S. Andrew Spooner

Automated Dose-Rounding Recommendations for Pediatric Medications

BACKGROUND: Although pediatric electronic prescribing systems are increasingly being used in pediatric care, many of these systems lack the clinical decision-support infrastructure needed to calculate a safe and effective rounded medication dose. This infrastructure is required to facilitate tailoring of established dosing guidance while maintaining the medications therapeutic intent. OBJECTIVE: The goal of this project was to establish best practices for generating an appropriate medication dose and to create an interoperable rounding knowledge base combining best practices and dose-rounding information. METHODS: We interviewed 19 pediatric health care and pediatric pharmacy experts and conducted a literature review. After using these data to construct initial rounding tolerances, we used a Delphi process to achieve consensus about the rounding tolerance for each commonly prescribed medication. RESULTS: Three categories for medication-rounding philosophy emerged from our literature review: (1) medications for which rounding is used judiciously to retain the intended effect; (2) medications that are rounded with attention to potential unintended effects; and (3) medications that are rarely rounded because of the potential for toxicity. We assigned a small subset of medications to a fourth category—inadequate data—for which there was insufficient information to provide rounding recommendations. For all 102 medications, we were able to arrive at a consensus recommendation for rounding a given calculated dose. CONCLUSIONS: Results of this study provide the pediatric information technology community with a primary set of recommended rounding tolerances for commonly prescribed drugs. The interoperable knowledge base developed here can be integrated with existing and developing electronic prescribing systems, potentially improving prescribing safety and reducing cognitive workload.

Evaluating the accuracy of electronic pediatric drug dosing rules

OBJECTIVE To determine the accuracy of vendor-supplied dosing eRules for pediatric medication orders. Inaccurate or absent dosing rules can lead to high numbers of false alerts or undetected prescribing errors and may potentially compromise safety in this already vulnerable population. MATERIALS AND METHODS 7 months of medication orders and alerts from a large pediatric hospital were analyzed. 30 medications were selected for study across 5 age ranges and 5 dosing parameters. The resulting 750 dosing rules from a commercial system formed the study corpus and were examined for accuracy against a gold standard created from traditional clinical resources. RESULTS Overall accuracy of the rules in the study corpus was 55.1% when the rules were transformed to fit a priori age ranges. Over a pediatric lifetime, the dosing rules were accurate an average of 57.6% of the days. Dosing rules pertaining to the newborn age range were as accurate as other age ranges on average, but exhibited more variability. Daily frequency dosing parameters showed more accuracy than total daily dose, single dose minimum, or single dose maximum. DISCUSSION The accuracy of a vendor-supplied set of dosing eRules is suboptimal when compared with traditional dosing sources, exposing a gap between dosing rules in commercial products and actual prescribing practices by pediatric care providers. More research on vendor-supplied eRules is warranted in order to understand the effects of these products on safe prescribing in children.

Transitioning from a computerized provider order entry and paper documentation system to an electronic health record: Expectations and experiences of hospital staff

OBJECTIVES To examine healthcare workers perceptions, expectations, and experiences regarding how work processes, patient-related safety, and care were affected when a quaternary care center transitioned from one computerized provider order entry (CPOE) system to a full electronic health record (EHR). METHODS The I-SEE survey was administered prior to and 1-year after transition in systems. The construct validity and reliability of the survey was assessed within the current population and also compared to previously published results. Pre- and 1-year post-implementation scale means were compared within and across time periods. RESULTS The majority of respondents were nurses and personnel working in the acute care setting. Because a confirmatory factor analysis indicated a lack of fit of our data to the I-SEE surveys 5-factor structure, we conducted an exploratory factor analysis that resulted in a 7-factor structure which showed better reliability and validity. Mean scores for each factor indicated that attitudes and expectations were mostly positive and score trends over time were positive or neutral. Nurses generally had less positive attitudes about the transition than non-nursing respondents, although the difference diminished after implementation. CONCLUSIONS Findings demonstrate that the majority of responding staff were generally positive about transitioning from CPOE system to a full electronic health record (EHR) and understood the goals of doing so, with overall improved ratings over time. In addition, the I-SEE survey, when modified based on our population, was useful for assessing patient care and safety related expectations and experiences during the transition from one CPOE system to an EHR.

Automated identification of antibiotic overdoses and adverse drug events via analysis of prescribing alerts and medication administration records

Objectives: Electronic trigger detection tools hold promise to reduce Adverse drug event (ADEs) through efficiencies of scale and real-time reporting. We hypothesized that such a tool could automatically detect medication dosing errors as well as manage and evaluate dosing rule modifications. Materials and Methods: We created an order and alert analysis system that identified antibiotic medication orders and evaluated user response to dosing alerts. Orders associated with overridden alerts were examined for evidence of administration and the delivered dose was compared to pharmacy-derived dosing rules to confirm true overdoses. True overdose cases were reviewed for association with known ADEs. Results: Of 55 546 orders reviewed, 539 were true overdose orders, which lead to 1965 known overdose administrations. Documentation of loose stools and diarrhea was significantly increased following drug administration in the overdose group. Dosing rule thresholds were altered to reflect clinically accurate dosing. These rule changes decreased overall alert burden and improved the salience of alerts. Discussion: Electronic algorithm-based detection systems can identify antibiotic overdoses that are clinically relevant and are associated with known ADEs. The system also serves as a platform for evaluating the effects of modifying electronic dosing rules. These modifications lead to decreased alert burden and improvements in response to decision support alerts. Conclusion: The success of this test case suggests that gains are possible in reducing medication errors and improving patient safety with automated algorithm-based detection systems. Follow-up studies will determine if the positive effects of the system persist and if these changes lead to improved safety outcomes.

Assessing the reliability of an automated dose-rounding algorithm

OBJECTIVE Pediatric dose rounding is a unique and complex process whose complexity is rarely supported by e-prescribing systems, though amenable to automation and deployment from a central service provider. The goal of this project was to validate an automated dose-rounding algorithm for pediatric dose rounding. METHODS We developed a dose-rounding algorithm, STEPSTools, based on expert consensus about the rounding process and knowledge about the therapeutic/toxic window for each medication. We then used a 60% subsample of electronically-generated prescriptions from one academic medical center to further refine the web services. Once all issues were resolved, we used the remaining 40% of the prescriptions as a test sample and assessed the degree of concordance between automatically calculated optimal doses and the doses in the test sample. Cases with discrepant doses were compiled in a survey and assessed by pediatricians from two academic centers. The response rate for the survey was 25%. RESULTS Seventy-nine test cases were tested for concordance. For 20 cases, STEPSTools was unable to provide a recommended dose. The dose recommendation provided by STEPSTools was identical to that of the test prescription for 31 cases. For 14 out of the 24 discrepant cases included in the survey, respondents significantly preferred STEPSTools recommendations (p<0.05, binomial test). Overall, when combined with the data from all test cases, STEPSTools either matched or exceeded the performance of the test cases in 45/59 (76%) of the cases. The majority of other cases were challenged by the need to provide an extremely small dose. We estimated that with the addition of two dose-selection rules, STEPSTools would achieve an overall performance of 82% or higher. CONCLUSIONS Results of this pilot study suggest that automated dose rounding is a feasible mechanism for providing guidance to e-prescribing systems. These results also demonstrate the need for validating decision-support systems to support targeted and iterative improvement in performance.

Pediatric Electronic Health Records and Research

Pediatric providers use electronic health record systems to review patient information, to document care, to order clinical interventions, and to perform related administrative tasks. All of these activities create data that might be useful in research, although research is seldom the objective of EHR-related data entry. Providers may use other information systems (e.g., specialized systems for analyzing electrocardiograms), but the EHR is the central application for clinical and administrative clinical activities. While there are a few EHR systems designed specifically for care of pediatric patients, most pediatric providers adopt general-purpose EHRs that must be customized for specialized pediatric environments. In this chapter we outline the special functional requirements of EHRs (e.g., growth monitoring, medication dosing, and immunization management), the relative difficulty of meeting these requirements with EHRs that are currently available in the marketplace, and current adoption trends. We discuss workflows that present special challenges to EHR implementation. We discuss the typical workflow phenomena that affect the use of data for research and other secondary uses. We also discuss special aspects of terminology systems employed by EHRs that have implications for pediatric usability. Lastly, we address special issues in the use of EHR data for the extraction of care quality measures.

Protecting Privacy in the Child’s Electronic Health Record

With the increasing availability of electronic health records, translational researchers frequently wish to extract information from or add information to these records to support various research projects. It is important that investigators be familiar with laws and regulations that protect the privacy of patients and restrict who can view or extract information from their EHRs. Laws and professional standards demand that all individually identifiable health information be secured at a high level and handled as private, sensitive information. Some information (mental health, reproductive health, abuse) is generally regarded as more sensitive than others in the health care of a patient at any age. In a situation where minors are involved, these security and privacy policies become more complicated because of possible conflicts between the interests of the child and the interests of parents or guardians. Situations specific to pediatric clinical practice and research increase the difficulty of implementing these policies: adolescent care, adoption, fetal care, foster care, and genetic disease. Security policies for access to systems intended to be used by patients (personal health records and patient portals) are complex. They can become even more challenging when the child has participated in clinical research and unexpected clinically relevant results are obtained.

Interfaces and Data Transmission Standards

Electronic health records in pediatric care must connect to other systems to integrate information and to communicate to providers in other systems. In order to perform this data transfer, there must be formats for the construction of messages, and standard terminologies that communicate the clinical concepts. Messaging standards are usually in the form of delimited character strings that follow the HL7 version 2.X standard. We will review the state of the art of HL7 version 2 messaging types and describe the best known example of this kind of messaging in the CDC Implementation Guide for Immunization Messaging. HL7 version 3, built on XML, has the potential for richer semantics, but is not yet widely used. We will use the Continuity of Care Document as a pediatric example of the use of this standard in real systems. Terminology systems, both open and proprietary, are used to encode clinical and administrative concepts in pediatrics. We will review terminology systems in current use and their pediatric-specific limitations.