Transparent Reporting Research Articles

Evaluasi Penerapan Aplikasi Sistem Keuangan Desa (Siskeudes ver. 2.0.3) dalam Peningkatan Kinerja Aparat Desa menggunakan Task Technology Fit

The Village Financial System (Siskeudes) is an information system that assists the village government in reporting transparent and accountable financial reports. On the other hand, there are adjustments to financial management during the Covid-19 pandemic, so Siskeudes application also needs to accommodate these adjustments. Moreover, various problems were found in this system such as delays in financial reporting and recording errors. One of the factors of the problem is the mismatch of tasks in operating the application. This study aims to analyze the causes and consequences of task mismatches using the Task Technology Fit (TTF) model. The study described in this paper used the technology-to-performance chain as a framework to address the question of how task–technology fit influences the performance impacts. Respondents in this study were 50 village officials in Boyolali district who had used Siskeudes Ver. 2.0.3. This study was analyzed using a questionnaire with closed questions and open questions. This research method used Partial Least Square (PLS) using SmartPls 3.3.3. In addition, the results of this study indicated that the task of the technology-fit model has a significant effect on Performance Impact. Villages also have apparatus in accordance with Siskeudes operations. In this case, the finance department (having knowledge in finance) have a better level of performance. However, there are some villages where the operation of Siskeudes assisted by non-financial officials so that utilization does not have a significant effect on improving the performance of the finance department.

Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review

BackgroundWhile many studies have consistently found incomplete reporting of regression-based prediction model studies, evidence is lacking for machine learning-based prediction model studies. We aim to systematically review the adherence of Machine Learning (ML)-based prediction model studies to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement.MethodsWe included articles reporting on development or external validation of a multivariable prediction model (either diagnostic or prognostic) developed using supervised ML for individualized predictions across all medical fields. We searched PubMed from 1 January 2018 to 31 December 2019. Data extraction was performed using the 22-item checklist for reporting of prediction model studies (www.TRIPOD-statement.org). We measured the overall adherence per article and per TRIPOD item.ResultsOur search identified 24,814 articles, of which 152 articles were included: 94 (61.8%) prognostic and 58 (38.2%) diagnostic prediction model studies. Overall, articles adhered to a median of 38.7% (IQR 31.0–46.4%) of TRIPOD items. No article fully adhered to complete reporting of the abstract and very few reported the flow of participants (3.9%, 95% CI 1.8 to 8.3), appropriate title (4.6%, 95% CI 2.2 to 9.2), blinding of predictors (4.6%, 95% CI 2.2 to 9.2), model specification (5.2%, 95% CI 2.4 to 10.8), and model’s predictive performance (5.9%, 95% CI 3.1 to 10.9). There was often complete reporting of source of data (98.0%, 95% CI 94.4 to 99.3) and interpretation of the results (94.7%, 95% CI 90.0 to 97.3).ConclusionSimilar to prediction model studies developed using conventional regression-based techniques, the completeness of reporting is poor. Essential information to decide to use the model (i.e. model specification and its performance) is rarely reported. However, some items and sub-items of TRIPOD might be less suitable for ML-based prediction model studies and thus, TRIPOD requires extensions. Overall, there is an urgent need to improve the reporting quality and usability of research to avoid research waste.Systematic review registrationPROSPERO, CRD42019161764.

Quality assessment of radiomics research in cardiac CT: a systematic review.

To assess the quality of current radiomics research on cardiac CT using radiomics quality score (RQS) and Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) systems. Systematic searches of PubMed and EMBASE were performed to identify all potentially relevant original research articles about cardiac CT radiomics. Fifteen original research articles were selected. Two cardiac radiologists assessed the quality of the methodology adopted in those studies according to the RQS and TRIPOD guidelines. Basic adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Among the 15 included articles, six (40%) were about coronary artery disease and six (40%) were about myocardial infarction. The mean RQS was 9.9 ± 7.3 (27.4% of the ideal score of 36), and the basic adherence rate was 44.6%. Fourteen (93.3%) and nine (60%) studies performed feature selection and validation, but only two (13.3%) of them performed external validation. Two studies (13.3%) were prospective, and only one study (6.7%) conducted calibration analysis and stated the potential clinical utility. None of the studies conducted phantom study and cost-effective analysis. The overall adherence rate for TRIPOD was 63%. The quality of radiomics studies in cardiac CT is currently insufficient. A higher level of evidence is required, and analysis of clinical utility and calibration of model performance need to be improved. • The quality of science of radiomics studies in cardiac CT is currently insufficient. • No study conducted a phantom study or cost-effective analysis, with further limitations being demonstrated in a high level of evidence for radiomics studies. • Analysis of clinical utility and calibration of model performance need to be improved, and a higher level of evidence is required.

Accounting Practices and its Effect on Performance of Oil and Gas Companys in Nigeria

: This work examined the extent to which Accounting practices affect theprofitability of Oil and Gas companies in Nigeria, particularly those in the upstream sector. The Researchers used Stratified Sampling Design approach. The target population comprised of Oil and Gas Companies in Nigeria. A total of 84 respondents were drawn from the population. Both primary and secondary data were used in the study. Primary Data were collected using questionnaires drawn using the Likert’s Scale with five points ranging from very great extent to no extent, while secondary data were sourced from already published materials. Hypotheses were formulated and data were analyzed using SPSS Software and other Descriptive statistical tools such as; percentages and tables. The result of the study showed that accounting practices had a significant relationship with performance of Oil and Gas Companies, particularly, the Return on Assets and Return on Capital Employed. It was recommended that proper and best accounting practices should be adopted by Oil and Gas companies to ensure better performance on one hand and fair, transparent and reliable financial reports on the other hand.

Endoscopic third ventriculostomy for adults with hydrocephalus: creating a prognostic model for success: protocol for a retrospective multicentre study (Nordic ETV)

IntroductionEndoscopic third ventriculostomy (ETV) is becoming an increasingly widespread treatment for hydrocephalus, but research is primarily based on paediatric populations. In 2009, Kulkarni et al created the ETV Success score...

Quality of Radiomics Research on Brain Metastasis: A Roadmap to Promote Clinical Translation.

ObjectiveOur study aimed to evaluate the quality of radiomics studies on brain metastases based on the radiomics quality score (RQS), Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) checklist, and the Image Biomarker Standardization Initiative (IBSI) guidelines.Materials and MethodsPubMed MEDLINE, and EMBASE were searched for articles on radiomics for evaluating brain metastases, published until February 2021. Of the 572 articles, 29 relevant original research articles were included and evaluated according to the RQS, TRIPOD checklist, and IBSI guidelines.ResultsExternal validation was performed in only three studies (10.3%). The median RQS was 3.0 (range, -6 to 12), with a low basic adherence rate of 50.0%. The adherence rate was low in comparison to the “gold standard” (10.3%), stating the potential clinical utility (10.3%), performing the cut-off analysis (3.4%), reporting calibration statistics (6.9%), and providing open science and data (3.4%). None of the studies involved test-retest or phantom studies, prospective studies, or cost-effectiveness analyses. The overall rate of adherence to the TRIPOD checklist was 60.3% and low for reporting title (3.4%), blind assessment of outcome (0%), description of the handling of missing data (0%), and presentation of the full prediction model (0%). The majority of studies lacked pre-processing steps, with bias-field correction, isovoxel resampling, skull stripping, and gray-level discretization performed in only six (20.7%), nine (31.0%), four (3.8%), and four (13.8%) studies, respectively.ConclusionThe overall scientific and reporting quality of radiomics studies on brain metastases published during the study period was insufficient. Radiomics studies should adhere to the RQS, TRIPOD, and IBSI guidelines to facilitate the translation of radiomics into the clinical field.

Application of Accounting Information Systems at Zakat, Infaq, Sadaqah Institutions in an Effort to Improve Internal Control on Cash Receipts

This study aims to determine the application of accounting information systems at zakat, infaq, shadaqah institutions in an effort to improve internal control on cash receipts at LAZISMU Sidoarjo. This research approach uses a qualitative approach with primary data sources. Data collection was obtained from the results of interviews, observations and documentation. Technical validity of data with triangulation model. The results of the study stated that the application of the accounting information system at LAZISMU, Sidoarjo Regency had used a system from the center, namely the ZISKA software which stands for (Zakat, Infaq, Shadaqah, and Humanity). The advantages of the system are more detailed. However, there are obstacles that occur such as network disturbances and to prevent the risk of data loss, data backup is carried out. To anticipate errors in recording cash receipts, cross checks and evaluations are carried out through meetings. The use of the form or document has been serially numbered printed. Transparent financial reports to the public. Cash deposits to the bank are made every day and are directly deposited on bank business days. In the element of internal control, several weaknesses were found.

EFEKTIVITAS PENGELOLAAN DAN TRANSPARANSI DANA DESA DI DESA SIDOHARJO KECAMATAN TOLANGOHULA KABUPATEN GORONTALO

This study aims to determine the Effectiveness of Village Fund Management and Transparency in Sidoharjo Village, Tolangohula District, Gorontalo Regency. This type of research uses descriptive research with a qualitative approach according to Arif (2015:21). The results of this study are that the Management and Transparency of Village Funds in Tolangohula District, Gorontalo Regency are in accordance with Permendagri Number 20 of 2018 where the planning, implementation, administration, reporting and accountability of Village Funds are in accordance with the provisions of Village Fund management as regulated in Permendagri No. 20 of 2018, but in terms of planning, Sidohardo Village still does not routinely involve the community in the village fund planning deliberation process as a form of supervision of the Village Government, in terms of implementation there are often changes to the budget made and in terms of transparency the management of Village Funds has been implemented. implemented by the Sidohardjo Village Government but there is still a need for government evaluation of the community regarding the delivery of Village Fund Management to the community properly and clearly in order to create transparent and accountable financial reports, this is as the theory expressed by Krina (2015:17).

A Next Generation Sequencing-Based Protocol for Screening of Variants of Concern in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic influences. There is an increasing demand for ASD genetic testing beyond the traditionally recommended microarray and syndromic autism testing; however, the current whole genome sequencing (WGS) and whole exome sequencing (WES) methods are lacking an academic standard for WGS variant annotation, reporting, and interpretation, tailored towards patients with ASD and offer very limited interpretation for clinical significance. Using WGS data from six family trios, we demonstrate the clinical feasibility and technical implementation of an evidence-based, fully transparent bioinformatics pipeline and report framework for an ASD-focused WGS genetic report. We confirmed a portion of the key variants with Sanger sequencing and provided interpretation with consideration of patients’ clinical symptoms and detailed literature review. Furthermore, we showed that identification of the genetic contributions of ASD core symptoms and comorbidities may promote a better understanding of the ASD pathophysiology, lead to early detection of associated comorbidities, and facilitate pharmacologic intervention based on pathological pathways inferred from the genetic information. We will make the bioinformatics pipeline and interpretation framework publicly available, in an easily accessible format, after validation with a larger cohort. We hope that the present proposed protocol can serve as a starting point to invite discourse and debate to further improve approaches in WGS-based genetic consultation for patients with ASD.

Automated Annotations for AI Data and Model Transparency

The data and Artificial Intelligence revolution has had a massive impact on enterprises, governments, and society alike. It is fueled by two key factors. First, data have become increasingly abundant and are often available openly. Enterprises have more data than they can process. Governments are spearheading open data initiatives by setting up data portals such as data.gov and releasing large amounts of data to the public. Second, AI engineering development is becoming increasingly democratized. Open source frameworks have enabled even an individual developer to engineer sophisticated AI systems. But with such ease of use comes the potential for irresponsible use of data. Ensuring that AI systems adhere to a set of ethical principles is one of the major problems of our age. We believe that data and model transparency has a key role to play in mitigating the deleterious effects of AI systems. In this article, we describe a framework to synthesize ideas from various domains such as data transparency, data quality, data governance among others to tackle this problem. Specifically, we advocate an approach based on automated annotations (of both data and the AI model), which has a number of appealing properties. The annotations could be used by enterprises to get visibility of potential issues, prepare data transparency reports, create and ensure policy compliance, and evaluate the readiness of data for diverse downstream AI applications. We propose a model architecture and enumerate its key components that could achieve these requirements. Finally, we describe a number of interesting challenges and opportunities.

Solitary pulmonary nodule malignancy predictive models applicable to routine clinical practice: a systematic review

BackgroundSolitary pulmonary nodule (SPN) is a common finding in routine clinical practice when performing chest imaging tests. The vast majority of these nodules are benign, and only a small proportion are malignant. The application of predictive models of nodule malignancy in routine clinical practice would help to achieve better diagnostic management of SPN. The present systematic review was carried out with the purpose of critically assessing studies aimed at developing predictive models of solitary pulmonary nodule (SPN) malignancy from SPN incidentally detected in routine clinical practice.MethodsWe performed a search of available scientific literature until October 2020 in Pubmed, SCOPUS and Cochrane Central databases. The inclusion criteria were observational studies carried out in low-risk population from 35 years old onwards aimed at constructing predictive models of malignancy of pulmonary solitary nodule detected incidentally in routine clinical practice. Studies had to be published in peer-reviewed journals, either in Spanish, Portuguese or English. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches. Exclusion criteria were non-human studies, or predictive models based in high-risk populations, or models based on computational approaches (such as radiomics). We used The Transparent Reporting of a multivariable Prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement, to describe the type of predictive model included in each study, and The Prediction model Risk Of Bias ASsessment Tool (PROBAST) to evaluate the quality of the selected articles.ResultsA total of 186 references were retrieved, and after applying the exclusion/inclusion criteria, 15 articles remained for the final review. All studies analysed clinical and radiological variables. The most frequent independent predictors of SPN malignancy were, in order of frequency, age, diameter, spiculated edge, calcification and smoking history. Variables such as race, SPN growth rate, emphysema, fibrosis, apical scarring and exposure to asbestos, uranium and radon were not analysed by the majority of the studies. All studies were classified as high risk of bias due to inadequate study designs, selection bias, insufficient population follow-up and lack of external validation, compromising their applicability for clinical practice.ConclusionsThe studies included have been shown to have methodological weaknesses compromising the clinical applicability of the evaluated SPN malignancy predictive models and their potential influence on clinical decision-making for the SPN diagnostic management.Systematic review registrationPROSPERO CRD42020161559

Sosialisasi Pengelolaan Keuangan Desa Kepada Aparatur Desa Untuk Pemberdayaan Masyarakat Di Desa Belangian Kecamatan Aranio Kabupaten Banjar

The purpose of this community service is to carry out programs and activities funded by the village income and expenditure budget, administering village financial transactions using the village accounting model, so as to be able to make transparent and accountable village financial reports. With the enactment of Law Number 6 of 2014 concerning Villages, the village government will obtain large enough funds and must be managed properly and can be accounted for. The method of implementing this activity uses data collection methods to collect data by analyzing the realization of the Village Revenue and Expenditure Budget (APBDes) documents, and conducting interviews with village government officials with the Village Consultative Body (BPD). The data analysis method used is a village accounting model to discuss problems, using an analysis of the village accounting model and existing regulations in the village. Socialization activities using data collection methods are very precise, this is really needed according to the needs of village officials, the impact of this socialization is to increase the knowledge of village officials in managing village finances as well as possible.

Artificial Intelligence for Computer Vision in Surgery: A Call for Developing Reporting Guidelines.

Artificial Intelligence for Computer Vision in Surgery: A Call for Developing Reporting Guidelines.

COMFORT communication in the ICU: Pilot test of a nurse-led communication intervention for surrogates.

This study was designed to investigate the feasibility, acceptability, and preliminary efficacy of a nurse-led communication intervention among surrogates in the intensive care unit (ICU) guided by the COMFORT (Connect; Options; Making meaning; Family caregivers; Openings; Relating; Team) communication model. As frontline communicators, nurses experience communication difficulties with surrogates who face complex informational and emotional barriers when making decisions for critically ill patients in the ICU. However, research on effective nurse communication focusing on both curative and end-of-life (EOL) care is lacking in the literature. A single-centre two-group pretest-posttest quasi-experiment. The total sample included 41surrogates of adult ventilated patients. Twenty participants were allocated to the intervention group who received a daily 20-min telephone call with content based on the COMFORT communication model. Twenty-one participants comprised the control group who received usual care. Participants completed a questionnaire before and after the study measuring satisfaction, anxiety and depression, decisional conflict, and quality of communication. The Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) checklist was followed for nonrandomised controlled trials. The intervention was feasible, with 19 of 20surrogates completing the follow-up surveys, and 48 telephone conversations completed (48% of the planned phone calls). Surrogates' satisfaction was higher in the intervention group than in the control group after adjusting for the selected covariates (25.43 and 24.15, respectively; p=.512). Preliminary efficacy outcomes favouring the intervention included quality of communication with healthcare providers, but not surrogates' perceived depression/anxiety and decisional conflicts. Implementation of the intervention is feasible, acceptable, and favourable among surrogates to improve quality of communication with healthcare providers in the ICU. Further research is needed to determine whether the intervention could be implemented by nurses to improve surrogates' outcomes in other ICUs.

Improving Reproducibility to Meet Minimal Information for Studies of Extracellular Vesicles 2018 Guidelines in Nanoparticle Tracking Analysis.

Nanoparticle tracking analysis (NTA) has been one of several characterization methods used for extracellular vesicle (EV) research since 2006. Many consider that NTA instruments and their software packages can be easily utilized following minimal training and that size calibration is feasible in-house. As both NTA acquisition and software analysis constitute EV characterization, they are addressed in Minimal Information for Studies of Extracellular Vesicles 2018 (MISEV2018). In addition, they have been monitored by Transparent Reporting and Centralizing Knowledge in Extracellular Vesicle Research (EV-TRACK) to improve the robustness of EV experiments (e.g., minimize experimental variation due to uncontrolled factors). Despite efforts to encourage the reporting of methods and controls, many published research papers fail to report critical settings needed to reproduce the original NTA observations. Few papers report the NTA characterization of negative controls or diluents, evidently assuming that commercially available products, such as phosphate-buffered saline or ultrapure distilled water, are particulate-free. Similarly, positive controls or size standards are seldom reported by researchers to verify particle sizing. The Stokes-Einstein equation incorporates sample viscosity and temperature variables to determine particle displacement. Reporting the stable laser chamber temperature during the entire sample video collection is, therefore, an essential control measure for accurate replication. The filtration of samples or diluents is also not routinely reported, and if so, the specifics of the filter (manufacturer, membrane material, pore size) and storage conditions are seldom included. The International Society for Extracellular Vesicle (ISEV)'s minimal standards of acceptable experimental detail should include a well-documented NTA protocol for the characterization of EVs. The following experiment provides evidence that an NTA analysis protocol needs to be established by the individual researcher and included in the methods of publications that use NTA characterization as one of the options to fulfill MISEV2018 requirements for single vesicle characterization.

NIMG-38. MEASURING ADHERENCE TO TRIPOD OF ARTIFICIAL INTELLIGENCE PAPERS IN THE GLIOMA SEGMENTATION

Abstract PURPOSE Generalizability, reproducibility and objectivity are critical elements that need to be considered when translating machine learning models into clinical practice. While a large body of literature has been published on machine learning methods for segmentation of brain tumors, a systematic evaluation of paper quality and reproducibility has not been done. We investigated the use of “Transparent Reporting of studies on prediction models for Individual Prognosis Or Diagnosis” (TRIPOD) items, among papers published in this relatively new and growing field. METHODS According to PRISMA a literature review was performed on four databases, Ovid Embase, Ovid MEDLINE, Cochrane trials (CENTRAL) and Web of science core-collection first in October 2020 and a second time in February 2021. Keywords and controlled vocabulary included artificial intelligence, machine learning, deep learning, radiomics, magnetic resonance imaging, glioma, and glioblastoma. The publications were assessed in order to the TRIPOD items. RESULTS 37 publications from our database search were screened in TRIPOD and yielded an average score of 12.08 with the maximum score being 16 and the minimum score 7. The best scoring item was interpretation (item 19) where all papers scored a point. The lowest scoring items were the title, the abstract, risk groups and the model performance (items number 1, 2, 11 and 16), where no paper scored a point. Less than 1% of the papers discussed the problem of missing data (item 9) and the funding of research (item 22). CONCLUSION TRIPOD analysis showed that a majority of the papers do not score high on critical elements that allow reproducibility, translation, and objectivity of research. An average score of 12.08 (40%) indicates that the publications usually achieve a relatively low score. The categories that were consistently poorly described include the ML network description, measuring model performance, title details and inclusion of information into the abstract.

Developing Specific Reporting Standards in Artificial Intelligence Centred Research.

Developing Specific Reporting Standards in Artificial Intelligence Centred Research.

Development and Internal Validation of a Preoperative Prediction Model for Sentinel Lymph Node Status in Breast Cancer: Combining Radiomics Signature and Clinical Factors.

PurposeTo develop and internally validate a nomogram combining radiomics signature of primary tumor and fibroglandular tissue (FGT) based on pharmacokinetic dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinical factors for preoperative prediction of sentinel lymph node (SLN) status in breast cancer patients.MethodsThis study retrospectively enrolled 186 breast cancer patients who underwent pretreatment pharmacokinetic DCE-MRI with positive (n = 93) and negative (n = 93) SLN. Logistic regression models and radiomics signatures of tumor and FGT were constructed after feature extraction and selection. The radiomics signatures were further combined with independent predictors of clinical factors for constructing a combined model. Prediction performance was assessed by receiver operating characteristic (ROC), calibration, and decision curve analysis. The areas under the ROC curve (AUCs) of models were corrected by 1,000-times bootstrapping method and compared by Delong’s test. The added value of each independent model or their combinations was also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. This report referred to the “Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis” (TRIPOD) statement.ResultsThe AUCs of the tumor radiomic model (eight features) and the FGT radiomic model (three features) were 0.783 (95% confidence interval [CI], 0.717–0.849) and 0.680 (95% CI, 0.604–0.757), respectively. A higher AUC of 0.799 (95% CI, 0.737–0.862) was obtained by combining tumor and FGT radiomics signatures. By further combining tumor and FGT radiomics signatures with progesterone receptor (PR) status, a nomogram was developed and showed better discriminative ability for SLN status [AUC 0.839 (95% CI, 0.783–0.895)]. The IDI and NRI indices also showed significant improvement when combining tumor, FGT, and PR compared with each independent model or a combination of any two of them (all p < 0.05).ConclusionFGT and clinical factors improved the prediction performance of SLN status in breast cancer. A nomogram integrating the DCE-MRI radiomics signature of tumor and FGT and PR expression achieved good performance for the prediction of SLN status, which provides a potential biomarker for clinical treatment decision-making.

Estimation of the Share of Net Expenditures on Insulin Captured by US Manufacturers, Wholesalers, Pharmacy Benefit Managers, Pharmacies, and Health Plans From 2014 to 2018

Recent US media and policy attention on insulin affordability has focused on the role of manufacturers in setting prices; however, the role of other drug distribution intermediaries in determining prices has received less attention. To estimate the share of net expenditures on insulin captured by manufacturers, wholesalers, pharmacy benefit managers, pharmacies, and health plans from 2014 to 2018. This cross-sectional study of the US insulin market was conducted in 2020 using 2014-2018 data from multiple sources, including list and estimated net prices from SSR Health for 32 insulin products, mean use weights from a commercial pharmacy claims database, mean acquisition costs and reimbursements from the Centers for Medicare & Medicaid Services, mean spread and share of rebates retained by pharmacy benefit managers from state Medicaid and drug transparency reports, and profit margins from the public filings of distribution system participant companies. Participants were insulin manufacturers, drug wholesalers, pharmacies, pharmacy benefit managers, and health plans. Mean list and net insulin prices, mean net expenditures on insulin, share of expenditures retained by each distribution system participant. Between 2014 and 2018, mean list prices of 32 insulin products increased by 40.1% (from $19.60 to $27.45), while mean net prices received by manufacturers decreased by 30.8% (from $10.53 to $7.29). Net expenditures per 100 units of insulin increased by 3.2% (from $15.11 to $15.59) while the share of a hypothetical $100 insulin expenditure accruing to manufacturers decreased by 33.0% (from $69.71 to $46.73) and the share accruing to health plans decreased by 24.7% (from $13.82 to $10.40). The share of insulin expenditures retained by pharmacy benefit managers increased by 154.6% (from $5.64 to $14.36), the share retained by pharmacies increased by 228.8% (from $6.21 to $20.42), and the share retained by wholesalers increased by 74.7% (from $4.63 to $8.09). Results of this cross-sectional study of the distribution of insulin expenditures suggest that policies to control insulin costs should consider all entities throughout the insulin distribution system. Manufacturers represented a decreasing share of insulin expenditures, and pharmacies, pharmacy benefit managers, and wholesalers accounted for a growing share; all entities play a role in increasing insulin costs.

Effect of an evidence-based poster on the knowledge of delirium and its prevention in student nurses: A quasi-experimental study

Background A major barrier to nurses adopting evidence-based practice (EBP) has been the limited awareness of evidence underpinning clinical practice, often due to poor access and understanding of the literature base. To address this, we piloted the development of educational posters summarizing the evidence base around clinical practices to see if they help nurses better understand the rationale behind their care. Our first poster focused on the evidence supporting the management of delirium in older persons, specifically delirium identification and its prevention. Objective To examine the effect of an evidence-based poster education on the delirium knowledge of student nurses. Design A prospective two-armed quasi-experimental study. Methods 188 student nurses were recruited in December 2017. Participants were alternated to receive either an evidence-based poster education session or a reflective education session as a control. Both groups were assessed on their general knowledge on delirium, knowledge on delirium detection and knowledge on delirium prevention. This was conducted both before exposure to either the intervention or control, and one week after exposure. Unpaired t-tests with 95% confidence intervals (CI) were applied to compare the mean change in pre-test and post-test delirium knowledge. We used the Transparent Reporting of Evaluations with Nonrandomized Designs (TREND) checklist to report our methods and findings. Results Students in the poster education group reported greater improvements in mean scores of delirium identification (Mean increase = 1.0, p = 0.007, 95% CI: 0.3-1.6), delirium prevention (Mean increase = 1.6, p < 0.001, 9% CI: 1.0-2.2) and overall delirium knowledge (Mean increase = 2.7, p < 0.001, 95% CI: 1.5-3.8) than students in the control. Conclusion Summarised research evidence within a poster format can increase student nurses’ access to the evidence base. This has shown to increase their knowledge to guide their clinical practice. Impact statement Exposure to poster summaries of research evidence underpinning delirium care increases student nurses’ clinical knowledge of delirium identification and prevention.