The aim of this study was to determine the impact of a patient-centered health information technology (HIT) on the error rate for ordering and prescribing of medications during emergency pediatric care.
We conducted a quasi-experimental intervention study by using control and intervention periods to evaluate the effect on medication ordering and prescribing from a patient-centered HIT designed to enhance communication between parents and emergency clinicians during emergency care. Parent-child dyads presenting to 2 emergency department (ED) sites with complaints of fever, asthma, head trauma, otalgia, and dysuria were eligible. During intervention periods, parents used the HIT to enter data on symptoms and medication-related history; a printout provided recommendations to clinicians. Data on errors/adverse drug events were collected via record reviews and phone interviews with parents. The primary outcome was the number of medication errors in orders or prescriptions for drugs targeted by the HIT.
Of 2002 parent-child dyads screened, 1810 (90%) were eligible, 1411 of 1810 (78%) were enrolled, and 1410 analyzed; 1097 subjects had a total of 2234 orders or prescriptions written. Of these events, 1289 of 2234 (58%) were associated with at least 1 error. Of the 1755 errors discovered, 232 errors were serious and preventable. Among 654 patients exposed to medications targeted by the HIT, the number of errors per 100 patients during control versus intervention periods was not significantly different (173 vs 134 with both sites combined; P = .35.)
The patient-centered HIT demonstrated minimal impact on medication errors during ED care.
[Show abstract][Hide abstract] ABSTRACT: 1. Patients and their carers will usually be the first to notice any observable problems resulting from medication errors. They will probably be unable to distinguish between medication errors, adverse drug reactions, or ‘side effects’.
2. Little is known about how patients understand drug related problems or how they make attributions of adverse effects. Some research suggests that patients' cognitive models of adverse drug reactions bear a close relationship to models of illness perception.
3. Attributions of adverse drug reactions are related to people's previous experiences and to their level of education. The evidence suggests that on the whole patients' reports of adverse drug reactions are accurate. However, patients do not report all the problems they perceive and are more likely to report those that they do perceive as severe. Patients may not report problems attributed to their medications if they are fearful of doctors' reactions. Doctors may respond inappropriately to patients' concerns, for example by ignoring them. Some authors have proposed the use of a symptom checklist to elicit patients' reports of suspected adverse drug reactions.
4. Many patients want information about adverse drug effects, and the challenge for the professional is to judge how much information to provide and the best way of doing so. Professionals' inappropriate emphasis on adherence may be dangerous when a medication error has occurred.
5. Recent NICE guidelines recommend that professionals should ask patients if they have any concerns about their medicines, and this approach is likely to yield information conducive to the identification of medication errors.
British Journal of Clinical Pharmacology 07/2009; 67(6):646-50. DOI:10.1111/j.1365-2125.2009.03421.x · 3.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Maryland hospitals have been improving the safety of medication use practices since 2000. A retrospective analysis of 35 hospitals was conducted for 2005-2007 to determine the changes in medication use practices, communication methods within hospitals, patient education and changes in medical record management.
Thirty-five Maryland hospitals completed the Institute for Safe Medication Practices Medication Safety Self-Assessment for Hospitals, a voluntary initiative to improve the safety of medication use. A weighting structure is applied to calculate key element scores, core characteristic scores and overall self-assessment scores that were used in ANOVA and regression analyses. Findings: The state-wide aggregate score significantly increased from 74.2% in 2005 to 81.2% in 2007 (p<0.05). The 35 hospitals scored highest in the following key areas in 2007: drug standardisation, storage and distribution (90.2%); drug labelling, packaging and nomenclature (88.1%); and environmental factors (84.3%). Results indicated that hospitals scored lowest in the key element area related to accessibility of patient information (72.5%) and in the core characteristics pertaining to redundancies and independent double checks (64.2%) in 2007. A substantial number of hospitals had positive and significant (p<0.05) changes in certain key elements and/or core characteristics. Few hospitals showed significant (p<0.05) decreases in their scores.
MEDSAFE has directly assisted Maryland hospitals in improving medication use safety. The strategies and tools of MEDSAFE have been used in Maryland since 2000 and Singapore and Austria since 2006.
Quality and Safety in Health Care 10/2009; 18(5):331-5. DOI:10.1136/qshc.2008.027938 · 2.16 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The authors report on a preliminary analysis of an electronic database that includes more than 32 000 pediatric hospitalizations during 2000-2003. They analyzed pediatric inpatient medication use in a defined geographic area, the catchment area for the Alfred I. duPont Hospital for Children, serving Delaware, Maryland, New Jersey, and Pennsylvania. The study population included 18 108 female and 14 375 male children. The authors calculated the percentages of children receiving at least 1 administration of each drug. More than 700 drugs were received by children in the study population; 9 were received by at least 10% of all patients. The probability of receiving specific medications varied with patient age, sex, and race, but much further work is needed to quantify the variations. The database has the potential to inform pediatric health services research and pediatric comparative effectiveness research, and it may be the first analysis of hospitalizations for a pediatric population comprising all ages from 0 to 18.
American Journal of Medical Quality 05/2010; 25(3):225-31. DOI:10.1177/1062860609359934 · 1.25 Impact Factor
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