You can’t treat what you can’t see. In the healthcare arena, this statement rings true not only for patient care but also for the business performance of healthcare organizations. With the passage of the Affordable Care Act and its associated focus on value-based versus volume-based care, both payers (health plans/insurers) and providers (hospitals/clinics/integrated delivery systems) are finding they must change the way they do business to make their patients healthier—and to manage the costs associated with achieving that goal.
Big data and predictive analytics are leading the way in this new business model. However, healthcare organizations still struggle to manage and leverage effectively the massive amounts of data they collect and generate.
Historically, payers applied business intelligence tools primarily to claims data stored in data warehouses to reduce overall costs, detect fraud, and optimize the operation of their facilities. This data helped payers gain market share within partner networks and cut overall claim costs by detecting fraudulent and wrongful claims early.
But today, payers feel growing pressure to make fuller use of data. Specifically, they’re looking to negotiate more favorable, lower-cost contracts with providers; predict high-risk patients for Accountable Care Organizations (ACOs); anticipate how value-driven activities such as tests and procedures will improve clinical outcomes; and quantify healthcare costs and recommended wellness activities.
These are highly sophisticated goals, and payers are turning to highly sophisticated datasets to accomplish them. They’re collecting and analyzing a dizzying array of customer experience data (including sentiment, social, website, call center notes, financial and demographic information, and IoT data from wearable devices); supplementary clinical EHR data points and pharmacy records; and additional billing, financial and provider supply chain data.
To draw value from it all, payers are also rapidly evolving their information architecture to support predictive analytics. Forward-thinking organizations are leveraging analytics to understand and meet inventory needs, develop better pricing models, slash fraud and waste, optimize their workforces, manage costs, and improve profitability.
Blue Cross of California, Family Health Network, and Healthcare Services Corporation (HCSC) worked with Oracle to strengthen their foundational systems and reduce costs. These organizations chose Oracle Cloud Applications to help them provide healthcare coverage at a more affordable cost by digitizing and modernizing their financial, planning, budgeting, and business processes. The Oracle Enterprise Resource Planning (ERP) Cloud has helped all these organizations simplify and streamline operations with increased visibility and insights into financial and operational activities. Reducing IT complexity and costs have increased productivity, freeing employees to provide insured members with better, more affordable health insurance plans.
Providers constantly face the challenge of managing costs while improving the patient experience and patient health outcomes. Facing the same pressures as payers when it comes to shifting reimbursement models, providers are also looking for new and innovative ways to analyze patient data to improve clinical quality and strengthen their bottom lines.
With patient data going digital, providers have a growing body of information they can consolidate and analyze to improve patient outcomes in the move to value-based care and population health-based business models. And, while clinical data is fueling the initial analytics drive, providers are also looking beyond clinical information.
Effective population health management requires healthcare providers to rely heavily on additional data derived from their own IT systems. Identifying patients at high risk of for chronic diseases or failing to follow treatment protocols is a significant challenge for many organizations, but this capability is quickly becoming essential for value-based care.
To develop a comprehensive portrait of a patient’s clinical, financial, and social risks, healthcare providers must aggregate key data from across the care continuum before they can leverage risk scoring frameworks and target interventions to individuals. Those data sources include not only clinical data from EHRs, but also genomic sequencing profiles, billing and financial records, customer experience and wearables data.
To organize and leverage this rising sea of data effectively, organizations need a robust IT infrastructure. Oracle Big Data Appliance and Oracle Database Appliance serve as the foundation for a data solution that can harness clinical and related data and turn it into better patient outcomes.
Wit-Gele Kruis is a home-care organization providing nursing services to more than 150,000 homes across five provinces in Flanders, Belgium. The organization wanted to increase operational efficiency and improve patient care by providing nurses and management staff with timely, accurate, up-to-date business intelligence. Wit-Gele Kruis deployed Oracle Database Appliance and Oracle Business Intelligence Suite with a focus on improving its analytics and automation capabilities. Now, service department leaders are able to monitor staff performance in real time rather than having to generate monthly performance reports. New dashboards allow them to detect and respond immediately to changes in demand for nursing services throughout the provinces. In addition, the organization has automated the creation and delivery of customized reports to staff, managers, and employees, which has saved time and helped prevent errors. Says Steven De Block, IT manager of Wit-Gele Kruis, “Our new data warehouse, which is run on Oracle Database Appliance, improved the quality of home care we provide to tens of thousands of patients.”
The more that payers and providers can leverage the data being generated by a growing ecosystem of sources, the better they will be able to deliver on their goals of providing better care at lower cost. Emerging information sources like genetic data, digitized clinical data, customer experience data, and information from IoT-powered wearable technologies will drive more personalized care and reduce overall healthcare costs.
Payers and providers appreciate the role that predictive analytics will play in their efforts to personalize treatment, manage chronic diseases, and mitigate clinical and financial risks. In fact, a whopping 93% of healthcare organizations participating in a 2017 Society of Actuaries survey said they won’t be able to address the financial and clinical challenges of the future without investing in forward-looking, big data analytics.
These analytics capabilities, however, will not be possible without the scalability of the cloud. Healthcare organizations need cloud-ready IT infrastructure that not only makes it simple to move operations to the cloud, but includes hardware and software engineered to work optimally together for the best performance possible. Oracle engineered systems deliver out-of-the-box functionality for the high-end analytics that healthcare demands and offer identical on-premises and cloud infrastructure for seamless migration to the cloud.
Michael Walker is the Industry Solutions Group Global Lead for Healthcare and Life Sciences at Oracle with over 25 years of experience in various capacities working across healthcare, medical device, biopharmaceuticals and clinical research.
In addition to Oracle, Mike has held positions in management consulting and industry including, Vice President of Supply Chain, Director of Product Strategy, and operations roles. Mike holds a degree in computer science from the University of Pennsylvania with certifications in Six Sigma and APICS.