begins with a data governance strategy
As the age of analytics emerges in healthcare, healthcare organizations find themselves increasingly challenged to define a data governance strategy that maximizes the value of healthcare data to the increase care. But there is no denying the dramatically growing importance of data analytics to business success. This is especially true for those businesses based in knowledge management delivery, which is certainly the case with healthcare.
The rising importance the data warehouse and analytics market has resulted in significant noise from vendors and consultants who promise to help healthcare systems develop their data governance strategies. Telliant Systems’ analytics teams help solve the challenges by conducting a thorough assessment of your data governance strategy. We know how and where to start the data governance journey in healthcare and provide a roadmap to evolve that journey incrementally over the lifespan of the organization.
Lean data governance achieves results
Telliant’s approach to data governance is to be as lean as possible—govern to the least extent necessary in order to achieve the greatest common good.
Lean Data Governance results in the following benefits:
- Less constraints on data
- More effective use of resources
Pairing the data governance function with overseeing the development and evolution of an enterprise data warehouse (EDW) allows the data to be tangible and efficient. Utilizing a late-binding data engineering architecture and an EDW, combined with lean data governance, enhances your options.
Tools for Data Governance
To achieve the best data governance strategy, the stakeholders will require detailed reports to completely analyze and expose inconsistencies in the quality of the data.
Data Completeness + Data Validity = High Data Quality
Data completeness is measured by measuring the null values in a data set, identifying all the areas where data should be collected and planning a strategy to begin collection. Data stewards will be responsible for data associated with their systems
Data validity is measured by joining data collected from primary source systems (EMR and registration systems) and the master reference data in the EDW
Data stewards use the reports to ensure
the data is high quality by:
- Identifying the gaps and mismatches between the source system and the master reference data.
- Ensuring the data collected is useful for a wide variety of analytics uses.
Extraction, Transformation and Loading (ETL) Best Practices
ETL is critical to the success of any data warehouse project, particularly for healthcare, many transformations are needed to ensure that the data is usable for end users.
ETL is the mechanism most data governance processes use to extract data out of the source systems to upload to an integrated data warehouse. Although it is more complex than a simple dump and load, a good ETL strategy process ensures many opportunities including applying business rules and introducing quality checks.
Following a software development best practices for ETL will ensure the data quality. For any ETL project to be successful it should include; naming conventions, error handling and notification, reusability, metadata management and failure and recovery processes.
Clinical Data Repository (CDR)
Planning for Providers
Telliant services improve decision making with a consolidated patient view through a facility-wide vendor-neutral repository of all relevant health data. CDR’s empower data managers, and other users to control their data in real time. Consolidating data from varied sources and empowers users to view the unified data to make good clinical decisions.
Many early adopters and innovators have seen the value that can be derived from CDR technology. The costs and risks associated with adopting new technology is negligible when you weigh the benefits.
Healthcare organizations are beginning to realize that the real value of health IT comes not only from the use of its applications but more importantly, from understanding of the data
The real value of health IT comes not only from the use of its applications but also from understanding of the data. Unfortunately, today much of the structured data stored in proprietary systems are not shared, making care coordination, real-time analytics and knowledge discovery the top challenge.
Our approach is two-fold; using a vendor-neutral structured clinical data repository (CDR) and a full-featured retrieval process mitigating the challenges
Having a full-featured real-time CDR for exchanging data with transactional storage combined with a retrieval process is the first part. Built on community sourced clinical data models with an integrated clinical data repository, providing the API and foundation for developers to build semantically interoperable applications, enterprise clinical information and apps for modern mobile devices.
Revenue Cycle Management & Optimization
Critical parts of a transformative revenue cycle
Successful health care organizations must zero in on improving financial performance and enhancing the patient experience, while delivering efficiencies and reducing the overall revenue cycle cost. The four key elements of a successful transformation and optimization include:
- Optimizing the technology environment
- Adopting advanced analytics techniques
- Improving payer connectivity
- Enhancing the patient experience
Organizations that focus on these four pillars will achieve an
effective RCM environment.
Optimizing the RCM technology environment
Optimizing the technology environment is an essential step in every RCM transformation.
An integrated system not only requires connecting the EHR with the RCM system, but also enhancing operational capabilities of the RCM and streamlining the clinical and financial systems for greater insights into treatments, costs and outcomes.
Adding functionality and rules-based workflow capabilities, increases efficiency and contributes to revenue improvements through exception-based processing.
Adopting advanced analytics techniques
Advance analytics are becoming increasingly important with increasing healthcare efficiencies. These same tools can also identify claims denials and revenue losses, but also to leverage the information for predictive intelligence. Key elements of advanced analytics include:
- Tools to reduce bad debt write-offs and days receivables outstanding (DRO)
- Proactive denials management to improve accuracy and resubmittals
- Predictive analytics and business intelligence with risk modeling strategies
Healthcare Compliance is a
Telliant understands the importance of risk and compliance management. Having a complete strategy to satisfy the federal requirements protects the organization, patients, and providers. A good strategy should include the following parts:
Improve patient and customer satisfaction
The satisfaction of patients is paramount to a healthcare organization’s success. Trust is the foundation of satisfactory relationships, and trust is achieved by demonstrating privacy is a priority.
Reduce the cost of data breaches
HHS has made it clear: noncompliance is expensive. With the advent of HITECH, investing in compliance management and risk mitigation is required. Meaningful use and MACRA incentives and penalties are good motivations to invest in secure systems.
Build and maintain reputation and competitiveness
Securing your reputation in the healthcare industry is critical to success. Validation of HIPAA compliance and trustworthy control of personal health information (PHI) will go a long way to secure a competitive market-share.
Improve public health
Public health systems and programs can be transformed by integrating information exchanges with providers. By developing electronic surveillance and registry systems, providers can streamline reporting, and epidemiologists can identify and analyze disease trends more quickly. This can only be accomplished through secure, HIPAA-compliant systems.
Prevent system downtime
Public health systems, programs and organizations will be transformed by the interoperability of information exchanges. Developing electronic surveillance and registry systems will allow providers to streamline reporting ensuring epidemiologists are able to identify and analyze disease trends more quickly. This can only be accomplished through secure, HIPAA-compliant systems.
Prevent system downtime
The greatest threat to day-to-day operations is HIT system downtime. Critical decisions are made based upon clinical information collected, analyzed, delivered, and stored electronically. The costs of losing access to vital clinical data are enormous: patients’ wellbeing, the organization’s reputation, and malpractice risks.
The steps to managing risks and compliance
Having a partner like Telliant, with extensive experience in advising healthcare executives and providers in compliance requirements within the healthcare industry is critical. Telliant will work with you on a risk and compliance management strategy from the very beginning of HIT development.