Characteristics associated with postdischarge medication errors

Abstract

Objective: To examine the association of patient- and medication-related factors with postdischarge medication errors.

Patients and methods: The Vanderbilt Inpatient Cohort Study includes adults hospitalized with acute coronary syndromes and/or acute decompensated heart failure. We measured health literacy, subjective numeracy, marital status, cognition, social support, educational attainment, income, depression, global health status, and medication adherence in patients enrolled from October 1, 2011, through August 31, 2012. We used binomial logistic regression to determine predictors of discordance between the discharge medication list and the patient-reported list during postdischarge medication review.

Results: Among 471 patients (mean age, 59 years), the mean total number of medications reported was 12, and 79 patients (16.8%) had inadequate or marginal health literacy. A total of 242 patients (51.4%) were taking 1 or more discordant medication (ie, appeared on either the discharge list or patient-reported list but not both), 129 (27.4%) failed to report a medication on their discharge list, and 168 (35.7%) reported a medication not on their discharge list. In addition, 279 participants (59.2%) had a misunderstanding in indication, dose, or frequency in a cardiac medication. In multivariable analyses, higher subjective numeracy (odds ratio [OR], 0.81; 95% CI, 0.67-0.98) was associated with lower odds of having discordant medications. For cardiac medications, participants with higher health literacy (OR, 0.84; 95% CI, 0.74-0.95), with higher subjective numeracy (OR, 0.77; 95% CI, 0.63-0.95), and who were female (OR, 0.60; 95% CI, 0.46-0.78) had lower odds of misunderstandings in indication, dose, or frequency.

Conclusion: Medication errors are present in approximately half of patients after hospital discharge and are more common among patients with lower numeracy or health literacy.

Figure 1

Classification of medication errors identified during the post-discharge phone interview. Panel a. Example of outcome codes for the comparison of patient report and discharge list. Panel b. Three examples of counting misunderstandings for select cardiac medications on discharge list: lisinopril, clopidogrel, and simvastatin. Footnotes: ^aExamples of other accepted indication responses for anti-platelet medications: “helps blood flow,” “for clots,” “blood thinner,” “for circulation” ^bExamples of other accepted indication responses for lipid lowering medications: “high cholesterol”, “fat in blood”, “high fat”, “high LDL”

Figure 1

Classification of medication errors identified during the post-discharge phone interview. Panel a. Example of outcome codes for the comparison of patient report and discharge list. Panel b. Three examples of counting misunderstandings for select cardiac medications on discharge list: lisinopril, clopidogrel, and simvastatin. Footnotes: ^aExamples of other accepted indication responses for anti-platelet medications: “helps blood flow,” “for clots,” “blood thinner,” “for circulation” ^bExamples of other accepted indication responses for lipid lowering medications: “high cholesterol”, “fat in blood”, “high fat”, “high LDL”

Figure 2

Flow chart displaying how patient eligibility was determined.

Figure 3

Factors associated with discordant medications (panel a), errors of omission (panel b), and commission (panel c), reported as odds ratio with 95% confidence intervals.

Figure 4

Factors associated with any misunderstanding (indication, dose, or frequency—panel a), indication (panel b), dose (panel c), and frequency (panel d).