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Biomedical subjects

G J Kuperman

Publications and source records attributed to G J Kuperman.

At least 37 records · Page 2Linked to original sources
PubMed1998

Measuring and improving quality using information systems.

Information systems (IS) are increasingly important for measuring and improving quality. In this paper, we describe our integrated delivery system's plan for and experiences with measuring and improving quality using IS. Our approach is that for quality measurement to be practical, it must be integrated with the routine provision of care, and whenever possible should be done using IS. Thus, at one hospital, we now perform almost all quality measurement using IS. However, IS are not only useful for measuring care, but represent powerful tools for improving care using decision support. Specific areas in which IS has already been particularly effective include reducing the unnecessary use of laboratory testing, reporting important abnormalities to key providers rapidly, adverse drug event detection and prevention, initiatives to reduce the costs of drugs, and making critical pathways available to providers. The next wave of effort will be to promote widespread use of computerized guidelines, which is likely to prove more challenging. However, the advent of managed care in the U.S. has produced strong incentives to provide high quality care at low cost, and our perspective is that only with better IS than exist today will this be possible on a widespread basis. Such systems make feasible implementation of care improvement and cost reduction initiatives on a scale which could not previously be considered.

Decision Making, Computer-Assisted↗
PubMed1998

Components of the optimal ambulatory care computing environment.

We present here a framework of core components of an ambulatory care computing environment, based on clinical and functional needs and workflow scenarios. We have established this framework through the use of two study devices: a vision of the clinical office of the future, and a survey of possible computer applications, both designed to help clinicians and practice directors communicate their information needs to systems designers. Clinicians prioritize applications based on strategic and practice goals: support for clinical users' workflow, improved quality of care, reduced cost of care, and the ability to measure performance and status. By reorganizing the needed functionality from a clinical viewpoint into a technical viewpoint, we are able to identify core information components for systems design. Based on this analysis, information needs in the ambulatory environment can be divided into five primary functions: patient data retrieval, documentation, communication, knowledge resources, and aggregate reporting. Three other fundamental processes--knowledge-based interventions, information integration, and confidentiality--run through all of these front-line functions. Component applications and data structures built with this framework in mind will afford a maximum combination of functionality and flexibility to handle future changes in the clinical environment.

Ambulatory Care↗
PubMed1998

Extracting findings from narrative reports: software transferability and sources of physician disagreement.

While natural language processing systems are beginning to see clinical use, it remains unclear whether they can be disseminated effectively through the health care community. MedLEE, a general-purpose natural language processor developed for Columbia-Presbyterian Medical Center, was compared to physicians' ability to detect seven clinical conditions in 200 Brigham and Women's Hospital chest radiograph reports. Using the system on the new institution's reports resulted in a small but measurable drop in performance (it was distinguishable from physicians at p = 0.011). By making adjustments to the interpretation of the processor's coded output (without changing the processor itself), local behavior was better accommodated, and performance improved so that it was indistinguishable from the physicians. Pairs of physicians disagreed on at least one condition for 22% of reports; the source of disagreement appeared to be interpretation of findings, gauging likelihood and degree of disease, and coding errors.

Diagnosis, Computer-Assisted↗
PubMed1998

Towards improving the accuracy of the clinical database: allowing outpatients to review their computerized data.

We developed an application that allowed patients coming to the clinic to review on a paper form their computerized health maintenance, medication, and allergy data. The patient could edit the paper form and the physician then could enter the new data into the database. We implemented the system in 4 clinics (17 MDs) To evaluate the system, we reviewed 80 forms from one physician's patients to determine how often patients provided new data. We also sent questionnaires to the physicians asking for their estimates of how often there was new data and for their impression of the system. We interviewed secretaries in the clinics about logistical issues. Of the 80 forms, 29 (36%) had new data; 28% had new health maintenance data and 19% had new medication data. The 7 physicians who responded to the questionnaire estimated that new health maintenance data were present on 22% of the forms. The physicians who responded to the questionnaire felt the system was useful. The secretaries said that managing the paper flow in the clinic was often unwieldy and in some clinics, the system has been abandoned or is used intermittently. Having patients review their data is one avenue to improving the accuracy of computerized records.

Adult↗
PubMed1998

P-CAPE: a high-level tool for entering and processing clinical practice guidelines. Partners Computerized Algorithm and Editor.

The Partners Computerized Algorithm Processor and Editor (P-CAPE) is a high-level tool intended to remove the programming bottleneck for implementing practice guidelines in our computer-based record system, and to integrate guideline-based advice into the clinician's workflow. P-CAPE has three major components: 1) An Editor that allows an analyst to enter the parameters of a guideline in the form of an algorithm; 2) A Navigator that processes the steps of the guideline and logs all transactions in a patient-specific file; and 3) A clinician Notifier that sends messages to a patient's covering clinician, seeking data or presenting recommendations and order sets that can be processed by the system. P-CAPE's guideline object model was adapted from the InterMed Collaboratory GuideLine Interface Format (GLIF).

Algorithms↗
PubMed1998

A graphical user interaction model for integrating complex clinical applications: a pilot study.

We have developed and implemented a multi-faceted, graphical user interaction model for an advanced clinical information system. This paper describes a classification scheme for applications used by clinicians in their daily work, discusses the way clinicians interact with these applications, and the issues that arise during these user interactions. Through its emphasis on support for application interoperation, the graphical user interface that implements the model presents a single, consistent, context to the user, and thereby helps maintain patient safety and ensure ease of use.

Computer Graphics↗
PubMed1997

Does the computerized display of charges affect inpatient ancillary test utilization?

BACKGROUND: The computerized display of charges for ancillary tests in outpatients has been found to affect physician-ordering behavior, but this issue has not been studied in inpatients. OBJECTIVE: To assess whether the computerized display of charges for clinical laboratory or radiological tests affected physician-ordering behavior. PATIENTS AND METHODS: Two prospective controlled trials, randomized by patient, were performed. Each trial included all medical and surgical inpatients at 1 large teaching hospital during 4 and 7 months: 3536 intervention and 3554 control inpatients in the group with clinical laboratory tests, and 8728 intervention and 8653 control inpatients in the group with radiological tests. The intervention consisted of the computerized display of charges for tests at the time of ordering. MAIN OUTCOME MEASURES: The number of clinical laboratory and radiological tests ordered per admission and the charges for these tests. RESULTS: For the clinical laboratory tests, during a 4-month study period, patients in the intervention group had 4.5% fewer tests ordered, and the total charges for these tests were 4.2% lower, although neither difference was statistically significant. Compared with historical controls from the same 4-month period a year before, the charges for the tests per admission had decreased 13.3%, but the decrease was temporally correlated with a restriction of future ordering of tests, and not with the introduction of the display of charges. For the radiological tests, during a 7-month period, the intervention group had almost identical numbers of tests ordered and charges for these tests. CONCLUSIONS: The computerized display of charges had no statistically significant effect on the number of clinical laboratory tests or radiological procedures ordered or performed, although small trends were present for clinical laboratory tests. More intensive interventions may be needed to affect physician test utilization.

Computer Systems↗
PubMed1997

Electronic communication with patients. Evaluation of distance medicine technology.

OBJECTIVE: To evaluate controlled evidence on the efficacy of distance medicine technologies in clinical practice and health care outcome. DATA SOURCES: Systematic electronic database and manual searches (1966-1996) were conducted to identify clinical trial reports on distance medicine applications. STUDY SELECTION: Three eligibility criteria were applied: prospective, contemporaneously controlled clinical trial with random assignment of the intervention; electronic distance technology application in the intervention group and no similar intervention in the control group; and measurement of the intervention effect on process or outcome of care. DATA EXTRACTION: Data were abstracted by independent reviewers using a standardized abstraction form and the quality of methodology was scored. Distance technology applications were described in 6 categories: computerized communication, telephone follow-up and counseling, telephone reminders, interactive telephone systems, after-hours telephone access, and telephone screening. DATA SYNTHESIS: Of 80 eligible clinical trials, 61 (76%) analyzed provider-initiated communication with patients and 50 (63%) reported positive outcome, improved performance, or significant benefits, including studies of computerized communication (7 of 7), telephone follow-up and counseling (20 of 37), telephone reminders (14 of 23), interactive telephone systems (5 of 6), telephone access (3 of 4), and telephone screening (1 of 3). Significantly improved outcomes were demonstrated in studies of preventive care, management of osteoarthritis, cardiac rehabilitation, and diabetes care. CONCLUSIONS: Distance medicine technology enables greater continuity of care by improving access and supporting the coordination of activities by a clinician. The benefits of distance technologies in facilitating communication between clinicians and patients indicate that application of telemedicine should not be limited to physician-to-physician communication.

Communication↗
PubMed1997

Advanced alerting features: displaying new relevant data and retracting alerts.

We added two advanced features to our automated alerting system. The first feature identifies and displays, at the time an alert is reviewed, relevant data filed between the login time of a specimen leading to an alerting result and the time the alert is reviewed. Relevant data is defined as data of the same kind as generated the alert. The other feature retracts alerts when the alerting value is edited and no longer satisfies the alerting criteria. We evaluated the two features for a 14-week period (new relevant data) and a 6-week period (retraction). Of a total of 1104 alerts in the 14-week evaluation, 286 (25.9%) had new relevant data displayed at alert review time. Of the 286, 75.2% were due to additions of comments to the original piece of alerting data; 24.1% were due to new or pending laboratory results of the same type that generated the alert. Two alerts (out of 490) were retracted in a 6 week period. We conclude that in our system, new clinically relevant data is often added between the time of specimen login and the time that an alerting result from that specimen is reviewed. Retractions occur rarely but are important to detect and communicate.

Data Display↗
PubMed1996

WWW-based interfaces to clinical information systems: the state of the art.

Nine WWW-based interfaces to clinical information systems were reviewed. Five have progressed past the proof of concept phase and into alpha testing in the clinical environment. All key features desirable in an advanced clinical information were present in at least one interface, however many implementations were rudimentary. Much human computer interface research and WWW tool development needs to occur before implementation of a WWW-based interface to a clinical information system should be considered for a mission-critical, production environment.

Computer Communication Networks↗
PubMed1996

Detecting alerts, notifying the physician, and offering action items: a comprehensive alerting system.

We developed and evaluated a system to automatically identify serious clinical conditions in inpatients. The system notifies the patient's covering physician via his pager that an alert is present and offers potential therapies for the patient's condition (action items) at the time he views the alert information. Over a 6 month period, physicians responded to 1214 (70.2%) of 1730 alerts for which they were paged; they responded to 1002 (82.5% of the 1214) in less than 15 minutes. They said they would take action in 71.5% of the alerts, and they placed an order directly from the alert display screen in 39.4%. Further study is needed to determine if this alerting system improves processes or outcomes of care.

Attitude to Computers↗
PubMed1995

Representing hospital events as complex conditionals.

We have developed an approach to medical knowledge representation whereby simple medical concepts are combined to yield complex statements of testable medical logic. The logic is created from a small number of generic medical concepts that are instantiated and combined to create the rules. Rule writing is done through a rule editor and requires knowledge of the system's data dictionaries, though no programming is required. We have used the approach to create a large knowledge base including panic lab alerting rules, drug-laboratory interaction alerting rules, an adverse drug event monitor, and a drug-age interaction detection program. The rules have been used as part of an alerting system and for data collection to determine the frequency of events of interest. The scheme is extensible and yields a readable form of the created knowledge. The scheme holds great promise as a durable form of medical knowledge representation.

Artificial Intelligence↗
PubMed1994

A new knowledge structure for drug-drug interactions.

We developed a program to automatically screen patients' medication profiles for pairs of interacting drugs. Since some drug-drug interactions are indicated by changes in physiological parameters (e.g., ciprofloxacin and theophylline leading to an elevation of theophylline levels), the program considered the patients' relevant laboratory parameters prior to generating the alerts. We developed an editor to facilitate maintenance of the knowledge base. We evaluated the program for 3 weeks in two satellite pharmacies. The program reported 160 alerts of which 5 resulted in a change in the patients' therapies (one per 500 patient-days of care). These five interactions were potentially very serious. An additional 3 alerts led to changes in medication administration times. Subjectively, the program is well received and continues to be in routine clinical use.

Drug Interactions↗
PubMed1991

Innovations and research review: the impact of the HELP computer system on the LDS Hospital paper medical record.

This study sought to answer the question: What percentage of an LDS Hospital patient's chart is contained in the HELP system? Using the number of pages in the record as the criteria, the answer is about 26 percent overall, but between 35 percent and 40 percent for patients in nursing divisions where computerized nurse charting is used. Although this fraction is likely to rise in the near future, the critical factor driving computerization is the desire for data usable in computerized decision making rather than the need to computerize the entire chart per se. The medical record at LDS Hospital will probably be a hybrid of computerized and paper data for some time to come.

Documentation↗
PubMedDate not supplied

Identifying hospital admissions due to adverse drug events using a computer-based monitor.

BACKGROUND: Hospital admissions due to adverse drug events (ADEs) are expensive, and many may be preventable, yet few institutions have ongoing surveillance for these events. OBJECTIVE: To evaluate the use of a computer-based ADE monitor to identify admissions due to ADEs and to measure the associated costs. DESIGN: Prospective cohort study in one tertiary care hospital. PARTICIPANTS: All patients admitted to nine medical and surgical units in a tertiary care hospital over an 8-month period. MAIN OUTCOME MEASURE: Admissions to the hospital due to an adverse drug event. METHODS: A computer-based monitoring program generated alerts suggesting that an ADE might be present. A trained reviewer then evaluated the record. RESULTS: Among the 3238 admissions, 76 (2.3%, 1.4% after adjusting for sampling) were found to be caused by an ADE. Of these ADEs, 78% were severe and 28% were preventable. Estimated costs were $16,177 per ADE, and $10,375 per preventable ADE; annualized costs to the hospital were $6.3 million per year for all ADEs, and $1.2 million for preventable ADEs. CONCLUSIONS: Many admissions were caused by ADEs, although our point estimate undoubtedly represents a lower bound. These events were mostly severe, often preventable, and expensive. The computer-based monitoring system represents a practical approach for identifying ADEs that occur in outpatients and cause admission to the hospital.

Adult↗
PubMedDate not supplied

Using information systems to measure and improve quality.

Information systems (IS) are increasingly important for measuring and improving quality. In this paper, we describe our integrated delivery system's plan for and experiences with measuring and improving quality using IS. Our belief is that for quality measurement to be practical, it must be integrated with the routine provision of care and whenever possible should be done using IS. Thus, at one hospital, we now perform almost all quality measurement using IS. We are also building a clinical data warehouse, which will serve as a repository for quality information across the network. However, IS are not only useful for measuring care, but also represent powerful tools for improving care using decision support. Specific areas in which we have already seen significant benefit include reducing the unnecessary use of laboratory testing, reporting important abnormalities to key providers rapidly, prevention and detection of adverse drug events, initiatives to change prescribing patterns to reduce drug costs and making critical pathways available to providers. Our next major effort will be introduce computerized guidelines on a more widespread basis, which will be challenging. However, the advent of managed care in the US has produced strong incentives to provide high quality care at low cost and our perspective is that only with better IS than exist today will this be possible without compromising quality. Such systems make feasible implementation of quality measurement, care improvement and cost reduction initiatives on a scale which could not previously be considered.

Computer Communication Networks↗