Three national quality improvement leaders on July 30 posted a perspective piece in the Health Affairs Blog, sharing their conclusions on the subject of “High-Value Care Every Time: Recommendations From The National Quality Task Force.” And an absolutely key element of their set of recommendations had to do with optimizing the use of data, and achieving interoperability. The authors of the article were Shantanu Agrawal, M.D, MPhil, president and CEO of the National Quality Forum; Ayesha D’Avena, vice president, strategic planning, at the NQF; and Kenneth W. Kizer, M.D., M.P.H., director of the Institute for Population Health Improvement at UC Davis Health. The Washington, D.C.-based National Quality Forum (NQF), describes itself as “a not-for-profit, nonpartisan, membership-based organization that works to catalyze improvements in healthcare.”
“Despite significant policy efforts and investments in the past two decades, notable shortcomings in the health care system persist,” the authors write in their perspectives article. “Health equity concerns continue to grow, and care is increasingly fragmented and insufficiently person-centered. Although notable progress has been made towards ensuring patients receive high-quality, cost-effective care, this goal remains illusory for too many, and the most feasible strategy to achieve it remains unclear.”
In that regard, they write, “To address these concerns, the National Quality Forum (NQF) launched the National Quality Task Force (the ‘Task Force’) in 2019. The Task Force sought to address systemic limitations and define actionable opportunities to improve delivery system alignment, so that every person in every community consistently receives high-value care by 2030. Through a process that engaged diverse leaders, subject matter experts, innovators, consumers, and patients, the Task Force reflected on challenges that have emerged since the Institute of Medicine (IOM) published its landmark report Crossing the Quality Chasm in 2001. The Task Force’s report, The Care We Need: Driving Better Health Outcomes for People and Communities, affirmed two key points.”
Those two points? “Developments over the past twenty years have not altered the fundamental improvement aims and health system redesign recommendations identified in Crossing the Quality Chasm [the groundbreaking 2001 book authored by the Committee on Quality of Health Care in America, in the Institute of Medicine]. The Task Force did update certain IOM recommendations to reflect current priorities and evidence. For example, the Task Force evolved the IOM aim of ‘patient-centered care’ to ‘person-centered care,’ given the need for health care to promote wellness and equity while treating episodic and chronic illness,” they write. Further, “A second evolution broadens the aim of ‘effective’ care to ‘appropriate’ care, recognizing the growing evidence of harm and waste associated with overuse, underuse, and misuse of health care services.”
Importantly, they write, “In formulating its recommendations… the Task Force considered cross-industry comparisons and included representation from the automotive and aviation industries. Many quality initiatives outside of health care have focused on safety technologies and processes—such as the Toyota Production System, Lean, and High Reliability—that have provided powerful lessons to reduce variations in care, create safety cultures, and reduce serious reportable event rates in health care. Near miss and sentinel event data is routinely shared in aviation, allowing for real time and predictive analytics of potential quality and safety issues.”
The authors emphasize five key strategies: “ensuring appropriate, safe, accessible care”; “implementing seamless flow of reliable data”; “paying for person-centered care and healthy communities”; “supporting activated consumers”; and “achieving actionable transparency.”
Among the “accelerators” the authors list that can help move all of this forward:
Ø Ensure advanced technologies improve safe and appropriate outcomes through the use of a technology evaluation framework;
Ø Expand use of high-value care settings by integrating virtual and innovative care modalities throughout the delivery system;
Ø Improve access to optimal care anywhere by creating pathways to recognize clinical licenses across the country;
Ø Accelerate adoption of leading practices by highlighting exemplar performers;
Ø Cultivate a culturally aligned, value-driven workforce by fostering competencies in safe, appropriate, person-centered care.
The authors note that, in formulating those strategies, “The Task Force drew additional lessons from other industries as well. Perhaps the most significant lesson was the impact of standardized data. Across the financial and transportation sectors, standardized data and financial reporting processes have provided important consumer safeguards and enabled valid, transparent, and benchmarked metrics to reliably compare information across companies. For example, key financial health terms and underlying data—such as earnings per share (EPS) and earnings before interest, taxes, depreciation, and amortization (EBITDA)—are universally defined and audited for validity. Audited financial statements based on standardized terms and data can be easily accessed from the Securities and Exchange Commission and used for a variety of purposes.”
Meanwhile, “By comparison, in the health care sector, multiple definitions may exist for critical terms and measures, undermining peer-comparisons and data analyses. Furthermore, the relevant data may not be readily available. An organization’s accounting system is the hub of financial data, but a unified repository with complete patient data does not exist for health care; data is typically captured in discrete environments with limited interoperability. Electronic Health Records (EHR) are increasingly viewed as the hub of health care data; however, they face challenges in unifying patient data across an increasing number of sources. The lack of standardized data in health care undermines the free flow of data into, out of, and among silos,” the authors emphasize. “This challenge becomes more acute as the number of relevant data sources grows (e.g., condition-specific registries) and as new partners enter the ecosystem (e.g. Community Benefit Organizations that are capturing critical information related to social determinants of health).”
The authors go on to state that “The Task Force consistently identified the need for standardized, reliable, valid data to address challenges and capitalize on opportunities. Similar to financial transactions flowing from accounting systems to audited financial statements, essential patient data captured through disparate points in the clinical workflow should flow seamlessly to meet the needs of various users. Some steps have been taken to help achieve this goal. For example, the 21st Century Cures Act advances interoperability and thereby facilitates data sharing. Likewise, health care organizations and health IT companies are improving health data standardization and addressing problems related to interoperability with the Trusted Exchange Framework and Common Agreement.”
Nevertheless, they emphasize that “[S]olving interoperability problems has been slow. Similar to accounting systems, EHRs may not be suitable for maintaining all data necessary to support both internally focused quality improvement priorities and externally focused, consumer-driven quality analysis.”
And, they add, “Consistent with the 2002 NQF National Framework for Healthcare Quality Measurement and Reporting, the Task Force specified the need to capture accurate data at the point of care to improve data veracity and reduce administrative burden. Timely transparency of valid data is necessary for comparative benchmarking and continuous improvement. Data standardization is also necessary to reduce duplicative measures and administrative burden and bolster measure alignment and development. The Task Force validated the need to align stakeholders to a universal, limited set of identical measures, allowing for additional measure sets as necessary to account for geographic and population-specific variation.”
