Across industries, there is a shift from traditional systems to cloud-native systems. Such digital transformation is being favored by companies that deal with data and need to protect and process that data. When it comes to digital transformation in healthcare IT consulting, cloud adoption plays a major role. However, cloud adoption also needs to be enhanced, and that is possible through AIOps.

Importance of Cloud Adoption in Healthcare

Data that is related to healthcare services is crucial. It is critical for accurate treatment plans and for predicting patient conditions. However, to be able to use this data, it is important to store it properly, so that it can be easily accessed and processed. This is what cloud adoption ensures. When healthcare service providers adopt cloud computing and start using cloud-native architectures, instead of on-premises databases, it becomes easier to store expanding volumes of data. This also keeps sensitive information secure and makes it accessible to those who have the need for it.

Cloud adoption is vital for protecting and managing patient records. This information will keep increasing and if it is not stored on remote servers that are secure, systems can get affected and compromised. To avoid such issues, it is best to adopt cloud technologies.

Following are certain ways in which cloud adoption can benefit the healthcare industry.

• Reduction in Healthcare Data Storage Costs
  It is expensive to maintain on-premises IT infrastructures. Hospitals and healthcare service providers would have to pay upfront and purchase hard drives to store large volumes of data. This volume would keep expanding, and that would lead to an increase in costs. However, cloud adoption ensures low costs. This is because cloud solutions include storage and maintenance of data, along with administration and construction services. Therefore, the healthcare service providers do not need to pay separately for these, thus decreasing the overall cost of storing data.

• Possibility of Big Data Applications
  There was always enough information available through past medical cases, research, and healthcare records that could have predicted certain worldwide medical conditions. But most of this data is stored in on-premises and traditional databases which are almost inaccessible. Cloud adoption helps to overcome such barriers. Through big data and predictive analytics in healthcare, it is possible to quickly access data on cloud storage systems, analyze it, and make accurate decisions. The implementation of algorithms and the use of big data applications will allow healthcare workers to provide prompt responses to specific conditions and resolve issues without error.

• Better Chance for Medical Research
  Any kind of research requires a thorough analysis of previous and current data. If this data can be found in one place or is easily accessible, then it allows research to happen at a greater speed. This is why medical research can benefit from cloud adoption. Cloud adoption or the digitization of healthcare data, when stored in cloud-native systems, increases accessibility. Medical researchers can not only access huge volumes of information that can aid their area of research, but also make use of computing solutions that were not previously accessible.

• Increased Flexibility and Scalability
  There is a cost involved in frequent scaling and upgrading, especially when dealing with traditional storage systems. Cloud data storage solutions are flexible and easily scalable and thus reduce management costs. The increase in scalability ensures low costs for both the hospital and the patients. Flexibility in healthcare systems is available in the form of pay-as-you-go storage facilities. Healthcare service providers can utilize such cloud-native architectures to store data and increase the available space, only when they need it. Thus, cloud systems are flexible, expandable, and fully scalable.

While cloud adoption is necessary for the healthcare industry, there is also a need to enhance the same. This is possible through cloud enablement in healthcare AI services. AIOps-led cloud systems can be automated, upgraded, and ensure quick optimization.

Accelerating Cloud Adoption in Healthcare with AIOps

Cloud-native systems are useful but can also be complex. When healthcare companies first make the shift from on-premises databases to cloud-based architectures, it can be difficult to deal with the changes and the new solutions. This is why it is important to utilize AIOps. AIOps, through tools like machine learning and automation, can simplify cloud applications. AIOps solutions can also reduce error and increase efficiency.

The integration of AIOps in healthcare systems can enhance cloud adoption. This is possible through the following ways.

• Increased Efficiency in Healthcare Record-Keeping
  Implementation of AI for healthcare cloud enablement services enhances the electronic record-keeping of data. While cloud computing is usually focused on improving the quality of healthcare services through safer and more efficient solutions, it is also important to ensure the same for digital healthcare records. AIOps-led solutions ensure that these records are up-to-date and accurate. AIOps tools can also be used for analyzing the records. For example, predictive analytics can help to determine future medical conditions and risks, through the efficient analysis of existing and historical records.

• Enhance Patient Safety
  Patient safety is crucial and if information about a patient’s movements and interactions are available, then this safety can be ensured. To do this, it is important to implement AIOps tools and adopt cloud technologies for storing electronic health records. These records can be then analyzed with ease to predict the patient’s conditions. Analysis can also help to understand if there is a risk of over-prescribing of medications, or if the patient has already undergone a specific line of treatment, thus ensuring that the patient is not stressed or burdened with unnecessary drugs.

• Enable Data Interoperability through Cloud Computing
  Data can be available across systems and be stored in multiple databases. This means that there has to be a method of accessing different systems and obtaining that data with ease. Such interoperability is not always seen in the healthcare industry and this can lead to inaccuracies and inefficiency in inpatient care. However, through AIOps solutions in cloud computing, better interoperability is possible. When AIOps is used for cloud adoption, a single and accessible platform for data storage and maintenance can be created. So, AI in healthcare IT solutions can ensure data interoperability.

Conclusion

AIOps in cloud adoption help with collaborative approaches in treatment and patient care within the healthcare system and improve cybersecurity and risk management services in healthcare. The scope for AIOps is, therefore, constantly expanding. The implementation of AIOps solutions when opting for cloud adoption can benefit the entire healthcare industry.