Intraperitoneal Instillation of Bupivacaine and Ropivacaine for Postoperative Analgesia in Laparoscopic Cholecystectomy.

Background: Intraperitoneal instillation of local anesthetics in laparoscopic cholecystectomy (LC) has been used to reduce postoperative pain and to decrease the need for postoperative analgesics.

Aims: This study aimed to compare intraperitoneal instillation of bupivacaine and ropivacaine for postoperative analgesia in patients undergoing LC.

Settings And Design: This was a prospective, randomized, double-blind study.

Application of Discharge Criteria for Home Readiness Using Bispectral and Supraglottic Airway Devices in Day-care Surgery without Using Muscle Relaxants.

Introduction: The availability of rapid and short-acting intravenous and volatile anesthetics has facilitated early recovery that is why nowadays ambulatory surgery is becoming more common. If the criteria used to discharge patients from the Postanesthesia Care Unit (PACU) are met in the operating room (OR), it would be appropriate to consider bypassing the PACU and transferring the patient directly to the step-down unit. This process is known as "fast-tracking" after ambulatory surgery.

Information warehouse - a comprehensive informatics platform for business, clinical, and research applications.

Since its inception in 1997, the IW (Information Warehouse) at the Ohio State University Medical Center (OSUMC) has gradually transformed itself from a single purpose business decision support system to a comprehensive informatics platform supporting basic, clinical, and translational research. The IW today is the combination of four integrated components: a clinical data repository containing over a million patients; a research data repository housing various research specific data; an application development platform for building business and research enabling applications; a business intelligence environment assisting in reporting in all function areas. The IW is structured and encoded using standard terminologies such as SNOMED-CT, ICD, and CPT.

Aberrant expression of DNA damage response proteins is associated with breast cancer subtype and clinical features.

Landmark studies of the status of DNA damage checkpoints and associated repair functions in preneoplastic and neoplastic cells has focused attention on importance of these pathways in cancer development, and inhibitors of repair pathways are in clinical trials for treatment of triple negative breast cancer. Cancer heterogeneity suggests that specific cancer subtypes will have distinct mechanisms of DNA damage survival, dependent on biological context. In this study, status of DNA damage response (DDR)-associated proteins was examined in breast cancer subtypes in association with clinical features; 479 breast cancers were examined for expression of DDR proteins γH2AX, BRCA1, pChk2, and p53, DNA damage-sensitive tumor suppressors Fhit and Wwox, and Wwox-interacting proteins Ap2α, Ap2γ, ErbB4, and correlations among proteins, tumor subtypes, and clinical features were assessed.

Toward a fully de-identified biomedical information warehouse.

The Information Warehouse at the Ohio State University Medical Center is a comprehensive repository of business, clinical, and research data from various source systems. Data collected here is a valuable resource that facilitates both translational research and personalized healthcare. The use of such data in research is governed by federal privacy regulations with oversight by the Institutional Review Board.

Innovative applications of an enterprise-wide information warehouse.

The Information Warehouse at The Ohio State University Medical Center is a comprehensive effort integrating data from over 70 sources throughout the enterprise. The IW serves a broad diversity of customers in all mission areas of the medical center, from clinical operations and administration to education, to research. This comprehensiveness has facilitated an innovative application of cross-disciplinary technologies and methodologies to problem domains beyond the roles traditionally envisioned for data warehousing.

Data delivery workflow in an academic information warehouse.

The Ohio State University Medical Center (OSUMC) Information Warehouse (IW) collects data from many systems throughout the OSUMC on load cycles ranging from real-time to on-demand. The data then is prepared for delivery to diversity of customers across the clinical, education, and research sectors of the OSUMC. Some of the data collected at the IW include patient management, billing and finance, procedures, medications, lab results, clinical reports, physician order entry, outcomes, demographics, and so on.

Honest broker protocol streamlines research access to data while safeguarding patient privacy.

At Ohio State University Medical Center, The Honest Broker Protocol provides a streamlined mechanism whereby investigators can obtain de-identified clinical data for non-FDA research without having to invest the significant time and effort necessary to craft a formalized protocol for IRB approval.

Implementation of a metadata architecture and knowledge collection to support semantic interoperability in an enterprise data warehouse.

In order to enhance interoperability between enterprise systems, and improve data validity and reliability throughout The Ohio State University Medical Center (OSUMC), we have initiated the development of an ontology-anchored metadata architecture and knowledge collection for our enterprise data warehouse. The metadata and corresponding semantic relationships stored in the OSUMC knowledge collection are intended to promote consistency and interoperability across the heterogeneous clinical, research, business and education information managed within the data warehouse.

A comparative analysis of the dissemination of best practice measures for key populations.

In collaboration with the department of Quality and Operations Improvement, Clinical Applications and the Information Warehouse, we have leveraged available Information Warehouse data to build a Best Practice Compliance Measurement Dashboard. This tool combines information from our operating room charting system, our order entry system and coding information from the patient billing and management system to provide 'previous day', data on a patients current course of treatment.

Identification of potential surgical site infections leveraging an enterprise clinical information warehouse.

At The Ohio State University Medical Center (OSUMC), infection control practitioners (ICPs) need an accurate list of patients undergoing defined operative procedures to track surgical site infections. Using data from the OSUMC Information Warehouse (IW), we have created an automated report detailing required data. This report also displays associated surgical and pathology text or dictated reports providing additional information to the ICPs.

Use of synthesized data to support complex ad-hoc queries in an enterprise information warehouse: a diabetes use case.

The Ohio State University Medical Center (OSUMC) Information Warehouse (IW) is a comprehensive data warehousing facility incorporating operational, clinical, and biological data sets from multiple enterprise system. It is common for users of the IW to request complex ad-hoc queries that often require significant intervention by data analyst. In response to this challenge, we have designed a workflow that leverages synthesized data elements to support such queries in an more timely, efficient manner.

Managing data quality in an existing medical data warehouse using business intelligence technologies.

The Ohio State University Medical Center (OSUMC) Information Warehouse (IW) is a comprehensive data warehousing facility that provides providing data integration, management, mining, training, and development services to a diversity of customers across the clinical, education, and research sectors of the OSUMC. Providing accurate and complete data is a must for these purposes. In order to monitor the data quality of targeted data sets, an online scorecard has been developed to allow visualization of the critical measures of data quality in the Information Warehouse.

Predicting patient volume in cardiac catheterization laboratory to improve resource management.

Using historical data within the Information Warehouse of the Ohio State University Medical Center, prediction on daily patient volume to catheterization laboratory was attempted to facilitate resource management and planning.

The design of a pre-encounter clinical trial screening tool: ASAP.

Manually screening patients for clinical trials eligibility prior to their clinical encounters is labor-intensive and time-consuming. In order to increase the efficiency of such processes, we have developed a web-based system, called Advanced Screening for Active Protocols (ASAP).

Using data mining tools to discover novel clinical laboratory test batteries.

Using statistical analysis and data mining tools, we examined possible associations among clinical laboratory orders placed at the Ohio State University Medical Center between January and October of 2006. Upon applying the Frequent Itemset data mining technique to this data set, the results indicated that, while the most frequently ordered battery of tests was not associated with others, some highly associated orders may be good candidates to comprise new test batteries.

A framework for workflow-based clinical research billing disambiguation.

Medicare received authorization in 2000 to reimburse for routine costs incurred in association with patients participating in clinical research. However, we hypothesize that the inability to accurately differentiate standard from investigational care has resulted in under-coding of potentially reimbursable clinical events. To address this problem, we have initiated the development of a methodology for constructing computational clinical workflow models that can be employed to aid in the disambiguation of routine versus research costs.

Data mining tools for genotype-phenotype correlation.

Single Nucleotide Polymorphisms (SNPs) may be the key to diagnosing and treating certain diseases. A preliminary study was conducted at The Ohio State University Medical Center Information Warehouse to correlate such SNPs with a selected group of lab values for cardiology patients. Early results show that data mining tools can be valuable for understanding such correlations, but further refinement of the methodology and data preparation is needed to fully realize such value.

Development of an ontology-anchored data warehouse meta-model.

Data warehouses must provide a flexible data model that is integrated with knowledge and metadata describing their components and contents. To provide for advanced query functionality at The Ohio State University Medical Center (OSUMC), we have developed an abstraction layer, or meta-model for our existing Information Warehouse (IW) in order to conceptually and semantically describe and classify its structure and contents using the UMLS.

ICD9 Code Assistant: A prototype.

At The Ohio State University Medical Center (OSUMC) patient reports are available in real time along with other clinical and financial data in the OSUMC Information Warehouse (IW). Using the UMLS Meta Thesaurus we have leveraged the IW to develop a tool that can assist the medical record coders as well as administrators, physicians and researchers to quickly identify clinical concepts and their associated ICD-9 codes.

Augmenting Oracle Text with the UMLS for enhanced searching of free-text medical reports.

The intrinsic complexity of free-text medical reports imposes great challenges for information retrieval systems. We have developed a prototype search engine for retrieving clinical reports that leverages the powerful indexing and querying capabilities of Oracle Text, and the rich biomedical domain knowledge and semantic structures that are captured in the UMLS Metathesaurus.

Leveraging an information warehouse to create translational research environment for wound care center.

In order to discover new biomarkers and therapeutic agents for personalized wound care, a vast amount of clinical information is collected and stored at The Ohio State University Medical Center (OSUMC) Comprehensive Wound Center (CWC). The Information Warehouse (IW) group at OSUMC has developed and implemented a comprehensive data collection network and analysis pipeline to support clinical, translational and outcomes research, and cost analyses that can be converted into clinical best practices for wound care.

A knowledge-anchored integrative image search and retrieval system.

Clinical data that may be used in a secondary capacity to support research activities are regularly stored in three significantly different formats: (1) structured, codified data elements; (2) semi-structured or unstructured narrative text; and (3) multi-modal images. In this manuscript, we will describe the design of a computational system that is intended to support the ontology-anchored query and integration of such data types from multiple source systems. Additional features of the described system include (1) the use of Grid services-based electronic data interchange models to enable the use of our system in multi-site settings and (2) the use of a software framework intended to address both potential security and patient confidentiality concerns that arise when transmitting or otherwise manipulating potentially privileged personal health information.

Prototype integration of protein electrophoresis laboratory results in an information warehouse to improve workflow and data analysis.

This poster demonstrates our efforts to enhance workflow and clinical analysis of protein electrophoresis (PEP) data through integration with the Information Warehouse (IW) at The Ohio State University Medical Center (OSUMC). A new desktop application has been developed with the aim of enabling more efficient and accurate gel analysis by clinical pathologists. This tool gives the pathologists the ability to perform their analysis conveniently from anywhere on the OSUMC network along with the aid of numerical analysis algorithms, image enhancement techniques, and access to historical PEP results for the given patient.

An indexing scheme for medical free text searches: a prototype.

At the Ohio State University Medical Center, a significant amount of valuable data pertaining to a patient's visit is stored in the form of dictated reports such as discharge summaries, cardiology reports, and radiology reports. We have implemented conceptual search capability to facilitate more comprehensive content mining from clinical free text.