The panel discussion at last week's SAS Health Care & Life Sciences Executive Conference surfaced plenty of ideas, opinions and, ultimately, strategies for effective customer engagement in health care.
Over at Customer Analytics (the SAS blog about, well, customer analytics), John Balla provides this great summary.
What's the cure for high-cost health care and medical diagnoses that miss the mark? Technology and analytics, says Clayton M. Christensen, author and professor at Harvard Business School.
Christensen spoke Thursday during the 9th Annual SAS Health Care & Life Sciences Executive Conference.
As both a medical doctor and a stroke survivor (living with lymphoma and Type 1 diabetes), Christensen shared insights that were as poignant as they were unique.
His experiences as both doctor and patient shape his belief that the US health-care system must embrace technology and health analytics in particular in order to make health care affordable and medical diagnoses more precise and accurate.
“The business models themselves need to change so we can deliver outcomes at a much lower cost with higher probabilities,” Christensen said.
As health analytics and related technologies become more ubiquitous and standard among providers -- patients even -- smaller clinics will be able to treat many of the conditions and ailments that currently require hospitalization. And the services rendered by today's clinic will move into the home.
At the same time, outcomes will improve.
A recent study Christensen cited concluded that 70 percent of today’s hospital patients would have been in the intensive care unit 30 years ago, and 70 percent of today’s intensive care patients would have been dead 30 years ago.
“Our hospital has been extraordinarily capable of ever more miraculous things,” he said.
Data allows providers to take the next step toward more precise, personalized care. Because symptoms overlap for so many health problems, it is harder for physicians to accurately diagnose a condition or provide the most ideal treatment.
Christensen said that using “magnificent analytics” to focus on common problems, such as Type 2 diabetes, obesity or depression, will let physicians begin to identify hypotheses for these types of diseases.
“You can be more accurate more often, and more importantly you can give guidance to scientists looking for (disease) markers because you have a more pure population to work with,” he said. “I can’t imagine that anybody in the world has the intellectual horsepower to address patients in this way. SAS is in a great position to do good things here.”
The SAS Center for Health Analytics and Insights (CHAI) has launched an online community to connect leaders and practitioners in the health and life sciences industries who are dedicated to transforming health care.
CHAI Managing Director Jason Burke announced the community, known as the Center for Health Analytics, this morning during opening remarks at the 9th Annual SAS Health Care & Life Sciences Executive Conference.
“We want to facilitate a different dialogue about health transformation," Burke said. “Our research with health plans, health providers and life sciences firms finds that health analytics is pivotal to a cost-effective and outcomes-oriented health system. But the work requires collaboration. This open community will help customers, partners, regulators and other industry stakeholders explore together how health analytics can power a more information-driven health ecosystem.”
The Center for Health Analytics features content and updates from CHAI on health analytics research and practice across such broad topics as consumer engagement, health risk prediction, bundled payments, accountable care, evidence-based medicine, adaptive clinical trials, federal legislation and fraud prevention.
Industry leaders and stakeholders will add unique content and participate in discussions.
“One of our explicit goals is to balance input from our employees, customers, partners, thought leaders and industry pioneers,” Burke said. “We are launching this community to offer a platform for multi-directional communication, education and exchange. We have a lot to share, but we have as much to gain from those who visit and join in the dialogue.”
Blue Cross and Blue Shield of North Carolina (BCBSNC) and SAS are collaborating to help health plans offer more and better personalized care and service while holding down costs for individuals and employers.
The announcement came this morning during the 9th Annual SAS Health Care & Life Sciences Executive Conference.
Plans can use the software to create products and services that better match the specific health needs of their consumers.
“In an industry that has not used insights to their fullest potential, BCBSNC and SAS are blazing a path to the future of health care," says Dr. Graham Hughes, SAS Chief Medical Officer. "This SAS software will provide health plans with predictive models similar to those in other consumer-focused industries."
"By better engaging customers, health plans can provide top-notch customer service and support," he adds. "This will allow the health system to deliver consumer-focused patient care. Better care often means reduced costs – the health plan wins, the provider wins. Most importantly, the customer wins.”
The collaboration enhances BCBSNC’s ability to identify customers who may benefit from programs specific to their health needs. At the same time, the software will help BCBSNC anticipate the best way to engage them.
Using these tools, BCBSNC can, for example, determine the best way to encourage a customer to get a doctor-recommended colonoscopy or to receive a flu shot. The same information will allow BCBSNC to develop new products, services and programs -- and tailor existing ones -- that will deliver more value for customers.
That means, for example, BCBSNC can communicate with customers in the way they find most helpful, guiding them to better health outcomes. And BCBSNC will use these insights to point prospective customers, whether individual or group, to the plans and services they need.
“Our work with SAS addresses an issue that’s at the crux of the health care challenges we face today: improving health in order to reduce costs for our customers,” says BCBSNC Chief Medical Officer Don Bradley. “Traditionally, we’ve based health plan designs and care management programs on conventional research. Now we can look through a new lens at readily available data to create health plans better targeted to consumers’ needs. And, more importantly, we can offer more personalized care management programs, which individuals are more likely to respond to – making it more likely that these efforts will improve their health.”
The collaboration is sponsored by the SAS Center for Health Analytics and Insights (CHAI), a health industry think tank focused on identifying novel ways of applying advanced analytics to the challenges facing the health and life sciences industries.
In the year since its inception, CHAI has published industry-leading research on the transformative opportunities for health analytics within both health plans and health care providers, and fostered industry collaborations in areas such as adaptive clinical trials, bundled payment analytics and now, personalized health insurance.
“Personalization through the use of predictive analytics is rapidly gaining momentum across health and life sciences,” says Jason Burke, Managing Director of CHAI. “Consumers are increasingly expecting both health plans and providers to understand their individual health needs. They want a higher-quality, more informed experience, which we strongly believe produces better health outcomes.”
Whether or not you're attending the SAS Health Care & Life Sciences Executive Conference in person, you can still keep up with the proceedings, which kick off first thing Thursday morning.
We'll post updates on this blog throughout the day. Follow us on Twitter (@SASAnalytics) using hashtag #HealthAnalytics or look for any of these handles: @JaBurke, @dhandelsman, @CarolDSanders, @Bryan_Engle, @MarkWeadon, @aharp, @kellymiller22, @Postgrad.
Looking ahead to Thursday's SAS Health Care & Life Sciences Executive Conference, we shared seven must-reads for life sciences yesterday. Today, seven must-reads for health care:
Providers: 5 strategies for navigating health care reform
Plans: Will you thrive in the new market landscape?
Learn from the pros: 5 traits of every successful customer-focused company
Claims fraud is easier than ever. Are you prepared to stop it?
Video: Detect, prevent fraud with SAS
Buzz Word: Analytics -- Graham Hughes on the challenge of big data
What could you do with better, faster answers?
All these challenges making your head swim? Here's some advice from the good folks at Britain's Ministry of Health.
Attending the 9th Annual SAS Health Care & Life Sciences Executive Conference this week? No need to pick up a magazine for the plane ride. We've got you covered.
Below, seven must-reads for life sciences. Tomorrow, seven must-reads for health care.
Five ways to improve marketing ROI
The three secrets behind successful marketing programs
Negotiate like a pro in managed markets
Confessions of a clinical programmer
Succeed with adaptive clinical trials
Reduce the cost, time of managing clinical research
What could you do with faster, better answers?
This year's conference digs deeper into the discussion about big data and health analytics.
UPDATE: Removes Twitter handle attributed in error to Berwick in earlier version.
During the 9th Annual SAS Health Care & Life Sciences Executive Conference this week, industry leaders from around the world will discuss the No. 1 issue they face: providing quality patient care while managing costs.
Don Berwick, MD, former administrator for the Centers for Medicare and Medicaid Services, and Clayton M. Christensen, author and professor at Harvard Business School, will headline Thursday's event.
Berwick, a pre-eminent voice for high-quality health care in the US, will talk about the challenges facing modern health care systems.
Christensen (@ClayChristensen) is a leading expert on innovation and change whose ideas have been applied to national economies, startups and Fortune 50 companies.
This year's conference will look at health analytics in an era of "big data" and how closing the gap with third-party information sharing will allow for brighter insights, improved patient relationships and healthier outcomes.
As our elected officials debate the constitutionality of healthcare reform, the need for curbing spending on healthcare continues to increase. At last count, healthcare spending will account for 19.5% of our country’s gross domestic product by 2017. Whether you support the existing legislation or not, it’s clear that we need to approach healthcare spending differently.
That’s what baseball’s Oakland A’s did under general managers Sandy Alderson and Billy Beane. The A’s looked at an existing problem – how to assemble a competitive team in a small market, meaning a low team salary, – in a different way. Michael Lewis chronicled Beane’s odyssey in his book Moneyball, which showed how the Oakland A’s contended with major market teams by challenging the status quo. Traditionally, teams scouted players based upon subjective measures of potential, such as size and projected ability. The A’s instead employed sabermetrics (advanced analytics) to identify under-valued players, based upon their ability to, for example, get on-base, which is more closely aligned with scoring runs than a player’s batting average. In fact, Beane realized that a walk was about as good as a hit. By using advanced analytics and an entirely new approach to filling the roster, the Oakland A’s delivered significant results at a fraction of the cost of other teams.
Let’s look at the numbers for the 2002 Oakland A’s:
· Lost three of their 2001 high-profile free agents who pursued larger salaries elsewhere
· Oakland A’s 2002 salary budget - $41 Million (NY Yankees $125 Million)
· Cost per win - $388 thousand (NY Yankees ~$1.2 Million/win)
· Season wins – 103 (tied with NY Yankees)
· Won the division
· Won 20 consecutive games (most for any American League team ever)
Chart of the MLB payrolls for the 2002 season related to MONEYBALL, 2 October 2011, Darrylleewood
The baseball world drastically changed after the publication of Moneyball. Every team now employs advanced statistics across a variety of non-traditional metrics for scouting and recruiting of players.
What does this all mean relative to healthcare?
The healthcare industry, as a whole, has just started to investigate the promise of advanced analytics. There are many who dismiss analytics in favor of the status quo: that medicine is an art and should not be beholden to data or analytics in treating patients; that sales and marketing within life science companies should be based upon field experience and intuition rather than investment allocation analysis; and that defining risk for prospective members in establishing costs of healthcare for payers is an impossible exercise without historical member data. These are only a few examples.
The healthcare industry traditionalists are opposed to change. It has been quoted elsewhere that physicians view evidence based medicine as “cook-book” medicine. The sales and marketing at life sciences companies has been driven for decades by a status quo mentality based upon field experiences and decile-based target with limited evolution.
Enter “healthcare advanced analytics”(HC2A). HC2A has the promise of bending the cost curve for both payers and providers by defining treatment pathways that deliver better overall results at a lower cost point, defining the risk of a previously uninsured patient population for an industry faced with reform, and redefining how life science companies approach their customers. A few examples:
· Supporting Providers in the development of standards based approaches to care that yields better results at a lower total cost of care than common treatment approaches. A number of examples cited here – bone marrrow transplant with high dose chemo for breast cancer patients(http://theincidentaleconomist.com/wordpress/the-rise-and-fall-of-bone-marrow-transplantation-for-breast-cancer-a-tragic-success-story/); antibiotics for ear infections (http://www.cnn.com/2010/HEALTH/11/16/antibiotics.ear.infections/index.html As a side note, our toddler daughter was given antibiotics for an ear infection and suffered a severe allergic reaction.) and prostate cancer screening(http://www.webmd.com/heart-disease/news/20110104/study-overuse-of-implanted-cardiac-defibrillators).
· Enabling Life Science companies to improve multi-channel marketing through investment allocation and channel mix optimization that delivers more sales than traditional approaches to targeting. Additionally, the incremental sales can be forecasted and quantified in advance of the campaign launch.
· Empowering Payers to define the relative risk and costs of previously uninsured prospect member populations for the purposes of designing and pricing health insurance plans in the post reform era.
This is no different than sabermetrics redefining baseball’s historic approach to scouting and valuing players at the lowest total cost to field the team.
Here’s an excerpt from Moneyball of Boston Red Sox’s owner John Henry trying to recruit Billy Beane to become the general manager of the Red Sox after the 2002 season:
“For forty-one million, you built a playoff team. You lost Damon, Giambi, Isringhausen, Pena and you won more games without them than you did with them. You won the exact same number of games that the Yankees won, but the Yankees spent one point four million per win and you paid two hundred and sixty thousand. I know you’ve taken it in the teeth out there, but the first guy through the wall. It always gets bloody, always.
It’s the threat of not just the way of doing business, but in their minds it’s threatening the game. But really what it’s threatening is their livelihoods, it’s threatening their jobs, it’s threatening the way that they do things. And every time that happens, whether it’s the government or a way of doing business or whatever it is, the people are holding the reins, have their hands on the switch. They go bat <expletive> crazy. I mean, anybody who’s not building a team right and rebuilding it using your model, they’re dinosaurs. They’ll be sitting on their <expletive> on the sofa in October, watching the Boston Red Sox win the World Series.”
(The Boston Red Sox won the World Series in 2004. The previous time they played in the World Series was in 1986 and they lost. The last time they won the World Series was 1918.)
So, you decide where you want to be next season… Leveraging HC2A to drive the investment of your company’s monies albeit with a new approach to the company’s commercial model or sitting on the sofa using the status quo of last year’s approach with everyone else.
In a prior post I made some estimates of the global size and growth rate of medical data stored in databases across the world. Whether those estimates were close or not, the point is that there is a huge amount of medical data available today and the vast majority of those data remain unanalyzed or dramatically underanalyzed.
It's not surprising really because the systems that generate those data were seldom purchased with future analysis in mind and the pressure to respond to organizational imperatives with additional automation tends to overwhelm even the most forward thinking CIO. At some stage it just comes time to regroup and consider how best to leverage the assets you have and how to architect for the ongoing curation and analysis of the data that you will have.
Before going further, let's take a quick detour. Anyone remember the early days of "dark fiber"? In the late 1990's, during the dot-com boom, telecommunications and media companies anticipated the future demand for extremely high bandwidth communications channels locally, regionally, nationally and internationally. They were quick to envisage a future where on-demand digital streaming multimedia was the norm and that existing infrastructure was clearly inadequate. There was the equivalent of an arms race to create and own optic fiber bandwidth and each company started laying hundreds of thousands of miles of ultra high capacity optic cable in anticipation of the future demand. For a long time most of that fiber was just sitting there waiting to be used at a future date. Well, I think that's sort of what we have in healthcare now; "dark data" - vast pools of digital healthcare data at rest, hardly ever touched and now dormant.
The reality is that big data is more that just the 3 V's - Volume, Velocity & Variability; all of which are increasing rapidly in healthcare today. It's really about the 4th V - Value. It's time to take the Big Data you have and turn it from dark data into value.
There are 5 key areas where I feel that we have tremendous potential to analyze healthcare's big, dark data in support of the national Three Part Aim of Better Health, Better Healthcare and Lower Costs.
1) Risk: Gain a deeper data-driven understanding of clinical and financial risk - both at the individual and population level
2) Care Quality & Outcomes: Expand and supplement existing EMR based clinical decision support systems (CDSS) with richer clinical signals detected using advanced analytics. The signals identify opportunities to intervene earlier and avert patient harm.
3) Care Efficiency: Improved understanding of the basis for both appropriate and inappropriate variability in both the cost and quality of care delivery.
4) Patient Engagement: Blend traditional healthcare data with other consumer information, including social media and other web based data to understand motivation and readiness to change as a way of beginning to unlock the complex issue of how best to drive improvements in patient engagement at an individual level.
5) Data and Knowledge Curation: There are vast stores of poorly curated knowledge in all healthcare organizations, from the increasingly tangled web of metadata that associates meaning to the data in storage, through to patterns in clinical care delivery that are not formalized into any formalized template driven structure. Analytics can help identify complex patterns in existing data and provide significant insight to help automate the ongoing challenge of institutional knowledge management.
Everyone is talking about Big Data in Healthcare but not many are yet giving specifics around how to tap big data to deliver value. The shovels required for this data driven gold rush will be true analytic solutions that move beyond current BI capabilities to allow us to look ahead and prepare for the future before it happens.
In future posts, I'll explore each of the 5 key areas above and give example of how we're addressing these opportunities with our customers.
