Patient Management Process Research Articles

An Activity-Based Costing model applied to the management process of patients with migraine at IRCCS Mondino Foundation

Background and aim: The ageing of the general population, with the increase in chronic diseases, poses the need for using technological innovation to face the growing healthcare needs. The present analysis applied the Activity-Based Costing tool in migraine patients followed at the IRCCS Mondino of Pavia to formalize and quantify the costs of the whole patient’s management process and to estimate the overall economic burden of migraine from the perspective of the National Health Service (NHS). Methods: A two-stage analysis was conducted. The first stage aimed at drawing patient’s pathway, defining all the possible activities and actors involved in the healthcare delivery and treatment for migraine at the IRCCS during year 2022. The second phase was the development of a model to estimate the costs of the entire process by pricing the individual activities. Results: The described model yielded an estimated total annual cost for the overall management of migraine of € 1,222,392, corresponding to a direct cost for a therapy of approximately 6 months per single patient of € 814. The most impactive items on the estimated annual expenditures were hospitalizations, followed by diagnostic examinations after follow-up visits and drugs dispensed by Hospital Pharmacy for home-administration (monoclonal antibodies). Conclusions: This analysis allowed detailing the single activities and resources used in migraine patient’s pathway and then estimating the direct costs sustained by the NHS. The model could be translated to other diseases for optimizing the diagnostic/therapeutic and economic management of assisted patients and improving healthcare resource allocation.

Meta-analysis of the association between sex hormones and pulmonary fibrosis

ABSTRACT Background This study aimed to investigate the association between sex hormones and the risk of pulmonary fibrosis by conducting a meta-analysis of previously published studies. Methods We executed a comprehensive search of the PubMed, Embase, Cochrane Library, and Web of Science databases to locate pertinent studies published up to April 2024. We included studies that reported the association between sex hormones and the risk of pulmonary fibrosis. Standardized mean difference (SMD) with 95% confidence intervals (CIs) were calculated using a random-effects model. Results A total of 10 articles, encompassing 1371 patients, were finally incorporated in this meta-analysis. Based on the evaluation of the included studies, it was observed that the levels of dehydroepiandrosterone sulfate (DHEA-S) (pooled SMD: −0.72, 95% CI: −1.21 to −0.24, p < 0.001), testosterone (pooled SMD: −1.25, CI: −2.39 and −0.11, p < 0.001) and estrogen (pooled SMD: −0.56, 95% CI: −0.96 to −0.15, p < 0.001) were significantly lower in patients with pulmonary fibrosis, whereas the levels of luteinizing hormone (LH) remained unaffected. Publication bias was ruled out through funnel plots. Conclusion This meta-analysis indicates that reduced levels of DHEA-S, testosterone, estrogen may serve as potential risk factors for pulmonary fibrosis. There is a pressing need for additional studies to confirm this association and explore the underlying biological mechanisms. Clinicians should recognize the potential influence of sex hormones in the etiology of pulmonary fibrosis and consider this aspect during the patient management process.

Leveraging graph neural networks for supporting automatic triage of patients

Patient triage is crucial in emergency departments, ensuring timely and appropriate care based on correctly evaluating the emergency grade of patient conditions. Triage methods are generally performed by human operator based on her own experience and information that are gathered from the patient management process. Thus, it is a process that can generate errors in emergency-level associations. Recently, Traditional triage methods heavily rely on human decisions, which can be subjective and prone to errors. A growing interest has recently been focused on leveraging artificial intelligence (AI) to develop algorithms to maximize information gathering and minimize errors in patient triage processing. We define and implement an AI-based module to manage patients’ emergency code assignments in emergency departments. It uses historical data from the emergency department to train the medical decision-making process. Data containing relevant patient information, such as vital signs, symptoms, and medical history, accurately classify patients into triage categories. Experimental results demonstrate that the proposed algorithm achieved high accuracy outperforming traditional triage methods. By using the proposed method, we claim that healthcare professionals can predict severity index to guide patient management processing and resource allocation.

Practical management of disease-related manifestations and drug toxicities in patients with multiple myeloma.

Multiple myeloma (MM) is a very heterogeneous disease with multiple symptoms and clinical manifestations. MM affects mainly elderly patients and is difficult to manage in the presence of comorbidities, polypharmacy, frailty and adverse events of disease-targeted drugs. The rapid changes in MM treatment resulting from constant innovations in this area, together with the introduction of numerous new drugs with distinct mechanisms of action and toxicity profiles, have led to an increased complexity in the therapeutic decision-making and patient management processes. The prolonged exposure to novel agents, sometimes in combination with conventional therapies, makes this management even more challenging. A careful balance between treatment efficacy and its tolerability should be considered for every patient. During treatment, a close monitoring of comorbidities, disease-related manifestations and treatment side effects is recommended, as well as a proactive approach, with reinforcement of information and patient awareness for the early recognition of adverse events, allowing prompt therapeutic adjustments. In this review, we discuss various issues that must be considered in the treatment of MM patients, while giving practical guidance for monitoring, prevention and management of myeloma-related manifestations and treatment-related toxicities.

Bacterial Infections in Intensive Care Units: Epidemiological and Microbiological Aspects.

Intensive care units constitute a critical setting for the management of infections. The patients' fragilities and spread of multidrug-resistant microorganisms lead to relevant difficulties in the patients' care. Recent epidemiological surveys documented the Gram-negative bacteria supremacy among intensive care unit (ICU) infection aetiologies, accounting for numerous multidrug-resistant isolates. Regarding this specific setting, clinical microbiology support holds a crucial role in the definition of diagnostic algorithms. Eventually, the complete patient evaluation requires integrating local epidemiological knowledge into the best practice and the standardization of antimicrobial stewardship programs. Clinical laboratories usually receive respiratory tract and blood samples from ICU patients, which express a significant predisposition to severe infections. Therefore, conventional or rapid diagnostic workflows should be modified depending on patients' urgency and preliminary colonization data. Additionally, it is essential to complete each microbiological report with rapid phenotypic minimum inhibitory concentration (MIC) values and information about resistance markers. Microbiologists also help in the eventual integration of ultimate genome analysis techniques into complicated diagnostic workflows. Herein, we want to emphasize the role of the microbiologist in the decisional process of critical patient management.

An assessment of PET and CMR radiomic features for the detection of cardiac sarcoidosis.

Visual interpretation of PET and CMR may fail to identify cardiac sarcoidosis (CS) with high specificity. This study aimed to evaluate the role of [18F]FDG PET and late gadolinium enhancement (LGE)-CMR radiomic features in differentiating CS from another cause of myocardial inflammation, in this case patients with cardiac-related clinical symptoms following COVID-19. [18F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19 (PC) and 40 CS datasets. Regions of interest were delineated manually around the entire left ventricle for the PET and LGE-CMR datasets. Radiomic features were then extracted. The ability of individual features to correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PC using Mann-Whitney U-tests and logistic regression. Features were retained if the P-value was <0.00053, the AUC was >0.5, and the accuracy was >0.7. After applying the correlation test, uncorrelated features were used as a signature (joint features) to train machine learning classifiers. For LGE-CMR analysis, to further improve the results, different classifiers were used for individual features besides logistic regression, and the results of individual features of each classifier were screened to create a signature that included all features that followed the previously mentioned criteria and used it them as input for machine learning classifiers. The Mann-Whitney U-tests and logistic regression were trained on individual features to build a collection of features. For [18F]FDG PET analysis, the maximum target-to-background ratio (TBRmax ) showed a high area under the curve (AUC) and accuracy with small P-values (<0.00053), but the signature performed better (AUC 0.98 and accuracy 0.91). For LGE-CMR analysis, the Gray Level Dependence Matrix (gldm)-Dependence Non-Uniformity showed good results with small error bars (accuracy 0.75 and AUC 0.87). However, by applying a Support Vector Machine classifier to individual LGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy (0.91 and 0.84, respectively). Using radiomic features may prove useful in identifying individuals with CS. Some features showed promising results in differentiating between PC and CS. By automating the analysis, the patient management process can be accelerated and improved.

A study of pre-analytical errors in a public hospital biochemistry laboratory according to their causes and units

The clinical laboratory is an important stakeholder in the patient management process with a direct impact on patient care by providing evidence and data for diagnosis and treatment. Identifying reliable quality indicators in clinical laboratories is an important step in enabling users to measure the quality of laboratory service. Any error in the pre-analytical process affects other processes and jeopardizes patient safety. This study aimed to examine the number of specimen rejections in clinical laboratories, their reasons, and their range according to the departments. The study was a descriptive retrospective study. The population of the study consisted of samples rejected from the Biochemistry Laboratory of a teaching and research hospital in 2021. Data were analyzed using percentage and frequency analysis. The study recommends that practices to minimize errors in the pre-analytical process should be carried out urgently by the management and a training plan for sample collection should established. Keywords: Clot; hemolysis; patient safety; pre-analytical process; sample rejection.

Current status and prospects for thoracic surgery

The world today is undergoing revolutionary changes in science, technology, and industry. These changes have optimized the surgical procedure for lung cancer treatment into a more minimally invasive, precise, comprehensive, industrialized, and patient-centered manner. The definition of minimally invasive treatment for lung cancer has been expanded from simply reducing the size of the skin incision to reserve the lung function. The principle of precision surgery is emphasized throughout the whole process of patient management including diagnosis and treatment. Multimodality therapy helps narrow the gaps between different disciplines and thus provides more personalized treatment for lung cancer patients. Integration of industrial techniques such as visualization, surgical robot, and artificial intelligence into medical practice will potentially lead to a revolution in thoracic surgical procedure. Today, thoracic surgeons are responsible for establishing a self-reliant surgical practice for Chinese patients with lung cancer. It is necessary to attach great importance to patient-centered care, move forward to review minimally invasive surgical procedure, and foster better practice for lung cancer management by keeping up with cutting-edge research on science and technology in the context of changes and challenges.

Correlation of immediate prevalence of cervical precancers and cancers with HPV genotype and age in women with atypical glandular cells cytology: A retrospective analysis of 369 cases.

This study aims to assess the immediate risk of cervical precancers and cancers in women with atypical glandular cells (AGC) cytology, based on high-risk human papillomavirus (hrHPV) genotypes and age. A retrospective analysis was conducted on 369 cases of AGC with immediate follow-up biopsy results, including 299 AGC-not otherwise specified (NOS) and 70 AGC-favor neoplastic (FN). Among the 369 AGC cases, 127 tested positive for hrHPV (34.4%). The predominant high-risk type was other 11 genotypes (44.1%), followed by 16+ (29.1%), 18/45+ (26.0%), and 16 and 18/45 double-positive (0.79%). Precancers and cancers were detected in 30.4% (112 of 369) and 9.8% (36 of 369) of cases, respectively. The HPV-18/45+ group had notably higher adenocarcinoma in situ and adenocarcinoma (AIS+) prevalence compared to other 11 genotype groups (p<.0001 and p=.001, respectively). The HPV-16+ group showed significantly higher high-grade cervical squamous epithelial lesion and squamous cell carcinoma prevalence than other 11 genotype groups (p<.0001 and p=.017, respectively). Using 40-year cutoff, older women had significantly higher prevalence of abnormal glandular lesion+lesions (17.6% vs. 7.6%, p=.005) and adenocarcinoma (AC) (12.4% vs. 2.5%, p=.001). Using 50-year cutoff, older women had higher prevalence of squamous cell carcinoma (SCC) (3.3% vs. 0.4%, p=.042) and AC (15.2% vs. 5.8%, p=.005). Subgroup analysis revealed that AGC-FN women showed more severe cervical pathology than AGC-NOS women (p<.001). AGC women have a significantly increased risk of cervical precancerous lesions and cancer. HPV genotyping and patient age factors need to be taken into consideration in the clinical management process of AGC patients.

End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks

BackgroundAtrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas- cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil. MethodsWe used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition. ResultsThe deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years. ConclusionWe developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.

Cross-cultural adaptation and psychometric evaluation of a Sinhalese version of the &lt;em&gt;Multidimensional Scale of Perceived Social Support (MSPSS)&lt;/em&gt; in patients with cancer

Introduction: The Multidimensional Scale of Perceived Social Support (MSPSS) is a tool widely used in health surveys to assess social support (SS) perceived by individuals. The lack of an appropriate tool to measure SS perceived by patients with cancer has hindered our understanding of how SS is associated with the management and recovery process of Sri Lankan patients with cancer. The study aimed to examine the reliability and validity of the Sinhalese version of the MSPSS.Methods: Cross-cultural adaptation of the MSPSS was done following the standard guidelines of the process of translation and adaptation set by the World Health Organization. The study sample consisted of 40 patients with cancer at the Teaching Hospital Karapitiya, Galle, Sri Lanka. Data analysis was done using SPSS 25.0. Internal consistency of the overall MSPSS was calculated using Cronbach’s alpha. Test-retest reliability of the tool was also assessed using the intra-class correlation coefficient (ICC). The convergent and divergent validity of the tool was assessed using the Centre for Epidemiological Studies-Depression (CES-D) and the World Health Organization-Quality of Life-Brief Scale (WHOQoL-BREF). Construct validity was assessed using Exploratory Factor Analysis (EFA).Results: The Sinhalese version of MSPSS showed high reliability (Cronbach’s alpha-0.911). The tool showed favourable test-retest reliability (ICC=0.91). The overall MSPSS score was correlated negatively with depressive symptoms (r= -0.459, p&lt;0.001) and positively with dimensions of quality-of-life scores; overall (r=0.674, p&lt;0.001), physical (r=0.426, p&lt;0.001), psychological (r=0.540, p&lt;0.001), social (r=0.674, p&lt;0.001) and environmental quality of life (r=0.767, p&lt;0.001) ensuring strong discriminant/divergent and convergent validity of the Sinhalese version of the MSPSS. Factor analysis extracted three factors (e.g., family, friends, and significant others) explaining 96.65% of the variance.Conclusion: The Sinhalese version of MSPSS is a reliable and valid tool to assess the perceived SS from family, friends, or significant others among patients with cancer.

Compliance of Interventional Radiologists With Interventional Oncology Accreditation Standards.

We aimed to evaluate interventional radiologists' compliance with patient care and the quality management process of cancer patients using a national survey. An electronic survey was designed with questions derived from the core criteria of the International Accreditation System for Interventional Oncology (IASIOS), with the approval of the IASIOS council. Among the interventional radiologists contacted by e-mail through the national association, 34 responded to the questionnaire. The agreement of the participants with the core requirements was evaluated in five questions consisting of 34 articles using the 5-point Likert scale. Regarding the years of experience in interventional radiology (IR), the mean scale for the less than five-year group was 118.4, while that for the group with more than 15 years was 145.17 (p = 0.030). The mean scale of the five- to 15-year-old group was 121.75, versus that of more than 15 years, which was 145.17 (p = 0.028). Thus, significant differences arose between <five years versus >15 years and five to 15 years versus >15 years groups; later groups were more likely to comply. There was also a statistical difference between the groups formed according to the ratio of oncological interventions (<25% vs. 25%-50%) in the daily workload (p = 0.010). Increased experience in IR and more relay on oncological interventions appear to augment compliance with the IASIOS criteria. We believe that interventional radiologists who have distinct territorial praxis could benefit from such a framework with improved self-awareness.

Radiological Imaging Results in HIV-Infected Patients in Mogadishu-Somalia: A Four-Year Retrospective Review

Somalia, which is one of the countries that has been trying to integrate with the rest of the world in terms of many socio-economic parameters, including the field of health in recent years, still faces some important health problems. One of these problems is the difficulties encountered in the early diagnosis and treatment of patients with human immunodeficiency virus (HIV) infection, primarily due to social discrimination and limited treatment access. In this study, it was aimed to examine the findings detected in the radiological imaging examinations requested during the first examination in patients who were diagnosed with HIV for the first time by detecting HIV seropositivity in tests performed for different clinical reasons, and to determine the pathologies caused by advanced disease in patients who did not receive treatment. The study includes 235 patients who were diagnosed for the first time out of 269 patients with HIV confirmed by two different serological diagnostic tests during a previous comprehensive seroepidemiological study, and 14 patients with a suspicious test result for HIV infection but the presence of infection cannot be definitively proven in the absence of molecular diagnostic methods. In retrospective examinations, it was determined that 117 (49.8%) and 13 (92.9%) patients in both groups had radiological imaging (magnetic resonance imaging-MRI, computed tomography-CT, ultrasonography, and chest X-ray), respectively. While 16 of 117 HIV-infected patients had non-specific radiological findings and 53 had normal radiological findings, at least one radiological imaging of 48 patients revealed abnormal radiological imaging findings that may be associated with HIV infection. In these 48 patients, pneumonia findings in thorax CT and chest X-ray examinations, and encephalitis-related findings in patients with central nervous system involvement were the most common anomalies. In addition of these, other abnormal radiological findings included mass lesions compatible with neoplasia, lesions compatible with metastasis, lymphadenopathies, hepatosplenomegaly, and lesions indicating spleen involvement. The presence of similar findings (lesions compatible with pneumonia, encephalitis, and neoplasia) in 9 of 13 patients whose HIV infection could not be confirmed indicates that radiological tests can make significant contributions to clinical evaluations in the management of patients with suspicious laboratory results. The data we present from a region where significant obstacles are encountered in the diagnosis and follow-up of HIV infections due to the fear of discrimination (stigma) of the patients and the lack of molecular tests draw attention to the fact that many patients have advanced lesions when they are diagnosed, and this situation will have negative effects in the patient management and treatment process.

The value of a digital management system for the medical records of patients with cerebral hemorrhage.

The present study aimed to explore the value of a digital management system based on micro digital imaging technology for the medical records of patients with cerebral hemorrhage. A total of 540 patients with intracerebral hemorrhage diagnosed and treated in the hospital from November 2016 to November 2019 were selected as the subjects of this study. A digital management system based on micro digital imaging technology was used to establish how to handle the medical records of these patients. The medical record management process of patients with cerebral hemorrhage comprises five modules: medical record editing, medical record querying, medical record borrowing management, statistical analysis, and system maintenance. The purpose of these is to manage and store digitalised medical records for patients, present the most useful information on the first page of the medical records, monitor the safety of the medical records, and enable real-time data sharing. Establishing a digital management system based on micro digital imaging technology for the medical records of patients with cerebral hemorrhage can effectively enable the preservation and use of these documents. It improves information management, such as data sharing, security, and the overall level of information. This is worth promoting.

Recognizing pathology of renal tumor from macroscopic cross-section image by deep learning

ObjectivesThis study aims to develop and evaluate the deep learning-based classification model for recognizing the pathology of renal tumor from macroscopic cross-section image.MethodsA total of 467 pathology-confirmed patients who received radical nephrectomy or partial nephrectomy were retrospectively enrolled. The experiment of distinguishing malignant and benign renal tumor are conducted followed by performing the multi-subtypes classification models for recognizing four subtypes of benign tumor and four subtypes of malignant tumors, respectively. The classification models used the same backbone networks which are based on the convolutional neural network (CNN), including EfficientNet-B4, ResNet-18, and VGG-16. The performance of the classification models was evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Besides, we performed the quantitative comparison among these CNN models.ResultsFor the model to differentiate the malignant tumor from the benign tumor, three CNN models all obtained relatively satisfactory performance and the highest AUC was achieved by the ResNet-18 model (AUC = 0.9226). There is not statistically significance between EfficientNet-B4 and ResNet-18 architectures and both of them are significantly statistically better than the VGG-16 model. The micro-averaged AUC, macro-averaged sensitivity, macro-averaged specificity, and micro-averaged accuracy for the VGG-16 model to distinguish the malignant tumor subtypes achieved 0.9398, 0.5774, 0.8660, and 0.7917, respectively. The performance of the EfficientNet-B4 is not better than that of VGG-16 in terms of micro-averaged AUC except for other metrics. For the models to recognize the benign tumor subtypes, the EfficientNet-B4 ranked the best performance, but had no significantly statistical difference with other two models with respect to micro-averaged AUC.ConclusionsThe classification results were relatively satisfactory, which showed the potential for clinical application when analyzing the renal tumor macroscopic cross-section images. Automatically distinguishing the malignant tumor from benign tumor and identifying the subtypes pathology of renal tumor could make the patient-management process more efficient.

Lean Six Sigma to reduce the acute myocardial infarction mortality rate: a single center study

PurposeCardiovascular diseases are the leading cause of death worldwide. In Italy, acute myocardial infarction (AMI) is a major cause of hospitalization and healthcare costs. AMI is a myocardial necrosis event caused by an unstable ischemic syndrome. The Italian government has defined an indicator called “AMI: 30-day mortality” to assess the quality of the overall care pathway of the heart attacked patient. In order to guarantee high standards, all hospitals had to implement techniques to increase the quality of care pathway. The aim of the paper is to identify the root cause and understand the mortality rate for AMI and redesign the patient management process in order to improve it.Design/methodology/approachA Lean Six Sigma (LSS) approach was used in this study to analyze the patient flow in order to reduce 30-days mortality rate from AMI registered by Complex Operative Unit (COU) of Cardiology of an Italian hospital. Value stream mapping (VSM) and Ishikawa diagrams were implemented as tools of analysis.FindingsProcess improvement using LSS methodology made it possible to reduce the overall times from 115 minutes to 75 minutes, with a reduction of 35%. In addition, the corrective actions such as the activation of a post-discharge outpatient clinic and telephone contacts allowed the 30-day mortality rate to be lowered from 16% before the project to 8% after the project. In this way, the limit value set by the Italian government was reached.Research limitations/implicationsThe limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.Practical implicationsThe LSS approach has brought significant benefits to the process of managing patients with AMI. Corrective actions such as the activation of an effective shared protocol or telephone interview with checklist can become the gold standard in reducing mortality. The limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.Originality/valueLSS, applied for the first time to the management of cardiovascular diseases in Italy, is a methodology which has proved to be strategic for the improvement of healthcare process. The simple solutions implemented could serve as a guide for other hospitals to pursue the national AMI mortality target.

The Standard Operating Procedures in COVID-19 Pandemic for Periodontal Aerosol-Generating Procedures: A Process Audit.

This study aims to audit the process of patient management with aerosol-generating procedure (ultrasonic scaling) while adherence to the guidelines for health care workers (HCWs) during the coronavirus disease 2019 (COVID-19). Audits records at the Department of Periodontology at University College of Medicine and Dentistry Hospital, Lahore, Pakistan were collected (prospectively) over the period of October 1 to November 30, 2020 (1st cycle) and December 14, 2020 to February 12, 2021 (2nd cycle). The audit was divided into three components based on the guidelines: (1) physical environment, (2) patients/appointments, and (3) COVID standard operating procedures related to HCWs. The recommended physical layout and procedural factors, as suggested by the guidelines for dental clinics, were observed during the first cycle of audit, and discrepancy of ventilation system was fixed after the first cycle. Audit team reported the observance of fallow time three times daily, which revealed 83.3% observance of fallow time.Later in the second cycle when the extraoral high-volume air evacuator was installed, the fallow time was reduced to 15 minutes and not only five procedural slots per day were created but fallow time was also observed 100% of the time. Following the standard guidelines resulted in more efficient working environment and lesser risk for HCWs while performing aerosol-generating procedures.

Needs assessment survey of healthcare providers' perceptions and practices regarding delirium prevention at a university medical center.

Background: Despite the high prevalence and serious implications of delirium, identification, tracking, and documentation of the condition remain a challenge for the health care team, impeding management of patients. This survey is the first phase of a qualitative study to build a conversational agent-based tool for screening and managing delirium-prone patients. Objectives: To assess healthcare providers’ perceptions of delirium management, focusing on patient assessment, therapeutic interventions, and subsequent communication and documentation. Design: An electronic web-based survey was distributed to healthcare providers identified as caring for inpatient acutely ill older adults admitted for medical and orthopedic surgery needs. Respondent contact information was removed to preserve anonymity. Setting: A 1,000 bed university-affiliated teaching hospital in an urban setting. Participants: 23 residents in family practice, 36 residents in internal medicine, and a total of 492 advanced care nurses, nurses, and clinical staff. Approach: The analysis of survey responses provided insight into providers’ current experiences with delirium assessment tools including computerized documentation, as well as their perceptions and attitudes toward delirium prevention. Key results: Most respondents (89%) thought delirium could be prevented, and 85% thought targeting delirium risk factors was helpful. Fifty one percent reported patients’ loneliness and need for companionship, and 65% believed delirium was linked to higher mortality. Only 14% of respondents thought existing Electronic Health Record (EHR) alerts to identify high-risk delirium patients were useful, and 38% thought current delirium assessment protocols were helpful. In addition, 33% of nurses never received formal delirium prevention training, and 48% indicated that they needed improved systems to assess and manage patients at risk for delirium. Conclusion: A majority of providers affirmed that current delirium protocols are helpful; however, existing screening instruments and methods for documentation are cumbersome, resulting in incomplete or limited documentation of episodes. These barriers lead to an understatement of evidence available for continuous improvement of the patient management process.

Postsurgical pain management among obstetrics and gynecology patients in a teaching hospital in Tabriz, Iran: a best practices implementation project.

The purpose of this project was to improve the compliance of patients' pain management process after surgery using evidence-based criteria at the Al-Zahra Educational Hospital in Tabriz. Reducing and relieving pain are among the basic rights of patients, and the management of this component should be one of the basic goals of the patient care team. Inadequate pain control can have many unpleasant consequences for the patient and increase hospital costs. Due to the importance of pain control and a gap in this area, it was decided to implement a project to improve pain control in postoperative patients grounded in evidence-based recommendations. This project was carried out at a Level III hospital in Iran from December 2019 to June 2020. A baseline audit, based on the JBI Practical Application of Clinical Evidence-Based System (JBI PACES) and Getting Research into Practice (GRiP) audit and feedback tool was conducted with 40 patients in the surgery ward of the hospital. After developing the GRiP table (barriers, strategy, resources and outcome), a follow-up audit was done three times. The different stages of the audit were centered in evidence-based criteria. At each stage of follow-up, 40 patients were randomly selected in the postoperative stage. At the baseline audit, out of a total of eight criteria, only criterion 2 corresponded to the audit criteria where there was no pain assessment tool or protocol for pain or for training patients and nurses. Over the three follow-up audits, 100% improvement was achieved in half of the criteria through preparing visual analogue scale pain instruments, and development of a pain protocol and a pain self-care protocol, and a 63% improvement was observed in one of the criteria. Patients' pain decreased from very severe to mild/moderate in the first few hours in 70% of patients after surgery. The use of this best practices implementation project led to the improvement of the postoperative pain management process of patients and the improvement of patient care quality. The use of the JBI Method is recommended to address other current or defective hospital processes.

THE IMPACT OF INDONESIAN MEDICAL DOCTORS NATIONAL COMPETENCY EXAMINATION (IMDNCE) TOWARDS LEARNING AND CLINICAL PRACTICES: A QUALITATIVE STUDY ON THE INTERNSHIP DOCTORS’ PERSPECTIVES

Background: The implementation of the national licensing examination for medical doctors is expected to have a broad impact on doctors and society. Indonesian Medical Doctor National Competency Examination (IMDNCE; Indonesian: Uji Kompetensi Mahasiswa Program Profesi Dokter or UKMPPD) as an ‘exit exam’ in the medical education process may significantly impact learning and clinical practices. The study’s objective was to explore the impact of IMDNCE on both the learning and clinical practices of doctors.Methods: The study subjects were internship doctors who had passed the IMDNCE. Participants were recruited by purposive sampling based on the ownership status of the institution (state/private) and the accreditation of respective medical schools and participants’ gender. The study participants consisted of 41 internship doctors working in 6 regions from 33 different medical schools out of 75 medical faculties in Indonesia.Results: IMDNCE has a positive influence on learning and clinical practice. The IMDNCE process emphasizes standard competencies that must be mastered and patient management process with current evidence that is not always achieved during clinical education, increasing clinical knowledge and skills, and increasing awareness of professional development. IMDNCE also has very well affected in the development of self-confidence and a sense of responsibility which are essential in clinical practice. In addition to psychological influences, IMDNCE improves competence in clinical skills and promotes good medical practice.