Digital Priorities of the C-Suite

Digital Priorities of the C-Suite

How Vertical Solution Providers Can Support Health System Competitiveness  

Since the onset of COVID-19, health system C-Suites’ view of “digital” has rapidly evolved from latest buzzword to cause for concern, then call to action, and ultimately exciting, but existential, imperative. Health system leaders recognize the myriad of new entrants vying to “own” the patient relationship as serious competition. As evaluations continue of the direct-to- consumer, virtual-first options, and omni-channel capabilities offered by big-box stores, leaders are comparing their own internal capabilities and options for next steps. With this emergence of digitally enabled competitive threats, Kx wanted to better understand the prevailing approach(es) of health systems to vendor evaluation and solutioning. We recently conducted in-depth interviews with CIOs, CMIOs, and Digital Strategy executives from some of the nation’s most progressive enterprises. Compilation of our findings revealed a nearly unanimous perception of opportunities and boundaries regarding horizontal vs. vertical options in healthcare digital technology.

Environmental Shifts

Almost overnight, the pandemic shifted consumers’ ideas about digital experience in healthcare. Consumers now expect convenient, personalized, tech enabled care, and providers must adapt their processes, adopt new tools, and transform their mindset to more closely mirror other industries that focus on the consumer. With nearly $30B in U.S. venture capital funding introduced in 20211, upstarts, larger solution providers, and Big Tech (e.g., Microsoft, Google, Amazon, Apple) are all well-capitalized and rapidly mobilizing to introduce consumer-friendly tools and capture market share.   The proliferation of both vertical solutions and horizontal (Big Tech) offerings is prompting health system buyers to commit to a vision of their digital transformation end-state and whom they will partner with along the way. There’s broad acknowledgment of the imperative to pursue digital strategies that progress the quality and efficiency of care and strengthen their connection with the patient beyond and in between each episode of care. Nothing less than convenient, consumer-friendly experiences will suffice in our digitally saturated post-pandemic world. Given these requirements – which match so closely to some of Big Tech’s core competencies – Big Tech seems like the obvious answer. However, despite the variety of foundational capabilities that Big Tech brings to the health system enterprise, we uncovered a tech partnership “line in the sand” in the minds of health system leaders.  

Necessity of Specificity   

Apart from Microsoft (due to the Nuance acquisition), our conversations found that health systems leaders generally preferred vertical vendors over horizontal technology providers for impact areas such as the EHR, clinical workflows and patient engagement. The lack of explicit enterprise strategy from Big Tech in healthcare is a significant detractor, characterized by one health system leader as “[the company] floating around like a rudderless ship, with no commitment, support, or strategy around healthcare.” Other reasons include the overall lack of expertise, the perception of healthcare opportunities as potentially lower-margin than other industries, and likely pushback from EHRs to interact with Big Tech solutions.  Even so, horizonal tech players remain a contender in the areas where they lead across industries. The key drivers of health systems considering a Big Tech purchase or co-development partnership include the following:   

  • Proven and well-regarded cloud infrastructure and data migration capabilities from Amazon and Microsoft that are trusted in regulated industries (Google’s solution in this space is negatively perceived across the provider market) 
  • Stated interest and initial positive results from Amazon, Microsoft, and Google to create the necessary data ecosystems for developing and running analytics, and deriving actionable insights to support the delivery of efficient, high-quality care  
  • Broad success in the consumer wearables market (Apple’s Watch, Google’s FitBit) and the acknowledgement that patient-generated data will become more relevant and useful over time   

Implications for Vertical Players  

This conclusion from health system enterprise decision makers – that vertical solution vendors are better positioned than horizontal tech players to support their digital transformation initiatives – is good news for Digital Health companies but comes with caveats.  An academic medical center CMIO stated “there are plenty of interesting startups that offer more intricate solutions, but they may go out of business and leave us without a solution.”  Despite the risk factors, digital health solutions are instrumental, highly visible components of health systems’ enterprise strategies and are typically considered on a different plane than Big Tech.  To capitalize on the positives and mitigate some of those negative considerations, digital health companies can understand and prepare for expectations that health systems have of them, including:  

  • Configuration Flexibility: Flexibility and willingness to configure the solution to meet unique health system needs  
  • Security Commitment: Readily available security documentation and a willingness to meet enterprise-specific security and compliance requirements 
  • Clear ROI Story: A competitive pricing model and the ability to speak to both near-term and downstream ROI implications of the product (including being able to “sell” this storyline to a variety of health system stakeholders – clinical, IT, Finance, etc.) 
  • Understanding of Competitive Implications: A thoughtful analysis of the health system’s competitive landscape and perceived advantages gained via user adoption of the solution 
  • Credible Implementation Plan: A thorough implementation plan that forecasts a reasonable timeline, strategies for end-user change management support, and EHR integration plans  
  • Team-wide Subject Matter Expertise: Consistent exhibition of deep expertise in the subject matter addressed by the solution – credentialing and reinforcing trust in the solution’s capabilities throughout the sales, implementation, and stabilization cycles 
  • Ability to Measure Impact: A plan to show impact through easily digestible, configurable, self-service reports accessible upon go-live 

Our interviews concluded that as long as vertical vendors continue satisfying the true needs of health systems, health system leaders will continue preferring to partner with vertical solution vendors. Keeping pace with morphing buzzwords and emerging external threats are daily challenges faced by every health system C-Suite. By reliably performing as expected, vertical solution vendors will maintain their preferred status with health systems, simplify aspects of each organization’s digital transformation journey, and support the overall goals of the health system business.  

How Kx Can Help You  

Kx Advisors’ Digital Health and Health IT team partners with digital health solutions companies so they can outshine the competition, delight their customers and end users, and maximize their growth potential. Ready to start winning against your competition and achieving your growth goals? Contact Rachael at rachael.england@kxadvisors.com to learn more. 

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Six Considerations to Evolve Your Capital Equipment Pricing Strategy

Six Considerations to Evolve Your Capital Equipment Pricing Strategy  

Capital Equipment Pricing Models  

As the world of capital equipment changes rapidly, manufacturers must find innovative ways to stay competitive. With new technology and enhancements, such as software upgrades and digital and connectivity solutions, as a crucial part of the value proposition of capital equipment, manufacturers can offer alternative pricing solutions to provide greater customer customization. Flexible pricing is especially pertinent for highervalue equipment on the market, such as AI-assisted imaging equipment, roboticallyassisted surgical equipment, and advanced monitoring equipment. With the shift in procedures from hospitals to smaller office-based labs and ambulatory surgical centers, manufacturers can also capture new business opportunities with these alternative models.  

New Pricing Models for Capital Equipment  

The traditional pricing models offered three options: an upfront purchase with each component sold separately, a consumable upcharge model, or a leasing model. A combination of new technology and more customized pricing improves a manufacturer’s value proposition. With new pricing models, manufacturers can boost revenues, increase penetration, and build long-term relationships with clients by offering greater flexibility.  

These new models include:   

  • Risk-based or outcomes-based model: Risk-sharing pricing strategies factor in a cost savings component from any operational efficiencies gained and clinical outcomes achieved in this model 
  • Recurring revenue stream model: Instead of the traditional transfer of ownership model, manufacturers offer a subscription with a recurring fee. The purchaser or user is granted access to a set number of capital equipment devices for the subscription period. This fee may or may not include unlimited usage in the number of consumables 
  • Patient usage pricing model: Based on patient usage, manufacturers can offer a per-patient fee for the equipment over a period of time with this model 
  • Enterpriselevel model: This model bundles the customers capital equipment needs across entire care units and multiple hospitals within the network. The bundle would normally include both equipment and services components. Payment schedules could be yearly or bi-yearly

Six Considerations for Identifying the Right Pricing Model  

With so many pricing models emerging, it can be challenging to identify the right one for your product offerings. As your organization moves towards a new pricing model, like the ones above, there are six key considerations to keep in mind to identify the most effective model for your team: 

  1. Set clear objectives: With an identified goal, your organization can better evaluate the potential models. Objectives can include increasing revenue, expanding the adoption rate, smoothing revenue, maximizing profit, and expanding account use of a suite of products and services. For example, if a manufacturer’s goal is to increase the use of a full suite of products, the recurring revenue stream model may be a better fit for their goal 
  2. Identify the value drivers of your product:  Drivers, such as clinical efficacy, payment model, ROI, and the strength of existing relationships, impact pricing and the manufacturer’s ability to customize the pricing model  
  3. Determine the decision-maker: Sometimes the end-user who makes the purchase decision is different from the purchaser who chooses the pricing model. Broadly, there are three types of capital equipment buyers: economic, clinical, and operational. The economic buyer’s sole focus is to improve their organization’s profit. In contrast, the clinical buyer is more focused on the clinical value of the product offerings, like patient outcomes or improved patient experienceOperational buyers typically focus on other factors such as department workflow, device integration with key clinical systems, or maintenance and uptime. Knowing the levels of influence and priorities for each buyer type will help determines which pricing model to offerIf the buying decision is more committee-basedthe pricing model will need to consider all stakeholder needs  
  4. Consider the impact on clients’ budgets: Pricing structure might impact where a client categorizes a purchase (i.e., capital expenses or operational expenses). Often capital expenses will fall under the hospital’s capital budget while operational expenses fall under the department’s budget, which may sway some clinicians towards a capital expense model  
  5. Understand clients’ financial health: Innovative recurring pricing models might be a better fit for clients working under capital restraints. This consideration is crucial overseas, especially in countries where COVID-19 has ravaged hospitals, which would seek to reduce the upfront cost of purchasing capital equipment  
  6. Establish benchmarking metrics: This consideration is the most important for risk-based or outcomes-based pricing, as identifying the equipment’s impact on patient outcomes or operational efficiencies dictates price. These metrics could include hospital readmission rates or the number of adverse events related to the equipment. When determining these benchmarks manufacturers must ensure they are measurable and that clients have the right infrastructure system in place to measure them 

How Kx Can Help You  

With our expertise in pricing strategy, Kx Advisors can guide your team through developing an optimized capital equipment business model. Our team of healthcare experts will help you evaluate your base, identify your customer segments, effectively appeal to your ideal customer, and position your organization for long-term success.  

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Using Your Product Launch Forecast as a Strategic Tool

Using Your Product Launch Forecast as a Strategic Tool 

Forecasting as a Decision-Making Tool

Too often, commercial planning teams approach revenue forecasting as a required financial exercise rather than a strategic planning activity. The highest performing teams, however, develop revenue models to drive decision-making and reinforce strategy. The forecasting process – designing the model, understanding the demand funnel, gathering insights, aligning on assumptions, and analyzing results – can drive decisions and deliver more value than the output itself. Elevating a revenue forecast to a powerful decision-making tool requires careful planning and thoughtful design considerations.

Crafting Your Product Launch Forecast to Inform Strategy

While revenue models are commonly designed to inform resource allocation, investor communications, or inventory planning, the most robust and accurate models are also designed to inform commercial strategy.  With the correct design considerations, your commercial planning team can learn more about the patient segments driving forecast value, identify opportunities in the patient journey to drive product adoption, and pinpoint the investments needed to drive share. Further, the most effective models consider multiple scenarios to plan for key unknowns.

Unfortunately, many project teams jump into forecasting with unclear objectives, insufficient data sources, or too many scenarios, and ultimately fail to develop a useful decision-making tool. Your team can avoid common modeling pitfalls by following best practices in three critical planning steps:

  1. Create the decision-making framework  
  2. Find the applicable data for the model   
  3. Define the scenarios    

Create the Decision-making Framework

The first step of any model should be aligning on the end goals (i.e., defining the decisions model will inform).  An end goal could be, for example, determining the focus and magnitude of commercial investments, evaluating strategic options in the face of a new market force, or determining supply need for a quarterly production plan. After identifying the overarching question(s), your team can determine how to approach the model.  

Your team can use the end goal to decide on the type of model. The type of model, from market share model to launch planning to production demand, determines the model’s specificity. Analyzing the structure before gathering data to ensure the model aligns with the end goal will save your team time and effort.  For example, is an annual model sufficient to calculate net revenue, or does the organization need monthly/weekly sales granularity to inform production planning? Is there a need (and reliable data) to support international country-level forecasts, or would a regional forecast be more accurate and equally actionable? Once you understand the key questions the model is answering, the desired output, and the aligned model type, your team will have the clarity to move to the next step: finding the data.     

Find the Applicable Data for the Model    

First, your team should identify and classify relevant data sources about your product and market, such as epidemiology studies, claims data sets, qualitative interviews, quantitative surveys, historical product sales, and competitor sales, among others, for input. Forecasting teams should take a “best source” approach –evaluating every assumption individually for the highest confidence source. Without pinpointing potential knowledge gaps, models can provide incorrect or incomplete information, impacting the outputs of the model, and ultimately, the launch’s success.  

If the data does not exist in the public domain or within research resources, it can often be collected. Kx specializes in designing and executing market research with key stakeholders (e.g., providers, patients, and payers) to inform quantitative forecasts.   When designing primary market research, it is important to start with the model structure and work backward to design the research to fit the model. Designing for the model’s purpose will lead to a more accurate forecast. Finally, research should be designed to enable a “living, breathing” forecast. Research approaches such as choice-based conjoint surveys can allow forecasters to simulate new market conditions as they arise and update key assumptions without conducting additional market research. 

Define the Scenarios  

After outlining the criteria for the data, the next step is to determine which scenarios need to be analyzed. Often teams will initially attempt to investigate and list all possible options, but if the model becomes too complex, it will lose its effectiveness. Instead, the best practice is to define a base case or most likely scenario. A base case typically uses a consensus estimate or confidence-based weighting along key assumptions to drive forecast outputs. Once your team identifies the most likely scenario, define the parameters you want to test. Identifying priorities and areas of uncertainty will help determine which scenarios to test. For example, breadth of market access or coverage, varying price points, the impact of future clinical study outcomes on adoption, and changes to competitor mix are some of the most frequently explored scenarios.  

How Kx Can Help With Your Product Launch Forecast

Over the last four decades, our team has developed proven modeling and forecasting approaches that produce accurate, insightful outputs and drive strategic decision making. Our team acts as strategic partners to help guide you through the entire process, including developing the product launch forecast, gathering the underlying data and insights, aligning internal stakeholders, and ultimately preparing the model for you to run.  

 

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How Understanding Cognitive Bias Can Drive Patient Volumes

How Understanding Cognitive Bias Can Drive Patient Volumes

Understanding Patient and Healthcare Provider Behavior 

We all strive to make rational choices. But as humans, we are prone to bias and misjudgment. In the medical field, cognitive biases can have a profound impact on both patients and healthcare providers. Kx frequently conducts studies to uncover cognitive biases in referral pathways, including specialist referrals for more advanced therapies or interventions.

By pinpointing these biases, our team helps specialty drug and medical device clients focus their marketing and education efforts and increase market penetration within their eligible patient population. 

Common Dilemmas

Often specialists do not refer patients for treatment quickly enough or at all. These delays in or lack of treatment not only allow the patient’s condition to deteriorate, but also prevent the drug and device companies from fully reaching their addressable patient population. In our recent studies, Kx found that cognitive biases exist at each stage of the referral process.

Cognitive bias map of specialist referral pathway
Click to expand

 

The Kx Solution

When guiding healthcare organizations by improving their specialist referral pathway, the Kx team runs an in-depth qualitative analysis speaking with specialists to understand critical attitudes, behaviors, and beliefs across the population of relevant doctors. Key differences within demographic segments (e.g., age, specialty, practice type) and behavioral segments (e.g., willingness to refer, referral choice) help identify drivers of attitudes and potential solutions for changing these behaviors. 

Uncovering Cognitive Bias to Reach the Addressable Patient Population  

Kx developed the following key findings to drive the patients through the specialist referral pathway:

  1. Awareness that symptom recognition is often the most significant barrier in the referral process and education to combat the issue. Early in the referral process, during the diagnosis phase, cognitive biases result in the specialist not probing consistently, missing symptoms by not asking the right questions, or simply not asking enough clarifying questions. Incorrectly identifying patients’ health status based on outward appearance or insufficiently probing symptoms can result in critical underdiagnoses or undertreatment.
  2. A clear path to referral, particularly one with a singular point of contact, can help referring physicians feel more at ease. Successful drug and device companies reduce friction in referral pathways by helping referring physicians establish clear points of contact across hospitals, specialists, and surgical teams. Elucidating a single point of contact cuts down on ambiguity and removes an obstacle for referring providers.
  3. Direct relationships between the referring specialists and the treatment teams (surgery team) build comfort and encourage referrals.
  4. When creating tools for doctors, simplicity and ease of use are key factors. Biases exist among doctors to simplify complex thought processes. Though tools, like decision guides for complex cases, can be extremely beneficial, they must be simple and easy to understand and use to overcome biases and help physicians better identify which patients need further treatment.

How Kx Can Help

Our healthcare experts can guide you by adjusting various aspects of our corporate strategy, including your referral pathway, with insights from market research. Cognitive bias is built into our research methodology, enabling your team to overcome any we find and fulfill more referrals. As data-driven decision-makers, we design research using both traditional factors and behavioral science to pinpoint process improvement and qualitative analysis opportunities. 

 

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