In vitro diagnostics players are being tested as their offerings are increasingly commoditized. Digital diagnostics offers a path to growth
体外诊断产品的商业化之路日渐成熟，数字化诊断是未来的发力点
Growth is slowing in the diagnostics industry as historically unmet demand is being met. This is particularly true in areas such as hematology, clinical chemistry, and immunoassays. Over the past decade, for instance, the price of next-generation sequencing has decreased roughly 100-fold. At the same time, new lower-cost players are entering the market, and the consolidation of health systems and group purchasing organizations is driving down net prices (see sidebar, “Current trends in diagnostics”). Thus, for in vitro diagnostics (IVD) players, simply having a test is no longer sufficient. It’s incumbent on executives to look for the next area of growth.
当前的医疗诊断市场已经趋于饱和，因此相关产业的发展进入到“瓶颈期”，这种现象在血液学、临床化学以及免疫分析等领域尤为明显。在过去的几十年间，二代测序(next-generation sequencing)的价格已经下降了近100倍，更廉价的诊断仪器也纷纷涌入市场，医保制度以及采购部门发布的种种举措都在挤压诊断产品的净利润（见附件“诊断产品的现行趋势”）。因此，对于体外诊断（IVD）企业而言，仅能实现“检测”功能是远远不够的，公司高层必须寻求新的发展机遇。
A great place to look is digital diagnostics, which combines data and analytics with traditional IVD testing to generate new clinical insights and more-efficient workflows. McKinsey research shows that select digital markets adjacent to diagnostics, including clinical decision support, remote patient monitoring, and population health management, are projected to outgrow the core diagnostics market over the next several years (Exhibit 1). Of course, this value is not only for IVD players to capture. Other players, such as health tech and data companies, are also eyeing the space. However, as developers of data-generating equipment are already being integrated into key clinical workflows, IVD companies have a right to play and could potentially use their position to become key stakeholders in the healthcare delivery ecosystem.
数字化诊疗是将传统IVD产品检测的数据和分析结果进行整合，最终为临床方案的制定提供新的视角，整个工作流程更加高效，因此可以为IVD产业的发展助一臂之力。麦肯锡（McKinsey）调查报告显示，在未来的几年，与诊断相结合的数字经济（比如：临床决策支持、远程患者监控、以及健康管理）会推动其核心市场的发展。当然，除了IVD，其他领域的企业（比如：医疗科技以及数据公司）对数字诊疗板块也跃跃欲试。但是，由于数据设备的开发人员已经将数据处理板块嵌入到临床工作的关键流程中，因此，IVD公司在数字化诊疗领域有先发优势，而且在未来医疗保健系统中有可能成为核心决策者。
The question is, where are the best opportunities? And how can IVD players move quickly to capture them? In this article, we discuss these questions and suggest some next steps for IVD manufacturers making the move to digital diagnostics.
问题在于机遇在哪？以及IVD企业该如何快速得捕捉到这个机遇？在这篇文章中，我们对这些问题进行讨论，并且给IVD企业提供了实现这个愿景的步骤。
Current trends in diagnostics
诊断行业的当前趋势
Diagnostics is moving from its traditional back-office, pay-for-service role to a critical stakeholder role within the healthcare delivery ecosystem. Three main shifts occurring today give digital and analytics the chance to play a part in transforming the in vitro diagnostics (IVD) industry:
诊断行业正在从传统的后台付费服务方，向医保系统的关键角色进行转变。当前发生的三个主要转变，使得数据分析工作在体外诊断行业的发展和转型中发挥重要作用。
Improving the diagnostic tests themselves. Health systems are anticipating two main improvements in diagnostics. The first is providing true measurement metrics for outcome-based healthcare. This means going beyond a simple result (for example, hemoglobin A1c is above the normal range) and tying it to key outcomes (X points of reduction in HbA1c means Y fewer complications for patients). The second is bringing these measurements forward to clinicians as insights rather than just as results, applying local context, trends, and patient-specific data points to help clinicians make more-accurate care decisions.
诊断服务的改善。卫生部门希望诊断产品在以下两个方面有所提升：首先，由于医疗工作是以结果为导向，因此诊断产品的测量指标必须能反映真实问题。诊断产品不能只给出一个简单的结果（比如：糖化血红蛋白的含量高于平均水平），而是要给出一个关键性的结论（比如：患者体内糖化血红蛋白的减少意味着发生并发症的概率较低）；其次，对于临床医生而言，诊断结果给出的意见要具有指导性，包括当前本地发病状况、发病趋势以及患者的个性化情况，这些都有助于临床医生做出更为精准的诊疗方案。
Transforming care delivery. Diagnostics sits at the center of clinical decision making and therefore is a critical component of enabling care delivery in the future. There are three main elements of future care delivery, the first of which is new care models, such as home and virtual care. As health systems evolve these care models, diagnostics will have to define new workflows and tests that enable remote care without sacrificing quality. The second trend in care delivery is an increased focus on prevention. This necessitates new IVD tests that can help screen patients more accurately and in a cost-effective manner. For example, a molecular colon-cancer screening test powered by algorithms could improve accuracy and enable earlier detection. Finally, personalized medicine (selecting the right treatment based on patient data) will be critical to improving care delivery. Here, IVD players will need to screen new diagnostic panels that will allow physicians to select the right therapy among increasing options for patients.
医疗服务方式的转变。诊断能为医疗决策提供帮助，因此在未来医疗服务中的地位非常重要。未来的医疗服务主要由三大板块构成，其一是新型监护模式，比如远程居家监控。由于卫生系统部门不断完善监护模式，因此诊断相关的工作流程和测试产品也需要不断得更新，以保证在不牺牲检测性能的前体下实现远程监控；其二是防控工作更加受到重视。这就要求新型诊断产品具有更高的检测性能，而且医疗方案成本更低。比如：由算法主导的分子肠癌检测技术可以提高结果的准确度并且能提早发现癌症；其三是个性化用药（指根据患者的情况进行个性化治疗）对于医疗服务质量的改善至关重要。可供患者使用的治疗方案眼花缭乱，因此急需能够帮医生做出精准决策的产品。
Expanding the remit of diagnostics within healthcare. Broader applications of diagnostic tests beyond disease identification will generate tremendous impact, both for IVD players and for society. The most vivid example of this is that diagnostics can be used as a primary line of defense for future pandemics and related health emergencies (such as bio threats). Furthermore, diagnostics can increase the efficiency and effectiveness of drug development. This allows for more-targeted medical therapies as well as companion diagnostics to identify patients who are most likely to benefit from a specific treatment or who are at risk of an adverse event due to a therapy, enabling the selection of a more appropriate alternative.
扩大诊断在医疗服务领域中的应用范围。除了疾病诊断外，将诊断产品应用于其他领域将对IVD企业及社会都会产生很大的影响。比如，诊断产品对流行病以及卫生突发事件（例如生物入侵）都有防控作用。而且，诊断提高了药物研发的速度和效率。多靶点药物联合伴随诊断结果，可以帮助医生筛选出某种治疗方案的适应性或者不适应人群，从而能够选择最合适的替代方案。
New digital diagnostics solutions must provide value that health system leaders can easily understand—for example, clearly improving patient outcomes. So while better sensitivities and specificities are great, incremental improvements in these metrics often do not translate into better outcomes because of factors such as inefficiencies within the patient treatment journey and the natural fluctuations of many biomarkers, which limit the diagnostic impact of a test. Instead, ensuring the appropriate use of a diagnostic test and facilitating its interpretation—and, where necessary, applying patient- and population-specific context—can lead to a greater improvement in outcomes. Therefore, the first step in exploring digital diagnostics is to define where an IVD manufacturer can provide differentiated clinical value. Potential ways to do this exist across the patient journey, including developing screening tests that use local data, providing long-term health tracking and personalized treatment suggestions, and developing algorithms for companion diagnostics.
对于医疗系统领导人而言，新型数字化诊断方案体现的临床价值必须是通俗易懂的，比如：某产品可以改善患者的结局。由于患者随访信息缺失或者某些生物标志物稳定性差等原因，有些产品的灵敏度和特异度虽然很好，但临床最终结局的效果并不好。因此，正当使用诊断产品，突出临床价值（必要情况下，提供针对个体或者群体的应用环境），才能改善临床最终结局。因此，数字化诊疗探索的第一步是要确定IVD产品在哪个领域可以提供差异化临床价值，这个问题可以在患者治疗过程中寻找到答案，比如可以基于当地患者数据开发出筛查工具，为患者提供长期的健康追踪或者个性化治疗建议，以及伴随诊疗算法的开发等。
While stand-alone use cases may be sufficient, multiple use cases across the patient journey often need to come together to deliver value. Consider cholesterol testing, which currently occurs at various points across a patient’s health journey. A physician then translates the test results into cardiac risk based on a score (often the Framingham criteria). Digital diagnostics can use that risk to assess overall health across the longer term, tracking not just cholesterol but also other blood tests and results. Based on that profile, digital tools can provide tailored recommendations for patients and track those outcomes, resulting in better care. Delivering this end-to-end value requires multiple use cases—patient- and population-adjusted insights, long-term health tracking and personalized treatment suggestions, and at-home diagnostics and monitoring. Diagnostic players, therefore, have to think differently about how to piece together the right use cases and participate more broadly in the health journey, whether organically or through partnerships and M&A.
当前单一诊断指标的产品在市场上可能趋于饱和，而在患者治疗过程中更需要多指标联合的产品。比如在患者健康管理中胆固醇检测就包含多个指标。有医生将这种检测结果转换成心血管患病风险分数值（即弗雷明汉标准）。数字化诊断产品对胆固醇及其他血管情况进行追踪分析，最后基于分数高低对患者的整体情况进行评估。因此，数字化工具可以为患者提供个性化治疗意见，并基提供更好的监管服务。要达到这一目的需要多方面的努力，包括患者或人群情况的洞察，长期健康追踪，个性化治疗意见的输出，以及居家式诊断和监控的实现。因此，IVD企业无论是进行组织框架调整、合作还是并购其他企业，都必须想方设法将这些关键步骤融合在一起，并参与到医疗服务的更多领域中。
Integrate effortlessly into clinical workflows将诊断集成到临床工作流程中
New tests and solutions would benefit from either being integrated seamlessly into existing workflows or through introducing simpler, more efficient workflows. With today’s healthcare environment facing worker shortages and burnout, health systems will not be interested in adopting new diagnostics systems that create more work for the organization.
如果将新型诊断产品及流程无缝嵌入到现有的工作流程中，或者引入更简单高效的工作流程，那么绝对会大受欢迎。随着当前医疗卫生环境面临劳动力短缺的问题，卫生系统对于那些需要更多人手的新型诊断系统并不感兴趣。
Imagine a new solution for prevention: an at-home test that screens for various common pathologies such as the flu, COVID-19, and strep. All the workflows would need to be in place for this system to be adopted. Data would need to be connected to electronic medical records, appropriate telehealth connections (synchronous or asynchronous) would need to be made, and insights or reports that physicians could easily digest would need to be generated. IVD players may not be able to own all the workflow components (such as telehealth), and they will need to carefully assess where and how to participate to ensure smooth workflows and maximum adoption.
请想象下新的疾病防控场景：居家检测就可以得知是否感染流行病，比如：流感病毒，新冠肺炎病毒以及链球菌。要实现这个目的，所有的工作流程必须做到位——数字化的电子医疗记录，相应的远程医疗连接平台（同步或者不同步均可）以及通俗易懂的报告解读。IVD企业可能不具备所有的操作模块（比如远程医疗），他们需要做的是对参与的环节及实施的步骤进行仔细评估，以确保整个工作顺利进行并被大众所接受。
Be cost-effective for health systems
对于医疗系统而言，必须是低成本的
Cost should be a top priority, especially in the near term given inflationary pressures on health systems. IVD players need to be able to communicate hard cost-effectiveness metrics—such as costs of materials and required personnel—to healthcare practitioners (HCPs), laboratories, and other customers.
成本是首要考虑因素，特别是通货膨胀也给医疗卫生系统带来了资金压力。对于面向医疗使用者、实验室以及其他客户的产品而言，IVD企业在生产的各个环节都要严格控制成本（比如原材料以及劳动力成本）。
How to play within digital health ecosystems
如何参与到数字化医疗系统中？
IVD players can choose not only where in the patient journey to add value but also how best to deliver digital diagnostics in these areas. These players are well positioned to lead across each type of delivery, but the value of digital varies depending on the type of IVD data generated and the type of offering that an IVD player provides. Certain types of offerings have more value for certain types of data (Exhibit 3).
至于参与到疗程的哪个环节以及怎样将数字化诊断产品传达给用户，IVD企业都有一定的选择权。但由于IVD数据类型的不同以及提供的方式不同，数字化诊断的价值也不一。使用格式统一的数据才能挥产品的最大价值。
Data collection. Many IVD players are already collecting data. How can they best leverage it? Broadening connectivity across IVD devices to enable centralized, standardized data collection could provide more-powerful data sets to run analytics, understand trends, and manage populations holistically across sites of care. This is particularly valuable for lab players that can generate massive amounts of data across the population.
数据收集。许多IVD企业已经开始收集数据。那怎样才能利用好这些数据呢？
增强IVD设备的连通性，对收集的数据进行集中统一处理，这样才能进行基于大数据的分析、进行趋势解读并对跨院区的患者进行管理。对于实验室人员而言，基于群体的大数据信息是非常珍贵的。
Data integration. IVD players may not have all the data required to pursue a key use case, so they may need to look at options for combining data sources—either through acquiring data or by acting as middleware (for example, connecting software). Acting as an integrator can then unlock new use cases, whether directly for IVD manufacturers (see the following section on data products) or for customers (for example, payers and health systems) that are eager to acquire larger, more-complete, and more-comprehensive health data sets. The value of data integration increases as more of the patient journey is connected, with diagnostic data being among the most critical components.
数据整合。IVD企业所具有的数据可能还不足以解决某一关键性问题。但他们可以向他人发起请求或者作为中间机构（比如：连接软件）获得数据，最后将多种数据进行合并。对于IVD企业以及客户（包括消费者还是卫生系统），将数据集整合起来意味着能解决更多的问题，毕竟大家都急需更全面且综合性的数据集。患者病例信息可以共享，其中诊断数据是最重要的部分，因此基于多人群的数据整合工作也越来越重要。
Data products. Data-dependent products may be where diagnostics players have the most experience, such as next-generation sequencing, companion diagnostics, and liquid biopsies. However, data products can be more than just algorithms powering a diagnostic test result. IVD players could potentially create customer-facing products that improve clinical decision making, provide a better user experience for clinicians, and streamline operations for IVD customers across sites of care. Data products have been successfully employed for molecular diagnostics (for example, Cologuard from Exact Sciences)3 but could be equally valuable for proteomics—especially multiplexed or ultrasensitive proteomics.
数字服务。诊断企业对数据驱动产品的开发可谓是驾轻就熟，比如：二代测序，伴随诊断以及液体活检。但是，除涉及诊断结果的算法外，数字产品还包括其他很多类别。企业还可以推出更多面向终端客户的产品，为临床决策提供帮助，改善用户体验，并实现跨院区合作。分子诊断领域成功将数字工具嵌入到产品中
（比如，Cologuard以及Exact Science），这种模式可以推广到蛋白组学（特别是多重或超灵敏蛋白质组学）领域中。
Data services. Moving beyond products to provide services may seem daunting, but IVD players may be very well positioned among medical technology players to achieve this. Pairing appropriate services with real-time data from devices could provide significant value, such as by providing real-time guidance for clinical management, testing cost management, or predicting repairs.
数字化服务。在医疗技术领域，只有IVD产品最有可能实现产品的“超值服务”。
可以产生实时数据的配套服务具有更大的临床价值，比如为临床管理、检测费用管理以及维修提供实时意见。
How to get started on digital diagnostics
如何实现数字化诊疗？
Digital diagnostics can be challenging because it requires IVD players to build new capabilities (such as connectivity and data analytics), navigate a complex data regulatory environment, and clearly articulate a value proposition that resonates with customers, who are often skeptical. With that in mind, five moves underpin a successful strategy for pursuing digital diagnostics:
数字化诊疗理念一直饱受争议，主要有以下几点原因：IVD企业需要搭建新的匹配设备（比如：数据共享及分析处理）、数据管理环境更为复杂、清晰阐述产品的临床价值并且与有疑问的客户产生共鸣。基于上述考虑，要进行数字化诊疗产业需要做到以下5点——
Define a clear digital strategy linked to clinical care. The strategy should explicitly link digital solutions to meaningful improvements in clinical care from the perspective of both outcomes and cost. Too often, organizations focus on how to “monetize” digital and data, prioritizing what customers will pay for in the near term. The reality is that customers (including labs and hospital systems), end users (such as clinicians), and, increasingly, patients themselves aren’t interested in digital for digital’s sake, but they will pay for better outcomes and cost savings.
定义一个清晰的、数字化的临床护理方案。该方案必须以结果和成本为导向，清晰得阐述数字化方案在临床上的价值。通常，买方更关注如何将数据“变现”，并优先顾客在近期会购买的产品。现实是客户（实验室和医院系统），终端用户（临床医生）以及越来越多的患者对数字化结果并不感兴趣，他们更多得会选择诊断性能高但价格低的产品。
Be customer-centric, and engage customers in the right way. IVD players should let their customers guide them based on their needs, which can range across applications (for example, cardiac risk), capabilities (data analytics), and infrastructure (connectivity and the cloud). By working closely with customers to iterate, IVD players can tailor products and ensure uptake early on.
以客户为中心，从客户的角度体验产品。无论应用、工具还是配套设施的开发，IVD企业都应该基于客户的需要。通过与客户的紧密合作进行产品迭代，最终生产出被用户普遍接受的定制化产品。
Don’t do it all yourself. Find the right set of partners early and invest at scale. Many data-enabled businesses fail to scale, often because the IVD player has no natural ownership of certain aspects of the solution, such as cloud hosting and cybersecurity. The right partners can bridge those gaps and accelerate a scale-up while allowing the IVD player to focus on the value driven by the diagnostic data.
企业不要单打独斗。尽快寻找到合适的合作方并进行大规模投资。通常企业在数据云或者互联网安全等领域没有掌控权，因此难以形成产品规模。但通过合作可以弥补这些板块，IVD企业也可以将精力集中到诊断数据的应用价值上，加速扩大产业规模。
Begin moving your organization’s operating model to a digital one. Early in the process, move toward a product operating model that links product development, software development, and customer-centric iterations. Ensure clear product ownership with multidisciplinary pods to create end-to-end solutions.
将产品运作模式转型为数字化模式。在早期阶段，不断得向产品开发、软件开发、以及客户导向的迭代模式靠拢。确保跨学科合作的产品所有权，创建端对端的解决方案。
Develop and refine a regulatory strategy. Regulatory requirements for the use of digital in diagnostics are evolving. It’s essential to have a clear plan that outlines factors such as what components of the ecosystem are or are not software as a medical device and what features have a clear regulatory approval path. This plan should be aligned with the latest guidance from regulatory bodies, especially for any data models that will need to be updated or modified based on regional or country-level data regulations.
制定和完善监管战略。数字化诊断领域的监管体系也在不断发展完善。当前有必要根据某些重要因素制定一个清晰的计划，比如生态系统的组成元件是否属医疗设备软件，以及哪些功能需要有明确的管理审批。上述计划应该参考管理机构发布的最新指南，区域或者国家水平的数据管理需求更是如此。
