Healthcare Failure Research Articles

Access and adherence to cancer care through the Veteran Affairs Close to Me cancer care service.

111 Background: Diagnosing and treating more than 56,000 Veterans annually, the Veterans Affairs (VA) National Oncology Program (NOP) is one of the nation’s largest integrated providers of oncology services. Within VA, oncology care and parenteral therapies are primarily offered at VA Medical Centers (VAMCs) in urban areas, often inaccessible to rural patients. Issues with travel distance, parking, time, and caregiver support can prevent patients from adhering to treatment appointments as evidenced by historical annual No-Show rates for VAMC infusion clinics that range from 1.1-6.7%. To mitigate potential barriers to access, NOP launched the Close to Me (CTM) cancer care service. The service deploys Registered Nurses (RNs) to local VA Community Based Outpatient Clinics (CBOCs) to administer cancer treatments. VA has opened 23 CTM clinics across 5 geographical regions since October 2021. Methods: The CTM service was implemented at VAMCs with NOP providing direct project management, safety assessment and resources such as a comprehensive implementation toolkit, standard operating procedures, care coordination tools, a tiered risk drug matrix and a standardized Healthcare Failure Mode and Effect Analysis risk evaluation. RNs followed a standardized workflow to assess patient eligibility and verify treatment clearances. Access to care was reported by numbers of unique patients and treatment visits. Patient appointment adherence was monitored by no-show rates documented in the electronic health record. Infusion reactions and medical emergencies were reported by RNs. Travel miles saved was calculated by subtracting the difference in miles round trip from the patient’s home to main VAMC and from home to CBOC, then multiplied by number of treatment visits to CBOC. Results: From October 2021 through April 2024, 23 new CTM clinics opened across 5 regions. 515 unique patients were enrolled for a total of 1,916 patient visits. Treatment appointment no-show rate was 1% across all CTM clinics. The most commonly administered medication classes include gonadotropin-releasing hormone agonist (30%), immune globulin (14.5%), immune checkpoint inhibitors (9.3%) and bisphosphonates (8.3%). Zero infusion reactions or medical emergencies were recorded across 1,430 treatments administered. A total of 204,000 travel miles were saved by patients enrolled in this program. Conclusions: The CTM cancer care service safely optimizes current VA CBOC infrastructure to increase access points to oncology treatment for patients across various geographical regions. CTM reduced travel burden for patients and increased ability to adhere to treatment appointments as evidenced by the service’s low no-show rate. These consistent results across CTM services at VAMCs nationwide have cemented CTM as a safe and effective treatment delivery model to expand access. CTM will be scaled to an additional 30 regions by end of 2025.

Interactions between the context of a health-care organisation and failure: the situational impact of failure on organisational learning

PurposeThis study aims to explore how health-care organisations learn from failures, challenging the common view in management science that learning is a continuous cycle. It focuses on understanding how the context of a health-care organisation and the characteristics of failure interact.Design/methodology/approachSystematically collected empirical studies that examine how health-care organisations react to failures, both in terms of learning and non-learning, were reviewed and analysed. The key characteristics of failures and contextual factors are categorised at the individual, team, organisational and global level.FindingsSeveral factors across four distinct levels are identified as being susceptible to the situational impact of failure. In addition, these factors can be used in the design and development of innovations. Taking these factors into account is expected to stimulate learning responses when an innovation does not succeed. This enhances the understanding of how health-care organisations learn from failure, showing that learning behaviour is not solely dependent on whether a health-care organisation possesses the traits of a learning organisation or not.Originality/valueThis review offers a new perspective on organisational learning, emphasising the situational impact of failure and how learning occurs across different levels. It distinguishes between good and bad failures and their effects on a health-care organisation’s ability to learn. Future research could use these findings to study how failures influence organisational performance over time, using longitudinal data to track changes in learning capacity.

The application of healthcare failure mode and effect analysis in reducing medication errors in the emergency department of Regional Public Hospital

Introduction: Medication or medication error is an essential issue in the world of health, both in the world and in Indonesia. The emergency department is a health service unit that provides emergency services 24 hours non-stop, which is very likely for medication errors to occur. Most medication incident errors can be prevented. One method that can be used is of healthcare failure mode and effect analysis (HFMEA). Applying HFMEA in hospitals helps avoid and identify possible or potential problems or errors in healthcare services. Methods: This qualitative study used the HFMEA approach to conduct risk analysis regarding medication events and errors in the emergency department (ER), at Regional Public Hospital, Central Java. Brainstorming and focus group discussion were conducted with all members of the HFMEA team at the regional public hospitals’ ER in Central Java following HFMEA guidelines. Results: Four process flows in ER drug or medication administration services were identified, encompassing 14 service sub-processes and 57 failure modes. Of the 57 failure modes, only 34 were subjected to hazard analysis, and only 24 failure modes required control measures. From these data, four control strategies were obtained. Conclusion: This study found 24 failure modes need to be addressed and suggested four control strategies, including enterprise risk management formats according to the needs of ER’ health workers, improving ER service management, improving standard operational procedures for medical services, and improving pharmacy management.

Proactive patient safety: enhancing hospital readiness through simulation-based clinical systems testing and healthcare failure mode and effect analysis

BackgroundRecognizing and identifying latent safety threats (LSTs) before patient care commences is crucial, aiding leaders in ensuring hospital readiness and extending its impact beyond patient safety alone. This study evaluated the effectiveness of a combination of Simulation-based Clinical Systems Testing (SbCST) with Healthcare Failure Mode and Effect Analysis (HFMEA) with regard to mitigating LSTs within a newly constructed hospital.MethodsThree phases of the combined SbCST and HFMEA approach were implemented across all hospital settings. The scenarios tested system functionalities, team responses, and resource availability. The threats thus identified were categorized into system-related issues, human issues, and resource issues, after which they were prioritized and addressed using mitigation strategies. Reassessment confirmed the effectiveness of these strategies before hospital commissioning.ResultsMore than 76% of the LSTs were mitigated through the combined approach. System-related issues, such as nonfunctional communication devices and faulty elevators, were addressed by leadership. Human issues such as miscommunication and nonadherence to hospital policy led to improvements in interprofessional communication and teamwork. Resource issues, including missing equipment and risks of oxygen explosion, were addressed through procurement, maintenance, and staff training for equipment preparation.ConclusionThe SbCST and HFMEA were highly effective with regard to proactively identifying and mitigating LSTs across all aspects of hospital preparedness. This systematic and comprehensive approach offers a valuable tool for enhancing patient safety in new healthcare facilities, thereby potentially setting a new standard for proactive hazard identification and risk management in the context of healthcare construction and commissioning.

COVID-19 healthcare success or failure? Crisis management explained by dynamic capabilities

IntroductionThis paper presents a structured review of the use of crisis management, specifically examining the frameworks of surge capacity, resilience, and dynamic capabilities in healthcare organizations. Thereafter, a novel deductive method based on the framework of dynamic capabilities is developed and applied to investigate crisis management in two hospital cases during the COVID-19 pandemic.BackgroundThe COVID-19 pandemic distinguishes itself from many other disasters due to its global spread, uncertainty, and prolonged duration. While crisis management in healthcare has often been explained using the surge capacity framework, the need for adaptability in an unfamiliar setting and different information flow makes the dynamic capabilities framework more useful.MethodsThe dynamic capabilities framework’s microfoundations as categories is utilized in this paper for a deductive analysis of crisis management during the COVID-19 pandemic in a multiple case study involving two Swedish public hospitals. A novel method, incorporating both dynamic and static capabilities across multiple organizational levels, is developed and explored.ResultsThe case study results reveal the utilization of all dynamic capabilities with an increased emphasis at lower organizational levels and a higher prevalence of static capabilities at the regional level. In Case A, lower-level managers perceived the hospital manager as brave, supporting sensing, seizing, and transformation at the department level. However, due to information gaps, sensing did not reach regional crisis management, reducing their power. In Case B, with contingency plans not initiated, the hospital faced a lack of management and formed a department manager group for patient care. Seizing was robust at the department level, but regional levels struggled with decisions on crisis versus normal management. The novel method effectively visualizes differences between organizational levels and cases, shedding light on the extent of cooperation or lack thereof within the organization.ConclusionThe researchers conclude that crisis management in a pandemic, benefits from distributed management, attributed to higher dynamic capabilities at lower organizational levels. A pandemic contingency plan should differ from a plan for accidents, supporting the development of routines for the new situation and continuous improvement. The Dynamic Capabilities framework proved successful for exploration in this context.

Translation and cultural adaptation of the HFMEA into European Portuguese

ABSTRACT Introduction Health organizations are faced with daily challenges, requiring them to provide a quality service, ensuring effectiveness and efficiency. Risk management is one of the conditioning factors to achieve this purpose, ensuring preventive actions for all processes, promoting the identification of risk to the mitigation of its consequences for the patient, professionals, or organization. Patient safety is a priority and healthcare organizations should be concerned with the implementation of methodologies and tools to promote risk management, such as Healthcare Failure Mode and Effects Analysis (HFMEA). HFMEA has a high potential for risk management in healthcare organizations, with a proactive, prospective, and continuous approach to improvement. Objective Translation and adaptation of the HFMEA instrument into European Portuguese. Materials and methods A methodological study was carried out based on the proposal presented by Beaton and followed the recommendations of the International Test Commission and World Health Organization. Results The HFMEA 2021 was linguistically translated and culturally adapted to the new context ensuring reliability, content validity was assured by a group of experts, which ensured semantic, idiomatic, experimental, and conceptual equivalence between the original instrument and the translation. Conclusions HFMEA 2021 was successfully translated and adapted to European Portuguese, allowing its application.

Medication Error Prevention Using Healthcare Failure Mode And Effect Analysis At Clinical Pharmacy Installation

Medication error is the second most common patient safety incident worldwide. Medication errors can be defined as unintentional failures in medication services that have the potential to cause harm to patients. Maintaining safe health services is highly dependent on the ability of service providers to proactively conduct patient safety risk analysis, one of which is using the Healthcare Failure Mode and Effect Analysis (HFMEA) method. This study was aimed at obtaining the HFMEA design as an effort to prevent medication errors at Company X Clinical Pharmacy Installation. The research method used is qualitative research with a specific type of Operations Research. Data collected by in-depth interviews, observation, secondary data analysis, and focus group discussion. The results of this study found factors that cause medication errors to occur from organizational factors and staff factors. These results then analyzed for the HFMEA design which obtained 11 risks that required attention and then 14 action plans are made to overcome them. This study successfully developed HFMEA design to prevent medication error in Company X Clinical Pharmacy Installation.

Descriptive feedback with targeted education to improve telephonic escalation of care: a simulation-based study

BackgroundAwareness of communication failures in healthcare has necessitated the implementation of standardized, validated handover tools such as Identification, Situation, Background, Assessment, Recommendation (ISBAR). Although educational sessions improve communication, the effectiveness of individualized care escalation communication training is unknown. The primary aim was to conduct a simulation-based study to assess individualized one-on-one communication training for junior medical doctors for improving care escalation in pediatric emergencies. The secondary aim was to assess the evaluation of the training.MethodsThe prospective observational study assessed participants pre- and post-intervention. In Session One, participants presented a written case scenario telephonically to two senior pediatricians. Fifty participants were scored using an 18-item checklist based on the ISBAR tool and “free text” responses. Immediately following case presentations, participants completed individualized one-on-one 30-minute educational sessions regarding self-reflection, didactic teaching, and constructive feedback based on the ISBAR. Session Two included a second case presentation and reassessment. We conducted qualitative analysis of supervisor’s feedback on performance and trainee doctor’s evaluation of the training.ResultsThere was significant improvement in 8 of the 18 components of the ISBAR checklist. All elements of care escalation were significantly improved, and overall communication was higher post-intervention (P < 0.001); however, no improvement was noted in participants’ explorations of differential diagnoses (P = 0.263). The qualitative analysis identified themes of improved urgency in seeking senior support and conversational clarity from supervisors, and improved intervention quality and self-confidence from participants.ConclusionsIndividualized communication training may improve pediatric emergency care escalation and communication among junior doctors.

Operationalizing the Women-Centred HIV Care Model for trans women and persons with transfeminine experience living with and affected by HIV: a qualitative study

Background The Women-Centered HIV Care (WCHC) Model and associated toolkits were created to address the health care barriers and disparities that women and gender diverse people living with HIV experience. Since trans women and transfeminine people experience disproportionately high rates of HIV acquisition (in comparison to their cisgender peers) amidst biologic, social, political, and historical factors that affect their general care experiences negatively, more research is needed. Aim We aimed to obtain feedback on the WCHC Model regarding the acceptability, applicability, usability, gaps, and potential adaptations needed to meet the needs of trans women and gender diverse people with transfeminine experience. Methods Our study was grounded in community-based research principles and intersectionality frameworks. We conducted semi-structured interviews with 17 trans women and transfeminine people residing in Ontario, Canada. We analyzed the data using a descriptive qualitative content analysis approach. Results Participants were largely satisfied with the WCHC Model. However, participants were concerned with the model’s implementation due to a lack of knowledge among healthcare providers regarding trans women’s experiences within broader social contexts. Simultaneously, participants affirmed the need for care providers to offer person-centered care – a central component of the WCHC Model. Lastly, participants spoke to the healthcare system limitations and failures that disproportionately affected trans women and posed significant barriers to WCHC access and engagement. Discussion Our findings demonstrate that trans women perceive successful healthcare delivery as combining holistic care frameworks – like the WCHC Model – with healthcare providers’ understanding of individual and community needs. There is a need for policy reform to improve the healthcare system. We offer reflections and recommendations for improving healthcare for trans women.

Proactive Risk Management using Healthcare Failure Mode Effect Analysis Tool to Improve Medication Management Process

Proactive risk management program is essential to maintain the quality and safety of patient care, treatment, and services within a healthcare system. According to the Joint Commission, hospitals need to adopt a proactive approach for risk management and develop risk mitigation strategies to reduce or eliminate the potentially harmful impact of possible risk. There are multiple tools that can be used for proactive analysis. Leaders of Evercare hospital Dhaka selected Healthcare FMEA tool to identify the potential failure modes in the current medication management process as it is one of the complex and high processes in healthcare settings. A multidisciplinary Healthcare FMEA team was formed comprising physician, nurse, pharmacist, quality, IT personnel and senior managements of EHD to conduct Healthcare FMEA. After completing Healthcare FMEA, twenty failure modes(n-20) and fifty-nine potential causes(n-59) of failure modes were detected in existing medication management process of EHD. The hazardous score was Two hundred &amp; seventeen (n-217). There were Twelve major failures modes with higher hazardous score. Healthcare FMEA team members decided to eliminate major failures and actions were taken to control these failures. The main objective of this study is to maintain the medication error of EHD within the target (2/1000 patient days) by implementing required strategies and redesigning existing medication management process. The limitation of this study was it is a time-consuming process, it only helps to identify the possibilities of fail; it does not eliminate them, additional efforts are required to develop corrective action. Pulse Vol.15, 2023 P: 28-33

Healthcare workers' perceptions about the use of mobile health technologies in public health facilities in Lagos, Nigeria.

Mobile health has enormous potential in healthcare due to the increasing use of mobile phones in low- and middle-income countries; its effective deployment, uptake, and utilization may result in improved health outcomes, including a reduction in neonatal deaths. However, there is a suboptimal uptake of mobile health technologies among healthcare workers in low-resource settings like Nigeria, which are often context-specific. To investigate healthcare workers' perceptions of mobile health technologies in public health facilities in Lagos, Nigeria. A qualitative study was conducted, and data were collected through six focus group discussions with 26 healthcare workers (doctors, nurses, and community health extension workers) from three public health facilities in Lagos, Nigeria. The collected data were analyzed using a thematic approach, where themes and subthemes were created. Although the participants acknowledged that mobile health enhances patient-provider communication and saves time, they identified altering of healthcare workers' routine practices, information overload, power and network failure, skepticism, lack of trust, and concerns over diagnostic accuracy as potential barriers to its uptake. Addressing healthcare workers' perceptions of mobile health technologies may enhance the deployment and uptake of such solutions in Nigeria and similar low-resource settings. Developers and implementers of such can use them to create new or enhance existing mobile health solutions to better meet the needs and requirements of healthcare workers in low- to middle-income health settings, such as Lagos, Nigeria.

Healthcare Failure Mode and Effect Analysis in Surgery Setting: A Bibliometrics Analysis and Literature Review.

In the ever-evolving healthcare landscape, the imperative to ensure patient safety has driven the adoption of robust safety approaches. One of the most popular methods is Healthcare Failure Mode and Effect Analysis (HFMEA). This study aims to conduct a bibliometric analysis of HFMEA research in a surgery setting to identify relevant authors, topics, and journals, highlighting the scholarly collaboration trends in this area. This analysis can provide valuable insights into the current state of research, emerging trends, and future research directions. The data was acquired online from the PubMed database on December 16th, 2023. The downloaded data were analyzed using Google Sheets to predict trends. The publication output was then analyzed using VOSviewer. Subsequently, Biblioshiny was used to analyze the characteristics of the study, productive author, institution, and country; thematic map analysis; and topic timeline analysis. This study analyzes 25 documents spanning 2005 to 2022, reflecting a collaborative effort involving 155 contributors. The upward trend in annual scientific publications, notably the surge from 2014 onwards and significant peaks in 2019 and 2022, underscores the growing recognition of HFMEA in enhancing patient safety within surgical environments. The prominent influence from prolific authors like Ahmed K, leading institutions such as King's College London, and the substantial contributions from Norway and the USA in shaping the HFMEA research landscape. This study contributes valuable insights that can shape the trajectory of HFMEA in the evolving landscape of surgical healthcare, ensuring enhanced patient safety and quality improvement.

Reducing the risk of NHS disasters

How could we better use public inquiries to stem the recurrence of healthcare failures? The question seems ever relevant, prompted this time by the inquiry into how former nurse Letby...

Healthcare failure mode and effects analysis and cost-minimization analysis of three pharmaceutical services

ObjectiveThe main purpose of this study was to analyze and compare three different medication delivery methods used by the outpatient care unit of a hospital pharmacy, namely health center collection, community pharmacy collection and home delivery. The secondary purpose was to compare the economic cost of those methods for the Spanish health service. MethodA failure mode and effects analysis was carried out to attain the primary objective. For the secondary objective, an in-depth analysis was performed of the economic costs associated with each program using a cost-minimization analysis. ResultsThe failure mode and effects analysis resulted in scores of 184, 170 and 126 points for the health center collection, home delivery and community pharmacy collection programs, respectively. The economic evaluation, for its part, rendered estimated costs of €18,434.52, €11,417.08 and €7,986.52 for home delivery, health center collection and community pharmacy collection services, respectively. ConclusionsThe results of the study indicated that collection at the community pharmacy was the program associated to the lowest risk, most likely due to the crucial role of the pharmacist regarding the custody and preservation of medicines. As regards cost, dispensation at the community pharmacy was also associated with the lowest cost. Nevertheless, this finding was biased by the fact that, given the generous collaboration of pharmaceutical distributors during the COVID-19 pandemic, the cost of transport and delivery to the pharmacy during the study period was zero. Further economic analyses are required to evaluate the costs of community pharmacy delivery and determine their impact on the public health system in cases where transport costs are different from zero.

Profiles of patients with myelomeningocele admitted to the neonatal unit at Universitas Academic Hospital in Bloemfontein, South Africa

&#x0D; &#x0D; &#x0D; &#x0D; Background. Myelomeningocele (MMC) is a common neural tube defect with significant sequelae. There are limited recent data on the mortality and morbidity of MMC in South Africa (SA).&#x0D; Objective. To describe the outcomes and characteristics of patients with MMC admitted to the neonatal unit at Universitas Academic Hospital (UAH) in Bloemfontein, SA.&#x0D; Methods. A retrospective, descriptive study which included 53 patients with MMC admitted to the neonatal unit between 1 January 2017 and 31 December 2019 was conducted. Electronic patient records were reviewed. Data included outcomes, length of stay, complications and maternal and infant characteristics.&#x0D; Results. The inpatient mortality rate was 11.3% (n=6/53). The median length of stay was 18 days. Notable MMC complications included hydrocephalus (88.7%; n=47/53), Chiari malformation type II (44.7%; n=21/47), lower-limb paralysis (84.9%; n=45/53), lower-limb deformities (60.4%; n=32/53), meningitis (52.8%; n=28/53), neuropathic bladder (37.7%; n=20/53) and loss of anal tone (41.5%; n=22/53). MMC repair was performed in 62.2% (n=33/53) and 27.3% (n=9/33) developed complications. Wound sepsis and breakdown were the most common complications (18.2%, n=6/33), with a median 8 days to complications. Antenatal sonar was not performed in 62% (n=31/50) of cases. MMC was detected antenatally in 20% of cases.&#x0D; Conclusion. The inpatient mortality rate in thisstudy was lower than the mortality rates reported in other low- and middle-income countries although significant morbidity was identified. A lack of quality antenatal care and access to antenatal sonars were barriers to early detection of MMC. Other healthcare system infrastructural failures may be contributory, which highlights the need for ongoing inter- sectoral collaboration for prevention, early detection and management of MMC to improve patient outcomes.&#x0D; &#x0D; &#x0D; &#x0D;

The Effect of Nursing Intervention Based on HFMEA Model on the Prevention of Radiation Dermatitis: A Randomized Controlled Study

Radiationdermatitis is one of the most common complications in patients received radiotherapy. Previous studies shown that incidence of radiation induced dermatitis (RD) is 95%. HFMEA (Healthcare Failure Mode and Effect Analysis) is a new model of nursing management. Many studies reported that HFMEA could reduce incidence of complications and adverse events, and significantly improve patient satisfaction. From March 2023 to October 2022, patients received radiotherapy in our center were recruited in this study. Participants were randomly divided into control group (N = 60) and observation group (N = 60) in a ratio of 1:1. Patients in the control group were given routine skin care, health education before radiotherapy and skin care manual during radiotherapy. Based on the standard care, a HFMEA-based nursing intervention was adopted in the observation group by the following methods: Set up HFMEA care team. HFMEA team is composed of head nurses, wound specialist nurses, psychotherapists, etc. The members of the group searched the literature, case analysis and brainstorming to find out the potential failure reasons in every process of nursing radiotherapy patients in the past. Implementation of targeted measures to improve the corresponding: all patients with radiation dermatitis baseline assessment, focus on high-risk patients to shift, regular guidance medication, responsible nurses check the management of patients' skin every day to strengthen the attention of medical staff and patients' family members to radiation dermatitis. The degree of skin injury, pain and psychological status were compared between the two groups at the end of radiotherapy. A total of 120 patients were enrolled in this study. Grade 1 RD was the most common in the observation group at the end of radiotherapy, and Grade 2 and 3 skin RD were less in the observation group than in the control group. There was not significant difference in the scores of SAS and SDS between the two groups before and after nursing (P > 0.05). In the observation group, the SAS scores (44.10±11.25 vs. 32.29 ± 7.72, P = 0.016) and SDS scores (40.98 ± 9.12 vs. 30.11 ± 5.23, P = 0.013) were significantly higher than the control group after nursing(P<0.05). The scores of SAS and SDS in the Observation Group were significantly lower than those in the control group. The scores of SAS in the Observation Group VS the control group were 32.29 ± 7.72 VS 39.09 ± 9.37 after nursing, SDS scores of Observation Group VS control group (30.11 ± 5.23 VS 38.76 ± 7.52, P<0.05). The visual analogue scale (Vas) score in the observation group was significantly lower than that in the control group (2.37 ± 0.45 VS 4.02 ± 0.53, P & Lt; 0.001), and the satisfaction degree of patients in the observation group was significantly higher than that in the control group (96.67% VS 80%, p = 0.004). HFMEA model could effectively reduce incidence of RD, eliminate negative emotion, relieve pain and improve nursing satisfaction.

Applying the healthcare failure mode and effects analysis approach to improve the quality of an organised colorectal cancer screening programme.

The first level of a colorectal cancer (CRC) screening process was systematically analysed using the Healthcare Failure Mode and Effects Analysis (HFMEA) approach by a multidisciplinary team aiming to improve the programme quality. The study was conducted at the Local Health Authority of Bologna, Northern Italy. Seven brainstorming sessions were conducted and all the activities performed were recorded on a FMEA worksheet consisting of individual records reporting the specific phases of the analysed process along with associated activities, possible failure modes, their causes and effects, the obtained risk priority numbers (RPNs) and the control measures to plan. Twenty-three failure modes, 14 effects and 12 possible causes were identified. Nine failure modes were prioritised according to the RPN obtained; most resulted in possible false-negative faecal immunochemical test (FIT) results (66.7%), followed by sample loss (22.2%) and not reaching the entire target population (11.1%). This leads to 66.7% of corrective/preventive actions being applied to the phase of returning the stool sample by the citizen. For this phase reorganisation, the local pharmacies were involved not only as FIT kit delivery points but also as specimen collection and sending points to the laboratory. These organisational changes allowed the introduction of complete traceability of kits and specimens flow, as well as temperature control. A re-evaluation of the prioritised failure modes 6 months after launching the implemented screening process showed that HFMEA application decreased the risk of potential errors by 75.9%. HFMEA application in CRC screening programme is a useful tool to reduce potential errors.

Quantum machine learning‐based framework to detect heart failures in Healthcare 4.0

AbstractQuantum machine learning (QML) is an emerging field that combines the power of quantum computing with machine learning (ML) techniques to solve complex problems. In recent years, QML algorithms have shown tremendous potential in various applications such as image recognition, natural language processing, health care, finance, and drug discovery. QML algorithms aim to reduce computation costs and solve complex problems beyond the scope of classical machine learning algorithms. In this article, we study the performance of two QML algorithms, that is, quantum support vector classifiers (QSVC) and variational quantum classifiers (VQC), for chronic heart disease prediction in Healthcare 4.0. The performance of the two classifiers is assessed using different evaluation metrics like accuracy, precision, recall, and F1 score. The authors concluded the superior performance of QSVC over VQC with an accuracy of 82%.

47: Using Healthcare Failure Modes and Effects Analysis and in-situ simulation to identify latent safety threats in a new pediatric ECMO program

47: Using Healthcare Failure Modes and Effects Analysis and in-situ simulation to identify latent safety threats in a new pediatric ECMO program

Predicting emergency department visits and hospitalizations for patients with heart failure in home healthcare using a time series risk model.

Little is known about proactive risk assessment concerning emergency department (ED) visits and hospitalizations in patients with heart failure (HF) who receive home healthcare (HHC) services. This study developed a time series risk model for predicting ED visits and hospitalizations in patients with HF using longitudinal electronic health record data. We also explored which data sources yield the best-performing models over various time windows. We used data collected from 9362 patients from a large HHC agency. We iteratively developed risk models using both structured (eg, standard assessment tools, vital signs, visit characteristics) and unstructured data (eg, clinical notes). Seven specific sets of variables included: (1) the Outcome and Assessment Information Set, (2) vital signs, (3) visit characteristics, (4) rule-based natural language processing-derived variables, (5) term frequency-inverse document frequency variables, (6) Bio-Clinical Bidirectional Encoder Representations from Transformers variables, and (7) topic modeling. Risk models were developed for 18 time windows (1-15, 30, 45, and 60days) before an ED visit or hospitalization. Risk prediction performances were compared using recall, precision, accuracy, F1, and area under the receiver operating curve (AUC). The best-performing model was built using a combination of all 7 sets of variables and the time window of 4days before an ED visit or hospitalization (AUC = 0.89 and F1 = 0.69). This prediction model suggests that HHC clinicians can identify patients with HF at risk for visiting the ED or hospitalization within 4days before the event, allowing for earlier targeted interventions.