Patient’s requirements and expectations about healthcare organizations are ever-changing. They want to be informed, connected, and engaged within the healthcare system to understand and explore their treatment process. Smart healthcare technology is on the path of transforming the relationship between healthcare providers, patients and the health system.
Implementing smart AI solutions in healthcare understands the industry and integrates smart solutions in healthcare practices seamlessly. Smart healthcare has the potential to transform the healthcare industry in a sustainable way making treatments less stressful and more enjoyable. They empower clinicians with more expertise and time to spend on patients with personalized and less invasive care. New technologies will enhance the evolution of a patient’s journey challenging the current status quo.
In the previous blog, we discussed what is smart healthcare, the key technologies and few applications of smart healthcare. Here, we continue to explore the applications of smart healthcare.
Medical imaging is a procedure that can create images on parts of the human body to diagnose and provide treatment within digital health. The types of medical imaging include radiological imaging techniques such as X-ray radiography, Ultrasound, Endoscopy, Fluoroscopy, Magnetic resonance imaging (MRI), Tactile imaging, Thermography, Medical photography etc… Additionally, it includes recording and measurement techniques that produce data often represented as graphs or maps. Medical imaging assists physicians to make accurate diagnoses and treatment decisions. Advanced medical imaging helps in diagnosis and treatment to achieve any level of accuracy. Diagnostic medical imaging uses ‘invisible’ waves such as magnetic fields, electromagnetic radiation, or sound waves. These waves primarily start from a source located on one side of the body, travel through the region of interest, and hit a detector that is located on the other side of the body to create an image. Medical Imaging is used for spot diagnosis, monitoring disease progression, treatment planning, evaluating the efficacy of treatment, and age-related calculations.
Insurance Fraud Detection
Software applications assist the health providers with more control over their claims. They allow providers to find assets, people, businesses, and their affiliations if it is needed during an investigation. This allows us to connect between incidents and activities so individuals can be immediately identified where the fraud can be detected and prevented. Healthcare providers can also help in fighting fraud biometrics, predictive models, blockchain, artificial intelligence and microchips. By implementing insurance fraud detection technology, we can determine fraudulent claims, track inventory, identify specific patients, and notify clinicians if there are any suspicious medication requests. Technology can be considered as one of the greatest strengths of the healthcare industry. But some instances makes us to have a fail-safe if a system goes down.
Smart Health Record Analysis
Capturing clinical data with natural language processing (NLP) help clinicians to concentrate on their patients rather than the technology. AI tools integrate with commercial EHRs and support data collection and composition.
Clinical Decision Support recommends strategies for treatments that were generic and rule-based in the past. Machine-learning solutions explores new data and enable for a more personalized care. Artificial Intelligence is applied in EHR systems specifically to improve data discovery and extraction with personalized treatment recommendations. It makes EHRs more user friendly. EHRs helps clinicians largely with their process. AI and machine learning help EHRs adapt to user’s preferences and improve the outcomes and quality of life. Every patient is unique with their own attributes. The patient data gathered can be both active and passive data which are then continuously integrated and upgraded with the e-medicinal records. The patient data are available in real-time to avoid any possible friction in availing treatment. The record insights will help in predicting and diagnosing the patient’s condition and plan the prescription accordingly. The updated information will be shared across all the departments from the nurse practitioner to case managers. Thus, it reduces friction and improves the patient experience entirely.
Artificial Intelligence is a concept that’s been witnessing exponential growth in a short period. It can transform the healthcare industry even further with the power of AI. What we once considered an unexplored path of automating the healthcare system with AI is now completely adopted in healthcare services. Their applications in healthcare are an infinite list where the health of a patient can be monitored with very minimum effort. A wide range of automated AI tools has sprouted into the healthcare systems and applications for personalized and assisted treatment management.