The lab has a ‘super-power.’ Clinical laboratory testing data informs up to 70% of medical decisions. The absence or slowness of deployment of data actually impacts patient lives. The Lab 2.0 Movement is a call-to-action to use lab data to drive real-time decisions to identify risks and trends that improve population health. The goal is to super-charge this data so it can predict and chart future directions of patient care in a value-based environment.

Our clinical lab industry leadership is encouraging a national effort to inspire organizations to move beyond the lab virtual walls and help define a higher valuation of laboratory data into the healthcare continuum. The Lab 2.0 Movement is a challenge for laboratories to take charge of their organizations and pioneer new ways of elevating the value of lab informatics to support better patient care and predictive population health management. The 2020 COVID-19 pandemic is a stark reminder of how the clinical laboratory is the backbone of the healthcare system and failure to integrate data into care pathways can have disastrous outcomes. The availability of testing services with the right test at the right time is crucial not only in a crisis but for overall better patient care.

Super-power to super-charge

The goal of Lab v2.0 is to demonstrate increased value of laboratory testing beyond its commoditization. This means that the massive data generated from testing must be harnessed in new ways to not only report the current state of the patient and the  community but used  to predict future patient and populations outcomes. The current coronavirus situations give us a real-life example of why lab testing and the data generated from testing is directly impacting our national and economic welfare. Our science and political leaders are making life-saving decisions based on laboratory testing. The lab data from the Coronavirus pandemic will be used for years to come to predict community out-break hot-spots and what actions need to be taken to mitigate its spread. New serological testing of individual immunity will determine how we interact and conduct our daily lives.

Lab testing is one of the key drivers of actionable data and the basis of programmatic changes for sick care, disease screening, and wellness programs

So, yes, data is a lab’s super power!

Use of auto-verification technology

One of the tenants of super-charging laboratory data in the Lab 2.0 construct is to use current and future technology to leverage the collation of this data into useable data sets.

So – how do labs even start to ‘un-pack’ the meaning of these lofty concepts to actualize the spirit of the Lab 2.0 Movement? What can labs do on a smaller scale to feed into the bigger picture?

One of the most under-utilized yet highly effective technology tools that laboratories can employ is the use of auto-verification rules. The effective use of auto-verification tools as a ‘result qualifier’ and ‘result processer’ can actually transform laboratory operations and the quality of the data output.

However, the use of auto-verification capability is not always used in most labs despite its transformational impact on lab performance on multiple levels. The use of auto-verification once implemented is an immediate positive impact on lab efficiency that is measurable and verifiable.

What is Auto-verification?

The use of software decision rules is called autoverification, which replaces the manual method of lab technologists reviewing results against written lists of review criteria. Without auto-verification rules, labs must rely heavily on written instructions for result review criteria for hundreds of types of tests. Auto-verification eliminates the review of thousands of tests per shift so that technologists can focus on a small number of abnormal results.

What is the process of auto-verification?

Autoverification is a process of using computer-based rules to initially evaluate instrument results and qualify them against a defined set of algorithms established by clinical standards and best practices. Each laboratory defines its own result review criteria based on patient demographics, acuity and clinical specialty. For example, a cancer center that uses a different set of rules vs. a community or university hospital.

Autoverification logic typically includes analytical decisions that filter results by normal or abnormal status on the most basic level. The autoverification rules release normal results directly to the LIS or EHR/EMR without user intervention. Those results that trigger a decision rule logic are held for technologist intervention and further investigation. Example of common rules includes:

• Analytic reference ranges

• Instrument flags (short sample, mechanical errors, linearity, clinical sample artifacts

• Indices (hemolysis, lipemia, icterus)

• Critical result values

• Delta Checks

• Calculations (simple to complex)

• Conditions for re-analysis (repeat, reflex, dilutions, linearity, outliers)

• Addition of comments on test or order level

• LIS processing rules

• QC or other quality rules

• Scripted instructions for patient specific rules
  

  Impact to you:

Auto-verification verifies results without human interaction for faster result deployment to the clinical medical professionals

Where are the auto-verification rules set up and defined?

Typically, autoverification rules are implemented in the LIS (laboratory system) or in software solutions  that connect instrument and the LIS, called middleware. Many instrument vendors now provide rules-based software systems with their instrument or automation system offerings to complement their system configurations. The scope of rules can be split between systems or concentrated in one system – the flexibility of where the rules reside is based on the organization’s instrumentation, informatics capability within the clinical laboratory and functionality of the LIS.

What are the real benefits of auto-verification?

The use of autoverification rules is more efficient and accurate as humans interject their own biases and variances in interpreting and applying review criteria when manually approving patient laboratory results. Auto-verification eliminates common mistakes made by technologists when reviewing and interpreting results.

• Decreased turnaround time (TAT) for post-analytic phase

• Decrease in manual lab test results reviewed by technologists

• Reduction in routine, manual and other time-wasting activities

• Standardization of lab results to a level of quality that is truly ‘predictable’

• Eliminates review of instrument paper print-outs and manual data interpretation

• Reduction in human errors and review bias

• Improvement in ability to adapt to spikes in lab volume

• Reduction in reagent, QC and other consumable costs

Impact to you.

These might be examples of inefficient processes in your lab.

• Normal values review: Why are labs still reviewing them one-by-one? No additional actions are going to result from manual review

• Critical value repeats: Why are labs still repeating critical values? These results are usually time-sensitive, and studies indicate that repeating them does not change the original result. Why delay by repeating them?

• Unnecessary reruns: Why do labs re-run instrument flags to eliminate them? If important flags identify abnormal results, then rerunning results delay results

• Paper management: Reviewing results from instrument print-outs is a redundant activity that has no value resulting in errors, misinterpretation and lost data, not to mention costs related to storing and archiving paper that will never be used again.
  

What types of actionable data can be derived from auto-verification
rules?

The data retrieved from auto-verification rules also has value beyond auto-verification first pass rates (auto-verification rates).  The number and type of rules triggered over time can add to the overall pool of informatic data that can explain or predict future states. Labs can leverage this type of data to develop the next generation of actionable information:

Number of positive or negative rules ‘triggered’ by test or rule type – The incidence and absolute and percentage numbers can describe in patient populations the current rates and predict future incidence when combined with other patient demographic data (acuity, region, ethnicity, etc.)

Example: Monitoring of trend lines of specific tests such as the Coronavirus by rule cut-off values (positive, negative, presumptive positive or negative values).

Trending or shift of a specific rule type in absolute or percentage numbers – A spike or trending up or down of a specific rule can provide ‘insights’ into possible treatment efficacy or treatment plan when longitudinally analyzed.

Example: Monitoring of shift in the number of results for Hemoglobin A1C outside the normal range for a specific patient population. Spikes and trends can help the healthcare organization identify patient populations at risk.

Result Outliers detected by specific or groups of rules that have triggered – By studying specific result and rule outliers, laboratories and their clinical counterparts can start to identify risk factors, disease facts or gaps in care not previously known.

Example: Monitoring of specific result outliers in hematology by instrument flags could point to changes in disease states, emergence of new diseases or efficacies of treatment that could be beneficial or harmful

Auto-verification  - Power tool for your laboratory

The use of auto-verification rules is a tool that so completely transforms your laboratory because it optimizes your laboratory in all three areas of your lab operation – real power to multiply your returns across your laboratory spectrum. It is the one technology you can implement that will impact your laboratory either within or across disciplines so completely that it can impact all facets of your lab business– clinical, operational and financial.

Impact to you.

Clinical:       Higher qualified, predictable and faster result delivery that support patient and population specific driven medicine

Operational:        Minimizes errors, increases test review capacity and quality

Financial:            Increases billable tests capability, reduces lab waste & redundancies

Put on your cape

It is time for you to start moving your lab to the next level – version 2.0. The architects of the Lab v2.0 Movement want labs to move in the direction of producing actionable data of the best and most consistent quality. The use of auto-verification is the power tool  technology that helps you get there. Auto-verification lets you qualify patient results at a higher quality level: consistent, predictable outcomes delivered faster to the care giver.

It is time to put on your cape and explore your laboratory’s ability to take advantage of auto-verification rule opportunities in your LIS, through your instrument vendor or from firms that offer auto-verification solutions.

Each lab should ask how they can take advantage of auto-verification power-tools to move up the value of their laboratory data in the healthcare chain.

Inspire you.

What is your auto-verification rate? What do you want it to be?  Click here to understand how a high auto-verification rate is important to achieve a higher caliber of lab excellence.