Seven Ways DOS™ Simplifies the Complexities of Healthcare IT (White Paper)

Health Catalyst Data Operating System (DOS) is a revolutionary architecture that addresses the digital and data problems confronting healthcare now and in the future. It is an analytics galaxy that encompasses data platforms, machine learning, analytics applications, and the fabric to stitch all these components together.

DOS addresses these seven critical areas of healthcare IT:

  1. Healthcare data management and acquisition
  2. Integrating data in mergers and acquisitions
  3. Enabling a personal health record
  4. Scaling existing, homegrown data warehouses
  5. Ingesting the human health data ecosystem
  6. Providers becoming payers
  7. Extending the life and current value of EHR investments

This white paper illustrates these healthcare system needs detail and explains the attributes of DOS. Read how DOS is the right technology for tackling healthcare’s big issues, including big data, physician burnout, rising healthcare expenses, and the productivity backfire created by other healthcare technologies.

Ten Essential Steps for Your Readmission Reduction Program (Executive Report)

Effective care management is essential during the first 30 days after discharge to prevent unnecessary readmission and associated costs. Care managers can follow a 10-step readmission reduction program to help patients stay on track with recovery and avoid acute care:

  1. Call the patient within two days of discharge.
  2. Assess the patient’s self-care capacity.
  3. Frontload homecare and ensure patient ‘touches’, if appropriate.
  4. Conduct a home safety evaluation.
  5. Order and install durable medical equipment prior to discharge.
  6. Order an emergency alert/medication reminder system and preprogram important phone numbers on patient’s phone.
  7. Implement fall prevention program, intervention, and education.
  8. Provide in-home education on new diagnoses or unmanaged chronic conditions.
  9. Connect the patient with community resources.
  10. Establish a best practice for follow-up phone calls after discharge.

A Landmark, 12-Point Review of Population Health Management Companies (Executive Report)

Population health management (PHM) is in its early stages of maturity, suffering from inconsistent definitions and understanding, overhyped by vendors and ill-defined by the industry. Healthcare IT vendors are labeling themselves with this new and popular term, quite often simply re-branding their old-school, fee-for-service, and encounter-based analytic solutions.  Even the analysts —KLAS, Chilmark, IDC, and others—are also having a difficult time classifying the market. In this paper, I identify and define 12 criteria that any health system will want to consider in evaluating population health management companies.  The reality of the market is that there is no single vendor that can provide a complete PHM solution today.  However there are a group of vendors that provide a subset of capabilities that are certainly useful for the next three years.  In this paper, I discuss the criteria and try my best to share an unbiased evaluation of sample of the PHM companies in this space.

 

Is Your Care Management Program Working: A Guide to ROI Challenges and Solutions (Executive Report)

Care management programs play a large part in many health systems’ population health strategies. However, these programs can consume a lot of resources. It is important to know if a care program is effective, and eventually, to show a positive ROI. Many roadblocks stand in the way:

  • Complexity of Environment
  • Prolonged Time to ROI
  • Lack of Access to Disparate Data
  • Difficulty Engaging the Patient

A thoughtful approach and a robust analytics platform can help organizations overcome these challenges. Care management ROI should be a long-term strategy, but cost savings and quick wins are possible using the Health Catalyst® Cost Management Suite.

How to Use Data to Improve Patient Safety (Executive Report)

Healthcare organizations have worked hard to improve patient safety over the past several decades, however harm is still occurring at an unacceptable rate. Though the healthcare industry has made efforts (largely regulatory) to reduce patient harm, these measures are often not integrated with health system quality improvement efforts and may not result in fewer adverse events. This is largely because they fail to integrate regulatory data with improvement initiatives and, thus, to turn patient harm information into actionable insight.

Fully integrated clinical, cost, and operational data coupled with predictive analytics and machine learning are crucial to patient safety improvement. Tools that leverage this methodology will identify risk and suggest interventions across the continuum of care.

A Guide to Care Management: Five Competencies Every Health System Must Have (Executive Report)

The goal and responsibility of every healthcare organization and provider using a care management approach is to deliver the right care at the right time to the right patients. This standard of care management can only be achieved if five competencies are in place:

  • Data Integration
  • Patient Stratification and Intake
  • Care Coordination
  • Patient Engagement
  • Performance Measurement

This guide to care management reviews each competency and shows how to put it all together into an effective program that gets results for organizations and patients alike.

Outcomes Improvement Governance: A Handbook for Success and Achieving More with Less (Executive Report)

For healthcare organizations looking to achieve outcomes improvement goals, effective governance is the most essential must-have. This leadership culture ensures success by enabling health systems to invest in outcomes improvement and allocate resources appropriately toward these goals.

This executive report is an outcomes improvement governance handbook centered on four guiding principles (and associated helpful steps) health systems can follow to achieve effective governance and start achieving more with less:

  1. Stakeholder engagement
  2. Shared understanding
  3. Alignment
  4. Focus

With these four principles, organizations can build a foundation of engagement and focus around the work, where they maximize strengths, and discover and address weaknesses. They establish an improvement methodology, define their goals, and sustain and standardize improvement work.

Preparing for MACRA: A Comprehensive FAQ for Physicians (Executive Report)

The Medicare Access and CHIP Reauthorization Act (MACRA) overhauls the payment system for Medicare providers. It’s a complex program that requires careful study so physicians can make the best choice for how they want to report. This choice ultimately impacts reimbursement and the potential bonuses or penalties associated with each reporting option.

This FAQ covers both tracks of the new rule, the Merit-based Incentive Payment System (MIPS), and the Advanced Alternative Payment Model (APM), with a background review and a comprehensive list of questions and answers.

It’s a practical guide complete with next steps for strategic and tactical planning.

The Best Way to Maximize Healthcare Analytics ROI (White Paper)

When it comes to maximizing analytics ROI in a healthcare organization, the more domains, the merrier. Texas Children’s Hospital started their outcomes improvement journey by using an EDW and analytics to improve a single process of care. It quickly realized the potential for more savings and improvement by applying analytics to additional domains, including:

  • Analytics efficiencies
  • Operations/Finance
  • Organization-wide clinical improvement

The competencies required to launch and sustain such an organizational sea change are all part of a single, defining characteristic: the data-driven culture. This allows fulfillment of the analytics strategy, ensures data quality and governance, encourages data and analytics literacy, standardizes data definitions, and opens access to data from multiple sources.

This article highlights the specifics of how Texas Children’s has evolved into an outcomes improvement leader, with stories about its successes in multiple domains.

Hadoop in Healthcare: Getting More from Analytics (White Paper)

Healthcare data is positioned for momentous growth as it approaches the parameters of big data. While more data can translate into more informed medical decisions, our ability to leverage this mounting knowledge is only as strong as our data strategy. Hadoop offers the capacity and versatility to meet growing data demands and turn information into actionable insight.

Specific use cases where Hadoop adds value data strategy include:

  1. Archiving
  2. Streaming
  3. Machine learning