Parenteral Protein Decision Support System Improves Protein Delivery in Preterm Infants: A Randomized Clinical Trial.

BACKGROUND: Management of neonatal parenteral protein intake for preterm infants is challenging and requires daily modifications of the dose to account for the infant's postnatal age, birth weight, current weight, and the volume and protein concentration of concurrent enteral nutrition. The objective of this study was to create and evaluate the Parenteral Protein Calculator (PPC), a clinical decision support system to improve the accuracy of protein intake for preterm infants who require parenteral nutrition (PN). MATERIALS AND METHODS: We integrated the PPC into the computerized provider order entry system and tested it in a randomized controlled trial (routine or PPC). Infants were eligible if they were ≤3 days old, had a birth weight ≤1500 g, and had no inborn error of metabolism. The primary outcome was the appropriate total protein intake, defined as target protein dose ±0.5 g/kg. RESULTS: We randomly allocated 42 infants for 221 PN days in the control group and 211 in the PPC group. Total protein intake in the PPC group was more accurate as compared with the control group (appropriate protein dosing: odds ratio = 5.8; 95% CI, 2.7-12.4). Absolute deviation from protein target was 0.41 g/kg (0.24-0.58) lower in the PPC group. CONCLUSION: The PPC improved appropriate protein dosing for premature infants receiving PN. Further studies are needed to test whether clinical decision support systems will reduce uremia and improve growth and to replicate similar findings in the cases of other PN nutrients.

Reducing Inappropriate Testing for the Evaluation of Diarrhea Among Hospitalized Patients.

BACKGROUND: Diarrhea is one of the most common illnesses in the United States. Evaluation frequently does not follow established guidelines. The objective of this study was to evaluate the effectiveness of a computerized physician order entry-based test guidance algorithm with regard to the clinical, financial, and operational impacts. METHODS: Our population was patients with diarrheal illness at a tertiary academic medical center. The intervention was a computerized physician order entry-based test guidance algorithm that restricted the use of stool cultures and ova and parasites testing of diarrhea in the adult inpatient location vs nonintervention sites, which were the emergency department, pediatric inpatient and adult and pediatric outpatient locations. We measured stool culture, ova and parasites, and Clostridium difficile testing rates from July 1, 2012 to January 31, 2016. Additionally, we calculated advisor usage, consults generated, accuracy of information, and cost savings. RESULTS: There was a significant decrease in stool culture and ova and parasites testing rates at the adult inpatient (P = .001 for both), pediatric (P < .001 for both), and adult emergency department (P < .001; P = .009) locations. The decrease at the intervention site was immediate, whereas the other locations showed a delayed but sustained decrease that suggests a collateral impact. A significant increase in the rate of stool culture and ova and parasites testing was observed in the outpatient setting (P = .02 and P = .001). We estimate that $21,931 was saved annually. CONCLUSIONS: A point-of-order test restriction algorithm for hospitalized adults with diarrhea reduced stool testing. Similar programs should be considered at other institutions and for the evaluation of other conditions.

Clinical decision support for atypical orders: detection and warning of atypical medication orders submitted to a computerized provider order entry system.

The specificity of medication-related alerts must be improved to overcome the pernicious effects of alert fatigue. A systematic comparison of new drug orders to historical orders could improve alert specificity and relevance. Using historical order data from a computerized provider order entry system, we alerted physicians to atypical orders during the prescribing of five medications: calcium, clopidogrel, heparin, magnesium, and potassium. The percentage of atypical orders placed for these five medications decreased during the 92 days the alerts were active when compared to the same period in the previous year (from 0.81% to 0.53%; p=0.015). Some atypical orders were appropriate. Fifty of the 68 atypical order alerts were over-ridden (74%). However, the over-ride rate is misleading because 28 of the atypical medication orders (41%) were changed. Atypical order alerts were relatively few, identified problems with frequencies as well as doses, and had a higher specificity than dose check alerts.