Banner by Nicole Rodriguez
Digital Twin
By Nicole Rodriguez
Sweaty palms, fidgety limbs, and racing thoughts dominate medical waiting rooms. Fear and anxiety tend to be ubiquitous amongst medical patients, as receiving medical care can be a vulnerable experience. As a patient, one must entrust their health to a physician and consent to collaborate on decisions that will affect their own physical and mental domain. There are very few contexts that require one to rely on another person in the way that medical care does. Therefore, the patient and the physician must form a special bond, termed the patient-physician relationship, which is built on trust. Within the patient-physician relationship, the patient places trust in the physician to use their medical expertise to improve the patient’s health. In turn, the physician promises to place the patient’s well-being above all other interests. Despite the faith that patients place in their physician and the oath that the physicians make to their patients— healthcare workers are human and sometimes make mistakes. A 2022 report approximated that 7.4 million patients who visit the emergency department will be misdiagnosed and 2.6 million of these patients will incur injurious outcomes as a result (7). A new development in healthcare—digital twin technology— could be the solution to these problems, however, it may have consequences for traditional patient-physician trust.
A digital twin is a highly accurate and virtual representation of a physical object. It is a virtual replication of the object, a continuous stream of data that is collected from the actual object, and complex algorithms. The algorithms integrate the data stream with the virtual replication to simulate the status of the object. Therefore, the virtual representation of the object is constantly updated to reflect the real-time state and functionality of the object. Furthermore, the algorithms within digital twin models can predict the future status of the object and how the object will respond to different manipulations. Many industries have adopted digital twins to guide and improve their operations. Within the context of healthcare, a digital twin is a dynamic virtual representation of the patient. In theory, a patient’s digital twin would be equipped with virtual replications of the patient’s organs, tissues, and microenvironment– including blood vessels and protein profile. Furthermore, a patient’s digital twin would receive data collected from the patient’s real-life health record, physical exams, diagnostic tests, wearable devices, and other streams of information. The patient data would be integrated with the virtual replication to simulate the patient’s health status in real-time. The model’s algorithms would be able to compute the patient’s anatomical and physiological performance, predict changes to this performance, and suggest interventions to improve this performance. By filtering through vast amounts of patient data to arrive at medical decisions, digital twin technology will pave the way for more precise and personalized medicine and reduce the incidence of medical mistakes in the field. In practice, physicians would be able to use digital twin technology to make more accurate medical diagnoses, identify risk factors early, implement preventative interventions, and test treatment outcomes to select the best treatment plan.
For example, cardiac resynchronization therapy (CRT) is a treatment option for patients with heart failure, however, about one-third of CRT recipients present with unchanged or worsened symptoms after the intervention (6). During CRT, a patient receives a surgically implanted pacemaker device that will administer electrical signals to the heart to correct irregular heart rhythms and improve blood circulation. Recently, a digital twin device that models an individual’s organ and cellular level response to CRT was developed to determine if a given patient would benefit from the treatment. Similarly, several digital twin models are designed to predict patient response to therapeutic drugs. These models use information about the patient’s genome to predict their biochemical response to different medications. Pharmaceutical digital twins are expected to identify the most effective medication for a given patient and facilitate the development of new therapeutic drugs. Digital twin technology is anticipated to be most helpful in managing chronic conditions, improving surgical outcomes, and in treating geriatric patients. The incorporation of digital twins within healthcare is in its early stages, but many believe that this technology is the key to personalized care and accurate medicine.
Digital twin technology has had some promising, early applications in healthcare but there is still a long way to go before this software is suitable for widespread clinical use. It is still worth exploring whether this technology should be adopted into the clinical setting after these software improvements are made. Although digital twin technology is designed to improve accuracy and reduce error within medicine, this may come at the cost of other aspects of healthcare. What consequences will this technology have for physician-patient relationships? Will the incorporation of digital twin technology bolster, erode, or completely restructure the trust that is at the foundation of this bond? One way to analyze the impact of digital twin technology on the patient-physician relationship is to consider how this software will affect patient perception of physician trustworthiness.
Research on the initiation and maintenance of trust between patients and physicians has identified crucial factors that influence the amount of trust patients have in their physicians. Some of these factors include physician demonstration of eye contact, active listening, and approachable body language. Other factors include physician o which the physician consults the patient during decision making. The presence of digital twin technology is likely to alter each aspect of patient-physician trust and eventually, re-characterize this bond.
It is likely that some factors contributing to the development of patient trust for their physician will remain immune to the presence of digital twin technology. For example, this technology is unlikely to change a physician’s body language to either become more aloof or more approachable than before. However, it is plausible to predict that some elements will decline with the incorporation of this technology. The accuracy of a digital twin is dependent on the breadth of patient data that is input into the model. As a result, physicians may become increasingly concerned with extracting and documenting as much patient information as possible during appointments. Social cues, including eye contact and active listening, may dwindle within this new data-centric orientation. Furthermore, the presence of digital twins may negatively impact patient perception of physicians’ medical knowledge. Patients will undoubtedly be informed of the use and purpose of digital twin technology if this software becomes a part of their care plan. Therefore, patients will be aware of the analytical power of this technology to predict health outcomes. Patients may come to view digital twin technology as a second expert whose medical opinion is as important, if not potentially more important, than the physicians. Patient trust may become increasingly fractionalized in cases where mechanical and human opinion do not align, leading to increased doubt toward one party.
Conversely, some elements of trust formation are likely to improve with the incorporation of digital twins in healthcare. For example, the technology may enable physicians to provide a more comprehensive explanation for disease development than previously possible. Digital twin analysis considers a massive amount of health variables to compute the onset and progression of disease. Therefore, this technology can identify numerous, specific factors to delineate disease etiology and may supply patients with a more fulfilling explanation. It is also reasonable to predict that physician efforts to investigate patient symptoms will surge under the use of this technology as focus will shift towards gathering data to feed into the digital twin algorithms. The incorporation of digital twins will encourage physicians to quantify patient symptoms and physiology with medical tests. This may subsequently offer patients a greater sense of reassurance that their physical health is being monitored using modern exams.
Although the influence of digital twin technology on some factors of trust formation is rather apparent, its influence on patient involvement during medical decision-making and physician accessibility is more difficult to predict. A patient treatment plan should be formulated from the collaboration of the physician and the patient. As the patient will be the recipient of the outcomes and the cost of the intervention, their concerns and values should be appropriately considered by the physician. However, digital twin technology utilizes massive amounts of quantitative data to produce patient treatment plans, and therefore, it has difficulty factoring in more qualitative data, such as patient opinions, into this process. Furthermore, the technology’s use of elusive, intricate algorithms may make patients feel increasingly distant from the decision-making process. Patients may have reservations about placing the direction of their health in the hands of a black box, or a device whose internal processes are mysterious and difficult to understand. Digital twin technology risks making patients feel like a case to be solved rather than a human being through its mechanization of medical decision-making. On the other hand, the reliance of digital twin technology on a consistent stream of patient data may offer patients a new avenue to remain connected to the governance of their medical plan. Real-time data can be collected through patient use of wearable devices or their completion of surveys which are then transmitted into the digital twin algorithm for analysis. Patients may feel increasingly involved in the management of their treatment as they actively contribute to the data collection that will inform the direction of this treatment. Patients will become an integral player in updating their own health plan and this will likely make the decision-making process feel more like a partnership between the patient and physician. For similar reasons as patient involvement, physician accessibility stands to benefit and suffer from this technology. If digital twin technology is adopted, physicians will have continual access to a virtual representation of the patient and will be able to always monitor changes to the patient’s health status. Digital twins will break down the traditional borders of time and space that currently separate physicians from patients. There is some comfort in knowing that a physician can monitor your real-time health status and order medical interventions if necessary. However, this may also mean that the frequency of in-person appointments may diminish. Although digital twin technology enables physicians to remotely supervise health changes and rapidly enact necessary interventions like never before, patients appear to value person to person interactions with their physicians.
As increasingly more focus is placed on the development of digital twin technology, it is important to weigh the benefits and the disadvantages that this technology can have on trust within the patient physician relationship. This technology seems promising in offering a more personalized and analytical form of medical care that can only be accomplished through advanced algorithms. However, it is also plausible that this technology may alter the traditional bond between physicians and patients and have unforeseen repercussions on trust within healthcare.