Effects of two commercial electronic prescribing systems on prescribing error rates in hospital in-patients: a before and after study.

BACKGROUND: Considerable investments are being made in commercial electronic prescribing systems (e-prescribing) in many countries. Few studies have measured or evaluated their effectiveness at reducing prescribing error rates, and interactions between system design and errors are not well understood, despite increasing concerns regarding new errors associated with system use. This study evaluated the effectiveness of two commercial e-prescribing systems in reducing prescribing error rates and their propensities for introducing new types of error. METHODS AND RESULTS: We conducted a before and after study involving medication chart audit of 3,291 admissions (1,923 at baseline and 1,368 post e-prescribing system) at two Australian teaching hospitals. In Hospital A, the Cerner Millennium e-prescribing system was implemented on one ward, and three wards, which did not receive the e-prescribing system, acted as controls. In Hospital B, the iSoft MedChart system was implemented on two wards and we compared before and after error rates. Procedural (e.g., unclear and incomplete prescribing orders) and clinical (e.g., wrong dose, wrong drug) errors were identified. Prescribing error rates per admission and per 100 patient days; rates of serious errors (5-point severity scale, those ≥3 were categorised as serious) by hospital and study period; and rates and categories of postintervention "system-related" errors (where system functionality or design contributed to the error) were calculated. Use of an e-prescribing system was associated with a statistically significant reduction in error rates in all three intervention wards (respectively reductions of 66.1% [95% CI 53.9%-78.3%]; 57.5% [33.8%-81.2%]; and 60.5% [48.5%-72.4%]). The use of the system resulted in a decline in errors at Hospital A from 6.25 per admission (95% CI 5.23-7.28) to 2.12 (95% CI 1.71-2.54; p<0.0001) and at Hospital B from 3.62 (95% CI 3.30-3.93) to 1.46 (95% CI 1.20-1.73; p<0.0001). This decrease was driven by a large reduction in unclear, illegal, and incomplete orders. The Hospital A control wards experienced no significant change (respectively -12.8% [95% CI -41.1% to 15.5%]; -11.3% [-40.1% to 17.5%]; -20.1% [-52.2% to 12.4%]). There was limited change in clinical error rates, but serious errors decreased by 44% (0.25 per admission to 0.14; p = 0.0002) across the intervention wards compared to the control wards (17% reduction; 0.30-0.25; p = 0.40). Both hospitals experienced system-related errors (0.73 and 0.51 per admission), which accounted for 35% of postsystem errors in the intervention wards; each system was associated with different types of system-related errors. CONCLUSIONS: Implementation of these commercial e-prescribing systems resulted in statistically significant reductions in prescribing error rates. Reductions in clinical errors were limited in the absence of substantial decision support, but a statistically significant decline in serious errors was observed. System-related errors require close attention as they are frequent, but are potentially remediable by system redesign and user training. Limitations included a lack of control wards at Hospital B and an inability to randomize wards to the intervention.

Flocculation of polymer stabilized nanocrystal suspensions to produce redispersible powders.

Aqueous suspensions of crystalline naproxen nanoparticles, formed by antisolvent precipitation, were flocculated with sodium sulfate, filtered, and dried to form redispersible powders for oral delivery. The particles were stabilized with polyvinylpyrrolidone (PVP K-15) and/or poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) (poloxamer 407). The yield of the drug in the powder was typically 92-99%, and the drug loading was reproducible to within 1-2%. The filtration process increased the drug loading by up to 61% relative to the initial value, as unbound surfactant was removed with the filtrate. Upon redispersion of the dried powder, the average particle size measured by light scattering was comparable to the original value in the aqueous suspension prior to flocculation, and consistent with primary particle sizes observed by scanning electron microscopy (SEM). For 300-nm particles, up to 95% of the drug dissolved in 2 min. The dissolution rate was correlated linearly with the specific surface area calculated from the average particle diameter after redispersion. The redispersion of dried powders was examined as a function of the salt concentration used for flocculation and the surfactant composition and concentration. Flocculation followed by filtration and drying is an efficient and highly reproducible process for the rapid recovery of drug nanoparticles to produce wettable powders with high drug loading and rapid dissolution.

Does computerized provider order entry reduce prescribing errors for hospital inpatients? A systematic review.

Previous reviews have examined evidence of the impact of CPOE on medication errors, but have used highly variable definitions of "error". We attempted to answer a very focused question, namely, what evidence exists that CPOE systems reduce prescribing errors among hospital inpatients? We identified 13 papers (reporting 12 studies) published between 1998 and 2007. Nine demonstrated a significant reduction in prescribing error rates for all or some drug types. Few studies examined changes in error severity, but minor errors were most often reported as decreasing. Several studies reported increases in the rate of duplicate orders and failures to discontinue drugs, often attributed to inappropriate selection from a dropdown menu or to an inability to view all active medication orders concurrently. The evidence-base reporting the effectiveness of CPOE to reduce prescribing errors is not compelling and is limited by modest study sample sizes and designs. Future studies should include larger samples including multiple sites, controlled study designs, and standardized error and severity reporting. The role of decision support in minimizing severe prescribing error rates also requires investigation.