Evolving Technology in Long-Term Care Integration of Data

The increasing use of telehealth, remote patient monitoring, smart devices, and artificial intelligence in healthcare, particularly in the senior population, presents challenges in integrating data to allow for effective decision-making.  Multiple stakeholders need access to all patient data, including healthcare providers for clinical decisions, insurers for coverage decisions, and potentially attorneys for claims and litigation decisions.  The basis to knowing where to find this data and ensuring a comprehensive electronic health record is monitoring government regulations and industry advancements.


Government Initiatives

In June 2023, Congress introduced an updated version of the CONNECT (Creating Opportunities Now for Necessary and Effective Technologies) for Health Act.  Originally introduced in 2016, the Act is intended to provide Medicare beneficiaries with access to virtual care.  The updated version would permanently remove all geographic restrictions on telehealth services, expand originating sites to include home and other sites, permanently allow health centers and rural clinics to provide telehealth services, allow more eligible healthcare professionals to utilize telehealth, and remove unnecessary in-person visit requirements for telemental health services.  Long-term care facilities must continue to implement best practices regarding privacy, security, and documentation for telehealth visits as these telehealth changes become permanent.

Artificial Intelligence

ChatGPT, the fastest growing consumer application in history, employs large language models which use deep learning techniques to understand and predict content.  According to a report by Accenture, it is estimated that 40% of working hours across all industries can be impacted by large language models.  In healthcare, the use of AI by practitioners has a high potential to automate and augment their workday.  Half of healthcare organizations included in this report plan to use ChatGPT for learning purposes.

Current applications of AI in healthcare include:

  • Clinical documentation
  • Imaging using AI algorithms to process images and provide suggestions to radiologists. AI can analyze medical images more quickly and accurately than human radiologists and can easily integrate with EHR systems.
  • Remote patient monitoring to track and analyze data.
  • Research and testing new drugs in simulated environments.
  • Robotics to assist with surgeries.

Experts note that ensuring AI is safe and clinically proven is a significant challenge, and while a useful tool, final decisions must be made by the medical professionals.  Some health leaders believe there should be federal oversight of AI to ensure accuracy and quality of care.  Healthcare providers also note technology is not a substitute for human touch and interaction.

Tech giants Amazon Web Services and Microsoft have developed AI-automated clinical documentation applications to capture doctor-patient discussions, create summaries, and store the information in the EHR.  A startup company, DeepScribe, developed a similar tool intended to convert doctor-patient conversations into medical records.  The Wall Street Journal  recently reviewed this application and found that the tool produces many inaccuracies in its reports, including medical terminology and medication errors.  All reports generated must be reviewed by people working for the startup, and ultimately corrected through a final review by the physician.  In addition to such concerns about quality, healthcare providers must consider legal issues when utilizing AI tools, including data security and confidentiality standards.

Smart Technologies/Remote Patient Monitoring

 Every day there are exciting AI applications in development or entering the market that are designed to assist seniors.  Pilot programs are underway to develop tools to limit fall risks, improve sleep, monitor Alzheimer’s and dementia, and provide continuous health management.  Virtual reality, in combination with an Apple watch, may be used to treat chronic conditions by using a patient’s biometric data and sending treatment protocols in real time.  Even toilets are getting smarter, with “advanced biosensor systems” that provide daily wellness information for staff to monitor via a smartphone app.

Approximately 40% of nursing home patients suffer from congestive heart failure.  Tools to remotely monitor CHF, including the ReDS Vest, a non-invasive tool that uses radar sensors to measure lung fluid and CardioMEMS, an implanted device which wirelessly measures and monitors pulmonary artery pressure and heart rate have both shown to reduce hospital readmissions in this patient population.  Monitoring these residents is labor intensive, and while these devices help, they still require specifically trained staff.

As these examples demonstrate, senior living providers and vendors are expanding the use of telehealth and artificial intelligence applications to improve operations and resident care.  Integration of AI and data collected by these smart technologies can help forecast potential health issues with residents through the electronic health record, but as one EHR vendor notes, “that isn’t something EHR reporting systems can do – yet.”

Excelas continues to monitor advancements in telemedicine, with a special interest in integration of data from AI applications and remote patient monitoring tools with the electronic medical record.  Excelas can assist your facility in a documentation review to ensure that your organization can prove the integration of data into the medical record is timely and complete.  Comprehensive and complete medical record data is critical not only to patient care, but to reimbursement, compliance, and risk management.

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