The effect of Computerised Physician Order Entry on prescribing errors: An interrupted time-series study at a secondary referral hospital in Australia.

BACKGROUND: Computerised Physician Order Entry (CPOE) software is increasingly used across the world to improve medication safety. However, few high-quality studies have reviewed the impact of CPOE on prescribing errors and patient harm. OBJECTIVE: To investigate the effect of a hybrid CPOE-paper prescribing system on prescribing errors at a secondary hospital site. DESIGN: An interrupted time-series study was conducted by identifying prescribing errors via prospective medical chart review before and after the implementation of CPOE across three medical wards. PARTICIPANTS: The medication orders of all patients admitted to the medical wards during the study period were reviewed. INTERVENTION: Implementation of a CPOE across three medical wards. MEASURES: A blinded expert panel risk stratified the errors according to level of severity, preventability and potential for harm. Pearson's chi square and segmented regressions were used to determine if there were differences in prescribing errors pre- and post-CPOE implementation. KEY RESULTS: A total of 10,535 medication orders were reviewed pre-CPOE and 13,841 medication orders reviewed post-CPOE. Analysis demonstrated that after implementation of CPOE there were reductions in the proportion of orders with one or more of any error (-30.1%, 95 %CI: -36.5%, -23.7%, p < 0.001). Reductions in the proportion of orders with one or more errors were seen across the error categories of dosing errors (-20.1%, 95 %CI: -25.1%, -15%, p < 0.001), procedural/administrative errors (-18.9%, 95 %CI: -22.8%, -15%, p < 0.001), and therapeutic errors (-2.6%, 95 %CI: -4.1%, -1%, p = 0.002). Post-CPOE there were reductions in the proportion of orders with at least one non-intercepted serious error (-12.6%, 95 %CI: -16.4%, -8.8%, p < 0.001). CONCLUSION: The introduction of CPOE was associated with reductions in prescribing errors. There is also evidence that this translated into a reduced risk of harm to patients post-CPOE implementation through the reduction in actual adverse drug events.

Accuracy of best possible medication history documentation by pharmacists at an Australian tertiary referral metropolitan hospital.

AIM: To determine the quality of best possible medication history (BPMH) taking activities undertaken by pharmacists. To identify factors which impact upon erroneous documentation. To assess risks associated with erroneous documentation of BPMH by pharmacists. METHOD: A clinical pharmacist randomly selected patients across a tertiary referral, metropolitan hospital over an 9-day period and documented comparator medication histories (CMHs) using a structured interview. BPMH documented by pharmacists as part of routine care and CMH were compared, and erroneous documentation was classified according to previous definitions in the literature. Erroneous documentation was risk stratified. RESULTS: 99 BPMH and CMH were compared. There were 14 medication omissions which occurred across 10 patients and 14 discrepancies across 12 patients. There was no association identified between erroneous documentation and pharmacist seniority/experience (p=0.25), where BPMH taken (p=0.7), day of week BPMH documented (p=0.45) or time since admission to when BPMH was documented (p=1). Patient age did not impact erroneous documentation rates (p=0.22). There was an association between the number of sources used to confirm a medication history and erroneous documentation incidence (p=0.035). The number of medications increased the rate of documentation error. While 85.19% (n=115) of erroneous documentation were deemed unlikely to cause patient discomfort or clinical deterioration, 1.48% (n=2) had the potential to result in severe discomfort or clinical deterioration. CONCLUSION: Six out of seven BPMH documented by pharmacists as part of usual clinical practice are accurate. Major influences on accuracy include the number of medications and sources used. There is a low possibility that erroneous documentation by pharmacists will cause harm.

Prediction of glycaemic control in young children and adolescents with type 1 diabetes mellitus using mixed-effects logistic regression modelling.

OBJECTIVES: Glycaemic control in children and adolescents with type 1 diabetes mellitus can be challenging, complex and influenced by many factors. This study aimed to identify patient characteristics that were predictive of satisfactory glycaemic control in the paediatric population using a logistic regression mixed-effects (population) modelling approach. METHODS: The data were obtained from 288 patients aged between 1 and 22 years old recorded retrospectively over 3 years (1852 HbA1c observations). HbA1c status was categorised as 'satisfactory' or 'unsatisfactory' glycaemic control, using an a priori cut-off value of HbA1c ≥ 9% (75 mmol/mol), as used routinely by the hospital's endocrine paediatricians. Patients' characteristics were tested as covariates in the model as potential predictors of glycaemic control. RESULTS: There were three patient characteristics identified as having a significant influence on glycaemic control: HbA1c measurement at the beginning of the observation period (Odds Ratio (OR) = 0.30 per 1% HbA1c increase, 95% confidence interval (CI) = 0.20-0.41); Age (OR = 0.88 per year increase, 95% CI = 0.80-0.94), and fractional disease duration (disease duration/age, OR = 0.80 per 0.10 increase, 95% CI = 0.66-0.93) were collectively identified as factors contributing significantly to lower the probability of satisfactory glycaemic control. CONCLUSIONS: The study outcomes may prove useful for identifying paediatric patients at risk of having unsatisfactory glycaemic control, and who could require more extensive monitoring, support, or targeted interventions.