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Envisioning a Digitalized Global Artificial Intelligent Shared Health System

The views expressed are those of the author and do not necessarily reflect the views of ASPA as an organization.

By Tekisha King
December 6, 2019

Innovative technologies can advance global healthcare with a cloud-based simplified shared artificial intelligent (AI) electronic health system to promote health equity. The system infrastructure will grant classified user access to authorized health entities and local and federal authorities, to include emergency management responders (EMRs) as amended under the Health Insurance Portability and Accountability Act (HIPAA) of 1996.  In addition, the system will preserve, transmit and interchange eminent protected personal health information (PHI)/personal identifiable information (PII) required by federal law as a national standard to protect the disclosure of sensitive patient health information. Concurrently, shared health applications would interface with Artificial Intelligence (AI) databases and Internet of Things (IoT) technologies to lessen the clinical administrative burden and focus on goals aimed to embrace quality patient-centric care. Hence, the integrated cloud-based shared health system is the first futuristic movement to integrate health data for collaboration using advanced technologies.     

The mainframe of the system infrastructure will be designed by Athena Health, partnered with database programming developers at Apple, Microsoft and Google. First, the system network security measures will include AI technologies: voice/face/fingerprint recognition, two-step multi-factor authentication and zero sign-on approaches. Next, clinical documentation will transliterate imported and exported health data with telemedicine capabilities into the electronic health record (EHR). Lastly, a self-designed user-friendly mobile application will allow smartphone users to track biometric information, prescription and other pertinent medical information to diffuse in the EMR through the patient portal. Thus, the outcomes will achieve the Organization for Economic Co-Operation and Development (OECD) policy framework with the formation of a shared decisionmaking environment for patient reporting measures: patient-reported outcome measures (PROMs), condition-specific, quality of life (QoL) and patient-reported experience measures (PREMs). 

Data management would abridge population health for providers to better cognize the patient’s needs. The Centers for Medicare and Medicaid Services (CMS) proposed a Valued-Based Care (VBC) model evolution in healthcare using design specific algorithms with health strategies to develop modern health policies. For instance, the Long-Term Support and Services (LTSS) and Home-Based Care Services (HBCS) evaluate the quality of the assessment, care coordination and care planning for dual-eligible (Medicare and Medicaid) and Medicaid recipients with chronic and incapacitating medical intricacies. The framework will empower providers and clinicians to focus on medical care. It will also empower home health agencies to focus on dedicated health services and health vendors with the adoption of cultivated integrated health solutions. Furthermore, effective collaboration and efficient shared clinical documentation would transcend efficient health care for the abundant notable, “Great Leaders,” of the past, in the future. 

Artificial intelligence (AI) applications can allow computer programming with human intelligence and streamlined recurring tasks with speech recognition, decisionmaking, language translation and visual perception. In healthcare, AI technologies has altered medical sectors with radical surgical procedures (e.g., The Davinci Robot), substance-use disorders (SUD) epidemic (e.g., Virtual Reality (VR)) and medical imaging (e.g., Magnetic Resonance Imaging (MRI)).  According to the Substance Abuse and Mental Health Services Administration, in 2017, approximately 19.7 million Americans aged 12 and older met the screening criteria for a SUD, but only about 4 million (or 20%) received treatment. According to CMS, the Substance Use–Disorder Prevention that Promotes Opioid Recovery and Treatment (SUPPORT) for Patients and Communities Act (P.L. 115-271) (SUPPORT Act) addresses, among other issues, the pressing need for substance use disorder (SUD) treatment and prevention services in healthcare. In brief, AI has conceded the, “One-size-fits-all,” hypothesized theory for providers in local, public and private international health entities managing public health programs.   

Inevitable natural disasters governed by emergency medical responders (EMRs) will embrace flexible access with shared AI health technologies for managing, “Unresponsive or unidentifiable,” individuals. Next, urgent health care needs can be addressed effectively and efficiently with knowledge of prior medical conditions, medication management and designated emergency contact(s).  Moreover, interpersonal accessibility with a shared health system can promote patient-centric medical care, reduce medical errors and modernize emergency medicine.  Patient safety is exercised with an, “Education for all,” philosophy to provide quality healthcare services with emergent and non-emergent situations. The result is aligned with the Emergency Triage, Treat and Transport (ET3) model aimed to improve quality, lower costs and reduce unnecessary hospitalizations transports.

Healthcare complexities are atypical to amalgamate and acquiesce a state-of-the-art cloud-based shared health system to eliminate health disparities and provide equitable health care services.  Today, government agencies, accreditation, health entities and community-based organizations (CBOs) have partnered with specialized vendors and trustworthy public participation to revolutionize the social determinants of health (SDOHs) barriers.  For instance, the National Committee of Quality Assurance (NCQA) has conducted surveys entreating feedback to measure health plan performances progress addressing social determinants of health (SDOHs). Secondly, the Council for Affordable Quality Healthcare (CAQH) conducted surveys to measure medical document exchanges with clinical information for prior authorization, healthcare claims, quality measures and valued-based payments. Besides, effective and efficient global collaboration with integrated AI technologies classify as an auspicious force to obliterate health disparities with one goal targeted to execute health inequities. 


Author: Tekisha King, Doctorate Candidate. Tekisha attested and sponsored the transformation to a Valued-Based Care (VBC) healthcare  model(s) expansion to improve accessible cost-effective health services exceeding quality standards. She is firmly focused on the integral delivery of interpersonal collaboration, integrated technologies, and robust business partnerships to benefit diplomatically. Tekisha manages voluminous local, state, and federal projects as a devoted respected doctorate candidate at Walden University. E-mail: [email protected]

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