CLC Prototype Project

pptx

School

Grand Canyon University *

*We aren’t endorsed by this school

Course

436

Subject

Medicine

Date

Dec 6, 2023

Type

pptx

Pages

11

Uploaded by GrandMorning7506

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PRIORITY PATIENT Jerrod James, Cherilyn Smith, & Jennifer Townsend
2 Multiple portals containing important details about the patient limiting a detailed view of the patient’s overall health. THE PROBLEM Photo retrieved from: https://dribbble.com/shots/11433513- Sign-In-Sign-Up-Page-App-UI
WIREFRAME Name: John Doe DOB: 09/30/1979 (43) Gender: Male Blood Type: A+ Organ Donor: Yes Advance Directives: Yes (AdvancedDirectives.pd f) Insurance: BCBS ID: 1234567 Emergency Contact: Jane Doe (Wife) Phone: (580) 456-7899 EKG: Ordered by Dr. Smith for heart palpitations on 10/22/2021. Results: Sinus rhythm, no A-Fib detected. Scheduled to wear a heart monitor for one month to capture palpitations. Tonsillectomy: 03/06/1999 performed by Dr. Fisher. Removed tonsils due to continuous infection of tonsils. 3 PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES
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WIREFRAME Comprehensive Metabolic Panel (04/01/2023) Ordered by: Dr. Simon Component Value Ref. Range Glucose 73 70- 110 mg/dL BUN 11 8-26 mg/dL Creatinine 0.69 0.40-1.00 mg/dL Potassium 3.9 3.5-5.2 mmol/L Calcium 8.3 (L) 8.4- ALLERGY ALERT: SULFA Current Medications: Atorvastain 20mg daily (began therapy 08/20/21) for elevated cholesterol. Prescribed by: Dr. Simon Discontinued Medications: Acetazolamide (05/31/20) Allergic reaction – rash and difficulty breathing. 4 PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES
WIREFRAME Dr. Smith 10-22-2021 Patient was seen in clinic on 10/22/2021 for heart palpitations. EKG performed to check for atrial fibrillation. Results concluded patient was in regular sinus rhythm. Scheduled a heart monitor for one month to record these palpitations. Follow up in one month for results of monitor recordings. Dr. Simon – 05/20/2023 at 2:30. Routine yearly checkup (Synced to Google Calendar with reminder). Dr. Smith - 04/16/2023 at 10:30 Follow up appointment. 5 PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES PATIENT DEMOGRAPHICS MEDICAL HISTORY MEDICATIONS LAB VALUES APPOINTMENTS PROGRESS NOTES
CHALLENGES SECURITY The preservation and security of data privacy in relation to sensitive patient health information is of paramount importance. A primary hurdle to overcome when incorporating an AI-driven patient portal is the assurance that patients' data remains safeguarded (Omar, 2021). COSTS AI systems require high-performance computing resources, including servers, storage systems, and high-speed internet connectivity. Developing AI systems requires specialized skills and expertise, including data science, and software engineering. Hiring skilled professionals or outsourcing development can be expensive. Additionally, achieving regulatory compliance can be time- consuming and costly, particularly for smaller healthcare providers (Combi et al., 2022). INTEGRATION Integration with Emergency Health Record Systems (EHR): For a successful synchronization of patient portals and EHR systems, it is crucial to ensure the accuracy and currency of patient data (Enlitic, n.d.). USER ADOPTION Patient portals may present intricacy and cognitive overload to certain users, subsequently creating a learning curve (Combi et al., 2022). 6
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SOLUTION To address these challenges, it’s critical to use secure encryption protocols to store and transfer patient data. It's also crucial to comply with data protection regulations such as HIPAA (Omar, 2021). COSTS Cloud-based solutions offer an affordable and scalable way to deploy AI systems, without the need for significant upfront investment in infrastructure. Implementing AI in a phased manner, starting with smaller- scale pilot projects, can help healthcare providers minimize risk and control costs (Enlitic, n.d.). INTEGRATION One solution is to use standardized data formats and APIs to facilitate data exchange between the portal and EHR systems (Enlitic, n.d.). USER ADOPTION A simple product gives customers the information they need in order to stock their hospitals with the right equipment (Enlitic, n.d.) . Also, portals should be designed with simplicity and user- friendliness in mind. It is essential to provide adequate training and support to medical staff ensuring that they are comfortable using the portal (Combi et al., 2022). 7 SECURITY
REAL-WORLD EXAMPLES VIRTUAL DOCTOR/NURSE AI-powered capability to monitor patients remotely, read vitals, alert to abnormalities, and provide personalized recommendations based on their medical history and symptoms(Enlitic, n.d.). DIAGNOSTICS AI algorithms can examine medical images and scans, aiding in the identification of diseases such as cancer, heart disease, and stroke. This enables physicians to reach more precise diagnoses and create more efficient treatment strategies (Enlitic, n.d.). 8 MEDICATION MANAGEMENT Aids healthcare providers in making informed decisions about which medications to prescribe and at what dosages. AI algorithms also analyze a patient's medication history and flag potential drug interactions, which can help healthcare providers avoid prescribing medications that could cause harmful side effects. (Combi et al., 2022).
Click to add photo PITCH DECK 9 Ability to perform microscopic surgeries Assist in the triage of patients Virtual nursing assistants saving costs and lives Administrative workflow assistance Precision medication detecting the undetectable REAL WORD EXAMPLES This Photo by Unknown Author is licensed under CC BY-NC-
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OUR COMPETITION OUR ADVANTAGE Singular product = singular focus Affordability = marketability Efficiency over popularity COMPETITORS Google Health/Deep Mind Butterfly Network Atomwise Ada Health 10
11 Combi, C., Amico, B., Bellazzi, R., Holzinger, A., Moore, J.H., Zitnik, M, & Holmes, J.H.. (2022). A manifesto on explainability for artificial intelligence in medicine. Artificial Intelligence In Medicine, 133. https://doi-org. lopes.idm.oclc.org/10.1016/j.artmed.2022.102423 Compunnel Digital. (2021). AI in Healthcare: Top 5 real-world related examples. Retrieved from https:www.compunneldigital.com/blog/ai-in-healthcare-top-5-real-world-examples/ Graham, C. (2022). Science daily. Science news. Robot performs first laparoscopic surgery without human help. Retrieved from https://www.sciencedaily.com/releases/2022/01/220126143954.html Omar, R. A. (2021). Unabashed bias: How health-care organizations can significantly reduce bias in the face of unaccountable AI. Denver Law Review, 98(4), 807–837. https://lopes.idm.oclc.org/login?url=https://search.ebscohost.com/login.aspx? direct=true&db=a9h&AN=151985755&site=eds-live&scope=site Reimagined healthcare requires reimagined intelligence. (n.d.). Enlitic Inc. https://enlitic.com/ The Medical Futurist. (2023). Artificial intelligence in medicine. Healthcare design. Top artificial intelligence companies in healthcare to keep an eye on RESOURCES