How acute patient care artificial intelligence can assist the healthcare industry
Risk management is one of the most relevant aspects of clinical governance in healthcare. This pursuit has become even more challenging over the last several years, given the changes in the biomedical and technological ecosystem and an increasingly complex operational environment. While many of the novel developments and improvements have been technological (owing to the rapid growth and evolutive nature of digital paradigms), some of these changes have been normative.
Regardless, there is one common denominator: all are demanding increased efficiency as a matter of necessity. Also, hospitals, nursing homes, and skilled nursing and rehabilitation facilities have increasingly become the targets of lawsuits. Therefore, these facilities must not only manage risk, but they must also be prepared to defend their practices.
Hard Numbers, Hard Facts
Up to 50% of adverse patient events that occur in hospitals are preventable. Furthermore, the most prevalent threats to patient safety associated with nursing care occur in hospital inpatient units. For the purposes of this discussion, an adverse event is an unintended injury or complication that is caused by, or occurs during the course of, the delivery of clinical care, rather than coming about as a result of a patient’s underlying condition.
While language barriers and disabilities that affect communication have been shown to decrease the quality of care, myriad factors can contribute to adverse events. Cardiac and major vascular surgeries are procedures that are widely associated with high rates of postsurgical complications and hospital readmissions. Chronic diseases (such as cardiovascular disease and COPD) often lead to unplanned hospital visits requiring acute care, whether these ultimately result in an inpatient admission or not.
One key factor contributing to high postsurgical complications and readmission rates following major procedures is a deficiency in existing systems for patient monitoring in hospitals and later, at home.
In-hospital remote automated monitoring and virtual home patient care systems have demonstrably improved patient outcomes following major procedures and treatment for high-risk chronic conditions. However, deploying and reliably evaluating these systems is complex and has been subject to instances of significant implementation failure.
In recent years, the use of digital medical devices for patient home monitoring—such as blood pressure monitors, thermometers, glucometers, and fingertip pulse oximeters—has become quite common. This has given rise to the integration of these and even more sophisticated devices into the paradigm of remote patient monitoring (RPM), in which episodic data from these devices is transmitted directly to healthcare providers in facilities or hospitals. This new generation of patient home monitoring devices (many of which now interface with smartphone applications) employ acute patient care artificial intelligence and can transmit patient data to the cloud, where it can be retrieved and reviewed by healthcare providers. Remote patient monitoring can detect disease exacerbations and facilitate proactive management, reducing expensive acute and potentially risky hospital stays.
Avoiding Complications with Acute Patient Care Artificial Intelligence
While remote patient monitoring can provide significant benefits over virtual home care systems because it provides episodic patient data rather than real-time patient data, it is of limited value when dealing with high-risk chronic patients and those recovering from major procedures.
Recently, the evolution from remote patient monitoring to precisely evaluating patients’ health in real time has become a reality. The power of continuous remote patient monitoring (CRPM) lies in its ability to deliver detailed, accurate patient data via acute patient care artificial intelligence. With CRPM, wearable medical devices collect and transmit data as events occur, facilitating immediate patient supervision and responses to potential emergencies.
In this new generation of patient monitoring, software employs predictive algorithms (artificial intelligence, or AI) that can detect even minor deviations from the established patient baseline. These medical intelligence algorithms immediately recognize changes in that baseline and react accordingly, whether it’s a change in the respiratory parameters established for a patient suffering from a chronic heart ailment or a patient missing a dose of medication.
In the case of high-risk chronic patients, continuous patient monitoring offers:
- Improved patient quality of life
- Improved quality of care
- Reduced risk of medical crises
- Reduced risk of hospital stays (acute care)
Using AI’s predictive analytics to avoid medical crises, CRPM can detect nascent complications, facilitate proactive management, and reduce expensive acute hospital stays. This leads to better patient outcomes and less operational and financial stress on the healthcare system (which has significantly greater impact at scale).
For example, a patient with chronic obstructive pulmonary disease (COPD) may be comfortable resting at home but may experience physical limitations or even respiratory distress, which has the potential to escalate into a clinical emergency. In many cases, these symptoms result in a trip to the emergency room or a weekend at the hospital under observation.
Through the continuous monitoring of the COPD patient’s vital signs with acute patient care artificial intelligence, clinicians can be alerted immediately regarding the early signs of worsening symptoms and help the patient take steps to avoid a clinical emergency. This results in far less risk to the patient, as well as less expense. Factoring in scale and the numerous high-risk chronic conditions routinely addressed by clinicians, there are millions of patients who stand to derive benefits from CRPM.
Reducing Acute Care Visits—and Risk
Oxitone is a pioneering digital continuous care model with an AI-powered RPM solution that is true CRPM. It includes three patented innovations: an FDA-cleared wrist-sensor, a multi-parameter medical monitor, and a SaaS clinician’s portal powered by AI medical intelligence tools. This combination of AI’s predictive power with the convenience of wearable medical technology enables a new level of transparency and actionable insights for remote patient monitoring.
The Oxitone platform provides a clear definition of patient risk categories, speeds up care delivery, and accelerates access to care. The wide range of insights and data delivered in real time can reduce acute care use for patients with cardiovascular disease, COPD, and other high-risk chronic conditions.
With Oxitone, clinicians can access patients’ real-time, intelligent insights and follow up on hundreds of high-risk patients with just one click. Oxitone features advanced integrated SaaS, a physicians’ web portal and dashboards, secured cloud infrastructure, data analytics tools, reports, API integration tools, and data delivery on demand.
Remote patient monitoring has already been shown to improve provider access to patient information, save money, enhance patient lifestyles, and improve patient access to certain types of care. Oxitone’s powerful, full-suite solution fully addresses the needs of chronic, high-risk patients and reduces the instance of acute care visits. Its real-time delivery of data makes it a superior patient solution to traditional remote patient monitoring.
Here at Oxitone, we boost value-based healthcare by delivering extraordinary patient, clinical, and economical outcomes at reduced medical utilization and cost. Patients need a prompt response to emergencies. Physicians need an easy and timely follow-up with patients. Our mission is to transform chronic disease management and help save lives worldwide.
Let’s save lives together! To see how we help remote patient monitoring companies and physicians improve the management and care of high-risk patients, contact us today!