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Data: Quality, Management, Governance

The Healthcare Cybersecurity Framework: A Top Defense Against Data Breaches and Attacks (White Paper)

Between 2017 and 2020, more than 93 percent of healthcare organizations experienced a data breach. While digital technology and connectivity is increasingly critical in meeting operational and clinical challenges, such as COVID-19, more integration also enables increased exposure to cyberattacks that can impact care delivery, safety, and privacy.

In response to healthcare’s significant and growing cybersecurity threats, vendor organizations and their health system partners need a security framework. A defensible protocol holds vendors accountable to routine audits and compliance measures at a regular cadence, ensuring both parties keep cybersecurity programs active and optimized.

Interoperability in Healthcare: Making the Most of FHIR

With the CMS and ONC March 2020 endorsement of HL7 FHIR R4, FHIR is positioned to grow from a niche application programming interface (API) standard to a common API framework. With broader adoption, FHIR promises to support expanding healthcare interoperability and prepare the industry for complex use cases by addressing significant challenges:

  1. Engaging consumers.
  2. Sharing data with modern standards.
  3. Building a solid foundation for healthcare interoperability.

Critical Healthcare M&A Strategies: A Data-driven Approach

Historically technology and talent were primary assets used to weigh the value of M&A activity, but data is an equal pillar. Buyers (the acquiring organizations) face enormous responsibility and risk with M&A transactions. C-suite leaders have a lot to consider—enterprise-wide technology, finances, operations, facilities, talent, processes, workflows, etc.—during the due diligence process. But attention is often heavily weighted toward time-honored balance sheet and facility assets rather than next-generation assets with the long-term strategic value in the M&A process: data. The model for conducting due diligence around data involves four disciplines:

  • Establish the strategic objectives of the M&A with the leadership team.
  • Prioritize data along with the standardization of solutions and the design of a new IT organization (i.e., a co-equal effort for data, tools, and talent).
  • Identify the near-term data strategic priorities, stakeholders, and tools.
  • Assess the talent and consider creating an analytics center of excellence (ACOE) to harness organizational capabilities.

Healthcare Analytics Platform: DOS Delivers the 7 Essential Components

The Data Operating System (DOS™) is a vast data and analytics ecosystem whose laser focus is to rapidly and efficiently improve outcomes across every healthcare domain. DOS is a cornerstone in the foundation for building the future of healthcare analytics. This white paper from Imran Qureshi details the seven capabilities of DOS that combine to unlock data for healthcare improvement:

  1. Acquire
  2. Organize
  3. Standardize
  4. Analyze
  5. Deliver
  6. Orchestrate
  7. Extend

These seven components will reveal how DOS is a data-first system that can extract value from healthcare data and allow leadership and analytics teams to fully develop the insights necessary for health system transformation.

When Healthcare Data Analysts Fulfill the Data Detective Role

There’s a new way to think about healthcare data analysts. Give them the responsibilities of a data detective. If ever there were a Sherlock Holmes of healthcare analytics, it’s the analyst who thinks like a detective. Part scientist, part bloodhound, part magician, the healthcare data detective thrives on discovery, extracting pearls of insight where others have previously returned emptyhanded. This valuable role comprises critical thinkers, story engineers, and sleuths who look at healthcare data in a different way. Three attributes define the data detective:

  1. They are inquisitive and relentless with their questions.
  2. They let the data inform.
  3. They drive to the heart of what matters.

Innovative analytics leaders understand the importance of supporting the data analyst through the data detective career track, and the need to start developing this role right away in the pursuit of outcomes improvement in all healthcare domains.

The Four Balancing Acts Involved with Healthcare Data Security Frameworks

There’s a lot at stake for healthcare organizations when it comes to securing data. A primary concern is to protect privacy and avoid costly breaches or leaks, but at the same time, data must be accessible if it’s to be used for actionable insights. This executive report introduces four balancing acts that organizations must maintain to build an ideal data security framework:

  1. Monitoring
  2. Data de-identification
  3. Cloud environments
  4. User access

This can be a tug-of-war between IT and security, two groups that often have divergent interests, however well-meaning they may be. Healthcare systems that build bridges between these interests and strike the crucial balance between data utilization and security can dial in on long-term goals, like better care at a lower cost and overall outcomes improvement.

PHI Security and Auditing: Reducing Risk and Ensuring Compliance with a Data Warehouse

EHRs and other electronic health information has created many benefits for patients and the healthcare industry, from improved treatment to reduced duplication of services. However, electronic data also increases the risks associated with PHI. Ensuring compliance with PHI security, including auditing trails, is more important than ever. Breaches constitute a violation of HIPAA and can result in stiff financial penalties and tarnished reputations. Health Catalyst addresses security compliance using a multifaceted solution that ensures the right balance between having enough granularity of information available to the people who need it and securing that information from people who don’t need that level of detail.

The Changing Role of Healthcare Data Analysts—How Our Most Successful Clients Are Embracing Healthcare Transformation (Executive Report)

The healthcare industry is undergoing a sea change, and healthcare data analysts will play a central role in this transformation. This report explores how the evolution to value-based care is changing the role of healthcare data analysts, how data analysts’ skills can best be applied to achieve value-based objectives and, finally, how Health Catalyst’s most successful health system clients are making this cultural transformation happen in the real world.

Demystifying Healthcare Data Governance (Executive Report)

Finding the perfect data governance environment is an elusive target. It’s important to govern to the least extent necessary in order to achieve the greatest common good. With the three data governance cultures, authoritarian, tribal, and democratic, the latter is best for a balanced, productive governance strategy. The Triple Aim of Data Governance is: 1) Ensuring data quality; 2) Building data literacy; and 3) Maximizing data exploitation for the organization’s benefit. The overall strategy should be guided by these three principles under the guidance of the data governance committee.

Anatomy of Healthcare Delivery Model: How a Systematic Approach Can Transform Care Delivery (white paper)

Read about this breakthrough model and framework, developed and refined by Dr. David Burton during his 25 years of executive healthcare experience. This model creates a framework that maps major healthcare processes into common patterns and process flows that can then be used to systematically examine and improve healthcare delivery. By using a systematized framework to reduce variations in clinical and operational processes, health systems can experience sustainable cost and quality gains. This framework won’t eliminate critical thinking, but it will provide a standardized, evidence-based approach to care delivery, which will bring all care up to the same, high standard.

Accountable Care Organizations Drive Demand for Data Warehouse (Executive Report)

Analytics packages offered by their EHR vendor and their existing business intelligence/analytics tools are not up to the task of supporting the transformation currently underway. Adaptive data warehouses and the analytical tools now available provide crucial, actionable intelligence that health system clinicians can use to identify opportunities to improve clinical effectiveness, cost effectiveness and safety.

7 Essential Practices for Data Governance in Healthcare (Executive Report)

Data is now one of the most valuable assets in any organization, especially healthcare as we transition into a more analytically driven industry. If we accept the assertion that healthcare is a knowledge delivery industry—that is, the application of specialized skills and knowledge, along with specialized tools—it is our obligation to exploit the data assets in our environment to augment and optimize that knowledge and those skills.