Healthcare facilities worldwide are facing challenges with modernization as the majority of hospitals and clinics are still running on outdated technology systems. A recent global poll has found that 75 percent of health organizations are prioritizing digital transformation and AI adoption, but they’re unable to modernize due to insufficient planning and resources. Given the current economic climate and increasing financial pressures on health systems, it’s no wonder why most respondents said that budget constraints is one of their main obstacles in digital transformation. Meanwhile, 34 percent lacked readiness to adopt and scale new technology that could potentially ease workloads and save lives.
Hospitals that run on outdated legacy systems face the risk of grave consequences, ranging from increased cybersecurity risks to regulatory non-compliance and legal liabilities. But by adopting new technology to improve processes and procedures, hospitals and treatment clinics can proactively manage risks and ensure patient safety. Here’s how adopting new technology and other innovations can streamline and secure clinical workflows in healthcare facilities.
Prevents Data Leaks and Breaches
Hospitals are a prime target of cybercriminals as their patient records contain social security numbers, medical histories, and financial information that are highly valued in the black market. According to experts, each patient record can be worth up to $1,000. What’s more, the need for 24/7 system availability makes healthcare facilities a favorite for ransomware attacks as hackers can disable or lock legacy systems and demand a ransom in exchange for restoring access to patient data and other vital processes and networks.
Integrating healthcare IT security solutions like encryption and access controls can help to prevent sensitive patient data from being stolen or manipulated, while firewalls and endpoint detection and response (EDR) stops ransomware from locking essential systems. Security software can also be used to protect patients as these can prevent Internet-connected medical devices like pacemakers and MRI machines from being hijacked by hackers.
Automates Administrative Tasks and Enhances Patient Flow
Most patients wait for hours to get admitted or discharged from a hospital. According to a study, majority of patients stay for about 4 hours in the emergency room while waiting for an inpatient bed. Meanwhile, the average discharge process can take as long as 4 to 6 hours as delays usually happen from the moment the doctor approves the discharge. A combination of high demand, resource constraints, staffing shortages, and operational inefficiences is responsible for the bottlenecks throughout the patient flow process, so healthcare institutions should consider automating systems to minimize waiting times and ensure timely and efficient care.
Automating tasks like appointment scheduling and data entry can significantly reduce administrative workloads and prevent errors, while automating digital check-ins and queueing can result in shorter waiting times. For effective resource allocation, consider using AI-driven systems to predict demand for beds and private patient rooms as this will enable staff to make the necessary adjustments. These AI tools may also help workers to prioritize those with acute needs or people who require urgent care. By automating repetitive or manual tasks, healthcare workers can focus on giving quality care while improving patient movement from admission to discharge.
Enables Proactive Care
Traditional laboratory testing methods in hospitals and clinics are thought to be slow and prone to errors since most of them involve multi-step processes that occur in different areas within the facility. Having untrained staff, instrument failure, or improper sample collecting methods may also cause inaccuracies even before the sample reaches the medical technologist. What’s more, understaffed laboratories often face a high volume of tests, increasing the likelihood of errors and turnaround time.
Using AI-powered diagnostics can help streamline laboratory processes since artificial intelligence can handle large volumes of data results and provide accurate findings at a shorter amount of time. It also improves accuracy and detection since AI can easily identify abnormalities or diseases in blood samples. One example of an AI-assisted application that’s being used in diagnostic decision making is Paige AI, and it uses algorithms to analyze tissue samples to detect breast cancer or prostate cancer cells. Other AI applications may help patients to save money on laboratory costs since these will recommend only the necessary or relevant tests. AI tools like Labcorp’s Test Finder has been beneficial for medical technicians as it can select the appropriate tests based on symptoms, reducing the need for unecessary, painful, or costly testing.
Modernizing hospital infrastructure can enhance clinical efficiency and patient safety. By improving cybersecurity and transitioning to automated processes, healthcare facilities can protect their reputation, prevent revenue loss, and deliver excellent care to all patients.
