The challenges and uses of AI and Machine Learning in Healthcare

Healthtech Security

Article | November 29, 2023

Embark on a journey into the frontier of healthcare innovation in this article. Discover how EHR telemedicine and remote patient monitoring serve as catalysts, driving forward a new era in healthcare. Contents 1. Integration of EHRs in Telemedicine and Remote Patient Monitoring 2. Technical Challenges and Solutions in EHR Integration 3. Financial Analysis: Cost-Benefit Assessment of Integration 4. Data Privacy and Consent in Integrated EHR-Telemedicine Systems 5. Forging Stronger Patient-Clinician Relationships 1. Integration of EHRs in Telemedicine and Remote Patient Monitoring EHR telemedicine and remote patient monitoring have reshaped healthcare delivery by seamlessly integrating electronic health records, allowing healthcare providers and patients to exchange information effortlessly, regardless of geographical barriers. This synergy empowers healthcare professionals to access patients' comprehensive medical histories in real time, facilitating more informed decision-making during virtual consultations. During the spring of 2020, when pandemic restrictions kept most people in the US at home, the use of telehealth rose to about 51%. [Source: Elation Health] Moreover, it enhances the accuracy of remote patient monitoring by providing up-to-date data, enabling timely interventions and improving overall healthcare outcomes. Integrating EHR telemedicine systems enhances efficiency and ensures that patient care remains at the forefront of modern healthcare, transcending traditional physical boundaries. 2. Technical Challenges and Solutions in EHR Integration Navigating telehealth EHR integration and remote patient monitoring solutions uncovers a range of technical challenges, each with its own set of potential remedies. These include interoperability issues, which can be mitigated by adopting standardized data formats like HL7 FHIR. EHR interoperability solutions may involve using data exchange protocols such as HL7's Consolidated Clinical Document Architecture (C-CDA) or developing custom APIs to facilitate seamless data exchange between EHRs and telemedicine platforms. Additionally, the imperative need for data security and privacy is achieved through robust encryption and adherence to regulations like HIPAA or GDPR. Data integration challenges arising from varying EHR data storage methods can be resolved using middleware or integration platforms. Investing in telecom infrastructure and developing offline-capable telemedicine apps can address limited connectivity in remote areas. Ensuring real-time data access involves optimizing EHR databases and creating low-latency systems. Other challenges encompass integrating data from medical devices, ensuring data accuracy, scalability, user-friendly interfaces, regulatory compliance, and cost management strategies. 3. Financial Analysis: Cost-Benefit Assessment of Integration When contemplating the integration of EHR telemedicine and remote patient monitoring systems, conducting a comprehensive cost-benefit analysis is crucial. This assessment covers financial aspects, including initial implementation costs (software development, hardware upgrades, training, and data migration), ongoing operational expenses (maintenance and data storage), and potential efficiency gains (streamlined workflows and improved data accessibility). It also evaluates the impact on patient outcomes, satisfaction, and financial benefits of enhanced healthcare quality, reduced readmissions, and increased patient engagement. Healthcare organizations can estimate cost savings in remote patient monitoring and explore expanding telemedicine services to underserved populations to make informed financial decisions. Additionally, this analysis considers long-term financial viability and alignment with organizational goals, including regulatory compliance costs, risk assessment, scalability considerations, and the competitive advantages of integrated telemedicine services. By calculating ROI and assessing potential risks, healthcare entities can develop risk mitigation strategies, ensuring that EHR integration in telemedicine and remote patient monitoring enhances healthcare delivery and aligns with the organization's financial sustainability and long-term success. 4. Data Privacy and Consent in Integrated EHR-Telemedicine Systems Data privacy and obtaining informed consent are paramount in integrated EHR and telemedicine systems. Patients should provide explicit consent, understanding the data collected and its intended use, with strict encryption protocols safeguarding data during transmission. Access controls and data minimization practices restrict unauthorized access, while patient portals enable individuals to manage their data-sharing preferences and revoke consent if needed. Compliance with regulations such as HIPAA or GDPR is crucial, as is maintaining comprehensive audit trails to track data access. Training, awareness, and robust incident response plans fortify data privacy efforts, fostering trust and transparency in these integrated systems where healthcare organizations and patients share responsibility for secure data handling. 5. Forging Stronger Patient-Clinician Relationships Integrating EHR telemedicine and remote monitoring systems goes beyond mere efficiency and accessibility objectives. It serves as a catalyst for nurturing more substantial and meaningful patient-clinician relationships. This fusion of technology and healthcare has the capacity to bridge physical distances, allowing clinicians to truly understand and engage with their patients on a deeper level. Patients, armed with increased access to their health data, become more active participants in their healthcare, while clinicians, with their comprehensive information, can offer more personalized and informed guidance. The potential of EHR telemedicine reaches far beyond the digital screen; it empowers both patients and clinicians to collaborate in pursuit of improved health outcomes, ushering in a new era of patient-centric care grounded in trust, communication, and shared knowledge.

Health Technology, Digital Healthcare

Article | July 14, 2023

© 2019 American Cranes & Transport Magazine. Night moves Moving over-sized, over-dimensional loads during the day is no easy task. Adding darkness and poor visibility to your trip adds numerous hazards that must be thoroughly identified and mitigated. When planning a specialized transportation project, there are three primary objectives: Ensure the safety of the transport crew and the general public. Protect the integrity of the cargo and transport equipment. Protection of Infrastructure – roads, bridges, traffic control devices, utilities and the like. For the most part, specialized carriers perform night transports to reduce the impact on day-time commuter traffic. Route challenges – construction, road closures, lane crossovers, bridges and other obstacles – are often better solved at night. Police and utility support are often more readily available at night. Night transport hazards include employee fatigue, slowed reaction time and poor visibility for both the transport crew and motorists. Decreased visibility increases potential for trips, falls, runovers, back overs and equipment strikes. It can’t be emphasized enough how critically important it is to ensure that all transport crew members have had adequate rest for these projects. Workers need complete rest before the transport takes place. A fatigued worker is a danger to himself as well as his fellow crew members. And while impaired drivers can be out on the streets during the day, there is often an increased number of these drivers on roadways at night. Limited visibility is a given when it comes to night-time transports. Limited visibility increases the chance of going off route and striking objects, and the transport driver’s maneuverability and reaction time maybe be reduced. Road conditions can abruptly change during a night-time transport. Therefore, it is critically important to know the route and to have drivers run it in advance. Statistically speaking, accident frequency increases when the transporter goes off route and attempts to correct itself. While providing the necessary lighting to make night transport is important, artificial lighting can pose visibility hazards, especially to the drivers. Other hazards may include bright work lighting that produces glare. OSHA has identified the “Focus Four” accident events that make up the most serious injuries and fatalities in the construction business. They are also known as the “Fatal Four.” Many carriers have had employees injured in the past as a result of one of these four incidents. Caught-in-between hazards are injuries resulting from a person being squeezed, caught, crushed, pinched or compressed between two or more objects or between parts of an object. This is also referred to as “pinch points or entrapment.” As the transporter navigates its designated route the landscape is continuously changing. It is imperative that all ground crew members maintain situational awareness and not place themselves between the moving transporter and fixed objects such as guardrails, parked vehicles, buildings, etc. Struck-by hazards are injuries produced by forcible contact or impact between the injured person and an object or piece of equipment. There are many potential struck-by hazards. Guide wires that must be raised can snap and strike workers on the ground. Tag lines should be used to control loads. The primary purpose of using tag lines is to control the load but more importantly give the worker a safe buffer distance away from suspended and the uncontrolled movement of these loads. Fall hazards are anything that could cause an unintended loss of balance or bodily support and result in a fall. To prevent fall hazards all workers should have either fall prevention or a means of fall protection in place. As a rule, 100 percent tie off is required when using a fall arrest system (FAS). FAS’s should be thoroughly inspected before each use. Electrocution hazards result when a person is exposed to a lethal amount of electrical energy. Maintaining minimum approach distances (MAD) is a critical safety practice. As everyone knows, equipment does not have to physically make contact with energized equipment or lines to cause serious injuries and even death. Electrical energy can “jump” from lines into equipment that has encroached the Minimum Approach Distance based on its voltage. As noted above, it is critically important to ensure that crew members have had adequate rest and are not fatigued. Night transports are difficult enough, and the last thing you want to introduce are tired and fatigued workers. Being fatigued creates a risk for anyone who undertakes an activity that requires concentration and a quick response. All companies should have an “Hours Worked Policy” that clearly spells out the number of hours allowed to work before a mandatory rest period. This policy should ensure that the transport crew has had adequate rest during day, that a fatigue assessment is conducted on all team members, that crews are never allowed to work double shifts and that employees are prohibited from driving long distances to return home. Dealing with darkness Visibility and slowed reaction times should be a part of the project planning. A limited amount of ambient light that only projects upward and outward impedes vision and increases blind spots for drivers. Lights cast shadows, increasing the potential for slips, trips and falls. All transport moves should establish pre-planned Emergency Action Plans. When an emergency occurs, time is of the essence and can mean the difference between life and death. If it is a long-distance move the emergency numbers and first responder information can change. Crews should know when it’s time to seek emergency “safe harbor.” When approaching overhead obstructions such as guide wires, electrical lines, communication lines and overpasses, travel speed is of utmost importance. Again, pre-route surveys provide advance knowledge of obstructions. At night, visual identification of roadway obstructions is reduced and delayed and last second reactions to oncoming hazards can lead to accidents. Support personnel in bucket trucks also have the challenge of reduced visibility. In darkness, overhead hazards often require more utility support for height clearances, which means the need for raising energized lines, lifting traffic control devices, trimming tree limbs, releasing tension on guide wires, removing highway signs, repositioning street lights and raising railroad crossing arms. Traffic control can also create hazards. The general public may ignore pilot car lights at night, so it’s often advisable to also use police escorts. All support vehicles and trucks should be properly marked and equipped with strobe lights. The configuration of the transport system can also be a hazard. Navigating sharp turns or crossovers is greatly reduced based on the length of transporter. Snake-like maneuvers of trailers pose an increased risk. It’s important to never allow personnel to take shortcuts by walking through or under transporter while it’s in motion. Stop or have the worker go around. Situational awareness The transport crew must always maintain “situational awareness” to prevent being in line of fire or entrapped between moving and fixed objects. All the equipment used in the transport must be deemed safe. You should have procedures to conduct thorough assessment of all new equipment. Ensure machine guard devices are in place especially around moving components. Provide secured areas using catwalks/railing system. All steps should be designed with slip resistant material. Ensure that all deck openings are properly protected and covered. Components that hydraulically extend and retract should be clearly posted with DANGER signs. Roadway conditions are always a bigger concern at night. Assess weather conditions prior to start of the project and don’t take chances. A “Go – No Go” criteria should be developed for each project. Once the decision is made to transport the load there is no turning back. Changing weather can cause the transporter to lose traction. Underpasses that are shaded during the day will likely freeze up more quickly. If the temperatures drop significantly during the move, equipment performance may be affected – especially those with hydraulics. Because the reaction time of the transport crew is reduced, speeds are often reduced, causing potential for curfew violations. Boarding and deboarding the transporter increases risk for slips and falls. Other potential road condition hazards include grade of road, width of road, shoulder surfaces, railroad crossing clearances and bottoming out, overpasses, tight and narrow turning lanes, parked vehicles and frequent grade changes. Crew prep is essential and should be a part of the job plan and job training. The team should be briefed each day to identify the responsibilities of all crew members. The crew should know it is empowered; everyone has the authority to stop the transport if something looks unsafe or when someone is unsure. In the event of a complication, crews should be informed of how to regroup and formulata mitigation plan. There should be an established means of communication that is limited only to transport issues. Most importantly, crew should embrace these words: When in doubt, call time out! A Task Hazard Analysis (THA) should address all scope of work activities, identify hazards and have a mitigation plan for each, clear channels of communication, the traffic control plan and an “Emergency Preparedness Plan.” And finally: Know the route; ride the route and expect the unexpected. Edwards-Moving_Faktor-5 (2).jpg Edwards Moving performs a night move using it’s Goldhofer Faktor-5 transport system. Keys to a successful night transport Early planning and attention to detail. Anticipate roadway hazards such as guardrails, poles & hydrants that pose obstruction with travel path or turning radius. Preparing a detailed traffic control plan. Thorough due diligence throughout scope of work. Established contingency plan for equipment.

Health Technology, Digital Healthcare

Article | August 21, 2023

Healthcare is top of mind as the coronavirus hits hard everywhere. The inefficiencies of the system itself are on full display during the pandemic — where testing is hard to come by, diagnoses and treatments are reactive rather than proactive, and many people do not get the care they need, when they need it. Adrian Aoun, CEO and founder of Forward, a tech-driven healthcare startup, told Karen Webster that it’s possible to build a completely new healthcare ecosystem, beginning with primary care — and the overhaul needs to leverage data and artificial intelligence (AI).

Article | December 15, 2020

As medical science has improved rapidly, life expectancy around the world also has risen. Still, as longevity increases, healthcare systems are facing a growing demand for advanced services, increased costs, and a struggling workforce to meet various requirements of patients. Demand is driven by many unstoppable forces: a shift in lifestyle choices, shifting patient expectations, population aging, and the never-ending cycle of innovation are a few among others. Challenges Faced by the Healthcare Industry According to Mckinsey, one in four people in North America and Europe will be over the age of 65 by 2050. This shows that, soon, the healthcare industry will have to deal with a larger number of patients with more complex requirements. Catering to these patients is expensive and requires health systems for providing long-term focused and proactive care. To remain sustainable, healthcare systems need major transformational and structural changes. The industry also needs a larger workforce because according to the World Health Organization (WHO), globally there is a shortfall of approximately 9.9 million nurses, physicians, and midwives. Apart from attracting, training, and retaining these healthcare professionals, you also have to ensure that their time and effort add value to patient care. Utilizing the solutions powered by modern technologies, such as Artificial Intelligence (AI) in the healthcare industry, will add perfection and more value to human efforts. AI in the healthcare industry has the potential required to transform and revolutionize healthcare by addressing the challenges in the industry mentioned earlier. AI can better the outcomes, improve efficiency, and augment productivity in healthcare delivery. This article takes an in-depth look at the impact of AI in healthcare. Impact of AI in the Healthcare Industry In the coming years, AI in the healthcare industry will improve the day-to-day life of healthcare practitioners, augment the patient experience, improve care delivery, and can even facilitate life-saving treatments and revolutionize the industry. Additionally, AI will improve population-health management, operations, and strengthen innovations. According to Statista, the global AI healthcare market will increase to more than US$28 billion by 2025. Here is a detailed look into the areas where and how AI in the healthcare industry will be impactful. Chronic Care Management Chronic diseases, such as cancer, diabetes, kidney diseases, are the leading cause of disability and death in the US and the main drivers of the country’s annual health cost. Effectively managing various chronic diseases is an overarching and long-term process. But with the help of the right tool, healthcare providers can meet the needs of these patients without delay. Artificial intelligence tools in the healthcare industry can help healthcare providers overcome the complexities of chronic disease management and make it more effective and provide quality treatment. AI in the healthcare industry is increasingly being leveraged by organizations to improve chronic disease management, enhance patient health, and drive down costs, which will also eventually result in data-driven and personalized care. AI in the healthcare industry is expected to move the industry toward proactive care delivery from a reactive one and lead the industry to provide more individualized treatments. This is just one of the ways AI in the medical industry is going to revolutionize chronic care management in hospitals. Care Delivery Artificial intelligence in the healthcare industry is changing the way care is delivered; it is expected to make healthcare more efficient, accurate, and accessible. Reducing costs and improving health outcomes are the values health systems and hospitals are trying to deliver to patients every day. Hospitals are increasingly incorporating technologies, which are powered by the use of AI in healthcare to meet the challenge. According to the American Hospital Association (AHA), AI in the healthcare industry has unlimited potential to solve most of the vexing challenges in the industry. They identify AI use cases in the healthcare industry in four broad areas, which are administrative, operational, financial, and clinical areas. Administrative Use Cases for AI in the Healthcare Industry • Admission procedures • Appointment scheduling • Customer service responses • Discharge instructions • Hiring and orientation protocols • Licensure verification • Patient check-in procedure • Prior authorizations • Quality measure reporting Operational Use Cases of AI in the Healthcare Industry • Inventory management • Materials management • Supply chain management • Facilities management Financial Use Cases for AI in the Healthcare Industry • Billing and collections • Claims management • Insurance eligibility verification • Revenue cycle management Clinical Use Cases of AI in the Healthcare Industry • Predictive technologies • Interventional technologies By incorporating and utilizing these scopes with AI in the healthcare industry, the industry can be transformed into a next-gen level in no time. It also allows healthcare practitioners to focus more on patients, which would eventually help in raising staff morale and improving retention. Clinical Decision Support Recent advancements in AI in the health industry are capable of enhancing the currently used clinical decision support (CDS) tools to have value-based imaging and to improve patient safety. According to the National Institute of Health (NIH), the synergy between CDS systems and AI in the healthcare industry will be able to: • Reduce friction in radiology workflows • Identify relevant imaging features easily • Generate structured data to develop machine learning algorithms • Enable an evolution toward decision support for a holistic patient perspective • Suggest imaging examinations in complex clinical scenarios • Assist in identifying appropriate imaging opportunities • Suggest appropriate individualized screening • Aid health practitioners to ensure continuity of care AI in the healthcare industry is competent in making CDS a next-gen one, enhancing the experiences of radiologists and providers, and improving patient care. Diagnostics Slowly but surely, AI is improving almost every aspect of human life with innovations and advancements. The latest is that AI in the healthcare industry is impending a revolution in medical diagnostics by providing accurate risk assessments, accelerating disease detection, and boosting hospital productivity. By automatically prioritizing urgent cases and accelerating reading time, image recognition AI enhances the workflow of radiologists. It even helps in the prevention of diseases by the early detection of diseases. In medical images such as x-rays, MRIs, and CT scans, AI-driven software can efficiently be used to accurately spot signs of many diseases, especially in detecting many chronic diseases such as cancer. According to the NIH, AI will be widely applied in the healthcare industry especially for various tasks such as patient engagement and adherence, diagnosis, and treatment recommendations. So, there is no doubt that AI in healthcare will revolutionize the diagnostic process in the approaching years by detecting diseases, classifying diseases, and improving the decision-making process. The application of AI in the healthcare industry will make people live longer. Triage and Diagnosis AI can be effectively used to automatically triage cases. AI algorithms will analyze the cases and forward cases to pathologists after determining the priority based on the probability of cases according to the criteria set by labs. This makes the workflow of pathologists easier and efficient. Through the process the algorithm will be able to: • Verify the digital images attached to the case belong to that case • Validate the tests ordered and match the specimen type • Identify cases marked as stat • Determine the cases, which can be positive or are most likely to be negative Moreover, AI technologies in the healthcare industry also can be effectively used to provide more accurate and faster diagnoses. This speeds up the entire process of triage and diagnosis and is expected to revolutionize the healthcare industry soon. The Future Outlook for AI in the Healthcare Industry Over the next few years, AI in the healthcare industry has the best opportunities in hybrid models to support clinicians in diagnosis, identifying risk factors, and in treatment planning. This scope will result in faster adoption of AI technology in healthcare, which will show measurable improvements in operational efficiency and patient outcomes. With a plethora of issues to overcome, which are driven by documented factors such as growing rates of chronic diseases and the aging population, it is obvious that the healthcare industry needs new innovative solutions. AI-powered solutions in the healthcare industry will achieve a clear impact on the global healthcare industry in a short time. Frequently Asked Questions Which is the best application of AI in the healthcare sector? Cognitive surgical robotics is the best application of AI in the healthcare sector as it helps practitioners collect data from real surgical processes, which would help in improving existing surgical approaches. Why is artificial intelligence important in healthcare? Artificial intelligence in healthcare is vital as it can help make decisions, analyze and manage data, and have conversations. So, AI will drastically change the everyday practices and roles of clinicians. When was AI-first used in healthcare? The term, Artificial intelligence (AI) was first described in 1950, but the limitations of the term prevented its acceptance. In the 2000s, these limitations were overcome and people started to accept the term.