Electronic Health Record-Embedded Decision Support Platform for Morphine Precision Dosing in Neonates

Abstract

Morphine is the opioid most commonly used for neonatal pain management. In intravenous form, it is administered as continuous infusions and intermittent injections, mostly based on empirically established protocols. Inadequate pain control in neonates can cause long-term adverse consequences; however, providing appropriate individualized morphine dosing is particularly challenging due to the interplay of rapid natural physiological changes and multiple life-sustaining procedures in patients who cannot describe their symptoms. At most institutions, morphine dosing in neonates is largely carried out as an iterative process using a wide range of starting doses and then titrating to effect based on clinical response and side effects using pain scores and levels of sedation. Our background data show that neonates exhibit large variability in morphine clearance resulting in a wide range of exposures, which are poorly predicted by dose alone. Here, we describe the development and implementation of an electronic health record-integrated, model-informed decision support platform for the precision dosing of morphine in the management of neonatal pain. The platform supports pharmacokinetic model-informed dosing guidance and has functionality to incorporate real-time drug concentration information. The feedback is inserted directly into prescribers' workflows so that they can make data-informed decisions. The expected outcomes are better clinical efficacy and safety with fewer side effects in the neonatal population.

Conflict of interest statement

Conflict of Interest

AAV, FM, DB, TJD, DEC, SK, TD, KDRS, JZ, JCE, TM, and KD declared no competing interests for this work. NP is president of Medimatics a company that provides consulting services on medical information systems located in Maastricht, the Netherlands. EK receives royalties for the licensing of acute kidney injury algorithms to VigiLanz Corporation. These algorithms are unrelated to the work presented here. PS and RK are employees of Pomiet, LLC a healthcare consulting company specializing in user-centered lean software development located in Cincinnati, OH. As an Associate Editor for Clinical Pharmacology & Therapeutics, Alexander A. Vinks was not involved in the review or decision process for this paper.

© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics.

Figures

Figure 1.

NeoRelief software platform prototype. Depicted are the dosing table that can be populated with morphine doses by continuous infusion and intermittent bolus administration after which the model-predicted concentration time profile is generated (orange dotted line) using the calculation (F10/calc) button. Similar model predicted profiles for the metabolites can be generated by checking the M3G and M6G boxes. Once concentration results become available and by clicking the Bayesian feedback box an individual concentration time profile is generated after selecting the calculation button (blue solid line); with measured morphine concentrations are represented by the open circles. The dotted lines represent the potential target range of 10 to 30 ng/mL (mean 20 ng/mL in red) as suggested in the literature. Target plasma concentrations of morphine, which are needed to determine the infusion rate, have not been firmly established in the pediatric population, although concentrations around 20 ng/ml have been suggested for postoperative neonates and infants. (11, 19, 25)

Figure 2.

Summary of internal validation of the morphine population models. Panels A, present the model predicted morphine clearance estimates (in L/h) as a function of gestational age from 30 to 40 weeks; Panel B, present the model predicted morphine clearance estimates (in L/h) as a function of age from zero to 3 years of age; Panel C, present the model predicted morphine clearance estimates (in mL/min) for each of the nine case examples: a 32 week preterm neonate (PT1D), a 32 week preterm neonates (PT2W), a 38 week term neonate (FT1D), a 40 week term neonate (FT2W), a 3 month old infant born term (IN3M), a 6 month old infant (IN6M), and a one year old infant (IN1Y), a 2 year old infant (IN2Y), and a 3 year old infant (IN3Y). Patient weight was derived using gestational age (Panel A: data from https://www.momjunction.com/articles/baby-weight-gain-and-weight-chart_00362524/#gref) or the post-natal age (Panel B: standard growth curve).

Figure 2.

Summary of internal validation of the morphine population models. Panels A, present the model predicted morphine clearance estimates (in L/h) as a function of gestational age from 30 to 40 weeks; Panel B, present the model predicted morphine clearance estimates (in L/h) as a function of age from zero to 3 years of age; Panel C, present the model predicted morphine clearance estimates (in mL/min) for each of the nine case examples: a 32 week preterm neonate (PT1D), a 32 week preterm neonates (PT2W), a 38 week term neonate (FT1D), a 40 week term neonate (FT2W), a 3 month old infant born term (IN3M), a 6 month old infant (IN6M), and a one year old infant (IN1Y), a 2 year old infant (IN2Y), and a 3 year old infant (IN3Y). Patient weight was derived using gestational age (Panel A: data from https://www.momjunction.com/articles/baby-weight-gain-and-weight-chart_00362524/#gref) or the post-natal age (Panel B: standard growth curve).

Figure 3.

Morphine clearance estimates generated with the NeoRelief platform versus results from the NEOPAIN study. Closed circles represent morphine clearance estimates in newborns treated in NICU at Cincinnati Children’s analyzed using NeoRelief and expressed as percentage of the mature morphine clearance (84.2 L/l per 70 kg)(3). The solid line and shaded areas represent the median and 5–95 percentiles, respectively of morphine clearance values simulated using the Anand model. The figure insert shows the original clearance estimate data of the NEOPAIN study with morphine clearance estimates (red symbols) for our neonatal cohort generated with NONMEM(2) and verified with the NeoRelief platform.

Figure 4.

Screen shots of the NeoRelief application as displayed in the electronic health record. Panel A; shows the default landing page (and activated via the “details tab” in the left-hand corner). This page graphically presents NPASS, morphine dose (infusion and PRN doses), heart rate, and breathing frequency. NPASS scores and dosing events are also summarized chronologically in table format to be viewed over different selectable time frames. Panel B; a second screen (activated via the “concentration tab”) summarizes the NPASS data, the doses administered (Infusion “drip” and “bolus” doses), and the model-based translation of the dosing regimen into a morphine concentration time profile (morphine plasma concentration in μg/L). Dosing events (date, time, type of dose, and dose unit) are also summarized in Table format. The symbol size and colors (green, yellow, orange, and red) represent the severity (red, orange, yellow, green) represent the severity of the NPASS: score 0–3 (green); 4–5 (shades of orange); 6–7 (shades of red). As all patient info, doses and time(s) of dosing, and concentration results in the EHR embedded platform are automatically being pulled from the EHR, the data entry panels of the prototype as shown in Figure 1 have disappeared.

Figure 4.

Screen shots of the NeoRelief application as displayed in the electronic health record. Panel A; shows the default landing page (and activated via the “details tab” in the left-hand corner). This page graphically presents NPASS, morphine dose (infusion and PRN doses), heart rate, and breathing frequency. NPASS scores and dosing events are also summarized chronologically in table format to be viewed over different selectable time frames. Panel B; a second screen (activated via the “concentration tab”) summarizes the NPASS data, the doses administered (Infusion “drip” and “bolus” doses), and the model-based translation of the dosing regimen into a morphine concentration time profile (morphine plasma concentration in μg/L). Dosing events (date, time, type of dose, and dose unit) are also summarized in Table format. The symbol size and colors (green, yellow, orange, and red) represent the severity (red, orange, yellow, green) represent the severity of the NPASS: score 0–3 (green); 4–5 (shades of orange); 6–7 (shades of red). As all patient info, doses and time(s) of dosing, and concentration results in the EHR embedded platform are automatically being pulled from the EHR, the data entry panels of the prototype as shown in Figure 1 have disappeared.