Optimal Health Care Delivery Research Articles

The recommended patient syndrome: Charting new frontiers.

Very important person (VIP) syndrome, or recommended patient syndrome (RPS), is a phenomenon in healthcare where well-intentioned efforts to enhance care inadvertently result in harm. Celebrities, physicians, and political leaders often receive preferential treatment, leading to potentially unnecessary interventions. This review delves into its causes, manifestations, consequences, real-life instances, prevention, and management, considering the shifting paradigm of recent advances in the medical field. We conducted a qualitative and critical review by searching databases such as PubMed, Scopus, and Google Scholar, as well as online news outlets, exploring available data and literature, including journal articles and news articles published at any time on VIP syndrome. Twenty articles were found relevant and analyzed. Manifestations of VIP syndrome range from over- to under-treatment, disrupting established healthcare systems. Consequences encompass increased costs, heightened risks, and diminished satisfaction for patients and healthcare teams. Real-life instances, exemplified by Michael Jackson's case, highlight unintended complications. Prevention strategies advocate transparent resource allocation and adherence to established guidelines. A written VIP patient management plan, involving the hospital's command center, security, and press spokesperson, is crucial. Proposed directives underscore the importance of valuing medical skills, teamwork, effective communication, and resisting external pressures. This short communication underscores the necessity of systematically addressing VIP syndrome to ensure fair, ethical, and optimal healthcare delivery. By addressing this issue in an organized way, healthcare providers can work towards treating all patients equally, following ethical guidelines, and providing the best possible care to everyone, regardless of their status or influence. Future research should focus on developing standardized protocols for managing VIP patients, incorporating ethical considerations and evidence-based practices.

Knowledge and perception of mHealth medication adherence applications among pharmacists and pharmacy students in Jazan, Kingdom of Saudi Arabia.

The advances in digital health, including mobile healthcare (mHealth) medication adherence applications (MApps), have been demonstrated to support medication adherence and improve health outcomes. This study aims to evaluate the knowledge and perception of the MApps among pharmacists and pharmacy students. An online cross-sectional survey was conducted among 223 pharmacists and pharmacy students in the Jazan region of Saudi Arabia between 1st and 30th April 2023. The survey collected information about the participants' socio-demographics, knowledge, and perception of the MApps. Among the 223 participants included in the study, 105 (47.1%) were pharmacists and 118 (52.9%) were pharmacy students. Most participants were females (72.6%) and aged 18-30 (70.4%). About half of the participants had poor knowledge of the MApps [pharmacists (48.0%) and students (42.0%)] and mainly encountered Medisafe (18.1%) or Pills (17.0%) MApps, respectively. Pharmacy students showed significantly higher knowledge of MApps (p = 0.048), especially the Pills (p = 0.022) than pharmacists. However, the pharmacists had significantly higher knowledge of MyMeds (p = 0.001) than pharmacy students. Most participants had a positive perception of the usefulness of the MApps (pharmacists, 79.0%; students 80.0%). Notably, over 85% of the participants expressed willingness to know and provide guidance on MApps, with over 50% willing to recommend it to the patients. There was no significant difference in perception between the pharmacists and pharmacy students (p>0.05). In conclusion, the study demonstrates limited knowledge with a positive perception of mHealth medication adherence applications among pharmacists and pharmacy students. Integrating digital adherence tools like the MApps into pharmacy training could significantly improve professional practice mHealth competencies, and optimize healthcare delivery and patient outcomes.

Optimizing Healthcare Delivery: Navigating the Challenges and Benefits of the Satellite Medical Model in Modern Hospital Management

In the rapidly evolving landscape of healthcare management, the Satellite Medical Model has emerged as a strategic solution to enhance service delivery by decentralizing care through a network of satellite facilities connected to a central hub hospital. This model not only improves accessibility and optimizes resource utilization but also addresses workforce shortages, particularly in underserved regions. Rooted in the hub-and-spoke design from the transportation sector, the Satellite Medical Model facilitates efficient healthcare services, allowing primary care units to manage routine cases while more complex conditions are referred to specialized facilities. Despite its advantages, the implementation of this model faces significant challenges, including technical issues related to data security and interoperability, financial constraints, and operational complexities. This paper explores the potential of the Satellite Medical Model in modern hospital management, examining both its benefits and challenges. By identifying strategic approaches to mitigate these barriers, this study aims to provide healthcare leaders with actionable insights to effectively adopt this model, ultimately leading to improved patient outcomes and greater operational efficiency in healthcare delivery.

Burnout and associated factors among nurses in psychiatric and general tertiary hospitals in Botswana: A cross-sectional study.

Research has consistently documented that nurses are at a higher risk for developing burnout syndrome due to the nature of their jobs. The high prevalence of burnout among nursing staff negatively affects healthcare delivery. Nurses experiencing burnout cannot provide quality care or actively participate in health promotion, and those experiencing emotional exhaustion are unlikely to be able to tend to the emotional needs of patients. The study aimed to determine the prevalence and factors associated with burnout syndrome among nursing staff in Botswana referral general and psychiatric hospitals. A cross-sectional survey was conducted among 249 nursing staff working in a referral psychiatric and general hospital. The job satisfaction survey, Maslach burnout inventory, and the OCEAN-20 were used to assess job satisfaction, burnout occurrence, and personality traits, respectively. A researcher-designed sociodemographic questionnaire was used to capture demographic data. Variables identified to be associated with burnout on bivariate analyses were entered into a regression analysis to determine to what extent these factors predicted burnout. The prevalence of emotional exhaustion, depersonalization, and reduced personal accomplishment was 65.7%, 56.9%, and 54%, respectively. Being in a general hospital, neuroticism, poor operating condition, and poor communication predicted emotional exhaustion, R 2 = 28%, F (9, 229) = 9.937, p < 0.001. Depersonalization was predicted by neuroticism and poor operating conditions, R 2 = 17%, F (9, 229) = 4.709, p < 0.001. Reduced personal achievement was significantly predicted by the number of people in the household, time at the current hospital, agreeableness, and nature of work, R 2 = 21%, F (7, 203) = 7.875, p < 0.001. Our findings highlight the need for interventions to be developed to address burnout among nursing staff to optimize healthcare delivery.

Unlocking the potentials of digital twins for optimal healthcare delivery in Africa

Abstract Advances in big data analysis, the Internet of Things and simulation technology have led to a surge in interest in digital twin technology, which creates virtual clones of physical entities across several industries. The technological revolution with digital twins, incorporating Internet of Things, big data analysis and simulation technologies, holds the potential for predictive insights, real-time monitoring and increased operational efficiency across the healthcare industry. This paper explores the potential of digital twins to improve healthcare delivery and health outcomes in Africa. It examines their applications in various health sectors, explores their feasibility and highlights the potential challenges associated with their implementation while proposing sustainable recommendations.

Integration technologies in laboratory information systems: A systematic review

Clinical laboratories have evolved with technological advancements through integrating various subsystems into Health Information Systems (HIS), particularly the Laboratory Information System (LIS). The LIS automates processes, manages results, and interfaces with healthcare information sources. Challenges include workflow inefficiencies and data interpretation issues. Despite increased data accessibility, managing clinical data across systems remains complex. Integrating laboratory machines into LIS is essential for optimizing healthcare delivery, requiring effective integration technologies. This study aims to synthesize the existing empirical studies on the utilization of integration technologies for Software-to-Software (S2S) communication in automating clinical laboratory processes. This study systematically examined integration technologies in LIS using PubMed and following PRISMA 2020 guidelines. The three-phase methodology included a scoping analysis, methodological analysis, and a gap analysis, focusing on S2S communication, interoperability frameworks, data standards, communication protocols, and challenges in LIS integration technologies. Analysis of 28 sample studies revealed a complex landscape in LIS integration shaped by end-users, care providers, and researchers. Clinical laboratories prioritize integration, focusing on patient data and sustainability. Standards like HL7 and FHIR ensure interoperability. Eleven methodologies highlight system development in Health Information Systems (HIS). Interoperability is a common objective, with 22 out of 28 studies achieving success. Challenges include limited generalizability, poor validation, and post-implementation modifications. Issues like security, data incompatibility, and evolving standards persist.

A Comparative Analysis of Telerehabilitation and Telemedicine Utilization During the COVID-19 Pandemic in Poland: Trends, Patterns, and Implications.

The study aimed to examine the influence of COVID-19 on the adoption of teleservices in Poland, with a focus on contrasting patterns between rehabilitation and ambulatory care settings. We conducted a retrospective analysis of a national dataset to assess trends in telehealth use from 2020 to 2022. The use of teleservices peaked in April 2020 in both sectors. The share of the teleservices in the period of October 2020-December 2022 was much higher in the ambulatory (average 7,8%) than the rehabilitation sector (average 0,16%). Although, the analysis showed a moderate relationship between COVID-19 incidence and telehealth utilization (Spearman's rho from 0.39 and 0.52). Our findings demonstrate no statistically significant difference in Spearman's rho values between ambulatory care and rehabilitation, indicating a similar strength of response to the pandemic waves. Our findings underscore the importance of telehealth services in ensuring healthcare accessibility during times of crisis, emphasizing their role in facilitating continuity of care amidst pandemic-related disruptions. This study contributes to the understanding of telehealth utilization trends during the COVID-19 pandemic, offering insights into the adaptive responses of healthcare systems to unprecedented challenges. Further research is warranted to explore the long-term implications of telehealth use and to inform strategies for optimizing healthcare delivery in post-pandemic contexts.

Care fragmentation is associated with increased mortality after ileostomy creation

BackgroundIleostomy is the mainstay treatment option for various gastrointestinal conditions. Given the increased risk of post-discharge complications and high readmission rates that can be further aggravated by receiving care at different facilities (care fragmentation), further examination is necessary. We thus used a national cohort to explore the associations of care fragmentation among ileostomy patients experiencing adverse outcomes and increased hospitalization expenditures. MethodsAll adult hospitalizations for ileostomy were tabulated from the 2016 to 2020 Nationwide Readmissions Database. Those readmitted within 90 days after discharge were included for analysis. Patients treated at a different facility than the original location where the index ileostomy was performed were categorized into the care-fragmented cohort. Multivariable regressions were developed to characterize the association of the care-fragmented cohort with postoperative outcomes, readmissions, and expenditures. ResultsOf 52,254 patients with ileostomy creation hospitalizations with 90-day nonelective readmission, 9,045 (17.3%) experienced care fragmentation. Following risk adjustment, those experiencing care fragmentation faced increased odds of mortality (adjusted odds ratio 1.81, 95% confidence interval 1.54–2.12), cardiac (adjusted odds ratio 1.63, 95% confidence interval 1.42–1.85), respiratory (adjusted odds ratio 1.71, 95% confidence interval 1.53–1.91), infectious (adjusted odds ratio 1.33, 95% confidence interval 1.23–1.43), and thromboembolic (adjusted odds ratio 1.28, 95% confidence interval 1.13–1.45) complications. Furthermore, patients experiencing care fragmentation were more likely to have increased hospitalization costs ($1,700, 95% confidence interval 0.8–2.5). ConclusionCare fragmentation in ileostomy patients demonstrated an increased risk for mortality, postoperative complications, and increased hospitalization expenses. To mitigate risks for adverse outcomes, future studies should evaluate the impacts of inter-hospital communication with the goal of improving care continuity and optimizing healthcare delivery for care-fragmented populations.

Machine learning in healthcare strategic management: a systematic literature review

PurposeThis study specifically seeks to investigate the strategic implementation of machine learning (ML) algorithms and techniques in healthcare institutions to enhance innovation management in healthcare settings.Design/methodology/approach The papers from 2011 to 2021 were considered following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. First, relevant keywords were identified, and screening was performed. Bibliometric analysis was performed. One hundred twenty-three relevant documents that passed the eligibility criteria were finalized.Findings Overall, the annual scientific production section results reveal that ML in the healthcare sector is growing significantly. Performing bibliometric analysis has helped find unexplored areas; understand the trend of scientific publication; and categorize topics based on emerging, trending and essential. The paper discovers the influential authors, sources, countries and ML and healthcare management keywords.Research limitations/implications The study helps understand various applications of ML in healthcare institutions, such as the use of Internet of Things in healthcare, the prediction of disease, finding the seriousness of a case, natural language processing, speech and language-based classification, etc. This analysis would help future researchers and developers target the healthcare sector areas that are likely to grow in the coming future.Practical implications The study highlights the potential for ML to enhance medical support within healthcare institutions. It suggests that regression algorithms are particularly promising for this purpose. Hospital management can leverage time series ML algorithms to estimate the number of incoming patients, thus increasing hospital availability and optimizing resource allocation. ML has been instrumental in the development of these systems. By embracing telemedicine and remote monitoring, healthcare management can facilitate the creation of online patient surveillance and monitoring systems, allowing for early medical intervention and ultimately improving the efficiency and effectiveness of medical services.Originality/value By offering a comprehensive panorama of ML's integration within healthcare institutions, this study underscores the pivotal role of innovation management in healthcare. The findings contribute to a holistic understanding of ML's applications in healthcare and emphasize their potential to transform and optimize healthcare delivery.

How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications.

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

Health Policy and Planning in Health Management System

Health policy and planning play pivotal roles in the effective management of healthcare systems. These aspects encompass the formulation, implementation, and evaluation of strategies and regulations to optimize healthcare delivery. Robust health policies ensure equitable access, quality care, and cost-effectiveness, while planning entails resource allocation, infrastructure development, and workforce distribution. Successful health management systems hinge on evidence-based policies, stakeholder engagement, and adaptability to evolving health challenges. This abstract highlights the critical interplay between policy formulation and strategic planning, emphasizing their indispensable contributions to achieving efficient, accessible, and sustainable healthcare services.

Optimization of guideline-directed medical therapies in patients with diabetes and chronic kidney disease.

Diabetes is the leading cause of chronic kidney disease (CKD) and kidney failure worldwide. CKD frequently coexists with heart failure and atherosclerotic cardiovascular disease in the broader context of cardio-kidney-metabolic syndrome. Diabetes and CKD are associated with increased risk of all-cause and cardiovascular death as well as decreased quality of life. The role of metabolic and hemodynamic abnormalities has long been recognized as an important contributor to the pathogenesis and progression of CKD in diabetes, while a more recent and growing body of evidence supports activation of both systemic and local inflammation as important contributors. Current guidelines recommend therapies targeting pathomechanisms of CKD in addition to management of traditional risk factors such as hyperglycemia and hypertension. Sodium-glucose cotransporter-2 inhibitors are recommended for treatment of patients with CKD and type 2 diabetes (T2D) if eGFR is ≥20ml/min/173m2 on a background of renin-angiotensin system inhibition. For patients with T2D, CKD, and atherosclerotic cardiovascular disease, a glucagon-like peptide-1 receptor agonist is recommended as additional risk-based therapy. A non-steroidal mineralocorticoid receptor antagonist is also recommended as additional risk-based therapy for persistent albuminuria in patients with T2D already treated with renin-angiotensin system inhibition. Implementation of guideline-directed medical therapies is challenging in the face of rapidly accumulating knowledge, high cost of medications, and lack of infrastructure for optimal healthcare delivery. Furthermore, studies of new therapies have focused on T2D and CKD. Clinical trials are now planned to inform the role of these therapies in people with type 1 diabetes (T1D) and CKD.

Piloting patient-reported outcome measures for evaluation of the Irish Chronic Disease Programme

Abstract Background The Irish National Integrated Care Programme for Chronic Disease (ICPCD) aims to deliver end-to-end, patient-centred care across three clinical programmes; Heart, Respiratory and Diabetes. Patient-reported outcome measures (PROMs) are a means of objectively measuring changes in patients’ subjectively-perceived health status over time in response to services. As such, PROMs facilitate service monitoring and evaluation and are an important tool for the ICPCD to ensure optimal, patient-centred, value-based healthcare delivery. Methods To select the most appropriate PROMs instrument for use across ICPCD, comprehensive literature review was undertaken followed by key stakeholder consultation in winter 2022. Following consideration against a set of pre-determined criteria the EQ-5D-5L, a well-validated, reliable PROMs instrument, was selected as the most appropriate PROMs instrument for use. Study design involved pilot implementation of EQ-5D-5L in one ICPCD ambulatory care hub service followed by mixed methods evaluation of staff experience of the pilot. Results The pilot was conducted from April to June 2023 among a socio-demographically diverse sample of patients attending their first and last episode of care with the ICPCD diabetic patient education service in Galway. Following service attendance there was a significant aggregate improvement in self-reported overall health rating but no significant change in self-reported mobility, self-care, usual activities, pain/discomfort or anxiety/depression. Predominant staff concerns included staff and patient burden and the need for adequate staff resourcing and information technology support. Conclusions In conjunction with key national stakeholders findings from the pilot will be used to support the development of a PROMs implementation plan at scale for adoption across all ICPCD services. Ultimately national implementation will support the ongoing delivery of high quality patient-centred care within ICPCD services. Key messages • PROMs facilitate service evaluation and are an important tool for the Irish National Integrated Care Programme for Chronic Disease (ICPCD) to ensure optimal patient-centred healthcare delivery. • This pilot will support PROMs implementation at scale across ICPCD services and ultimately reinforce the ongoing delivery of high-quality, value-based, integrated healthcare.

Associations of a current Australian model of dietetic care for women diagnosed with gestational diabetes and maternal and neonatal health outcomes

BackgroundGestational diabetes mellitus (GDM) is a significant public health burden in Australia. Subsequent strain on healthcare systems is widespread and current models of care may not be adequate to provide optimal healthcare delivery. This study aimed to assess a current model of dietetic care with maternal and neonatal outcomes.MethodsHospital medical record data from The Women’s Hospital, Melbourne, for women with GDM (n = 1,185) (July 2105-May 2017) was retrospectively analysed. Adjusted linear and logistic regression were used to analyse associations between the number of dietitian consultations and maternal and neonatal health outcomes.ResultsHalf of all women (50%) received two consultations with a dietitian. 19% of women received three or more consultations and of these women, almost twice as many were managed by medical nutrition therapy (MNT) and pharmacotherapy (66%) compared with MNT alone (34%). Higher odds of any maternal complication among women receiving 3 + consultations compared to those receiving zero (OR = 2.33 [95% CI: 1.23, 4.41], p = 0.009), one (OR = 1.80 [95% CI: 1.09, 2.98], p = 0.02), or two (OR = 1.65 [95% CI: 1.04, 2.60], p = 0.03) consultations were observed. Lower odds of infant admission to the Neonatal Intensive Care Unit (NICU) were observed among women receiving one (OR = 0.38 [95% CI: 0.18, 0.78], p = 0.008), two (OR = 0.37 [95% CI: 15 0.19, 0.71], p = 0.003), or three + consultations (OR = 0.43 [95% CI: 0.21, 0.88], p = 0.02), compared to no consultations.ConclusionThe optimal schedule of dietitian consultations for women with GDM in Australia remains largely unclear. Alternate delivery of education for women with GDM such as telehealth and utilisation of digital platforms may assist relieving pressures on the healthcare system and ensure optimal care for women during pregnancy.

Understanding how and under what circumstances integrated knowledge translation works for people engaged in collaborative research: metasynthesis of IKTRN casebooks.

Interaction and collaboration between researchers, patients/public, clinicians, managers and policy-makers are necessary to enhance the relevance and use of research, improve planning, and optimize healthcare delivery and outcomes. The Integrated Knowledge Translation Research Network (IKTRN) published four casebooks from 2019 to 2021, describing varied approaches to research co-production. Our aim was to examine the case studies to extend existing theoretical and empirical perspectives about how co-production works. We used metasynthesis, a qualitative research design that includes seven iterative steps (clarify the purpose, delineate the case studies included, extract and code the data, derive themes from the coded data, determine the relationships of the themes to research co-production, synthesize the concepts, and build theory). A total of 35 cases was reviewed. The aggregate findings of this metasynthesis identified multiple contextual and process factors, barriers, and facilitators that influence integrated knowledge translation (IKT), and a range of IKT activities that increased the likelihood of success of co-production during research. In comparing the findings from the metasynthesis with existing literature, we found a number of consistencies, but also new information about barriers, facilitators, IKT activities and outcomes, thereby adding to our understanding about factors that influence co-production. This metasynthesis provided concrete examples to optimize co-produced clinical and health system research. More research is needed to fully understand how to overcome some challenging modifiable barriers, establish relationships, facilitate communication, overcome power differentials and create processes for knowledge-users working across boundaries (clinical practice and research) to stay engaged and participate fully in research endeavours.

Optimizing Healthcare Delivery: A Model for Staffing, Patient Assignment, and Resource Allocation

The healthcare industry has recently faced the issues of enhancing patient care, streamlining healthcare operations, and offering high-quality services at reasonable costs. These crucial issues include general healthcare administration, resource allocation, staffing, patient care priorities, and effective scheduling. Therefore, efficient staff scheduling, resource allocation, and patient assignments are required to address these challenges. To address these challenges, in this paper, we developed a mixed-integer linear programming (MILP) model employing the Gurobi optimization solver. The model includes staff assignments, patient assignments, resource allocations, and overtime hours to minimize healthcare expenditures and enhance patient care. We experimented with the robustness and flexibility of our model by implementing two distinct scenarios, each resulting in two unique optimal solutions. The first experimental procedure yielded an optimal solution with an objective value of 844.0, with an exact match between the best-bound score and the objective value, indicating a 0.0% solution gap. Similarly, the second one produced an optimal solution with an objective value of 539.0. The perfect match between this scenario’s best-bound score and objective value resulted in a 0.0% solution gap, further affirming the model’s reliability. The best-bound scores indicated no significant differences in these two procedures, demonstrating that the solutions were ideal within the allowed tolerances.

A Study on Sustainable Hospital Supply Chain Management towards Societal Advancement in the Post-Pandemic Era

Abstract— This study delves into the intricate relationships between Hospital Infrastructure Development (HID), Collaboration Information Flow (CIF), Forecasting and Planning Management (FPM), Technology Supply Chain Application (TSCA), Sustainable Hospital Supply Chain Management (SHSCM), and Sustainable Societal Advancement (SSA) within the healthcare sector of Bangladesh. Utilizing a structured questionnaire, data was collected from a diverse group of 22 respondents, including doctors, administrators, and patients. Frequencies Analysis, conducted using IBM SPSS, provided a comprehensive demographic overview, while the Alpha Cronbach test affirmed the reliability of the research instrument with a high value. The fitness index analysis, performed using IBM AMOS software, subsequent modifications based on the Modification Index (MI) results led to a model that closely met the criteria of CMIN, degrees of freedom (df), CMIN/df, incremental fit CFI IFI, and absolute fit RMSEA, underscoring the pivotal role of the aforementioned variables in enhancing SHSCM and contributing to SSA. The findings emphasize the significance of a robust healthcare supply chain in ensuring optimal healthcare delivery and broader societal benefits. This research offers valuable insights for healthcare administrators, policymakers, and stakeholders, providing a roadmap for building resilient, efficient, and sustainable healthcare systems in the post-pandemic era.Keywords—Sustainable Hospital Supply Chain Management (SHSCM), Sustainable Societal Advancement (SSA), IBM SPSS, IBM AMOS.

PEMANFAATAN ARTIFICIAL INTELLIGENCE DALAM BIDANG KESEHATAN

The existence of Artificial Intelligence (AI) technology has changed the landscape in every field, especially in the health sector, optimizing medical data analysis, making diagnoses, and personalizing treatment. This article explores the application of AI in healthcare, highlighting its potential to improve patient outcomes, improve medical decision-making, and optimize healthcare delivery. This article also explores the ethical challenges and considerations associated with the integration of AI in healthcare. The article concludes by looking into the future of AI in healthcare, emphasizing the importance of collaboration between healthcare professionals and AI systems to optimize its potential

Optimizing Healthcare Delivery: Analyzing the Relationship Between Inpatient Medical Record Return Time and Service Effectiveness at Ciremai Hospital

The medical record installation must maintain medical records correctly and appropriately, including the return of medical records. According to the Ministry of Health (2006), the standard for returning inpatient medical records is ≤ 2x24 hours after completion of treatment. Meanwhile, the standard of service effectiveness in the form of time for providing outpatient medical records according to Kepmenkes number 129 of 2008 is ≤ 10 minutes. The purpose of the study was to determine the relationship between inpatient medical record return time and service effectiveness. The research method used is quantitative with a cross-sectional design. The population is 220 medical records of post-inpatient patients who are controlled outpatients at Ciremai Hospital during January 2022. The total sample is 145 using the Slovin formula with the purposive sampling technique. Univariate analysis using frequency distribution and bivariate analysis using the Spearman rank correlation test are used because the data is not normally distributed. The results show that the average time to return inpatient medical records is 115,86 hours, the fastest time is 24 hours, and the longest time is 360 hours. The average service effectiveness in the form of outpatient medical record provision was 222,26 minutes; the fastest time was 3 minutes; and the longest time was 710 minutes. The Spearman rank correlation coefficient is 0,418 with a p-value of 0,000 ≤ 0,05. The conclusion is that there is a relationship with moderate correlation strength between inpatient medical record return time and service effectiveness, with a value of 0,418.

Understanding the Clinical Profile and Hospitalisation Patterns of Residents From Aged Care Facilities: A Regional Victorian Hospital Study.

Introduction Residents of residential aged care facilities (RACFs) are typically frailer than their community-dwelling counterparts. They often present to the emergency department (ED) with varied health issues, frequently leading to hospital admissions. These admissions can exacerbate patient frailty and strain the healthcare system. Despite global efforts to reduce ED presentations from RACFs, effective strategies still need to be discovered. This study examines the clinical profile and hospitalisation patterns of RACF residents in a regional Victorian town. Aims The study aimed to assess the prevalence of ED presentations and representations from RACFs, investigate the causes and outcomes of hospital admissions stemming from these presentations, and evaluate the prevalence of documented (advanced care directives) ACDs within this patient cohort. Methods Following ethical approval, we conducted a retrospective analysis of 467 ED presentations from 310 RACF patients admitted to Goulburn Valley Health's (GVH) ED from January to June 2022. We collected and examined data on demographics, ACD existence, ED presentation characteristics, and hospital admissions, classifying admission reasons into eleven groups. Statistical analysis was performed with GraphPad Prism and IBM SPSS, using inferential tests and logistic regression to assess readmission odds at a significance threshold of p<0.05. Results Our study encompassed 310 patients from multiple RACFs, yielding 467 ED presentations. These constituted 2.28% of total ED visits and 9.85% of those aged 65 and above. Most of the cohort were females (59.4%), aged between 79 and 91. About 98 patients presented multiple times, and 48.2% of presentations led to hospital admissions, with 6.2% of admitted patients succumbing during the hospital stay. A documented ACD was absent in 42.9% of the cohort. Statistically significant results include a correlation between male sex and an increased frequency of ED representations (p=0.0422) and a longer ED stay duration for admitted patients (p<0.0001). No significant associations were found between ACD presence and ED representations, ACD and sex, or between age and duration of stay in the ED. Age did not differ significantly among patients with single or multiple presentations or between patients with or without ACD. Regarding fall-related presentations, no significant sex-based difference in admission rates was found. The duration of stay between surgical and medical admissions was also statistically indifferent. Conclusion Our study highlights the significant utilisation of ED services by RACF residents, mainly males. The substantial percentage of these presentations resulting in hospital admissions underlines the critical nature of these visits. The absence of ACD in a significant portion of the cohort and the lack of its influence on the frequency of representations signal the need for further exploration. The results underline the ongoing challenge of meeting the complex healthcare needs of RACF residents and emphasise the importance of gender-specific interventions and efficient hospital utilisation strategies to optimise healthcare delivery in this population. Future studies should further investigate the underlying reasons for these findings to inform targeted strategies for reducing unnecessary ED visits and hospital admissions. Furthermore, fall-related presentations necessitate comprehensive ED assessments and integrated management approaches.