Technology Trends that will Revolutionize the Medical Industry in 2021

Health Technology, Digital Healthcare

Article | September 7, 2023

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.

Health Technology, Digital Healthcare

Article | August 16, 2023

Electronic medical records (EMR) conferences are vital for professionals who wish to stay updated on latest healthcare innovations. Join industry experts to tackle challenges and seize opportunities. Electronic medical records (EMR) are digital versions of patients’ medical information. These can be managed, accessed, and shared by authorized healthcare providers within a single healthcare organization. Staying informed with the latest updates on EMR conferences is crucial for healthcare providers, administrators, and IT professionals responsible for implementing and maintaining these systems. Attending these conferences offers the opportunity to keep up with the latest trends and technologies, network with experts, earn continuing education credits, and enhance professional development in the rapidly-evolving healthcare landscape. Explore the EMR conference schedule and highlights for the healthcare industry, featuring the best EMR conferences for medical professionals with a focus on digital health, electronic patient records, and other notable advancements. Attend these top events to stay informed and connect with industry experts: 1.MedInfo 2023 July 8 to 12 | Sydney MedInfo, a health informatics event with the theme ‘The Future is Accessible’, will take place at the International Convention Centre (ICC). The conference aims to explore digital healthcare beyond borders and will feature 700 keynote speakers addressing over 3,000 delegates from more than 50 countries. The event will cover a diverse range of topics, with particular emphasis on nursing and digital health. 2.e-Health 2023 Conference and Tradeshow May 28 to 30 | Toronto e-Health, a premier event for Canadian digital health professionals, will be held at Beanfield Centre. Committed to making a difference in health and healthcare delivery, this annual conference & tradeshow has remained a vital epicenter of digital health discussion and debate since 2000, attracting a diverse line-up of in-demand speakers, expert panelists, presenters, and leading-edge exhibitors. Attendees can expect a wonderful platform to learn, connect, and engage with peers both nationally and globally, along with networking and knowledge-sharing opportunities. 3. Digital Healthcare World Congress 2023 May 23-24 | London Digital Health World Congress 2023, slated to take place at Kensington Conference & Event Centre, will feature discussions on various medical and mobile technologies such as e-health, m-health, telehealth, telemedicine, genomics, biotech, life sciences, healthtech, genetics, pharma, and healthcare IT. This event will be crucial for healthcare professionals looking to gain insights into the latest developments in electronic medical records. 4. 11th International Conference on Internal Medicine & Patient Care July 20-21 | Florida The conference aims to explore the latest developments and advancements in the field of internal medicine through the theme of ‘Current Research and Advances in Internal Medicine’. It will cover topics such as dermatology, cosmeceuticals, and laser treatments, with a significant scientific session on ‘Electronic Medical Record and Disease Management’. Attendees can take advantage of opportunities to present their research, learn about career development, and gain insights into the latest tools & technologies. The conference promotes collaboration among young researchers and offers a chance to interact with peers and established leaders globally. 5. openEHR Conference June 6 | Barcelona openEHR aims to bring together healthcare professionals, medical informatics experts, care providers, researchers, authorities, regulators, and service providers. The event's theme 'No time to waste: building the lifelong, patient-centric EHR,' emphasizes raising awareness about the current state of semantic interoperability in healthcare. The objective is to enable different healthcare systems and applications to share and utilize patient data seamlessly and accurately, irrespective of the technology used, to create patient-centric electronic records that can be accessed and used throughout a patient's lifetime. 6. Oracle Health Conference September 18-20 | Las Vegas Attend the Oracle Health Conference to discover how Oracle Health is revolutionizing healthcare technology. Formerly known as the Oracle Cerner Health Conference, this event features innovative product demos, education sessions on industry challenges, and networking opportunities with like-minded peers. Gain insights into how technology can improve patient outcomes, enhance clinical efficiency, and drive innovation in healthcare organizations. 7. Electronic Medical Records Boot Camp August 21-22 | Virtual The upcoming Electronic Medical Records Boot Camp invites attendees to gain valuable insights into biostatistical methods for analyzing EMR data. This intensive two-day program features seminars and hands-on analytical sessions, providing attendees with an overview of electronic health data opportunities, statistical challenges, and the latest techniques related to electronic medical records. The program aims to help attendees leverage electronic medical records for better healthcare outcomes. 8. The Healthcare Innovation Congress June 20 – 22, 2023 | Washington, DC The Healthcare Innovation Congress (thINc360), formerly known as The World Health Congress, aims to bring together executives from a wide range of healthcare sectors. Over the course of three days, the conference will offer tailored educational experiences specifically designed for executives representing healthcare professionals, health plans, and hospitals. 9. Digital Health Transformation Summit 2023 May 22-24 | Chicago This event aims to highlight how innovation is driving change across the healthcare industry, leading to gains in quality, affordability, accessibility, and sustainability. The panel of Modern Healthcare's Top 25 Innovators will discuss the latest innovative projects, products, and developments in healthcare, including the use of AI to leverage the abundance of patient data from EHRs and digital tools for improved diagnoses, treatments, and disease prevention. 10. World Medical Innovation Forum June 12-14 | Boston World Medical Innovation Forum (WMIF) is a global event that brings together leaders in healthcare investment, technology, manufacturing, and regulation at Westin Boston Seaport District. The forum, presented by Mass General Brigham and Bank of America, aims to advance patient-benefitting technologies by exploring the promise of new patient care and addressing the challenges to their development and investment. The ultimate goal is to find solutions to medical, operational, and economic challenges to benefit patients, providers, and healthcare organizations at the earliest feasible time. 11. Bits & Pretzels Healthtech June 20-21 |Munich Conference will focus on technology-driven healthcare innovation and its potential to enhance patient outcomes. The conference will explore the patient journey from prevention to aftercare, with a focus on technology's role in driving innovation. Attendees will examine how new technologies such as AI, bio 2.0, and IoT ingestible can improve healthcare delivery. 12. IHI Patient Safety Congress May 22-24 | Maryland Organized by the Institute for Healthcare Improvement (IHI), the event, which will take place at National Harbor, aims to bring individuals together who are passionate about ensuring safe and equitable care for patients in all settings, including hospitals, outpatient facilities, and homes. It will feature engaging speakers who will share their vision for smarter, safer care, and attendees will have access to practical workshops, which will provide real-world insights that can be implemented within their organizations. This event is a must-attend for anyone interested in shaping the future of patient safety. 13. Intelligent Health Conference 2023 June 14 | Pilestredet The Intelligent Health Conference 2023 is an event organized by Intelligent Health Initiative at OsloMet – Oslo Metropolitan University to provide an update on the latest developments & research in the field of digital health. The event will bring together experts & researchers in the field to discuss the use of digital technologies such as AI and wearable devices for improved health services. The conference will focus on various technologies that are becoming an integrated part of daily life, including mobile health and applications, electronic medical records, and telehealth as well as telemedicine. 14. HealthTech Innovation Days October 24-25 | Paris October 27 | Virtual The fifth edition of HealthTech Innovation Days (HTID) event, organized by the non-profit organization HealthTech Care and initiated by France Biotech, aims to facilitate faster delivery of innovative products to patients by providing a platform for European life sciences stakeholders. The HTID event provides various activities to facilitate the progress of innovation, such as the chance to engage with knowledgeable professionals, participate in panel discussions led by experts from around the world, and obtain valuable insights into critical subjects. 15. Digital Health Innovation Summit June 6-7, 2023 | California The 23rd rebranded edition of Digital Health Innovation Summit, organized by World BI, will take place at Hyatt Regency San Francisco Embarcadero Waterfront Hotel. The event aims to provide a unique opportunity for professionals in the pharma, healthcare, and medtech industries to connect with thought leaders, explore the latest trends in digital health technologies & advancements in electronic medical records, and gain valuable insights to enhance patient care. With the participation of clinicians, scientists, entrepreneurs, biomedical engineers, patient advocates, and top technology providers, this summit will serve as a crucial gathering for professionals driving innovation in healthcare. Wrapping Up Participating in electronic medical records conferences can facilitate professional development, accrue continuing education credits, and help individuals stay abreast of the rapidly-evolving healthcare landscape. EMR conferences frequently offer focused conference tracks or sessions dedicated to various EMR-related topics such as implementation, data analytics, interoperability, privacy and security, and patient engagement. Participating in these specialized tracks can provide attendees with a more targeted and comprehensive learning experience, and can contribute significantly to improving the quality of healthcare delivery, enhancing patient outcomes, and driving innovation in the healthcare industry.

Digital Healthcare

Article | November 29, 2023

Momentum in digital healthcare transformation… it’s massive, and much needed. As organizations adapt to new modes of care, demands on resources, and consumer expectations, payors and providers are eyeing opportunities to reduce costs, improve care, build awareness, and expand relationships.Here are 8 trends we’re currently tracking into 2021: TREND 1 The evolution of healthcare will be characterized by a reengineering of clinical care and operations around digital health and pervasive real-time use of data and advanced analytics.​ Gartner TREND 2 The current landscape has underscored the importance of improving workflows, achieving greater clinical efficiencies and better integrating data across organizations through tools like natural language processing, remote process automation, and cloud-based technologies. Becker’s Hospital Review TREND 3 Now more than ever, healthcare organizations must build a multi-channel digital experience portfolio to deliver personalized consumer-centric experiences that drive engagement and reduce costs. Becker’s Hospital Review TREND 4 With increasing emphasis on cross-platform (EHR, CRM, CMS, virtual health, etc.) and cross-organizational data portability, advanced APIs and interoperability should ensure secure and efficient data exchanges between EHR systems, devices, and various channels of care. Forbes TREND 5 COVID-19 has pushed telehealth into the mainstream, and adoption has gained impressive traction. Expect expansions of asynchronous virtual care leveraging integrated wearable technologies. Business Insider Intelligence / Research and Markets TREND 6 With more healthcare data available, artificial intelligence and machine learning technologies will provide greater speed and insights to analyze and predict outcomes that drive change in patient care. Gartner / Forrester TREND 7 Organizations will continue looking to Social Determinant of Health strategies to help understand health disparities – including those highlighted through COVID-19 infections – and alleviate some of the financial strains while delivering high quality care. Fierce Healthcare / Healthify TREND 8 Successfully making the transition to offering greater price transparency will not only put healthcare organizations in compliance, but help satisfy patient demand, increasing patient engagement and even point-of-service payments. Health Leaders Media The strategy imperative With so much call for transformation, it’s vital to resist the pull of “shiny object” point solutions and to, instead, build a fully-considered digital strategy. Need help getting started? Our healthcare experts help the nation’s largest providers and payers navigate and execute their north star strategy, tackling specific challenges through assessments, best-practice advice, strategy, and roadmaps. Explore our thought leadership and connect with us to learn more today.

Article | September 4, 2020

A digital twin is a digital representation of a real-world entity or system. The implementation of a digital twin is a model that mirrors a unique physical object, process, organization, person or other abstraction. For healthcare providers, digital twins provide an abstraction of the healthcare ecosystem’s component characteristics and behaviors. These are used in combination with other real-time health system (RTHS) capabilities to provide real-time monitoring, process simulation for efficiency improvements, population health and long-term, cross-functional statistical analyses. Digital twins have the potential to transform and accelerate decision making, reduce clinical risk, improve operational efficiencies and lower cost of care, resulting in better competitive advantage for HDOs. However, digital twins will only be as valuable as the quality of the data utilized to create them. The digital twin of a real-world entity is a method to create relevance for descriptive data about its modeled entity. How that digital twin is built and used can lead to better-informed care pathways and organizational decisions, but it can also lead clinicians and executives down a path of frustration if they get the source data wrong. The underlying systems that gather and process data are key to the success for digital twin creation. Get those systems right and digital twins can accelerate care delivery and operational efficiencies. Twins in Healthcare Delivery The fact is that HDOs have been using digital twins for years. Although rudimentary in function, digital representations of patients, workflow processes and hospital operations have already been applied by caregivers and administrators across the HDO. For example, a physician uses a digital medical record to develop a treatment plan for a patient. The information in the medical record (a rudimentary digital twin) along with the physician’s experience, training and education combine to provide a diagnostic or treatment plan. Any gaps in information must be compensated through additional data gathering, trial-and-error treatments, intuitive leaps informed through experience or simply guessing. The CIO’s task now is to remove as many of those gaps as possible using available technology to give the physician the greatest opportunity to return their patients to wellness in the most efficient possible manner. Today, one way to close those gaps is to create the technology-based mechanisms to collect accurate data for the various decision contexts within the HDO. These contexts are numerous and include decisioning perspectives for every functional unit within the enterprise. The more accurate the data collected on a specific topic, the higher the value of the downstream digital twin to each decision maker (see Figure 1). Figure 1: Digital Twins Are Only as Good as Their Data Source HDO CIOs and other leaders that base decisions on poor-quality digital twins increase organizational risk and potential patient care risk. Alternatively, high-quality digital twins will accelerate digital business and patient care effectiveness by providing decision makers the best information in the correct context, in the right moment and at the right place — hallmarks of the RTHS. Benefits and Uses Digital Twin Types in Healthcare Delivery Current practices for digital twins take two basic forms: discrete digital twins and composite digital twins. Discrete digital twins are the type that most people think about when approaching the topic. These digital twins are one-dimensional, created from a single set or source of data. An MRI study of a lung, for example, is used to create a digital representation of a patient that can be used by trained analytics processes to detect the subtle image variations that indicate a cancerous tumor. The model of the patient’s lung is a discrete digital twin. There are numerous other examples of discrete digital twins across healthcare delivery, each example tied to data collection technologies for specific clinical diagnostic purposes. Some of these data sources include vitals monitors, imaging technologies for specific conditions, sensors for electroencephalography (EEG) and electrocardiogram (ECG). All these technologies deliver discrete data describing one (or very few) aspects of a patient’s condition. Situational awareness is at the heart of HDO digital twins. They are the culmination of information gathered from IoT and other sources to create an informed, accurate digital model of the real-world healthcare organization. Situational awareness is the engine behind various “hospital of the future,” “digital hospital” and “smart patient room” initiatives. It is at the core of the RTHS. Digital twins, when applied through the RTHS, positively impact these organizational areas (with associated technology examples — the technologies all use one or more types of digital twins to fulfill their capability): Care delivery: Clinical communication and collaboration Next-generation nurse call Alarms and notifications Crisis/emergency management Patient engagement: Experiential wayfinding Integrated patient room Risks Digital Twin Usability Digital twin risk is tied directly to usability. Digital twin usability is another way of looking at the issue created by poor data quality or low data point counts used to create the twins. Decision making is a process that is reliant on inputs from relevant information sources combined with education, experience, risk assessment, defined requirements, criteria and opportunities to reach a plausible conclusion. There is a boundary or threshold that must be reached for each of these inputs before a person or system can derive a decision. When digital twins are used for one or many of these sources, the ability to cross these decision thresholds to create reasonable and actionable conclusions is tied to the accuracy of the twins (see Figure 2). Figure 2: Digital Twin Usability Thresholds For example, the amount of information about a patient room required to decide if the space is too hot or cold is low (due to a single temperature reading from a wall-mounted thermostat). In addition, the accuracy or quality of that data can be low (that is, a few degrees off) and still be effective for deciding to raise or lower the room temperature. To decide if the chiller on the roof of that patient wing needs to be replaced, the decision maker needs much more information. That data may represent all thermostat readings in the wing over a long period of time with some level of verification on temperature accuracy. The data may also include energy load information over the same period consumed by the associated chiller. If viewed in terms of a digital twin, the complexity level and accuracy level of the source data must pass an accuracy threshold that allows users to form accurate decisions. There are multiple thresholds for each digital twin — based on twin quality — whether that twin is a patient, a revenue cycle workflow or hospital wing. These thresholds create a limit of decision impact; the lower the twin quality the less important the available decision for the real-world entity the twin represents. Trusting Digital Twins for HDOs The concept of a limit of detail required to make certain decisions raises certain questions. First, “how does a decision maker know they have enough detail in their digital twin to take action based on what the model is describing about its real-world counterpart?” The answer lies in measurement and monitoring of specific aspects of a digital twin, whether it be a discrete twin, composite twin or organization twin. Users must understand the inputs required for decisions and where twins will provide one or more of the components of that input. They need to examine the required decision criteria in order to reach the appropriate level of expected outcome from the decision itself. These feed into the measurements that users will have to monitor for each twin. These criteria will be unique to each twin. Composite twins will have unique measurements that may be independent from the underlying discrete twin measurement. The monitoring of these key twin characteristics must be as current as the target twin’s data flow or update process. Digital twins that are updated once can have a single measurement to gauge its appropriateness for decisioning. A twin that is updated every second based on event stream data must be measured continuously. This trap is the same for all digital twins regardless of context. The difference is in the potential impact. A facilities decision that leads to cooler-than-desired temperatures in the hallways pales in comparison to a faulty clinical diagnosis that leads to unnecessary testing or negative patient outcomes. All it takes is a single instance of a digital twin used beyond its means with negative results for trust to disappear — erasing the significant investments in time and effort it took to create the twin. That is why it is imperative that twins be considered a technology product that requires constant process improvement. From the IoT edge where data is collected to the data ingestion and analytics processes that consume and mold the data to the digital twin creation routines, all must be under continuous pressure for improvement. Recommendations Include a Concise Digital Twin Vision Within the HDO Digital Transformation Strategy Digital twins are one of the foundational constructs supporting digital transformation efforts by HDO CIOs. They are digital representations of the real-world entities targeted by organizations that benefit from the advances and efficiencies technologies bring to healthcare delivery. Those technology advances and efficiencies will only be delivered successfully if the underlying data and associated digital twins have the appropriate level of precision to sustain the transformation initiatives. To ensure this attention to digital twin worthiness, it is imperative that HDO CIOs include a digital twin vision as part of their organization’s digital transformation strategy. Binding the two within the strategy will reinforce the important role digital twins play in achieving the desired outcomes with all participating stakeholders. Building new capabilities — APIs, artificial intelligence (AI) and other new technologies enable the connections and automation that the platform provides. Leveraging existing systems — Legacy systems that an HDO already owns can be adapted and connected to form part of its digital platform. Applying the platform to the industry — Digital platforms must support specific use cases, and those use cases will reflect the needs of patients, employees and other consumers. Create a Digital Twin Pilot Program Like other advanced technology ideas, a digital twin program is best started as a simple project that can act as a starting point for maturity over time. Begin this by selecting a simple model of a patient, a department or other entity tied to a specific desired business or clinical outcome. The goal is to understand the challenges your organization will face when implementing digital twins. The target for the digital twin should be discrete and easily managed. For example, a digital twin of a blood bank storage facility is a contained entity with a limited number of measurement points, such as temperature, humidity and door activity. The digital twin could be used to simulate the impact of door open time on temperature and humidity within the storage facility. The idea is to pick a project that allows your team to concentrate on data collection and twin creation processes rather than get tied up in specific details of the modeled object. Begin by analyzing the underlying source data required to compose the digital twin, with the understanding that the usability of the twins is directly correlated to its data’s quality. Understand the full data pathway from the IoT devices through to where that data is stored. Think through the data collection type needed for the twin, is discrete data or real-time data required? How much data is needed to form the twin accurately? How accurate is the data generated by the IoT devices? Create a simulation environment to exercise the digital twin through its paces against known operational variables. The twin’s value is tied to how the underlying data represents the response of the modeled entity against external input. Keep this simple to start with — concentrate on the IT mechanisms that create and execute the twin and the simulation environment. Monitor and measure the performance of the digital twin. Use the virtuous cycle to create a constant improvement process for the sample twin. Experience gained through this simple project will create many lessons learned and best practices to follow for complex digital twins that will follow.