On a path to smart hospital: make your regulatory audits a breeze
Why the healthcare sector keeps struggling with data accuracy
According to the recent O’Reilly report, the majority of organizations are still dealing with data quality concerns due to the lack of resources to build up data governance frameworks. With healthcare being a highly regulated industry, the situation is aggravated by the need to promptly share medical operational data with supervisory institutions on demand. So why is preserving the accuracy of regulatory data still so difficult to achieve?
First, the federal reporting requirements from CMS, AHRQ, and the Joint Commission continue to shift and increase in complexity. A recent report on data quality management in 2019 identified the growing market demand for quality management solutions with a wide range of functionality to keep up with changing regulations:
“Organizations who are looking for this type of information explain that the regulations are often just a gauge of the bare minimum they should be doing. To pursue true excellence in quality, they need tools that give them detailed insights into things like patient readmissions, treatment costs, and staff efficiency.” KLAS Report, 2019
Then there is the abundance of scattered multi-format data, as healthcare data historically tends to be stored in multiple places — from different source systems, like EMRs or HR software, to different departments within hospitals. Healthcare data also occurs in different formats: radiology uses images, old medical records exist in paper format, and today’s EMRs can hold hundreds of rows of textual and numerical data. Aggregating this data into a single, central system, will make this data accessible and actionable.
However, this kind of system is still very scarce. This is mainly due to the financial and operational overheads for deploying and managing a completely new technology stack for data management. And the consequences of data mishandling are piling up — from inventory build-ups and shortages of materials during manufacturing or packaging to draining the resources and missing medical records while external audits.
Here’s how to start collecting quality healthcare data with more confidence
To reduce these multiple overheads and manage human and tangible assets more efficiently, both healthcare vendors and providers need data management systems to preserve the accuracy of regulatory (for external audits) and planning data (to drive cost-efficiency and production optimization). With access to data from this environment, stakeholders can proactively improve the internal logistics of their assets such as the medical supplies and pharmaceuticals, as well as gain greater control over the human assets. These actionable insights will ultimately optimize the utilization of existing resources and create more revenue opportunities.
As data supply chains in healthcare are still often unpredictable, we suggest the following blueprint for accelerating the path towards becoming more data-conscious:
- Digitize all medical and operational records and set up a simple interface around the database.
- Create a metadata repository to enhance data integrity.
- Anchor all read/write access into the blockchain to have a clear tamper-free audit trail.
- Analyze and react to data in real-time with streaming data architecture.
Eventually, all stakeholders will enjoy improved production, procurement, and business communication as a result of optimized decision-making. One of the global healthcare players, Merck, is a great example here. The use case started with a need to understand why some of their vaccines had higher than usual discard rates. Using advanced analytics, Merck processed data from 16 different sources. The data was aggregated and aligned across common factors such as batch ID and time stamp. Then this data was used to develop and test models to prove/disprove the hypothesis behind low yields. After multiple calculations and batch-to-batch comparisons, Merck was able to identify certain fermentation traits for further lab testing before changing the production process, once regulatory approvals were secured. Now, they are applying this expertise to optimize the production of other vaccines.
With Taraxa — a full-fledged platform for data infrastructure optimization — you have the power to collect operational data and metadata from stakeholders and suppliers with a full audit trail recorded.
- Enjoy the real-time view of data: monitor data at any given point in time using customized filters
- To accelerate the rate at which these benefits can be achieved, the quality of data at the source is critical.
- End-users access EMR data easily with a single sign-on functionality, while customers can generate detailed reports with patient-compliance data.
- Enable better compliance monitoring: get clinical-abstraction guidelines to fit the regulatory-submission specifications
- Enhance hospital bio-surveillance capabilities and improve infection and disease identification and control
To learn more about our solution and how it can help you meet your data quality challenges, reach out at firstname.lastname@example.org or watch our demo.
- Quality Management 2019 The Search for a One-Stop Shop
- The state of data quality in 2020
- Oliver Wight EAME LLP – White Papers & Brochures
On a path to smart hospital: make your regulatory audits a breeze was originally published in Taraxa Project on Medium, where people are continuing the conversation by highlighting and responding to this story.