Focus on Value 2
How data & analytics are facilitating outcomes-based health.
As with other industries, digital is having a profound effect on the healthcare sector – not simply by enhancing and smoothing existing operating models, but in a truly transformational way. Following a familiar pattern, digital has, until recently, been used as a facilitator perhaps to cut cost or make existing processes more efficient; but now there are new data sets and analytics capabilities that open the door to innovative approaches capable of transforming everything from R&D to commercialization. Digital – in the context of a determined emphasis on value and outcomes, and increasing consumer power – is helping to transform payers, providers and suppliers, while ushering in new participants to the market, by reshaping commercial and operating models within this ecosystem.
Jeff Elton, managing director in Accenture Strategy and global lead of Accenture Predictive Health Intelligence and Accenture Intelligent Patient Solutions, emphasizes the fundamental nature of this transformation.“I think data and analytics are now actually becoming foundational.”
Raymond Tew, President and CEO of Medicus Innovation, which publishes the Provider’s Guide for Value-Based Medicare Reimbursement, supports this analysis. “Value-based healthcare relies on capturing patient data relating to the quality of care they receive; but raw data in and of itself is not helpful. There is a desperate need for value-based analytics that can make sense of patient care metrics that have been pulled from raw claims submissions and hospital internal data warehouses".
Elton cites the traditional approach to clinical trials as an example of another area in which data aggregation and analysis are transforming existing practices. Under the old model, hugely expensive studies of hundreds or possibly thousands of patients are conducted via clinical centers; then the research is submitted, written up and reviewed before publication in a journal often several years later – a long-drawn-out process. “Whereas now, I can look at data and I actually validate in my population with millions of people whether or not those same results hold up. I can actually run analyses in minutes, second or, if it’s a complicated area, within a few days.”
This newfound digital capability is a big material change, according to Elton. Moreover, with wearables and other devices, digital tools are now becoming ubiquitous and they can measure and interact with populations 24/7. “The ubiquity of digital is a huge part of this trend,” he adds. Throw into the mix electronic health records (EHR) and we have a system positively overflowing with data.
The significance of analytics
The ability to analyze this data is becoming fundamental to the way that health systems and payers operate. Today, they are often heavy risk bearers and are starting to rely on population health and other analytic tools to generate insight that informs their programs to manage quality, population and health outcomes more effectively.
“Analytics plays into how a lot of the delivery of how health payers and larger health provider systems are beginning to operate, which means you are getting a sophistication level that is not just around taking what’s in the literature, but you’re actually getting institutions that understand what’s different about their populations, what works, what doesn’t.”
Furthermore, such data-based insight guided by analytics helps drive period-over-period, iterative improvements in outcomes, in a way that was extremely difficult to implement historically. “Any kind of continuous improvement wasn’t really possible before,” Elton confirms.
At the same time, leading life sciences companies are starting to undertake sophisticated data analysis early on in their programs to understand what the standard of care looks like and to gain insight into the current treatment of patients; outcomes and efficiencies; and gaps in care and related services all the way back through the R&D phase. “They can actually design trials to be more real-world like, so that the data they’re collecting translates better over into the context. Historically, that wasn’t really an area of focus.”
This thinking flows all the way through to how organizations approach commercialization, as they seek to gain a fundamental understanding of a particular disease state and care path, and then into how this translates into deployment of their solutions – perhaps by supporting the value of their current pricing or possibly by entering into contracting with a performance-value component. An ability to run observational studies in real time gives life sciences companies the opportunity to prove hypotheses to the satisfaction of payers and providers, and creates a firm foundation for new risk-focused payment models.
In terms of how far such innovation has penetrated orthodox thinking, Elton suggests that the new model is now moving from the proof of concept stage to become a core capability and part of the language of interaction among health authorities and provider systems, risk bearers and life sciences companies. “Our view is that we’ve seen this happen very rapidly over the past three to four years. I think we’re going to see huge advances. It’s going to be quite beneficial, but it’s going to be quite foundational to how the industry is going to function.”
Anne O’Riordan, global industry senior managing director at Accenture Life Sciences provides a real-world example of how such a model works in the context of a program to improve chronic cardiovascular care in European hospitals (see case-study 1: insight into chronic cardiovascular disease care). She says: “Socio-economic changes are driving the market to move to value-based care, and new data-driven care transformation services are a great enabler of delivering high-quality healthcare at the right cost. Working together with Boston Scientific, we are able to bring to market digital capabilities and analytics-driven insights that focus on improving patient and economic outcomes.”
A new platform, jointly designed by Accenture and Boston Scientific seeks to help providers standardize care, reduce overall length of stay and lower readmission rates. Mike Mahoney, president and chief executive officer, Boston Scientific, tells eyeforpharma: “The Care Pathway Transformation program is designed to enable healthcare professionals and patients to have more informed relationships, leading to better health outcomes and lower costs for health systems.”
Another example is provided by Medicus Innovation. It demonstrates how value-based market insights about healthcare systems can be translated into significant commercial opportunities for pharma. Case-study 2 describes how, by improving the promotional approach for a $500 million drug, pharmaceutical companies could increase sales by as much as 15% or $75 million.
Elton places companies such as Medicus Innovation in a growing category of innovators that help players in the healthcare sector interpret data around the various value-based reimbursement models. “These are actually going to be very important companies,” he declares.
Such tools are becoming important in the context of health authorities, government entities, private payers and risk-bearing providers – and as life sciences companies take on more service-centered qualities – in order to establish the relevant baseline characteristics, the level of risk between contracting parties and potentially to supporting the execution of those contract structures as well. He cautions that there needs to be neutrality and independence in this process, along with the expertise, business model and understanding of the security implications of interacting with personal health data, and this is one reason why we’re seeing these sorts of third parties emerging.
Data analytics is poised to usher in a whole new era of healthcare insight. It is this insight that will drive improved health outcomes for individuals and populations and also define commercial success within the new healthcare landscape.
Case-Study 1: insight into chronic cardiovascular disease care
Medical technology specialists Boston Scientific and consultants Accenture have developed a cloud-based, data-driven digital health solution for hospitals, designed to help improve patient outcomes and reduce costs in treating patients with chronic cardiovascular diseases. Known as ADVANTICS™ Care Pathway Transformation, it enables providers to make more proactive and informed decisions based on insights into the patient population; this will ultimately improve the care a patient experiences from a hospital stay through post-discharge care and in-home support.
The solution uses the Accenture analytics insights platform to provide actionable insights into care coordination and patient population health patterns, revealing opportunities to improve the consistency and efficiency of care coordination. It focuses on three key measurements:
- Pathway analytics – how a patient moves through the hospital system, how long each step takes and whether a patient can be better served by a more efficient system;
- Care management – how patients are diagnosed, treated and monitored, by whom and how often, as well as their ongoing vital signs and risk analysis; and
- Patient engagement – how patients are educated, monitored and receive communication during their hospitalization and after discharge.
We identified a 25% unnecessary heart failure readmissions rate, and therefore, a definite need for better care coordination, supported by modern technology and processes that can decrease overall costs.
In developing this solution, both companies worked with two of the largest hospitals in Scandinavia – Karolinska University Hospital in Sweden and Tampere Heart Hospital in Finland – to assess the current state of care delivery for heart failure patients and identify opportunities for improvement at each hospital. Heart failure has been identified as one of the costliest disease states to manage, accounting for some two percent of healthcare spending and resulting in an average 11-day hospital stay in Europe.
“The collaboration with Boston Scientific and Accenture exposed significant opportunities to increase provider collaboration and improve the quality of care that patients experience when coming to our hospital,” explains Dr Kari Niemelä, CEO, Tampere Heart Hospital. “For example, we identified a 25% unnecessary heart failure readmissions rate, and therefore, a definite need for better care coordination, supported by modern technology and processes that can decrease overall costs.”
The solution has been tailored for insight into patients with heart failure, but the companies plan to expand it to additional disease states. Boston Scientific and Accenture initially plan to make the solution available to hospitals in the United Kingdom and Scandinavia and expect to pilot projects throughout Europe and the United States soon.
Case-Study 2: Analysis of COPD market opportunities in the United States
This case-study is a scenario created to illustrate two different strategies for identifying market opportunities for a mature COPD product in the US market. One strategy utilizes value-based market analytics and one does not. The company has an established product for COPD and is currently ranked 5th for market share among branded products in this treatment category. The company wants to reinvigorate its brand by improving its promotional approach.
Scenario A – This option focuses on just one aspect of a value-based market strategy: effective customer targeting. Its goal is to increase sales of a $500 million COPD drug by 15% over two years. Current market analysis includes historical pharma market analytics such as:
- COPD market size and location (zip code, hospital and physician) of known cases of COPD
- Identity of physicians treating COPD with the brands and dosages of prescribed products.
- Physician attitudinal survey results about the market and available products
Typical market analysis tools suggest that “Hospital System A” has the highest market potential with $5 million in potential sales for COPD medications. However, research into product status at Hospital System A indicates that generics are first line, a competitor’s branded product is second line, and the company’s product is stocked but not on formulary.
The result of the targeting analysis is that the local field sales team prioritize their efforts and promotional spending to this account. Their goal is to increase the number of details to high prescribers in this hospital system focusing on the key selling product attributes: once-a-day dosing, minimal side effects, and efficacy. Their package insert does not include data on comparative studies between their product and the first second-line branded product on formulary. They execute this strategy for six months.
Results – Though the sales team is able to increase the number of product presentations, the company is unable to improve the positioning of its product to second-line therapy on formulary or to increase market share of the product at this health system.
Scenario B – This same pharmaceutical company seeks to develop a customer-centric market strategy utilizing value-based market analytics for this product; the goal is to create a targeting strategy for boosting COPD product sales by developing a more accurate territory-level market perspective. Using the Medicus Innovation Value-Based Market Analytics platform and subject matter expertise, the company discovers the following market insights about prospective customers:
• While Hospital System A was high in potential sales of COPD products, it was also ranked in the top 5% nationally among health systems in quality scores for treating COPD.
• This insight brings up the obvious question: “How receptive will the hospital be to changing its medication treatment protocols when it is already ranked as one of the best hospital systems in the country for treating COPD?” Most likely, it will not be very receptive to marketing efforts aimed at changing those protocols.
• Further value-based market analysis identifies three other “smaller, less-prestigious” local hospital systems with combined market potential 50% greater than Hospital System A ($7.5 million versus $5.0 million).
• These three systems were ranked in the bottom 30% of hospital systems for COPD readmissions and pneumonia mortality.
• Two of the hospital systems have the product as second-line therapy. The third hospital system does not have the product on formulary but it is stocked and available for third-line therapy.
• These hospital systems had over $2.5 million in reimbursement penalties for COPD and pneumonia for 2015.
From a pure targeting perspective, value-based market analytics enable a pharma company to develop unique market insights to guide investment of field resources toward customers with the greatest potential ROI (defined as product sales potential plus the highest likelihood of receptivity to change). As per the above case-study, Hospital System A would typically be the priority if traditional targeting techniques were used; however, with value-based market analytics, it becomes clear that scenario A would actually not represent the best use of field resources; in fact, scenario B offers greater sales potential and a higher likelihood of sales success.
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