Artificial Intelligence
Consulting
Development ServicesOver the last couple of years, the healthcare industry has experienced a whirlwind of acquisitions and mergers. All this activity makes sense from a business perspective, but what does it mean for the quality of patient care? What about hospital ratings?
While all these partnerships might yield some benefits, we believe that patient and hospital data integration can lead to a long-term success. In fact, data is critical to healthcare. It’s the underlying force that helps create an accurate and in-depth picture of the industry.
When you have all this valuable data at your fingertips, you’ll have a better understanding of the following:
- Efficiency
- Costs
- Outcomes
- Performance
Data isn’t only vital to healthcare professionals in the industry, it’s also important for researchers who conduct long-term studies. It’s essential to the finance department as well since they rely on data to develop spending forecasts and determine the overall financial health of the organization.
So it makes a lot of sense that most professionals in the healthcare industry list data and analytics as a priority to improve decisions making.
The data lakes that are readily available to hospitals, clinics, and private practices can help resolve not only business and operational challenges, but also ensure enhanced delivery of adequate patient care. However, not everyone is taking advantage of the data that’s available to them.
According to research, only about 30% of hospitals in the US leverage clinical data warehouses and only 33% of healthcare institutions use business intelligence tools. At this juncture, it’s important to note that organizations making data-driven decisions have an output and productivity that’s 5%-6% higher than their peers.
High performing healthcare organizations also engage in data and analytics five times more than their low performing counterparts. It’s easy to conclude that big data development is the big differentiator in the healthcare industry because it can boost revenue by 8%.
Data and analytics are credited for the following:
- Improved financial reporting
- Improved overall health outcomes
- Improved patient care
- Reduced re-admission rates
All these different elements also come together to have an impact on hospital ratings. As patients start relying more on publicly available hospital rating when seeking care, there will be financial consequences for not meeting the quality benchmarks.
As a result, it’s critical to ensure that healthcare organization only analyze quality data because working poor (or corrupted) data can quickly lead to inaccurate assessments.
So how does the industry engage in quality data integration to improve hospital ratings and decision making? Let’s take a look.
1. Engage in Extensive Planning Before Migrating Data into a Common Electronic Health Record (EHR) Platform
Whenever there’s an acquisition or a merger, there might be a need to migrate patient data from one system to another to manage it in a single platform. This approach helps lower costs when it comes to managing and maintaining the system.
Effective data migration also helps eliminate data silos that can contribute to inaccurate findings. However, migrating sensitive patient data isn’t going to be effortless, and healthcare providers shouldn’t ignore the data integrity risks involved.
According to Rod Piechowski, Senior Director of Health Information Systems at HIMSS, “one of the biggest challenges, which is also one of the most important elements of a successful migration, is developing a plan that properly addresses the scope of data that needs to be migrated, the order in which it should be done, and the amount of time that a quality migration can take.”
Proper planning requires a lot of effort and forward thinking among all stakeholders across the healthcare institution. When this isn’t approached correctly, healthcare organizations significantly increase the risk of data integrity issues down the road that can lead to dire consequences.
It’s important to avoid making assumptions that there will be seamless relationships with different data types and fields. Everything won’t just flow highly accurately or go smoothly (and that’s just a fact of life).
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For example, the implications of mapping errors can have significant consequences for both patients and providers. So it’s essential to implement a manual component (like clinical abstraction services) to the migration process to ensure that critical information isn’t lost or corrupted.
It’s also important to note that if the corrupted data doesn’t just affect patient care, it can also have an impact on functions like scheduling and billing. Whenever there are business interruptions and revenue issues, it can also damage the hospital reputation.
Before moving forward with a complete migration, conduct an extensive QA testing. With so much at stake, it would be beneficial to engage an experienced third-party partner to help with the EHR migration project.
2. Evaluate the Integrity of Clinical Documentation and Coded Data
Data-driven decisions are only as good as the quality of data it's based on. So it’s important to keep evaluating the integrity of clinical documentation and the coded data regularly. There should be processes in place to assess institutional data quality.
According to Daniel Land, RHIA, CCS, Nationally Recognized Healthcare Revenue Integrity & Coding Compliance Subject Matter Expert, “the findings can be used to correct current deficiencies, identify opportunities for improvement, and proactively monitor data quality over time—which should ultimately improve an organization’s ratings.”
The best way to approach this is to set up auditing protocols across the organization. For example, when you do this, healthcare information management (HIM) professionals can also play the role of subject matter experts on the coding elements that factor into hospital ranking.
HIM specialists can also work with different departments across the institution to ensure that improvements are made to clinical documentation based on data audits. Together, these individuals will also be able to address data gaps.
3. Establish a Data-Driven Culture
Once the data migration is completed and the data auditing protocols are in place, business and technology leaders within the organization have to strive to develop a data-driven culture.
Although many healthcare providers try to achieve this overnight, it’s important to take a long-term approach. However, this might not always be easy with cost pressures and the threat of poor ratings.
Providing data-driven value-based care requires the execution of specific strategies. It also demands a system of continuous improvement that will most often come with a learning curve. This process starts with designing an appropriate plan of action to nurture a data-driven culture within the healthcare organization.
The healthcare industry is accelerating ahead into a high-tech future of better care and improved outcomes that will be data-driven. However, to get there, healthcare institutions will have to carefully plan and execute every step of the process from migration to developing a data-driven culture.
Need help with a data integration project for your organization? Reach out to one of our data experts now.
