To implement and measure the effects of automatic computerized laboratory signals (ALS) as a detection support tool of adverse drug reactions (ADRs) in hospital.
This was a prospective observational study of a total of 192 patients (199 sequential medical admissions) during a 2-month period in a 34-bed medical ward at the Hadassah University Hospital, Jerusalem, Israel. The study involved the routine (daily) distribution to staff physicians of lists of automatic signals generated from computerized laboratory data as potential indicators of ADRs. Patient charts were reviewed by the clinical pharmacology team for ADRs and to see whether these were recognized by the staff physicians.
Seventy-one ADRs were detected in 64 of the 199 (32%) admissions. Twenty-seven per cent of the ADRs were serious, 9% of the admissions were due to ADRs. Two hundred and ninety-five ALS were generated involving 69% of the admissions. Sixty-one per cent of the ADRs were identified by ALS. ALS were present in 58% of the ADR negative admissions. Eighty-five per cent of the ADRs were recognized as such and 19% of the ALS-positive ADRs were not recognized by the staff physicians.
The routine implementation of ALS doubled the number of ADRs recognized by the physicians while patients were hospitalized in the medical ward. The use of the system appeared valid, simple and potentially cost-effective.
"and reasons for discontinuation can be included in the questionnaire. Such projects have proved useful for the study of acute and relatively common ADRs (Schumock et al., 1995; Levy et al., 1999; Van Puijenbroek et al., 2002; Coulter, 2002). ADRs and events have a considerable impact not only on the health of the population but also on health care costs; they account for 5% of all hospital admissions, occur in 10–20% of inpatients, cause death in 0.1% of medical and 0.01% of surgical inpatients and increase the costs of patient care (Meyboom et al., 2002; Pirmohamed et al., 1998). "
[Show abstract][Hide abstract] ABSTRACT: Adverse drug reactions (ADR) are a significant cause of morbidity and mortality, often identified only post-marketingly. Improvement in current ADR reporting, including utility of underused or innovative methods, is crucial to improve patient safety and public health. Hospital-based monitoring is one of the methods used to collect data about drug prescriptions and adverse events. The aims of this study were to identify the most frequent ADRs recognized by the attending physicians, study their nature, and to target these ADRs in order to take future preventive measures. A prospective study was conducted over a 7-month period in an internal medicine department using stimulated spontaneous reporting for identifying ADRs. Out of the 254 admissions, 32 ADRs in 37 patients (14.56%) were validated from the total of 36 suspected ADRs in 41 patients. Female predominance was noted over males in case of ADRs. Fifty percent of total ADRs occurred due to multiple drug therapy. Dermatological ADRs were found to be the most frequent (68.75%), followed by respiratory, central nervous system and gastrointestinal ADRs. The drugs most frequently involved were antibiotics, anti-tubercular agents, antigout agents, and NSAIDs. The most commonly reported reactions were itching and rashes. Out of the 32 reported ADRs, 50% of the reactions were probable, 46.87% of the reactions were possible and 3.12% of the reactions were definite. The severity assessment done by using the Hartwig and Seigel scale indicated that the majority of ADRs were 'Mild' followed by 'Moderate' and 'Severe' reactions, respectively. Out of all, 75% of ADRs were recovered. The most potent management of ADRs was found to be drug withdrawal. Our study indicated that hospital based monitoring was a good method to detect links between drug exposure and adverse drug reactions. Adequate training regarding pharmacology and optimization of drug therapy might be helpful to reduce ADR morbidity and mortality.
"st of 86 million euros.(Leendertse et al., 2008) Medication errors occur due to the rapidly increasing complexity of evidence based medicine and error sensitivity of healthcare.(James, 2002) Physicians need to take many drug-and patient specific characteristics into account and literature shows that this is often omitted or not recognized in time.(Levy et al., 1999;Schiff et al., 2003;Denekamp, 2007) Beyond reminders, CDSS can integrate clinical data to support professionals managing an increasingly complex practice environment.(James, 2001) Integration of these specific parameters is necessary to guide patients through the complete clinical pathway from anamnesis to evaluation and fine-tuning of "
"34 bed medical ward in teaching hospital Jha et al., 1998 39 726 bed tertiary teaching hospital Raschke et al., 1998 46 650 bed community teaching hospital Levy et al., 1999 18 34 bed medical ward in teaching hospital Dormann et al., 2000 41 9 bed medical ward in a teaching hospital Brown et al., 2000 48 238 bed Veterans Administration Medical Center Jha et al., 2001 42 726 bed tertiary care teaching hospital Thuermann et al., 2002 43 86 bed neurology department in teaching hospital Dormann et al., 2004 44 29 bed gastroenterology ward in teaching hospital Silverman et al., 2004 47 726 bed tertiary care teaching hospital Hartis et al., 2005 "
[Show abstract][Hide abstract] ABSTRACT: Despite demonstrated benefits, few healthcare organizations have implemented clinical event monitors to detect adverse drug events (ADEs). The objective of this study was to conduct a systematic review of pharmacy and laboratory signals used by clinical event monitors to detect ADEs in hospitalized adults.
We performed a comprehensive search of MEDLINE, CINHAL and EMBASE to identify studies published between 1985 through 2006. Studies were included if they: described a clinical event monitor to detect ADEs in an adult hospital setting; described laboratory or pharmacy ADE signals; and, provided positive predictive values (PPVs) or information to allow the calculation of PPVs for individual ADE signals.
We calculated overall estimates of PPVs and 95% confidence intervals (CIs) for signals reported in 2 or more studies and contained no evidence heterogeneity. Results were examined by signal category: medication levels, laboratory tests, or antidotes.
We identified 12 observational studies describing 36 unique ADE signals. Fifteen signals (3 antidotes, 4 medication levels, and 8 laboratory values) contained no evidence of heterogeneity. The pooled PPVs for these individual signals ranged from 0.03 [CI=0.03-0.03] for hypokalemia, to 0.50 [CI=0.39-0.61] for supratherapeutic quinidine level. In general, antidotes (range=0.09-0.11) had the lowest PPVs, followed by laboratory values (0.03-0.27), and medication levels (0.03-0.50).
Results from this study should help clinical information system and computerized decision support producers develop or improve existing clinical event monitors to detect ADEs in their own hospitals by prioritizing those signals with the highest PPVs [corrected]
Journal of the American Medical Informatics Association 04/2007; 14(4):451-8. DOI:10.1197/jamia.M2369 · 3.50 Impact Factor
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