Big data and artificial intelligence (AI) fueled technologies have evolved to leverage massive datasets and predictive analytics to suit different industries needs and interests. In this module we will examine how these technology trends have impacted the healthcare sector and patient care.
Electronic Health Records (EHRs) are a necessary part of medical care in the 21st century. These sophisticated information system technologies spur massive production of discrete data, which then fuel AI implementations to support medical decision-making. The key categories of applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. All of these medical IS applications raise a host of social and political issues related to justice, equity, diversity, and inequality of the current U.S. medical and public health system that in turn impact technical aspects of designing AI based health data systems such as massive dataset quality control, algorithmic fairness and the potential for inherent biases, and medical system access and trust. There are also a variety of privacy concerns with AI-systems based on how the training and testing datasets are constructed and evaluated related to HIPAA data protections.
Please, answer this short concept check. - approx. 5 minutes
The goal of this activity is for you to gain familiarity with EHR data entry through a role play scenario with an example “EHR” system. Read over the “Activity 1 Patient Intake Instructions” and wait for your group assignments.
Activity 1 Patient Intake Instructions
Medical Intake Form Patient Intake Data
Next:
Jamboard Reflection: Physician Stakeholder Concerns
Read Pew Report and work on a draft of the Letter to the EHR Development Team (see Classroom). Bring the letter draft to class on Wed for peer review (as Google Doc).
Listen: Machine Ethics Podcast Dr. Cosima Gretton on AI, Health care and it's current cost structure and technologies, Ethics in education
Read: One of the two AI Ethics Framework Papers
Read Article Schute and Fry (2019) Death by a Thousand Clicks: How Electronic Health Records Went Wrong
Read Pew Report (2023) on Lack of Trust in Use of AI in Healthcare Decision-Making
Jamboard Reflection: Your Medical AI Consent
Group Letter Construction: Take your drafts and combine best parts of individual arguments to create compelling letter to EHR development team about why the failures of the system are important to the organization. Submit to Classroom as a group.
Please answer this short concept check approx. 5 minutes by Sunday March 5 11:59pm.
Submit: Compile and revise your letters as a small group and submit to Classroom by Wed March 8th 11:59pm.
Watch: Ted Talk Dr. Cosima Gretton Technology and the Future of Medicine
Watch: Video on Vermont's investigation into EHR ethical issues (2015)
Read: EHRs Fail to Detect Up To 33% of Medication Errors (2020)
Read: Nurses Give EHRs an F in New Study (2021)
Read: Ransomware Attack Wipes out Arizon Clinic EHR system and Corrupts 35,000 Patient Records
Read: HITECH and Meaningful Use Standards
Read: Epic Systems and Cerner lead EHR Vendors in AI development
See Classroom for additional narratives on this topic