The Road to Smart Hospitals: Completing Regulatory Audits Made Easy

Why the healthcare industry still struggles with data accuracy

A recent report by O'ReillyIt shows that most institutions are still busy dealing with data quality issues due to lack of resources to build a data governance framework. The healthcare industry is a strictly regulated industry, which needs to share medical operation data with regulatory agencies in a timely manner as required, so the situation is even more severe. So why is it still so difficult to maintain the accuracy of regulatory data?

First, the data reporting requirements of the Centers for Medicare and Supplement Services (CMS), the Agency for Healthcare Research and Quality (AHRQ), and the Joint Commission have been changing and becoming more complex. Recently aboutData Quality Management in 2019The report clearly pointed out that the market demand for data quality management solutions is increasing, and organizations need a set of multifunctional solutions to deal with changing regulatory policies:

“Organizations that are looking for this type of information explain that regulatory requirements are often just the bare minimum they have to meet. If they want to be really high quality, they need tools that provide insight into information such as patient readmissions, treatment costs, and job costs. Efficiency of personnel, etc.” (fromKLAS Report, 2019）

Second, since the past has tended to store medical data in various places (including different departments in the hospital, different source systems such as EMR, HR, etc.), today the data format is messy and scattered. Healthcare data comes in a variety of formats: from image data in radiology departments, to paper-based medical records of the past, to hundreds of lines of text and digital records carried by EMR electronic medical records today. This data can be captured and processed by aggregating it into a unified central system.

Today, however, such systems are few and far between, largely because of the financial and operational expenditures required to deploy and manage an entirely new data management technology stack. In addition, the consequences of mishandling data can pile up, such as inventory building, material shortages for manufacturing and packaging, and resource drain and loss of medical records during external audits.

How to Capture High-Quality Healthcare Data With More Confidence

To reduce expenses and improve the efficiency of managing people and physical assets, both the sales and supply sides of the healthcare industry need data management systems to maintain regulatory data (for external audits) and planning data (for cost-effectiveness and production optimization) accuracy. Accessing data through this environment enables stakeholders to proactively improve internal logistics, assets such as medical supplies and pharmaceuticals, while gaining greater control over human assets. These viable options will ultimately optimize the utilization of existing resources and create additional revenue opportunities.

Given the unpredictability of the data supply chain in the healthcare industry, we propose the following solutions to accelerate data optimization:

• Realize the digitization of all medical and operational data, and build a simple database interface;

• Create a metadata repository to improve data integrity;

• Anchoring all read/write access to the blockchain to createAn immutable audit trail channel;

• Real-time analysis and response to data through streaming data architecture.

By building a mature data architecture optimization platform, collect operational data and metadata from stakeholders and suppliers, and at the same timeKeep a complete audit trail。

• Browse data in real time: monitor data at any given time through custom filters;

• If you want to accelerate your gains, you must ensure data quality from the source;

• End users can easily access EMR data through a simple login function, and consumers can also generate detailed reports consistent with physician orders;

• Better compliance monitoring: align clinical sampling guidelines with regulatory submission specifications;

• Improve the identification and control of diseases and infectious diseases by improving the biological detection capacity of hospitals.