Let's quantify something you probably already know. In 2012, the U.S. spent 20% of its gross domestic product (or $3 trillion) on healthcare. Not only is this massive, it's twice as much as any other developed country. And costs will get worse before they get better, according to recent projections.
Despite its world-class medical technology, the U.S. is grossly inefficient in terms of controlling costs, managing patient information and reducing waste. To wit, an estimated 28% of its annual spend was deemed "unnecessary" by the Kauffman Foundation.
The Affordable Care Act (ACA) hopes to change that, of course, by tying reimbursements to providers' cost and patient care performance. Case in point: Unnecessary procedures, which nearly half of all practitioners see as a problem.
But hospitals, physicians and healthcare providers need more than just regulation to improve care, predict outcomes, reduce costs and empower patients. They need analytics.
Six Ways Analytics Can Improve Healthcare
1. Better collaboration. Gone are the days of authoritative medicine. With the enactment of the ACA, payers and providers must work together and share accountability for the total cost of care. To do this, information about patient health is increasingly being combined with non-health information and third-party consumer insights to create multidimensional predictive models. These models are important because they lead to better patient stratification, which ultimately leads to higher engagement, improved health and reduced costs.
2. Reduced costs. Under the status quo, health organizations are incentivized by excessive visits or procedures, presumptuous admissions and other inefficiencies to increase volume of billing. Analytics, on the other hand, can be used to base pay on performance, where instead of volume, providers get paid by outcomes. Obviously, practitioners are entitled to fees for work performed even when a patient's health takes a turn for the worse. But when armed with analytics, providers can and should use available data that focus more on outcomes and value than on volume of patient care. For instance, analytics better enable early diagnosis to reduce total cost of an ailment or illness. With rule-based triggers, analytics also combat billing fraud, duplicate prescriptions and excessive medication. And they can help prioritized surplus or scarce healthcare access to those most in need.
3. Smarter outcomes. Big data benefits healthcare, too. But only if medical providers know how to capture all patient data in a single place which helps them better interpret what the information is telling them. In other words, evidence-based medical decisions related to recent practitioner research, technical reports, clinical trial studies, expert views and patient characteristics (including those from their social Web site and app usage) to enable appropriate intervention at the point and time of care. Like all industries, healthcare-related data is growing at a rate of 35% per year. Analytics are required to effectively mine this data to improve health outcomes.
4. Reduced admissions. Nearly one in five Medicare patients are readmitted within 30 days of hospitalization. That has to stop. Analytics can help. By one example, a leading U.S. healthcare was able to reduce readmissions by 22% with analytics. And where hospitals and other providers fail to show a reduction in admissions, regulators will penalize them with up to 3% of reimbursements. So not only will analytics be necessary to reduce waste, they're required to ensure compliance and full payouts. Hence, it's imperative for healthcare organizations to understand readmission metrics, prepare a response by condition and physical performance and compare outcomes with benchmark rates.
5. Better preventive care. In an increasingly competitive world, where reimbursements are declining and proof of better care is required to improve outcomes, organizations must analyze all available data to their advantage. But they can also use the data to conduct risk assessments, identify patients at risk, analyzing gaps in care, prioritize treatment and elevate pre-care planning. In other words, when armed with analytics, providers can move from administering care to preventing it. For instance, employing mobile apps such as wellness calculators to educate and engage patients. Once engaged, providers can then tailor a preventive health plan unique to them. They can also use such information to identify at-risk patients.
6. Empowered patients. Consumers can and should become more responsible for their own health (and its associated cost) if provided with more insights. They can, for instance, select the best provider in their vicinity by examining a report card on various institutions. And customer relationship management and marketing techniques used in retail can also be emulated to understand appropriate correspondence with patients to send the right message at the right time. For instance, monitoring systems are available to notify patients at prescribed intervals for need procedures and medicine or therapeutic reminders about their health.
The Way Forward: Six Things to Do
Given the benefits, healthcare organizations must create an analytics environment that pervades the entire organization. For instance, data should focus on patients' protected health information for research while still complying with HIPAA. Transparency should be overseen by a reliable steward as the organization shifts from volume transactions to quality outcomes. And providers should begin collecting, piloting and deploying high-value subsets of data around specific diseases, as well as train and acquire talent in health IT and clinical informatics.
That said, here are six ways to get there:
1. Emphasize fact-based decision-making. Data should be structured and analyzed as a guideline for the organization to improve efficiencies and make decisions. The data should be freely available to all stakeholders who want to use it. Of course, there must be balance between data quantity and quality so that physicians are not overwhelmed; only relevant insights should be made available to them.
2. Provide feedback where required. Most clinicians appreciate comparative analysis with other clinicians. If analytics are used and the shortcomings are presented in the right format, then an overall improvement in outcomes should follow. When that happens, clinicians should be clearly told what needs to change, such as drug administration or the use of testing.
3. Ensure collaboration between IT and domain experts. Both structured and unstructured data from inside and outside the organization should be integrated, allowing for both insights and foresights. These insights should be delivered across the entire organization and its applications. Only then can analytic tools be applied to decision-enabling forecasts.
4. Digitize physical data. Data is data. But you can't run a successful analytics program with manila folders. To get the most of the information you have as well as making it available to other stakeholders, the data must be in electronic form. It's a costly endeavor, no doubt, but also much needed medicine to become a analytics-driven healthcare organization.
5. Make secondary use of transactional data. For example, healthcare organizations should consider revenue-generating partnerships with pharmaceutical companies to leverage transactional data. This ensures an immediate return on analytics for all participating suppliers.
6. Use a pay-per-use analytics model. As volumes increase, this can help your organization avoid higher fixed investments while scaling its analytics culture.
All told, analytics are of equal benefit to the payer and provider. Implementing them in a healthcare setting is understandably a significant challenge. But they are a key enabler of better information, better collaboration, better effectiveness and most importantly, better health.
For more information, read the full white paper, Analytics-Driven Healthcare: Improving Care, Compliance and Cost or visit our Healthcare Practice.