AHRM Blog

Data-Driven Pricing: Supporting Access through Clinical and Economic Endpoints

Posted by Raf Magar on Tue, Oct 22, 2019 @ 02:45 PM

A near-constant headline over the past several years has been the rising cost of healthcare, whether referring to a hospital visit, a novel (or—in some cases—existing) pharmaceutical compound, or cutting-edge surgical procedures. As medical technologies become more advanced, the cost of research and development increases; while at the same time, the economic impact of interventions on payers (whether governmental, commercial, or individual) is a serious concern. How is it possible to balance these forces pushing and pulling on the economic proposition of a medical intervention?

In nearly every developed market, Health Technology Assessment (HTA) agencies are tasked with trying to understand the clinical and economic impact of healthcare interventions. These agencies may be government bodies (such as NICE in the UK and CADTH in Canada) or private institutions (such as ICER in the USA). In any case, they all seek to develop quantitative evaluations of the clinical benefit and economic impact of healthcare interventions. Their evaluations may be directly or indirectly used by payers to influence access or pricing of interventions. Thus, the economic endpoints of budget holders now represent a significant influence on the market access of a medical intervention in addition to the regulatory bodies that over-see clinical endpoints.

With this in mind, companies working to develop healthcare interventions are now tasked with demonstrating a value proposition focused on defensible data-driven pricing. In practice this means performing research that can establish clinical and real-world evidence in support of the pricing for the intervention, and that the economics of the intervention fit within guidelines of the various HTA and the payers they may represent. Accomplishing this requires consideration of health-economic endpoints earlier in the R&D cycle of an intervention so that data such as patient-reported outcomes or other quality-of-life measures can be collected and used to develop defensible and data-driven pricing. In AHRM’s experience, including these data points in Phase II-IV studies is becoming more and more important. In the end, the goal is to anticipate the findings of HTA agencies and develop an early clinical and economic strategy that will minimize friction. 

Bringing an intervention to market without a serious data-driven pricing strategy presents a difficult situation, and doing so opens the door for significant influence of HTA agencies in how the intervention is priced and in some cases if the intervention is granted access or reimbursement in that market at all. There are no shortage of instances in which budget holders simply say that an intervention is too expensive for the clinical benefit it provides and subsequently limiting access.

It is important to note that there is no upper-limit on absolute cost of an intervention. In repeated discussions with HTA and payers, we have learned that expensive treatments and medications are certainly acceptable, but that they must be worth the cost. Interventions costing over USD $1M are no longer a hypothetical, but in order to warrant that price the intervention must deliver a tremendous improvement over the standard-of-care: interventions seeking a premium price should present research that shows a premium benefit to patients and payers.

AHRM’s familiarity with HTA evaluations can provide insight into what analyses they will be looking to perform, what endpoints may be useful to demonstrate patient impact, and how to correspond with HTA about these matters. The ability for AHRM to predict the likely outcomes of HTA evaluations can provide an edge for companies developing a novel intervention or looking to expand access.

For further information or discussion, please contact:

Raf Magar, MBA

rmagar@ahrminc.com

+1-919-758-8203 

Topics: Health Economics, Outcomes Research, HEOR, Clinical Trial, budget impact, Market Access, Drug Pricing

Barriers to Conducting Research: Helping the Private Practice Physician Overcome the Limitations

Posted by Laura Dalfonso on Thu, May 04, 2017 @ 11:28 AM

Practicing physicians have consistently cited three major barriers to conducting independent research and/or participating in industry sponsored research: lack of time, lack of money, and lack of research staff. This is especially true for physicians in private practice without direct access to the type of resources available to those practicing in academic-affiliated institutions. 

Practicing physicians hold patient care as their highest priority and often are unable to devote the time necessary to research funding opportunities, develop conceptual research designs, protocols, and CRFs necessary for conducting research.  This is unfortunate because often these physicians have questions or hypotheses regarding treatment comparisons, potential new indications, and other related research ideas based upon what they witness in real world practice. Following through with such research ideas could contribute to a further understanding of medications, diseases, economic impacts, and patient outcomes. 

All research requires either direct or indirect assets in order to complete the necessary steps to bring it from concept to published results that can be shared with the scientific community, patients, payers, and other interested parties. Once a physician has a research concept, potential funding opportunities need to be identified and applications must be made.  When a source of funding has been secured, a protocol must be written, case report forms designed, and a database built and tested.  The research may require an informed consent, along with IRB submission and a statistical analysis plan. All of this while trying to run a successful practice and keeping the care of patients at the forefront?  Clearly this seems virtually impossible for the practicing private physician, regardless of their desire to conduct research.  

 Opportunities to participate in industry Sponsored research can also present limitations.  The processes of subject screening, obtaining informed consent and completion of case report forms is much too time intensive for the typical physician to simply add it to his/her list of current responsibilities.  When you consider all of this, it quickly becomes apparent just how difficult it can be to do so without a team in place.

We here at AHRM Inc. have witnessed this over the past several years and so we have developed a service to assist physicians who have a strong desire to conduct research. We work to collaborate with them to complete all of the necessary steps to bring their research idea to fruition.  We will assist in procurement of funding, completion and submission of applications, development of protocols, CRFs, informed consent documents, etc.  We can build the database, perform the analysis, train the staff and provide monitoring services.  Our services are provided free-of-charge to the physician and are subcontracted through the funding source(s).  This collaboration allows valuable research to be conducted by helping to break down the barriers faced by private practice physicians.   

If you have an idea for research that you are interested in conducting within your practice, or would like to participate in an industry sponsored opportunity that has been made available, please email (ldalfonso@ahrminc.com)  or call +1(716)994-7912 to schedule an initial discussion.

 

Topics: Real World, Data Management, Clinical Trial, CRF

Clinical Data Management and the Data Manager

Posted by Laura Dalfonso on Mon, Jan 12, 2015 @ 03:59 PM

What is Data Management?

Data Management is a term encompassing various functions and applicable within several industries.   Within the field of research it is often referred to more specifically as Clinical Data Management.   Data Management is an integral part of doing research and can best be described as a process for collecting, validating and reporting the data produced during a clinical trial or other type of research study.   Highly effective Data Management is crucial for the generation of reproducible and reliable study results.     The degree of Data Management will vary from one research effort to another, but all research efforts will require some level of data management prior to the data being analyzed and published.  How the data is to be collected, validated and reported are precisely outlined in a document called the Data Management Plan.   This helps to ensure that the way in which data is reported and collected is consistent among all sites participating in the research effort, as well as the consistency in which the data is analyzed. 

 

What is the role of a data manager?

A data manager is an important member of the research team, whose main priority, is to ensure the integrity of the data that is generated for use during a clinical trial or other research effort.   They can be employed by pharmaceutical or medical device firms, as well as by contract research organizations.  Some large hospitals or clinics may also hire data managers if their involvement in research is great enough to support position(s).  Often data managers at hospitals and clinics have other responsibilities as well; including direct patient care.  For the remainder or this section, we will focus on the responsibilities of data managers employed by either pharmaceutical/medical device firms or by contract research organizations.  

The data manager is charged with a variety of tasks related to developing the processes and procedures for the collection; validation and reporting of the data generated for use during a clinical trial other research effort.   Among these responsibilities, are the development and processing of case report forms (CRF), the identification and generation of necessary logic checks and writing and resolving queries.  Because much of a data manager’s time is spent performing one of these three tasks, we will take a deeper look at each of these. 

Case Report Forms (CRFs) are forms used during a clinical trial or other research effort to collect and report the required subject level data.  They can be in either electronic (eCRF) or paper (CRF) format.   The number of CRFs used for a given research effort will depend on how much data is being collected, what types of data are being collected and how often data is being collected on each subject.  It will also depend on how each form is designed and how much information is included on a single form.  Sometimes a CRF may be designed where data related to Medical History and the results of a Physical exam are combined, while other CRFs separate this information onto two separate forms. 

Logic Checks, as indicated by their name, look for a logical pattern to the data that has been reported on the CRF/eCRF.   They are also referred to as edit checks and are generated to identify errors in the data.  The errors range from simple identification of missing data to more complex issues, like lack of consistency between a data point reported on Form A, for example, and a related data point reported on Form B.  An example of this is that on Form A, the subject’s gender is reported as Male, but on Form B, the results of the screening pregnancy test are reported as negative, instead of not applicable.   They also identify data that is out of range, which means that the value is abnormal and not likely to be true.  An example to this would be a subject who is reported as being 152 years old. 

Writing and resolving queries is often the most time intensive part of a data manager’s job; especially early on in the data collection process.  It is not abnormal for several queries to be written on each CRF submitted for the first several subjects.  Generally speaking, as the research effort progresses, the queries begin to decrease in number because the necessary corrections are made in the collection and reporting process.   Although queries cannot be completely eliminated by the use of eCRFs, they do significantly decrease the number of queries generated, by disallowing certain data to be entered, such as an age of 152 years old, and also requiring that all mandatory fields have been completed in real-time.  

Querying advice for the data manager

When writing queries for research conducted using paper CRFs, double check the Site Number, Subject Number, CRF Title and Question Number before sending the query.  Often there is an error in one of these which makes it unlikely or impossible for the site to answer.  If they are able to determine the correct Site Number, Subject Number, CRF Title or Question Number, it will require unnecessary time that most site staff do not have the luxury of.   These errors will also most likely result in having to send an additional query to the site, for which they will have to again spend time to resolve.   Other helpful tips include:

-          Do not combine queries on separate CRFs into a single query.

-          If a response is to be reported as a predefined value, list the options for the response, such as negative, positive, or not applicable. 

The best advice you can give to a participating hospital or clinic regarding queries, is to complete queries as soon as possible after receiving them.  This will alert them to errors/omissions sooner rather than later, and prevent them from continuing to complete additional forms in a manner that will continue to generate the same queries.  

Topics: Outcomes Research, CRO, Query, Data Management, Clinical Trial, CRF, Validation