2012 February 20

Automatic detection of omissions in medication lists.

J Am Med Inform Assoc Start a Discussion »

Feb 202012

Automatic detection of omissions in medication lists.

J Am Med Inform Assoc. 2011 Jul-Aug;18(4):449-58

Authors: Hasan S, Duncan GT, Neill DB, Padman R

Abstract
OBJECTIVE: Evidence suggests that the medication lists of patients are often incomplete and could negatively affect patient outcomes. In this article, the authors propose the application of collaborative filtering methods to the medication reconciliation task. Given a current medication list for a patient, the authors employ collaborative filtering approaches to predict drugs the patient could be taking but are missing from their observed list.
DESIGN: The collaborative filtering approach presented in this paper emerges from the insight that an omission in a medication list is analogous to an item a consumer might purchase from a product list. Online retailers use collaborative filtering to recommend relevant products using retrospective purchase data. In this article, the authors argue that patient information in electronic medical records, combined with artificial intelligence methods, can enhance medication reconciliation. The authors formulate the detection of omissions in medication lists as a collaborative filtering problem. Detection of omissions is accomplished using several machine-learning approaches. The effectiveness of these approaches is evaluated using medication data from three long-term care centers. The authors also propose several decision-theoretic extensions to the methodology for incorporating medical knowledge into recommendations.
RESULTS: Results show that collaborative filtering identifies the missing drug in the top-10 list about 40-50% of the time and the therapeutic class of the missing drug 50%-65% of the time at the three clinics in this study.
CONCLUSION: Results suggest that collaborative filtering can be a valuable tool for reconciling medication lists, complementing currently recommended process-driven approaches. However, a one-size-fits-all approach is not optimal, and consideration should be given to context (eg, types of patients and drug regimens) and consequence (eg, the impact of omission on outcomes).

PMID: 21447497 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

The role of housestaff in implementing medication reconciliation on admission at an academic medical center.

Am J Med Qual Start a Discussion »

Feb 202012

The role of housestaff in implementing medication reconciliation on admission at an academic medical center.

Am J Med Qual. 2011 Jan-Feb;26(1):39-42

Authors: Evans AS, Lazar EJ, Tiase VL, Fleischut P, Bostwick SB, Hripcsak G, Liebowitz R, Forese LL, Kerr G

Abstract
Since 2006, the Joint Commission has required all hospitals to have a process in place for medication reconciliation (MR). Although it has been shown that MR decreases medical errors, achieving compliance has proven difficult for many health care institutions. This article describes a housestaff-championed intervention of a "hard stop" for on-admission MR orders that led to a statistically significant increase in compliance that was sustained at 6 months after intervention. Academic medical centers, which comprise large numbers of housestaff, can improve compliance with on-admission MR by engaging housestaff in the development of solutions and in communication to their peers, leading to sustained results.

PMID: 20501865 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

High-tech approach to medication reconciliation saves time, bolsters safety at hospital in northern Virginia.

ed manag Start a Discussion »

Feb 202012

High-tech approach to medication reconciliation saves time, bolsters safety at hospital in northern Virginia.

ED Manag. 2011 Oct;23(10):117-9

Authors:

Abstract
Clinicians in the ED at Alexandria Inova Hospital in Alexandria, VA, have been able to streamline the medicine reconciliation process with the help of a new high-tech tool that retrieves a patient's medication history in a matter of minutes and transforms the data into a form that can automatically populate the patient's electronic medical record.The approach is facilitated by the regional health information exchange (HIE) organization, and will eventually be available to other providers in northern Virginia. Thus far, 80% to 90% of patients who have come through the ED have consented to have their medication history electronically retrieved. Eventually, administrators anticipate that the same approach will be used to share patient radiology studies, laboratory results, and other patient information across providers. Experts predict this practice will be commonplace among U.S. hospitals within five years, but they encourage hospital and ED administrators to take advantage of opportunities to leverage regional HIEs.

PMID: 21972757 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

Emergency department medication lists are not accurate.

J Emerg Med Start a Discussion »

Feb 202012

Emergency department medication lists are not accurate.

J Emerg Med. 2011 Jun;40(6):613-6

Authors: Caglar S, Henneman PL, Blank FS, Smithline HA, Henneman EA

Abstract
BACKGROUND: Medication errors are a common source of adverse events. Errors in the home medication list may impact care in the Emergency Department (ED), the hospital, and the home. Medication reconciliation, a Joint Commission requirement, begins with an accurate home medication list.
OBJECTIVE: To evaluate the accuracy of the ED home medication list.
METHODS: Prospective, observational study of patients aged > 64 years admitted to the hospital. After obtaining informed consent, a home medication list was compiled by research staff after consultation with the patient, their family and, when appropriate, their pharmacy and primary care doctor. This home medication list was not available to ED staff and was not placed in the ED chart. ED records were then reviewed by a physician, blinded to the research-generated home medication list, using a standardized data sheet to record the ED list of medications. The research-generated home medication list was compared to the standard medication list and the number of omissions, duplications, and dosing errors was determined.
RESULTS: There were 98 patients enrolled in the study; 56% (55/98, 95% confidence interval [CI] 46-66%) of the medication lists for these patients had an omission and 80% (78/98, 95% CI 70-87%) had a dosing or frequency error; 87% of ED medication lists had at least one error (85/98, 95% CI 78-93%).
CONCLUSION: Our findings now add the ED to the list of other areas within health care with inaccurate medication lists. Strategies are needed that support ED providers in obtaining and communicating accurate and complete medication histories.

PMID: 18829201 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

Effect of emergency department crowding on pneumonia admission care components.

Am J Manag Care Start a Discussion »

Feb 202012

Effect of emergency department crowding on pneumonia admission care components.

Am J Manag Care. 2011 Apr;17(4):269-78

Authors: Fee C, Weber EJ, Bacchetti P, Maak CA

Abstract
OBJECTIVE: To determine pneumonia admission care components that are most affected by emergency department (ED) crowding.
STUDY DESIGN: Secondary analysis of a cross-sectional observational survey.
METHODS: The setting was a 29-bed academic ED with 39,000 visits per year and state-mandated ratios of nurses to patients. The patients were ED admissions with pneumonia, January 1, 2004, to June 30, 2005. From ED medical records and databases, we abstracted the times of arrival, room placement, ordering of chest radiograph and when obtained, ordering of blood culture and when obtained, and ordering of antibiotic and when administered. We assessed associations between ED volume at the time of arrival of a patient with pneumonia and component durations using multivariate linear regression.
RESULTS: For 407 ED admissions with pneumonia, the median component durations (in minutes) were as follows: 20 for arrival to room placement, 44 for arrival to chest radiograph order, 10 for chest radiograph order to radiograph obtained, 120 for room placement to antibiotic order, 10 for blood culture order to culture obtained, 30 for antibiotic order to antibiotic administered, and 195 for arrival to antibiotic administered. Sixty-one percent of patients received antibiotic within 4 hours. We estimate that for every 10 additional ED patients the time from arrival to ordering of a chest radiograph was prolonged by 14.3 minutes and from ordering of antibiotic to administration by 9.3 minutes.
CONCLUSIONS: Despite compliance with mandated ratios of nurses to patients, the time from antibiotic ordering to administration (a nursing task) was prolonged with higher ED volumes, as were throughput measures. Targeting these may expedite treatment under crowded ED conditions.

PMID: 21615197 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

Intensive care unit admission of decompensated cirrhotic patients: prognostic scoring systems.

transplant proc Start a Discussion »

Feb 202012

Intensive care unit admission of decompensated cirrhotic patients: prognostic scoring systems.

Transplant Proc. 2011 May;43(4):1079-84

Authors: Feltracco P, Brezzi M, Barbieri S, Milevoj M, Galligioni H, Cillo U, Zanus G, Vitale A, Ori C

Abstract
Cirrhotic patients who need critical care support show high morbidity and mortality rates compared with other critically ill patients. Their prognosis is, in fact, influenced by both the severity of the underlying hepatic disease and the worsening of extrahepatic organ function. Clinicians and investigators have been persistently looking for objective scoring systems capable of providing accurate information on disease severity and short-term prognosis. Risk stratification helps differentiate patients who would not benefit from admission to the intensive care unit (ICU) from those who could achieve better outcomes once aggressively treated. The most common scores, ie, multiple organ dysfunction score, sequential organ failure assessment, and acute physiology and chronic health evaluation, developed in general ICUs to evaluate illness severity, have also been validated to predict the prognosis of cirrhotic patients admitted to the ICU. However, their absolute predictive value has been questioned. A weakness of common prediction models consists in not recognizing the continuum of physiological changes in critically ill decompensated cirrhotic patients. In addition, the predictive power to stratify individual risk is relatively low due to the great variability of liver dysfunction stages, the severity of related manifestations, and the number of nonfunctioning organs on admission. Probability models are not capable of predicting whether a patient will live or die with 100% accuracy, nor can they deny or confirm the indications for mechanical ventilation, vasopressor support or renal replacement therapy, or help to decide when to withhold or withdraw support. Because there are no absolute criteria to predict which cirrhotic decompensated patients will improve with normalization of organ function or deteriorate progressively, a scoring system should be regarded as an adjunct rather than a substitute for clinical judgment in the decision process concerning whether a patient should be admitted to the ICU.

PMID: 21620058 [PubMed - indexed for MEDLINE]

Link to Article at PubMed

Older Entries

February 2012
M	T	W	T	F	S	S
« Jan				Mar »
		1	2	3	4	5
6	7	8	9	10	11	12
13	14	15	16	17	18	19
20	21	22	23	24	25	26
27	28	29