Every avenue of the healthcare industry seems to be lapping up technological advancements; medical imaging technology and informatics are no exception. Clinical informatics solutions are applied to collect, store, analyse, and exchange information to improve the caregiving process. Healthcare informatics can also considerably lend itself toward population health management.   

Medical imaging informatics is a branch of healthcare informatics that addresses every avenue of data related to medical imaging business. Image generations, processing of medical diagnosis of images, storage management, transfer and distribution of images, translation, and security all benefit the automation of informatics in medical imaging. As mHealth spreads its wings across multiple health clinics, patients can significantly benefit from informatics in healthcare. A radiology informatics company applies clinical data analysis to provide advanced health informatics.   

As technology advances toward electronic health records, informatics in healthcare has created a drastic improvement in radiology. The ultimate goal of advanced health informatics is to apply information and data toward improving patient care and providing a better experience to healthcare entities. Custom healthcare solutions advance health informatics toward application in relevant areas, particularly medical imaging informatics.   

OSP’s Advanced Health Informatics Solution

A U.S. client was looking for higher caregiving solutions by applying technologies to advance health informatics toward data mining and management. We leveraged our health informatics services to offer the following solutions:  

  • Data extraction toward holistic translation of crucial and relevant data patterns for meaningful translations through electronic data exchange.   
  • Suggestions are made for potential findings based on these translations and patient history.  
  • Quantitative reports for efficient comparison and an increase in speed and efficiency of the medical imaging professional.   
  • The key features of medical imaging machines were combined on a digital chip for increased real-time accessibility through integrated healthcare systems.   

Challenges with Traditional Medical Imaging Processes

1. Disorganized Data

High volumes of unstructured data make the traditional medical imaging process tedious, with an urgent need for automated informatics healthcare in medical imaging.

2. Increasing Backlogs

Healthcare medical imaging accessibility is at an all-time low with the number of appointment backlogs in the current system, raising an urgent need for healthcare provider’s solutions.

3. Reduced Profits and Reimbursements

With the shift from fee-for-service to value-based payments, there is a severe drain on medical imaging revenues and reimbursement rates.

4. Exclusive Work Profile

When a medical imager is merely involved in translating the relevant image, holistic medical information is amiss. Informatics systems can offer reference points and suggestions for complete translations.

5. Rise in Competition

Traditional medical imaging systems struggle to stay relevant in a technologically advanced market that is rife with competition toward integrated care management through informatics systems.

6. Increased Patient Demands:

Satisfying today’s digitally aware customers with basic caregiving services, and patients expect a higher quality of care through informatics solution.

A Developmental Guide Toward Medical Imaging Informatics

1. Virtual Assistants

A virtual assistant is deployed by medical informatics companies with massive amounts of data and images as a reference guide and through intelligent healthcare automation. This feature uses health informatics technology for immediate clinical decision support toward diagnosis.

Advanced deployments initiate the execution of meaningful interpretation of medical diagnosis and the culling of latent information to distinguish patterns and offer suggestions and translations accordingly. Health informatics technology allows for the structuring and mining of data, allowing radiologists to use these translations and suggestions or virtual assistants toward meaningful analysis.   

2. Real-time Imaging

The traditional system where a medical imager observes and translates a scan with full and final dependency on his interpretation is a thing of the past. With the deployment of automated and advanced health systems, informatics for medical imaging technologies offers intelligent learning capabilities in medical image analysis software.   

Healthcare analytics solutions apply data mining toward identifying patterns and abnormalities that surpass the ability of human radiologists. Deep learning technologies are deployed to speed up this process and make it possible in real-time through healthcare interoperability.   

3. Image Analysis

Data mining and image analysis are the most significant features of health informatics applications. Radiologists stand to gain immense benefit through intelligent data analysis of medical images. However, medical imaging software companies must be mindful of HIPAA compliance when dealing with data.

Medical image professionals can incorporate medical imaging software toward analysing data for higher patient experiences. A medical imaging software company can incorporate image analysis solutions that offer advanced deep learning computer vision software for automated analysis. The results are far superior to traditional methods and offer a significantly higher rate of accuracy and speed through artificial intelligence medical imaging.   

4. Predictive Analysis

The predictive analysis technology can make great strides in increasing the overall efficiency of imaging equipment utilization for a diagnostic imaging company. The likelihood of errors is mitigated, and a misdiagnosis can be avoided entirely, contributing to higher patient experiences.   

Embedding predictive analysis into medical image processing software will ensure that the technology executes identical processes as human involvement but higher efficiency and speed. Embedded with advanced mechanisms, patient engagement systems directly contribute toward value-based care.    

5. Data Mining

Comprehensive research applications are deployed into the intelligent algorithms technology of medical imaging system solutions. These features aid the recognition of familiar and unfamiliar textures in medical images and offer meaningful suggestions toward its implications. Data repositories from medical records management solutions are integrated and applied for mining in medical imaging.

Patterning in medical images is more often than not missed out by radiologists and medical image examiners. This is due to the sheer incapacity of the human memory to recognize and retain information patterns. Therefore, computer-aided diagnosis adapts to the limitations of human radiologists and offers medical imaging solutions that harness the power of both.    

6. Cloud-based Platform

Through cloud computing in healthcare, medical imaging solutions allow access to data across multiple locations and systems in a secure encrypted manner. A cloud-based platform allows the integration of medical imaging diagnostics for holistic analysis from multiple health clinics.  

The traditional medical imaging business method involves physical analysis and labeling of medical images into relevant categories. A cloud-based platform offers data augmentation to image informatics in medicine that restricts the software from adopting comfortable structures and categories and forces the use of performance data that lies outside of the immediate box. This enhances the exposure of the software to offer results that are of higher probability and efficiency.   

Benefits of Medical Imaging Informatics:  

  • Intelligent imaging analytics to offer better diagnostics  
  • Cloud-based platform to transform the traditional model of medical imaging  
  • Deep learning for medical image examination and speedier diagnosis   
  • Reconstruction of regular images into 3D imaging for higher accuracy  
  • Superior level of patient imaging, eradicating the possibility of a misdiagnosis  
  • Improved overall image quality, thereby reducing non-profitable repeat scans  
  • Combined image analysis and big data analysis to create whole slide images   
  • Microscopic analysis that is infused with superior level analogies  
  • Radiologists receive automated suggestions based on past data and consequent diagnosis  
  • Summative pointers of related cases for intelligent analysis  
  • At-risk patient identification for the adoption of preventive measures  
  • Significant reduction of false-positive through minimal errors  

Conclusion

There is no doubt that imaging information systems are loaded with automation benefits for radiologists and health clinics. Keeping in tune with value-based care, these solutions are designed to automate and optimize medical imaging analysis of X-rays, ultrasounds, mammography, CT scans, and MRIs. The informatics system will serve as a reliable bridge between healthcare professionals and healthcare data to bring out the best.   

The use of healthcare data is significantly enhanced through the informatics process with a secure transmission network. Adopting medical imaging automation techniques will allow healthcare organizations to gain a significant competitive advantage toward value-based care and higher patient engagement.