Author: Healthcare Innovation
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Using Generative AI to Extract SDOH
Problem Background Recognizing the critical role of inclusive data and cultures when approaching healthcare challenges and reducing health inequities, two leading healthcare organizations collaborate on an approach to identify Social Determinants of Health (SDOH) in medical data. This new collaboration aims to co-validate technology approaches labelling SDOH factors such as socioeconomic status, housing, and transportation.…
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Using Generative AI to Effectively Triage Cancer Patients
Problem Background Effectively triaging patients is a key factor in improving access to world-class cancer care and reducing the administrative burden for staff and clinicians. Patient service representatives (PSR) staff, must review detailed, complex, and lengthy triage instructions. Reconciling these important, but often times difficult to understand triage instructions, can result in mismatched routings of…
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Increasing Transparency for Patients During Referrals
Problem Background Patient Contact Centers around the US are vital in facilitating patient care coordination, whether it be through scheduling appointments, connecting people to specialty care providers, or providing access points for customers to the clinical system. One of the PCC’s primary responsibilities is processing referrals, or requests from a Primary Care Physician (PCP) to…
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Open-source data: Total Body PET (TB PET) Scanner
Problem Background Until today, the world’s community of TB PET imaging professionals has been small and disparate. Although many of them frequently encounter common issues associated with the technology, they have lacked a centralized platform to collaborate on, contribute to, and discuss them. These challenges – which center around issues like data anonymization, high barriers…
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Combatting Medical Misinformation
Problem Background Around the world, public health administrators are overwhelmed by false medical information and its impacts on their communities. As demonstrated throughout the COVID-19 pandemic, community members’ acceptance of dangerous medical rumors can have severe impacts on their health and livelihood, leading them to eschew professional diagnoses in favor of scientifically unfounded and potentially…
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An open-source approach to Patient Reported Outcomes
Problem Background Medical departments often use disparate software platforms or manual processes to manage patient-reported outcome (PRO) data collection. This leaves surgeons with numerous blind spots and biases in understanding how their patients’ recoveries are progressing, leading to patient education with incomplete data. This gap is exacerbated by the fact that underserved patients typically underreport…