This article was originally published in the 2014, Q3 edition of CLMR.
By Paul L. Epner
Talk to laboratory professionals and you’re likely to hear them lament the extent to which laboratories are devalued within our system of healthcare as well as express concerns over the constant pressure on budgets that inevitably lead to staff cuts. The emerging shift in reimbursement within the United States to bundled payments has led to further concern that those realities will only intensify. Why does the laboratorian’s claim of significant value and plea for increased investment fall on deaf ears? In my opinion, it is because laboratory professionals — and other healthcare professionals — focus too narrowly on technological aspects of the laboratory: quick, accurate and low cost test results. We’re good at those outcomes and continue to try to do better. Our goals target operational efficiency through Lean Six Sigma Initiatives as well as laboratory consolidation, increased centralization of testing, more automation and less dependence on personnel. These are admirable goals, but thus far they have eclipsed the most important part of the testing process: the impact on the patient.
Every factory tries to reduce waste and process defects. And every factory attempts to start with good raw materials and end with final products made according to specification. But in healthcare, this approach leads to serious flaws. Our most critical raw material is a test order, and it is often inappropriate. Our finished product, an accurate test result, often sits unutilized or inappropriately utilized. Instead of operational efficiency within the laboratory, the real value to healthcare from laboratory services should be measured by clinical effectiveness, defined as that which improves patient outcomes.
Presently, laboratory resources are highly skewed toward the former rather than the latter. A major shift is required in healthcare policy and the U.S. healthcare system’s priorities — from cutting laboratory costs to maximizing testing value to laboratories operating like a factory to laboratories becoming a partner in care delivery. According to the IOM (Institute of Medicine, 2012), 30 percent of healthcare spending — $750 billion — is wasted each year. Meanwhile, all of laboratory testing totals only 2.3 percent of healthcare spending (Wolcott, Schwartz, & Goodman, 2008).
Given the relative magnitude of healthcare waste and laboratory spending, healthcare’s financial problem will never be solved through cuts to the laboratory budget. However, by focusing solely on departmental cost reductions, we run many risks. For example, test utilization initiatives that focus solely on financial savings to the department run the risk of reduced appropriate testing. This, in turn, could lead to greater healthcare waste by depriving clinicians of objective data needed for efficient patient care. Support for this perspective can be found in a recent meta-analysis, which established that under-testing occurred twice as frequently as over-testing (Zhi, Ding, Theisen-Toupal, Whelan, & Arnaout, 2013). A major component of maximizing testing value lies in eliminating test-related patient harm (TPH). A recent publication introduces a “five cause model” that identified most sources of TPH (Epner, Gans, & Graber, 2013). The five causes were: 1) an inappropriate test is ordered; 2) an appropriate test is not ordered; 3) an appropriate test result is misapplied; 4) an appropriate test is ordered, but a delay occurs somewhere in the total testing process; and 5) the result of an appropriately ordered test is inaccurate. This model was later expanded to add a sixth cause, iatrogenic harm associated with the testing process itself (Epner, 2014).
CLMA Answers With ICE Initiative
CLMA, in partnership with Orchard Software and The Dark Report, recently announced a new initiative, Increasing Clinical Effectiveness (ICE), intended to catalyze and disseminate practices that can reduce patient harm and improve patient outcomes. All laboratory departments can participate in the initiative by taking the following steps:
1. Determine which of the six causes of TPH you seek to reduce;
2. Determine an intervention that you believe will reduce harm;
3. Determine a plan for implementing the intervention;
4. Determine a plan for measuring the status before the intervention and again after the intervention. Measure the baseline;
5. Implement the plan; and
6. Collect the post-intervention data and analyze the results.
The difference between ICE and other quality improvement initiatives is the focus on patient outcomes and the utilization of measures to gauge impact on patient care. Consider these two examples, both of which come from Dr. Michael Kanter, medical director of quality and clinical analysis for Kaiser Permanente in Southern California. In the first example, Dr. Kanter chose to reduce harm associated with laboratory test results that were either not retrieved or not acted upon appropriately. In one such case, he used data mining techniques to identify all patients in their system that had an abnormal creatinine result without a second result within 90 days. After contacting more than 5,000 such patients and performing a second test on those who responded, more than 1,000 patients were identified with undiagnosed chronic kidney disease (Graber et al., 2014). The first example focused on the improper use of laboratory test results. The second one is focused on the absence of appropriate test ordering. Dr. Kanter used data mining techniques again to identify patients on anticonvulsants for whom no drug monitoring was being conducted. In a two-year period, more than 10,000 patients were identified who had not received appropriate therapeutic drug level monitoring. Once test orders were placed, more than 4,000 patients were tested and over 1,700 were found to have abnormal drug levels (Graber et al., 2014). These examples highlight two important issues. First, “simple” quality improvement projects can be devised that do not require significant expenditures of funds nor bureaucratic procedures such as Internal Review Board (IRB) approval. Second, laboratory professionals have the knowledge and skills to devise practices that can produce significant benefits for patient care. Very little literature currently exists that demonstrates the important role the laboratory can and does play in improving patient outcomes. One goal of the ICE initiative is to increase that body of knowledge by encouraging each laboratory department to implement a project linking its services to patient care, and then share its findings with other laboratories through ICE abstract submissions — as well as administrators and non-laboratorians in their own healthcare system. Such evidence will substantiate for healthcare professionals and policy makers the vital role that the laboratory and laboratory professionals play in improving patient care.
Epner, P. L., Gans, J. E., & Graber, M. L. (2013). When diagnostic testing leads to harm: a new outcomes-based approach for laboratory medicine. BMJ Quality & Safety, 22 Suppl 2(August), ii6–ii10. doi:10.1136/bmjqs-2012-001621
Epner, P. L. (2014). Achieving the Promise of Point-of-Care Testing. Point of Care: The Journal of Near-Patient Testing & Technology, 13(3), 112–113. doi:10.1097/POC.0000000000000022.
Graber, M. L., Trowbridge, R., Myers, J. S., Umscheid, C. A., Strull, W., & Kanter, M. H. (2014). The next organizational challenge: finding and addressing diagnostic error. Joint Commission Journal on Quality and Patient Safety / Joint Commission Resources, 40(3), 102–10. Retrieved from http://www.ingentaconnect.com/content/ jcaho/jcjqs/2014/00000040/00000003/art00002
Institute of Medicine. (2012). Best Care at Lower Cost: The Path to Continuously Learning Health Care in America. (M. Smith, R. Saunders, L. Stuckhardt, & J. M. Mcginnis, Eds.) (p. 450). Washington DC: The National Academies Press. Retrieved from http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:B est+Care+at+Lower+Cost:+The+Path+to+Continuously+Learning+H ealth+Care+in+America#0
Wolcott, J., Schwartz, A., & Goodman, C. (2008). Laboratory Medicine: A National Status Report (p. 385).
Zhi, M., Ding, E. L., Theisen-Toupal, J., Whelan, J., & Arnaout, R. (2013). The Landscape of Inappropriate Laboratory Testing: A 15-Year MetaAnalysis. PLoS ONE, 8(11), e78962. doi:10.1371/journal.pone.0078962