Life Sciences

CMS healthcare programs are shifting from an optional data reporting submissions to mandatory electronic submissions. To meet these requirements, healthcare organizations need to align their organization’s data with evolving standards, which can require a whole-system transformation.This is the first of three articles that stress the urgent need for healthcare systems to take an all-in approach to data and analytics, starting with the need for and benefits of high-value data.High-value data has been standardized and can be used to identity standardized attributes across previously siloed systems. It enables: faster downstream analytics, aggregated benchmarking, novel data combinations that produce exponential value.Organizations that make high-value data the foundation of an integrated data strategy, can supply providers, clinicians, and administrative leaders with the trusted, timely data they need to maximize reimbursement and drive informed decisions for better outcomes.

Healthcare leaders must increase revenue and decrease costs without negatively impacting care quality and patient outcomes. At HAS 2022, a panel of healthcare leaders and executives shared key recommendations on leveraging data analytics to achieve this precarious balance.

Provider burnout was a challenge for healthcare organizations before 2020’s COVID-19 pandemic, and the pressures of the global crisis exacerbated the problem. In 2022, 56 percent of critical care and 60 percent of emergency medicine physicians reported burnout. Today, however, the industry is looking to the same digital care technologies that helped hospitals navigate the pandemic to alleviate provider burnout and improve care.

Identifying and executing achievable population health goals requires insights from a vast amount of accurate but often incomplete data. Population health experts offer three key strategies to navigate complex data.1. Start with the available accurate data. Resist the urge to wait for “perfect data.”2. Consult clinicians early and often when selecting and executing population health initiatives. Familiarize these clinicians with data dashboards and keep dashboards user-friendly to advance success.3. Consider the role risk stratification plays in setting goals. While high-risk patients may be a care team’s primary focus, initiatives that transcend risk levels and include initiatives for rising-risk and low-risk patients prevent care cost escalations.

A primary focus for healthcare organizations post-Covid is improving health equity for their communities. At HAS 2022, a duo of data scientists from ChristianaCare shared an analytics framework for measuring and managing equity disparities and described how they developed and applied a machine-learning-based algorithm to quantify differences in health outcomes. The framework consists of a data layer, an analytics layer, and an interpretation and decision support layer. The data layer identifies and standardizes data structures for a list of health outcomes. The analytics layer calculates the defined metrics in an integrated, automated way. And the interpretation and decision support layer highlights how a user-centered design dashboard can support clinicians and leaders in understanding and interpreting outcomes.

HIEs can become a primary driver to healthier communities through high-value data access. Adopting a strategy that addresses emerging data use cases, data quality, and strategic partnerships will fuel long-term success and add new revenue streams from a wider range of participants.

Several healthcare leaders from hospitals and health systems across the country share their team’s best practices when implementing a data analytics platform to improve quality and operations initiatives.The strategies shared by the leaders that yielded the most success at their organizations include encouraging collaboration between data analytics teams and process improvement teams, aligning data insights with established operational initiatives, focusing analytics initiatives on a limited number of improvement areas with the broadest potential impact, telling a story with the data to inspire meaningful change.

Healthcare organizations are accustomed to starting each new year with changes to billing and coding policies. However, in 2023 providers and suppliers are finding that some updates need extra clarity. Guidelines on the recent updates will help providers create consistent processes to reduce errors and reimbursement delays.

The Centers for Medicare & Medicaid Services has released its latest updates to the Clinical Modification (ICD-10-CM) system and the International Classification of Diseases, 10th Revision, Procedure Coding System (ICD-10-PCS). Effective April 2023, healthcare leaders will have 42 ICD-10-CM and 34 ICD-10-PCS additions to navigate.

Different entities within an ACO need access to the same patient information to coordinate around delivering better patient care at lower costs. Despite this clear need for data sharing, organizations face common barriers, including patient confidentiality, cumbersome processes, and legal and compliance considerations. However, ACOs can overcome these barriers with a team mindset and robust data infrastructure. A teamwork approach aligns each system’s goals more closely, ensuring the entire ACO prioritizes patients and their data as the key to better care coordination. Next, organizations need to invest in advanced technologies, including a data platform that easily aggregates and securely distributes patient information to the right people at the right time. These two changes—working together and supporting data-sharing tools—elevate ACO performance and care coordination