In the healthcare industry, information is at its most important level. Information on patients’ wellbeing, care history, and ancestry is pivotal in ensuring the right care is delivered at the right time. For this reason, it is estimated that a whopping 30% of the global data volume is generated by the healthcare industry. Things from diagnostics, electronic medical records, hospital admissions, and prescription refills are all viable and important data even years after they are originally captured.

However, life saving information is not the only data that hospitals work with. Documenting billing codes, medical charts, getting prior authorization, and logging progress notes are all menial tasks that serve to distract from the direct care of a patient. For this reason, around 2 in every 3 physicians are experimenting with using AI to automate and expedite these processes. However, there are extreme concerns with using generative AI or public LLM’s as this requires the information to be fed to the algorithm and leaving customers exposed as a result. This also raises regulatory concern, as this manner of data usage violated HIPAA and SOC2 regulations.

The Power of Data Warehouses

So, with the quantity of data, and the concerns expressed with traditional AI, how can we go about safely securing hospital data while also making the most of it? Data warehouses are a great happy medium that both safely secures data, and makes it accessible by both knowledge workers and AI alike. While it is possible to create your own data warehouse, this is an incredibly resource intensive approach. It costs anywhere from 12 to 36 months, based on how complex a project is and the number of setbacks. Furthermore, you must not only pay for the technology upfront, but also for the tech team that both creates and supports it over time.

Fortunately, creating your own data warehouse is not the only approach. Companies like Mega Data offer pre-built frameworks that are made to house massive quantities of data without a hassle. Because of this, the timeline from planning to implementation is as short as just 90 days. The initial 30 days are spent on a consultation and source mapping. Then, the next 30 days to customize the data warehouse to your organization and validate the data uploaded, and just 30 more days to get the system and run quality assurance. 

Moreover, they have a seasoned tech team, which is used to the technology and can rapidly implement any fixes for your warehouse. And, for large healthcare organizations, they ensure any warehouse made for the healthcare industry lives up to both HIPAA and SOC2 compliance standards.

Conclusion

Best of all, your data does not sit idly by while being secure. Data warehouses allow for in-house workflow integrations, which includes AI automations and insights. These integrations allow you to do anything from generating custom charts about your organization to aggregating time clock and payroll data to ensure your organization runs smoothly. Regardless of how large your healthcare organization is, if you want to keep your data secure while leveraging it for your company, utilizing a data warehouse is an excellent way to go.