A Need for Alignment: How ICER’s New Cost-Effectiveness Framework Compares with the Second Panel’s Recommendations

By Matthew Sussman, MA

Headshot of Matt Sussman

Methodologists in the HEOR community have been busy over the past 9 months. In September 2016, the Second Panel on Cost-Effectiveness in Health and Medicine published a special communication in JAMA (and subsequent hardcover book) that sought to provide guidance for improving the quality of cost-effectiveness (CE) analyses. A few months later in February 2017, the Institute for Clinical and Economic Review (ICER) presented updates to its Value Assessment Framework, which contains its conceptual approach for conducting incremental cost-effectiveness analyses (CEAs). While ICER’s framework sets to guide their internal modeling efforts and makes no claims to influence general modeling principles, HEOR practitioners throughout the industry may turn to ICER’s framework for guidance especially as the organization gains national attention.

With an increasing need to establish value for healthcare spending, HEOR practitioners should be armed with a unified direction for designing, implementing, and reporting CEAs. This blog aims to compare ICER’s new cost-effectiveness framework with the Second Panel’s recommendations.

A Snapshot of the Similarities and Differences

As experienced economic modelers, we tend to frame the design of our CEAs using several model elements, some of which include: Population, Perspective, Time Horizon, Inputs, Outputs, and Analysis. Our review of the similarities between the Second Panel’s recommendations and ICER’s approach follows this framework. Below is a figure that summarizes my opinion. Model elements labeled with a check(“”)  indicate similarities, elements marked with a question (“?”)  indicate a mixed bag of similarities and differences, and elements labeled with an “X” indicate inconsistencies.



The Similarities: A Detailed Review

We found similarities in 4 of the 6 CEA model elements:

Population: Subgroups

The Second Panel recommends conducting subgroup analyses among subpopulations that may experience differential effectiveness from an intervention. Subgroups may be formed based on: differing baseline clinical risk of an outcome, differing expectations of resource consumption (and cost savings) because of an intervention, and/or differing preferences (health utilities) for the relevant outcomes. Inclusion of subgroup analyses may elicit health benefits and/or greater efficiency of resources in at-risk groups, and thus should be considered. While ICER does not specifically recommend subgroup analyses in their updated framework, the organization routinely incorporates subpopulations in their network meta-analyses and CEAs.

Inputs: Drug Prices

The Second Panel recommends using the Federal Supply Schedule (FSS) for determining the cost paid for drugs by US federal agencies. ICER obtains drug pricing data from SSR Health, which provides pricing net of discounts, rebates, and other price concessions. While the proposed sources differ between the two groups, the conceptual approach is the same.

Outputs: QALYs

The Second Panel and ICER recommend that the primary effectiveness measure is quality-adjusted life years (QALYs), leading to an evaluation of incremental costs per QALY gained. In addition to QALYs, ICER proposes to evaluate secondary effectiveness measures such as life years and other clinically-relevant consequences (e.g., strokes averted within atrial fibrillation population).

Analysis: A Single CE Threshold vs. A Range of CE Thresholds

In the healthcare sector reference case, the Second Panel recommends that a range of CE thresholds should be considered. They cite differences between supply side concepts of thresholds (based on limited availability of resources to deliver healthcare) and demand side concepts of thresholds (based on patient willingness to pay for health gains) as the reasons for their recommendation.

ICER proposes to apply their weighted cost-effectiveness threshold, methods described in a previous blog post, in 2 ways: (1) to determine a single drug price needed to achieve the weighted cost-effectiveness threshold, and (2) to determine which drugs represent high vs. low long-term value for money. We take a closer look at both below.

  • Drug prices: ICER defines the value-based price benchmark for a drug as the price that would achieve not only the weighted cost-effectiveness threshold but also each extreme value within the CE threshold range (i.e., $50,000 per QALY, $150,000 per QALY). Based on historical evidence, ICER’s final reports and press releases will present a broad range of prices needed to achieve each threshold value (i.e., the weighted CE threshold, $50,000 per QALY, $150,000 per QALY).
  • Long-term value for money: ICER proposes to use a range, ±$25,000 per QALY from the weighted cost-effectiveness threshold, for evaluating a drug’s long-term value for money. A sample figure can be found below illustrating this. For instance, using the weighted CE threshold as an anchor, ICER will find a lower bound of the CE range by subtracting $25,000 per QALY from the weighted threshold; similarly, to find the upper bound of the range, ICER will add $25,000 per QALY to the weighted threshold. In the sample figure below, using a weighted CE threshold of $110,000 per QALY, the CE threshold range then becomes $85,000-$135,000 per QALY. Similar to NICE’s evaluations, ICER determines that a drug whose calculated CE ratio falls below the lower bound of the range represents “high” long-term value for money, while a drug whose calculated CE ratio falls above the upper bound represents “low” value. A calculated CE ratio in between the lower and upper bounds will be identified as having “intermediate” long-term value for money.


When determining both value-based price benchmarks and long-term value for money, ICER applies a range of CE thresholds, which is consistent with the Second Panel’s recommendations.

The Mixed Bag: A Detailed Review

We found a mixed bag of similarities and differences in 2 of the 6 CEA model elements:

Perspective: Healthcare, Societal

The Second Panel recommends that all studies report a reference case analysis based on the healthcare perspective focusing on direct medical costs reimbursed by third-party payers or paid out-of-pocket by patients. The Panel also recommends a societal reference case capturing broader effects of interventions, such as: time costs of patients in seeking and receiving care, time costs of informal (unpaid) caregivers, transportation costs, effects on future productivity and consumption, costs to the legal or criminal justice system, the cost of interventions on home improvements, production of toxic waste pollution by intervention, and others. ICER also proposes to maintain the health system perspective as the base case, and perform scenario analyses from a societal perspective focused exclusively on work productivity. However, ICER will not likely consider the other societal impacts raised by the Second Panel, stating issues with finding reliable data inputs.

Time Horizon: Short- vs. Long-term

The Second Panel recommends that the time horizon in a CEA should be “long enough to capture all differences” in health effects and costs between interventions. The Panel indicates that the time horizon will be subject to the intervention and therapeutic/disease area under study, and may include the short term, long term (including lifetime), or one that spans generations (e.g., for an intervention that removes environmental toxins). ICER proposes a more rigid approach, one that focuses on the implementation of a long-term perspective, generally the full lifetime of patients.

Summary: How Well Are They Aligned?

After thorough review of both the Second Panel’s recommendations and ICER’s updated framework, we find that the two approaches share consistent methodologies on most of the CEA elements in our checklist and are therefore relatively well aligned. The HEOR community should find resolution on the two elements found to be a mixed bag so that practitioners can base their CE model design and implementation on a single set of unified principles.

How Does ICER’s New Cost-Effectiveness Framework Stack Up to Industry Practice?

By Matthew Sussman, MA

In early February, the Institute for Clinical and EcoHeadshot of Matt Sussmannomic Review (ICER) presented proposed updates to its Value Assessment Framework, based largely on stakeholder feedback received during a public comment period in late 2016. These updates focused on four domains of the framework: (1) comparative clinical effectiveness; (2) incremental cost-effectiveness (CE); (3) other benefits or disadvantages; and (4) contextual considerations. While each domain is important, the incremental CE analysis has proved the most controversial. Since the current comment period is almost up, here’s my review of the updates to the CE framework.

How Does Each Proposed Change Stack Up?

Below is a table I’ve put together to summarize ICER’s proposed updates and to indicate my opinion for the final framework release. The updates that don’t need additional revision are labeled with a check (“”), changes that require additional clarification are marked with a question (“?”), and changes that need major revisions are labeled with an “X”.

ICER Value Framework Updates: No Revisions Needed

Three of ICER’s proposed updates adhere to industry “best” practices today. These include:

  • 3.1 Maintain the primary effectiveness measure
    • The primary effectiveness measure will remain quality-adjusted life years (QALYs), leading to an evaluation of incremental costs per QALY gained.
  • 3.5 Include drug prices net of discounts, rebates, and other price concessions
    • ICER proposes to use drug prices net of discounts, rebates, and other price concessions instead of wholesale acquisition costs in its cost-effectiveness and budget impact analyses.
  • 3.7 Do not project price changes due to patent and exclusivity time horizons
    • ICER proposes to no longer include projections for price changes due to patent and exclusivity time horizons in their CE analyses. Scenario analyses may be conducted if a major change to pricing is anticipated within 12 to 24 months.

As noted in Section 3.1, the QALY is an industry-approved measure for capturing both the quantity and quality of life years generated by healthcare interventions1, and therefore is a natural output for this framework. In Section 3.5, using undiscounted wholesale acquisition costs would overestimate real-world acquisition costs, so applying drug prices net of discounts is a worthwhile change. Likewise, there is tremendous long-term uncertainty regarding market and pricing dynamics, so limiting price changes due to patent and exclusivity time horizons is a reasonable approach in Section 3.7.

ICER Value Framework Updates: Additional Clarification Required

There are also three updates to the new framework that need additional consideration and clarification. These include:

  • 3.2 Use a broader range of cost-effectiveness thresholds
    • For several years, ICER used a range of $100,000 to $150,000 per QALY gained. However, further review of the literature coupled with discussions with stakeholders have led ICER to propose a broader range of incremental CE thresholds between $50,000 and $150,000 per QALY gained.
  • 3.3 Include other effectiveness measures
    • As stated in Section 3.1, ICER will evaluate QALYs as the primary effectiveness measure. In addition to QALYs, ICER proposes to base the denominator of the incremental CE ratio on secondary effectiveness measures such as life years and other clinically-relevant consequences (e.g., strokes averted within atrial fibrillation population).
  • 3.6 Conduct scenario analyses from a societal perspective
    • ICER proposes to maintain the health system perspective as the base case, and perform scenario analyses from a societal perspective focusing on work productivity.

Evaluating an economically-justifiable price based on an incremental CE threshold is a decades-old practice for determining society’s willingness to pay for a new intervention. However, Section 3.2 raises the question as to whether ICER’s lower bound of $50,000 per QALY gained is too low. Based on alternative assumptions and calculations, some experts have indicated this to be the case, and instead have proposed using either $100,000 or $150,000 per QALY gained if a single threshold is desired.2

We mostly agree with the inclusion of effectiveness measures complementary to QALYs in Section 3.3, but caution should be used by ICER. Benchmarks in the literature should be a requirement for comparison to ICER’s incremental cost per consequence output. Without proper and relevant benchmarks, the model output will have no direct comparison, thereby limiting its interpretation.

Similarly, we agree that scenario analyses representing the societal perspective should be assessed in Section 3.6. Yet, ICER modeling teams should carefully consider which populations are most impacted by productivity losses. For instance, in their most recent documentation for the osteoporosis topic, the ICER modeling team indicated that productivity losses would be assessed – in this case, among a starting population of 70-year old postmenopausal women – which is counterintuitive among an elderly population.

ICER Value Framework Updates: Revisions Needed

Two of ICER’s proposed updates raised significant questions and will hopefully be revised and clarified in the final framework. These updates include:

  • 3.4 Conduct scenario analyses to assess the impact of lower health utilities
    • ICER proposes to conduct scenario analyses that compare the impact of lower baseline health utilities among patients with chronic and severe conditions to higher baseline health utilities for the general population. The incremental costs per QALY gained will be compared and the relative difference will be evaluated. If the impact of lower utilities on the incremental CE ratio for the chronic and severe population is substantially different, ICER along with key stakeholders will decide which scenario analysis will serve as the base case.
  • 4 Link ‘other benefits or disadvantages and contextual considerations’ to long-term value for money
    • ICER’s proposed approach for estimating the CE threshold attempts to link ‘other benefits or disadvantages and contextual considerations’ – such as unmeasured patient health benefits, relative complexity of the treatment regimen, impact on productivity, among others – to long-term value for money. The approach contains a modified form of multi-criteria decision analysis (MCDA), in which 10 total elements are considered but not quantitatively weighted to yield an average ranking on a scale from 1-5. The average score will, in turn, be used to assign a single incremental CE ratio benchmark from $50,000-$150,000 per QALY.

ICER Value Framework Section 3.4 Concerns:

The rationale behind this update was not clearly stated and raised a few questions that will need to be addressed in the final framework:

  • What is the rationale for this proposed change? Is it that the patient mix will include patients who are newly diagnosed and thus have baseline utilities closer to the general population?
  • What criteria will be used to decide which scenario analysis serves as the base case?
  • Will literature-based benchmarks be factored into the decision?

This proposed change also raises the issue of sub-group analyses, specifically among at-risk groups (e.g., those with greater disease severity and/or varying patient profiles). Instead of deciding on one scenario analysis that serves as the base case, perhaps sub-group analyses should be conducted in which both scenarios are presented.

ICER Value Framework Section 4 Concerns:

As with Section 3.4, I have a few reservations about the new CE threshold estimate proposed in Section 4. ICER indicated that a single incremental CE ratio will be used to determine a value-based price, as well as an overall value rating, for each intervention under study. This means that ICER’s findings could place additional downward pressure on drug prices. The potential impact of this proposed change on pharma stakeholders cannot be overstated or de-emphasized: your products will be judged against the CE ratio benchmark. For a more detailed review of the new CE Threshold, I recommend a quick read of my previous post, ICER’s New Cost-Effectiveness Threshold Raises 5 Major Questions.

Next Steps For ICER’s Value Assessment Framework

ICER has attempted to address hundreds of pages of comments and suggestions in their Value Assessment Framework, and should be lauded for their efforts. However, several proposed revisions to their incremental CE framework require greater clarification and/or adjustment prior to ratification and implementation. We have submitted our concerns, and look forward to seeing them addressed in the revised framework due out April 15th.

1Weinstein MC, Torrance G, McGuire A. QALYs: The basics. Value Health. 2009 Mar;12 Suppl 1:S5-9.

2Neumann PJ, Cohen JT, Weinstein MC. Updating cost-effectiveness – The curious resilience of the $50,000-per-QALY threshold. N Engl J Med. 2014;371(9):796-797.

Big Changes for HEOR in 2017

By Joe Menzin, PhD.

Headshot of Joe MenzinAs we make our way through the first quarter of 2017, there are a lot of exciting changes happening in the field of health economics and outcomes research (HEOR) that may have important implications for how researchers generate and disseminate evidence.

Here are some of them, in no particular order, with commentaries to follow over the coming days and weeks:

  • Panel on Cost-Effectiveness in Health Care: The long-waited 20th anniversary of the original Gold Report now includes two perspectives: societal and healthcare system. It also includes additional documentation in the form of checklists and inventories.
  • 21st Century Cures Act: New legislative update to FDAMA 114, that expands the use of real-world evidence in the development of dossiers and, potentially, drug labelling.

These major updates and changes should keep the research community busy throughout 2017 and beyond, creating new economic models and expanding the array of observational database studies performed.  There is no better time to be an outcomes researcher!

ICER’s New Cost-Effectiveness Threshold Raises 5 Major Questions

By Matt Susssman, MA

Headshot of Matt SussmanEarly last month the Institute for Clinical and Economic Review (ICER) released a revised Value Assessment Framework for public comment based on feedback received from patients, clinicians, life science companies, and other stakeholders. While a majority of the proposed changes lacked real luster, there is one proposed change that pharma should take note of: the new method for estimating the cost-effectiveness (CE) threshold.

Proposed Method for Estimating Cost-Effectiveness (CE) Threshold

ICER’s proposed approach for estimating the CE threshold attempts to link ‘other benefits or disadvantages and contextual considerations’ – such as unmeasured patient health benefits, relative complexity of the treatment regimen, impact on productivity, among others – to long-term value for money. The approach contains a modified form of multi-criteria decision analysis (MCDA), in which 10 total elements are considered but not quantitatively weighted to yield an average ranking on a scale from 1-5. The average score will, in turn, be used to assign a single incremental CE ratio benchmark from $50,000-$150,000 per quality-adjusted life year (QALY). In particular, ICER proposes the following steps:

Proposed ICER Steps for Cost-Effectiveness Threshold Estimate

Why Should Pharma Care About ICER’s Revised CE Threshold?

The single incremental CE ratio will be used to determine a value-based price, as well as an overall value rating, for each intervention under study. This means that ICER’s findings could place additional downward pressure on drug prices. The potential impact of this proposed change on pharma stakeholders cannot be overstated or de-emphasized: your products will be judged against the CE ratio benchmark.

5 Questions For ICER’s Value Assessment Cost-Effectiveness Threshold

During the ongoing public commentary period, pharma should examine every nook and cranny of ICER’s Value Assessment Framework, especially the new CE threshold estimate, and ask for greater clarity where necessary. As a start, here are our five main questions regarding the new threshold approach:

Question 1: Who are the members of the independent public appraisal committee?

Drug manufacturers will need to understand the backgrounds of those directly impacting the CE ratio benchmark, since their initial decisions may ultimately place pressure on drug prices. In particular, pharma should seek to find out:

  • What are the profiles of the committee members?
  • Will the profiles of each member be made publicly available?
  • Is the committee comprised of clinicians, economists, patient advocacy leaders, and/or payers?
  • How many committee members are there in total, and how many members are from each stakeholder group?

Question 2: Will the case studies be specific to a therapeutic/disease area, or will they be generic across therapeutic/disease areas?

If the goal of the case studies is to inform scoring for each of the 10 elements on a visual analog scale, the case studies will need to be relevant to the therapeutic/disease area under consideration. Otherwise, generic case studies may lead the committee to score the element in an unintended way.

Question 3: Is it appropriate to link selected ‘other considerations’ focused on societal impacts to direct cost per QALY thresholds?

Selected elements, such as ‘impact on productivity’, ‘impact on caregiver burden’, and ‘impact on public health’, are societal constructs. Yet these societal elements will be used, along with other considerations, to determine an overall ranking leading to a direct cost per QALY threshold. If these societal elements are to be used, perhaps they should lead to a direct plus indirect cost per QALY threshold.

Question 4: Are the overall ranking scores of 1-5 referenced and compared across therapeutic/disease areas or similar treatments?

Embedded in their proposed changes, ICER clearly states that the overall ranking score determined by the public appraisal committee “reflects one group’s judgement”, hinting that a second committee may produce a different score. This raises the question as to how ICER could explain differences in scores on the same topic from two hypothetical committees. Perhaps a committee’s score should be compared to past scores in similar therapeutic/disease or product areas, as a means of checks and balances.

Question 5: Is it appropriate to assign a ‘one-size fits all’ threshold range across diseases and treatments?

It is reasonable to expect, as discussed by Drummond and Sorenson1, that the CE threshold may differ depending on the treatments being evaluated or the patient populations being studied. Consider the case of rare diseases, for which orphan or ultra-orphan drugs may not be cost effective and may exceed ICER’s CE range of $50,000-$150,000 per QALY. Payers may still approve coverage of these therapies, irrespective of a high CE ratio, since they are used to treat life-threatening diseases for which other therapeutic options may not be available. Should these drugs, and others used in special circumstances, be held to a different CE range?

ICER’s Value Assessment Framework Comment Period Is Now Open

Although there are many more questions that can and should be asked of ICER regarding proposed changes to its Value Assessment Framework, the cost-effectiveness threshold estimate is the most impactful and controversial and should be given a full review. Take the time and make comments. We’re submitting these questions, but ICER needs more feedback. Once this change and all others have been ratified, ICER will not revisit their methodology until April 2019. Now is your opportunity to inspect, comment, and critique the new CE benchmarking approach before the public commentary period ends on April 3rd, at 5pm ET.

1Drummond M, Sorenson C. Nasty or NICE? A perspective on the use of health technology assessment in the United Kingdom. Value in Health. 2009; 12(2):S8-S13.

2016 Industry Insights: RWE and Centers of Excellence (CoE) Teams Growing

By Jack Fuller, MS

At BHE, we spend a lot of time speaking with leaders in the field of real world data about the ways in which they go about generating robust, reliable evidence for use with key stakeholders both internally and externally.  Fundamentally, it is the unique way that companies combine database experts, processes, and technology that provides the best indication of success.  Below are a few of my thoughts on this topic based on conversations with our clients and industry stakeholders in 2016.

Expansion of Internal Analytics Teams

Along with the growing trend of bringing large datasets in-house, many life science companies are expanding their internal analytics teams to better serve stakeholders who rely on advanced analytics for decision making.  The traditional outsourcing model, while still important, is no longer efficient or cost-effective enough to handle the large volume of requests that health economics, epidemiology, drug safety, and commercial analytics groups receive.  To deal with this paradigm shift, companies are building centralized functions in the form of Real World Evidence (RWE) or Centers of Excellence (CoE) teams. These teams typically have three main responsibilities:

  1. Centralize Real World Data (RWD) assets and tools for analysis
  2. Reduce the friction between groups to generate efficient results
  3. Develop and implement standard methodologies

Finding Talent Is a Challenge

The one thing all the companies I’ve spoken to agree on is that finding talent is extremely difficult. An effectively run data and analytics group requires prioritizing talent who know and understand data, technology, and informatics. However, these skill sets may not apply to many graduates of epidemiology and health economics programs.

Technology Is Key to CoE Success

Technology also plays a key role in any centralized analytics group, especially as expectations increase. One company I recently spoke with anticipates that the number of projects their analytics group is expected to complete will triple in the next three years. Traditional methods of programming become bottlenecks to productivity as the queues for analytics teams continue to grow. Scaling with hard-to-find analysts alone, may not be the entire solution to growth in demand for real-world evidence.

Looking Forward in 2017

Our work with RWE groups provides us with a unique window into industry trends.  We look forward to sharing our knowledge and also learning from others, as new opportunities arise with the 21st Century Cures Act and the proliferation of new, exciting data sources that can be brought to life via technologic advances.

BHE Employee Spotlights – Q1 2017

BHE’s team grew considerably over the past few months. Here’s a look at three of our new team members:

Robert I. Griffiths, MS, ScD: Chief Scientific Officer

headshot of Robert GriffithsDr. Griffiths has over 25 years of experience in outcomes research, including evaluating the comparative effectiveness and cost-effectiveness of medical technologies and practice in clinical trials, and in electronic health record and insurance claims databases.  He has contributed to more than 70 peer-reviewed articles published in medical journals that include the New England Journal of Medicine, JAMA, Cancer, and Blood. Prior to joining BHE, he was a Senior Research Fellow in the Nuffield Department of Primary Care Health Sciences at Oxford University, United Kingdom. Dr. Griffiths received a master’s degree in Science and Technology Studies from Virginia Polytechnic Institute and State University, and a Doctor of Science in Health Policy and Management (concentration health finance) from the Johns Hopkins University Bloomberg School of Public Health.  He is currently completing a Doctor of Philosophy (DPhil) in Evidence-Based Health Care at Oxford University, where he is also a member of Balliol College. In addition, Dr. Griffiths holds a part-time faculty appointment at the Johns Hopkins University School of Medicine, Baltimore, MD.


Rahul Jain, PhD: Senior Manager

Rahul Jain HeadshotDr. Jain’s primary research experience is applied health economics using advanced econometric techniques and he has specialized in pharmacoeconomics, health outcomes research and health policy research. Dr. Jain’s research has also focused on using novel data analytic techniques that address non-random treatment assignment reflecting “real world” treatments patterns within large administrative claims and other databases. Prior to joining Boston Health Economics, Dr. Jain was Research Manager at HealthCore, Inc. and an Assistant Professor at the University of Georgia College of Pharmacy. Dr. Jain has a master’s degree from the Indian Statistical Institute and a PhD in Economics from the State University of New York at Buffalo. He completed his Post-Doctoral fellowship from Department of Pharmaceutical Health Services Research at the University of Maryland Baltimore School of Pharmacy.

Know anyone who would be a good fit for the BHE team?

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Instant Health Data (IHD): Leading the Way in Rapid Analytics for Real-World Data

Written by Jack Fuller, Business Development Manager

Boston Health Economics (BHE), a 19-year-old healthcare analytics firm, is excited to celebrate greater industry use of our leading Instant Health Data (IHD) platform.  Over the past few years, IHD has been transforming the way researchers and analysts interact with real-world data for improved insights.

IHD supports rapid analysis of multiple types of data including claims, claims and laboratory results, electronic medical records, hospital, and integrated data sources. Drawing on a respected team of outcomes researchers, physicians, methodologists, and software engineers, IHD has become a standard analytical tool for life science companies looking to leverage real world evidence (RWE) data assets.  Through extensive adoption and use of IHD, we have learned countless lessons from our clients and partners, with the main focal points being:

  1. People matter. Analytics platforms provide speed of analyses and rapid hypothesis testing capabilities, but there is no tool that can replace the analytic decisions made by clinical and statistical experts.
  2. Benefits of Big Data have been realized for RWE groups. The time is right to leverage advances in computer hardware and software to make optimal use of the wide variety of data assets.
  3. Speed is everything. The move to value based reimbursement has put even more pressure on companies to provide robust analyses to support products like never before. Stakeholders need answers quickly that can impact company bottom lines.

For the past two decades, BHE has worked with large observational datasets to perform retrospective database studies for clients throughout the life science industry.  BHE has constantly been on the cutting edge of utilizing technology to improve the efficiency of our work and has built several tools over the years to improve how we analyze real world evidence. The vision behind IHD was to develop a web-based interface that would remove the technical barriers in transforming data into information that can be shared with key stakeholders.  IHD has been leveraged by companies across the life sciences industry, including many of the top 10 pharmaceutical and medical device companies.

Agile analytics will be the key for companies moving forward, which we will explore in greater detail in future articles to come. If you are interested in learning more about IHD and how it can help your organization complete studies in days instead of weeks or months, please reach out to Jack Fuller at jfuller@bhei.com.

Diabetes Hospitalization

The above is an example of the type of visualization you can build in IHD. This bar chart represents percent of patients who have a Diabetes related hospitalization, stratified by age groupings.

ICD-10: The New Metric System?

At last, the 30+ year old ICD-9 code set has become outdated in the US. No longer considered usable for today’s treatment, reporting, and payment processes, it does not reflect advances in medical technology and knowledge, or provide accurate patient diagnoses.

On October 1, 2015, ICD-10-CM, the 10th revision of the International Statistical Classification of Diseases and Related Health Problems, became effective. Now including 68,000 codes for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or disease, ICD-10-CM has already had a profound impact on daily practice in terms of documentation challenges. In addition, the US also has the ICD-10 Procedure Coding System (ICD-10 PCS), a coding system that contains 76,000 supplementary codes not used by other countries.

So, what implications does ICD-10 have for healthcare analytics?

First, one must consider whether the full range of ICD-10 codes will be used, or just a subset based on convenience.  The clinical work necessary to accurately choose codes may be too overwhelming for busy practitioners, leading to time-saving short-cuts in the form of limited diagnosis code checklists.

Second, just like coding under ICD-9-CM, analysts need to be cautious about the clinical value and accuracy of ICD-10-CM codes. While ICD-9-CM has been using outdated codes that produce inaccurate and limited data, the hope here is that the new ICD-10-CM codes will make it easier to measure the results of treatment and the quality of care.

The structure of the ICD-10 code is as follows:

  • 1-3 (Category of disease)
  • 4 (Etiology of disease)
  • 5 (Body part affected)
  • 6 (Severity of illness)
  • 7 (Placeholder for extension of the code to increase specificity)

To make the conversion from ICD-9 to ICD-10, and sometimes vice versa easier, translation tables have been developed: https://www.cms.gov/medicare/coding/icd10/downloads/gems-crosswalksbasicfaq.pdf

Embrace the change, it’s time to jump on board with the rest of the world.

Will Cost-Effectiveness Save the Day in the USA?

With the 2016 election campaign season fast approaching, conversations about high and rising pharmaceutical prices are moving to the forefront.  This topic, which has always been part of presidential politics — for those of us old enough to remember — has been supercharged of late by concerns over price gouging and downright greed.

The focus has been on individual medications, such as Daraprim, whose price increased from $13.50 per pill to $750 (Wall Street Journal, September 29, 2015), and the market more generally, with prices increasing by 76% from 2010 through 2014 for the top 30 products (WSJ, October 5, 2015). While some newspaper editorials have pointed to the value of innovation, which price controls will presumably stifle, there is surprisingly little discussion of value-for-money.

The privately-funded Institute for Clinical and Economic Review is playing a key, but perhaps less heralded role, in providing guidance on drug pricing through economic analysis, most notably for the new PKSC9 inhibitors for high cholesterol.  While the ICER methods still need refinement, its more rational, value-based approach to drug pricing is clearly better than arbitrary price controls or delisting drugs from formulary altogether.

Perhaps we’ve finally reached the point where economic analysis and value-based purchasing can supplant hyperbole and help turn down the temperature in an overheated election season.

There’s much more to come between now and next November’s election, so stay tuned, and enjoy our newly rebranded newsletter!

You also can learn more about BHE here.