2
Emerging Requirements Driving Multilayered Transformation

Like other sectors of society,1 health care today is data-driven and will become more so, especially if quality and safety are to be assured. As the provider of health care coverage to more than one-third of the U.S. population,2 CMS already maintains a huge repository of clinical, administrative, and claims data as well as information both on providers and on individual patients. To improve health care significantly and as mandated in the legislation referred to in Chapter 1, CMS is required to move beyond processing claims—it must also collect, manage, analyze, and make available information extracted from its data repositories. To date, the capabilities of CMS for improving health care quality have been limited because it cannot identify poor-quality performers and intervene in a timely fashion. Clinical data will likely play a much more central role in meeting the new requirements for information placed on the agency. A focus on clinical data3 will have significant repercussions—some positive, such as the accrual of additional information to help combat and detect fraud and abuse; and some challenging, such as the need to deal with massive increases in the volume of data and the requirement for new procedures for handling and analyzing new kinds of information. And, of course, another challenge will be that of developing and implementing appropriate policies and technical capabilities to ensure the confidentiality and security of data. To manage this shift, CMS will likely need to evolve both its information systems and its business processes, reassess the roles that it plays, and develop and implement a public communications strategy.

1

 Earlier this year, The Economist (February 25, 2010, available at http://www.economist.com/node/15557443) produced an accessible overview—“Data, Data Everywhere”—on the abundance of data and the challenges of managing information. See also Rakesh Agrawal, Anastasia Ailamaki, Philip A. Bernstein, Eric A. Brewer, Michael J. Carey, Surajit Chaudhuri, AnHai Doan, et al., “Claremont Report on Database Research,” May 2008; available at http://db.cs.berkeley.edu/claremont/claremontreport08.pdf.

2

July 2010 numbers from the Secretary of the Department of Health and Human Services indicate that 98 million Americans are enrolled in either Medicare or Medicaid/CHIP or both. See http://answers.hhs.gov/questions/3640.

3

The term “clinical data” refers to individual data elements related to patient care rather than to summary data or administrative claims data. Traditionally CMS has had to know, for instance, what tests and procedures were performed (in order to reimburse for those items), but now increasingly it will also have to know the results of those tests and procedures in order to do, for example, quality assessments.



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2 Emerging Requirements Driving Multilayered Transformation Like other sectors of society,1 health care today is data-driven and will become more so, especially if quality and safety are to be assured. As the provider of health care coverage to more than one-third of the U.S. population,2 CMS already maintains a huge repository of clinical, administrative, and claims data as well as information both on providers and on individual patients. To improve health care significantly and as mandated in the legislation referred to in Chapter 1, CMS is required to move beyond processing claims—it must also collect, manage, analyze, and make available information extracted from its data repositories. To date, the capabilities of CMS for improving health care quality have been limited because it cannot identify poor-quality performers and intervene in a timely fashion. Clinical data will likely play a much more central role in meeting the new requirements for information placed on the agency. A focus on clinical data3 will have significant repercussions—some positive, such as the accrual of additional information to help combat and detect fraud and abuse; and some challenging, such as the need to deal with massive increases in the volume of data and the requirement for new procedures for handling and analyzing new kinds of information. And, of course, another challenge will be that of developing and implementing appropriate policies and technical capabilities to ensure the confidentiality and security of data. To manage this shift, CMS will likely need to evolve both its information systems and its business processes, reassess the roles that it plays, and develop and implement a public communications strategy. 1 Earlier this year, The Economist (February 25, 2010, available at http://www.economist.com/node/ 15557443) produced an accessible overview—“Data, Data Everywhere”—on the abundance of data and the challenges of managing information. See also Rakesh Agrawal, Anastasia Ailamaki, Philip A. Bernstein, Eric A. Brewer, Michael J. Carey, Surajit Chaudhuri, AnHai Doan, et al., “Claremont Report on Database Research,” May 2008; available at http://db.cs.berkeley.edu/claremont/claremontreport08.pdf. 2 July 2010 numbers from the Secretary of the Department of Health and Human Services indicate that 98 million Americans are enrolled in either Medicare or Medicaid/CHIP or both. See http://answers.hhs.gov/questions/3640. 3 The term “clinical data” refers to individual data elements related to patient care rather than to summary data or administrative claims data. Traditionally CMS has had to know, for instance, what tests and procedures were performed (in order to reimburse for those items), but now increasingly it will also have to know the results of those tests and procedures in order to do, for example, quality assessments. 4

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The following are just some of the types of information that emerging demands will likely require CMS to provide: Information to support consumers and patients in health maintenance and improvement. CMS is experiencing increasing expectations and demands for making data and information tools available to support consumer empowerment and patient-centered medical care. Examples of such expectations and demands include the following: interfacing more proactively with program beneficiaries and patients through consumer-friendly user interfaces (making secondary non-electronic channels available as needed), offering access to personal health information, and providing users with decision-support tools to help them make better- informed decisions about health choices. Information to support a “learning health care system.” 4 CMS must identify those areas in which timely access to accurate information will best contribute to objectives for health care improvement just as other large enterprises are using information to meet analogous business objectives. Examples of such areas include the following: (1) collecting and disseminating meaningful data on quality (especially data that can be generated from and incorporated readily into provider workflows), (2) promoting population health (which also has specific implications for data needs and data structures),5 and (3) generating claims data in a timely fashion (e.g., to support the effective functioning of accountable care organizations6). CMS may well need to be able to partner with patient-centered medical homes to provide the necessary data. Information needed to implement the meaningful-use program for electronic health records. Pursuant to the provisions of the HITECH Act described in Chapter 1, CMS must determine whether an eligible health care provider meets the prescribed meaningful-use criteria in order to determine when it is appropriate for incentives to be paid or for penalties to be applied. CMS is the final arbiter with respect to meaningful-use outcome measures, which will ultimately need to be generated from EHR data. This responsibility demands new levels of IT sophistication from the agency and its partners. Not only will CMS have to be able to share data and extract information related to meaningful-use criteria from clinical health information, but it will also be playing an integral role in defining how such data are collected. This new role raises a host of issues related to standards, data modeling, terminology, best practices, accuracy, completeness, security, and confidentiality, and it will need to be factored in to the design of CMS’s process and planning for its future IT infrastructure. Consumable data about health provision and outcomes. CMS will need to support the provision of data and information, often of new types, to a wide variety of users. This is largely 4 See the Institute of Medicine’s Roundtable on Value and Science-Driven Healthcare and its associated reports (available at http://www.iom.edu/Activities/Quality/VSRT.aspx) for more on the topic of a learning health care system. 5 See D.J. Friedman and R. Gibson Parrish II, “The Population Health Record: Concepts, Definition, Design, and Implementation,” Journal of the American Medical Informatics Association 17:359-366, 2010. 6 The term “accountable care organization” refers to a health system model that organizes care providers into entities responsible for managing patients and delivering a continuum of care across different institutional settings, such as hospitals, outpatient clinics, and so on. 5

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a new activity that CMS and its IT systems do not appear to be designed, resourced, or organized to support. For example, the agency is mandated by the HITECH Act to work to reduce racial and ethnic disparities in health care, and pursuant to the Patient Protection and Affordable Care Act it is mandated to collect and report data reflecting key demographic variables required to meet this obligation.7 Researchers also seek clinical data that are captured during the patient-care encounter rather than as a by-product of the claims-submission process. Managers of clinical services need these data as well, and their needs tend to be more time- critical, often regarding ongoing patient care or institutional performance, making timely access to accurate information important. Timely information to support the preemptive detection of fraud. Despite considerable attention to this very significant issue, such as the formation of cross-agency initiatives with the Department of Justice, much of the focus is on investigation, prosecution, and the recouping of dispensed funds. The preemptive detection of fraud—that is, before payment is made— generally has significantly higher payback than does detection after payment is made, but preemptive detection requires very timely data as a foundational capability. CMS may need to further develop, or partner to improve, its ability to access, process, and analyze data in a timely fashion as a first step, and then to implement appropriate systems and business processes to enhance this vital function. The multitude of potential stakeholders in CMS’s efforts is suggested by the range of CMS’s responsibilities today. Those responsibilities include the following: As a purchaser of health care services, CMS is responsible for provider contracting, quality improvement, and so on. As an administrator of health plan services, it is responsible for eligibility determination, enrollment, payment, referrals, and monitoring for fraud and abuse. As a provider of health education and health promotion, CMS is responsible for the delivery of personalized health information to enrollees and patients, among other tasks. 7 With respect to Medicare, CMS depends primarily on the Social Security Administration for demographic data, but indications are that these data are incomplete and insufficient. For Medicaid, indications are that state-level data collection and reporting are inconsistent and not always either systematic or reflective of the minimum standards promulgated by the Office of Management and Budget (OMB) and addressed by recent studies from the Institute of Medicine (IOM) and related studies on subpopulation data needs. The minimum standards established by OMB in 1997 require reporting of the following groups: American Indian/Alaskan Native, Asian, Black/African-American, Native Hawaiian/Other Pacific Islander, and White. OMB also provides for the reporting of ethnicity with the two broad categories Hispanic or Latino, and Not Hispanic or Latino. (See Federal Register, Vol. 62, No. 210, October 30, 1997. In addition, see Institute of Medicine, Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement, Cheryl Ulmer, Bernadette McFadden, and David R. Nerenz, eds., The National Academies Press, Washington, D.C., 2009; and Institute of Medicine, Future Directions for the National Healthcare Quality and Disparities Reports, Cheryl Ulmer, Michelle Bruno, and Sheila Burke, eds., The National Academies Press, Washington, D.C., 2010.) 6

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As a regulator, CMS is responsible for Medicare, Medicaid, CHIP, some aspects of health reform, and some aspects of health IT. And, of course, as an employer itself, CMS has responsibilities related to that role. Managing expectations for CMS’s wide range of constituencies will be ever more important, along with developing and maintaining methods to learn from and communicate with stakeholders. As the health care industry continues to evolve, the requirements for data from multiple constituencies will continue to increase rapidly. These requirements will include the need to provide access to clinical information, the generation of improved administrative and claims data, and the incorporation of new information and the aggregation of multiple data sources. Demand will increase from a number of sectors, including researchers who require increased access to clinical-level information for diverse populations as well as improved administrative and claims information to support comparative-effectiveness research and the evaluation of new care-delivery models. Policy makers will demand more timely information (e.g., a lag of 2 to 3 months rather than the current lag of 18 months or more) so that they can better evaluate the impact of new policies on program performance and cost. Additional potential requirements include demands for increasingly well integrated patient-level information at the point of care; the implementation of new care-delivery models such as accountable care organizations, including medical homes; increased dependency on EHRs and evidence-based decision-support systems; and the identification of methods to improve public health.8 It is not yet clear to what extent CMS will be required to play a role in meeting the requirements described above and what will be asked of it. But CMS should expect, sooner or later, to become a principal participant in all of these areas.9 To the extent that CMS itself will be responsible for developing or procuring solutions, it will need to provide support and direction to entities (e.g., subcontractors) regarding solutions and systems that will address indicated needs; CMS will need to ensure that such entities have appropriate levels of understanding of enterprise-wide architectural considerations. An understanding of the existing IT infrastructure capabilities of CMS will be a critical starting point in this consideration. An objective understanding of the existing capabilities, strengths, and weaknesses is a huge asset in such an undertaking. Developing a vision of the future requires a thorough picture of the current situation and the technical marketplace. This understanding allows more credible planning and more potential for optimizing the vision with less uncertainty. It will also be important for attention to be focused on developing both an appropriate infrastructure and an organizational alignment to meet these needs. In particular, it 8 With regard to improving public health, IT systems transformation could offer the opportunity to do more sophisticated sharing and exchange of data with other agencies (for example, with the Food and Drug Administration and the Centers for Disease Control and Prevention)—to the extent that policy decisions or user demands urge such exchanges. 9 Complicating matters still further, a clear trend in data-driven domains (for example, business intelligence) is that as benefits accrue from improved or additional data, the demand for data rises. Thus, it can be expected that demand will increase, fueled by the value derived from access to data. Anticipating data demands far in excess of currently projected uses will likely be important. 7

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seems likely that in many cases it will not be sufficient for new data and information products to be viewed as just add-on features to, say, an existing claims-processing system. To start to address the sorts of demands described above, CMS might begin to consider information that it provides as a new set of “products.” More generally, the current and prospective roles of CMS and the consequent needs for data and information raise the following kinds of fundamental questions for the agency: What kinds of information can and should CMS provide? What is the market for such information, and what does that market expect in terms of data and information products? How can CMS processes and systems be restructured or replaced to support easier generation of such information and data? How should CMS track and manage provenance information associated with the data that it is using? What protections will be in place for assuring compliance with legally mandated and emerging confidentiality and security requirements for patient data while also ensuring sufficient access for legitimate biomedical and health research? What is the role of CMS relative to other stakeholders—for example, in setting standards and in data collection, data management, and data and information extraction and distribution? How should CMS design, manage, make available, and recover the costs of its information products? In short, CMS is faced with significant growth in the complexity of requirements, some of which may conflict with one another when quality constraints are applied. In such circumstances, evolving the scope of change incrementally to control complexity is important. Furthermore, the requirements and demands on the infrastructure (hardware, middleware, software architecture) need to be understood and specified. In particular, the future growth and change scenarios ought to be explicitly characterized as part of the process of gathering requirements. Modern IT solutions such as data warehousing, identity management, business process management, and business intelligence—and associated new architectural approaches—all have the potential to play important roles in meeting CMS’s future data and information requirements. Chapter 3 briefly discusses enterprise transformation—in terms of both business process and information systems. 8