- Find the Believers (Identify Clinician Champions)
- Organize a Cross-Functional Team (with Appropriate Governance)
- Invest Time and Resources
- Celebrate Progress Along the Way
- Use Early Successes to Scale and Spread
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- Data: Quality, Management, Governance
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Given the industry’s shift toward value-based, outcomes-based healthcare, organizations are working to improve outcomes. One of their top outcomes improvement priorities should be early detection and action, which can significantly improve clinical, financial, and patient experience outcomes. Through early detection and action, systems embrace a proactive approach to healthcare that aims to prevent illness; the earlier a condition is detected, the better the outcome. But, as with most things in healthcare, improving early detection is easier said than done. This executive report provides helpful, actionable guidance about overcoming common barriers (logistical, cultural, and technical) and improving early detection and action by integrating six must-haves:
- Multidisciplinary teams
- Leadership-driven culture change
- Creative customization
- Proof-of-concept pilot projects
- Health Catalyst tools (knowledge briefs, outcomes improvement packets and worksheets, and care process improvement maps).
There’s a formula for success when putting together outcomes improvement projects and organizing the teams that make them prosper. Too often, critically strategic projects launch without the proper planning, structure, and people in place to ensure viability and long-term sustainability. They never achieve the critical mass required to realize substantial improvements, or they do, but then the project fades away and the former state returns. The formula for enduring success follows seven simple steps:
- Take an Outcomes Versus Accountability Focus
- Define Your Goal and Aim Statements Early and Stick to Them
- Assign an Owner of the Analytics (Report or Application) Up Front
- Get End Users Involved In the Process
- Design to Make Doing the Right Thing Easy
- Don’t Underestimate the Power of 1:1 Training
- Get the Champion Involved
Healthcare outcomes improvement can’t happen without effective outcomes measurement. Given the healthcare industry’s administrative and regulatory complexities, and the fact that health systems measure and report on hundreds of outcomes annually, this article adds much-needed clarity by reviewing the top seven outcome measures, including definitions, important nuances, and real-life examples. The top seven categories of outcome measures are:
- Safety of care
- Effectiveness of care
- Patient experience
- Timeliness of care
- Efficient use of medical imaging
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Patients who undergo surgery frequently follow a rehabilitation program afterwards to promote recovery. However, starting this program before the procedure may help further accelerate recovery time. Prehabilitation is defined as physical or lifestyle preparation that happens before surgery and is designed to help patients regain function in less time. Prehabilitation includes the following four main components:
- Medical optimization of pre-existing medical conditions.
- Physical fitness.
- Nutritional status.
- Psychological support.
A healthcare CIO’s role can demand such an intense focus on technology that IT leaders may struggle to find natural opportunities to engage with their C-suite peers in non-technical conversations. To bridge the gap, healthcare CIOs can answer five fundamental questions to better align their programs with organizational strategic goals and guide IT services to their full potential:
- Whom do we serve?
- What services do we provide?
- How do we know we are doing a great job?
- How do we provide the services?
- How do we organize?
As health systems face more pressure than ever to deliver cost savings, they’re turning their attention to cost-per-case improvement projects. These strategies can produce quick wins for improvement teams looking to gain momentum and buy-in. This article addresses the following topics:
- How to identify areas of opportunity.
- The importance of costing accuracy.
- Four strategies for implementing cost-per-case improvement projects.
- Example projects for new teams.
- How to sustain results.
While healthcare waits for the expanded data interoperability that FHIR promises, the industry needs an immediate solution for accessing and using disparate data from across the continuum of care. With FHIR potentially several years away, continuity of care documents (CCDs) are the best option for acquiring the ambulatory clinical care data health systems need to close quality gaps today. Because organizations that rely only on claims data to drive quality improvement risk missing out on more that 80 percent of patient information, CCDs are the current must-have answer to interoperability for successful quality improvement.
In order to thrive in an increasingly challenging healthcare environment, undertaking quality improvement projects is more important than ever for healthcare systems’ continued survival. However, health systems need to tackle the right projects at the right time to maximize the impact to their organization. This article shares both clinical and financial and operational examples of quality improvement in healthcare that may help others as they tackle improvement projects. Some examples shared include:
- Pharmacist-led Medication Therapy Management (MTM) reduces total cost of care.
- Optimizing sepsis care improves early recognition and outcomes.
- Boosting readiness and change competencies successfully reduces clinical variation.
- New generation Activity-Based Costing (ABC) accelerates timeliness of decision support.
- Systematic, data-driven approach lowers length of stay (LOS) and improves care coordination.
- Clinical and financial partnership reduces denials and write-offs by more than $3 million.
Bobbi Brown, MBA, and Stephen Grossbart, PhD have analyzed the biggest changes in the healthcare industry and 2018 and forecasted the trends to watch for in 2019. This report, based on their January 2019, covers the biggest 2019 healthcare trends, including the following:
- The business of healthcare including new market entrants, business models and shifting strategies to stay competitive.
- Increased consumer demand for more transparency
- Continuous quality and cost control monitoring across populations.
- CMS proposals to push ACOs into two-sided risk models.
- Fewer process measures but more quality outcomes scrutiny for providers.
Quality improvement efforts are more important than ever. However, even improvement efforts that have the right people, processes, and technology can struggle to make progress. A medical writer with healthcare knowledge and strong information design skills may be the missing ingredient that can help speed time to adoption and value. This article discusses the functions a medical writer can fulfill, and why they matter. You will also learn:
- The four skills that a medical writer with strong information design skills brings to an improvement team.
- Examples of output of medical writers in a healthcare setting.
- The skills a medical writer needs.
Health systems attempt to measure an ever-increasing amount of clinical measures, these often miss the mark of what matters to patients. Patient-Reported Outcomes (PROs) are the missing link in empowering patients and helping to define good outcomes. This article walks through how patient-reported outcome measures (PROMs) can help identify best practices and drive system-wide quality improvement. PROMs can help health systems do the following:
- Serve as a guide for appropriateness and efficiency.
- Lead to better shared decision-making.
- Demonstrate value and transparency
With an increasing emphasis on value-based care, Accountable Care Organizations (ACOs) are here to stay. In an ACO, healthcare providers and hospitals come together with the shared goals of reducing costs and increasing patient satisfaction by providing high-quality coordinated healthcare to Medicare patients. However, many ACOs lack direction and experience difficulty understanding how to use data to improve care. Implementing a robust data analytics system to automate the process of data gathering and analysis as well as aligning data with ACO quality reporting measures. The article walks through four keys to effectively implementing technology for ACO success:
- Build a data repository with an analytics platform.
- Bring data to the point of care.
- Analyze claims data, identify outliers, including successes and failures.
- Combine clinical claims, and quality data to identify opportunities for improvement.
A robust data analytics operation is necessary for healthcare systems’ survival. Just like any business, the analytics enterprise needs to be well managed using the principles of successful business operations. This article walks through how to run an analytics operation like a business using the following five-question framework:
- Who does the analytics team serve and what are those customers trying to do?
- What services does the analytics team provide to help customers accomplish their goals?
- How does the analytics team know they’re doing a great job and how do they communicate that effectively to the leadership team?
- What is the most efficient way to provide analytics services?
- What is the most effective way to organize?
Many health systems have a hospital capacity problem as demand for patient beds rises. When the supply of usable patient beds can’t meet demand, the negative impact on patients and staff can be significant. Hospitals can solve capacity problems with four key concepts:
- Using data, start with the problem and the ideal solution.
- Be sure the analytics team works with teams throughout the organization—including leadership.
- Have leaders spend time with the operations team to understand workflow.
- Focus on the impact, not the tool.
As healthcare systems are pressured to cut costs and still provide high-quality care, they will need to look across the care continuum for answers, reduce variation in care, and look to emerging technologies. This article walks through how to evaluate the safety and effectiveness and of emerging healthcare technology and prioritize high-impact improvement projects using a robust data analytics platform. Topics covered include:
- The importance of identifying variation in innovation.
- Ways to improve outcomes and decrease costs.
- The value of an analytics platform.
- The reliable information that produce sparks for innovation.
- Identifying and evaluating emerging healthcare technology.
- Knowing what data to use.
- The difference between efficacy and effectiveness in evaluation of emerging healthcare technology.
Health systems continue to prioritize reducing hospital readmissions as part of their value-based payment and population health strategies. But organizations that aren’t fully integrating analytics into their readmission reduction workflows struggle to meet improvement goals. By embedding predictive models across the continuum of care, versus isolated them in episodes of care, health systems can leverage analytics for meaningful improvement. Organizations that integrate predictive models into readmissions reduction workflows have achieved as much as a 40 percent reduction in risk-adjusted readmissions indexes. Effective analytics integration strategies use a multidisciplinary development approach to meet the needs of a patient’s entire care team and deliver common tools for all involved in the patient’s healthcare journey.
Overcrowding in the emergency department has been associated with increased inpatient mortality, increased length of stay, and increased costs for admitted patients. ED wait times and patients who leave without seeing a qualified medical provider are indicators of overcrowding. A data-driven system approach is needed to address these problems and redesign the delivery of emergency care. This article explores common problems in emergency care and insights into embarking on a successful quality improvement journey to transform care delivery in the ED, including an exploration of the following topics:
- A four-step approach to redesigning the delivery of emergency care.
- Understanding ED performance.
- Revising High-Impact Workflows.
- Revising Staffing Patterns.
- Setting Leadership Expectations.
- Improving the Patient Experience.
Current quality measures are expensive and time consuming to report, and they don’t necessarily improve care. Many health systems are looking for better ways to measure the quality of their care, and they are using data analytics to achieve this goal. Data analytics can be helpful with quality improvement. There are four key considerations to evaluate quality measures:
- Organizations must develop measures that are more clinically relevant and better represent the care provided.
- Clinician buy-in is critical. Without it, quality improvement initiatives are less likely to succeed.
- Investment in tools and effort surrounding improvement work must increase. Tools should include data analytics.
- Measure improvement must translate to improvement in the care being measured.
Project management skills and good project managers are increasingly important to the healthcare industry because they can help control costs, manage risk, and speed improvement project outcomes. By applying project management techniques, from waterfall to agile methodologies, organizations can plan, organize, and execute a set of tasks efficiently in order to maximize resources and achieve specific goals. This article explores project management techniques and offers considerations for healthcare leaders when adapting these techniques for clinical, financial, and operational process improvement. The author also shares a pragmatic application and practical tips for implementing these project management techniques in a healthcare environment.