IBM SoftwareWhite Paper

Healthcare

Using analytics and collaboration to improve healthcare quality and outcomes

2 Using analytics and collaboration to improve healthcare quality and outcomes

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Contents

2 Executive summary

4 Advancing patient safety

5 Improving clinical outcomes

7 Promoting wellness and disease management

8 Moving toward better collaboration and analytics

11 How IBM can help

Executive summaryHealthcare provider organizations are facing major market and regulatory changes that are driving a fundamental shift in the expectations of all stakeholders. They are looking to transform their organizations in ways that will allow them to maintain the highest standards of quality while transitioning to new business models based on outcomes and value.

o address these market forces, providers need to adopt new approaches that will enable them to deliver better quality and outcomes, and focus on giving patients the full value of the money they spend on healthcare. Many organizations realize that enhancing collaboration and utilizing analytics will help them achieve these goals, but are not sure exactly what is needed or how to get there.

Collaboration in the healthcare setting means much more than people working together to treat patients. It is about connecting care delivery channels so that evidence-based insights and clinical knowledge can be coupled with patient-specific information to personalize care. Achieving this level of insight requires organizations to do a better job of aggregating trusted patient data and applying specialized knowledge to improve decision making, care delivery and health outcomes.

ccess to more and better information alone does not ensure effective collaboration. The ability to analyze that information and turn it into meaningful change is what will make the biggest difference in helping to ensure the long-term success of healthcare providers’ transformation efforts.

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Many organizations are already improving performance by leveraging analytics. Those organizations using analytics to achieve competitive advantages are 2.2 times more likely to substantially outperform their industry peers, and 84 percent more likely to have information management and business analytics integrated into their core business strategy.1

As healthcare organizations attempt to enhance processes to improve care and outcomes, most will focus first on one of three core areas where collaboration and analytics can yield the greatest benefits: advancing patient safety, improving clinical outcomes and promoting wellness and disease management. Organizations that use collaboration and analytics capabilities across all three areas will achieve the most significant competitive advantages from a financial, marketing, consumer targeting, safety and outcomes perspective and will be better equipped to:

• Comply with safety and quality reporting requirements• Predict and prevent adverse events and readmissions• Identify new effective treatments and care plans• Measure and effectively communicate results to consumers• Identify and manage a defined population of patients• Coordinate care among care team members• Manage wellness and diseases instead of treating illnesses

This white paper discusses how organizations can benefit from implementing collaboration and analytics processes in the three core areas, how healthcare organizations are successfully using collaboration and analytics to improve outcomes and value, and the best way for organizations to achieve their collaboration and analytics goals.

4 Using analytics and collaboration to improve healthcare quality and outcomes

Advancing patient safety Patient safety failures, often called “silent killers,” result from medication errors, medical administration errors, wrong-site surgical errors, hospital-acquired infections, falls and other accidents and problems. Hospitals want to advance patient safety practices to keep patients safer and reduce their legal and financial risk. Improving safety is especially important as both patients and payers look more closely at provider patient safety ratings and reward or penalize organizations based on their results.

To advance patient safety, healthcare organizations are looking for ways to efficiently comply with required safety reporting requirements, predict and prevent adverse events and reduce preventable readmissions. Although there are some established patient safety reporting metrics that hospitals already participate in, such as Leapfrog and the US National Committee for Quality Assurance, organizations are struggling with how best to gather and measure data to meet new reporting requirements, track patient safety with key performance indicators (KPIs), define the patient safety attributes they want to improve and make sense of all of the data dispersed throughout their enterprise, including data in unstructured formats such as electronic medical records, patient charts, incident reports and so on. In addition, healthcare organizations are attempting to quantify the impact of safety metrics and gaps on outcomes and quality of care.

With regard to patient safety, healthcare organizations want to have the capabilities to:

• Provide early alerts on adverse events to prevent infections or outbreaks

• Offer cost-effective preventative programs to decrease costly emergency room care

• Create a standardized and timely set of patient safety data • Move toward automated enterprise-level reporting• Enable physicians, nurses and other caregivers to proactively

identify patients at risk for readmission• Identify allergies and medications to prevent adverse

drug interactions

Analytics can help organizations realize these patient safety goals and more. For example:

• NorthCarolina’sDukeUniversityHealthSystem prides itself on a deep culture of innovations that manifests in every part of the organization, from clinical operations that are consistently ranked among the top 10 in the United States to world-class academic and research capabilities that drive breakthrough discoveries. Duke University Health System is using analytics to help improve patient safety. By drilling down into millions of clinical records and then applying analytics, Duke University Health System is able to detect near-miss situations, develop predictive models that automatically flag potential high-risk future scenarios, define best clinical practices and train hospital personnel on best practices and how to better detect potential patient safety issues.

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• TheHospitalforSickChildren(SickKids)inToronto, the largest center dedicated to improving children’s health in Canada, wanted to improve outcomes for infants afflicted with life-threatening nosocomial infections. Findings from a research study conducted at the University of Virginia indicated that infants who had contracted the disease could have undetectable changes in heart rates up to 24 hours before overt signs of trouble occurred. SickKids is combining the research findings with more than a thousand data streams from bedside monitors and analytics to better detect potential signs of an infection. The project, called Artemis, is a research collaboration between SickKids, the University of Ontario Institute of Technology and the IBM T.J. Watson Research Center’s Industry Solution Lab. About one-third complete, to date the project has gathered data from 300 children. It is still too early to report on success, but researchers and clinicians are hopeful that Artemis will deliver significant future benefits for many types of medical diagnostics.

Advancing patient safety will go a long way toward helping provider organizations improve care quality and outcomes, but enhanced collaboration and use of analytics have additional direct benefits on efforts to improve clinical outcomes.

Improving clinical outcomesImproving the outcomes of clinical treatments and processes has been a focus of healthcare providers for many years, but it is now more important than ever as they strive to become more competitive and participate in accountable care organizations (ACOs). Analytics help providers identify new effective treatments and care plans, and measure compliance against those plans, which is necessary to ensure high quality rankings, qualify for reimbursement based on new funding models and gain insights in time to have a positive effect on patient outcomes.

As consumers become more responsible for their own healthcare, many are evaluating providers based on quality rankings that are influenced by outcomes, such as those published by the US Department of Health and Human Services (HHS). A recent study by the HHS Agency for Healthcare Research and Quality (AHRQ) found that consumers were more likely to choose high-value providers when presented with strong, unambiguous quality and cost information.2 Therefore, it is increasingly important for organizations to measure and effectively communicate cost and quality results to consumers.

To provide high-value care while improving outcomes, and operate within the cost constraints of the new reimbursement models, the most effective approach for health organizations is to actively participate in collaborative care initiatives. Competitive healthcare organizations are using analytics to help in this process.

6 Using analytics and collaboration to improve healthcare quality and outcomes

As organizations begin to examine what they need to do to enhance clinical outcomes, they are asking how they can:

• Move from a fee-for-service to a performance-based reimbursement model

• Effectively aggregate patient records to deliver a true longitudinal view

• Give physicians and other caregivers the information they need to make more-informed decisions

• Assess whether patients are following treatment protocols • Identify and implement new treatment protocols

more quickly• Determine which individual providers are delivering superior

efficacies on specific morbidities • Enable providers to collaborate more effectively

Analytics help provide answers to all of these questions and more. For example:

• CaliforniaPacificMedicalCenterinSanFrancisco is one of the largest private, not-for-profit academic medical centers in California. Through the medical center’s Research Institute, patients and physicians have opportunities to participate in groundbreaking clinical studies in a number of disciplines including cardiology, oncology and neurology. The cardiac research program is involved in a number of complex, multidisciplinary projects to advance the treatment and survival rate of patients with cardiovascular disease. These projects require thousands of data elements to be managed and analyzed to determine more effective ways to treat patients; develop accurate cardiac risk models that improve long-term outcomes, shorten patient stays and reduce costs; and establish new, proven treatment protocols that can be shared with and adopted by cardiologists worldwide.

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• SoutheastTexasMedicalAssociates(SETMA), an innovative and award-winning primary healthcare group based in Beaumont, Texas, is using analytics technologies to reduce hospital readmission rates. The practice analyzes clinical data to help it identify the causes of patient readmission and develop more comprehensive treatment and intervention care plans that prevent patients from returning to the hospital. In just six months, SETMA reduced the number of hospital readmissions by 22 percent. Physicians collect and analyze data that identifies patient characteristics that resulted in lower readmission rates including ethnicity, socioeconomic groups, follow-up care received, and how much and how quickly patients were able to receive care. Analytics are also used to determine similarities among readmitted patients, and develop post-hospital treatment plans that include recommendations vital to many patients’ recovery such as immediate at-home care or interventional support for patients who live alone.

In addition to patient safety and clinical outcomes, collaboration and analytics can provide significant benefits for the promotion of wellness and disease management, especially for patients with chronic diseases.

Promoting wellness and disease managementAs the US reimbursement model shifts its focus to a person’s overall health versus treating episodes of care, healthcare providers must focus more on managing wellness. Individuals with chronic conditions today account for 75 percent of total US healthcare expenditures.3 More than 125 million Americans suffer from at least one chronic condition and 75 million have two or more chronic conditions.4 Disease management and

programs that promote wellness can improve the overall health of those with chronic diseases, which will help reduce healthcare costs.

To successfully implement wellness and disease management programs, healthcare organizations must be able to accurately identify populations of patients, coordinate patient care teams, and shift their focus to managing patient wellness instead of illness. For example, organizations that are able to identify and manage patient populations with a specific chronic disease, such as diabetes or heart disease, can more effectively monitor these high-risk patients, coordinate care plans and more rapidly intervene to prevent disease-specific medical conditions from developing.

Analytics can help provider organizations identify patient populations and provide insights that effect collaboration across care teams—both of which are difficult to achieve today. In addition, analytics enable organizations to determine how to:

• Better manage the health of defined populations• Identify the best potential candidates for wellness and disease

management programs • Determine the patient and clinical information needed to

better promote wellness or manage diseases• Communicate and monitor patients outside of care venues • Define and manage the data touchpoints across the

continuum of care• Aggregate the information required to demonstrate better

outcomes and qualify for bundled payments • Calculate the return on investment (ROI) for population

health management and wellness programs

8 Using analytics and collaboration to improve healthcare quality and outcomes

Analytics also help organizations support effective prevention and disease management programs. For example:

• SetonHealthcare, the leading provider of healthcare services in central Texas, wanted to identify patients with congestive heart failure who were most likely to be readmitted to the hospital and provide them with proactive disease management to reduce cost and mortality rates, and improve patient quality of life. Seton is utilizing analytics technologies to extract key elements from unstructured data such as physician notes and discharge summaries, and apply proven predictive models against structured and unstructured data to achieve rich clinical and operational insights. Trends and patterns in patient care and outcomes are identified by detecting correlations or disparities that were previously hidden in inaccessible free-text files. Access to this new information allows Seton to improve disease management processes and prevent avoidable readmissions.

• AnAustraliancompany that is transforming the management of chronic diseases developed a chronic disease management network, an automated collaborative management system that drives the uptake and ongoing use of patient care plans to manage chronic diseases. The network uses innovative decision support and rules-based technologies combined with broadband and mobile services to assist with evidence-based practices, care coordination, wellness monitoring, patient self-management and performance analysis. By enabling the creation of best-practice patient care plans and allowing caregivers to track and share patient information and care plans, the network helps ensure the effective delivery

of a collaborative treatment plan. Users of the system have benefited from a 100 percent increase in evidence-based care and best-practice treatment, a 140 percent increase in care team collaboration across providers and a 60 percent improvement in the use of patient care plans.

Many healthcare providers are already on their way to improving care and quality through better collaboration. What steps do organizations that want to embark on this journey need to take? The following is an overview of a proven process—one that many providers have already deployed—that will help organizations get started.

Moving toward better collaboration and analyticsHealthcare provider organizations that want to achieve better collaboration and analytics proficiency to improve care quality and outcomes will need to follow a number of steps to get there. To begin, they must evaluate their own organization and decide which of the three core areas (patient safety, clinical outcomes or wellness and disease management) they should focus on first. The choice is often based on which area will deliver the greatest value in the shortest timeframe, but some organizations have pressing operational or risk issues that will drive their decision.

Once the area of focus has been determined, organizations will need to plot where they fit on the business optimization maturity curve (see Figure 1) and understand what they need to do to advance along that curve. From there, they will develop an actionable, customized plan to successfully implement analytics for the first core area and create an infrastructure that will effectively support all three core areas. At all times, the focus should be on mapping their strategy to overall business goals and objectives.

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Figure 1: Ad hoc organizations use very basic spreadsheets and data extracts that provide them with a lot of data but little information. As they deploy analytics and data-driven processes, they become breakaway organizations that fully leverage their data, turning it into a strategic asset and utilizing it with predictive real-time analytics to improve care quality and outcomes.

• Actionable insights, pre-emptive and predictive business management

• Information deemed a strategic asset

• Predictive, real-time analytics

• Business scenario modeling• Deep analytical skill sets• Information is governed

• Consistent and trusted reporting

• Standard data definitions and governance

• Lack of analytical skill sets• Minimal report standardization• Manual data manipulation

• Basic

operational needs

• Data, but no information

• Spreadsheets

and extracts

• Master data management• Basic data warehouses and

departmental data marts

• Data warehouse appliance

• Dashboards, scorecards

• Structured and unstructured data

• Advanced information management

• Content analytics

Ad hoc

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Competitive

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Smarter analytics maturityHow the business manages information and learns from it

10 Using analytics and collaboration to improve healthcare quality and outcomes

Most organizations will find themselves somewhere in the middle of the maturity curve; the majority will be in the foundational area of the curve. This means they have implemented some data warehouses and are doing basic analytics, but need to move up the business optimization maturity model to truly address the imperative of collaborating to improve care and outcomes.

Organizations must next create a strategy and road map for turning data into information and using it as a strategic asset to deliver the greatest possible impact. During this process, they will need to consider how to:

• Align people, processes and information to sustain strategic value over time

• Establish end-to-end information-driven strategies and objectives that promote business priorities

• Architect an extensible infrastructure that leverages existing information assets

• Accelerate short-term and long-term ROI

The strategy and road map will need to account for many of the challenges healthcare provider organizations will face as they attempt to improve their collaboration and analytics capabilities. These challenges will likely include aggregating widely dispersed data, delivering data in a timely way to the systems and people that need it, providing caregivers with a complete and accurate picture of the patient, and alerting caregivers about patient safety, clinical treatment and care plan issues at the point of care where they can have an immediate impact.

Once the strategy and road map are complete, organizations can begin implementation. This process involves creating a trusted, relevant and governed information environment where data can be managed, integrated and analyzed while ensuring data quality, security and privacy standards are met (see Figure 2). The system must be able to accommodate data from internal and external sources that must be mastered and managed, and will need to integrate with a range of transactional, collaborative and analytics applications. Once the system is complete, healthcare provider organizations will be able to deliver trusted information and insights that can be used to improve care quality and drive smarter outcomes.

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How IBM can helpIBM can guide you on your journey to improving care quality and outcomes through better collaboration. From assessing your current place on the maturity curve to developing a road map and strategy, to implementing new collaboration and analytics capabilities, IBM has experienced consultants, products and solutions that can help.

IBM has more than 8,000 employees dedicated to healthcare, has completed more than 3,000 successful healthcare transformation initiatives, and holds more than 600 patents in the life sciences, healthcare and medical device fields. As an active participant with its healthcare clients and partners, IBM is working to lay the foundations of a 21st-century healthcare system by redefining value and success in healthcare and helping to build a smarter healthcare industry.

Govern Lifecycle StandardsQuality

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Manage

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Content

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External information sources

Business analytics applicationsIntegrate

and cleanse

Figure 2: Data must be managed, integrated and analyzed to deliver trusted information and insights. Data governance processes should be built into the entire process to ensure that data quality, security and privacy standards are met.

For more information To learn more about IBM solutions for healthcare, visit ibm.com/analytics/us/en/solutions/industry/healthcare.html

© Copyright IBM Corporation 2012

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Produced in the United States of America October 2012

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This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates.

The client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions. THE INFORMATION IN THIS DOCUMENT IS PROVIDED “AS IS” WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided. Statements regarding IBM’s future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

1 The New Intelligent Enterprise, a joint MIT Sloan Management Review and IBM Institute of Business Value analytics research partnership. Copyright © Massachusetts Institute of Technology 2011.

2 “Study Finds Consumers Choose High-Value Health Care Providers When Given Good Cost and Quality Information.” http://www.ahrq.gov/news/press/pr2012/highvaluepr.htm. Accessed August 24, 2012.

3 “Chronic Illness Accounts for 75 Percent of Health Spending,” US News & World Report. http://health.usnews.com/health-news/blogs/on-health-and-money/2009/01/06/chronic-illness-accounts-for-75-percent-of-health-spending. Accessed August 24, 2012.

4 Geyman JP. “Disease Management: Panacea, Another False Hope, or Something in Between?” Annals of Family Medicine, Vol 5(3), May/June 2007.

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