Everywhere you look, healthcare is undergoing an incredible shift. Changing reimbursements, payer uncertainty, provider consolidation, and even how patients themselves are taking control of their care decisions. Analytics promises to move the dial on many of these challenges the industry is facing.
If you’re a provider, whether in private practice, or part of a hospital or health system you’ve no doubt seen the shift in patient behavior first-hand. With the growth of high-deductible healthcare plans, patients have never been more engaged in their healthcare journey, taking a more consumer-centric approach to their care. Its why providers need insight into patient satisfaction and opportunities to build loyalty.
While legislative uncertainty around healthcare seems to be the new normal, the industry is on an ongoing march from cost-based care towards outcome-based care. Payers are partnering more closely with providers around claims and clinical data, looking to learn what’s working and what’s not for member engagement programs, and adjust member outreach as needed. Providers are looking to gain a clearer picture of how to make better, more effective care decisions based on aggregated clinical data by applying population health management analytics and strategies.
Pharmaceutical sales teams are pushing to up their effectiveness by having more focused, meaningful discussions centered on healthcare outcomes with physicians, decision makers, and other influencers—because most physicians prefer a meeting that’s five minutes or less.1 This is why it’s crucial to understand how a sales team is adjusting their behavior, and where the opportunities are to coach them.
In MedTech, field support and advisory services are overtaking traditional sales as the best way of reaching physicians— a recent Bain study finding surgeons now value technical support in the operating room and on-call support more than a standard sales pitch.2 Data from IoT connected medical devices is shifting field and customer service from being reactive to proactive. MedTech sales teams must now understand a 360-view of an account, from sales to every aspect of service to driving revenue.
Data science and analytics is a clear opportunity … but
Analytics and technologies like machine learning and Artificial Intelligence will enable every kind of healthcare organization to drive change. According to its report on big data in healthcare, McKinsey estimates it will deliver close to half a trillion dollars in value to the healthcare industry—better outcome-based decisions, more efficient claims management, more effective sales and service.3
But here’s the thing—only 10% of healthcare leaders say they are using data analytics to their fullest potential, as estimated by KPMG.4
Why the gap? There are three big reasons. Healthcare data is incredibly siloed across electronic health and medical record systems, payment systems, clinical decision support apps, and other systems. Legacy data warehouses and traditional business intelligence tools just aren’t agile enough to keep up. Analytics tools haven’t kept up with the spiraling growth of healthcare data volumes that is increasing by nearly 50% annually, as predicted by EMC and IDC Research.5 Running analytics for population health, or for claims reporting, is often just plain unwieldy and slow.
But the final gap is perhaps the biggest too little relevance. Analytics tools are stuck on desktops of a few analysts, not where it counts—in the hands of health plan service agents, pharmaceutical sales managers, or hospital administrative staff.
Change is on the horizon
Things, however, are changing fast. HIMSS conducted a workforce study that suggests that deploying data analytics technology to drive better, faster decisions has jumped to a top-five priority across the healthcare technology landscape this year.6
The opportunity and benefits have now become too good to ignore. The latest AI and machine-learning technologies now enable healthcare professionals to answer not only what happened, and why it happened, but what will happen and what they can do about it — providing insights on the best course of action to take, at scale, and in context.
In healthcare service, it means enabling service agents and managers to not only make smarter decisions, whether fielding a question from a health insurance plan member on online chat, or handling a complicated technical support call on an imaging modality, but do so at scale by managing customer satisfaction, case volume, team performance, and trends across all channels. And for those in healthcare administration, it’s about running from easily comparing hospital operating expenses against an external benchmark and understand the roadblocks to excellent patient experience and relationship.
The capabilities and applications of analytics are innumerable for the healthcare industry, and so analytics will be a major underpinning of the next wave in healthcare transformation.
- Sullivan, T. (2018, May 6). Nearly Half of US Physicians Restrict Access by Manufacturer Sales Reps — New Strategies to Reach Physicians. Policy & Medicine. Retrieved from https://www.policymed.com/2013/10/nearly-half-of-us-physicians-restrict-access-by-manufacturer-sales-reps-new-strategies-to-reach-physicians.html
- van Biesen, T., Weisbrod, J., Brookshire, M., Coffman, J. & Pasternak, A. (2017). Front Line of Healthcare Report 2017: Why involving doctors can help improve US healthcare. Bain & Company. Retrieved from https://www.bain.com/insights/front-line-of-healthcare-report-2017
- Kayyali, B., Knott, D. & Van Kuiken, S. (2013). The big-data revolution in US health care: Accelerating value and innovation. McKinsey & Company. Retrieved from https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/the-big-data-revolution-in-us-health-care
- Healthcare must climb analytics maturity ladder. (July 2016). KPMG. Retrieved from https://assets.kpmg.com/content/dam/kpmg/pdf/2016/07/colombia-bt2-9hc-healthcare-must-climb-the-analytics-maturity-ladder.pdf
- Corbin, K. (2014, December 16). How CIOs Can Prepare for Healthcare ‘Data Tsunami’. CIO. Retrieved from https://www.cio.com/article/2860072/healthcare/how-cios-can-prepare-for-healthcare-data-tsunami.html
- 2018 HIMSS U.S. Leadership and Workforce Survey. (2018). Healthcare Information and Management Systems Society. Retrieved from https://www.himss.org/sites/himssorg/files/u132196/2018_HIMSS_US_LEADERSHIP_WORKFORCE_SURVEY_Final_Report.pdf