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									                                                           Original Contributions

National Health Data
Warehouse: Issues to
 Lynn A. Blewett, PhD, Stephen T. Parente, PhD, Michael D. Finch, PhD, and Eileen
                               Peterson, RN, MPH

 A B S T R A C T                                                                                 maintained and mined by health services
A national data warehouse that links public and private data                                     researchers and analysts for national pol-
                                                                                                 icy development and, more recently, to
could be used to monitor trends in healthcare costs, utilization,                                monitor quality of care. The patient-level
                                                                                                 diagnosis related groups (DRGs) of
quality of care, and adherence to quality guidelines and changes                                 Medicare’s Prospective Payment System
                                                                                                 (PPS) were created using historical
in treatment protocols. The development of the data warehouse,                                   Medicare claims data. Similarly,
                                                                                                 Medicare’s physician payment system –
however, would require overcoming a number of political and                                      the Resource-Based Relative Value Scale
                                                                                                 (RBRVS) – was developed using physi-
technical challenges to gain access to private insurance data.
                                                                                                 cian-level claims data. In addition, efforts
This article outlines recommendations from a national                                            to identify national trends in costs, quali-
                                                                                                 ty of care, and access to care by under-
conference sponsored by the Agency for Healthcare Research and                                   served populations have also benefited
                                                                                                 by the use of Medicare claims data.
Quality (AHRQ) on the private sector’s role in quality                                              However, while Medicare claims data
                                                                                                 have been critical to the development of
monitoring and provides an operational outline for the                                           Medicare reimbursement systems, there
                                                                                                 is no comparable data warehouse for the
development of a national private sector health data warehouse.                                  non-Medicare, under-65 population.
                                                                                                 Consequently, there is little national data
 K E Y W O R D S                                        W    hile the debate about the useful-   available to analyze trends in quality and
                                                     ness and feasibility of a national health   cost for many chronic health conditions
Administrative data                                  data warehouse for private medical care     (e.g., heart disease and diabetes) that
National health data                                 claims continues, important questions       commonly develop in people under age
                                                     remain unanswered, including: What is       65. Attempts to build a national sample
                                                     the intrinsic value of a data warehouse?    for this population using state Medicaid
Quality monitoring                                   What purpose would it serve? Are the        claims data have shown promise, but
Community health                                     benefits worth the costs of development     such efforts do not provide nationwide
                                                     and maintenance?                            coverage due to the parochial design of
 management information
                                                        Analysts and regulators have             state Medicaid programs.
 systems (CHMIS)                                     addressed these questions using                On the private side, only a handful of
System design                                        Medicare claims data. For two decades, a    proprietary vendors, including Medstat
                                                     national health data warehouse of           and Ingenix, hold data warehouses of
Data specifications
                                                     Medicare fee-for-service claims has been    sufficient scale to be considered national
Data collection
52   Journal of Healthcare Information Management — Vol. 18, No. 1
                                                   Original Contributions

in scope. These databases, however, are       system. In the early '90s, the Hartford           resenting tens of millions of patients.
built using data from a convenient sam-       Foundation funded seven sites across the              Incorporating private health insurance
ple of clients who are willing to consent     country to construct Community Health             claims data into a national health data
to sharing their patient data in a de-        Management Information Systems                    warehouse presents a formidable chal-
identified format.                            (CHMIS). These systems were to serve as           lenge, as there are several hundred pri-
   This article explores the need for a       data networks and repositories to sup-            vate insurers and thousands of employ-
national health data warehouse for private    port the information needs for their indi-        ers who self-insure their patients.
health insurance claims and recommends                                                          Furthermore, insurers are currently
actions necessary if such a system is to be                                                     focused on compliance with the privacy
established. We begin with a discussion of                                                      and security provisions of the Health
the background of the data warehouse                                                            Insurance Portability and Accountability
concept. Next, we present the highlights
                                               “…because a number of insurers                   Act (HIPAA) and are uncertain about
of a national conference sponsored by the       have consolidated, only the top                 how to act even if they wanted to con-
Agency for Healthcare Research and                                                              tribute data to a national warehouse.
Quality (AHRQ) on the private sector’s         10 insurers would have to agree                      Despite these concerns, some recent
role in quality monitoring. We conclude                                                         developments make the proposition of
with recommendations for next steps in
                                                 to participate to constitute a                 building a private sector national health
the development of a private sector            database in the tens of millions                 data warehouse more tractable. First,
national health data warehouse.                                                                 because a number of insurers have con-
                                                of privately insured patients.”                 solidated, only the top 10 insurers would
The Need for a National Health                                                                  have to agree to participate to constitute
Data Warehouse                                                                                  a database in the tens of millions of pri-
   Currently, a multitude of private insur-   vidual geographic regions. The idea was           vately insured patients. In addition, sev-
ance plans pay claims for millions of         to link the regional data systems to cre-         eral of these large insurers already pos-
Americans. This multi-payer system            ate a national data repository. Due to a          sess research groups that seek to publish
includes for-profit and not-for-profit        confluence of political, market, technolo-        peer-reviewed results from their databas-
health plans, as well as fully insured,       gy and telecommunications develop-                es in scientific and industry journals. The
self-insured, and managed care plans.         ments, this project was largely unsuc-            timing is right, but grassroots interest and
The resulting mosaic of payers and pay-       cessful across all seven sites.2                  motivation must now be generated to
ment schemes makes it nearly impossible          The CHMIS experience, however, was             bring such a system to fruition.
to get a clear picture of the healthcare      instructive in several ways. First, the con-
financing structure in the United States.     cept was too grand. Too many parties              Data Specifications
   In recent years, there has been some       were involved requiring extensive coor-              To build a national health data ware-
interest in combining data across pay-        dination and consensus, and the upfront           house, the initial specifications would
ment systems with a focus on quality          investments of time and effort were too           consist of three basic components. First,
measurement.1 For the most part, these        high and yielded too few tangible                 healthcare claims data (including both
efforts have been led by the health insur-    results. Second, the project failed to            fee-for-service and managed care plans
ance industry and by large employers          build on existing data structures and sys-        data) would form the foundation of the
with programs such as: (1) the widely         tems. And third, the project did not con-         database and would permit the aggrega-
used Health Plan Employer Data                tain a model for use and applications of          tion of a single patient’s time-indexed
Information Set (HEDIS) sponsored by          the system and the data.                          health service utilization data across all
the National Committee for Quality               Despite the challenges faced by the            locations of medical care where insur-
Assurance (NCQA), (2) the Foundation          ambitious Hartford experiment, interest           ance payment was received. Second, the
for Accountability (FACCT) quality mea-       in such a concept continues to grow as            data residing in the warehouse would be
sures, and (3) the IMSystem and ORYX          the need to understand healthcare costs           de-identified to ensure patient privacy by
programs of the Joint Commission for          and utilization intensifies. Moreover,            replacing the actual patient IDs with
the Accreditation of Healthcare               monitoring quality indicators to support          encrypted values. This process would
Organizations (JCAHO). These projects         value-based purchasing will require a             enable patient data to be grouped by
have focused on the creation of discrete,     national database with a representation           specific treatment episodes across multi-
pre-defined measures of quality and out-      of millions of de-identified patients that        ple encounters with the healthcare deliv-
comes that cut across health plans and        combines public and private sector                ery system. Third, providing for future
provider organizations.                       patients. To engineer this database               ability to link clinical results to claims
   One ambitious initiative attempted to      would require addressing the missing              data by medical encounter or laboratory
bring together public and private inter-      piece in the mosaic of national data –            test would be essential to make the
ests to develop a common information          private health insurance claims data rep-         database “electronic medical record”

                                                                               Journal of Healthcare Information Management — Vol. 18, No. 1   53
                                                            Original Contributions

(EMR) compatible.                                     of design elements. To that end, we             type of drug, date and dosage of med-
   While we currently lack a model for                begin with a discussion of the basic            ication dispensed, duration of the pre-
linking clinical and administrative data,             strategic design approach and issues. We        scription, and amount dispensed.
initial work in linking data from inde-               then move on to consider a variety of           Pharmacy claims should follow the
pendent clinical labs with ambulatory                 specific diseases for inclusion in a proto-     guidelines produced by the National
claims data has demonstrated the possi-               type system.                                    Council for Prescription Drug Programs.
bility of building a database that records                                                               Include Patient-level Demographics
not only the use of a particular lab test,                                                            through Membership Databases. It is
but also the results of that test. For                                                                universally important to include patient-
example, a diabetic patient’s linked clini-                                                           level information to enable the appropri-
cal and administrative data would not                                                                 ate evaluation and comparison of out-
only describe the use of a lab test for
Hemoglobin (HbA1c), but it would also
                                                      “While the basic elements are                   comes. Information on age, gender, and
                                                                                                      geographic location is the most readily
contain the clinical value of that test                 straightforward, the devil in is              available. However, conference partici-
(HbA1c), which would indicate poor                                                                    pants were adamant that data on race,
metabolic health for that patient.
                                                                  the details.”                       income, and ethnicity must not be for-
   While the basic elements are straight-                                                             gotten. Moreover, they acknowledged
forward, the devil in is the details. We              System Design Elements                          that the routine collection and reporting
attempt to address one aspect of the                      Integrate Information from                  of these items is enmeshed with con-
detailed analysis necessary to prepare for            Multiple Automated Systems. It is               cerns about privacy, discrimination, and
the development a national health data                important to begin by linking data sys-         politics, and such issues require further
warehouse. This paper highlights the                  tems where feasible, but to also build in       consideration and discussion.
results from a workshop on the role of                flexibility for additional future linkage as    Membership databases should be linked
private sector data in monitoring national            technology allows. Currently, we would          with claims data and unique identifiers
quality sponsored by the Agency for                   be able to link medical claims, pharmacy        assigned members at the time of enroll-
Healthcare Research and Quality                       claims, and data on patient demographics.       ment. These identifiers should be struc-
(AHRQ). The University of Minnesota, in                   Start with Medical Claims. Medical          tured to allow the grouping of house-
partnership with UnitedHealth Group’s                 claims or encounter data are collected          hold members.
Center for Health Care Policy and                     from all healthcare sites (inpatient, hospi-       Link Patient Data with Finance
Evaluation, conducted this conference in              tal outpatient, emergency room, physi-          and Organization Variables. To truly
the fall of 2000. This one-day invitational           cian offices, surgery centers, etc.) for vir-   understand the dynamics of cost and
meeting of national experts focused on                tually all covered services provided to         quality interactions in healthcare, the
developing a conceptual model and cre-                enrollees, including specialty, preventive,     delivery and financing infrastructure of
ating an outline for a longitudinal data-             and office-based treatment. A claims-           the healthcare system must be examined
base using patient-level administrative               based system should include claims for          and understood. To do this, key indica-
data from the private sector. The objec-              inpatient and outpatient services, as well      tors of financial performance must be
tive of this meeting was to bring together            as submissions by managed care plans.           included in any data warehouse system
national researchers and policymakers to              Health plans and providers should be            to allow comparisons on cost, utilization,
evaluate the feasibility of establishing a            able to submit claims either by mail or         revenues, and expenditure trends.
private sector managed care data reposi-              electronically, and all claims and coding       Additional examples of performance
tory for the purposes of monitoring and               must conform to industry standards, i.e.,       information could include: (1) the impact
evaluating changes in healthcare quality              ambulatory claims, typically submitted by       of health plan organization on perfor-
over time.3 These discussions identified              physicians, must use the hcfa-1500 for-         mance; (2) the effects of capitation and
several issues relevant to the develop-               mat and claims submitted by institutions,       payment approaches on provider adher-
ment of a national health data ware-                  typically hospitals, should be in the           ence to and outcomes of practice guide-
house. These issues are presented in fur-             ub-82 or ub-92 format.                          lines; (3) a comparison of utilization
ther detail below.                                        Include Pharmacy Claims. Pharmacy           measures by geographic area, diagnosis,
   The intent of developing a national                claims are critical to understanding            or other sub-populations; and (4) the
private sector health data warehouse                  trends in costs, quality, and treatment         price elasticity of demand for specialist
would be to link public and private data              patterns. Claims for pharmacy services          care. Again, attention must be directed
over time in an effort to monitor trends              are typically submitted electronically by       toward what is currently available and
in healthcare costs, utilization, quality of          the pharmacy at the time a prescription         what can be added over time.
care, and adherence to quality guidelines             is filled and should be incorporated into          Include Medical Errors Reporting.
and changes in treatment protocols.                   any private sector data system. Each            Based on the recent Institute of Medicine
These goals should drive the discussion               pharmacy claim specifies the pharmacy,          (IOM) reports on medical errors and

54    Journal of Healthcare Information Management — Vol. 18, No. 1
                                                     Original Contributions

patient safety,4, 5 a great deal of focus has   from administrative records would be a            reporting, and links to other data sources
been placed on medical error reporting          more efficient way to monitor hyperten-           for the analysis of factors contributing to
and follow-up. Again, conference partici-       sion than expensive and labor-intensive           higher rates of surgical error.
pants expressed a fair amount of con-           retrospective medical record chart                   Depression. Perhaps because it is so
cern that any data systems developed to         reviews. A potential incentive to encour-         difficult to define, report, and monitor,
monitor medical errors not be indepen-          age plans to include specific measures in         another area that is often overlooked,
dent of ongoing quality initiatives.                                                              under-treated, or undiagnosed is depres-
Rather, the group agreed, that data col-                                                          sion. It may be relatively easy to identify
lection and reporting activities should be                                                        patients with depression diagnoses, and
integrated.                                                                                       then to evaluate whether they have
    Focus Must Include Prevention.
Consideration should be given to data            “HIPAA regulations                               received appropriate care. However, it is
                                                                                                  extremely difficult to identify patients
elements that could be used to highlight                                                          who may be suffering from undiagnosed
prevention services based on existing
                                                  requiring the adoption of data                  depression. Data elements to focus on
guidelines and protocols. For an                  standards and administrative                    include prescription drug and dosing
employed, privately insured patient pop-                                                          information, monitoring changes in prac-
ulation, preventive services are a key              simplification practices are                  tice and treatment, findings of depression
component of a quality monitoring sys-                                                            on routine health risk appraisals, and
tem. Such measures form the basis of
                                                     smoothing the way for the                    information on benefit sets, carve-outs,
ongoing quality monitoring systems, such              creation of consolidated                    and employment programs such as
as HEDIS. Prevention includes screening                                                           employee assistance plans. These mea-
for PSA, breast cancer, immunizations for                  data systems.”                         sures could help address issues of
children, flu shots for those at risk, as                                                         absence of care, meaning that services
well as smoking prevention and health                                                             might have been provided through other
education programs. Prevention is critical      their data files would be to exempt plans         mechanisms. Efforts should focus on
to maintaining and improving the health         that routinely submit these data from             using existing data on diagnosis and
status of populations.                          HEDIS chart review. While blood pres-             treatment and adding health status
    Focus on a Predefined List of               sure information is currently not collect-        assessments or screeners over time.
Conditions. Workshop participants               ed as part of an administrative data set,            Heart Attacks. Workshop partici-
agreed that the list of conditions to con-      there are initiatives to add some new             pants agreed upon one health condition
sider for inclusion in a national private       CPT codes, as blood pressure values               where good data and indicators are cur-
sector health data warehouse should ini-        would certainly be useful for monitoring          rently available in existing data structures
tially be short and targeted. Moreover,         hypertension care.                                – heart attack. Further, they agreed that
the conditions selected should represent           Patient Safety. While avoiding med-            future efforts should focus on how a pri-
high-volume, resource-intensive health-         ical errors and ensuring patient safety are       vate sector national health data ware-
care situations where evidence shows            clear priorities, these measures are              house initiative could augment the ongo-
that interventions can make a difference.       among the most difficult to tackle at the         ing work based on Medicare claims data.
Selection of conditions should include          outset. The workshop participants rec-            This issue appears to have a lot of
priority for conditions with the greatest       ommended two possible areas to address            momentum, and it might be a place
disease burden. In addition, the system         in this area: (1) drug dosing and dispens-        where quick turnaround of valuable data
should start with conditions where data         ing, and (2) surgical procedures. In the          may be available for reporting purposes.
is currently available and expand over          area of drug dosing/dispensing, adverse           Specific data elements to focus on
time to include other data linked to pri-       drug reactions (ADRs) were identified as          include: (1) medications after discharge,
ority conditions.                               an important area to address. The group           (2) the use of beta-blockers, and (3) the
                                                reached some agreement that govern-               use of aspirin.
Recommendations on Priority                     ment leadership may be required to                   Basic Prevention Screening. Basic
Conditions                                      encourage more rapid development of               screening information should be routine-
   The list of priority conditions could        interventions in this area. It is conceiv-        ly collected and reported. In addition,
vary based on the specific focus of the         able that a data system could be built on         practice guidelines for time frame, age,
system. In an effort to link cost and           existing algorithms utilizing drug refill         and risk factors should be followed.
quality monitoring the following list of        schedules, potentially harmful drug inter-        Screening protocols for the younger pop-
conditions is presented.6                       actions, and data on prescriptions filled.        ulation should include hearing and
   Hypertension. While HEDIS does               Surgical errors represent another area of         vision screening, blood lead-level screen-
include a measure of controlled hyper-          great concern to the public. There are            ing, high diastolic blood pressure
tension, the automated collection of data       opportunities for effective monitoring,           (HDBP), antibiotic history, and obesity.

                                                                                 Journal of Healthcare Information Management — Vol. 18, No. 1   55
                                                            Original Contributions

Screening protocols for an older popula-              an increasing competitive managed care        the development of query software to
tion should include cancer screening,                 environment. Information on the charac-       answer key “what if” policy questions in
obesity, and depression.                              teristics of the health plan and/or health-   a timely fashion.
                                                      care system should be linked with indi-           Use an Incremental Approach. The
Recommendations for Next Steps                        vidual measures of quality. An effective      development of a private sector quality
   Despite the multitude of barriers                  quality monitoring system will include        monitoring system that links health plan
described above, monitoring quality in                system measures that currently exist and      data over time is an ambitious and
the private sector is a timely and appro-             develop new indicators over time. Key         important task. Any such initiative
priate undertaking. Developing a proto-                                                             should start small and use an incremen-
type system to assess the practicality and                                                          tal approach, building on existing data
feasibility of a comprehensive national                                                             systems and reporting structures. The
health data warehouse infrastructure is a                                                           goal is to develop a usable, effective,
proposal that bears consideration for a                                                             data-driven system starting with existing
number of reasons. First, information
technology has advanced to where such
                                                         “Too often, legislative and                administrative data at a reasonable cost.
                                                                                                    Once a small-scale prototype is devel-
a system is not only feasible, but also                 policy initiatives are driven by            oped and its usefulness demonstrated,
practical. Second, HIPAA regulations                                                                additional plans and data elements could
requiring the adoption of data standards
                                                          anecdotes, instead of careful             be added over time. For example, a sys-
and administrative simplification prac-                consideration of available data.”            tem built with existing inpatient data
tices are smoothing the way for the cre-                                                            could be augmented by patient-level
ation of consolidated data systems. And                                                             and ambulatory care system data when
finally, we have seen demonstrated                    indicators of financial performance may       it becomes available.
momentum and interest in the develop-                 include such measures as health plan              Start with Macro-Level Indicators.
ment of effective tools to measure quali-             cost, utilization, source of revenues, and    A national private sector quality moni-
ty through a public-private collaborative             trends in health expenditures. Some           toring system should focus on major dis-
approach. Such a system can be viewed                 examples of performance information           ease categories and start with a broader
as beneficial for the public good, as well            include the effects of capitation and pay-    (macro-level) set of data and informa-
as a means for improving the quality of               ment approaches on quality indicators;        tion. The system should focus on those
care delivered through private healthcare             comparison of quality measures by geo-        health conditions that represent the
systems. The following recommendations                graphic area, diagnosis, or other subpop-     largest disease burden, thereby enabling
address the strategic next steps required             ulation of patients or health plans; the      efficient, targeted data collection and
to move this collaboration forward and                impact of health plan organization on         monitoring. While it will be impossible
to assure success.                                    specific quality performance measures;        to obtain the universe of data on all
   Establish Clear Concise Goals.                     and quality differences between type of       conditions, the intent should be to iden-
Many quality initiatives are under way                health plan structure and for-profit and      tify a midpoint between having no sys-
across the country, so it is important that           not-for-profit.                               tem and a perfect system and work
any new initiative clearly articulate its                Develop System that Can Address            from there.
goals and objectives, as well as build                Relevant Health Policy Questions.                 Build the Cost of Data Collection
upon the existing research base.                      Too often, legislative and policy initia-     into the System. If costs are to be
Additionally, while a private initiative              tives are driven by anecdotes, instead of     borne by private sector health plans and
can make a unique contribution, a clear               careful consideration of available data. A    providers, then the cost estimates for the
sense of that unique contribution must                national quality monitoring health data       system should include the cost of data
be articulated from the outset. Lack of               warehouse would facilitate analysis in a      collection. Electronic data interchange
clear goals may weaken an initiative’s                timely and efficient manner, thereby          (EDI) in the health arena is already
focus and contribute to the decline of                enabling analysts to inform the policy        being developed in the private sector.
the system’s sustainability over time.                debate by answering pertinent health          As systems are built, the data and infor-
Experience has shown that it is difficult             policy questions in real time. Such a sys-    mation necessary for quality monitoring
to justify a system’s values and costs if             tem would require ongoing input from          should be assessed, and a fee for access
the initiative has promised more than it              the policy arena to identify: (1) key poli-   to and use of the system could be
can deliver.                                          cy questions, (2) local and national          imposed. Additionally, a health plan
   Link Patient and Plan Data at the                  trends in the health policy debate, and       may choose to contribute to the cost of
Outset. The delivery system continues to              (3) data and information that could be        a system if the data and reports generat-
evolve in the forms of new payment                    used to address emerging health policy        ed are found to be of value in terms of
schemes, clinical management systems,                 issues. One possible mechanism identi-        specific quality improvements or other
vertical and horizontal integration, and              fied by conference participants would be      business applications.

56    Journal of Healthcare Information Management — Vol. 18, No. 1
                                                   Original Contributions

    Involve Data Collection Subjects          the model presented here. Such a proto-           data be analyzed and released as quickly
Early in the System Design Process.           type should be designed from a clinical           as possible. If the data suppliers recog-
Having buy-in at the local level will         and social perspective to demonstrate             nize its value and use it from the begin-
ensure that a private sector quality moni-    the value of a quality monitoring system.         ning, they will be more likely to contin-
toring system can be implemented and          An important part of this process                 ue to submit data to the warehouse. In
will be used. Buy-in requires consensus       involves establishing benchmarks to               addition, the release of summary data
building, information exchange, and edu-      measure differences in the data, identify         should be obligatory, regardless of
cation. It is partly a marketing function,    gaps, and develop a plan for moving               whether it is favorable to the industry,
but it is also a mechanism to obtain          beyond limited health plan participation          providers, or the system as a whole. As
community input toward building a sys-        toward broader representation.                    mentioned earlier, the data products
tem that will meet both public and pri-          Do Not “Re-invent the Wheel.” This             would include chart books, comparison
vate needs for quality monitoring.            private sector quality monitoring system          tables, and Web-based information.
    Build in Opportunities for                should be developed in the context of the
Linkages to Other Data Sources at             many ongoing quality initiatives men-             Conclusion
the Outset. Although it is likely that any    tioned earlier in this report. Because there         This article provides an operational
quality monitoring system will begin          are many overlapping interests between            outline for a national health data ware-
with administrative data, it is important     the public and private sectors, we are            house designed to detail specifications
to think about linkages to other data         hopeful that this initiative would inform         that, if met, would generate a resource
sources and surveys. Recently, promising      the debate and make a unique contribu-            of genuine value. While the challenges
strides have been made in the develop-        tion to development of an effective pri-          to build such a database are certain,
ment of automated medical records sys-        vate sector quality monitoring system.            they are not insurmountable. These
tems, physician practice management              Take Advantage of “Quick-Hit.” An              specifications assume the political and
systems, and linkages with population-        early demonstration of the value of               technical challenges to gaining access to
based surveys and data repositories. The      these data will help build credibility            private insurance data can be overcome.
union of detailed cost and utilization        with providers and consumers. In addi-            With this assumption, a practicality-
data, with patient- and member-reported       tion, communication efforts can set the           minded, limited, but focused scope of
perceptions, represents a powerful com-       stage for future advancements. The                work has been outlined to demonstrate
bination for analysis and research. In        value of the health data warehouse can            what could be achieved and how it
addition, there may be future opportuni-      be communicated via the dissemination             might be completed.
ties for follow-back surveys. Where con-      of short summary reports, chart books of
tents of the database repository are          data, quality measures reported by geo-           About the Authors
insufficient to answer the questions iden-    graphic area, etc. Reporting mechanisms              Lynn A. Blewett, PhD, is an assistant
tified in the research requirements, addi-    must be timely and relevant, and the              professor in the Division of Health
tional data would be collected based on       data included in these reports must be            Services Research and Policy of the
unit samples from the existing repository.    made available in an understandable               School of Public Health at the University
    Build in as Much Transactional            and accessible format.                            of Minnesota in Minneapolis.
Data as Possible. An ideal system                Establish Linkages Early with                     Stephen T. Parente, PhD, is an assis-
would be built upon detailed patient-         Other Groups. To enhance the viability            tant professor of healthcare management
level data at the level of patient-provider   of the proposed national private sector           at the Carlson School of Management in
transaction. This may not be possible at      quality monitoring system, we must                the University of Minnesota.
present, but, in the future, models and       endeavor to move quickly through the                 Michael D. Finch, PhD, is a senior
data systems may allow this type of           prototype phase, and through the initial          researcher at the Center for Health Care
information to be utilized. In the mean-      start-up activities. One goal would be to         Policy and Evaluation at UnitedHealth
time, the system should take advantage        get the community of health plans to              Group in Minnetonka, Minn.
of technological advances to build a pro-     break through organizational barriers in             Eileen Peterson, RN, MPH, is a vice
totype based the finest level of transac-     an effort to organize around quality.             president at the Center for Health Care
tional data currently available. To effect    Another opportunity involves linking to           Policy and Evaluation at UnitedHealth
real quality improvement, data systems        emerging private sector networks or to            Group in Minnetonka, Minn.
must both collect information at the          existing health plans that cover signifi-
patient-provider level and report infor-      cant numbers of enrollees. These link-            Note: This research was funded by a
mation at a “rolled-up” level for ongoing     ages are essential for broader applica-           conference grant from The Agency for
monitoring purposes.                          tions and will require considerable               Healthcare Research and Quality (AHRQ
    Develop and Test Production               investments of time and communication.            R13 HS10091-01). The views expressed
Prototype. A prototype database should           Release Data in a Routine and                  are those of the authors and do not nec-
be developed to test the applications of      Timely Fashion. It is important that              essarily reflect the views of AHRQ.

                                                                               Journal of Healthcare Information Management — Vol. 18, No. 1   57
                                                              Original Contributions

1. The Challenge and Potential for Assuring Quality Health Care for the 21st     4. Kohn, L. T., Corrigan, J. M., and Donaldson, M. S., Eds. To Err Is Human:
      Century. Washington, D.C.: U.S. Department of Health and Human                   Building a Safer Health System. Washington, D.C.: Institute Of Medicine,
      Services for the Domestic Policy Council, 1998.                                  2000.
2. Starr, P. “Smart Technology, Stunted Policy: Developing Health Information    5. Crossing the Quality Chasm: A New Health System for the 21st Century.
      Networks.” Health Affairs, 1997, 16: 91-105.                                     Washington, D.C.: Institute of Medicine, 2001.
3. Blewett, L., Finch, M., and Peterson, E. Private Sector Quality Monitoring,   6. See reference 3.
      Final May 2001 Report. Minneapolis: Submitted to the Agency for
      Healthcare Research and Quality, 2001.

58     Journal of Healthcare Information Management — Vol. 18, No. 1

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