James Studnicki

The Catch data warehouse: support for community health care decision-making

The measurement and assessment of health status in communities throughout the world is a massive information technology challenge. Comprehensive Assessment for Tracking Community Health (CATCH) provides systematic methods for community-level assessment that is invaluable for resource allocation and health care policy formulation. CATCH is based on health status indicators from multiple data sources, using an innovative comparative framework and weighted evaluation process to produce a rank-ordered list of critical community health care challenges. The community-level focus is intended to empower local decisionmakers by providing a clear methodology for organizing and interpreting relevant health care data. Extensive field experience with the CATCH methods, in combination with expertise in data warehousing technology, has led to an innovative application of information tehnology in the health care arena. The data warehouse allows a core set of reports to be produced at a reasonable cost for community use. In addition, online analytic processing (OLAP) functionality can be used to gain a deeper understanding of specific health care issues. The data warehouse in conjunction with Web-enabled dissemination methods allows the information to be presented in a variety of formats and to be distributed more widely in the decision-making community. In this paper, we focus on the technical challenges of designing and implementing an effective data warehouse for health care information. Illustrations of actual data designs and reporting formats from the CATCH data warehouse are used throughout the discussion. Ongoing research directions in health care data warehousing and community health care decision-making conclude the paper.

Response to the National Cancer Institute alert: The effect of practice guidelines on two hospitals in the same medical community

Background. Despite the recent increase in medical practice guideline development and dissemination, physician compliance with the guidelines has often been low. Previous research has suggested that physicians at hospitals with low volumes of cases and weakened financial status were more likely to omit indicated diagnostic testing or appropriate treatment. The authors sought to determine whether differences in compliance to a widely disseminated set of guidelines would exist even among the most dominant hospital providers within the same medical community.

Doing more with more information: Changing healthcare planning with OLAP tools

On-line analytical processing (OLAP) is an example of a new breed of tools for decision support that give decision makers the flexibility to customize the selection, aggregation, and presentation of data. To understand the impact of this type of tool, we study an implementation of an OLAP interface on the CATCH data warehouse used by knowledge workers at a regional health planning agency in the State of Florida. The results of a qualitative field study show that after the OLAP implementation, these workers made use of the additional capabilities of OLAP (e.g., aggregation levels and intuitive data manipulation), thereby leveraging their individual abilities to enhance and expand on the tasks they performed for their community. Consequently, they were able to perform in more of a consultative role to their clients, and improved their reputation in the community they serve. This research adds a new dimension to prior research in data warehousing by focusing on the decision support capabilities of OLAP.

The Impact of Legislatively Imposed Practice Guidelines on Cesarean Section Rates: The Florida Experience:

Florida legislation implemented in the fall of 1992, unique in the nation, mandated that practice guidelines regarding cesarean section deliveries be disseminated to obstetric physicians. The law also required that peer review boards at hospitals be established to review ce sarean deliveries and that the exact dates of implemen tation of the guidelines be reported to a state agency. To determine the impact of the legislation, we conducted a retrospective analysis of 366,246 total live births oc curring in Florida hospitals during 1992 and 1993, be fore and after formal hospital certification of the implementation of the guidelines. Changes in primary and repeat cesarean rates were analyzed for 108 inde pendent groups of births, controlling for the mothers age, race, payment source, and the timing of the imple mentation of the guidelines at hospitals. The guideline certification program did not accelerate the consistent but gradual downward trend in cesarean births which had already been evident in the three prior years. The data do suggest that the guideline program may have af fected repeat cesareans more than primary cesareans, especially in the first quarter of 1993, immediately after the hospital certification period. Reductions in repeat cesareans involved both Medicaid and commercially in sured births, whereas reductions in primary cesareans were found almost exclusively within commercially in sured mothers, where the existing rates are highest. Although births with a prior cesarean represent only 12.5% of all births, significant decreases in repeat ce sareans were found in groups representing 72.6% of this population. By comparison, significant decreases in pri mary cesareans were found in groups representing only 36.5% of the births without a prior cesarean. The date of guideline implementation reported by hospitals was not related to any systematic change in observed ce sarean section rates. We concluded that the mere dis semination of practice guidelines by a state agency may not achieve either the magnitude or the specificity of the results desired without an explicit and thorough guideline implementation program. Blunt legislative man dates may be ineffective when multiple initiatives are already achieving desired outcomes.

A national profile of the use of intensive care by medicare patients with cancer

Background. The broad picture of intensive care unit (ICU) outcomes and expenditures cannot be discerned from previous studies that were conducted at single hospitals and focused on narrow subsets of patients.

The role of data warehousing in bioterrorism surveillance

The development of an effective bioterrorism surveillance system requires effective solutions to several critical challenges. The system must support multidimensional historical data, provide real-time surveillance of sensor data, have the capability for pattern recognition to quickly identify abnormal situations, and provide an analytic environment that accelerates investigations by epidemiologists and other responders. The use of real-time or flash data warehousing provides the essential ability to compare unfolding health events with historical patterns of key surveillance indicators. To explore the role of data warehousing in surveillance systems, we study naturally occurring incidents, Florida wildfires from 1996 through 2001, as reasonable facsimiles of bioterrorism attacks. Hospital admissions data on respiratory illnesses during that period are analyzed to uncover patterns that might resemble an airborne biochemical attack. A principal contribution of this research is the adroit use of online analytic processing (OLAP) techniques, along with spatial and statistical analyses, to study the adverse effects of this natural phenomenon. These techniques will provide important capabilities for epidemiologist-in-the-loop surveillance systems, enabling the rapid exploration of unusual situations and guidance for follow-up investigations.

Bioterrorism surveillance with real-time data warehousing

This paper discusses several technical challenges in the developmentof an effective bioterrorism surveillance system. Three factors are critical:1. It must be multidimensional.2. It must accelerate the transmission of findings and data to most closely approximatereal time surveillance so as to provide sufficient warning.3. It must have the capability for pattern recognition that will quickly identifyan alarm or alert threshold value. We build on our on-going health care data warehousing research to provide solutionsto these challenges. The innovative use of flash data warehousing providesthe essential ability to compare real-time healthcare data with historicalpatterns of key surveillance indicators. A comprehensive architecture of a bioterrorismsurveillance system is presented. A demonstration project in Floridashowcases these ideas.

Strategic information systems planning with box structures

Strategic information systems planning (SISP) is the process of aligning an organizations business strategy with effective computer based information systems to achieve critical business objectives. SISP is a top concern of major executives and considerable resources (time and money) are spent in SISP activities. Many SISP initiatives are not successful due to the difficulty of implementing the recommendations. A significant problem is the specification gap between the description of the recommended systems and the detail needed for actual system implementation. Existing SISP methods do not provide sufficiently rigorous representations to specify detailed system recommendations. Box structures are proposed as a solution to this problem and a SISP process with embedded box structure methods is presented. We have used this innovative process in two SISP projects with large organizations. Partial results from one of the projects are presented as a case study to illustrate the use of box structures and their benefits.

Toward a population health delivery system: first steps in performance measurement.

In spite of the technological sophistication and clinical excellence of the U.S. health care industry and annual health expenditures in excess of a trillion dollars, the overall health status of the American population is comparatively poor. The BCHS in west central Florida sought to improve the health status of the communities that it serves. Known by the acronym CHAPIR, an information-driven health status decision support system was developed, pilot tested, and is now fully implemented throughout the BCHS. The methodological approach, quantitative indicators, report format components, and management implications of the system are described.

Measuring healthcare inequities using the Gini index

Questions of healthcare inequities have been of continuing concern to health researchers, planners, and policymakers. The answers to such questions can be difficult to interpret, but deeply affect policy formulation, resource allocation, and our perceptions of the fairness and compassion inherent in the institutions of government and society as a whole. This paper describes the data warehouse implementation of several measures of inequality drawn from the field of economics, including the Gini index. Past research has often focused on using these economic measures to characterize a small set of health status indicators, usually at fairly high levels of aggregation, with comparisons between states or nations. In this research, an ongoing healthcare data warehouse project under the auspices of the Center for Health Outcomes Research at the University of South Florida provides the infrastructure for exploring hundreds of health status indicators at the ZIP code level. The goal is to include information on healthcare inequities in the many reports generated for policymakers throughout Florida.