Harmonization of detailed clinical models with clinical study data standards.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". BACKGROUND: Data sharing and integration between the clinical research data management system and the electronic health record system remains a challenging issue. To approach the issue, there is emerging interest in utilizing the Detailed Clinical Model (DCM) approach across a variety of contexts. The Intermountain Healthcare Clinical Element Models (CEMs) have been adopted by the Office of the National Coordinator awarded Strategic Health IT Advanced Research Projects for normalization (SHARPn) project for normalizing patient data from the electronic health records (EHR). OBJECTIVE: The objective of the present study is to describe our preliminary efforts toward harmonization of the SHARPn CEMs with CDISC (Clinical Data Interchange Standards Consortium) clinical study data standards. METHODS: We were focused on three generic domains: demographics, lab tests, and medications. We performed a panel review on each data element extracted from the CDISC templates and SHARPn CEMs. RESULTS: We have identified a set of data elements that are common to the context of both clinical study and broad secondary use of EHR data and discussed outstanding harmonization issues. CONCLUSIONS: We consider that the outcomes would be useful for defining new requirements for the DCM modeling community and ultimately facilitating the semantic interoperability between systems for both clinical study and broad secondary use domains.

Results of a collaborative quality improvement program on outcomes and costs in a tertiary critical care unit.

OBJECTIVE: To demonstrate that by using the knowledge and skills of the primary care provider and by applying statistical and scientific principles of quality improvement, outcomes can be improved and costs significantly reduced. DESIGN: A before and after quasi-experimentally designed trial using historical controls plus an analysis of costs in areas not influenced by intensive care unit (ICU) practice to control for possible secular changes. SETTING: A tertiary ICU. PATIENTS: All patients admitted to the above-mentioned ICU from January 1, 1991, through December 31, 1995. INTERVENTIONS: a) A focused program that applied statistical and scientific quality improvement processes to the practice of intensive care. b) An organized effort to modify the culture, thinking, and behavior of the personnel who practice in the ICU. MEASUREMENTS: Severity of illness, ICU and hospital lengths of stay, ICU and hospital mortality rates, total hospital costs as analyzed by the cost center, and measures of improvement in specific areas of care. MAIN RESULTS: Significant improvement in glucose control, use of enteral feeding, antibiotic use, adult respiratory distress syndrome survival, laboratory use, blood gases use, radiograph use, and appropriate use of sedation. A severity adjusted total hospital cost reduction of $2,580,981 in 1991 dollars when comparing 1995 with the control year of 1991, with 87% of the reduction in those cost centers directly influenced by the intervention. CONCLUSIONS: A focused quality improvement program in the ICU can have a beneficial impact on care and simultaneously reduce costs.

Using statistical quality control techniques to monitor blood glucose levels.

Continuous Quality Improvement techniques developed in industry are increasingly being applied to the medical field. Statistical process control charts are a CQI technique aimed at monitoring a process and its variability. At our hospital, statistical quality control charts are being constructed from laboratory blood glucose measurements of patients receiving enteral or parenteral nutrition. The charts will be used to monitor glucose levels, reveal variations, and illustrate the effects of new protocols designed to manage glucose levels.

Representative charting of vital signs in an intensive care unit.

An automatic vital signs charting system had been operational in the intensive care units of our hospital for over 10 years, but the system was susceptible to non-representative transients in the data. A median selection rule was implemented to make the system less susceptible to transients. After implementation of the median rule, we examined (1) the agreement of the resulting medians and the values that would have been reported using the previous "real-time" system and (2) the frequency of occurrence of "out-of-range" values for each system. The median value system was found to improve the representativeness of the recorded data. Improved representativeness will enhance the usefulness of reports, but more importantly will enable us to use the resulting data as inputs to computerized practice protocols and other computerized decision support applications.

Computerized detection of arterial oxygen desaturations in an intensive care unit.

Automatic detection of arterial oxygen desaturations was investigated by collecting pulse oximeter saturation data through an MIB. Two algorithms, one based on a threshold principle and the other based on moving median calculations, performed the detection. The median algorithm detected fewer "unimportant" events than did the threshold algorithm, but also did not detect some "important" events that the threshold algorithm detected. Successful detection algorithms will likely need to incorporate into their decision-making other patient information in addition to saturation. A proposed recording algorithm is described.

Real time data acquisition: recommendations for the Medical Information Bus (MIB).

Care of the acutely ill patient requires rapid acquisition, recording and communications of data. In the modern hospital it is not unusual for a patient to be connected to several monitoring and recording devices simultaneously. Each of these devices is typically made by a different manufacturer who may specialize in one sort of measurement, for example, pulse oximetry. Most of the modern monitoring and recording devices are micro-processor based and have communication capabilities. Unfortunately, there is no operable standard communication technology available from all devices. In addition different clinical staff (physicians, nurses, or respiratory therapists) may be responsible for collecting data. As a result there is a need to develop methods, standards, and strategies for timely and automatic collection of data from these monitoring and recording devices. We report on more than 5 years of clinical experience of automated ICU data collection using a prototype of the Medical Information Bus (MIB).

Real time data acquisition: experience with the Medical Information Bus (MIB).

Care of the acutely ill patient requires rapid acquisition, recording and communications of data. In the modern hospital it is not unusual for a patient to be connected to several monitoring and recording devices simultaneously. Each of these devices is typically made by a different manufacturer who may specialize in one sort of measurement, for example, pulse oximetry. Most of the modern monitoring and recording devices are micro-processor based and have communications capabilities. Unfortunately, there is no operable standard communications technology available from all devices. In addition different clinical staff (physicians, nurses, or respiratory therapists) may be responsible for collecting data. As a result there is a need to develop methods, standards, and strategies for timely and automatic collection of data from these monitoring and recording devices. We report on more than 5 years of clinical experience of automated ICU data collection using a prototype of the Medical Information Bus (MIB).