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Personalized Medicine: Real Opportunities And Real Challenges For Doctors

Greg McStravick

In the first of a three-part series on how technology is transforming healthcare, Greg McStravick, GM and global head, SAP Platform GTM, takes a look at the potential of personalized medicine. Technology has the potential to create real value, but short-term challenges are significant. Find out more about technology and healthcare challenges and opportunities in Parts 2 and 3:

  • Part 2: Personalized Medicine and Big Data–Opportunities and Pitfalls of IT Innovation
  • Part 3: The Risks, Challenges–and Rewards–of Ensuring Medical Data Privacy

As we observe National Heart Month (#NationalHeartMonth) this February, it is both encouraging and exciting that a new effort is underway to create tailor-made medicine and medical treatments by drawing on exceptionally detailed and extensive biomedical data. The effort is ambitious and challengingand possible. The goal: wide availability of personalized medical care (aka precision medicine) that can be customized based on an individual’s genetic makeup and other factors.

But collecting this level of personal health care information, while it holds the possibility of game-changing personalized drugs and treatments, is not without major challenges–including those in the realms of patient privacy and data storage. Highly individualized diagnosis and treatment available on a large scale requires collection and management of petabytes of data, including but not limited to patient histories, genetic data, data from wearable health monitors, and information on individual microbiomes (bacteria, fungi, and viruses in and on the body). Privacy is of utmost concern, and even current big data standards could be strained by massive amounts of genetic data.

The possibilities are compelling, and the upside is huge. But personalized medicine is a challenge with real, difficult, and perhaps intractable problems attached.

Are we there yet?

We’ve been able to sequence the human genome for about 15 years. In certain specialties, such as oncology, we’re already seeing tremendous advancements thanks to genometrics. Cancer used to be thought of in terms of a cell gone wrong that affected the tissue around it, with treatments based on affected area – for example, lung, breast, or skin. Now, researchers are looking to treat each mutation by responding to its genetic fingerprint. The same treatment might be applicable regardless of the organ or tissue affected, and, for example, one patient’s lung cancer treatment might differ from another’s due to genetic differences in each person’s mutation.

However, along with important breakthroughs and new therapies to treat formerly untreatable diseases, we’ve also seen the need for exponentially more complex understanding – from not just researchers but front-line doctors. Now that we can sequence the DNA, we must understand and transcribe epigenomes, proteomes, metabolomes, and more. This poses a huge challenge for on-the-ground medical personnel, including primary care providers and specialists whose focus is broadly defined quality care.

Friend or foe?

The majority of physicians believe that personalized medicine will eventually create real value for individuals as well as entire populations. But in the short term, what will the average family practitioner get for her efforts? Physicians are under stress, working more and seeing patients less. Many doctors have just completed mandatory transitions to electronic medical records (EMRs), which has required more work but yielded little in tangible results. Privacy laws, insurance paperwork, and the shift to value-based pricing are requiring more data input and creating more hoops to jump through, lengthening the workday but providing minimal tangible value for patients and doctors. The fear here is that personalized medicine could mean more of the same for the vast majority of providers. Would primary care doctors need to verify even more information when a person is sick, taking into account all the additional characteristics that drive a doctor toward different therapies? Will all the new inputs yield equivalent benefits?

Outside the office

I believe that in order for personalized medicine to take off, we’ll need to capture not just genomic information, but accurate information about individual patients that falls well outside current hospital or clinical settings. How do patients live in their homes? What do they eat, drink, and smoke? What’s their documented level of physical and social activity? And even more important, how do we engage patients, especially those with chronic illness, in ways that support real change of unhealthy habits? I believe that for personalized medicine to reach its full preventative potential, the medical profession will have to engage with patients in their homes.

Also, correlating such lifestyle data is critically important to understanding and applying genomic data when predicting risk factors for certain diseases. But how will this lifestyle data be captured and stored? What infrastructure will be needed, and how will it be funded? Before we can consistently, accurately, and cost-effectively collect this data, we need a technology infrastructure and payment model in place.

Best practices: A final challenge

It can be a major challenge for the medical profession to implement best practices. Even when best practices are proven in controlled, randomized trials, it has often taken up to 20 years for a practice to be consistently adopted. Given this challenge, for personalized medicine protocols to really work for–and be consistently adopted by–doctors, they must:

  • Be time-neutral
  • Integrate into current workflows
  • Drive clear value for both doctors and their patients

It’s only when we address all these challenges–both technological and human-based–that we will be able to truly take advantage of the benefits that personalized medicine can offer.

Learn more about the SAP Foundation for Health and Personalized Medicine

SAP is passionate about creating transformative technology that can advance healthcare. The SAP Foundation for Health includes a sophisticated platform and advanced analytic solutions that can help unlock the value of biomedical data–from genomes to electronic medical records to clinical trials. Supporting deeper insights and enabling collaboration, the SAP Foundation for Health helps connect data silos and bring together mission-critical biomedical data, advancing personalized medicine to new levels.

Visit SAP at #HIMSS16 Booth #5828 February 29-March 4 to learn more, or continue the discussion on Twitter @SAP_Healthcare.

 

 

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Greg McStravick

About Greg McStravick

Greg McStravick is the general manager and global head of platform go-to-market within the Digital Enterprise Platform Group at SAP. He leads the go-to-market teams and strategies for SAP’s core innovation areas, including SAP HANA platform, analytics and insights, database and data management, and business platform as a service (SAP HANA Cloud Platform).

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

Christopher Koch

Robots: Job Destroyers or Human Partners? [INFOGRAPHIC]

To learn more about how humans and robots will co-evolve, read the in-depth report Bring Your Robot to Work.

Download the PDF (91KB)

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Christopher Koch

About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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What Is The Key To Rapid Innovation In Healthcare?

Paul Clark

Healthcare technology has already made incredible advancements, but digital transformation of the healthcare industry is still considered in its infancy. According to the SAP eBook, Connected Care: The Digital Pulse of Global Healthcare, the possibilities and opportunities that lie ahead for the Internet of Healthcare Things (IoHT) are astounding.

Many health organizations recognize the importance of going digital and have already deployed programs involving IoT, cloud, Big Data, analytics, and mobile technologies. However, over the last decade, investments in many e-health programs have delivered only modest returns, so the progress of healthcare technology has been slow out of the gate.

What’s slowing the pace of healthcare innovation?

In the past, attempts at rapid innovation in healthcare have been bogged down by a slew of stakeholders, legacy systems, and regulations that are inherent to the industry. This presents some Big Data challenges with connected healthcare, such as gathering data from disparate silos of medical information. Secrecy is also an ongoing challenge, as healthcare providers, researchers, pharmaceutical companies, and academic institutions tend to protect personal and proprietary data. These issues have caused enormous complexity and have delayed or deterred attempts to build fully integrated digital healthcare systems.

So what is the key to rapid innovation?

According to the Connected Care eBook, healthcare organizations can overcome these challenges by using new technologies and collaborating with other players in the healthcare industry, as well as partners outside of the industry, to get the most benefit out of digital technology.

To move forward with digital transformation in healthcare, there is a need for digital architectures and platforms where a number of different technologies can work together from both a technical and a business perspective.

The secret to healthcare innovation: connected health platforms

New platforms are emerging that foster collaboration between different technologies and healthcare organizations to solve complex medical system challenges. These platforms can support a broad ecosystem of partners, including developers, researchers, and healthcare organizations. Healthcare networks that are connected through this type of technology will be able to accelerate the development and delivery of innovative, patient-centered solutions.

Platforms and other digital advancements present exciting new business opportunities for numerous healthcare stakeholders striving to meet the increasing expectations of tech-savvy patients.

The digital evolution of the healthcare industry may still be in its infancy, but it is growing up fast as new advancements in technology quickly develop. Are you ready for the next phase of digital transformation in the global healthcare industry?

For an in-depth look at how technology is changing the face of healthcare, download the SAP eBook Connected Care: The Digital Pulse of Global Healthcare.

See how the digital era is affecting the business environment in the SAP eBook The Digital Economy: Reinventing the Business World.

Discover the driving forces behind digital transformation in the SAP eBook Digital Disruption: How Digital Technology is Transforming Our World.

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Paul Clark

About Paul Clark

Paul Clark is the Senior Director of Technology Partner Marketing at SAP. He is responsible for developing and executing partner marketing strategies, activities, and programs in joint go-to-market plans with global technology partners. The goal is to increase opportunities, pipeline, and revenue through demand generation via SAP's global and local partner ecosystems.