Closed-Loop Medication Management with an Electronic Health Record System in U.S. and Finnish Hospitals.

Many medication errors in the hospital setting are due to manual, error-prone processes in the medication management system. Closed-loop Electronic Medication Management Systems (EMMSs) use technology to prevent medication errors by replacing manual steps with automated, electronic ones. As Finnish Helsinki University Hospital (HUS) establishes its first closed-loop EMMS with the new Epic-based Electronic Health Record system (APOTTI), it is helpful to consider the history of a more mature system: that of the United States. The U.S. approach evolved over time under unique policy, economic, and legal circumstances. Closed-loop EMMSs have arrived in many U.S. hospital locations, with myriad market-by-market manifestations typical of the U.S. healthcare system. This review describes and compares U.S. and Finnish hospitals' EMMS approaches and their impact on medication workflows and safety. Specifically, commonalities and nuanced differences in closed-loop EMMSs are explored from the perspectives of the care/nursing unit and hospital pharmacy operations perspectives. As the technologies are now fully implemented and destined for evolution in both countries, perhaps closed-loop EMMSs can be a topic of continued collaboration between the two countries. This review can also be used for benchmarking in other countries developing closed-loop EMMSs.

Claims-based pharmacy markers for comprehensive medication management program case identification: Validation against concurrent and prospective healthcare costs and utilization.

BACKGROUND: Three claims-based pharmacy markers (complex, costly and risky medications) were developed to help automatically identify patients for comprehensive medication management. OBJECTIVE: To evaluate the association between newly-developed markers and healthcare outcomes. METHODS: This was a two-year retrospective cohort study using PharMetrics Plus patient-level administrative claims in 2014 and 2015. We included all claims from 1,541,873 individuals with: (1) 24-month medical and pharmacy enrollment in 2014 and 2015, (2) aged between 18 and 63 in 2014, and (3) known gender. Independent/control variables came from 2014 while outcomes came from 2014 (concurrent analysis) and 2015 (prospective analysis). Three pharmacy markers, separately or together, were added to four base models to predict concurrent and prospective healthcare costs (total, medical, and pharmacy) and utilization (having any hospitalization, having any emergency department visit, and having any readmission). We applied linear regression for costs while logistic regression for utilization. Measures of model performances and coefficients were derived from a 5-fold cross-validation repeated 20 times. RESULTS: Individuals with 1+ complex, risky or costly medication markers had higher comorbidity, healthcare costs and utilization than their counterparts. Nine binary risky category markers performed the best among the three types of risky medication markers; the Medication Complexity Score and three-level complex category both outperformed a simpler complex medication indicator. Adding three novel pharmacy markers separately or together into the base models provided the greatest improvement in explaining pharmacy costs, compared with medical (non-medication) costs. These pharmacy markers also added value in explaining healthcare utilization among the simple base models. CONCLUSIONS: Three claims-based pharmacy indicators had positive associations with healthcare outcomes and added value in predicting them. This initial study suggested that these novel markers can be used by pharmacy case management programs to help identify potential high-risk patients most likely to benefit from clinical pharmacist review and other interventions.

Comparing and validating medication complexity from insurance claims against electronic health records.

BACKGROUND: Patient effort to comply with complex medication instructions is known to be related to nonadherence and subsequent medical complications or health care costs. A widely used Medication Regimen Complexity Index (MRCI) has been used with electronic health records (EHRs) to identify patients who could benefit from pharmacist intervention. A similar claims-derived measure may be better suited for clinical decision support, since claims offer a more complete view of patient care and health utilization. OBJECTIVE: To define and validate a novel insurance claims-based medication complexity score (MCS) patterned after the widely used MRCI, derived from EHRs. METHODS: Insurance claims and EHR data were provided by HealthPartners (N = 54,988) (Bloomington, Minnesota) and The Johns Hopkins Health System (N = 28,589) (Baltimore, Maryland) for years 2013 and 2017, respectively. Yearly measures of medication complexity were developed for each patient and evaluated with one another using rank correlation within different clinical subgroupings. Indicators for the presence of individually complex prescriptions were also developed and assessed using exact agreement. Complexity measures were then correlated with select covariates to further validate the concordance between MCS and MRCI with respect to clinical metrics. These included demographic, comorbidity, and health care utilization markers. Prescribed medications in each system's EHR were coded using the previously validated MRCI weighting rules. Insurance claims for retail pharmacy medications were coded using our novel MCS, which closely followed MRCI scoring rules. RESULTS: EHR-based MRCI and claims-based MCS were significantly correlated with one another for most clinical subgroupings. Likewise, both measures were correlated with several covariates, including count of active medications and chronic conditions. The MCS was, in most cases, more associated with key health covariates than was MRCI, although both were consistently significant. We found that the highest correlation between MCS and MRCI is obtained with patients who have similar counts of pharmacy records between EHRs and claims (HealthPartners: P = 0.796; Johns Hopkins Health System: P = 0.779). CONCLUSIONS: The findings suggest good correspondence between MCS and MRCI and that claims data represent a useful resource for assessing medication complexity. Claims data also have major practical advantages, such as interoperability across health care systems, although they lack the detailed clinical context of EHRs. DISCLOSURES: The Johns Hopkins University holds the copyright to the Adjusted Clinical Groups (ACG) system and receives royalties from the global distribution of the ACG system. This revenue supports a portion of the authors' salary. No additional or external funding supported this work. The authors have no conflict of interest to disclose.

Levocarnitine supplementation for management of hypertriglyceridemia in patients receiving parenteral nutrition.

BACKGROUND: Levocarnitine deficiency has been observed in patients receiving parenteral nutrition (PN) and can cause or worsen hypertriglyceridemia. The objective was to characterize use of levocarnitine supplementation in PN and evaluate its effect on triglyceride levels in hospitalized adults. METHODS: This retrospective, single-center study included patients with triglyceride levels ≥175 mg/dl while receiving PN who had a subsequent reduction in lipid injectable emulsion dose. A piecewise linear regression was used to evaluate trends in triglyceride levels before and after the intervention, defined as initiation of levocarnitine in PN for the levocarnitine group, or reduction in lipid injectable emulsion alone for the control group. RESULTS: Two hundred sixty-one patients who received PN had an elevated triglyceride level and lipid injectable emulsion dose reduction, of which 97 (37.2%) received levocarnitine in PN. The median (IQR) levocarnitine dose added to PN was 8.0 (5.7-9.9) mg/kg. Triglyceride levels at 30 days post-intervention did not differ between groups (125 vs 176 mg/dl, P = .345). The addition of levocarnitine to PN was associated with a significantly greater rate of reduction in triglyceride levels pre-intervention to post-intervention compared with a reduction in lipid injectable emulsion alone (-11 vs -3 mg/dl per day; 95% CI, -15 to -2; P = .012). CONCLUSION: In hospitalized adults with hypertriglyceridemia who had a lipid injectable emulsion dose reduction, the addition of levocarnitine in PN was not associated with a difference in triglyceride levels at 30 days; however, a greater rate of improvement in pre-intervention to post-intervention triglyceride levels was observed.

Comparison of Clinical Scoring Tools to Predict Heparin-Induced Thrombocytopenia in Cardiac Surgery.

The 4Ts and HIT-Expert Probability (HEP) scoring tools for heparin-induced thrombocytopenia (HIT) have not been validated in cardiac surgery patients, and the reported sensitivity and specificity of the Post-Cardiopulmonary Bypass (CPB) scoring tool vary widely in the 2 available analyses. It remains unclear which of the available scoring tools most accurately predicts HIT in this population. Forty-nine HIT-positive patients who underwent on-pump cardiac surgery within a 6-year period were loosely matched to 98 HIT-negative patients in a 1:2 case-control design. The 4Ts, HEP, and CPB scores were calculated for each patient. Sensitivity and specificity of each tool were calculated using standard cut-offs. The Youden method was utilized to determine optimal cut-offs within receiver operating characteristic (ROC) curves of each score, after which sensitivities and specificities were recalculated. Using standard cut-offs, the sensitivities for the CPB, HEP, and 4Ts scores were 100%, 93.9%, and 69.4%, respectively. Specificities were 51%, 49%, and 71.4%, respectively. The AUC of the scoring tool ROC curves were 0.961 for the CPB score, 0.773 for the HEP score, and 0.805 for the 4Ts score. Using the Youden method-derived optimal cut-off of  ≥3 points on the CPB score, sensitivity remained 100% with improved specificity to 88.9%. The CPB score is the preferred HIT clinical scoring tool in adult cardiac surgery patients, whereas the 4Ts score performed less effectively. A cut-off of ≥ 3 points on the CPB score could increase specificity while preserving high sensitivity, which should be validated in a prospective evaluation.

Development of measurable criteria to identify and prioritize patients for inclusion in comprehensive medication management programs within primary care settings.

BACKGROUND: Pharmacists optimize medication use and ensure the safe and effective delivery of pharmacotherapy to patients using comprehensive medication management (CMM). Identifying and prioritizing individual patients who will most likely benefit from CMM can be challenging. Health systems have far more candidates for CMM than there are clinical pharmacists to provide this service. Furthermore, current evidence lacks widely accepted standards or automated mechanisms for identifying patients who would likely benefit from a pharmacist consultation. Existing tools to prioritize patients for pharmacist review often require manual chart review by a pharmacist or other clinicians or data collection by patient survey. OBJECTIVES: To (1) create new medication risk markers for identifying and prioritizing patients within a population and (2) identify patients who met these new markers, assess their clinical characteristics, and compare them with criteria that are widely used for medication therapy management (MTM). METHODS: Along with published literature, a panel of subject matter experts informed the development of 3 medication risk markers. To assess the prevalence of markers developed, we used Multum, a medication database, for medication-level characteristics, and for patient-level characteristics, we used QuintilesIMS, an administrative claims database derived from health plans across the United States, with data for 1,541,873 eligible individuals from 2014-2015. We compared the health care costs, utilization, and medication gap among patients identified through MTM criteria (both broad and narrow, as these are provided as ranges) and our new medication management score markers. RESULTS: We developed 3 claims-derivable markers: (1) instances when a patient filled a medication with high complexity that could affect adherence, (2) instances where a patient filled a medication defined as costly within a therapeutic category that could affect access, and (3) instances when a patient filled a medication defined as risky that could increase incidence of adverse drug events. In the QuintilesIMS database, individuals with 2 new medication risk markers plus at least 3 conditions and more than $3,017 in medication costs when compared with individuals meeting narrow MTM eligibility criteria (≥ 8 medications, ≥ 3 conditions, and > $3,017 medication costs) had increased costs ($36,000 vs $26,100 total; $24,800 vs 21,400 medical; $11,300 vs $4,800 pharmacy); acute care utilization (0.328 vs 0.256 inpatient admissions and 0.627 vs 0.579 emergency department visits); and 1 or more gaps in medication adherence(41.5% vs 34.7%). CONCLUSIONS: We identified novel markers of medication use risk that can be determined using insurance claims and can be useful to identify patients for CMM programs and prioritize patients who would benefit from clinical pharmacist intervention. These markers were associated with higher costs, acute care utilization, and gaps in medication use compared with the overall population and within certain subgroups. Providing CMM to these patients may improve health system performance in relevant quality measures. Evaluation of CMM services delivered by a pharmacist using these markers requires further investigation. DISCLOSURES: No outside funding supported this study. All authors are Johns Hopkins employees. The Johns Hopkins University receives royalties for nonacademic use of software based on the Johns Hopkins Adjusted Clinical Group (ACG) methodology. Chang, Kitchen, Weiner, and Kharrazi receive a portion of their salary support from this revenue. The authors have no conflicts of interests relevant to this study.

Is There Any Research Evidence Beyond Surveys and Opinion Polls on Automatic Substitution of Biological Medicines? A Systematic Review.

BACKGROUND: Biosimilars are expected to decrease growing health care expenditures. Given that uptake of biosimilars has been modest, automatic substitution has been suggested to increase their use, but the practice is not yet allowed or implemented in many jurisdictions. METHODS: A systematic review was performed by searching databases Scopus, Medline (Ovid), CINAHL, and Web of Science. Peer-reviewed, original studies written in English and published during the period January 1, 2006 to April 24, 2021 reporting any interventions, pilots or any other studies including experiences or perceptions of any relevant stakeholders on automatic substitution of biologics were included without limitation by setting or geography. The quality of the included studies were evaluated by pre-determined criteria. RESULTS: Altogether, 27 studies fulfilled the inclusion criteria, of which 23 were surveys, and four semi-structured interviews reporting mainly stakeholders' perceptions on automatic substitution. Most of the studies (56%, 15/27) were from Europe. Studies were conducted among prescribers (n = 12), pharmacists (n = 5), patients (n = 4), payers (n = 1), and mixed stakeholders (n = 5). The primary objective of the majority (81%, 22/27) of the studies was to investigate some other biosimilar topic than automatic substitution. The reported perceptions of substitution were mainly negative. Studies evaluating risks, safety or effectiveness, or reporting real-life experiences of biologic substitution were lacking except one intervention and two prospective risk management studies. The overall quality of the studies was low to moderate, and the results were not generalizable due to convenience sampling not representing the populations of interest, and low response rates. CONCLUSIONS: The current research evidence on the automatic substitution of biologics is scarce and of low to moderate quality, reflecting low stakeholder knowledge and their cautious attitude towards biosimilars. The safe and efficient implementation of automatic substitution requires well-designed practices, pilot studies, and evolving legislation.

Budgeting in the post-COVID era: Be in the room where it happens.

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Practical utility of mixed methods research in pharmacy practice.

PURPOSE: Our aim was to review key methodological concepts and provide a practical guide to employing mixed methods research to enhance pharmacy practice research. SUMMARY: Mixed methods research provides multiple organized analytic perspectives to thoroughly investigate complex social and scientific problems in a methodologically rigorous manner. This research design incorporates collection and analysis of both qualitative and quantitative data components to create a thorough understanding of a complex question. The 5 most commonly identified reasons for conducting mixed methods research include triangulation, complementarity, development, initiation, and expansion of results. For research questions that benefit from mixed methods research, we review how to structure the study, including timing, sequencing, and prioritization of methods. Illustrative examples from the literature highlight the utility of this methodology for clinical and operational pharmacy research questions. CONCLUSION: Mixed methods designs can enhance pharmacy research inquiry, provide a means to understand complicated issues, and uncover optimal interventions.

The Role of Oxytocin in Primary Cesarean Birth Among Low-Risk Women.

INTRODUCTION: To examine whether there is a threshold of oxytocin exposure at which the risk for primary cesarean increases among women who are nulliparous with a term, singleton, vertex fetus (NTSV) and how oxytocin interacts with other risk factors to contribute to this outcome. METHODS: This was a secondary analysis of the Consortium on Safe Labor data set that used a retrospective cohort study design. Women who met the criteria for NTSV who were not admitted for a prelabor cesarean and for whom oxytocin data were available, were included in the sample. Robust logistic regression was used to examine the association of oxytocin exposure with primary cesarean birth, while controlling for demographic and clinical risk factors and clustering by provider. RESULTS: The sample comprised 17,331 women who were exposed to oxytocin during labor. The women were predominantly white non-Hispanic (59.2%) with an average (SD) gestational age of 39.4 (1.1) weeks and an 18.5% primary cesarean rate. Exposure to greater than 11,400-milliunits (mU) of oxytocin resulted in 1.6 times increased odds of primary cesarean birth compared with less than 11,400 mU (95% CI 1.01-2.6). DISCUSSION: Exposure to greater than 11,400 mU of oxytocin in labor was associated with an increased odds of primary cesarean birth in NTSV women.

Assessment of Availability, Clinical Testing, and US Food and Drug Administration Review of Biosimilar Biologic Products.

Importance: Biosimilar biologic products were authorized in 2010, after the US Congress established an expedited pathway for approval of clinically similar versions of approved biologic products. Unlike for most small-molecule generic drugs, approval requirements for a biosimilar included animal studies and a comparative efficacy clinical trial. Objective: To analyze the evidence required to support a biosimilarity license application, examine the US Food and Drug Administration (FDA) evaluation process, and estimate the costs of the key clinical trial evidence. Design: This study evaluated all biosimilar biologic products approved from January 2010 through October 2019, using the publicly available FDA review documents, disclosures from ClinicalTrials.gov, and the published peer-reviewed literature. The costs of efficacy clinical trials were estimated using licensed proprietary software. Main Outcomes and Measures: The following elements of each approved biosimilar were evaluated: the extent of human clinical testing to establish that the biosimilar had no clinically meaningful differences with the reference product, results of comparative animal studies, and FDA-cited application deficiencies. The cited deficiencies included the following categories: (1) facility inspection, (2) manufacturing or product quality, (3) animal studies, (4) laboratory analytical studies, (5) phase 1 and/or immunogenicity studies, and (6) phase 3 comparative efficacy trials. Results: As of October 2019, the FDA had approved 23 biosimilar biologics for 9 reference products. The 29 clinical trials that established that the efficacy of the biosimilar products was comparable to that of the reference products enrolled a median (interquartile range [IQR]) of 504 (258-612) patients, had a median (IQR) estimated cost of $20.8 ($13.8-$35.3) million, and had a median (IQR) treatment duration of 52 (28-68) weeks. Substantial deficiencies temporarily halted the review of 9 applications, and the most frequent deficits were failed facilities inspections (n = 5) and manufacturing process quality problems (n = 6). The approved biosimilar submissions included 51 animal studies on species that included mice, rats, rabbits, dogs, and cynomolgus monkeys. Negative outcomes in 2 animal studies were attributed to differences between human and test species. The FDA generally met the standard 12-month review deadlines or stopped the review clock when serious deficiencies were identified. Conclusions and Relevance: This study found that most comparative efficacy trials supporting the FDA approval of biosimilars appeared to be as rigorous as and often larger, longer, and more costly than pivotal trials for new molecular entities. Further research is needed into whether less costly comparative efficacy trials could provide adequate evidence of biosimilarity and whether animal studies contribute useful scientific evidence.

Integrating E-Prescribing and Pharmacy Claims Data for Predictive Modeling: Comparing Costs and Utilization of Health Plan Members Who Fill Their Initial Medications with Those Who Do Not.

BACKGROUND: Nonfilling of prescribed medications is a worldwide problem of serious concern. Studies of health care costs and utilization associated with medication nonadherence frequently rely on claims data and usually focus on patients with specific conditions. Past studies also have little agreement on whether higher medication costs associated with higher adherence can reduce downstream health care consumption. OBJECTIVES: To (a) compare the characteristics between people with and without complete medication initiations from a general population and (b) quantify the effect of medication initiation on health care utilization and expenditures with propensity score weighting. METHODS: We conducted a retrospective cohort study using 2012 and 2013 electronic health records (EHR) and insurance claims data from an integrated health care delivery network. We included 43,097 eligible primary care patients in the study. Annual medication fill rates of initial prescriptions in 2012 were defined as the number of filled prescriptions from claims divided by the number of e-prescriptions from EHRs, while excluding all refills. A claim was considered filled if (a) EHR and claims records were from the same drug class; (b) claims occurred between the date of a current EHR order and that of the next EHR order of the same class; and (c) the maximum fill rate was 100%. The 6 annual outcomes included total costs, medical costs, pharmacy costs, being a high-cost "outlier" (in top 5%), having 1 or more hospitalizations, and having 1 or more emergency department (ED) visits. Individuals were classified as either having completed all medication initiations (100% annual filling rate for initiations) or not. We used propensity score weighting to control for baseline differences between complete and incomplete initial fillers. We adopted linear and logistic regressions to model costs and binary utilization indicators for the same year (concurrently) and next year (prospectively). RESULTS: Approximately 42% of the study sample had complete medication initiations (100% filling rate), while the remaining 58% had incomplete initiations. Individuals who fully filled initial prescriptions had lower comorbidity burden and consumed fewer health care resources. After applying propensity score weighting and controlling for variables such as the number of prescription orders, patients with complete medication initiations had lower overall and medical costs, concurrently and prospectively (e.g., $751 and $252 less for annual total costs). Complete medication initiation fillers were also less likely to have concurrent health care utilization (OR = 0.78, 95% CI = 0.68-0.90 for hospitalization; OR = 0.77, 95% CI = 0.72-0.82 for ED admissions) but no difference in prospective utilization other than for ED visits (OR = 0.93, 95% CI = 0.87-0.99). CONCLUSIONS: Identifying the subpopulation of patients with incomplete medication initiations (i.e., filling less than 100% of initial prescriptions) is a pragmatic approach for population health management programs to align resources and potentially contain cost and utilization. DISCLOSURES: No outside funding supported this study. This study applied the Adjusted Clinical Group (ACG) case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of this study, the goal of the study was not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. Chang, Kharrazi, and Weiner receive a portion of their salary support from this revenue. Chang is also a part-time consultant for Monument Analytics, a health care consultancy whose clients include the life sciences industry, as well as plaintiffs in opioid litigation. Alexander is past Chair of FDA's Peripheral and Central Nervous System Advisory Committee; has served as a paid advisor to IQVIA; is a co-founding Principal and equity holder in Monument Analytics; and is a member of OptumRx's National P&T Committee. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The other authors have nothing to disclose.

Assessment of impact of daily huddles and visual displays on medication delivery timeliness in a large academic medical center.

PURPOSE: To evaluate the impact of pharmacy team huddles and near real-time performance dashboards on the punctuality of medication delivery departures from the adult inpatient pharmacy of a multihospital medical center. METHODS: Baseline delivery punctuality was established during a 2-week unannounced preintervention period, followed by the implementation of daily huddles focused on delivery timeliness along with visual displays of delivery performance metrics. The 5- to 15-minute huddles included pharmacy technicians, pharmacists, and managers. Printed visual displays that tracked hour-by-hour timeliness over the prior 24 hours were prominently displayed in the pharmacy. The primary outcome was the overall change in the percentage of punctual medication delivery departures (ie, deliveries leaving the pharmacy at the scheduled time) during the 2 weeks after implementation of huddles and visual displays (the postintervention period). Punctuality was assessed at both the day and shift levels using generalized estimating equations in a piecewise regression model. A multivariable model was constructed using a forward stepwise selection process to assess the potential impacts of workload drivers and staffing levels on medication delivery punctuality. RESULTS: During the pre- and postintervention periods, the punctuality of a total of 1,032 deliveries was recorded. Punctuality of deliveries across all shifts increased by 37% (95% confidence interval [CI], 18%-56% [P < 0.001]), from 50% to 87%, immediately following implementation of the huddle intervention. When punctuality was assessed by individual shift, we observed statistically significant increases for the day (35% [95% CI, 13%-57%], P = 0.002), evening (34% [95% CI, 12%-56%], P = 0.003) and night (57% [95% CI, 35%-79%], P < 0.001) shifts. During the forward stepwise multivariable model-building process, order volume, message volume, and technician staffing levels were not significantly correlated with delivery punctuality at the day or shift level. CONCLUSION: Daily huddles with visual displays were successful in improving the punctuality of medication delivery departures from the pharmacy, independent of workload drivers and staffing levels.

Evaluation of Bedside Delivery of Medications Before Discharge: Effect on 30-Day Readmission.

BACKGROUND: This study is an evaluation of a discharge intervention that occurred in multiple hospitals across Maryland. In this program, patients received medications at their bedside before discharge with the goal of reducing the risk of primary nonadherence to prescribed medications. OBJECTIVE: To test if the intervention reduced the risk of 30-day readmission for the patients who received bedside medication delivery relative to comparable patients who did not receive bedside medication delivery. METHODS: This was a retrospective cohort study. Patients who received the intervention were linked to their claims data in the Maryland Health Information Exchange. These patients were matched on age, sex, diagnosis-related group, and hospital to a set of patients who did not receive the intervention. We used propensity score matching, as well as inverse-probability weighting, to account for residual differences between the treated and comparison patients. With robust Poisson regression, adjusting for hospital, we generated risk ratios for 30-day readmission and explored risk ratios in key subgroups. RESULTS: The cohort included 6,167 inpatients who received medications at bedside and 28,546 who did not from 10 Maryland hospitals. They were 60% female, 61% white, and 31% African American; the average age was 56 years. The risk ratio for readmission, comparing the intervention group to the propensity score-matched comparison group, was 1.21 (95% CI = 0.96-1.5). Inverse-probability weighting yielded a similar result (1.19 [95% CI = 0.98-1.45]). CONCLUSIONS: In this study, the isolated intervention of bedside medication delivery did not reduce 30-day readmission risk. We expect it may have favorable outcomes on other metrics such as primary nonadherence and patient satisfaction. It may also have a favorable effect when bundled with other care transition activities. As an isolated intervention, however, bedside medication delivery is unlikely to affect 30-day readmission rates. DISCLOSURES: This study was funded by Walgreen Co. through unrestricted funds to Johns Hopkins University, which has received fees from Walgreens for providing consultation as an institution to Walgreens. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict of interest policies. Segal received a grant from the National Institute on Aging during the conduct of this study. The other authors have nothing to disclose.

Defects in Processes of Care for Pharmacologic Prophylaxis Are Common Among Neurosurgery Patients Who Develop In-Hospital Postoperative Venous Thromboembolism.

BACKGROUND: Venous thromboembolism (VTE) is a cause of considerable morbidity and mortality in hospitalized patients. An evidence-based algorithm was developed and implemented at our institution to guide perioperative VTE prophylaxis management. OBJECTIVE: We evaluated compliance with prescription of risk-appropriate VTE prophylaxis and administration of prescribed VTE prophylaxis in neurosurgery patients. METHODS: This was a retrospective analysis of postoperative neurosurgery patients at a single institution with subsequent diagnosis of acute VTE during their inpatient stay. Descriptive statistics were used to characterize pharmacologic VTE prophylaxis and prescribing patterns. RESULTS: The incidence of VTE in our neurosurgery population was 248/13,913 (1.8%). Of the 123 patients, the median time to VTE diagnosis was 96 hours after surgery (interquartile range [IQR], 58-188 hours). A total of 108 patients (87.8%) were prescribed risk-appropriate VTE prophylaxis, among whom 61 (56.5%) received all doses as prescribed. Fifty-three patients (43.1%) missed ≥1 dose of prescribed prophylaxis and the median missed doses was 3 (IQR, 0-3). The median time to first dose of pharmacologic VTE prophylaxis was 42 hours (IQR, 28-51). More than half (n = 63, 51.2%) of the VTE risk assessments contained ≥1 error, of which 15 (23.8%) would have resulted in a change in recommendation. CONCLUSIONS: Our evidence-based VTE prophylaxis algorithm was not accurately completed in more than half of patients. Many patients who developed VTE had a defect in their VTE prophylaxis management during their inpatient stay. Research to improve optimal VTE prevention practice in neurosurgery patients is needed.