A common challenge still faced by many clinical laboratories is the absence of automated processes for extracting and analyzing data recorded in the lab’s LIS. Without an analytics system, laboratory staff often rely on time-consuming manual processes. In other cases, laboratories rely on information technology (IT) departments to compile these reports, which places an additional workload on already busy IT staff.
An analytics system reduces the need for extraordinary laboratory or IT resources and expedites the process of identifying unnecessary testing that is being carried out in the lab. Common categories of unnecessary testing can include tests used for screening and diagnosis as well as those used for reflex testing or patient monitoring. When a patient’s level of thyroid stimulating hormone (TSH) has been tested and found to be normal, for instance, there is no reason to order a test to determine the patient’s free thyroxine (FT4) level, which would be an appropriate reflex test in the case of an abnormal TSH level (see Table 1). An example of redundant testing would be simultaneously ordering tests for the cardiac markers troponin and creatine-kinase myoglobin (CK-MB), both of which are intended to detect damage to the heart muscle, as in the case of a heart attack. Excessive frequency of repeat testing is also a source of unnecessary testing; HbA1c testing to determine a patient’s long-term blood glucose level, for instance, should not be ordered more than once every 21 days. Such regularly ordered but unnecessary tests represent a drain on the financial resources of the health system, and also present a burden to patients who are undergoing tests unnecessarily.
In the table a review of health system utilization of duplicative testing for free thyroxine (FT4) and thyroid stimulating hormone (TSH). One system achieved less than 1% unnecessary FT4 testing; others reflect unsuccessful implementation of test management strategies (education, CPOE guidelines), or no efforts at all.
An analytics system plays a significant role in managing test utilization because it presents a given laboratory’s data in a way that identifies unnecessary testing and helps lab managers locate the areas of greatest opportunity for corrective action (see Figure 1). Using data compiled by the system, for instance, lab managers can establish performance benchmarks such as the number of tests per inpatient admission, length of stay, and length of stay versus tests per admission. Using such data to create benchmarks enables laboratories to develop the strategies necessary to implement an ongoing test utilization program.
Over and under utilization
Both over- and under-utilization of testing are known to have important consequences for patient care and financial performance. In addition to increasing overall costs, overutilization may lead to incorrect diagnoses, time wasted on insignificant abnormal results, longer lengths of stay, and even iatrogenic anemia. In some cases, overutilization results from unbridled ordering of tests for admitted patients—beyond what is recommended in professional guidelines or considered acceptable by payors—meaning that health systems are unlikely to be reimbursed for the costs of such unnecessary testing.
In cases of underutilization, consequences can be exceptionally significant. Serious consequences for patient care include morbidity due to missed or delayed diagnoses, higher pharmacy costs, and legal liabilities. Studies of closed malpractice claims have shown that 48% to 96% of delayed or missed diagnoses resulted from cognitive errors, including lack of knowledge, mistakes in judgment, and lapses in memory.3,4 The most common breakdown in the diagnostic process was failure to order the appropriate diagnostic test (55% to 58% of cases). Finally, missed and delayed diagnoses resulted in harm to patients in 48% to 59% of the cases, and resulted in death in 30% to 39% of the cases.
By way of example, many health systems are now carefully monitoring admitted patients for sepsis, an inflammatory response to bacterial infection that can lead to organ failure and death. In October 2015, the Centers for Medicare and Medicaid Services implemented new guidelines for monitoring and treating sepsis, the severe sepsis and septic shock early management bundle (SEP-1). Health systems that meet the SEP-1 requirements can reduce mortality rates, lengths of stay, and utilization of the intensive care unit. One key element of the SEP-1 guideline specifies that if the patient’s lactate level is ≥2 mmol/L, medical staff should repeat the test within 6 hours. Nevertheless, studies have shown that labs exhibit wide variation in how they observe this particular recommendation for repeat testing.
Using Analytics to improve utilisation
Strategies for Improved Utilization
An analytics system provides the meaningful data needed to identify sources of unnecessary testing so that laboratory managers can improve test utilization. There are a number of strategies that can be used to reduce overutilization of testing, including the placement of hard and soft stops in the computerized physician order entry system, requisition redesign, test formularies, audits, and education.
With the data from an analytics system, laboratory managers will know the most important areas of unnecessary testing so that rules can be developed for the electronic medical record, providing soft-stop guidance to physicians. In the case of expensive genetic testing, for instance, lab managers can block the ordering of a test and have it referred to a specialized genetics counselor for approval. Managers can also use this information to redesign requisitions in order to incorporate professional practice guidelines, limit esoteric tests, or minimize the use of bundled tests. For obsolete tests, such as those for creatine kinase isoenzymes, managers may decide to stop offering the test all together. Updated test formularies can also be created so that general practitioners order from a menu of common tests, while approved specialists order from a menu that includes more expensive, esoteric tests.
Elements of such strategies for improving test utilization are in use at NorDx, Scarborough, Me, a laboratory corporation that supports an integrated delivery system at Maine Health and serves more than a dozen hospital sites, physician practices, and long-term care facilities in Maine, New Hampshire, and Vermont. “Using Visiun’s Performance Insight, we are monitoring our internal hospital physician members as well as external members, including managed care and accountable care organizations,” says Stan Schofield, MS, MT(ASCP), president at NorDx, senior vice president of laboratory services at Maine Health, and managing principal at Compass Group. “Our laboratory experts and medical staff review the utilization rules and determine test frequencies and tests based on the patient’s medical condition.”
While a variety of strategies can be adopted to control unnecessary testing, auditing is the central strategy for addressing underutilization of testing. Without proper auditing, underutilization can go undetected, and in some cases result in serious harm to the patient.
The auditing functionality provided by an analytics system enables laboratory managers to monitor the effects of their strategies to manage test utilization over time. Analytics systems can automatically provide daily performance feedback and an immediate assessment of activities undertaken to improve test utilization. Such automated daily reporting can quickly identify unnecessary testing habits in an organization, reducing the likelihood that weeks’ or months’ worth of test data may go unchecked before being reviewed manually.
An analytics system can generate physician report cards that provide clear and actionable insight and direction on patterns of unnecessary testing. Such report cards identify heavy test users and outliers, and can be used to educate physicians about better test ordering practices. For example, physician ordering patterns can be monitored to generate reports that identify misinterpretations and unnecessary repeat testing. Soft-stop rules can then be built into the electronic medical record to support ordering patterns that reduce excessive frequency of testing, such as repeated HbA1c testing within 21 days.
In Sioux Falls, SD, Avera McKennan Hospital is using Visiun’s Performance Insight to gather the data needed to guide test utilization, including physician ordering practices. “We can track whether our physicians are ordering tests by established best practices and benchmark them with other physicians both internally and across the nation,” says Mike Black, MBA, MT(ASCP), DLM, assistant vice president of the hospital’s clinical laboratory. “The tool allows us to start a data-based discussion about best practices with our physicians. If we can change their habits to align with best practices, that’s good for everyone involved. It could provide better care for our patients while saving money.”
“Managing test utilization allows us to monitor correct test ordering as well as appropriate physician testing patterns,” agrees NorDx’s Schofield. “We have been able to improve our standard of care by using this information to educate physicians and other health system members about the standard of care in the laboratory. Physicians and clinicians that fall short of this standard are flagged.”
As an example, Schofield notes that NorDx monitors how often its physicians order HbA1c tests (see Figure 2). “The medical staff at NorDx use an agreed-upon HbA1c metric,” says Schofield. “We’ve been able to use laboratory analytics as a tool to monitor these patterns and trends for both internal and external physician ordering patterns, and we use that information to educate and set a standard of care that needs to be followed.”
Proper management of test utilization enables health systems to improve their financial performance. An analytics system not only identifies opportunities for immediate cost savings, it can also act longitudinally, enabling laboratory managers to monitor the financial impact of their strategies over time.
Any extent to which laboratories can avoid unnecessary testing represents a contribution to the financial bottom line of the health system. In studies based on audits of client data, we have found that use of an analytics system can result in potential cost savings averaging about $250,000 for every million billable inpatient tests (see Figure 3). For a large health system, that could equate to more than $1 million dollars annually.
Making the shift
Changes in reimbursement policy are increasingly compelling health systems to pay attention to the need for improvements in laboratory test utilization. In turn, managing test utilization requires the development and implementation of best practice protocols that incorporate both analytics and medical expertise. While multiple strategies are needed to improve laboratory test utilization, a laboratory analytics system is key to accomplishing this goal.
In some respects, these challenges faced by laboratory managers are the same for all laboratories, regardless of size. Laboratory and test utilization data may be available, but an analytics system is needed to evaluate the data and identify the best opportunities for improving test utilization while complying with complex and ever-changing guidelines.
To make the best use of the information currently available to a laboratory, a data analytics system often points to the need for a deeper culture shift within the lab. Once this shift is made, laboratories can identify their biggest opportunities to improve test utilization, enabling hospitals and health systems of all sizes to focus resources on the best opportunities to improve their bottom line.