The healthcare industry generates and utilizes a significant volume of information. This information is critical for proper patient care, and much of it is stored in a digital format known as an electronic health record. These electronic health records are necessary for clinicians to understand a patient’s condition and predict what might happen later. Therefore, it is necessary to invest in EHR modernization services with healthcare data, and this can be done through the use of AIOps tools. Much like other industries, the healthcare industry too can benefit from AIOps. When integrated into the EHR, these solutions can eliminate errors and improve efficiency.

Understanding Electronic Health Records (EHR)

Electronic health records, or EHR, are collections of health information about patients and the hospital population. This information is systemized and stored digitally, and can be shared across the hospital systems when required. Currently, the EHR systems that are most common are based on the old database infrastructure. These systems have not been updated and, therefore, can lead to inaccuracies in the information. Therefore, there is a need to update these systems, and it can be easily done by using AIOps solutions.

The information stored on EHR systems is crucial for enhancing patient care. But as long as the older systems exist, this data cannot be leveraged properly. This is why there is a need for AIOps. The AI tools for digital transformation in the healthcare industry can be implemented in EHR systems. These AIOps tools can help to decode the data and analyze it to understand what is necessary for a particular patient. AIOps in EHR can improve the diagnostic algorithms through automation, and also enhance data usage, and flexibility across systems, and offer decision support.

Role of AIOps in Facilitating the Healthcare Providers to Optimize EHR

Speed and accuracy are essential in providing healthcare services. However, an analysis of the electronic health records often reveals that doctors spend more time working on EHR functions per patient. This means an increase in costs and in care delivery time for the patient. Such issues need to be addressed and resolved. The best way to do this is by implementing AIOps solutions.

When AIOps are integrated into the EHR systems, healthcare service providers and workers can optimize various processes. This will increase the efficiency of the entire hospital system. Optimization can be done in the following ways after implementing various AIOps solutions.

• Reducing the Bulk of Clinical Documentation
  Administrative work is something that every healthcare worker is burdened with and is, unfortunately, quite necessary. However, it can become difficult, and clinicians often spend hours working on documentation and administrative tasks. These tasks include data entry, billing, system security checks, and coding. These can get quite time-consuming when managed through manual processes only, which also results in errors. Automation is done through natural language processing (NLP) and helps to lessen the bulk of documentation and administrative tasks. It allows healthcare workers to have more time to focus on patient care. When AIOps is implemented on EHR systems, documentation of patient issues, diagnostics, and treatments can be automated. The data on EHR systems can be turned into actionable insights that ensure fewer delays and errors.

• Ensuring Interoperability in EHR
  There is no set standard when it comes to collection or capturing, as well as managing and transmitting patient data. This is why the collection and analysis of data from various EHR systems can become challenging. The information can even get lost, especially when being shared across different health service providers. It can also result in issues and delays, and create inaccuracies. This could affect patient care and outcomes. This is why EHR modernization with health data management platforms is necessary. To resolve this, it is essential to ensure semantic as well as syntactic interoperability. If there are problems with interoperability, they can be resolved by implementing machine learning and artificial intelligence. This ensures that all EHR functions are working and all documentation is up to date so that patient care does not get delayed.

• Quick and Accurate Clinical Decision-Making
  EHR systems deal with huge volumes of data, and this data, when analyzed correctly, can lead to accurate insights. Therefore, it is important to leverage available data through AIOps solutions. When analyzed, the insights obtained can help predict high-risk conditions and provide the necessary information on personalized care. Thus, the use of AIOps in EHR systems is instrumental in ensuring proper decision-making. Using predictive analytics, AIOps solutions can help to understand the probability of patient readmissions, mortality, deterioration, the possibility of hospital-acquired illnesses, and the risk levels among patients. To gain these health insights, AIOps solutions provide image interpretation algorithms and allow real-time analysis and actions.

• Automation of Patient Data Extraction
  For healthcare workers to provide the necessary treatment and care, patient information needs to be readily available. But when information is present across EHR systems, it can get difficult to sort through and decide which data will be useful for a specific case. This leads to delays in decision-making and inefficient patient care. AIOps-led EHR systems allow quick access and extraction of patient data. Healthcare workers can access, extract and also export the necessary data without any errors. This maintains the data structures and allows the concerned authorities to review and utilize the data.

Conclusion

The use of AI in healthcare IT solutions is not new, but the implementation of solutions across systems is something that is still not very common. However, this change is necessary. Integration of AIOps into EHR is what allows for better patient care, and also helps healthcare workers detect or accurately predict issues. This is possible through the analysis of real-time data that generates actionable insights. AIOps-led EHR systems also assist doctors and clinicians in making accurate decisions and ensuring proper diagnosis in less time. Therefore, healthcare companies need to invest in AIOps solutions because proper analysis and leveraging of data can lead to enhanced treatment plans and ensure better health in many patients.