The big resignation in 2021 resulted in the resignation of millions of Americans. Not surprisingly, it dealt a heavy blow to the healthcare industry.
An emotional and unprecedented pandemic has entered its third year, has triggered many resignations in all industries, and has prompted many workers to reconsider their lives and career trajectories. For the medical staff on the frontline of Covid-19 care, the price is particularly difficult. Many of them are already exhausted, which is understandable.According to the U.S. Bureau of Labor Statistics, up to 534,000 In August alone, American health care workers resigned voluntarily.
As the demand for medical staff is expected to continue to increase in the coming years, the loss of workers-especially those who decide to leave the industry altogether-poses a serious threat to already overwhelmed hospitals and other medical facilities.
There is no easy answer to the healthcare workforce crisis. However, medical institutions and their teams can use some resources to relieve some of the burdens on overworked and stressed doctors, nurses, and staff-many of which are in the form of technological advancements. These resources may change the way we provide medical services. Way. The next few years.
Many of them are about to start now. Below are five predictions of healthcare advancement, and we will see further attention in 2022.
prophecy: More innovations to eliminate burnout are underway.
Burnout has long been a serious problem for medical staff, but Covid-19 has undoubtedly made the situation worse. Actually, 79% Of radiologists, neurologists, cardiologists, and intensive care physicians say they feel exhausted today, but they actually feel similar forward Pandemic. A key cause of this stress and fatigue is the large number of administrative duties and the “data flooding” required to track and follow up patients-this long-standing problem is exacerbated by the wave of patients infected with Covid-19.
Fortunately, technological progress is reducing this burden. Using new and improved algorithms to quickly and effectively evaluate large amounts of patient data, while eliminating certain repetitive tasks, clinicians can mine the information and insights needed to effectively treat patients. Whether it is equipment, department, or enterprise-wide workflow, we are striving to use data, analysis, and artificial intelligence to provide insights first, and then use these insights to automate repetitive tasks and improve workflow efficiency. We believe that efficiency can be increased by 30% through these technologies and software. Even in overburdened emergency rooms, providers can better manage patient mobility, which allows clinicians more time to complete the tasks they have been trained for.
prophecy: Clinicians will decide which artificial intelligence tools are right for them.
Building on the previous point, advances in data analysis and artificial intelligence have allowed clinicians and support staff to use many new tools to make their tasks easier. But are they really doing this work?
As with any new advancement, the learning curve can sometimes be steep.In fact, the most recent one Report It was revealed that less than half of the AI tools that radiologists are studying can directly promote patient care, which actually leads to an increase in the number of examinations performed by radiologists in a given time. Most of the rest will not change this number (or therefore the efficiency of radiologists), but can still directly contribute to patient care.
Clinicians are eager for tools that can be seamlessly integrated into existing workflows, limiting screen time and the amount of work required to enter data. My prediction is that they will accept those AI resources that perform well—for example, deep learning image reconstruction technology embedded in MR devices that can provide high-quality resolution and shorter scan times—and ignore those that don’t. . The winning artificial intelligence technology will appear in 22 years, and its impact will be huge. When it comes to using artificial intelligence to improve the workflow of equipment, whether it is operational or clinical, those that take into account multi-modal data sets (population health information, social determinants of health, genetic information, economic status, multi-modal clinical data) Artificial intelligence models, etc.) are often more accurate and precise than models based on single-factor data (single-modal information).
prophecy: High-tech solutions will eliminate many healthcare inequalities.
A long-term problem in the United States is health inequity, because many people from disadvantaged groups or historically oppressed groups are often at greater risk of poor health. The pandemic will only worsen the problem.
For example, since people of color, American Indians, and Alaska Natives became ill, Highest Covid-19 hospitalization rate. add, fear The number of regular screenings for cancer and other diseases due to infection with the virus and loss of health insurance has dropped significantly. Therefore, it is expected that these delays or missed screening appointments will have a negative impact on early detection and diagnosis, leading to an increase in deaths or serious illnesses.
But technology is working again, and its progress is expected to achieve health equity for almost everyone by creating new ways of care. Out of necessity, telemedicine has proliferated in 2020, but it is becoming the preferred delivery method for millions of people. Remote monitoring equipment can provide the ability to check patients in rural areas or those who have difficulty finding transportation to seek medical treatment. In addition, the use of predictive analysis helps to identify high-risk patients before they get sick so that preventive measures can be taken.
prophecy: Precision medicine will significantly improve medical results.
The industry has made tremendous progress in technologies that help diagnose and prevent diseases. By 2022, genomics-the study of a person’s genes or DNA-will take center stage, because we will see the availability of tools and technologies to treat diseases and disorders based on each person’s genetic fingerprint, environment, and lifestyle .
In the process, we will replace the one-size-fits-all medical approach with precise treatment solutions that are transforming the traditional care delivery model in a way that can significantly improve patient treatment outcomes.
Secondly, the use of multi-modal data, including genetic information, imaging, digital pathology and other multi-modal information, can accurately detect the disease state at an early stage and in progress, thereby making treatment more effective and reducing costs. One of the challenges of diagnosing upstream, especially in the United States, is the current reimbursement model. The demand and effectiveness of upstream diagnosis and treatment will accelerate the value-based care paradigm in 2022.
Although healthcare providers have been facing a huge burden, whether there is a pandemic or not, hope and help are at hand. With the continuous improvement of health care technology, the mental, physical, and emotional state of millions of people dedicated to caring for others will also continue to improve.
Photo: Nuthawut Somsuk, Getty Images
