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.
Quality & Process 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.
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.
Additionally, you will learn how to find this unique skill set and where you might find this key person.
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.
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.
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.
The survival of healthcare organizations depends on applying lean principles. Organizations that adopt lean principles can reduce waste while improving the quality of care. By applying stringent clinical data measurement approaches to routine care delivery, healthcare systems identify best practice protocols and incorporate those into the clinical workflow. Data from these best practices are applied through continuous-learning loop that enables teams across the organization to update and improve protocols–ultimately reducing waste, lowering costs, and improving access to care.
This executive report based on a presentation by Dr. Brent James at a regional medical center, covers the following:
How lean healthcare principles can help improve the quality of care.
The steps healthcare organizations need to take to create a continuous-learning loop.
How a lean approach creates financial leverage by eliminating waste and improving net operating margins and ROI.
Control charts are a critical asset to any health system seeking effective, sustainable improvement. With a simple three-line format, control charts show process change over time, including the average of the data, upper control limit, and lower control limit. This insight helps improvement teams monitor projects, understand opportunities and the impact of initiatives, and sustain improved processes.
Also known as Shewhart charts or statistical process control charts, control charts drive effective improvement by addressing three fundamental questions:
What is the goal of the improvement project?
How will the organization know that a change is an improvement?
What change can the organization make that will result in improvement?
Dr. John Haughom explains 5 key Deming processes that can be applied to healthcare process improvement. These include 1) quality improvement as the science of process management, 2) if you cannot measure it, you cannot improve it, 3) managed care means managing the processes of care (not managing physicians and nurses), 4) the importance of the right data in the right format at the right time in the right hands, and 5) engaging the “smart cogs” of healthcare.
By committing to transforming healthcare analytics, organizations can eventually save hundreds of millions of dollars (depending on their size) and achieve comprehensive outcomes improvement. The transformation helps organizations achieve the analytics efficiency needed to navigate the complex healthcare landscape of technology, regulatory, and financial challenges and the challenges of value-based care.
To achieve analytics transformation and ROI within a short timeframe, organizations can follow five phases to become data driven:
Establish a data-driven culture.
Acquire and access data.
Establish data stewardship.
Establish data quality.
Spread data use.
Healthcare is an art and a science. What many in the industry don’t understand is that systems and processes can coexist with personalized care. Quality improvement methods can be as effective in healthcare as they have been in other industries (e.g., agriculture, manufacturing, etc.).
Quality improvement in healthcare is not just achievable, it’s an absolute necessity given the amount of wasteful spending in the U.S. on healthcare. Organizations can reduce this wasteful spending while improving their processes by applying these five guiding principles:
Facilitate adoption through hands-on improvement projects.
Define quality and get agreement.
Measure for improvement, not accountability.
Use a quality improvement framework and PDSA cycles.
Learn from variation in data.
By using these principles and starting small, organizations can quicken the pace of quality improvement in healthcare.
In today’s improvement-driven healthcare environment, organizations must ensure that improvement measures help them reach desired outcomes and focus on the opportunities with optimal ROI. With data science-based analysis, health systems leverage machine learning to determine if improvement measures align with specific outcomes and avoid the risk and cost of carrying out interventions that are unlikely to support their goals.
There are four essential reasons that insights from data science help health systems implement and sustain improvement:
Measures aligned with desired outcomes drive improvement.
Improvement teams focus on processes they can impact.
Outcome-specific interventions might impact other outcomes.
Identifies opportunities with optimal ROI.
Healthcare process improvement leaders not only have to be a jack-of-all-trades, but they need to be a master, as well. This is one of the most important leadership roles in the healthcare system with responsibilities that can ultimately end up saving lives, improving the patient experience, improving caregiver job satisfaction, and reducing costs. Although there are many others, these eight skills are the most critical for the efficient, and ultimately, successful process improvement leader:
Understanding Process Management
Understanding Care Management Personnel
Constructive Accountability and Constructive Conflict
Resiliency and Persistency
Seeing the Big Picture
Along with the right training, education, and sponsorship, it’s easy to see why this role blends many elements of art and science.
Introducing Touchstone: The Next-Generation Healthcare Benchmarking and Opportunity Prioritization Tool
To do healthcare benchmarking effectively and efficiently, healthcare organizations need to know where they’re underperforming, where they’re performing well, and how to focus and prioritize their improvement efforts. They also need a new approach to benchmarking that isn’t limited to the inpatient setting.
The Health Catalyst® Touchstone™ product is the next-generation healthcare benchmarking and prioritization tool that delivers what antiquated benchmarking technologies cannot:
Risk-adjusted benchmarking across the full continuum of care.
Artificial intelligence-powered recommendations.
Ranked lists of improvement opportunities.
Detailed analytics and an intuitive user interface that enable the easy exploration of factors driving performance issues.
Democratized benchmarking that’s available to as many people as the organization wants.
Touchstone was designed with many users and use cases in mind, from population health analysts looking to improve ACO performance to C-suite leaders who need a data-driven approach to prioritizing improvement opportunities.
For healthcare organizations to be successful with their quality and cost improvement initiatives, physicians must be engaged with the proposed changes. But many physicians are not engaged because their morale is suffering. While some strategies to encourage buy-in for improvement initiatives don’t work, there are six strategies that have proven to be effective: (1) discover a common purpose, (2) adopt an engaging style, (3) turn physicians into partners, not customers, (4) segment the engagement plan, (5) use “engaging” improvement methods, and (6) provide them with backup—all the way to the board. Once the organization has their trust, physicians will gain enthusiasm to move forward with improvement efforts that will benefit everyone.
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:
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.
Why Clinicians Are the Missing Link in Healthcare Quality Improvement and Three Principles to Solve the Problem
When it comes to successful quality improvement (QI) in healthcare, clinicians tend to be the missing link. Fortunately, the disconnect between QI initiatives and the day-to-day work of clinicians can be explained and resolved if health systems adopt and embrace three clinician-focused principles:
Principle #1: QI starts at the front line (initiatives should be identified and driven by clinicians).
Principle #2: QI makes it easy for clinicians to do the right thing (removes barriers to good work rather than increasing the amount of work clinicians do).
Principle #3: QI empowers clinicians to adapt care (even if it’s not QI protocol).
Although some clinicians are enthusiastic advocates of their systems’ QI efforts, most are suspicious because they’re frequently cut out of the decision-making process or forced to ignore their best clinical judgement. Health systems that work to close the gap between leaders and clinicians by embracing these three principles will add the missing link—clinicians—back into successful healthcare QI.
For better or worse, hospitals are obligated to collect and report data for regulatory purposes. Or they feel compelled to meet some reputational metric. The problem is, an inordinate amount of time can be spent on what is considered data for accountability or punishment, when the real focus should be on data for learning and improvement. When time, effort, and resources are dedicated to the latter, it leads to real outcomes improvement.
Deming has three views of focusing on a process and this article applies them to healthcare:
Sub-optimization, over-emphasizing a single part at the expense of the whole.
Extreme over-emphasis, also called gaming the system.
The right amount of focus, the only path to improvement.
With data for learning as the primary goal, improving clinical, operational, and financial processes becomes an internal strategy that lifts the entire healthcare system.
The Top Seven Analytics-Driven Approaches for Reducing Diagnostic Error and Improving Patient Safety
From a wrong diagnosis to a delayed one, diagnostic error is a growing concern in the industry. Diagnostic error consequences are severe—they are responsible for 17 percent of preventable deaths (according to a Harvard Medical Practice study) and account for the highest portion of total payments (32.5 percent), according to a 1986-2010 analysis of malpractice claims. Patient safety depends heavily on getting the diagnosis right the first time.
Health systems know reducing diagnostic error to improve patient safety is a top priority, but knowing where to start is a challenge. Systems can start by implementing the top seven analytics-driven approaches for reducing diagnostic error:
Use KPA to Target Improvement Areas
Always Consider Delayed Diagnosis
Diagnose Earlier Using Data
Use the Choosing Wisely Initiative as a Guide
Understand Patient Populations Using Data
Collaborate with Improvement Teams
Include Patients and Their Families
Establishing a healthcare improvement initiative is just the first step toward transformation. The real work of improvement lies in sustaining it, which is why qualified change agent are essential to meaningful progress.
Change agents are trained to lead organizations in:
Case for change
Change management concepts
Cost Benefit Analysis
Health Catalyst’s Accelerated Practices Program gives change agents adaptive leadership training to guide systemwide change within their organizations. They are prepared to meet technical adaptive challenges while keeping teams engaged and productive, and, importantly, to use data analysis to improve quality, cost, and patient satisfaction outcomes.
In pursuit of the Triple Aim, healthcare leaders work hard to improve care, reduce costs, and improve the patient experience. But accomplishing these goals requires an engaged staff that makes progress, day in and day out. Adaptive Leadership (AL) principles help leaders understand human behavior to mobilize change and overcome work avoidance, which happens when staff operate above or below the productive zone of tension.
By understanding what adaptive work actually is (and that adaptive problems can’t be solved with technical fixes), and why work avoidance happens (because people are overwhelmed; the heat is too high), leaders can keep their teams engaged by using influence and leadership—not authority—to “lower the heat” on their people:
Validate the difficulty of the situation.
Simplify/clarify the work.
Provide additional resources (time, training, etc.)
Dr. Ulstad has worked with healthcare leaders and teams for the last 20 years to help them understand behaviors triggered by rapid, high-volume change, and apply AL principles to guide the changes critical to their organizations’ success.
Outcomes improvement is complicated, but we’re beginning to understand what successful quality improvement programs have in common:
Adaptive leadership, culture, and governance
Evidence- and consensus-based best practices
Although understanding the top five essentials for quality improvement in healthcare is key, it’s equally important to understand the most useful definitions and key considerations. For example, how different service delivery models (telemedicine, ACO, etc.) impact quality improvement programs and how quality improvement starts with an organization’s underlying systems of care.
This executive report takes an in-depth look at quality improvement with the goal of providing health systems with not only the top five essentials but also a more comprehensive understanding of the topic so they’re in a better position to improve quality and, ultimately, transform healthcare.
Perceptions of standardization and personalization vary widely by healthcare industry role. Advocates of standardized care say it improves efficiency, outcomes, and patient safety. Advocates of personalization, however, don’t want to see a one-size-fits-all approach become the norm. They want to see a healthcare system in which physicians treat patients like unique individuals.
But what if standardization and personalization didn’t have to be mutually exclusive? What if these historically competitive approaches to care improvement could work together to improve care?
Dr. Corbett describes how health systems can prioritize standardization and personalization using data to bridge the gap. Data enables informed decision making, customized treatment plans, and patient engagement. It supports both standardization and personalization approaches in the ultimate quest for care delivery improvement.
The healthcare industry is currently obsessed with outcome measures — and for good reason. But tracking outcome measures alone is insufficient to reach the goals of better quality and reduced costs. Instead, health systems must get more granular with their data by tracking process measures. Process measures make it possible to identify the root cause of a health system’s failures. They’re the checklists of systematically guaranteeing that the right care will be delivered to every patient, every time. By using these checklists, organizations will be able to improve quality and cost by reducing the amount of variation in care delivery.
IT teams are the guardians of health system data. Their role in quality initiatives in healthcare is undeniable. Yet maximizing IT contributions to quality initiatives requires a shift in IT’s traditional role.
Traditionally supporters of data governance, security, privacy, and access—all important for achieving quality initiatives—IT teams need to do more. They need to integrate five must-haves:
Data best practices
Engaged frontline staff
The industry is up against expanding regulatory requirements that will place high demands on IT teams, including ONC’s goal to reduce the collection and reporting burden on providers. IT teams that embrace these five must-haves are best positioned to create user-centric tools and processes that reduce this burden.