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Publication Record


Erratum to: effect of patient- and medication-related factors on inpatient medication reconciliation errors.
Salanitro AH, Osborn CY, Schnipper JL, Roumie CL, Labonville S, Johnson DC, Neal E, Cawthon C, Businger A, Dalal AK, Kripalani S
(2012) J Gen Intern Med 27: 1393
MeSH Terms: Humans, Medication Errors, Medication Reconciliation
Added December 10, 2013
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3 MeSH Terms
Effect of patient- and medication-related factors on inpatient medication reconciliation errors.
Salanitro AH, Osborn CY, Schnipper JL, Roumie CL, Labonville S, Johnson DC, Neal E, Cawthon C, Businger A, Dalal AK, Kripalani S
(2012) J Gen Intern Med 27: 924-32
MeSH Terms: Aged, Cross-Sectional Studies, Female, Health Literacy, Heart Diseases, Hospitalization, Humans, Male, Medication Errors, Medication Reconciliation, Middle Aged, Treatment Outcome
Show Abstract · Added December 10, 2013
BACKGROUND - Little research has examined the incidence, clinical relevance, and predictors of medication reconciliation errors at hospital admission and discharge.
OBJECTIVE - To identify patient- and medication-related factors that contribute to pre-admission medication list (PAML) errors and admission order errors, and to test whether such errors persist in the discharge medication list.
DESIGN, PARTICIPANTS - We conducted a cross-sectional analysis of 423 adults with acute coronary syndromes or acute decompensated heart failure admitted to two academic hospitals who received pharmacist-assisted medication reconciliation during the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL-CVD) Study.
MAIN MEASURES - Pharmacists assessed the number of total and clinically relevant errors in the PAML and admission and discharge medication orders. We used negative binomial regression and report incidence rate ratios (IRR) of predictors of reconciliation errors.
KEY RESULTS - On admission, 174 of 413 patients (42%) had ≥1 PAML error, and 73 (18%) had ≥1 clinically relevant PAML error. At discharge, 158 of 405 patients (39%) had ≥1 discharge medication error, and 126 (31%) had ≥1 clinically relevant discharge medication error. Clinically relevant PAML errors were associated with older age (IRR = 1.46; 95% CI, 1.00- 2.12) and number of pre-admission medications (IRR = 1.17; 95% CI, 1.10-1.25), and were less likely when a recent medication list was present in the electronic medical record (EMR) (IRR = 0.54; 95% CI, 0.30-0.96). Clinically relevant admission order errors were also associated with older age and number of pre-admission medications. Clinically relevant discharge medication errors were more likely for every PAML error (IRR = 1.31; 95% CI, 1.19-1.45) and number of medications changed prior to discharge (IRR = 1.06; 95% CI, 1.01-1.11).
CONCLUSIONS - Medication reconciliation errors are common at hospital admission and discharge. Errors in preadmission medication histories are associated with older age and number of medications and lead to more discharge reconciliation errors. A recent medication list in the EMR is protective against medication reconciliation errors.
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12 MeSH Terms
Prevalence and Clinical Significance of Discrepancies within Three Computerized Pre-Admission Medication Lists.
Peterson JF, Shi Y, Denny JC, Matheny ME, Schildcrout JS, Waitman LR, Miller RA
(2010) AMIA Annu Symp Proc 2010: 642-6
MeSH Terms: Hospitalization, Humans, Medication Errors, Medication Reconciliation, Patient Admission, Prevalence
Show Abstract · Added May 19, 2014
Inaccurate records of pre-admission medication exposure have been identified as a major source of medication error. Authors collected records of patients' pre-admission medications: 1) the most recent outpatient medication list ("EMR"), 2) the medication list recorded by admitting providers ("H&P"), and 3) a list generated by a medication reconciliation process conducted by nursing staff ("PAML"). Forty-eight sets of pre-admission records composed of 1087 medication entries were compared to a reference standard generated by trained study staff conducting an independent interview. Sensitivity was greatest for PAML (85%), compared to EMR (76%) and H&P (76%) sources. However, positive predictive value was greatest for the H&P source at 96% vs 88% and 91% for PAML and EMR sources respectively. Potentially harmful medication discrepancies were found within all lists. The authors concluded no single list was sufficiently accurate to avoid serious medication errors.
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6 MeSH Terms