Order Sets Research Articles

Do Decision Support Tools Decrease the Prevalence of Hospital-Acquired Venous Thromboembolisms When Compared to Clinical Judgement? A Single-Center Pre-Post Study.

Introduction: Hospital-acquired venous thromboembolisms (HA-VTEs) carry a significant health burden on patients and a financial burden on hospitals due to reimbursement penalties. VTE prophylaxis at our institute was performed through utilizing an order set based on healthcare professionals' perceived level of risk. However, the use of standardized risk assessment models is recommended by multiple professional societies. Furthermore, integrating decision support tools (DST) based on the standardized risk assessment models has been shown to increase the administration of appropriate deep vein thrombosis (DVT) prophylaxis. Nonetheless, such scoring systems are not inherently flawless and their integration into EMR as a mandatory step can come at the risk of healthcare professional fatigue and burnout. We conducted a study to evaluate the incidence of HA-VTE and length of stay pre- and post implementation of a DST. Methods: We conducted a retrospective, pre-post-implementation observational study at a tertiary medical center after implementing a mandatory DST. The DST used Padua scores for medical patients and Caprini scores for surgical patients. Patients were identified through ICD-10 codes and outcomes were collected from electronic charts. Healthcare professionals were surveyed through an anonymous survey and stored securely. Statistical analysis was conducted by using R (version 3.4.3). Results: A total of 343 patients developed HA-VTE during the study period. Of these, 170 patients developed HA-VTE in the 9 months following the implementation of the DST, while 173 patients were identified in the 9 months preceding the implementation. There was no statistically significant difference in mean HA-VTE/1000 discharge/month pre- and post implementation (4.4 (SD 1.6) compared to 4.6 (SD 1.2), confidence interval [CI] -1.6 to 1.2, p = 0.8). The DST was used in 73% of all HA-VTE cases over the first 6 months of implementation. The hospital length of stay (LOS) was 14.2 (SD 1.9) days prior to implementation and 14.1 (SD 1.6) days afterwards. No statistically significant change in readmission rates was noted (8.8% (SD 2.6) prior to implementation and 15.53% (SD 9.6) afterwards, CI -14.27 to 0.74, p = 0.07). Of the 56 healthcare professionals who answered the survey, 84% (n = 47) reported to be dissatisfied or extremely dissatisfied with the DST, while 91% (n = 51) reported that it slowed them down. Conclusions: There were no apparent changes in the prevalence of HA-VTE, length of stay, or readmission rates when VTE prophylaxis was mandated through DST compared to a prior model which used order sets based on perceived risk. Further studies are needed to further evaluate the current risk assessment models and improve healthcare professionals' satisfaction with DST.

Late Holocene vegetation dynamics: degree and regional patterns of the Dark Ages woodland regeneration (ad 300–700) in the Netherlands

AbstractDuring the Dark Ages, which include the Late Roman period (ad 270–450) and the Early Middle Ages (ad 450–1050), large-scale vegetation development in northwest Europe was characterised by widespread regeneration of woodlands. This regeneration phase represents a break from the extensive reduction in woodland from human activities in late Holocene vegetation history. In the Netherlands, possible causes for this reversal can be found in a decreased human impact on the landscape, a colder and possibly wetter climate, and geomorphological changes. This paper presents a synthesis from 38 pollen records from a range of sites across the Netherlands, from which regional differences in the degree of woodland regeneration and vegetation composition before and during the Dark Ages have been identified. Both original data as well as vegetation abundance modelled by REVEALS were used to assess the regrowth of the woodland cover. The observed trends were considered in terms of the landscape setting and population estimates in order to disentangle the relative importance of these forcing factors. The results indicate that landscape and human impact were the most important factors determining the vegetation structure and changes to it. The pollen data show that in the Netherlands, the clearance of woodland in the Roman period followed by its regrowth afterwards were greatest in the river area. This can be linked to a high population density there during the Roman period followed by a strong decrease of population in the Dark Ages and to increased flooding.

Improving Cardiac Rehabilitation Referral Rates in Patients with Coronary Heart Disease from Diverse Communities Using an Electronic Order System

Introduction: Despite the benefits of Cardiac Rehabilitation (CR), local and national CR referral and participation rates remain low when compared to established cardiovascular therapies, especially amongst racial/ethnic groups. Objectives: This study investigated the effects of the implementation of a CR program and electronic order set (EOS) in a large health system on CR referral and participation rates among a diverse group of patients with Coronary Heart Disease (CHD). Methods: A total of 360 patients from UCSD Health who presented with ACS were prospectively evaluated during initial hospitalization and 6- and 12-weeks post-discharge. The multivariable logistic regression model assessed referral and participation rates by week 1 and -12 post-discharge, adjusting for gender, age, race, ethnicity, geography, and referring physician subspecialty. Results: UCSD CR program implementation led referral rates to increase at week 1 (Pre- 38.6% and Post-54.9%, p = 0.003) and week-12 (Pre- 54.1% and Post- 59.8%, p = 0.386). Post-CR referrals were more likely at week-1 (OR: 1.93, 95% CI 1.27-2.95) and week-12 (OR: 1.26, 95% CI 0.79-2.00). EOS implementation increased referral rates at week-1 (Pre- 40.3% and Post- 58.7%, p < 0.001) and week-12 (Pre- 54.9% and Post- 60.4%, p = 0.394) with referrals more likely at week-1 (OR: 2.1, 95% CI 1.35-3.29) and week-12 (OR: 1.25, 95% CI 0.795-1.98). Participation in CR following EOS was more likely at both week-1 and week-12. Multivariable analysis revealed disparities in referral based on race, geographic location, and referring physician subspecialty. Conclusion: A CR program and EOS implementation were shown to increase referral rates with long-term potential for increasing referral and participation rates. Condensed abstract: This prospective study investigated the implementation of a Cardiac Rehabilitation (CR) program and Electronic Order Set (EOS) within the same health system on CR referral and participation rates. 360 patients with ACS were evaluated over 12 weeks. UCSD CR program and EOS implementation led referral rates to increase at week-1 and -12. CR participation was more likely to increase at week-1 and -12 following EOS. Multivariable analysis revealed disparities in referrals disproportionally affecting racial and ethnic minority groups and rural communities. CR and EOS implementation may increase CR referral rates for diverse patients with CHD.

Impact of an electronic smart order-set for diagnostic stewardship of Clostridiodes difficile infection (CDI) in a community healthcare system in South Florida

Inappropriate testing for Clostridiodes difficile infection (CDI) increases health care onset cases and contributes to overdiagnosis and overtreatment of patients in a community healthcare system. An electronic smart order set for the testing of CDI was created and implemented to improve the appropriateness of testing. A retrospective review of patients who were tested for CDI, pre and post, was conducted to determine if inappropriate stool testing for CDI decreased post-implementation of the order set. 224 patients were tested for CDI during the study period with the post-implementation period having a higher proportion of patients who met appropriate testing criteria defined by presence of diarrhea (80.5% vs 61.3%; P=.002). The rate of inappropriate CDI stool testing decreased from 31.1% to 11.0% after implementation (P<.001). A higher proportion of CDI patients were readmitted within 30 days of discharge (54.2% vs 33.0%; P=0.001) during the post-implementation period. There was a significant reduction in inappropriate CDI testing following the implementation of the order set. There was an observed increase in the proportion of patients who underwent recent gastrointestinal surgery which may have contributed to the increase in 30-day readmission rates during the post-implementation period.

Production Planning Optimization in a Two-Echelon Multi-Product Supply Chain with Discrete Delivery and Storage at Manufacturer’s Warehouse

In today’s competitive world, customers expect their demands to be met at the shortest possible time, while manufacturers aspire to deliver the orders within a convenient time and at a minimum cost. Thus, manufacturers are compelled to seek ways of lowering the costs of their services in order to satisfy customers and survive the competition in their respective industries. This research paper investigates a multi-product problem in a two-echelon supply chain consisting of a single manufacturer and several retailers. The main objective of this research is to develop and present a multi-product optimization model in which retailers receive their orders through discrete delivery and surplus manufactured goods are stored in the manufacturer’s warehouse. The objective function of the mathematical model in the economic dimension includes the minimization of the total supply chain costs and the maximization of profit. The retailers in this model place new orders when their inventory level drops to zero, and the manufacturer responds to the retailers’ orders at the same time as it begins processing each product. After delivering the last set of orders, the manufacturer stores surplus items in its warehouse in case the retailers place new orders. This optimization problem is modeled using mixed integer nonlinear programming, while numerical scenarios are coded using the MATLAB software which helps estimate the total cost within a short time. Finally, a sensitivity analysis is performed to determine the effects of a number of factors on the total cost, including problem parameters, demand and production rates, the production quantity, and the number of times the manufacturing machines are operated at each production cycle.

Reduction of Chest Drain Overuse Through Implementation of a Pleural Drainage Order Set.

Small chest drains are used in many centers as the default drainage strategy for various pleural effusions. This can lead to drain overuse, which may be harmful. This study aimed to reduce chest drain overuse. We studied consecutive pleural procedures performed in the radiology department before (August 1, 2015, to July 31, 2016) and after intervention (September 1, 2019, to January 31, 2020). Chest drains were deemed indicated or not based on criteria established by a local interdisciplinary work group. The intervention consisted of a pleural drainage order set embedded in electronic medical records. It included indications for chest drain insertion, prespecified drain sizes for each indication, fluid analyses, and postprocedure radiography orders. Overall chest drain use and proportion of nonindicated drains were the outcomes of interest. We reviewed a total of 288 procedures (pre-intervention) and 155 procedures (post-intervention) (thoracentesis and drains). Order-set implementation led to a reduction in drain use (86.5% vs 54.8% of all procedures, P < .001) and reduction in drain insertions in the absence of an indication (from 45.4% to 29.4% of drains, P = .01). The need for repeat procedures did not increase after order-set implementation (22.0% pre vs 17.7% post, P = .40). Complication rates and length of hospital stay did not differ significantly after the intervention. More pleural infections were treated with drain sizes of 12Fr and greater (31 vs 70%, P < .001) after order-set deployment, and direct procedural costs were reduced by 27 CAN$ per procedure. Implementation of a pleural drainage order-set reduced chest drain use, improved procedure selection according to clinical needs, and reduced direct procedural costs. In institutions where small chest drains are used as the default drainage strategy for pleural effusions, this order set can reduce chest drain overuse.

PICU admission order set: a quality improvement initiative in a developing country

PICU admission order set: a quality improvement initiative in a developing country

Enhancing the interpretability of sentiment analysis with signatures

Sentiment analysis is a significant research area within the field of natural language processing, with applications in various social contexts. Recent advances in related research have led to notable improvements in accuracy, yet existing text sentiment analysis models continue to face challenges in terms of interpretability. This paper proposes a text sentiment classification method integrating BERT and BiLstm, comprising three stages: training, signature generation, and testing. Our primary contribution lies in the signature generation and testing stages. In the training stage, BERT is employed to generate word embeddings, while BiLstm is utilized for learning to construct the text sentiment classification model. In the signature generation stage, the training and validation sets are passed through the aforementioned classification model, the feature vectors are extracted following their passage through the fully-connected layer, and the feature vectors are utilized to generate the signature generation stage. The signature is then stored in the database. In the Testing Stage, the aforementioned operation is repeated on the test set in order to obtain the signatures. The signatures are then matched in the constructed signature database in order to obtain the final classification results. The matching degree is subsequently used as a threshold in order to be employed for subsequent evaluation of the results. The method enhances the interpretability of the classification task by matching through signatures. Two datasets, SST-2 and IMDB, were subjected to experimentation. Four quantitative metrics were employed for the evaluation of the results: accuracy, recall, precision, and F1-score. With a threshold of 0.99, the models optimal accuracy, recall, precision, and F1-score results reached 0.896, 1, 0.896, 0.945 and 0.847, 0.999, 0.848, 0.917, respectively.

CS-count-optimal quantum circuits for arbitrary multi-qubit unitaries

In quantum computing there are quite a few universal gate sets, each having their own characteristics. In this paper we study the Clifford+CS universal fault-tolerant gate set. The CS gate is used is many applications and this gate set is an important alternative to Clifford+T. We introduce a generating set in order to represent any unitary implementable by this gate set and with this we derive a bound on the CS-count of arbitrary multi-qubit unitaries. Analysing the channel representation of the generating set elements, we infer JnCS⊂JnT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {J}}_n^{CS}\\subset {\\mathcal {J}}_n^T$$\\end{document}, where JnCS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {J}}_n^{CS}$$\\end{document} and JnT\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {J}}_n^T$$\\end{document} are the set of unitaries exactly implementable by the Clifford+CS and Clifford+T gate sets, respectively. We develop CS-count optimal synthesis algorithms for both approximately and exactly implementable multi-qubit unitaries. With the help of these we derive a CS-count-optimal circuit for Toffoli, implying JnTof=JnCS\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {J}}_n^{Tof}={\\mathcal {J}}_n^{CS}$$\\end{document}, where JnTof\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {J}}_n^{Tof}$$\\end{document} is the set of unitaries exactly implementable by the Clifford+Toffoli gate set. Such conclusions can have an important impact on resource estimates of quantum algorithms.

The Secretary Problem with Independent Sampling

The secretary problem is probably the most well-studied optimal stopping problem with many applications in economics and management. In the secretary problem, a decision maker faces an unknown sequence of values, revealed successively, and has to make irrevocable take-it-or-leave-it decisions. Her goal is to select the maximum value in the sequence. Although in the classic secretary problem the values of upcoming elements are entirely unknown, in many realistic situations, the decision maker has access to some information, for example, from past data. In this paper, we take a sampling approach and assume that before starting the sequence, each element is sampled independently with probability p. We study both the adversarial and the random arrival models. Our main result is to obtain the best possible algorithms for both settings and all values of p. As p grows to one, the obtained guarantees converge to the optimal guarantees in the full information case. Notably, we establish that the best possible algorithm in the adversarial order setting is a fixed threshold algorithm. In the random order setting, we characterize the best possible algorithm by a sequence of thresholds, dictating at which point in time we should accept a value. Surprisingly, this sequence is independent of p. We complement our theoretical results with numerical experiments on data of people playing the secretary problem repeatedly. Our results help explain some behavioral issues they raised and indicate that people play a strategy similar to our optimal algorithms from the start onwards, albeit slightly suboptimally. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was partially funded by the Agencia Nacional de Investigación y Desarrollo Chile [Grants FB210005 (Centro de Modelamiento Matamático), AIM23_0004 (Millenium Institute for Research in Market Imperfections and Public Policy), AFB230002 (Instituto Sistemas Complejos de Ingeniería), ACT210005, and Fondo Nacional de Desarrollo Científico y Tecnológico 1220054], the Alexander von Humboldt Foundation with funds from the German Federal Ministry of Education and Research, and the German Research Foundation within the Research Training Group Advanced Optimization in a Networked Economy [Grant Graduiertenkolleg 2201]. The views expressed in this paper do not necessarily reflect those of the European Central Bank or the Eurosystem. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01580 .

Improving Antibiotic Prescribing for Children with Community-acquired Pneumonia in Outpatient Settings

To assess whether a two-phase intervention was associated with improvements in antibiotic prescribing among nonhospitalized children with community-acquired pneumonia. In a large health care organization, a first intervention phase was implemented in September 2020 directed at antibiotic choice and duration for children 2months through 17years of age with pneumonia. Activities included clinician education and implementation of a pneumonia-specific order set in the electronic health record. In October 2021, a second phase comprised additional education and order set revisions. A narrow spectrum antibiotic (eg, amoxicillin) was recommended in most circumstances. Electronic health record data were used to identify pneumonia cases and antibiotics ordered. Using interrupted time series analyses, antibiotic choice and duration after phase one (September 2020-September 2021) and after phase two (October 2021-October 2022) were compared with a preintervention prepandemic period (January 2016-early March 2020). Overall, 3570 cases of community-acquired pneumonia were identified: 3246 cases preintervention, 98 post-phase one, and 226 post-phase two. The proportion receiving narrow spectrum monotherapy increased from 40.6% preintervention to 68.4% post-phase one to 69.0% post-phase two (P<.001). For children with an initial narrow spectrum antibiotic, duration decreased from preintervention (mean duration 9.9days, SD 0.5days) to post-phase one (mean 8.2, SD 1.9) to post-phase two (mean 6.8, SD 2.3) periods (P<.001). A two-phase intervention with educational sessions combined with clinical decision support was associated with sustained improvements in antibiotic choice and duration among children with community-acquired pneumonia.

Morbidity following robot-assisted surgery in a gynecological oncology setting: A cohort study.

The objective of the study was to provide a comprehensive description of perioperative morbidity associated with robot-assisted surgery (RAS) in a gynecological oncology setting in order to improve the preoperative counseling of women and support shared decision-making. All women scheduled for intended RAS between January 2015 and December 2022 were prospectively included in an electronic morbidity database for the analyses of perioperative complications. In total, 2225 women were included. Sixty-four patients (2.9%) experienced an intraoperative complication. Intraoperative complications were associated with a higher rate of conversion to laparotomy (15.6% vs. 1.8%, p < 0.001), a higher rate of major postoperative morbidity (9.3% vs. 2.4%, p < 0.001), and a higher rate of reoperation (9.3% vs. 1.7%, p < 0.001), compared to cases without intraoperative complications. Thirty-day postoperative morbidity was evaluated according to the Memorial Sloan-Kettering Cancer Center Surgical Secondary Events Grading System. Grade 3-5 events were considered major. A total of 57 patients (2.6%) experienced a major event after surgery, postoperative rupture of the vaginal vault being the most common complication requiring surgical intervention. Conversion to laparotomy occurred in 49 cases (2.2%) and was associated with higher intraoperative blood loss (300 mL vs. 25 mL, p < 0.001), a higher rate of postoperative major events (20.4% vs. 2.2%, p < 0.001), and a higher rate of reoperation (11.8% vs. 1.6%, p < 0.001). Our study demonstrates low rates of major perioperative morbidity and conversion to laparotomy after RAS performed by trained high-volume surgeons in a gynecological oncology setting.

Implementation of a Multidisciplinary Team to Improve the Quality of Care for Older Surgical Patients at a Rural Academic Medical Center.

For the first time in history, people age older than 65 years make up >20% of the non-metro population, compared with 16% of the metro population. From 2010 to 2020 the nonmetro population age older than 65 years grew by 22%, while the working-age population declined by 4.9%, and the population aged under 18 years declined by 5.7%.1,2 Multidisciplinary geriatric surgical programs are an increasingly recognized approach to the care of older surgical patients and preliminary data suggest they can reduce length of stay. Although rural areas have the greatest proportion of patients age older than 65 years, implementation of such programs faces special challenges in rural settings with limited resources. Dartmouth-Hitchcock Medical Center is one of the most rural academic centers in the United States. Challenges include a shortage of geriatric-trained providers, long distances to access primary care and subspecialists, and extremely limited postacute care options and skilled nursing facility beds. To address the unique needs of our provider and patient population we began with a development period where we conducted stakeholder interviews. Using these data, we mapped out a workflow and developed pilot projects to address different portions of the workflow, such as preoperative screening for frailty and cognitive impairment, interdisciplinary weekly case conferences, proactive case management, delirium and geriatric surgery postoperative pathway order sets, and a variety of tools for reorientation and delirium management. Herein we describe the process of development and pragmatic clinical implementation of geriatric-focused care for older surgical patients in our rural tertiary center, including some of the main challenges we faced and the strategies we undertook to overcome them, and some of our early patient centered and clinical outcomes. This information may assist other institutions as they design geriatric-focused surgical programs to address the growing population of older adults and the need for compliance with state legislation. The clinical program described is not a research study, and the outcome data we report is for the purpose of description, and should not be interpreted as a rigorous research investigation of the effect of our intervention.

Measuring aviator workload using EEG: an individualized approach to workload manipulation.

Measuring an operator's physiological state and using that data to predict future performance decrements has been an ongoing goal in many areas of transportation. Regarding Army aviation, the realization of such an endeavor could lead to the development of an adaptive automation system which adapts to the needs of the operator. However, reaching this end state requires the use of experimental scenarios similar to real-life settings in order to induce the state of interest that are able to account for individual differences in experience, exposure, and perception to workload manipulations. In the present study, we used an individualized approach to manipulating workload in order to account for individual differences in response to workload manipulations, while still providing an operationally relevant flight experience. Eight Army aviators participated in the study, where they completed two visits to the laboratory. The first visit served the purpose of identifying individual workload thresholds, with the second visit resulting in flights with individualized workload manipulations. EEG data was collected throughout both flights, along with subjective ratings of workload and flight performance. Both EEG data and workload ratings suggested a high workload. Subjective ratings were higher during the high workload flight compared to the low workload flight (p < 0.001). Regarding EEG, frontal alpha (p = 0.04) and theta (p = 0.01) values were lower and a ratio of beta/(alpha+theta) (p = 0.02) were higher in the baseline flight scenario compared to the high workload scenario. Furthermore, the data were compared to that collected in previous studies which used a group-based approach to manipulating workload. The individualized method demonstrated higher effect sizes in both EEG and subjective ratings, suggesting the use of this method may provide a more reliable way of producing high workload in aviators.

Low-dose overlap initiation with split tablets of buprenorphine in intubated intensive care unit patients with opioid use disorder

BackgroundAs the opioid public health crisis evolves to include fentanyl and other potent synthetic opioids, more patients are admitted to the hospital with serious complications of drug use and frequently require higher levels of care, including intensive care unit (ICU) admission, for acute and chronic conditions related to opioid use disorder (OUD). This patient population poses a unique challenge when managing sedation and ensuring adequate ventilation while intubated given their high opioid requirements. Starting a patient on medications such as buprenorphine may be difficult for inpatient providers unfamiliar with its use, which may lead to undertreatment of patients with OUD, prolonged mechanical ventilation and length of stay.MethodsWe developed a 7-day buprenorphine low dose overlap initiation (LDOI) schedule for patients with OUD admitted to the ICU (Table 1). Buprenorphine tablets were split by pharmacists and placed into pre-made blister packs as a kit to be loaded into the automated medication dispensing machine for nursing to administer daily. An internal quality review validated the appropriate dosing of split-dose tablets. To simplify order entry and increase prescriber comfort with this new protocol, we generated an order set within our electronic health record software with prebuilt buprenorphine titration orders. This protocol was implemented alongside patient and healthcare team education and counseling on the LDOI process, with follow-up offered to all patients upon discharge.ResultsHere we report a series of 6 ICU patients started on buprenorphine using the LDOI schedule with split buprenorphine tablets. None of the 6 patients experienced precipitated withdrawal upon buprenorphine initiation using the LDOI schedule, and 5/6 patients were successfully extubated during the buprenorphine initiation. Four of six patients had a decrease in daily morphine milligram equivalents, with 3 patients transitioning to buprenorphine alone.ConclusionInitiating buprenorphine via LDOI was found to be successful in the development of a protocol for critically ill patients with OUD. We examined LDOI of buprenorphine in intubated ICU patients and found no events of acute precipitated withdrawal. This protocol can be used as a guide for other institutions seeking to start critically ill patients on medication treatment for OUD during ICU admission.

Introduction of an order set after hip fracture improves osteoporosis medication initiation and persistence: a population-based before-after analysis.

A treatment gap exists after osteoporosis-related fractures. Introducing standardized care can improve treatment. We evaluated the impact of a hip fracture order set (OS) on anti-osteoporosis medication (AOM) initiation, persistence, and secondary fracture prevention. In 2015, one hospital in Manitoba, Canada, introduced a hip fracture OS including recommendations for the initiation of AOM (OS group). A control group was identified from the other hospitals in the same region. A retrospective cohort study was conducted using linked administrative health data. All individuals 50 + years with surgical treatment for low-energy hip fracture between 2010 and 2019 were included and followed for AOM initiation, medication persistence at 1year, and secondary fractures. Between-group differences for each year were assessed using chi-square tests. Logistic regression models tested the impact of socio-demographic and clinical factors on initiation, persistence of AOM. Cox regression tested the risk of secondary fracture. No baseline differences between OS group (813 patients) and control group (2150 patients) were observed in demographics, socioeconomic factors, or comorbidities. An increase in post-fracture AOM initiation was seen with OS introduction (OS group year before 16.7% versus year after 48.6%, p < 0.001). No change was seen in the control group. Persistence on AOM also increased (OS group year before 17.7% versus year after 28.4%, p < 0.001). No difference in secondary fractures was observed (OS group 19.8% versus control group 18.8%, p = 0.38). Introduction of a hip fracture OS significantly increased AOM initiation and persistence at 1-year post-fracture. There was no significant difference in secondary fractures.

Developing fracture liaison service framework based on comparative analysis and scoping review.

The primary goal is to review interventions in real world settings in order to provide the FLS framework that specifies the essential elements of its implementation and offers different perspectives on that. This study encompasses two phases: a comparative analysis of existing FLS models, including "Capture the Fracture," "5IQ," and "Ganda," and a scoping review from 2012 to 2022 in PubMed, Web of Science, Scopus, ProQuest, and IEEE databases limited to publications in English. The resulting model of comparative analysis identifies patient identification, investigation, intervention and integration or continuity of care as the four main stages of FLS. Additionally, the elements of quality and information span across all stages. Following comparative analysis, the framework is designed to be used for content analysis of the included studies in the scoping review. The intersection of columns (Who, Where, When, What, How, Quality) with rows (Identification, Investigation, Intervention, and continuity of care) yields a set of questions, answered in tabular form based on the scoping review. The framework offers potential benefits in facilitating the adoption of effective approaches for FLS implementation. It is recommended to undertake an in-depth review of each of these components in order to uncover novel and innovative approaches for improving their implementation.

Preoperative medication management turnkey order set for nonemergent adult cardiac surgery

ObjectiveThe management of preoperative medications is an essential component of perioperative care for the cardiac surgical patient. This turnkey order set is part of a series created by the Enhanced Recovery After Surgery Cardiac Society, first presented at the Annual Meeting of The American Association for Thoracic Surgery in 2023. Numerous guidelines and expert consensus documents have been published to provide guidance in preoperative medication management. Our objective is to integrate these documents into an evidence-based order set that will facilitate standardized implementation of best practices for preoperative medication management for nonemergent adult cardiac surgery. MethodsSubject matter experts were consulted to translate existing guidelines and peer reviewed literature into a sample turnkey order set for the preoperative management of patients’ medications. Orders derived from consistent Class I, IIA, or equivalent recommendations across referenced guidelines and consensus manuscripts appear in the order set in bold type. Selected orders that were inconsistently Class I or IIA, Class IIB, or supported by published evidence, were also included in italicized type. ResultsHolding antiplatelet and anticoagulant medications before nonemergent cardiac surgical procedures may reduce the risk of bleeding. Sodium-glucose co-transporter-2 inhibitors and glucagon-like peptide-1 agonists should also be discontinued to prevent acidosis and aspiration, respectively. Specific guidance for frequently used medications are complied within the manuscript, less frequently used medications are listed seperately. ConclusionsDespite strong recommendations from major guidelines and consensus manuscripts, variation exists in preoperative medication orders, with limited availability of succinct implementation tools. This turnkey order set may facilitate standardized comprehensive preoperative medication management before nonemergent cardiac surgery.

Sepsis Order Set Use Associated With Increased Care Value

BackgroundSepsis is common and expensive and there is evidence that sepsis order sets may help improve care. There is very incomplete evidence of the effects of sepsis order sets on the value of care produced by hospitals or the societal costs of sepsis care. Research QuestionIn patients hospitalized for sepsis, is the receipt a of a sepsis order set vs. no order set associated with improved value of care, defined as decreased hospital mortality, decreased hospital direct variable costs and decreased societal spending on hospitalizations? Study Design and MethodsRetrospective cohort study of patients discharged with sepsis ICD-10 codes over two years from a large integrated delivery system. Using a propensity score, sepsis order set users were matched to non-users to study the association between sepsis order set use and the value of care from the hospital and societal perspective. The association between order set receipt and hospital mortality, direct variable cost, and hospital revenue were also examined in a priori defined subgroups of sepsis severity and hospital mortality. Results97,249 patients were included in the study with 52,793 (54%) receiving the sepsis order set. 55,542 patients were included in the propensity score match analysis, 27,771 in each group. Recipients of the sepsis order set had a 3.3% lower hospital mortality rate, a $1487 lower median direct variable total cost (P < 0.01 for both). Median payer neutral reimbursement (PNR), a proxy for hospital revenue and thus societal costs, was $465 lower for sepsis order set users (P < 0.01). Receipt of the sepsis order set was associated with an $1022 increase in contribution margin, the difference between direct variable costs and PNR per patient. InterpretationReceipt of the sepsis order set was associated with improved value of care, from both a hospital and societal perspective.

Chemotherapy Care Companion: Enhancing cancer care through digital remote monitoring.

1636 Background: Oncology patients often encounter preventable acute issues prompting the need for proactive monitoring and management. To manage disease and therapy complications, Ochsner Health developed Chemotherapy Care Companion (CCC) for remote monitoring of treatment patients. This abstract highlights the feasibility of digital remote monitoring (DRM) in managing oncologic patient care, while increasing patient satisfaction and reducing patient events and healthcare costs. Methods: Starting in January 2021, patients initiating an oral or intravenous cancer treatment with an active Ochsner portal account and smartphone became eligible. Providers can manually enroll patients via an order set and receive enrollment reminders within the Epic electronic medical record (EMR). Patients receive a digital WiFi-enabled monitoring scale, blood pressure cuff, and ear thermometer, at no cost. Patients are reminded via phone alerts to take vitals at 9am and 3pm, along with a daily questionnaire. The data is transmitted wirelessly to the EMR, where abnormal vital signs or questionnaire responses trigger escalations sent to an Epic in-basket pool. During clinic hours, advanced practice providers (APPs) review and intervene, utilizing embedded urgent care slots for same-day access. In August 2022, a patient satisfaction survey comprising of nine questions was distributed to all enrolled patients. Results: A retrospective analysis was conducted from September 2022 to August 2023 including 722 participants, 7,360 escalations and 668 interventions. Patient compliance reached 62%, defined as submitting at least 50% of daily vitals. The most common interventions were related to hypertension, hypotension, weight changes, and questionnaire responses. Regarding questionnaire responses, diarrhea, pain, fever, and dizziness were the mostly frequently triaged. Data analytics revealed that CCC led to a 5.9% decrease in emergency room visits, a 41.7% decrease in the rate of inpatient hospital admissions, and a 32.3% improvement in the inpatient length of stay compared to non-enrolled patients. Extrapolating this data across 5,500 oncology patients within our hospital system, CCC could prevent 172 ER visits, 914 inpatient hospital admissions and 2,006 hospital days. The survey (131 responses) revealed high satisfaction with CCC: over 80% felt a sense of security, 90% were overall satisfied, and more than 90% would recommend CCC. Conclusions: Findings highlight the value of integrating DRM in cancer care, showcasing its ability to reduce healthcare costs and optimize resource utilization while enhancing patient care and satisfaction. Moreover, the study underscores the high patient satisfaction and engagement with DRM, bolstering its feasibility and acceptance in oncology care. Further investigation is warranted to explore the financial benefits for hospitals, insurance companies, and pharmaceutical companies.