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The Great Data Escape

August 1, 2007
by Sami Benmechiche, Carol Chouinard, Ross Christen, Deepak Goyal, Ajit Kumar, and Richard Kupcunas
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Successfully mining clinical data depends on first constructing a proper data warehouse

Clinical data has been around as long as the medical profession itself. The practice of documenting observations, diagnostics, prescribed drugs, and procedures is an intrinsic part of providing healthcare. As healthcare companies move away from paper-based clinical records and deploy clinical information systems (CIS), more information is being stored electronically. Our research shows that operational systems for patient administration, orders, and results management, as well as laboratory, radiology, and pharmacy systems, are playing a major role in generating and storing raw clinical data.

Existing applications have struggled to cope with storing and processing ever-increasing clinical data, leading to the emergence of clinical data warehouses. These large, electronic repositories of information accrue over time through the normal processing of healthcare systems. Use of data warehouses began with the production of mandatory regulatory reports. Today, they are evolving into a resource for sophisticated clinical and financial predictive analysis (see Figure 1).

Key Factors Contributing to Extensive Use and Use and Sharing of Health Care Data



The rush is on

Our research indicates that several convergent factors are contributing to the exponential growth in clinical and financial healthcare data, leading to the evolution of clinical data warehouses:

  • Connectivity and networking between healthcare companies, resulting in connected local, regional, and national health information networks

  • Maturity and standardization of interoperability standards, such as HL7, ANSI X12, and XML, all helping to enable integration of disparate systems

  • Maturity and standardization of coding, helping physicians document their diagnostic and procedure information in a consistent manner

  • Conversion of more documents to electronic media storage: for example, historical paper-based charts converted to electronic format, radiology imaging converted from film to electronic format (see Figure 2)

  • More-sophisticated diagnostic methods, such as genetic testing, the affordability of testing, and the growing complexity of procedures

  • Legal and regulatory pressures, requiring greater transparency and traceability throughout the care delivery life cycle

  • Greater acceptance of privacy- and security-related technologies and procedures, such as HIPAA.

EMR Adoption Percentage EMR Adoptin by Practice Size



Together, these factors are presenting information management challenges for every stakeholder in the healthcare value chain — hospitals, health plans, government health bodies, patients, pharmaceutical companies, and biotechnology companies. The gold rush is on to tap the potential for building and exploiting clinical data warehouses.

Who gets the gold?

As more data is created and managed through clinical data warehouses, key questions emerge: Who is all this data for? And, how are they going to use it? Here are some possible answers for key stakeholder groups.

Hospitals

Most hospitals have built a central data repository for continued data compilation from patient administration, clinical, financial, and claims submission systems (see Table 1).

Current and Future Benefits for Hospitals

Current Usage

Future Trends

  • Store historical information

  • Analyze and forecast the level of utilization of their facilities

  • Support medical research

  • Provide medical management data

  • Perform case management

  • Provide report to regulatory bodies

  • Create a secondary source of information — for situations where the primary applications become unavailable

  • Analyze and reconcile cost and revenue

  • Transfer or obtain electronic medical records (for out-of-area, or recently relocated patients)

  • Compare quality of care with comparable facilities

  • Submit reportable disease to authorities in real-time

  • Refer patients to other providers and electronically book appointments

  • Perform analysis that includes the patient's family history

  • Utilize medical data to reduce medical errors

  • Perform cost containment and feasibility studies

  • Adapt to consumerism: use customer relationship management data to enhance patient experience, share anonymous data with potential business partners

Enormous untapped potential exists for large providers that have yet aggregated data from multiple facilities or regions. Our research shows that many providers also have not yet used data in a preventive manner, such as using demographic data to schedule tests, influencing patient behavior (e.g., lifestyles and medication compliance), or comparing a patient's health history to the family's health history to better deal with possible negative outcomes.

Health plans

Health plans have been the most proactive in building data warehouses and effectively using clinical data (see Table 2). Health plan data warehouses, mainly built on claims data, have been used to conduct medical management analysis, detect fraud, monitor patient behavior, and implement preventive care programs. In fact, our research shows that health plans are at the forefront of trying to aggregate data from multiple sources — such as pharmacies, dentists, disability claims, and alternative medicine providers — and develop plans that cover all aspects of care.

Current and Future Benefits for Health Plans

Current Usage

Future Trends

  • Perform medical management analysis

  • Perform actuary analysis

  • Report to regulatory bodies

  • Provide data to pharmaceutical and biotech industry (for marketing analysis)

  • Detect fraud

  • Minimize redundancy of procedures

  • Align compensation to quality of care

  • Further support the promotion and implementation of preventive care programs

  • Enhanced capacity for cost sharing

  • Adapt to consumerism: further market segmentation, provide individual incentive for healthy behaviors (participation in health clubs, disciplined medication, not smoking, etc.), or share anonymous data with potential business partners

  • Transparency: a direct influence of the consumerism trend, health plans want to share more information (cost of procedures, alternative plans, etc.)

Now, health plans are starting to realize that it is possible to achieve financial benefits by analyzing aggregate data. It is widely known that health plan business models are based on the ability to predict the cost of providing healthcare to a group of patients. The more a health plan knows about its patients, the more accurate its forecast will be. One can only imagine the level of precision achievable with genomic, history-of-family health records, which could allow health plans to offer adapted coverage to large groups or achieve more precise market segmentation. However, although the potential benefits are huge, the ready availability of patient data poses ethical concerns.

Government health bodies

Availability of enhanced aggregate data at different levels of government can allow changes in the current reimbursement model (see Table 3). Instead of focusing only on the procedures performed, future contracts could be based on longer episodes (e.g., between life events), payments could be based on the quality of care, and providers could have incentives to be more aggressive in emphasizing prevention.

Current and Future Benefits for Government Health Bodies

Current Usage

Future Trends

  • Disease monitoring (for reportable conditions)

  • Medical management: analysis of cost, utilizations, claims trend

  • Payment by results

  • Ability to perform real-time disease monitoring

  • Centralized services, such as laboratory or radiology analysis

  • Understanding impact of programs and planning new programs

  • Enhanced fraud detection

Additionally, government agencies may be better able to protect consumers and develop frameworks and models that can work for all parties.

Patients

Patients have historically had very limited visibility into their own clinical data. Our research shows that a number of initiatives aimed at creation of patient-owned personal health records (PHRs) have had limited results. This situation may very well change as providers begin to deploy clinical information systems that simplify patient-provider interaction. New functionality could allow patients to make online appointments, e-mail their physicians, and view their personal medical records. We foresee a day when patients could also add to their EMRs by tracking their own habits, symptoms, and medications or by pointing their providers to other care providers, such as dentists, chiropractors, and alternative medicine practitioners.

Where to go from here?

What does all this mean to your company? For certain, the explosion of clinical information means that your data is increasingly becoming a strategic asset that you should better manage and more effectively use.

To meet some of the challenges discussed here, consider taking these actions:

  • Enforce information governance. Create a data governance body that will manage data as a strategic, enterprise-wide asset.

  • Prepare for a distributed model. Build mechanisms to exchange data among data warehouses or link data from different sources.

  • Think security. Address privacy and security issues by identifying legitimate groups of users requiring access to patient-specific information.

  • Collaborate. Promote networking and sharing of data with national or regional health information networks.

  • Standardize. Enforce enterprise-wide standards such as SNOMED (Systematized Nomenclature of Medicine), HL7 Clinical Documentation Architecture, and ANSI, and develop tools to map to other formats.

  • Adopt consumerism methods. Analyze patients' behavior and define methods such as communication and financial incentives that will help influence them toward better outcomes.

  • Engage and train business users. Establish a feedback loop for continuous improvement in data views and their applicability to your company.

  • Use an iterative delivery approach. Implement data warehousing projects in a series of steps, so you can adjust and adapt the solution rapidly to reduce risk.

Are you ready?

Total healthcare spending in the United States is expected to increase dramatically. With more information being created and processed by every healthcare stakeholder, the opportunity to tap the power of clinical data warehouses is tremendous. In this paper we have described the factors contributing to the explosion of clinical data and explored potential uses of data warehouses. Now, the most important challenge facing your organization is how and when to tap these powerful resources. Are you prepared to go for the gold?

Sami Benmechiche is senior consultant, Deepak Goyal is manager, and Carol Chouinard, Ross Christen, Richard Kupcunas and Ajit Kumar, are senior managers at New York-based Deloitte Consulting LLP


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