Data analytics and the healthcare market: a book review of Moneyball medicine — thriving in the new data-driven healthcare market

Workplace Health and Safety > Australian & New Zealand Journal of Health, Safety and Environment > 2020 Volume 36(3) > BOOK REVIEW > [¶36-381]

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By Harry Glorikian & Malorye Allison Branca

CRC Press, Taylor & Francis Groups (2017)

RRP: approx AUD$46.99; hardback

ISBN 978-1-138-19804-3 (hardback)

Reviewed by: Prashan S. M. Karunaratne, Ph.D., Macquarie Business School, Macquarie University.

Address for correspondence: Dr. Prashan S. M. Karunaratne, Room 243, 4 Eastern Road, Macquarie University, NSW 2019, Australia

Email: Tel: +61 2 9850 8409

With Moneyball Medicine — Thriving in the New Data-Driven Healthcare Market, the two authors, Harry Glorikian and Malorye Allison Branca, extensively discuss the scope and opportunity of how data and analytics can drive the delivery of healthcare in the United States of America in a single, 10-chapter volume.

The book is a very comprehensive account that explores both the breadth and the depth of the scope and opportunity that is set before the healthcare industry to produce transformative outcomes for patients, practitioners, product developers, and policy-makers. The choice of the metaphor, Moneyball, is fitting as the authors present documented, objective and reasoned cases for strategizing the data and the data analytics that are available to the sector, when coupled with constrained healthcare budgets, can deliver outcomes that benefit patients and practitioners, as well as utilise economics and entrepreneurship to deliver Moneyball outcomes to product developers and policy-makers.

If you are involved in policy-making in the healthcare space — particularly with lenses for efficiency, equity, economics, and entrepreneurship — then this compendium of cases that explores the scope and opportunity that awaits this market is essential reading. You will be informed and inspired by the 200 pages that methodically and meticulously present arguments to explore and exploit a plethora of avenues to use data and data analytics to achieve desired policy outcomes. The authors have thoroughly researched the academic literature, industry practice, as well as government policy to inform decision-makers and other stakeholders about an overview of the healthcare sector in the past, the outcomes being delivered in the present and the opportunity that awaits in the future.

As with any great venture, a strength can also be a weakness. The book is so comprehensive, and the cases presented are so extensive that perhaps some formatting in the lens of analytics would have added some more value to the reader. Perhaps lenses and tools of data analytics could have been utilised to present the cases in a visibly different font and format from the main text. Summaries of the data analytics used in each chapter could have also been presented in using data analytics lenses, such as charts and infographics. This may have conveyed the message of the book in a double-edged form where the reader is brought on board by the summarisation and strategic use of the information in the book via presentable data analytics and visualisations, just as the healthcare sector can be brought on board by the summarisation and strategic use of the information in the sector.

This wish list for presentable data analytics and visualisations is not to diminish the enormity of the work done by the authors, the rigour of their research as well as the breadth and depth of their cases and arguments. Perhaps the authors purposefully presented the book in its final format to engage readers from cover to cover without distracting them with other formats, summaries and visualisations.

After the introductory section, the book’s first chapter sets the scene to deconstruct the strategic opportunity that awaits the healthcare market using the Moneyball metaphor — The $10 Trillion Healthcare Industry’s Moneyball Moment (Ch 1).

Workplace Health and Safety > Australian & New Zealand Journal of Health, Safety and Environment > 2020 Volume 36(3) > BOOK REVIEW > [¶36-381] Data analytics and the healthcare market: a book review of Moneyball medicine — thriving in the new data-driven healthcare market.

The next part, seven chapters, which is the bulk of the book, then explores the breadth of the entire healthcare sector of the U.S., where each chapter is devoted to a specific nuance of the healthcare system there. Each of these chapters is ingeniously segmented as a deep dive into an aspect of the healthcare market, exploring several case studies which evidence the authors’ discussion and arguments:

• Precision Medicine, Data-Driven Diagnosis and Treatment (Ch 2) • Personally Tailored Cancer Treatment (Ch 3)
• Baby Testing Boom: Genomics-Based Prenatal Diagnostics (Ch 4) • New Hope for People with Rare Diseases (Ch 5)

• Price and Quality Transparency: The Dawn of Medical Shopping (Ch 6) • Value-Based Care: Paying for Results (Ch 7)
• Data-Driven Drug Discovery and Development (Ch 8)

The last part of the book moves away from the deep dive taken into specific healthcare market aspects, and take a birds-eye view approach to discuss:

• Re-Engineering the Healthcare System (Ch 9)
• Digital Health: Moving from Sci-Fi Fantasy to a New Healthcare Reality (Ch 10) • The Next-Generation Healthcare Landscape (Conclusion)

The second chapter is on Precision Medicine, and it opens with the unique problem faced by patients and practitioners in this scenario. The challenge here is that patients need to be treated based on their individual (hence the vernacular, “precision”) biological and risk factors, and the sample size, n, is equal to one. The sample size is this small because the patient has a unique condition and risk profile which makes it harder for practitioners to treat. Thus, the chapter discusses the scope for an assistant in the exam room by way of marrying clinical and research data to inform practitioners with current research. This chapter opens up the lens that data mining and data analytics of the big data available in the sector — from databases that are already held by hospitals, pharmaceutical labs and universities; to patient’s own step-counting devices; and together with artificial intelligence — can produce informative data analytics for optimal patient management. This is an effective choice in terms of the deep dive into a specific aspect of the healthcare market, as the author invites the reader to empathise with the individual in the special case of a sample size where n = 1. The authors argue that the information is out there, and the synthesis of several sets of data can effectively help patients and practitioners in the precision medicine space.

The next chapter on Cancer Treatment flows with the theme of personalised treatment — specifically discussing the opportunities that avail when it come to oncology, that is, precision oncology. The authors discuss the Moneyball moment that awaits by bringing together, mining and analysing of the databases of cancer institutes, genomic profiles and mutation databases. Together with cognitive computing, this will allow the growth of targeted therapy, as discussed in the previous chapter by allowing the matching of cancers to treatments as well as matching patients to optimal treatments. This would facilitate the treatments based on specific genetic mutations that patients have rather than the cancer type can produce better results, which the authors provide evidence for. Together with the sidebars that each explores a case study, the authors again draw on personalised narratives to draw the reader in and highlight the impact that a data-driven healthcare market can have.

Following on from the specific Moneyball moment in cancer, the next chapter discusses the Moneyball moment in Baby Testing. The chapter explores how pre-natal testing and neo-natal testing has evolved, including the importance of differentiating between screening tests versus diagnostic tests, and the importance of differentiating between the sensitivity or tests and the specificity of tests. While the scope and opportunity for data and analytics to transform this part of the healthcare market are discussed, the authors also explore the ethical and social consequences on non-invasive pre-natal screening tests and newborn screening, as well as how these tests and screenings will evolve in the future. With this “no stone left unturned” approach, the authors bring credibility to their expositions and arguments.

The fifth chapter is on Rare Diseases, which allows the reader to empathise with those in this scenario. The authors use real-life narratives of families who go through an odyssey when a loved one has a rare disease — trying to access the best practitioners, the correct diagnosis and the optimal treatments. Due to the market failure in bringing all the available data together in an efficient way to allow the production of data analytics to assist these cases, citizen-scientists have come in to bridge the gaps that exist in the sector, where families try and synthesise the various sources of information together to self-figure out an optimal treatment for the loved one with a rare disease. The authors also discuss the scope for social media in the fight against rare diseases. Together with the advancing of technology and precision medicine in the rare disease space, the authors present a scientific, emotional and business case for the theme of this entire book.

Workplace Health and Safety > Australian & New Zealand Journal of Health, Safety and Environment > 2020 Volume 36(3) > BOOK REVIEW > [¶36-381] Data analytics and the healthcare market: a book review of moneyball medicine — thriving in the new data-driven healthcare market

The next chapter, on Price and Quality Transparency, discusses the changing landscape in the healthcare market. The market for medical tourism is discusses where patients and their families engage in shopping on both the price and the quality fronts. However, such a market can only be efficient if the market was transparent, and information asymmetry remains. Information asymmetry is both deliberate — withheld by some stakeholders that are involved and unintentional — due the inefficient organisation of various sources of information that operate in silos. Thus, the authors argue that patients are unable to effectively shop for their care as when information is withheld deliberately it is misleading, and when information is unintentionally not synthesised it is incomplete. Information symmetry is argued for all stakeholders — hospitals, doctors, patients and their employers. Employers become a newly explored stakeholder in this chapter via the unique U.S. nuance of their health insurance system and health plans. This is a well-written chapter that draws on several lenses of readers to help them see the underlying structural issues in the healthcare market, and the power that data and data analytics plays in helping address these issues.

Continuing the discussion of price and quality, Chapter 7 has a neat segue into Value-Based Care. The authors discuss the two different approaches practiced in the healthcare market around the world — value- based care and the fee-for-service model — and objectively discuss the pros and cons of each approach. The authors extend this discussion of value versus service from the traditional scope of medical practitioners to the plethora of health products (pharmaceutical, therapeutic and digital devices) that are available. The sustainability of the healthcare market is discussed where we have more procedures, more treatments and more care — but without a discussion of value, the ultimate end user, the patient, may not actually be better off. The chapter discusses the role that the government has played and can continue to play in championing value-based care over a fee-for-service approach. In this regard, reportable outcomes of patients are discussed and the role that re-admissions and penalties can play in a value-based approach. Given this argument for the utilisation of data on the reporting of outcomes, and the Moneyball moment that awaits on the output end of the healthcare market, the authors discuss the role of data safety and privacy — again cementing the book’s “not stone left unturned” approach.

The next chapter takes a different turn and explores Data-Driven Drug Discovery and Development. The chapter opens with a discussion of the genome revolution in pharmacology and the amount of data that is being currently held and will be held as the sector grows. Databases are continually populated across the U.S. via large-scale drug screening and high-throughput screening. Already, clinical trials are changing in terms of both the design of studies and the recruitment of patients. Data is being utilised for personalised treatment and patient-report data is coming into the equation. The authors discuss some of the new and emerging tools that could be used by pharmaceutical companies to understand the language of biology, to re-purpose existing treatments and the lessons to be learnt from failure. The chapter concludes with a call to arms for big pharmaceutical corporations — how their agility via a data and data analytics lens can help deliver transformational outcomes in the healthcare market.

The final two chapters on Re-Engineering the Healthcare System and Digital Health: Moving from Sci-Fi Fantasy to a New Health Care Reality move away from the deep dives that have been made into specific aspects of the healthcare market in Chapters 2 through to 8. The book then brings together the previous expositions presented throughout to highlight that we need to make data work for patients, providers and health systems in general — optimising guidelines in daily medical practice, bringing health IT to hospitals and personalising the service to patients. Overall, this is an evolving business model where there is a shift from a fee-for-service lens to a value-based lens. Ultimately, the balance of power would shift towards patients, and thus deliver the desired outcome for society as a whole. The choice to effectively conclude the book using two angles — re-engineering the healthcare system and digital health is commendable as it highlights the two challenges and opportunities that sit before a thriving healthcare market.

Given this dawn of digital health, safety, security and privacy of data are intensified conversations that need to be had. The final chapter concludes giving an overview of what the future digital health will begin to look like: Providers — improving clinical workflow and paving the way for digital health. Patients — wearables and wireless devices that track patient data will become digital biomarkers that play a part in the utilising data.

Workplace Health and Safety > Australian & New Zealand Journal of Health, Safety and Environment > 2020 Volume 36(3) > BOOK REVIEW > [¶36-381] Data analytics and the healthcare market: a book review of moneyball medicine — thriving in the new data-driven healthcare market analytics for targeted healthcare. Commerce — a Moneyball moment to bring this data together by exploiting the opportunities that await. Information Technology — blockchain for connectivity, cognitive computing for analytics and artificial intelligence for insights. The book concludes with a view of the data and analytics- driven digital healthcare of tomorrow, where data and analytics is the vehicle that brings all stakeholders together to drive a thriving healthcare market.

Overall, this book has effectively covered both the breadth and depth of the U.S. healthcare market, specifically with the lens of data and data analytics that could enable this healthcare market to thrive. Every chapter has thorough evidence weaved throughout, and several case studies to engage the reader and provide them with nuanced insights. The case studies are presented as “sidebars” and do not have a notably visible change in format or style of font that is used, and this could be improved to help visually demarcate the avenues the book takes the readers through. Summaries or introductions to each chapter that presented the facts and figures in impactful data analytics and infographics would have also broadened the impact on readers and broadened the audience of reach — especially since the topic at hand is the importance of data and data analytics in optimal decision-making. However, these decisions may have been deliberately made by the authors and publishers to stick to a traditional peer-reviewed journalistic style of presentation — to pivot off the rigour and reputation that this form of publishing has garnered. The formatting and presentation of the book may have been made in view of the end users of this book, who are likely to be policy-makers and power-brokers who design and inform policy and thus require traditional lenses of rigour and reputation to inform their decision-making.

Last reviewed: 29 October 2020

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