Effectiveness Of Health Care Delivery Research Articles

Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.

Clinical decision support systems (CDSSs) are designed to assist in health care delivery by supporting medical practice with clinical knowledge, patient information, and other relevant types of health information. CDSSs are integral parts of health care technologies assisting in disease management, including diagnosis, treatment, and monitoring. While electronic medical records (EMRs) serve as data repositories, CDSSs are used to assist clinicians in providing personalized, context-specific recommendations derived by comparing individual patient data to evidence-based guidelines. This targeted literature review (TLR) aimed to identify characteristics and features of both stand-alone and EMR-integrated CDSSs that influence their outcomes and benefits based on published scientific literature. A TLR was conducted using the Embase, MEDLINE, and Cochrane databases to identify data on CDSSs published in a 10-year frame (2012-2022). Studies on computerized, guideline-based CDSSs used by health care practitioners with a focus on chronic disease areas and reporting outcomes for CDSS utilization were eligible for inclusion. A total of 49 publications were included in the TLR. Studies predominantly reported on EMR-integrated CDSSs (ie, connected to an EMR database; n=32, 65%). The implementation of CDSSs varied globally, with substantial utilization in the United States and within the domain of cardio-renal-metabolic diseases. CDSSs were found to positively impact "quality assurance" (n=35, 69%) and provide "clinical benefits" (n=20, 41%), compared to usual care. Among CDSS features, treatment guidance and flagging were consistently reported as the most frequent elements for enhancing health care, followed by risk level estimation, diagnosis, education, and data export. The effectiveness of a CDSS was evaluated most frequently in primary care settings (n=34, 69%) across cardio-renal-metabolic disease areas (n=32, 65%), especially in diabetes (n=13, 26%). Studies reported CDSSs to be commonly used by a mixed group (n=27, 55%) of users including physicians, specialists, nurses or nurse practitioners, and allied health care professionals. Overall, both EMR-integrated and stand-alone CDSSs showed positive results, suggesting their benefits to health care providers and potential for successful adoption. Flagging and treatment recommendation features were commonly used in CDSSs to improve patient care; other features such as risk level estimation, diagnosis, education, and data export were tailored to specific requirements and collectively contributed to the effectiveness of health care delivery. While this TLR demonstrated that both stand-alone and EMR-integrated CDSSs were successful in achieving clinical outcomes, the heterogeneity of included studies reflects the evolving nature of this research area, underscoring the need for further longitudinal studies to elucidate aspects that may impact their adoption in real-world scenarios.

Deep Learning Methods for Detecting Chest X-Ray and CT Scan Abnormalities

Deep learning's quick development has created new opportunities to improve medical image analysis, especially in the identification of anomalies in chest CT and X-ray scans. This work investigates several deep learning techniques designed for this particular purpose to enhance the efficiency and accuracy of diagnosis in medical settings. We explore the use of 3D CNNs, transfer learning, and convolutional neural networks, or CNNs, for the analysis of volumetric CT scan information as well as 2D chest X-ray pictures. Comparative analyses show the benefits and drawbacks of various deep learning architectures for identifying a variety of anomalies, including tumors, tumors in the lungs, pneumonia, and other diseases. We also go over the significance of preprocessing methods, assessment metrics specifically designed for medical picture analysis, and dataset preparation. The results highlight how deep learning has the potential to revolutionize chest imaging diagnostics by facilitating the quicker and more accurate identification of anomalies, which will enhance patient outcomes and the effectiveness of healthcare delivery. To spur additional developments in the deep learning-powered analysis of medical images for chest problems, future research topics, and obstacles in this area are also covered.

Materials for 3D printing in healthcare sector: A review.

Additive Manufacturing (AM) encompasses various techniques creating intricate components from digital models. The aim of incorporating 3D printing (3DP) in the healthcare sector is to transform patient care by providing personalized solutions, improving medical procedures, fostering research and development, and ultimately optimizing the efficiency and effectiveness of healthcare delivery. This review delves into the historical beginnings of AM's 9 integration into medical contexts exploring various categories of AM methodologies and their roles within the medical sector. This survey also dives into the issue of material requirements and challenges specific to AM's medical applications. Emphasis is placed on how AM processes directly enhance human well-being. The primary focus of this paper is to highlight the evolution and incentives for cross-disciplinary AM applications, particularly in the realm of healthcare by considering their principle, materials and applications. It is designed for a diverse audience, including manufacturing professionals and researchers, seeking insights into this transformative technology's medical dimensions.

The Overview on Effectiveness of Quality Enhancement for Enhancing Health Care and Professional Practice

Reorganizing the structure and delivery of services has been a typical focus of initiatives to improve the standard, safety, and effectiveness of health care delivery. Continuous quality improvement (CQI), a technique commonly used in the manufacturing and industrial sectors, has been applied to the health sector. Given the complexity and diversity of health systems, questions about CQI's efficacy persist despite its increased focus. This review evaluates CQI's efficacy in various healthcare environments and looks into the significance of the approach's many elements. Twenty- eight RCTs assessed the effectiveness of different approaches to CQI in a variety of scenarios using a non- CQI comparison. The methodologies used, the duration of the meetings, the participants, and the type of training provided varied throughout the interventions. It was believed that bias might taint any RCT and affect the results. The benefits of CQI compared to a non-CQI comparison on clinical process, patient, and other outcomes were not great, as evidenced by the fact that less than half of RCTs showed any effect. Benefits were usually demonstrated in clinical process metrics; these were impacted by the frequency (weekly), the type of meeting (leaders discussing implementation), and the methodology (Plan-Do-Study-Act, improvement methodology). Studying health disparities caused by socioeconomic status.

Healthcare Providers' Experience with Saudi Arabia's 937 Virtual Medical Call Centers and Telehealth.

This cross-sectional descriptive study evaluates the experiences and perceptions of healthcare providers (HCPs) regarding the 937 medical call center in Saudi Arabia, a key telemedicine initiative. To assess HCP satisfaction, identify challenges, and provide recommendations for improvement. Conducted from November 20th to December 15th, 2022, the study surveyed 454 HCPs, achieving a 90.5% response rate. A majority (86.8%) of respondents were satisfied with the call center, valuing its ease of use and effectiveness in healthcare delivery. However, challenges such as the accuracy of remote medical assessments, the need for clearer telehealth regulations, and concerns over management support and consultation overlaps were identified. The study also highlights the importance of ongoing support and updates, comprehensive telehealth regulations, integration of more medical specialties, and improvements in system integration and data confidentiality. The study underscores the need for strategic enhancements to the 937 call center to further improve healthcare accessibility and efficiency in Saudi Arabia. These enhancements are vital for aligning telehealth services with Saudi Arabia's healthcare objectives under Saudi Vision 2030.

Public-Private Partnership: Optimising the Outcomes for Plastic Surgery in a Resource-Limited Setting at the University of Port Harcourt, (UPTH) Rivers State, Nigeria

Background: Public Private Partnership (PPP) refers to a form of cooperation between public authorities and the world of business which aims to ensure the funding, construction, renovation, management and maintenance of an infrastructure or the provision of better services, better quality, better and better health in a relatively cost- effective manner or approach to the society.  Aim and Objectives: This paper highlights the role of PPP in optimizing outcomes for patients who require plastic surgical services.  Materials and Methods: This study was carried out to bring to light the perennial problems of the health care mixes within a period of 6 months in the Plastics and Reconstructive Surgery unit of The University of Port Harcourt Teaching Hospital. This work looked at the Public Private sector mixes in health care system using Nigeria as a case study.  Results: Cases managed at the public facility alone, cases managed at the private facility alone and the cases managed through the combined effort of both the Private and Public sector (PPP) were analyzed.  Conclusion: Public Private Partnership is key to the success and effectiveness of healthcare delivery in a resource poor setting as the PPP drives the marriage of effectiveness in administration and business prototype in the marriage of government infrastructure and large medical market with turn over into a partnership where the private component brings in the specific funding and equipment and expertise needed to make the medical business model.

To Enhance the Efficiency and Effectiveness of Electronic Health Record for Hospital Management System

Our project hospital management system includes registration of patient's details storing into the system and booking appointments with the doctors and taking care of staff. This website is powerful, flexible, and easy to use. Our software has the facility to give unique IDs to patients and staff. The details of each patient and staff are stored on this website. This interface is user friendly. Here website can be login through username and password. The lost data can be recovered easily. The admin can manage the total website and data is well protected here by admin. It improves the quality and management of the hospitals. The primary goal of a Hospital Management System is to enhance the efficiency and effectiveness of healthcare delivery by providing a centralized platform for managing various aspects of hospital administration, patient care, and related activities. The Hospital Management System encompasses a wide range of functionalities, including patient registration, appointment scheduling, billing and invoicing, electronic health records (EHR), inventory management, and reporting. It leverages information technology to create a seamless flow of information between different departments within the hospital, ensuring smooth communication and coordination.

Impact of Integrated Virtual and Live Nurse Triage on Patient Care Seeking and Health Care Delivery Effectiveness and Efficiency

Impact of Integrated Virtual and Live Nurse Triage on Patient Care Seeking and Health Care Delivery Effectiveness and Efficiency

De-Biased Disentanglement Learning for Pulmonary Embolism Survival Prediction on Multimodal Data.

Health disparities among marginalized populations with lower socioeconomic status significantly impact the fairness and effectiveness of healthcare delivery. The increasing integration of artificial intelligence (AI) into healthcare presents an opportunity to address these inequalities, provided that AI models are free from bias. This paper aims to address the bias challenges by population disparities within healthcare systems, existing in the presentation of and development of algorithms, leading to inequitable medical implementation for conditions such as pulmonary embolism (PE) prognosis. In this study, we explore the diverse bias in healthcare systems, which highlights the demand for a holistic framework to reducing bias by complementary aggregation. By leveraging de-biasing deep survival prediction models, we propose a framework that disentangles identifiable information from images, text reports, and clinical variables to mitigate potential biases within multimodal datasets. Our study offers several advantages over traditional clinical-based survival prediction methods, including richer survival-related characteristics and bias-complementary predicted results. By improving the robustness of survival analysis through this framework, we aim to benefit patients, clinicians, and researchers by enhancing fairness and accuracy in healthcare AI systems.

Smart Health Prediction Using Machine Learning

Machine learning-based smart health prediction is a fast- expanding topic that has the potential to completely change how we identify and treat diseases. We can create systems that can accurately forecast a patient's risk of contracting a disease or their chance of responding to a particular treatment by utilizing machine learning algorithms to examine enormous quantities of medical data.Although they are still in the early stages of research, smart health prediction systems could have a significant influence on how medicine is practiced in the future. Systems for making smart predictions about a person's health have the potential to boost healthcare delivery's effectiveness and quality. We can put preventative measures in place to lower a patient's risk of contracting a disease by precisely anticipating the patient's risk. Smart health prediction systems can also be used to pinpoint people who are most at risk for developing complications from an illness or who are most likely to have poor treatment outcomes. These data can be used to develop personalized treatment plans for patients.

Resilience, sense of danger, and reporting in wartime: a cross-sectional study of healthcare personnel in a general hospital

Background and AimsMaintaining healthcare services and ensuring the presence of healthcare personnel (HCP) during periods of conflict and high-intensity warfare in Israel including the significant security event that occurred on May 2021, pose significant challenges for hospitals in the range of missile attacks. The May 2021 event, marked by intense hostilities and military actions, brought about heightened security escalations and increased risks in the region. Despite the prevailing threat of missile attacks and ongoing security concerns, hospitals in the affected areas were required to sustain their services and uphold care standards. In light of these circumstances, this study aims to identify the factors that influence the percentage of HCP reporting for work during these intense periods of security escalations and wartime in Israel. Specifically, it explores the relationships between resilience, sense of danger, and HCP absenteeism in the context of the ongoing conflict. The findings of this study can provide valuable insights for designing interventions aimed at decreasing HCP absenteeism during security escalations, wartime, and emergency situations, ultimately contributing to the resilience and effectiveness of healthcare delivery in this challenging environment.MethodsDuring a relative calm period from December 2021 to January 2022, a cross-sectional study was conducted at a southern Israeli general hospital, situated within the range of missile attacks in the midst of a longstanding conflict. The study focused on HCP who were employed before May 21, which marked the end of the last war state at that time. The questionnaire, consisting of measures for resilience using the Conor-Davidson scale (CD-RISC 10) and the sense of danger assessed with the Solomon & Prager inventory, was administered online to all hospital employees at Assuta Ashdod Hospital, located in the southern city of Ashdod, Israel. This approach was chosen due to the challenging nature of conducting a study during an existing war, making it impractical to carry out the research during such periods of active war.ResultsIn total, 390 employees completed the survey (response rate of 24%). Of this sample, 77.4% reported fully to work during the last security escalations in May 2021. Most of the sample (84.1%) felt insecure on the way to work. The HCP who reported fully to work had a higher level of resilience than employees who reported partially or did not come to work at all (p = .03). A higher sense of danger in the workplace correlated with a 73% increase in absenteeism (p < .01). Absenteeism (partial or full) was higher among HCP with children who require supervision (p < .01). Hospital preparedness for emergencies as perceived by the employees increased HCP attendance at work (p = .03).ConclusionsHospital management should consider designing programs aimed at potentially strengthening the level of resilience and fostering a greater sense of security among hospital personnel, which might encourage greater attendance at work during wartime, crises, or emergencies.

Exploring the Ethics and Responsibilities of Internship Medical Students in the Doctor-Patient Relationship

As the complexity of medical services and the diversity of patients' needs increase, the doctor-patient relationship is facing unprecedented challenges. As an important part of healthcare delivery, the behavior of medical students-in-training directly affects the quality of the doctor-patient relationship and the effectiveness of healthcare delivery. However, medical students-in-training may feel confused and stressed when faced with ethical challenges and professional responsibilities. This has triggered the need for in-depth research on the professional ethics and responsibilities of medical students-in-training in the doctor-patient relationship. This paper proposes several strategies to improve the professional ethics of medical students in internship, including enhancing professional ethics education, training in communication skills, ethics training through simulation and scenario-based teaching, establishing and adhering to clinical practice guidelines, and mentoring and reflection in practice, to promote the growth of medical students in internship, improve the quality of healthcare services, and maintain a good doctor-patient relationship.

Transforming Healthcare through AI: Unleashing the Power of Personalized Medicine

The healthcare sector now places a lot of emphasis on providing patients with personalized care that is catered to their unique requirements and features. A significant force behind the development and use of customized healthcare is artificial intelligence (AI). This essay examines the use of AI in personalized healthcare and how it can affect several facets of healthcare provision. The study starts out by talking about how AI is being used in diagnostics, emphasizing how machine learning algorithms and the examination of various datasets can improve diagnostic accuracy. It goes into more detail about how AI can be used to create tailored treatment plans, utilizing patient-specific data and predictive analytics to maximize therapeutic results and reduce side effects. Examined are the ethical issues surrounding AI in customized healthcare, such as data privacy, algorithmic bias, and the value of responsibility and openness. The integration of AI into clinical practice is also covered in the study, along with prospects for improving decision-making, streamlining workflow, and overall healthcare delivery effectiveness. The healthcare sector now places a lot of emphasis on providing patients with personalized care that is catered to their unique requirements and features. A significant force behind the development and use of customized healthcare is artificial intelligence (AI). This essay examines the use of AI in personalized healthcare and how it can affect several facets of healthcare provision. The study starts out by talking about how AI is being used in diagnostics, emphasizing how machine learning algorithms and the examination of various datasets can improve diagnostic accuracy. It goes into more detail about how AI can be used to create tailored treatment plans, utilizing patient-specific data and predictive analytics to maximize therapeutic results and reduce side effects. Examined are the ethical issues surrounding AI in customized healthcare, such as data privacy, algorithmic bias, and the value of responsibility and openness. The integration of AI into clinical practice is also covered in the study, along with prospects for improving decision-making, streamlining workflow, and overall healthcare delivery effectiveness.&#x0D; &#x0D;

Impact Of Iot Adoption And Application For Smart Healthcare

The Internet of Things (IoT) is a rapidly growing technology that is transforming the healthcare industry. IoT devices and applications are enabling the collection and analysis of patient data, facilitating remote monitoring and diagnosis, and improving the efficiency and effectiveness of healthcare delivery. This abstract explores the impact of IoT adoption and application for smart healthcare. The study highlights the various applications of IoT in healthcare, such as remote patient monitoring, real-time patient tracking, and medication management. The study reviews the benefits of IoT in healthcare, such as improved patient outcomes, reduced costs, and increased efficiency. The study also examines the challenges of implementing IoT in healthcare, such as data privacy and security concerns, interoperability issues, and regulatory compliance. The study concludes that IoT is transforming the healthcare industry, enabling a new era of smart healthcare delivery. The adoption of IoT in healthcare has the potential to improve patient outcomes, reduce costs, and increase the efficiency and effectiveness of healthcare delivery. However, the challenges of implementing IoT in healthcare cannot be ignored, and the industry must work to address these challenges while harnessing the benefits of this emerging technology. Overall, the potential impact of IoT adoption and application for smart healthcare is significant and holds great promise for the future of healthcare delivery.

Role of pharmacists in healthcare delivery

Pharmacists play a multifaceted role in healthcare delivery, contributing significantly to patient care, medication management, and public health initiatives. This paper explores the diverse responsibilities and contributions of pharmacists within healthcare teams, highlighting their expertise in medication therapy management, preventive care, chronic disease management, and medication access and adherence. Through collaborative practice models, patient education initiatives, and innovative interventions, pharmacists play an integral role in promoting optimal health outcomes and improving the quality, safety, and effectiveness of healthcare delivery.

Time Motion Study to analyse the Medication Management from Prescription to Administration in a Private Hospital at East India

Indian healthcare systems have passing through a state of transition and especially tertiary hospitals face daunting challenges, like evolving technologies and reimbursement policies, and a worsening skilled workforce shortage. A reconsideration of skilled health manpower and work processes holds the potential to affect the efficiency and effectiveness of health care delivery for the foreseeable future. The time and motion study are to understand the time taken in several work stations and used for performance, evaluation, and planning of any process. The Hospital under study was facing some issues of Medication management and there by Patient satisfaction and patient safety was under risk. This is a Cross sectional Observation study. It starts from Medication prescription to Indenting, arranging, dispensing, and finally to administration to the patient. Three Volunteers were recorded the data One at Ward level, One at Pharmacy Level and One at Transportation Level. A total of 80 prescriptions were tracked from different Wards or ICU areas. A total six time were recorded and six duration were found namely D1 (Prescription to Indent Time), D2(Indent to Dispense Time), D3(Dispense to Delivery Time), D4(Delivery to Receiving Time), D5(Receiving to Administration Time) &amp; D6 (Prescription to Administration Time).It was found that average time taken for various process are as D1 – 236 minutes (3 Hrs 56 mints), D2 -120minutes (2 Hrs), D3 – 162 minutes (2 Hrs 42 mints), D4 - 38 min, D5 – 535minutes (8 Hrs 55 mints), &amp; D6 – 1091minutes (18 Hrs 11 mints). In all areas average distribution of five duration are D1(22%), D2(11%), D3(15%), D4(3%) and D5(49%). On detail discussion over interview, it was found that Pharmacist and Nursing Manpower may need optimization. Although an age-old technique, Time Motion study can be used to analyse any process flow to detect the bottlenecks and find the suitable solution to the problems.

Integrating Social and Behavioral Sciences Into the Pakistani Medical Curriculum is Essential

The majority of respondents who took part in a survey were of the opinion that there should be a greater focus placed on behavioural and social sciences within the curriculum of medical schools. This is done to ensure that graduates of medical schools will be able to practise medicine in a manner that is both safe and effective. Despite the fact that behavioural and social sciences make significant contributions to the effectiveness of health care delivery, traditional medical school curricula have not traditionally placed a significant amount of focus on the study of these subjects. This article's objective is to provide the reader with a more in-depth comprehension of the value of social and behavioural sciences in medical education as well as the breadth of their application in a variety of different settings. Additionally, it discusses the areas of social and behavioural sciences that are significant to medicine, as well as the efficacy of incorporating them into the curricula of medical schools in order to educate and train future medical professionals to practise medicine in a manner that is fully informed. Place of Study: Foundation University Islamabad Study Duration: February 2022 to July 2022 Study Design: Empirical research Conclusion: This study examines the importance of teaching future doctors about medicine's social and behavioural aspects. It gives medical school educators the latest information on how to best teach medical students to succeed in the medical industry. Medical educators, administrators, policymakers, and other stakeholders must work together to integrate social and behavioural sciences into medical curricula. Keywords: Medical curriculum's courses, the social and behavioral sciences, and the foundations of medical education.

Some Factors that Influence Doctor-Patient Relationship on Effective Healthcare Delivery in Some Public Health Care Facilities in Ogbia Local Government Area of Bayelsa State, Nigeria.

Background: Trust is a fundamental characteristic of the physician-patient relationship. Patients must trust that their physicians will work in their best interests to achieve optimal health outcomes. The quality of relationship between doctors and patients in government hospitals is fundamental for the several outcomes as regard services rendered by the doctor and those received by the patients and in other to improve the quality of healthcare delivery in public health care sector. The study conducted to determine the some factors that can influence of doctor-patient relationship which would eventually determine the effectiveness of health care delivery in public health centres in Ogbia, Bayelsa State, Nigeria. Methods: A descriptive cross-sectional study design was conducted among patients in Federal Medical Center, Otuoke, General Hospital, Kolo and Cottage Hospital, Otuasega, all in Ogbia Local Government Area of Bayelsa state. Data collection was carried out using both self-administered and interview administered questionnaire. 138 patients were selected for the study. An average of 20 interviews were conducted per clinic day. Results: Numerous factors such as age, gender, level of education, socioeconomic status, cultural and religious beliefs can affect physician-patient relationship. Results of this study demonstrated that communication and trust were the two most Communication and Trust. factors that greatly influenced the effectiveness of health care delivery and many patients were satisfied with the services received from their doctors. Conclusion: Communication and mutual trust between the doctor and patient are of the major factors that influences doctor patient relationship.

Orthopedist involvement in the management of clinical activities: a case study

BackgroundThe rapid shift in hospital governance in the past few years suggests greater orthopedist involvement in management roles, would have wide-reaching benefits for the efficiency and effectiveness of healthcare delivery. This paper analyzes the dynamics of orthopedist involvement in the management of clinical activities for three orthopedic care pathways, by examining orthopedists’ level of involvement, describing the implications of such involvement, and indicating the main responses of other healthcare workers to such orthopedist involvement.MethodsWe selected four contrasting cases according to their level of governance in a Canadian university hospital center. We documented the institutional dynamics of orthopedist involvement in the management of clinical activities using semi-structured interviews until data saturation was reached at the 37th interview.ResultsOur findings show four levels (Inactive, Reactive, Contributory and Active) of orthopedist involvement in clinical activities. With the underlying nature of orthopedic surgeries, there are: (i) some activities for which decisions cannot be programmed in advance, and (ii) others for which decisions can be programmed. The management of unforeseen events requires a higher level of orthopedist involvement than the management of events that can be programmed.ConclusionsBeyond simply identifying the underlying dynamics of orthopedists’ involvement in clinical activities, this study analyzed how such involvement impacts management activities and the quality-of-care results for patients.

Patient Satisfaction With Medical Services Provided at Unani Medicine Hospital, Bengaluru: A Cross-Sectional Study.

In medical care, patient satisfaction is a key indicator of the quality of care. Many studies have agreed on the fact that measuring patient satisfaction is a useful tool for determining the effectiveness of health care delivery and the quality of medical care provided. Hence, present study was aimed to determine the level of patient’s satisfaction with the quality of medical care services rendered in a teaching hospital of Unani medicine. A hospital-based cross-sectional study was conducted at the National Institute of Unani Medicine Hospital, Bengaluru, from April 2019 to October 2019 on 500 patients sampled from various service delivery points of the health facility. Data were gathered through exit interviews of patients after obtaining their written informed consent. A predesigned and pretested questionnaire on patient satisfaction patient satisfaction questionnaire (PSQ-18) was used as a study tool. The overall mean patient satisfaction score was 4.82 ± 0.23. Mean satisfaction was highest in the interpersonal manner (4.94) and communication (4.94), followed by time spent with the doctor (4.91), technical quality (4.87), financial aspect (4.87), accessibility and convenience (4.65), and least in general satisfaction (4.54). No sociodemographic variables were found to correlate significantly with satisfaction score (P > .05). In clinical variables, treatment effectiveness was found to be significantly associated with the satisfaction score (P = .002). The study found that overall patients were highly satisfied with the medical services provided by the health facility. Furthermore, the study finds that treatment effectiveness has a more significant effect on patients’ satisfaction compared with other factors.