New IOM Report on Implementing the Learning Healthcare System

Posted By: Jim Tate September 11, 2012

Informatics Central to a Learning Healthcare System

William Hersh, MD
Professor and Chair, OHSU
 Blog: Informatics Professor

Some of the most important reports for setting the context of the work of informatics have been those from the Institute of Medicine (IOM). These reports have now spanned over 20 years, with many serving to raise awareness of problems and provide a context for informatics solutions. Some of the IOM’s seminal reports have covered the topics of electronic health records [1, 2], telemedicine [3], computer networks and the Internet [4], privacy and security [5], medical errors and patient safety [6, 7], healthcare quality [8], health professions education [9], reducing costs while improving outcomes [10], and safety of health information technology [11].

More recently, these reports have coalesced around the notion of the learning health system, a system that learns from its experiences, incorporates the best science, and provides patient-centered care [12]. Additional reports have focused on issues that heavily involve informatics, such as developing the human and organizational [13] as well as digital [14] infrastructures for the learning healthcare system. The former Chief Science Officer of the Office of the National Coordinator for Health Information Technology tied its efforts to the notion of the learning healthcare system [15].

Best Care at Lower Cost

This past week, the IOM provided another “smash hit” in its series of reports. Entitled, Best Care at Lower Cost, this report notes the urgent need to address both the increasing complexity of the healthcare system as well as its continually increasing costs [16]. The report relates that many industries, from banking to manufacturing to transportation, operate with increasing coordination and efficiency in recent times, especially when aided by modern information technology. Yet healthcare is mired in the past, being highly uncoordinated and excessively labor-intensive.

The full report is available for viewing online and as a downloadable PDF. There are some condensed versions as well, including a report brief, the main recommendations, a list of the characteristics of a continuously learning healthcare system, and an infographic that highlights the main points. An article in JAMA also provides an overview of the report’s motivations, findings, and recommendations [17].

The report asserts that implementing standard practices from those of other industries could result in:

  • Records immediately updated and available for use by patients
  • Care delivered the has been proven “reliable at the core and tailored at the margins”
  • Patient and family needs and preferences are a central part of the decision process
  • All healthcare team members are fully informed about each other’s activities in real time
  • Prices and total costs are fully transparent to all participants in the care process
  • Incentives for payment are structured to “reward outcomes and value, not volume”
  • Errors are promptly identified and corrected
  • Outcomes are routinely captured and used for continuous improvement

These results could be possible now because of human and technological changes that have been adopted in most industries, including:

  • Substantial computational power that is affordable and widely available
  • Network connectivity that allows information to be accessed instantaneously from almost anywhere
  • Human and organizational capabilities that improve the reliability and efficiency of care processes
  • The recognition that effective care must be delivered collaboratively by teams of clinicians and patients, with each playing a vital role in the process

The report was motivated in part by the conclusions of a previous report that noted annual excess costs of care in the US to be around $750 billion (out of $2.5 trillion expended), resulting in approximately 75,000 annual premature deaths. It grouped the causes of this waste and harm as due to:

  • Unnecessary services provided
  • Services inefficiently delivered
  • Prices too high relative to costs
  • Excess administrative costs
  • Missed opportunities for prevention
  • Fraud

Also identified in the report are four “characteristics of a continuously learning healthcare system.” These include:

  1. Science and informatics – real-time access to knowledge and digital capture of the entire care experience
  2. Patient-clinician partnerships – engaged, empowered patients
  3. Incentives – aligned for value with full transparency
  4. Culture – instilled by leadership and with supportive system competencies

The report concludes with a series of recommendations for the continuously learning healthcare system group into three categories (verbatim):

I – Foundational Elements
1. The digital infrastructure. Improve the capacity to capture clinical, care delivery process, and financial data for better care, system improvement, and the generation of new knowledge.
2. The data utility. Streamline and revise research regulations to improve care, promote the capture of clinical data, and generate knowledge.
II – Care Improvement Targets
3. Clinical decision support. Accelerate integration of the best clinical knowledge into care decisions.
4. Patient-centered care. Involve patients and families in decisions regarding health and health care, tailored to fit their preferences.
5. Community links. Promote community-clinical partnerships and services aimed at managing and improving health at the community level.
6. Care continuity. Improve coordination and communication within and across organizations.
7. Optimized operations. Continuously improve health care operations to reduce waste, streamline care delivery, and focus on activities that improve patient health.
III – Supportive Policy Environment
8. Financial incentives. Structure payment to reward continuous learning and improvement in the provision of best care at lower cost.
9. Performance transparency. Increase transparency on health care system performance.
10. Broad leadership. Expand commitment to the goals of a continuously learning health care system.

The Role of Informatics

Informatics is of course central to the notion of the learning healthcare system by capturing, analyzing, and acting on data from the entire spectrum of care. There is another figure in the report that provides a “schematic” of the healthcare system that allows all of the critical informatics challenges and opportunities to be enumerated. This figure shows that the overall patient care experience begins from science, moving to evidence of what from the science improves patient care, followed by the delivery of that best care that will ideally result in the optimal patient outcomes and satisfaction. When any of these elements is carried out suboptimally, there are missed opportunities, waste, and harm. The only additions I would make to this figure would be feedback loops among the elements, i.e., the patient experience informs new science, evidence, and care, while the care experience feeds back to science and evidence, and so forth.

Informatics plays a role in each of these elements as well as the transitions between them. Starting with science, informatics increasingly plays a role in both driving and facilitating science. Informatics allows the science to learn from new discoveries in the data and also helps the scientist manage and analyze that data. It helps the clinical researchers select the best science to select and then evaluate for the evidence. Informatics also allows the best evidence to get implemented as care through methods such as clinical decision support. It also optimizes the care experience through quality measurement and improvement. In addition, informatics engages not only the patient and their caregivers but also other providers through health information exchange. Informatics also provides “safety rails” of sorts through maintaining safety, reducing error, facilitating privacy and security, and promoting adherence to standards. There is really no aspect of informatics that cannot be connected to this schematic.
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By the same token, there is no aspect of informatics that cannot be related in some way to the continuous learning healthcare system. For this reason, this new IOM report presents a vision and all the grand challenges for the entire healthcare system as well as the role of informatics within it. Of course, vision alone is not enough, and we now must turn our attention to implementing it. Encouraging studies and reports are already coming out, such as the learning healthcare system operationalized at Group Health in Seattle [18], coordinated care projects implemented by Medicare to reduce hospital readmissions [19], the “Choosing Wisely” initiative to reduce unnecessary and potential harmful tests and treatments [20], and new science making the vast findings of genomics clinically “actionable” [21]. As with many other IOM reports, this report presents a robust context for the work of informatics to improve health and the healthcare system and points a way forward for doing so.

References

1. Dick, R., Steen, E., et al., eds. (1991). The Computer-Based Patient Record: An Essential Technology for Health Care. Washington, DC. National Academies Press.
2. Dick, R., Steen, E., et al., eds. (1997). The Computer-Based Patient Record: An Essential Technology for Health Care, Revised Edition. Washington, DC. National Academies Press.
3. Anonymous (1996). Telemedicine: A Guide to Assessing Telecommunications in Health Care. Washington, DC. National Academies Press.
4. Anonymous (2000). Networking Health: Prescriptions for the Internet. Washington, DC. National Academies Press.
5. Anonymous (1997). For the Record: Protecting Electronic Health Information. Washington, DC. National Academies Press.
6. Kohn, L., Corrigan, J., et al., eds. (2000). To Err Is Human: Building a Safer Health System. Washington, DC. National Academies Press.
7. Aspden, P., Corrigan, J., et al., eds. (2004). Patient Safety – A New Standard for Care. Washington, DC. National Academies Press.
8. Anonymous (2001). Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC. National Academies Press.
9. Greiner, A. and Knebel, E., eds. (2003). Health Professions Education: A Bridge to Quality. Washington, DC. National Academies Press.
10. Yong, P. and Olsen, L. (2010). The Healthcare Imperative: Lowering Costs and Improving Outcomes – Workshop Series Summary. Washington, DC. National Academies Press.
11. Anonymous (2012). Health IT and Patient Safety: Building Safer Systems for Better Care. Washington, DC. National Academies Press.
12. Eden, J., Wheatley, B., et al., eds. (2008). Knowing What Works in Health Care: A Roadmap for the Nation. Washington, DC. National Academies Press.
13. Olsen, L., Grossman, C., et al. (2011). Learning What Works: Infrastructure Required for Comparative Effectiveness Research. Washington, DC. National Academies Press.
14. Grossman, C. and McGinnis, J. (2010). The Digital Infrastructure for a Learning Health System: Foundation for Continuous Improvement in Health and Health Care – Workshop Summary. Washington, DC. National Academies Press.
15. Friedman, C., Wong, A., et al. (2010). Achieving a nationwide learning health system. Science Translational Medicine, 2(57): 57cm29.
16. Smith, M., Saunders, R., et al. (2012). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. Washington, DC. National Academies Press.
17. Redberg, R. (2012). Getting to best care at lower cost. Archives of Internal Medicine: Epub ahead of print.
18. Greene, S., Reid, R., et al. (2012). Implementing the learning health system: from concept to action. Annals of Internal Medicine, 157: 207-210.
18. Brown, R., Peikes, D., et al. (2012). Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients. Health Affairs, 31: 1156-1166.
20. Cassel, C. and Guest, J. (2012). Choosing wisely: helping physicians and patients make smart decisions about their care. Journal of the American Medical Association, 307: 1801-1802.
21. Feero, W. (2012). Determining actionability of genetic findings in clinical practice. ACP Internist, July/August 2012.

This article post first appeared on The Informatics Professor on September 10, 2012.  Dr. Hersh is a frequent contributing expert to HITECH Answers.