A recent study by Change revealed that as of 2019, 48 of the 50 states in the USA have implemented value-based care initiatives. The result? The number of active value-based care programs in the US has increased seven-fold. This marks a significant shift for the healthcare system towards an outcome-based model that fosters higher efficiency and reduces the cost of treatment.
The advantages of value-based healthcare have been thoroughly discussed, tested, and established. But despite the exponential rise in the adoption of the value-based healthcare model, most healthcare institutions are far from being fully prepared to reap its benefits. And, while factors such as financial risks and gaps in care can be blamed for this, lack of visibility and interoperability among departments remain the primary challenge.
These challenges call for special attention because they lie at the heart of healthcare’s data problem and, subsequently, impact the industry’s journey towards digital maturity. In the context of value-based healthcare, as well, this raises issues in the timely reporting of quality information necessary for revenue generation and improved patient care.
In order to materialize the full potential of a value-based care system, hospitals need to implement an overarching data strategy. And, the first step towards that is to overcome health data silos.
The Importance of Data in a Value-based Care System
In a report by GE Healthcare, Nokia, and the University of Pittsburg Medical Center (UPMC) that explores the priorities in a value-based care ecosystem, almost half (47%) of the respondents reported below-average maturity for their enterprise-wide data integration journey. This is a cause for concern for hospitals that practice value-based care where the various departments work in tandem to deliver quality care and drive revenues.
For instance, the clinical documentation improvement (CDI) department is tasked with identifying and communicating opportunities and risks related to documentation inefficiencies. On the other hand, the health information management (HIM) department is responsible for identifying the correct category of codes that accurately document patient care, resources consumed, the severity of illness, and risk of mortality. A lack of adequate exchange of information between these teams could lead to the repetition of errors in coding and documentation. The result: decreased quality of care, ineffective care decisions by physicians, lower productivity, rise in the number of DNFC (discharged not finally coded) days, reimbursement issues, and subsequent loss of revenue.
A Single Platform Approach: Promoting AI-powered Collaboration
Now, let’s see what would happen if these departments had access to a single, unified data platform. By aggregating the information on documentation errors from the CDI team, the HIM department would be able to identify the error-prone categories and collaborate to eliminate the issues.
By creating a unified source of structured data, a single platform data strategy would promote technology implementation such as artificial intelligence (AI) and natural language processing (NLP) to boost interdepartmental collaboration and productivity. By reading patient medical records and suggesting queries and codes with evidence and trails to documentation, AI and NLP can assist coders in identifying the correct code category and reduce the chances of an error. As a result of this, the CDI department can focus on enhancing the quality of care while establishing a steady and streamlined cash flow for hospitals.
A single data platform could also be leveraged by AI-powered analytics to provide decision-makers with real-time operational visibility through performance-based reports and insights on the coding and documentation processes.
Choosing the Right Data Partner
Powered by adequate data, AI and NLP have the potential to provide hospitals with major benefits that include improved case mix index (CMI), enhanced care quality, and reduced denials. And with providers increasingly adopting innovative technologies that rely on AI and NLP components to increase revenue, it has become imperative for healthcare institutions to choose the right data partner in order to gain a competitive advantage. This is where ezDI steps in.
As the only born-in-the-cloud, AI-based, fully integrated CDI and CAC platform on the planet, ezDI provides a 360-degree view of data relevant to patients’ care, records, reimbursements over a single, unified, intuitive platform.
ezDI’s computer-assisted coding solution (ezCAC) is a key component in achieving this. ezCAC provides a singular integrated collaboration platform for all key stakeholders such as coders, CDI specialists, HIMs, physicians, internal auditors, and quality managers. This, in turn, enables proactive, data-driven decisions that drive up CMI and revenue while simultaneously reducing DNFC.
Take the case of Auburn Community Hospital (ACH), a non-profit acute care facility located near Syracuse, New York. The hospital was experiencing a DNFC of 7 days and a CMI of 1.2. Upon partnering with ezDI and implementing ezCAC, ACH not only witnessed a 4.59% increase in CMI and a 50% drop in DNFC but also more than a 40% rise in productivity. As a result, ACH was able to realize a 10-times increase in returns at USD 1.03 million.
ezDI’s AI-powered computer-assisted technologies like ezCAC, ezCDI, ezAnalytics, and ezMeasures are hosted on a single platform. By leveraging ezDI’s value additions, hospitals can promote collaboration among various teams including coders, CDI, physicians, quality, auditors, and the C-suite. This allows the organization to operate as a single unit across all hierarchical layers.
To learn more about ezDI’s AI-based mid-revenue cycle management solutions visit www.ezdi.com and to see the live product demo of our Clinical Documentation, Coding, Compliance/Auditing, Quality Measures, Encoder, and Enterprise Analytics request a live demo.