比較効果研究 (CER：Comparative Effectiveness Research) の分析：患者・医師・医療費支払い者の関わる価値の創出
Comparative Effectiveness Research: Value Stories that Engage Patients, Physicians and Payers
|発行||Cutting Edge Information||商品コード||337766|
|出版日||ページ情報||英文 53 Pages
|比較効果研究 (CER：Comparative Effectiveness Research) の分析：患者・医師・医療費支払い者の関わる価値の創出 Comparative Effectiveness Research: Value Stories that Engage Patients, Physicians and Payers|
|出版日: 2015年07月31日||ページ情報: 英文 53 Pages||
当レポートでは、医薬事業者による比較効果研究 (CER：Comparative Effectiveness Research) へのアプローチについて考察し、医療費払い者の要望を満たすためのCERの重要性、CERへの取り組みの体系化・組織化、十分なリソース配置の重要性、専門ベンダーの活用という選択肢、製品の提供価値の伝達の重要性とCERの影響力などについてまとめています。
A number of factors have contributed to the increasing importance of comparative effectiveness research (CER) - along with broader health economics and outcomes research - to payers.
This report is designed to give insight into how companies are approaching CER in the pursuit of meeting payer demands. To that end, many companies have turned to dedicated teams focused on developing CER. When it comes to delivering the all-important value proposition effectively, it is important to utilize the pharmacoeconomic expertise that medical science liaisons (MSLs) and health outcomes liaisons (HOLs) bring to the table. Identifying the appropriate comparators and minimizing potential risk are also key concerns. These can be alleviated with careful planning.
Dedicated comparative effectiveness or health economics teams are the best way to ensure that a product is ready for launch from a market access perspective. These dedicated teams can be involved from early in development to begin planning for what payers will need and how to best position the new product on the marketplace.
In addition to the broad strategic outlook, dedicated groups are able to reach into both prospective studies prior to launch and retrospective studies after launch. This capability ensures a continued portfolio of recent and relevant comparative effectiveness data to present to payers.
For companies that do not have a product portfolio that justifies a dedicated group, teams from medical affairs and managed markets should work closely, especially as a product approaches launch, to coordinate their efforts and ensure that payer needs are met. One interviewed team leader suggests meeting at least weekly to update counterparts on product developments.
For small companies with limited resources, the scale of comparative effectiveness research being requested from some payers can present a significant challenge. Even at larger operations, prioritization of resources often leaves comparative effectiveness close to the bottom of the list until the product is almost launched.
Companies in this position, and even after launch, should be able to find a useful role for specialty, boutique health economics vendors that provide significant value to companies while still returning a high-quality product. Several interviewed team leaders express confidence in the value of these boutique operations that pull heavily on their experience in health economics.
For some therapeutic areas, retrospective database studies in particular present a sizable challenge due to variations in how outcomes are recorded in different healthcare systems. In some cases, studies can be rendered impossible or wholly impractical by these challenges, so specialty therapeutic areas should be aware of these risks. However, in other cases, vendors can again be useful in collecting and then parsing the data down to a useable form that can be then be used in a retrospective study.
Engaging with key stakeholders in the healthcare landscape is a key component to successfully conducting comparative effectiveness research. Many companies have well-established relationships with payers, but other stakeholders involved in the patient care process should be considered and consulted before conducting research.
The model behind this kind of engagement is shown in Figure E.1. Companies should not think of engagement as a binary process of whether or not stakeholders are consulted in decision-making processes. Rather, engagement is a process by which research is affected, and then patient outcomes are improved as a result of that patient engagement.
Develop Engagement Systems to Improve Patient Outcomes
Comparative effectiveness groups may encounter resistance in the engagement process, especially since it is very difficult to measure effectively. Tracking metrics such as the number or duration of contacts with stakeholders may not accurately convey the level of engagement. When they are showing the value of engaging stakeholders, groups should focus on demonstrating stakeholder engagement's impact on the research being conducted.
Among interviewed CER and health economics and outcomes research (HEOR) team leaders, the usefulness of the finished comparative effectiveness product to account managers is a common concern. This potential issue can be addressed in a number of ways. The first tactic is to make sure that the presentation that account managers take to payers has been appropriately streamlined and tailored to match each payer's need. One HEOR director stated that once the payer message had been trimmed down, account managers were more comfortable with presenting the data, and it generated positive feedback from payers.
In cases where the message cannot be streamlined, managed markets teams should be encouraged to work closely with MSL and HOL teams that bring in specialized pharmacoeconomic skillsets. This expertise can provide a significant assist to account managers in the field. Some companies prefer to use these roles in a training capacity, giving account managers guidance on the technical aspects of the payer presentation. For other companies, the partnership may involve MSLs or HOLs accompanying account managers to talk with payers directly.
Overall, CER teams can take steps to make sure that their clinical outputs are being actively utilized in the field. They can make themselves available as a resource throughout the company, ensuring that everyone who could have a use for the data is familiar not only with the data itself, but the process and methodology used to generate it.