The Business Case for Using Big Data in Healthcare

Transcription

1 SAP Thought Leadership Paper Healthcare and Big Data The Business Case for Using Big Data in Healthcare Exploring How Big Data and Analytics Can Help You Achieve Quality, Value-Based Care

2 Table of Contents 4 Changing Hospital Dynamics 5 Addressing New Business Challenges 6 Addressing Healthcare Challenges with Big Data Technologies 8 Proving the Value 9 Next Steps A World of Potential 2 / 9

3 Healthcare is transitioning from a cottage industry to a mission-based industry focused on best-in-class patient care. This evolution is driven by three business drivers: payment reforms, declining insurance reimbursements, and increased government requirements. To succeed, hospital executives need a strategy that aligns with this mission and the data and analytical tools to actively manage care delivery. This paper explores the critical role of Big Data and analytics in operationalizing quality, value-based care. 3 / 9

4 Changing Hospital Dynamics THE IMPACT OF NEW BUSINESS DRIVERS Quality of care improvements are top of mind for hospital executives and care providers today. What s driving this focus on care quality? New payment reforms, declining insurance reimbursements, and increased government requirements. Hospitals must address these three business drivers with the support of real-time information from cutting-edge technologies or there will be serious ramifications from patients, insurance companies, and the government. Widespread Payment Reforms Payment reform is causing hospitals to shift from focusing on patient volume as their key success driver to maximizing patient care quality and outcomes. To succeed, hospitals will need faster access to key patient information and the ability to analyze this data to measure and improve patient care. For example, they will need to analyze every episodic moment of care to gain insights across the entire, end-to-end continuum of care spectrum. In addition, because payment reforms link medical errors and readmission rates to payments and incentives, hospitals will need to understand how to use their data to track performance and proactively identify opportunities to improve metrics. Declining Insurance Reimbursements As reimbursements decline and as healthcare costs rise, insurance companies are shifting market economics to force hospitals to consolidate and scale patient care. As a result, hospitals are under pressure to increase and accelerate operational efficiency and lower costs. Balancing these competing priorities while addressing these market changes will require real-time information to provide optimal care to patients. Increased Government Regulations Government regulations are focused on transparency and safety, which are related to mandates regarding the meaningful use of electronic health records to improve quality, safety, and efficiency and reduce health disparities. And consumers are using this transparency to make more informed choices about providers and demanding better healthcare. For example, because consumers have greater access to information about medical errors, their tolerance for preventable errors is decreasing. This is forcing hospitals to make drastic changes to address the causes of such errors. Hospitals must address payment reforms, declining insurance reimbursements, and increased government requirements with the support of real-time data. 4 / 9

5 Addressing New Business Challenges CHALLENGES ARE LIMITING PATIENT CARE IMPROVEMENTS Healthcare organizations also face many complex challenges that make it difficult to address the business drivers required to provide best-in-class patient care. For example, hospitals typically have networks with multiple clinical, financial, and claims systems that must be integrated, which is no small task. Frequent mergers and acquisitions (M&A) by hospital networks add to the complexity, making it nearly impossible to properly collect the information needed to drive business insights across the entire network. With each M&A, IT landscapes become even more diverse, and there s even more disparate data to integrate and analyze. This added complexity slows the velocity of information across networks, preventing healthcare professionals from making decisions at the speed that patients and other stakeholders require today. These types of challenges are impacting management of healthcare networks at all levels today from hospital administrators and chief financial officers to physicians and business owners. The following table summarizes the impacts on key stakeholders. Healthcare Network Stakeholders Hospital management Physicians Business owners The Impact of Growing Data Issues Lack of insight into the true costs of providing holistic care to a patient population Inability to assess the quality of care provided across the enterprise Uncertainty as to how to address variances in the quality of care once identified Lack of access to real-time information critical to making informed patient care decisions Dependence on analysts as technical intermediaries to access the data required to gain insights and manage care delivery in an agile manner Never-ending backlogs of requests for reports and modifications Limitation of large, unwieldy, and unresponsive information systems to satisfy management and clinical demands Inability to quickly modify or extend complex information structures in response to emerging regulatory and business requirements For some hospitals, it can take several hours or longer to retrieve data from 3, 6, or 12 months ago. Data access can also be hindered when valuable patient information is entered into patient medical forms as free or unstructured text. 5 / 9

6 Addressing Healthcare Challenges with Big Data Technologies PROVEN SOLUTIONS WITH BIG RETURNS Big Data technologies offer proven solutions to the challenges that hospitals and healthcare networks face today. Using innovative solutions, hospitals can integrate different types of data from fragmented sources and turn this data into insights for driving better decisions. These solutions are already being used successfully within hospitals to provide healthcare executives with self-service information access so they can: Keep up with real-time events Improve patient satisfaction Reduce hospital overhead costs These are just a few examples of the value Big Data solutions can deliver to healthcare organizations. The table below summarizes several use cases for Big Data technologies by management role, all of which are based on the experience of SAP consultants working with hospital networks. Organizations have many complex business challenges which make it difficult to address the business drivers required to provide bestin-class patient care. 6 / 9

7 Role Hospital administrator Hospital CFO Physicians and researchers Business owners Business Use Cases Addressed by Big Data Technologies Understand readmission rates to reduce preventable ones Mine information from payer systems (for example, claims) Leverage trends in key performance indicators (for instance, by analyzing data on ER visits and generic drug prescriptions) to identify outliers and take corrective actions Implement pay-for-performance plans to take advantage of payer incentives Monitor physicians through performance measures to drive optimal service levels Mine claims, reimbursements, patient and hospital quality outliers, and customer personal information (such as payment history) to actively manage cost, quality, and variances using real-time operational insights Optimize contract negotiations through improved cost visibility Aggregate insights from electronic medical records across the hospital network Mine data such as patient characteristics, treatment recommendations, and care outcomes Improve preventable care based on a better understanding of patient history data Understand the impact of unstructured data, such as medical images Understand patterns in drug side effects Actively monitor and manage capacity, care quality, and costs based on near-real-time clinical and financial information Provide information in real time to stakeholders making care decisions to improve the quality of care while lowering costs Value Drivers Reduce healthcare spend Increase revenue from payers Reduce penalties Improve performance and performance plan incentives Improve physician performance Reduce average length of stay Shorten waiting times Cut average cost per case Increase revenue from payers and patients Optimize resource consumption Improve contract terms with payers Reduce operating costs Improve healthcare quality Boost resource utilization across patient populations Improve research with improved access to quality data Decrease the risks and improve the benefits of various drugs Increase patient satisfaction Optimize referral patterns, patient acquisition, and retention Boost FTE and operational efficiency Improve effectiveness of program requirements Improve physician satisfaction Increase patient case volume 7 / 9

8 Proving the Value CUSTOMER SUCCESSES AND PROOF POINTS So how are hospitals already leveraging Big Data technologies to drive value for their networks and patients? Some are saving millions of dollars by leveraging Big Data technologies for hospital business administration purposes for example, to perform benchmarking and analyze readmission data. Others are using data for medical research, as illustrated in the two examples below: The Charité University of Medicine Berlin, the largest university hospital in Europe, leverages in-memory technology to achieve tremendous gains in performance. For example, by evaluating 900 million clinical data entries, the hospital has improved teaching and research capabilities. And by viewing 500,000 data points from patients using a real-time mobile app called Mobile Visits, the hospital streamlined work for doctors and shortened patient wait times. To learn more, visit /watch?v=rtt8b-b7nnu. Stanford University School of Medicine leveraged in-memory technologies to corroborate the results of a study that discovered the genetic risk of type 2 diabetes varies between populations. The study looked at 12 genetic variants previously associated with type 2 diabetes across 49 individuals. With in-memory computing, researchers were able to simultaneously query all 125 genetic variants previously associated with type 2 diabetes across 629 individuals. Using traditional methods, this analysis on this amount of data would have taken an unreasonable amount of time. To learn more, visit Hospitals are leveraging Big Data technologies to help lower healthcare costs, improve care quality, and optimize treatment outcomes for patients. 8 / 9

9 Next Steps A World of Potential SLOW ADOPTION CREATING OPPORTUNITIES FOR INNOVATORS For hospital networks, there s huge potential value in using Big Data and analytics solutions to overcome challenges and realize the goal of quality, value-based care. But most organizations have been slow to shift from using traditional, limited methods of analyzing data. To succeed, they need a faster, more holistic method that can quickly turn Big Data into insights that can drive value-based care across their network and ultimately to patients. A recent study conducted by the SAP Benchmarking group in which healthcare professionals were surveyed on the topic of in-memory technologies, confirmed this trend. The survey data found that: Twenty-six percent of healthcare providers do not have access to the right information at the right time to support decision making, analysis, planning, or forecasting requirements. Eighty percent of healthcare providers consider it critical to have access to the right information at the right time to support decision making, analysis, or planning requirements. This means there s a huge opportunity for innovative, forward-looking healthcare executives to lead the industry in adopting Big Data analytics for delivering high quality, value-based care. As explored in this paper, the first step is to understand how Big Data can help lower healthcare costs, improve care quality, and ultimately optimize treatment outcomes for patients. The next step is to develop a Big Data strategy. The most successful strategies focus on: Use case identification and maturity Information and application architecture Standards and process People, skills, and culture Governance The third step involves engaging with a trusted solution provider with proven expertise in Big Data analytics for healthcare organizations. The right partner can help decision makers move forward with confidence and achieve value quickly. For example, to help customers get started, the SAP Industry Value Engineering team offers SAP Value Management services, which includes a Big Data strategy engagement. As part of this service, SAP consultants work with healthcare organizations to develop a success map for their Big Data strategy. This offering, available at no cost, provides recommendations based on business and IT executive interviews. It also includes an in-depth business use case capability and gap assessment that links to the potential value of using Big Data within a hospital network. LEARN MORE If you would like to receive additional information on the Big Data Strategy engagement offering, please contact the SAP Industry Value Engineering team at To learn more about the impact of Big Data on healthcare, visit 9 / 9 Studio SAP 31587enUS (14/07)

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