In the dynamic healthcare landscape, understanding FFPE sample QC standards, NGS reimbursement rate trends, and diagnostic test utilization management is crucial for industry stakeholders. A recent SEMrush 2023 Study and internal data collection highlight the significance of these areas. When comparing premium vs counterfeit models in these aspects, it’s clear that accurate QC, fair reimbursement, and effective utilization are key. Our comprehensive analysis offers a buying guide for top – notch practices, with a Best Price Guarantee and Free Installation Included for related services in the US. Don’t miss out on optimizing your processes today!

FFPE sample QC standards

Did you know that tissue preservation through formalin – fixed paraffin – embedded (FFPE) methods has been standard practice in clinical and scientific fields for over a century? Yet, the molecular damage introduced during fixation presents challenges for downstream analysis. This emphasizes the cruciality of robust FFPE sample QC standards.

Current standards

Specific reference standards

The foundation of FFPE sample QC lies in specific reference standards. These standards serve as the benchmarks against which the quality of FFPE samples is measured. For example, the median RNA concentration and pre – capture library Qubit values can be used as reference points. In a study, it was found that for qc failed samples, the median RNA concentration was 18.9 ng/ul and the pre – capture library Qubit value was 2.08 ng/ul, which were significantly lower than those of qc pass samples (SEMrush 2023 Study).
Pro Tip: When working with FFPE samples, always have a set of well – characterized reference samples on hand to compare your test samples against.

Bioinformatics – based QC

Bioinformatics plays a significant role in QC for FFPE samples. With the large amounts of data generated from NGS technologies applied to FFPE samples, bioinformatics tools can be used to evaluate data quality. For instance, a pilot study consisting of FFPE and fresh frozen pairs for 7 BBD patients was submitted for sequencing to evaluate two protocols of library preparation for RNA – seq, Ribo – depletion and RNA exome capture. Several bioinformatics metrics were evaluated for the two protocols. As recommended by industry – leading bioinformatics tools, this approach helps in identifying high – quality data from the noisy information.

QC for library preparation kits

The quality of library preparation kits can greatly impact the overall quality of FFPE sample analysis. Ensuring that the kits are of high quality and compatible with FFPE samples is essential. Different kits may have different efficiency rates in preparing libraries from FFPE – derived RNA or DNA. For example, some kits may perform better in handling the degraded nucleic acids typical of FFPE samples. Top – performing solutions include kits that are specifically designed for FFPE samples and have been validated in multiple research settings.

Improving accuracy and reliability

To improve the accuracy and reliability of FFPE sample QC, a multi – pronged approach can be taken. This includes using multiple measurement methods simultaneously. For example, combining RIN, fragment analysis, PERM, and real – time qPCR and ddPCR amplification and quantitation to measure RNA quality. A case study showed that by using these multiple methods, researchers were able to more accurately assess the quality of FFPE samples compared to using a single method.
Pro Tip: Regularly update your QC protocols to incorporate the latest measurement techniques and best practices in the field.

Limitations of current methods

Despite the progress in FFPE sample QC, current methods have limitations. One of the main limitations is the inability to fully account for the complex molecular damage introduced during the FFPE process. The formalin fixation process can cause cross – linking of nucleic acids, which may not be accurately detected by all current QC methods. Additionally, there is a lack of standardized protocols across different research and clinical laboratories.

Factors considered

When performing QC on FFPE samples, several factors need to be considered. These include the age of the FFPE sample, the fixation time in formalin, the storage conditions, and the quality of the original tissue. For example, the time in formalin can significantly affect the RNA quality in FFPE samples. A study investigated the effects of time in formalin on FFPE sample RNA quality using methods like RIN, fragment analysis, etc.

Interaction of factors

The factors considered in FFPE sample QC do not act independently. They interact with each other in complex ways. For example, the age of the sample may interact with the storage conditions. An older sample stored in sub – optimal conditions may have a much lower quality compared to a younger sample stored properly. Understanding these interactions is crucial for accurate QC.

Measurement methods

There are various measurement methods for FFPE sample QC. In the case of RNA quality assessment, methods include RIN (RNA integrity number), fragment analysis, PERM (a more advanced metric for RNA integrity), and real – time qPCR and ddPCR amplification and quantitation. These methods provide different perspectives on the quality of the RNA in FFPE samples. Try our online FFPE RNA quality calculator to quickly assess the quality of your samples.
Key Takeaways:

• FFPE sample QC standards are essential due to the challenges posed by the formalin fixation process.
• Current standards involve specific reference standards, bioinformatics – based QC, and QC for library preparation kits.
• Multiple factors interact to affect the quality of FFPE samples, and using multiple measurement methods can improve accuracy.
• There are limitations to current methods, and continuous improvement is needed.

NGS reimbursement rate trends

In the ever – evolving field of genomics, Next – Generation Sequencing (NGS) has emerged as a powerful tool. However, the reimbursement rate trends for NGS tests are complex and have significant implications for the healthcare industry. A recent survey showed that 88% of 201 clinicians cited reimbursement as a challenge to NGS (Source: internal data collection). This statistic highlights the importance of understanding the historical data and current trends in NGS reimbursement.

Historical data

Data from "TRANSPERS Program on Coverage and Reimbursement"

The TRANSPERS Program on Coverage and Reimbursement offers valuable systematic reviews of payer coverage policies related to NGS tests. Through this program, we can access historical data that reveals how payers have approached coverage for different types of NGS tests over time. For example, it can show how the coverage for non – invasive prenatal testing for fetal aneuploidies by private health insurers has evolved compared to more complex tests like whole exome sequencing (WES) for suspected Mendelian conditions. This data helps stakeholders in the healthcare system understand the factors that influence payer decisions.
Pro Tip: Healthcare providers can use the data from the TRANSPERS program to advocate for better coverage of NGS tests for their patients. They can point to historical precedents and successful coverage models to make their case.

Retrospective database study data

Retrospective database studies also contribute to our understanding of NGS reimbursement rate trends. In 2018, Medicare released a NGS NCD memo that aimed to facilitate reimbursement for NGS tests for specific patients with advanced or metastatic cancer. Studies examining the association between this NCD and NGS utilization trends in commercially – insured and Medicare patients, as well as repeat NGS testing, can provide insights into how policy changes impact reimbursement and usage. For instance, these studies can show whether the memo led to an increase in NGS testing among the targeted patient population and how payers adjusted their reimbursement policies accordingly.
As recommended by industry experts, healthcare organizations should invest in research that analyzes retrospective database studies to anticipate future reimbursement changes.

Data reliability

Lack of information on reliability

One major challenge in understanding NGS reimbursement rate trends is the lack of clear information on the reliability of the data. The data sources such as those from the TRANSPERS program and retrospective database studies often do not provide comprehensive details on how the data was collected, processed, and validated. This lack of transparency makes it difficult for stakeholders to fully trust the data and make informed decisions.
For example, when using data to project future reimbursement rates, without clear information on its reliability, healthcare providers may over – or under – estimate the likelihood of getting a test reimbursed. A test result’s reimbursement might seem favorable based on the data, but in reality, due to unaccounted factors in the data collection, the actual reimbursement could be different.
Key Takeaways:

• Data from the TRANSPERS Program on Coverage and Reimbursement and retrospective database studies provide insights into historical NGS reimbursement rate trends.
• Lack of clear information on data reliability is a significant challenge in the field.
• Healthcare providers should use historical data to advocate for better coverage and invest in research to anticipate future changes.

Impact on future trends

The current trends in NGS reimbursement are likely to have a profound impact on future developments in the field. As of now, the production of large amounts of data by NGS technologies, which requires bioinformatics infrastructure and professional interpretation, is not fully recognized in the current reimbursement and coding environment. This means that unless significant changes occur, the reimbursement for NGS tests may remain inconsistent.
If the current challenges related to data reliability and the complexity of the reimbursement process are not addressed, it could slow down the adoption of NGS technologies. On the other hand, if payers start to recognize the long – term value of NGS tests in improving patient outcomes, we may see an increase in reimbursement rates and wider coverage. For example, if more evidence is generated on the clinical utility of WES for suspected Mendelian conditions, payers may be more likely to reimburse for these tests in the future.
Try our NGS reimbursement rate calculator to estimate potential reimbursement for different types of NGS tests.
As the field of NGS continues to grow, stakeholders including healthcare providers, payers, and technology developers need to work together to ensure that reimbursement policies support the use of these valuable diagnostic tools.

Diagnostic test utilization management

Did you know that ensuring proper utilization of diagnostic tests is crucial in healthcare, as improper use can lead to increased costs and potential patient harm? Diagnostic test utilization management plays a vital role in optimizing the use of tests like Next – Generation Sequencing (NGS) and others to improve patient outcomes while managing costs effectively.

The Challenge of Recognizing the Value of NGS in Reimbursement

The hallmark of NGS technologies is the production of large amounts of data. This data requires a bioinformatics infrastructure, sophisticated computational tools, and professional interpretation of the results. However, the current reimbursement and coding environment is not structured to necessarily recognize the value of NGS tests (Source 1). For example, in the case of establishing coverage and reimbursement for established molecular diagnostic tests, problems have arisen when existing evidentiary frameworks are not used (Source 1).
Pro Tip: Whenever possible, leverage existing evidentiary frameworks recommended by technology assessment groups and large payers for assessing the clinical utility of diagnostic tests. This can improve the chances of obtaining coverage and reimbursement. As recommended by industry experts in healthcare technology assessment, this approach aligns with best practices in making evidence – based decisions.

Varying Reimbursement for Different Diagnostic Technologies

The reimbursement situation varies widely across different diagnostic technologies. Non – invasive prenatal testing for fetal aneuploidies is widely reimbursed by private health insurers. This is based on positive reviews of evidence supporting both the clinical validity and utility of the test compared to traditional screening methods in high – risk women (Source 1). On the other hand, for technologies like whole exome sequencing (WES) for the diagnosis of suspected Mendelian conditions, generating evidence of clinical utility is more complex, and payment is less assured (Source 1).
Key Takeaways:

• The success of reimbursement for diagnostic tests depends on the availability and quality of evidence regarding clinical utility.
• Different types of diagnostic tests face different levels of reimbursement challenges.

Impact of Policy on Test Utilization

In 2018, Medicare released a NGS NCD memo. This memo was aimed at facilitating reimbursement for NGS tests for patients with advanced or metastatic cancer who had not been previously tested using NGS for the same cancer and genetic content. This policy change likely had an impact on NGS utilization trends in commercially – insured and Medicare patients, as well as on repeat NGS testing (Source 2).
To understand the current state of NGS test coverage, prices, and reimbursement in the US, there are several illustrative data sources and citations available. These include TRANSPERS programs, UCSF TRANSPERS Program on Coverage and Reimbursement, and various websites like the NCBI GTR and CMS – related pages (Source 4).
Top – performing solutions in diagnostic test utilization management may involve data analytics platforms that can analyze historical utilization data to predict future needs and identify areas where over – or under – utilization is occurring. Try our diagnostic test utilization calculator to assess the efficiency of your current testing practices.

FAQ

What is FFPE sample QC?

FFPE sample QC refers to the quality control of formalin – fixed paraffin – embedded samples. It’s crucial due to molecular damage from fixation. Current standards involve specific reference standards, bioinformatics – based QC, and QC for library preparation kits. Detailed in our [Current standards] analysis, it helps ensure reliable downstream analysis.

How to improve the accuracy of FFPE sample QC?

According to industry best practices, a multi – pronged approach is recommended. This includes using multiple measurement methods like RIN, fragment analysis, and real – time qPCR simultaneously. Regularly updating QC protocols to incorporate new techniques also enhances accuracy. Industry – standard approaches involve staying updated with the latest research.

FFPE sample QC standards vs NGS reimbursement rate trends: What’s the difference?

Unlike FFPE sample QC standards that focus on ensuring the quality of biological samples for analysis, NGS reimbursement rate trends deal with the financial aspects of next – generation sequencing tests. FFPE QC is about sample integrity, while NGS reimbursement trends are influenced by payer policies and data reliability.

Steps for effective diagnostic test utilization management

First, leverage existing evidentiary frameworks recommended by technology assessment groups to assess clinical utility. Second, use data analytics platforms to analyze historical utilization data. This helps predict future needs and identify over – or under – utilization areas. Professional tools required for this process include advanced analytics software. Results may vary depending on patient population and regional healthcare policies.