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Biomedical subjects

M G Kahn

Publications and source records attributed to M G Kahn.

At least 19 recordsLinked to original sources
PubMed1999

Clinical research databases and clinical decision making in chronic diseases.

Chronic diseases are the major source of morbidity, mortality, and resource utilization. Large-scale longitudinal databases are rapidly proliferating in both single- and multi-institutional settings, providing clinical data on a broad range of patients who receive 'real world' management. Although bias and changing medical management may limit the types of questions that can be addressed using the data contained in longitudinal clinical databases, many initial hypotheses can be generated from the data. Because chronic diseases persist over long periods of time, understanding the impact of temporal relationships, and of concurrent clinical events and contexts is critical to meaningful interpretation of clinical data. Adapting techniques initially developed for the physical sciences and for statistical process control can produce visual displays of clinical data that capture complex temporal and contextual information. With these tools, investigators can quickly explore vast quantities of clinical data, and discover new temporal relationships and emerging trends.

Case-Control Studies↗
PubMed1998

Combining laboratory data sets from multiple institutions using the logical observation identifier names and codes (LOINC).

A standard set of names and codes for laboratory test results is critical for any endeavor requiring automated data pooling, including multi-institutional research and cross-facility patient care. This need has led to the development of the logical observation identifier names and codes (LOINC) database and its test-naming convention. This study is an expansion of a pilot study using LOINC to exchange laboratory data between Columbia University Medical Center in New York and Barnes Hospital at Washington University in St. Louis, where we described complexities and ambiguities that arose in the LOINC coding process (D.M. Baorto, J.J. Cimino, C.A. Parvin, M.G. Kahn, Proc. Am. Med. Inf. Assoc. 1997). For the present study, we required the same two medical centers to again extract raw laboratory data from their local information system for a defined patient population, translate tests into LOINC and provide aggregate data which could then be used to compare laboratory utilization. Here we examine a larger number of tests from each site which have been recoded using an updated version of the LOINC database. We conclude that the coding of local tests into LOINC can often be complex, especially the 'Kind of Property' field and apparently trivial differences in choices made by individual institutions can result in nonmatches in electronically pooled data. In the present study, 75% of failures to match the same tests between different institutions using LOINC codes were due to differences in local coding choices. LOINC has the potential to eliminate the need for detailed human inspection during the pooling of laboratory data from diverse sites and perhaps even a built-in capability to adjust matching stringency by selecting subsets of LOINC fields required to match. However, a quality standard coding procedure is required and examples highlighted in this paper may require special attention while mapping to LOINC.

Clinical Laboratory Techniques↗
PubMed1998

Nosocomial penicillin-resistant pneumococcal infections at a Midwestern university hospital.

We analyzed 333 isolates of Streptococcus pneumoniae from adult inpatients over a continuous 30-month period. Twenty-five percent of isolates were resistant to penicillin, and 18% of tested strains were not susceptible to ceftriaxone. For 29 (15%) of 199 evaluable patients, S pneumoniae was isolated from a culture first obtained >48 hours after admission, and chart review satisfied our case definition for nosocomial infection. S pneumoniae isolates were penicillin-resistant in 14 of 29 nosocomial and 34 of 170 community-acquired cases (odds ratio, 3.73; 95% confidence interval, 1.53-9.15; P=.01).

Community-Acquired Infections↗
PubMed1997

Automated system for identifying potential dosage problems at a large university hospital.

A hospital's experience with an automated system for screening drug orders for potential dosage problems is described. DoseChecker was developed by the hospital pharmacy department in collaboration with a local university. Pharmacy, laboratory, and patient demographic data are transferred nightly from the hospital's mainframe system to a database server; DoseChecker uses these data and user-defined rules to (1) identify patients receiving any of 35 targeted medications, (2) evaluate the appropriateness of current dosages, and (3) generate alerts for patients potentially needing dosage adjustments. The alert reports are distributed to satellite pharmacists, who evaluate each patient's condition and make recommendations to physicians as needed. One of the system's primary purposes is to calculate creatinine clearance and verify that dosages are properly adjusted for renal function. Between May and October 1995, the system electronically screened 28,528 drug orders and detected potential dosage problems in 2859 (10%). The system recommended a lower daily dose in 1992 cases (70%) and a higher daily dose in 867 (30%). Pharmacists contacted physicians concerning 1163 (41%) of the 2859 alerts; in 868 cases (75%), the physicians agreed to adjust the dosage. The most common dosage problem identified was failure to adjust dosages on the basis of declining renal function. An automated system provided an efficient method of identifying inappropriate dosages at a large university hospital.

Adolescent↗
PubMed1997

Three perspectives on integrated clinical databases.

The dramatic transformation of health care organizations from independent local entities into regional and national integrated health care delivery enterprises has forced a reevaluation of the role of information systems. Until recently, nearly all clinical information systems were acquired to support financial and administrative services within single facilities. When independent facilities merge to form an integrated health system (IHS), they find that their unique computer systems do not allow for the sharing or combining of clinical data. However, new technologies are beginning to enable patient-specific data scattered among many information systems in many different hospitals and ambulatory care settings to be unified into a single database called a clinical data repository. The hope is that comprehensive electronic clinical records can enable IHSs to meet their goals of improving the quality and reducing the cost of health care. As the number of technological impediments to forming integrated clinical information systems rapidly decreases, nontechnologic issues surrounding the sharing of patient information become more prominent. The author focuses on the clinician's, the administrator's, and the patient's unique perspectives on the benefits and possible problems associated with clinical data repositories. He then describes how one IHS, together with an academic medical institution, has begun to grapple with many of these concerns through an effort called Project Spectrum. The goal of the project is the successful implementation of a comprehensive clinical data repository.

Clinical Medicine↗
PubMed1997

Using Logical Observation Identifier Names and Codes (LOINC) to exchange laboratory data among three academic hospitals.

Using a standard set of names and codes to exchange electronic laboratory data would facilitate multiinstitutional research and data pooling. This need has led to the development of the Logical Observation Identifier Names and Codes (LOINC) database and its test naming convention. We conducted a study which required 3 academic hospitals (in 2 separate medical centers) to extract raw laboratory data from their local information system for a defined patient population, translate tests into LOINC, and provide aggregate data which could then be used to compare laboratory utilization. We found that the coding of local tests into LOINC can often be complex, especially the "Kind of Property" field, and apparently trivial differences in choices made by individual institutions can result in nonmatches in electronically pooled data. In our study, 72-86% of the failures of LOINC to match the same tests between different institutions were due to differences in local coding choices. LOINC has tremendous potential to eliminate the needing for detailed human inspection during the pooling of laboratory data from diverse sites, and perhaps even a built-in capability to adjust matching stringency by selecting subsets of LOINC fields required to match. However, a quality, standard coding procedure at all sites is critical.

Academic Medical Centers↗
PubMed1997

Iterative usability testing: ensuring a usable clinical workstation.

Once the users' needs are determined, how does one ensure that the resulting software meets the users' needs? This paper describes our application of a process, usability testing, that is used to measure the usability of systems as well as guide modifications to address usability problems. Usability testing is not a method to elicit opinions about software, but rather a method to determine scientifically a product's level of usability. Our application of usability testing is designed to determine the current usability level of a workstation designed for the clinician's use, determine specific problems with the Clinical Workstation's usability, and then evaluate the effectiveness of changes that address those problems.

Evaluation Studies as Topic↗
PubMed1996

Evaluation of an objective plan-evaluation model in the three dimensional treatment of nonsmall cell lung cancer.

PURPOSE: Evaluation of three dimensional (3D) radiotherapy plans is difficult because it requires the review of vast amounts of data. Selecting the optimal plan from a set of competing plans involves making trade-offs among the doses delivered to the target volumes and normal tissues. The purpose of this study was to test an objective plan-evaluation model and evaluate its clinical usefulness in 3D treatment planning for nonsmall cell lung cancer. METHODS AND MATERIALS: Twenty patients with inoperable nonsmall cell lung cancer treated with definitive radiotherapy were studied using full 3D techniques for treatment design and implementation. For each patient, the evaluator (the treating radiation oncologist) initially ranked three plans using room-view dose-surface displays and dose-volume histograms, and identified the issues that needed to be improved. The three plans were then ranked by the objective plan-evaluation model. A figure of merit (FOM) was computed for each plan by combining the numerical score (utility in decision-theoretic terms) for each clinical issue. The utility was computed from a probability of occurrence of the issue and a physician-specific weight indicating its clinical relevance. The FOM was used to rank the competing plans for a patient, and the utility was used to identify issues that needed to be improved. These were compared with the initial evaluations of the physician and discrepancies were analyzed. The issues identified in the best treatment plan were then used to attempt further manual optimization of this plan. RESULTS: For the 20 patients (60 plans) in the study, the final plan ranking produced by the plan-evaluation model had an initial 73% agreement with the ranking provided by the evaluator. After discrepant cases were reviewed by the physician, the model was usually judged more objective or "correct." In most cases the model was also able to correctly identify the issues that needed improvement in each plan. Subsequent replanning confirmed that further manual plan optimization could be achieved in 17 patients. CONCLUSION: The objective plan-evaluation model was able to rank lung cancer radiotherapy plans from best to worst. It was useful in improving plans and may be useful to physicians in defining goals for patients based on the ability to effectively and safely treat their tumors.

Carcinoma, Non-Small-Cell Lung↗
PubMed1995

Using knowledge maintenance for preference assessment.

Most real-life decisions require the decision maker to make trade-offs in order to fulfill multiple conflicting objectives. This is especially true in medical decision making while selecting the optimal therapy plan from among competing therapy plans for a patient. Multi-attribute utility theory provides a framework to specify these trade-offs for optimal decision making based on the preferences of the decision maker. However traditional preference-assessment techniques are difficult to implement and rarely elicit the true preferences of the decision maker. We describe a new preference-assessment method based on the concept of knowledge maintenance where the preference model is changed each time it makes an incorrect recommendation. The method is implemented in a decision-theoretic system to evaluate competing three-dimensional radiation treatment plans. The preference-assessment method leads to preference models which perform better than preference models elicited using traditional assessment techniques.

Abdominal Neoplasms↗
PubMed1995

Extending a clinical repository to include multiple sites.

With the consolidation of health care organizations and services, a clinical repository comprising data from a single site is no longer sufficient. Individual patient data are now spread across multiple sites comprising a single enterprise. Users require an integrated view, or at least a common view, of these clinical data across multiple sites. Many issues arise when one tries to merge data from multiple, distinct organizations into an existing schema. We have addressed these issues while extending our clinical repository for Barnes Hospital with data from Jewish Hospital, both of which are members of the recently formed BJC Health System. We describe the architecture of our existing repository, approaches and issues in extending this repository to include multiple sites, and the specific issues we addressed in our system.

Computer Communication Networks↗
PubMed1995

Creating temporal abstractions in three clinical information systems.

Modern clinical information system developers recognize the need to associate temporal information with clinical data. However, specific clinical systems capture different temporal features using a variety of data modeling techniques. Two commonly used methods to represent temporal information are point-based events and interval-based durations. We recently implemented a rule-based expert system for drug dose monitoring on three clinical information systems. The expert system requires both static drug dosing information (drug name, amount, route, frequency) and temporal dosing information (duration of therapy, renewals, restarts). Our design goal was to use the same expert system code on all three information systems by defining a common database schema to hide differences in the original systems' data models. Although we have been successful in mapping clinical data from these three source systems into a unified temporal data representation, we describe how differences in handling time within the three clinical systems made this goal difficult to achieve.

Clinical Pharmacy Information Systems↗
PubMed1995

Contextual inquiry: discovering physicians' true needs.

Gathering user requirements that represent the true needs of the users is a challenge. There are many elicitation methods in use today, but they generally are not successful in identifying a comprehensive set of requirements that reflect the users' true needs. This paper describes the requirements gathering method, Contextual Inquiry, that we used to generate physician requirements for a comprehensive Clinical Information System. We feel that this method has advantages over traditional techniques such as surveys, questionnaires, traditional interviews, and focus groups, in obtaining a more comprehensive analysis of the true needs of the users.

Attitude to Computers↗
PubMed1995

Supporting ad-hoc queries in an integrated clinical database.

Whether caring for patients or conducting research, medical decision-makers need access to clinical data. To fulfill that need, commercial software developers have produced a wide range of database query tools that differ greatly in functionality and cost. Generally, tools that have a greater ability to conceal database complexity from the user also require more effort for administrative setup. We describe a cost-effective, commercially-available query tool that requires no special setup to perform most simple queries, yet can be customized to satisfy users' more complex querying requirements.

Clinical Pharmacy Information Systems↗
PubMed1995

A probability database for decision-analytic models of coronary revascularization procedures.

The time required to extract probabilities from medical literature is a primary reason decision analysis is not used more frequently for individual patient management decisions. Objective clinical trial information from the medical literature for one management decision was placed in a database which provided probabilities when queried. The database was tested with decision-analytic models of specific patient cases from the medical literature. Performance was assessed in terms of the ability to select trials which resembled the patients' individual characteristics, the number of trials providing probabilities for a given outcome, and the number of follow-up points available for that outcome. The timely assistance the database provides in expediting literature review and synthesis could enable the more common use of decision analysis in management decisions for individual patients.

Adult↗
PubMed1995

Improvement in user performance following development and routine use of an expert system.

Hospital-acquired (nosocomial) infections represent a significant cause of prolonged inpatient days and additional hospital charges. In many hospitals, infection control nurses manually review positive microbiology culture results to monitor the incidence and prevalence of potential nosocomial infections. We have developed an expert system called GermWatcherTM, which uses the United States Centers for Disease Control and Prevention National Nosocomial Infection Surveillance criteria to classify microbiology results as potential nosocomial infections. In February 1993, we deployed GermWatcher at a large tertiary-care teaching hospital. In July 1993, we implemented a revised version of GermWatcher. With each version, we performed an evaluation of the program by comparing its electronic classification of positive culture results to the paper-based manual classification performed by three infection control nurses and one Infectious Disease specialist (gold standard). In the present study, we focus not on changes in the performance of the expert system, but on changes in performance among the infection control nurses. We found significant improvement in agreement and accuracy in the manual classification of cultures by the infection control nurses in the second evaluation compared to the first evaluation. We attribute this improved manual performance to the development of the expert system's rule base throughout the two evaluation phases and to the use of the expert system in the nurses' daily activities.

Cross Infection↗
PubMed1994

Integrated software tools for the evaluation of radiotherapy treatment plans.

PURPOSE: This article announces the availability of a convenient and useful software environment for the evaluation of three-dimensional (3D) radiotherapy treatment plans. MATERIALS AND METHODS: Using standards such as American National Standards for Information Systems C and the X Window System allowed us to bring the computation and display of dose-volume histograms, dose statistics, tumor control probabilities, normal tissue complication probabilities, and a figure of merit together under one user interface. These plan evaluation tools are not stand alone, but must interact with a 3D radiation therapy planning system to obtain the required dose matrices and patient anatomical contours. Installation of the software involves a programmer who writes a software bridge between the radiation therapy planning system and the tools, thereby providing access to local data files. This design strategy confines portability issues to one area of the software. RESULTS: Access to the other tools is through the Graphical Plan Evaluation Tool (GPET). GPET coordinates the use of each of the tools and provides graphical facilities for display of their results. Importantly, GPET assures that the displayed results of each tool have been computed with the same input specifications for all treatment plans being compared. For added convenience, the user can rearrange the resultant data to be reviewed in various ways on the video screen. The software design also allows incorporation of customized algorithms and input data for computing tumor control probability and normal tissue complication probabilities, since those currently available are controversial. CONCLUSION: The Graphical Plan Evaluation Tool unifies the simultaneous computation for several analytical tools and graphical display of their results. Within the constraints of the X Window System environment, this assemblage of software tools provides a portable, flexible, and convenient method for the quantitative evaluation of several radiotherapy treatment plans.

Dose-Response Relationship, Radiation↗