Pathologists and clinical laboratory scientists may find one hospital’s use of a machine-learning platform to help improve utilization of lab tests both an opportunity and a threat
Variation in how individual physicians order, interpret, and act upon clinical laboratory test results is regularly shown by studies in peer-reviewed medical journals to be one reason why some patients get great outcomes and other patients get less-than-desirable outcomes. That is why many healthcare providers are initiating efforts to improve how physicians utilize clinical laboratory tests and other diagnostic procedures.
This effort came about after clinical and administrative leadership at Flagler Hospital realized that only about one-third of its physicians regularly followed certain medical decision-making guidelines or clinical order sets. Armed with these insights, staff members decided to find a solution that reduced or removed variability from their healthcare delivery.
Reducing Variability Improves Care, Lowers Cost
Variability in physician care has been linked to increased healthcare costs and lower quality outcomes, as studies published in JAMA and JAMA Internal Medicine indicate. Such results do not bode well for healthcare providers in today’s value-based reimbursement system, which rewards increased performance and lowered costs.
Clinical order sets are designed to be used as part of clinical decision support systems (CDSS) installed by hospitals for physicians to standardize care and support sound clinical decision making and patient safety.
However, when doctors don’t adhere to those pre-defined standards, the results can be disadvantageous, ranging from unnecessary services and tests being performed to preventable complications for patients, which may increase treatment costs.
“Over the past few decades we’ve come to realize clinical variation plays an important part in the overuse of medical care and the waste that occurs in healthcare, making it more expensive than it should be,” Michael Sanders, MD (above) Flagler’s Chief Medical Information Officer, told Modern Healthcare. “Every time we’re adding something that adds cost, we have to make sure that we’re adding value.” (Photo copyright: Modern Healthcare.)
Flagler’s AI project involved uploading clinical,
demographic, billing, and surgical information to the AyasdiAI platform, which then
employed machine learning to analyze the data and identify trends. Flagler’s
physicians are now provided with a fuller picture of their patients’ conditions,
which helps identify patients at highest risk, ensuring timely interventions that
produce positive outcomes and lower costs.
How Symphony AyasdiAI Works
The AyasdiAI application utilizes a category of mathematics called topological data analysis (TDA) to cluster similar patients together and locate parallels between those groups. “We then have the AI tools generate a carepath from this group, showing all events which should occur in the emergency department, at admission, and throughout the hospital stay,” Sanders told Healthcare IT News. “These events include all medications, diagnostic tests, vital signs, IVs, procedures and meals, and the ideal timing for the occurrence of each so as to replicate the results of this group.”
Caregivers then examine the data to determine the optimal
plan of care for each patient. Cost savings are figured into the overall
equation when choosing a treatment plan.
Flagler first used the AI program to examine trends among their pneumonia patients. They determined that nebulizer treatments should be started as soon as possible with pneumonia patients who also have chronic obstructive pulmonary disease (COPD).
“Once we have the data loaded, we use [an] unsupervised
learning AI algorithm to generate treatment groups,” Sanders told Healthcare
IT News. “In the case of our pneumonia patient data, Ayasdi produced nine
treatments groups. Each group was treated similarly, and statistics were given
to us to understand that group and how it differed from the other groups.”
Armed with this information, the hospital achieved an 80% greater physician adherence to order sets for pneumonia patients. This resulted in a savings of $1,350 per patient and reduced the readmission rates for pneumonia patients from 2.9% to 0.4%, reported Modern Healthcare.
The development of a machine-learning platform designed to
reduce variation in care (by helping physicians become more consistent at
following accepted clinical care guidelines) can be considered a warning shot
across the bow of the pathology profession.
This is a system that has the potential to become interposed
between the pathologist in the medical laboratory and the physicians who refer
specimens to the lab. Were that to happen, the deep experience and knowledge
that have long made pathologists the “doctor’s doctor” will be bypassed.
Physicians will stop making that first call to their pathologists, clinical
chemists, and laboratory scientists to discuss a patient’s condition and
consult on which test to order, how to interpret the results, and get guidance
on selecting therapies and monitoring the patient’s progress.
Instead, a “smart software solution” will be inserted into
the clinical workflow of physicians. This solution will automatically guide the
physician to follow the established care protocol. In turn, this will give the
medical laboratory the simple role of accepting a lab test order, performing
the analysis, and reporting the results.
If this were true, then it could be argued that a laboratory
test is a commodity and hospitals, physicians, and payers would argue that they
should buy these commodity lab tests at the cheapest price.
Centers for Medicare and Medicaid Innovation is considering adding clinical laboratory services to bundled payments in its proposed Oncology Care First model
CMMI, an organization within the Centers for Medicare and Medicaid Services (CMS), is charged with developing and testing new healthcare delivery and payment models as alternatives to the traditional fee-for-service (FFS) model. On November 1, 2019, CMMI released an informal Request for Information (RFI) seeking comments for the proposed Oncology Care First (OCF) model, which would be the successor to the Oncology Care Model (OCM) launched in 2016.
“The inefficiency and variation in oncology care in the
United States is well documented, with avoidable hospitalizations and emergency
department visits occurring frequently, high service utilization at the end of
life, and use of high-cost drugs and biologicals when lower-cost, clinically
equivalent options exist,” the CMMI RFI states.
With the proposed new model, “the Innovation Center aims to build on the lessons learned to date in OCM and incorporate feedback from stakeholders,” the RFI notes.
How the Oncology Care First Model Works
The OCF program, which is voluntary, will be open to
physician groups and hospital outpatient departments. CMMI anticipates that
testing of the model will run from January 2021 through December 2025.
It will offer two payment mechanisms for providers that
choose to participate:
A Monthly Population Payment (MPP) would apply
to a provider’s Medicare beneficiaries with “cancer or a cancer-related
diagnosis,” the RFI states. It would cover Evaluation and Management (EM)
services as well as drug administration services and a set of “Enhanced
Services,” including 24/7 access to medical records.
Of particular interest to medical laboratories, the RFI also
states that “we are considering the inclusion of additional services in the monthly
population payment, such as imaging or medical laboratory services, and seek
feedback on adding these or other services.”
In addition, providers could receive a
Performance-Based Payment (PBP) if they reduce expenditures for patients
receiving chemotherapy below a “target amount” determined by past Medicare
payments. If providers don’t meet the threshold, they could be required to
repay CMS.
Practices that wish to participate in the OCF model must go through an application process. It is also open to participation by private payers. CMS reports that 175 practices and 10 payers are currently participating in the 2016 Oncology Care Model (OCM).
“We want better quality care for patients,” explained Lara Strawbridge, MPH (above), Director of the CMMI Division of Ambulatory Payment Models, during a US Department of Health and Human Services public listening session on Nov. 8. “We hope that at the same time, costs are maintained or reduced.” The new OCF payment model will feature a Monthly Population Payment mechanism that could include reimbursements for medical laboratory services, which has some medical laboratory organizations concerned. (Photo copyright: Center for Medicare and Medicaid Innovation.)
Medical Lab Leaders Concerned about the CMMI OCF Model
One group raising concerns about the inclusion of medical laboratory service reimbursements in the Monthly Population Payment scheme is the Personalized Medicine Coalition. “Laboratory services are crucial to the diagnosis and management of many cancers and are an essential component of personalized medicine,” wrote Cynthia A. Bens, the organization’s senior VP for public policy, in an open letter to CMMI Acting Director Amy Bassano. “We are concerned that adding laboratory service fees to the MPP may cause providers to view them as expenses that are part of the total cost of delivering care, rather than an integral part of the solution to attain high-value care,” Bens wrote.
She advised CMMI to “seek further input from the laboratory
and provider communities on how best to contain costs within the OCF model,
while ensuring the proper deployment of diagnostics and other laboratory
services.”
Members of the coalition include biopharma companies, diagnostic companies, patient advocacy groups, and clinical laboratory testing services. Lab testing heavyweights Quest Diagnostics (NYSE:DGX) and Laboratory Corporation of America (NYSE:LH) are both members.
CMS ‘Doubles Down’ on OCM
The proposal received criticism from other quarters as well. “While private- and public-sector payers would be well served to adopt and support a VBP [value-based payment] program for cancer care, we need to better understand some of the shortcomings of the original OCM design and adopt lessons learned from other successful VBP models to ensure uptake by providers and ultimately better oncology care for patients,” wrote members of the Oncology Care Model Work Group in a Health Affairs blog post. They added that with the new model, “CMS seems to double down on the same design as the OCM.”
Separately, CMMI has proposed a controversial Radiation
Oncology (RO) alternative payment model (APM) that would be mandatory for
practices in randomly-selected metro areas. The agency estimates that it would
apply to approximately 40% of the radiotherapy practices in the US.
These recent actions should serve to remind pathologists and
clinical laboratories that CMS continues to move away from fee-for-service and
toward value-based care payment models, and that it is critical to plan for
changing reimbursement strategies.
Researchers find a savings of more than one million dollars and prevention of hundreds, if not thousands, of adverse drug events could have been had with machine learning system
Support for artificial intelligence (AI) and machine learning (ML) in healthcare has been mixed among anatomic pathologists and clinical laboratory leaders. Nevertheless, there’s increasing evidence that diagnostic systems based on AI and ML can be as accurate or more accurate at detecting disease than systems without them.
Dark Daily has covered the development of artificial intelligence and machine learning systems and their ability to accurately detect disease in many e-briefings over the years. Now, a recent study conducted at Brigham and Women’s Hospital (BWH) and Massachusetts General Hospital (MGH) suggests machine learning can be more accurate than existing clinical decision support (CDS) systems at detecting prescription medication errors as well.
The study was partially retrospective in that the
researchers compiled past alerts generated by the CDS systems at BWH and MGH
between 2009-2011 and added them to alerts generated during the active part of
the study, which took place from January 1, 2012 to December 31, 2013, for a
total of five years’ worth of CDS alerts.
They then sent the same patient-encounter data that generated those CDS alerts to a machine learning platform called MedAware, an AI-enabled software system developed in Ra’anana, Israel.
MedAware was created for the “identification and prevention
of prescription errors and adverse drug effects,” notes the study, which goes
on to state, “This system identifies medication issues based on machine
learning using a set of algorithms with different complexity levels, ranging
from statistical analysis to deep learning with neural networks. Different
algorithms are used for different types of medication errors. The data elements
used by the algorithms include demographics, encounters, lab test results,
vital signs, medications, diagnosis, and procedures.”
The researchers then compared the alerts produced by
MedAware to the existing CDS alerts from that 5-year period. The results were
astonishing.
According to the study:
“68.2% of the alerts generated were unique to
the MedAware system and not generated by the institutions’ CDS alerting system.
“Clinical outlier alerts were the type least
likely to be generated by the institutions’ CDS—99.2% of these alerts were
unique to the MedAware system.
“The largest overlap was with dosage alerts,
with only 10.6% unique to the MedAware system.
“68% of the time-dependent alerts were unique to
the MedAware system.”
Perhaps even more important was the results of the cost
analysis, which found:
“The average cost of an adverse event
potentially prevented by an alert was $60.67 (range: $5.95–$115.40).
“The average adverse event cost per type of
alert varied from $14.58 (range: $2.99–$26.18) for dosage outliers to $19.14
(range: $1.86–$36.41) for clinical outliers and $66.47 (range: $6.47–$126.47)
for time-dependent alerts.”
The researchers concluded that, “Potential savings of $60.67 per alert was mainly derived from the prevention of ADEs [adverse drug events]. The prevention of ADEs could result in savings of $60.63 per alert, representing 99.93% of the total potential savings. Potential savings related to averted calls between pharmacists and clinicians could save an average of $0.047 per alert, representing 0.08% of the total potential savings.
“Extrapolating the results of the analysis to the 747,985
BWH and MGH patients who had at least one outpatient encounter during the
two-year study period from 2012 to 2013, the alerts that would have been fired
over five years of their clinical care by the machine learning medication
errors identification system could have resulted in potential savings of
$1,294,457.”
Savings of more than one million dollars plus the prevention
of potential patient harm or deaths caused by thousands of adverse drug events
is a strong argument for machine learning platforms in diagnostics and
prescription drug monitoring.
Researchers Say Current Clinical Decision Support Systems
are Limited
Machine learning is not the same as artificial intelligence. ML is a “discipline of AI” which aims for “enhancing accuracy,” while AI’s objective is “increasing probability of success,” explained Tech Differences.
Healthcare needs the help. Prescription medication errors cause patient harm or deaths that cost more than $20 billion annually, states a Joint Commission news release.
CDS alerting systems are widely used to improve patient
safety and quality of care. However, the BWH-MGH researchers say the current
CDS systems “have a variety of limitations.” According to the study:
“One limitation is that current CDS systems are rule-based and can thus identify only the medication errors that have been previously identified and programmed into their alerting logic.
“Further, most have high alerting rates with many false positives, resulting in alert fatigue.”
Commenting on the value of adding machine learning
medication alerts software to existing CDS hospital systems, the BWH-MGH
researchers wrote, “This kind of approach can complement traditional rule-based
decision support, because it is likely to find additional errors that would not
be identified by usual rule-based approaches.”
However, they concluded, “The true value of such alerts is
highly contingent on whether and how clinicians respond to such alerts and
their potential to prevent actual patient harm.”
Future research based on real-time data is needed before machine
learning systems will be ready for use in clinical settings, HealthITAnalytics
noted.
However, medical laboratory leaders and pathologists will
want to keep an eye on developments in machine learning and artificial
intelligence that help physicians reduce medication errors and adverse drug
events. Implementation of AI-ML systems in healthcare will certainly affect
clinical laboratory workflows.
By negotiating directly with healthcare providers, employers cut health insurers out of the loop, at least for certain specified healthcare conditions and surgeries
It’s a new trend in how employers provide healthcare benefits for their employees. In order to save money, a growing number of employers are going to low-cost hospitals, physicians, and other providers to contract directly for their services. This may be the opening that allows some clinical laboratories to approach larger employers in their region and negotiate pricing and contract terms without the need to involve a health insurer.
What’s motivating more employers to reach out and contract directly with low-cost healthcare providers is the realization that their health insurance plan typically pays much more than Medicare to hospitals, physicians, clinical laboratories, and other ancillary providers. This fact is supported by a study conducted by the Rand Corporation that found “large employers generally lack useful information about the prices they are paying for healthcare services,” and that of the 1,600 hospitals in 25 states that Rand surveyed, “employer-sponsored health plans paid hospitals an average of 241% of what Medicare would have paid for the same inpatient and outpatient services in 2017,” which is up from 236% of Medicare in 2015, Modern Healthcare reported.
Thus, to better control the skyrocketing cost of healthcare,
and the health benefits plan they offer their employees, employers are
increasingly turning to self-coverage and implementing company benefits plans
that reward employees for price shopping and for selecting the lowest costs
healthcare services.
This trend is another reason why clinical laboratory leaders should be tracking changes in federal price transparency requirements, along with the increased consumer interest in accessing healthcare prices in advance of service.
Employers Negotiate Directly for Healthcare Services
Innovative employer plans to decrease healthcare costs
include:
Contracting directly with medical providers,
Opening primary care clinics within their
corporate facilities,
Referring employees to contracted providers for certain
procedures, and
Creating bundled-payment deals with select
providers.
Modern Healthcare reports that both public and
private employers in five states (Colorado, Connecticut, Michigan, Montana,
Texas, and Wisconsin) are “considering or launching group purchasing
initiatives with narrow- or tiered-network plans, onsite primary-care clinics,
and contracts with advanced primary-care providers,” as well as “direct-contracting
with providers, such as referring employees to designated centers of excellence
for some procedures and conditions under bundled-payment deals with warrantied
results.”
Cheryl DeMars, CEO of The Alliance, a Wisconsin healthcare purchasing cooperative, says there is a movement afoot. “I’m seeing a level of boldness on the part of our members that I haven’t seen before in my 27 years here,” she told Modern Healthcare.
“Almost 100 million employees covered through self-insured plans not only represents a staggeringly large market for healthcare cost containment, it is an extraordinary opportunity for America to meaningfully reduce our national healthcare bill,” Kirk Fallbacher (above), President and CEO of Advanced Medical Pricing Solutions (AMPS) told Healthcare Finance News. (Photo copyright: NextGenRBP.com)
Self-insured Employers can Reduce the Nation’s Healthcare
Bill, says KFF
A 2018 US Census Bureau report states that more than 181 million people in the US were enrolled in employer-sponsored health plans in 2017, and that the estimated average premium for employer-sponsored family coverage increased at an annual rate of 4.5% from 2008 to 2019.
That increase was approximately twice the rate of overall
inflation and growth in average hourly earnings during the same time period, according
to the report, which also states that the surge in premiums was driven by price
increases for medical services and that use of most healthcare services among
employees has actually been declining.
For US employers, “the steep increase in their healthcare
cost crowds out financial resources that could be used for employee wage
increases, capital investments, and other spending priorities, such as
retirement plans,” the report notes.
However, an estimated 94 million of the 156 million workers in the US—approximately 61%—are currently covered under a self-insured medical plan through their employer, the KFF Employer Health Benefits 2019 Annual Survey states.
Healthcare.gov defines the self-insured health insurance plan as a “type of plan usually present in larger companies where the employer itself collects premiums from enrollees and takes on the responsibility of paying employees’ and dependents’ medical claims. These employers can contract for insurance services such as enrollment, claims processing, and provider networks with a third-party administrator, or they can be self-administered.”
“It doesn’t signal the end of the insurance industry,” he
said. “On the cost side of the equation, the PPO approach is beginning to come
to an end. The costs are outstripping inflation and wages.”
Moving to self-insurance is another part of the current trend for price transparency in the healthcare industry and may offer opportunities for clinical laboratories to increase profits. Clinical laboratories and anatomic pathology groups might want to contact the Human Resources Departments of local major employers to educate them on the costs and quality value of their labs. Such a proactive and innovative move could encourage employers to include those labs in the provider networks of their self-insured health benefit plans.
At present, medical laboratories are collecting blood specimens for testing by authorized public health labs. However, clinical laboratories should prepare for the likelihood they will be called on to perform the testing using the CDC test or other tests under development.
“We need to be vigilant and understand everything related to the testing and the virus,” said Bodhraj Acharya, PhD, Manager of Chemistry and Referral Testing at the Laboratory Alliance of Central New York, in an exclusive interview with Dark Daily. “If the situation comes that you have to do the testing, you have to be ready for it.”
The current criteria for determining PUIs include clinical features, such as fever or signs of lower respiratory illness, combined with epidemiological risks, such as recent travel to China or close contact with a laboratory-confirmed COVID-19 patient. The CDC notes that “criteria are subject to change as additional information becomes available” and advises healthcare providers to consult with state or local health departments if they believe a patient meets the criteria.
Bodhraj Acharya, PhD (above), is Manager of Chemistry and Referral Testing at the Laboratory Alliance of Central New York. In an exclusive interview with Dark Daily, he stressed the importance that medical laboratories be prepared. “We need to be vigilant and be active and understand everything related to this virus and the testing. That’s the role of clinical laboratory scientists, to be ready because this can become a pandemic anytime. It can spread and tomorrow the CDC could announce it is disseminating the test to designated laboratories.” (Photo copyright: Laboratory Alliance of Central New York.)
Test Kit Problems Delay Diagnoses
On Feb. 4, the FDA issued a Novel Coronavirus Emergency Use Authorization (EUA) allowing state and city public health laboratories, as well as Department of Defense (DoD) labs, to perform presumptive qualitative testing using the Real-Time Reverse Transcriptase PCR (RT-PCR) diagnostic panel developed by the CDC. Two days later, the CDC began distributing the test kits, a CDC statement announced. Each kit could test 700 to 800 patients, the CDC said, and could provide results from respiratory specimens in four hours.
However, on Feb. 12, the agency revealed in a telebriefing that manufacturing problems with one of the reagents had caused state laboratories to get “inconclusive laboratory results” when performing the test.
“When the state receives these test kits, their procedure is to do quality control themselves in their own laboratories,” said Nancy Messonnier, MD, Director of the CDC National Center for Immunization and Respiratory Diseases (NCIRD), during the telebriefing. “Again, that is part of the normal procedures, but in doing it, some of the states identified some inconclusive laboratory results. We are working closely with them to correct the issues and as we’ve said all along, speed is important, but equally or more important in this situation is making sure that the laboratory results are correct.”
During a follow-up telebriefing on Feb. 14, Messonnier said
that the CDC “is reformulating those reagents, and we are moving quickly to get
those back out to our labs at the state and local public health labs.”
Above is a picture of CDC’s laboratory test kit for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CDC is shipping the test kits to laboratories CDC has designated as qualified, including US state and local public health laboratories, Department of Defense (DOD) laboratories, and select international laboratories. The test kits are bolstering global laboratory capacity for detecting SARS-CoV-2. (Photo and caption copyright: Centers for Disease Control and Prevention.)
Serologic Test Under Development
The current test has to be performed after a patient shows
symptoms. The “outer bound” of the virus’ incubation period is 14 days, meaning
“we expect someone who is infected to have symptoms some time during those 14
days,” Messonnier said. Testing too early could “produce a negative result,”
she continued, because “the virus hasn’t established itself sufficiently in the
system to be detected.”
Messonnier added that the agency plans to develop a serologic test that will identify people who were exposed to the virus and developed an immune response without getting sick. This will help determine how widespread it is and whether people are “seroconverting,” she said. To formulate this test, “we need to wait to draw specimens from US patients over a period of time. Once they have all of the appropriate specimens collected, I understand that it’s a matter of several weeks” before the serologic test will be ready, she concluded.
“Based on what we know now, we believe this virus spreads
mainly from person to person among close contacts, which is defined [as] about
six feet,” Messonnier said at the follow-up telebriefing. Transmission is
primarily “through respiratory droplets produced when an infected person coughs
or sneezes. People are thought to be the most contagious when they’re most
symptomatic. That’s when they’re the sickest.” However, “some spread may happen
before people show symptoms,” she said.
The virus can also spread when people touch contaminated surfaces and then touch their eyes, nose, or mouth. But it “does not last long on surfaces,” she said.
Where the Infection Began
SARS-CoV-2 was first identified during an outbreak in Wuhan, China, in December 2019. Soon thereafter, hospitals in the region “were overwhelmed” with cases of pneumonia, Dr. Acharya explained, but authorities could not trace the disease to a known pathogen. “Every time a new pathogen originates, or a current pathogen mutates into a new form, there are no molecular tests available to diagnose it,” he said.
So, genetic laboratories used next-generation sequencing, specifically unbiased nontargeted metagenomic RNA sequencing (UMERS), followed by phylogenetic analysis of nucleic acids derived from the hosts. “This approach does not require a prior knowledge of the expected pathogen,” Dr. Acharya explained. Instead, by understanding the virus’ genetic makeup, pathology laboratories could see how closely it was related to other known pathogens. They were able to identify it as a Betacoronavirus (Beta-CoVs), the family that also includes the viruses that cause SARS and Middle East Respiratory Syndrome (MERS).
This is a fast-moving story and medical laboratory leaders are advised to monitor the CDC website for continuing updates, as well as a website set up by WHO to provide technical guidance for labs.
This is an opportunity for top-producing sales reps from medical laboratories, anatomic pathology groups, and lab vendors to achieve national recognition at the upcoming Executive War College
Nominations are now open for The Dark Report’s 5th
Annual National Lab Sales Excellence Awards. This awards program recognizes
those laboratory sales professionals who exceed sales goals and successfully
help their lab organization win new clients and expand market share.
Nominating applications are available at Executive War College/5th Annual National Lab Sales Excellence Awards and should be submitted by the sales professional’s sales manager based on the sales rep’s 2019 performance. Winners will receive an all-expense paid trip to New Orleans for the 25th Annual Executive War College on Lab and Pathology Management on April 28-29.
Each winner will also receive a check for $2,000!
“This is the fifth year for this first and only national recognition program in the United States for sales professionals involved in the clinical laboratory profession,” stated Robert L. Michel, Editor-in-Chief of The Dark Report. “It’s important for our industry because it shows the leaders and pathologists in other labs that, despite negative trends in the lab marketplace, there are sales professionals who continue to generate substantial volumes of new clients, new specimens, and new revenue for the clinical labs and pathology groups they represent.
“Moreover, as the sales team in your lab learns what some of
their top-performing peers have accomplished, it raises the bar and motivates
them to achieve more and reach for stretch goals that benefit them personally
and contribute to the success of the lab that they represent,” emphasized
Michel.
“Each year, the winners of the National Lab Sales Excellence
Award tell us that this recognition was not only important for them, but that
their hospital CEO and senior administrators took notice and it raised the
profile of the lab throughout the entire hospital because of the national
recognition for the accomplishments of the lab’s top sales producer. In some
cases, the local newspapers picked up the story and reported it—another
positive benefit for the lab in the community. Some award winners report that
just the news coverage of the award led to new accounts from physicians who
wanted the top service these lab sales professionals deliver.”
Winners are selected in each of three categories that represent
the major sectors of the lab testing marketplace. The sectors are:
Hospital Laboratory Outreach;
Independent Clinical/Anatomic Pathology
Laboratory (including molecular and genetic testing); and
Robert L. Michel, Editor-in-Chief of The Dark Report, is shown above with Tammy W. Mullen, Sales Representative with HealthLab in Aurora, Ill., a full-service, pathologist-directed clinical laboratory that is part of Northwestern Medicine. Mullen received her award during the 2019 Executive War College on Laboratory and Pathology Management in New Orleans. Each year, Laboratory Sales professionals are recognized for their achievements with the National Lab Sales Excellence Award. (Photo copyright: The Dark Report.)
Nominations for National Lab Sales Excellence Awards
“We are asking that the sales managers and sales VPs of
these sales reps nominate their top candidates. Nominations of these
high-achieving medical lab industry sales professionals for the National Lab
Sales Excellence Award are being accepted now. Details and the nominating form
are available by clicking here
or by copy and pasting this URL into your web browser: https://www.executivewarcollege.com/lab-sales-excellence-award-contest/.
To be considered, nominee applications should encompass
actual sales results, feedback from nominating managers, and references from
clients. Lab sales professionals will also be judged on other variables, such
as:
The competitive environment;
Compliance with all state and federal
regulations; and
Ethical behavior.
“A panel of judges will evaluate each nomination,” noted
Michel. “These are individuals with their own impressive track record in sales
and marketing. They understand the techniques of ethical selling, the unique
aspects of marketing laboratory tests, and how much effort is required to build
the number of clients, specimen volume, and revenue from assigned territories.”
It’s the medical laboratory industry’s first and only National Laboratory Sales Award program. Sales representatives employed by clinical laboratories, anatomic pathology groups, specialty molecular and genetic testing lab companies, in vitro diagnostics companies, and laboratory information technology companies will be competing for national recognition as The Dark Report announces the winners of its 5th annual National Lab Sales Excellence Awards during the Executive War College on Laboratory and Pathology Management, which takes place April 28-29, 2020, in New Orleans. (Image copyright: The Dark Report.)
2020 Lab Sales Awards to Be Announced on April 29 in New
Orleans
Nominations for the National Lab Sales Achievement Award are
to be submitted to the offices of The Dark Report by Friday, March 20,
2020. Winners in each of the three categories will be notified by April 3 to
allow them time to make arrangements to travel to New Orleans to be at the
Executive War College for the award ceremony.
“Lab CEOs and hospital/health network lab administrators should recognize how having a winner from their sales team can turbo-charge their entire clinical laboratory sales program,” observed Michel. “By their nature, the 20% of the sales reps in your marketing program who do 80% of the business are highly competitive. We’ve had the sales vice presidents who nominated their top sales producer tell us, a year later, that having a National Lab Sales Excellence Award winner motivated the entire sales team, and that their lab saw substantial increases in specimen volume and revenue because other sales reps wanted to step up to the plate and show what they could produce.”
Michel also took the time to address the long-standing
popular wisdom in the clinical laboratory industry that every lab wants to keep
its top sales producers under wraps, because if competitors knew how much new
lab business they were generating, competitors would recruit them away.
“This is one of those clinical lab industry widely-held beliefs that
needs to disappear,” he explained. “The reality is that, in every community,
competing labs (and competing sales reps) always know who the top producers
are. Good lab leaders know how to retain their top performers and one way to do
that is to boost their reputations and recognize their sales achievements by
nominating these high-energy, result-driven producers for the unique
recognition that comes from the National Lab Sales Excellence Award.”
Lab CEOs, administrators, Sales VPs, and Sales Managers—you can click here to get the nominating form for the 5th Annual National Lab Sales Excellence Awards (or by pasting this URL into your browser: http://www.executivewarcollege.com/wp-content/uploads/National-Lab-Sales-2020-Nomination-Form_02-13-2020.pdf).
