By leveraging the efficiency and scalability of digital health and AI, we hope to create a national model for proactive and comprehensive care for every single IBD patient.”

Utilizing this grant, UC Davis Health, Mount Sinai, Cleveland Clinic, and Northwestern intend to establish disease control baseline levels and integrate automated precision-matched digital and medical home interventions. The four research groups said they plan to include behavioral health, digital skills, social determinants of health, referral to interdisciplinary care, and treat-to-target goals through apps.

Through the development and integration stages, the research groups aim to:

  • Combine existing digital assets to develop a digestive health toolkit to integrate into the EHR at the four research facilities
  • Evaluate levels of care metrics, digital connectivity, disease control, and quality of life data at the four facilities
  • Implement and evaluate precision-matched interventions, such as those for social determinants of health and behavioral health, among 1,500 patients using a randomized trial with the IBD toolkit
  • Support integration and distribution across various Clinical and Translational Science Awards (CTSA) sites

“Through the creation of a Digital Transformation Network (DTN) for Inflammatory Bowel Disease (IBD), we plan to reduce digital disparities and scientifically address the evidence gap of digital health interventions across populations and communities,” NIH said.

Medical researchers across the country are utilizing grants to develop EHR tools to aid specific medical issues.

In December 2020, researchers at the Lewis Katz School of Medicine (LKSOM) at Temple University received a $2.5-million grant from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to advance EHR tools that predict hospital readmission among diabetes patients.

Over a million diabetes patients are readmitted to the hospital for a diabetes-related illness and most are readmitted within 30 days of their last hospitalization. These readmissions are costly for the patient, and multiple readmissions can significantly impact a patient’s health.

Researchers from Temple developed a model called the Diabetes Early Readmission Risk Indicator (DERRI). The research group now aims to optimize this base model using EHR data, to predict 30-day readmission risk among diabetes patients.

“The DERRI app originally was developed for point-of-care use, with patients manually inputting information on a small number of variables, such as insulin use, co-existing conditions and recent hospital discharge,” said Daniel J. Rubin, MD, associate professor of Medicine at LKSOM and chair of the glycemic control taskforce at Temple University Hospital.

The Temple research group upgraded the DERRI model to eDERRI, which will integrate data from the PaTH Clinical Data Research Network (CDRN), a co-member of the National Patient-Centered Clinical Research Network.

The study author said the researchers would optimize predictive modeling by applying state-of-the-art deep-learning methods.

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