Superior Patient Care Research Articles

Innovative Orthopedic Solutions for AI-Optimized Piezoelectric Implants for Superior Patient Care

This research aims to optimize piezoelectric implants for orthopedic applications, enhancing energy harvesting efficiency and mechanical integrity. Our objectives include comparing piezoelectric materials (PZT, PVDF, and BaTiO3) and employing advanced theoretical modeling, finite element analysis (FEA), and validation to identify optimal configurations. Methodologically, this study integrates machine learning and AI-driven techniques to refine design parameters and predict performance outcomes. Significant findings have revealed that PZT demonstrated the highest sensitivity (2 V/mm), achieving a maximum power output of 4.10 Watts, surpassing traditional solutions by over 100%. The optimization process ensured uniform stress distribution, reducing mechanical failure risk, with predictive models showing high accuracy (R-squared value of 97.77%). Error analysis indicated minimal discrepancies, with an average error margin of less than 2%. The conclusions highlight the significant potential of optimized piezoelectric implants in developing durable, efficient, and patient-friendly orthopedic solutions, setting a new standard in intelligent medical device innovation and contributing to enhanced patient care and improved clinical outcomes.

Sustainable Healthcare Quality and Job Satisfaction through Organizational Culture: Approaches and Outcomes

This paper explores innovative strategies to enhance sustainable healthcare quality, emphasizing the pivotal role of organizational culture and placing a special focus on employee job satisfaction. Recognizing the indispensable nature of contented employees in delivering superior patient care, our discussion explores how an organizational culture that prioritizes optimized work processes, and a supportive work environment can significantly boost employee well-being. By mitigating workplace stress through the refinement of operations and the minimization of waste, healthcare organizations can foster a setting that greatly enhances job satisfaction. This enhancement, in turn, catalyzes superior patient care and underscores the healthcare system’s dedication to sustainability and the well-being of its employees. Our analysis indicates that concentrating on employee satisfaction, deeply rooted in the organizational culture, is not merely advantageous but essential for nurturing a sustainable, high-quality healthcare system. The insights offered aim to guide healthcare organizations toward embracing strategies such as Green Lean Six Sigma, with a heightened focus on improving workforce well-being through the lens of organizational culture. This approach is expected to produce a synergistic improvement in healthcare quality by promoting operational efficiency and advancing environmental sustainability in tandem.

Revitalizing motivation for healthcare office workers: An Analysis of Job Diagnostic Survey Through the Lens of Hackman and Oldham's Model

The unprecedented nature of technological advancements, emphasis on the need for superior patient care, and evolving workplace dynamics lead to the need for revitalizing various factors that improve motivation for healthcare workers. The study aims to comprehend motivation for healthcare workers through the intricate lens of the Hackman and Oldham model by conducting a job diagnostic survey. Healthcare is a crucial industry where timely delivery of patient care is prioritized, workers often aim to exceed expectations and stay motivated. The conceptual framework of Hackman and Oldham provides insight into understanding the motivational factors of the job design, employee satisfaction in their role, and channel efforts into improving the same. A key application of the survey can be identifying areas of focus and improvement that can significantly improve motivation levels for employees thereby improving their performance and reshaping the healthcare workforce. A novel approach to research has been adopted, as previous studies have extensively focused on health care workers; however, most have overlooked the challenges healthcare office workers face to support the physicians and nurses at hospitals. The originality of the study stems from this finding as healthcare administrative workers face unique challenges that may be absent in other industries, and with the current nature of jobs post the pandemic, employers have found difficulty in retaining talent, keeping workers motivated, and empowering them to perform. This study will lead to both empirical and practical implications, aims to provide insight to future researchers as well as organizational leaders to acknowledge the newer dynamics of the workplace where healthcare office workers face many struggles in their workplace like long hours of working, stressful work environment, and constant pressure to perform as their performance is directly related to patient care and often involves saving lives, leading to lack of work-life balance; and how motivation resolves these issues. The study is performed on healthcare office workers in a North Texas Hospital and Healthcare organization, by surveying them with the Hackman and Oldham instrument to grasp their motivation levels and provide suggestions to the leadership to assist employees to stay motivated and focused.

Deep Learning-based Precision Diagnosis of Lung Diseases on the Internet of Medical Things (IoMT)

Lung disease is one of the common and severe pathological conditions that affect the respiratory system, causing respiratory illness and potential mortality. In recent times, deep learning paradigm based on the Internet of Medical Things (IoMT) platform has been adopted as a viable solution to address the challenges encountered in detection of lung diseases which are characterized by their diverse nature and the complexities associated with their diagnosis. In this work, we have proposed an approach that aims to achieve accurate prediction and analysis of lung diseases. The proposed research methodology presents a Deep Learning-based Accurate Lung Disease Prediction (DL-ALDP) model based on deep learning algorithms to enhance its predictive capabilities. The DL-ALDP framework integrates several preprocessing techniques, including Wiener filtering, optimized region growing method (ORGM)-based feature extraction, and Contrast limited AHE (CLAHE)-based segmentation. The accurate prediction of lung diseases is achieved by utilizing a Deep Neural Network (DNN) for classification purposes. The DL-ALDP technique, as suggested, attained a precision of 86.77%, sensitivity of 82.47%, specificity of 92.87%, accuracy of 92.08%, and F1 score of 89.42%. The findings of this research underscore the prospective utility of deep learning techniques in forecasting and analyzing lung ailments within the context of the IoMT platform. Through IoMT capabilities, healthcare practitioners can avail themselves of enhanced prognostic accuracy and timeliness, resulting in superior patient care and outcomes.

Smart health costing system

Smart Health Costing provides the benefits of streamlined operations, improved management and control, superior patient care, strict cost control and improved productivity. HMS is powerful, flexible and easy to use and has been designed and developed to deliver real, conceivable benefits to hospitals. Most importantly, it is backed by reliable and dependable support. The Hospital Management System project is based on database, oriented and networking techniques. Because there are many areas where we keep records in the database we use SQL SERVER which is one of the best and easiest software to keep our information. This project uses C# as a front-end program which is object oriented programming and has a connection to SQL SERVER. The smart health costing system is specifically designed to meet the specific requirements of medium and large sized hospitals around the world. All required modules and features are specifically designed to suit your requirements. It covers all required modules right from patient registration, medicine details, doctor, wards, administrator, patient appointment, bill payment, discharge details etc. The human body is a very complex and developed structure consisting of millions of tasks. Man has understood all these complex functions, part by part from their research and experiments. With the advancement of science and technology, medicine has become an integral part of research. Gradually, medical sciences became a completely new branch of science. As of today, the health sector consists of medical institutions, such as hospitals, hospitals, etc., research and development institutions and medical colleges. Thus the health sector aims to provide the best medical facilities to the general public.

Radiography Managers' Perspectives on the Strategies to Mitigate Disruptive Behaviours: A Qualitative Exploratory Study.

Disruptive behaviours (DBs) are not normally in the scope of legal sanctions, notwithstanding their undesirable effects. Hence, many healthcare organizations still have difficulty in dealing with them in an effective manner. Several studies suggest that few organizations have tailor-made policies or procedures for evaluating, proving and mitigating these behaviours. However, evidence shows that mitigating DBs is critical to empowering healthcare workers to focus on providing superior, affordable and safe patient care. The aim of this study was to explore radiography managers’ perspectives on the strategies to mitigate DBs involving radiographers. An exploratory qualitative study employing one-on-one semi-structured in-depth interviews was carried out between March and April 2021. Eleven radiography managers at central hospitals in Harare Metropolitan Province were selected by criterion-purposive sampling. The interview data were analyzed using Tesch’s method of qualitative analysis. The data were first manually coded and then entered into Nvivo (QSR International Version 11) for further analysis. Three themes emerged from the interview data including awareness of DBs, willingness to address DBs, and conflict resolution. Context-specific strategies to mitigate DBs should be identified and implemented to guarantee a healthy work environment for radiographers so that they focus on providing excellent and safe patient care.

Advanced Hospital Management System

Abstract: Advanced Hospital Management System provides the benefits of streamlined operations, enhanced administration & control, superior patient care, strict cost control and improved profitability. IHMS is powerful, flexible, and easy to use and is designed and developed to deliver real conceivable benefits to hospitals. More importantly it is backed by reliable and dependable support. The project 'Advanced Hospital Management System' is based on the database, object oriented and networking techniques. As there are many areas where we keep the records in database for which we are using MY SQL software which is one of the best and the easiest software to keep our information. This project uses JAVA as the front-end software which is an Object-Oriented Programming and has connectivity with MY SQL. Advanced Hospital Management System is custom built to meet the specific requirement of the mid and large size hospitals across the globe. All the required modules and features have been particularly built to just fit in to your requirement This package has been widely accepted by the clients in India and overseas. Not stopping only to this but they are highly satisfied and appreciating. Entire application is web based and built on 3 tier architecture using the latest technologies. The sound database of the application makes it more users friendly and expandable. The package is highly customizable and can be modified as per the needs and requirements of our clients. Prolonged study of the functionalities of the hospital and its specific requirement has given it a wonderful shape both technically and usability wise. It covers all the required modules right from Patient Registration, Medicine details, Doctor, Wards, , Admin, Store, Patient appointment, bill payment, record modification, discharge details etc.

Predicting Severity of Huntington's Disease With Wearable Sensors.

The Unified Huntington's Disease Rating Scale (UHDRS) is the primary clinical assessment tool for rating motor function in patients with Huntington's disease (HD). However, the UHDRS and similar rating scales (e.g., UPDRS) are both subjective and limited to in-office assessments that must be administered by a trained and experienced rater. An objective, automated method of quantifying disease severity would facilitate superior patient care and could be used to better track severity over time. We conducted the present study to evaluate the feasibility of using wearable sensors, coupled with machine learning algorithms, to rate motor function in patients with HD. Fourteen participants with symptomatic HD and 14 healthy controls participated in the study. Each participant wore five adhesive biometric sensors applied to the trunk and each limb while completing brief walking, sitting, and standing tasks during a single office visit. A two-stage machine learning method was employed to classify participants by HD status and to predict UHDRS motor subscores. Linear discriminant analysis correctly classified all participants' HD status except for one control subject with abnormal gait (96.4% accuracy, 92.9% sensitivity, and 100% specificity in leave-one-out cross-validation). Two regression models accurately predicted individual UHDRS subscores for gait, and dystonia within a 10% margin of error. Our regression models also predicted a composite UHDRS score–a sum of left and right arm rigidity, total chorea, total dystonia, bradykinesia, gait, and tandem gait subscores–with an average error below 15%. Machine learning classifiers trained on brief in-office datasets discriminated between controls and participants with HD, and could accurately predict selected motor UHDRS subscores. Our results could enable the future use of biosensors for objective HD assessment in the clinic or remotely and could inform future studies for the use of this technology as a potential endpoint in clinical trials.

Technology Utilization in Fall Prevention.

Falls, defined as unplanned descents to the floor with or without injury to an individual, remain to be one of the most challenging health conditions. Fall rate is a key quality metric of acute care hospitals, rehabilitation settings, and long-term care facilities. Fall prevention policies with proper implementation have been the focus of surveys by regulatory bodies, including The Joint Commission and the Centers for Medicare and Medicaid Services, for all healthcare settings. Since October 2008, the Centers for Medicare and Medicaid Services has stopped reimbursing hospitals for the costs related to patient falls, shifting the accountability for fall prevention to the healthcare providers. Research shows that almost one-third of falls can be prevented and extensive fall prevention interventions exist. Recently, technology-based applications have been introduced in healthcare to obtain superior patient care outcomes and experience via efficiency, access, and reliability. Several areas in fall prevention deploy technology, including predictive and prescriptive analytics using big data, video monitoring and alarm technology, wearable sensors, exergame and virtual reality, robotics in home environment assessment, and personal coaching. This review discusses an overview of these technology-based applications in various settings, focusing on the outcomes of fall reductions, cost, and other benefits.

Patient Perception of the Remote Versus Clinic Visits for Interrogation of Implantable Cardioverter Defibrillators.

Implantable Cardioverter Defibrillators (ICDs) are used in the management of sudden cardiac arrest. Compared with clinic visits, remote interrogation of these devices has shown clinical benefit and lower cost. We hypothesize that demographic and socioeconomic factors influence patient satisfaction with remote monitoring and therefore the choice of a pathway for follow-up. Questionnaires were mailed to 85 patients (mean age 63 ± 13.5 years, 73% male), with ICDs implanted for primary prevention of sudden cardiac arrest. Information regarding education, social support, employment, and income was collected. To compare clinic and remote monitoring, patients were given questionnaires to assess which parameters they consider important: convenience, accuracy, human contact, scheduling, and cost. Of the 34 responders, patients rated clinic visit to be as accurate with better opportunity to ask questions and better human contact, but there was no difference in perception of convenience, scheduling, or cost between the 2 groups. Significant number of patients dropped from the labor market after ICD implantation; however labor status, education, or income did not influence the preference of clinic appointment. Survey respondents preferred clinic to remote interrogation because they believe clinic appointments allow better interaction. Educating patients about the benefits of remote interrogation and improved communication will enhance utilization of this sophisticated technology for superior patient care.

Patient Data Integration: A Panacea for Effective Healthcare

A huge challenge in the healthcare domain has remained the spread and proliferation of fragmented information systems and multiplicity of data that accumulate from growing quantities of heterogeneous data of patient. This challenge must be addressed as the whole domain gradually transforms into models of delivery of healthcare that is electronic and patient-centered. The presence of inadequate data integration at various levels incapacitates medical personnel from building a wholesome and total understanding of patient condition. In this paper, an integration platform called Integrated Patient Management System (IPMIS) for managing clinical and historical information for patients is incorporated. Previous systems could not undertake the problems like; delay in treatment of patients in cases of emergencies, wrong prescription of drugs due to wrong diagnosis as a result of unavailability of patients’ history, lack of health data interoperability and loss of life. Seeking solution to the above problems led to the development of an Integrated Patient Management Information System (IPMIS) that enables patient clinical data sharing, provides streamlined operations, enhances administration and control, permits superior patient care and continuity of treatment, and improved decision making for healthcare institution. This paper enhances patient’s referral, with a messaging system that alerts the hospital which the patient has been referred to and also the patient that is referred. The development of the system helps to collate patient’s data that are disparately located to a centralized data base for efficient interoperability of care. It also helps for the interoperability of multiple hospitals for effective patient management. The new system enables and provides timely patient health record information sharing where it is need and when it is needed in cases of emergencies, referrals or continuity of treatment and it is presently being used in a federal teaching hospital in Nigeria.

Artificial intelligence in dentistry: current applications and future perspectives

Artificial intelligence (AI) encompasses a broad spectrum of emerging technologies that continue to influence daily life. The evolution of AI makes the analysis of big data possible, which provides reliable information and improves the decision-making process. This article introduces the principles of AI and reviews the development of AI and how it is currently being used. AI technology has influenced the health care field because of the need for accurate diagnosis and superior patient care. In order to understand the trend of AI in dentistry, electronic searching was carried out, combined with approaching individual companies to obtain the details of AI-based services. The current applications of AI in clinical dentistry were introduced and summarized. In the future, the AI-based comprehensive care system is expected to establish high-quality patient care and innovative research and development, facilitating advanced decision support tools. The authors believe that an innovative inter-professional coordination among clinicians, researchers, and engineers will be the key to AI development in the field of dentistry. Despite the potential misinterpretations and the concern of patient privacy, AI will continue to connect with dentistry from a comprehensive perspective due to the need for precise treatment procedures and instant information exchange. Moreover, such developments will enable professionals to share health-related big data and deliver insights that improve patient care through hospitals, providers, researchers, and patients.

Shared Care: Using an Electronic Consult Form to Facilitate Primary Care Provider–Specialty Care Coordination

ObjectiveThe quality of children's health is compromised by poor care coordination between primary care providers (PCPs) and specialists. Our objective was to determine how an electronic consultation and referral system impacts referral patterns and PCP–specialist communication. MethodsThe primary care clinic at Boston Children's Hospital piloted an electronic referral and consultation system with the neurology and gastroenterology departments from April 1, 2014, to October 31, 2016. PCPs completed an electronic consult form, and if needed, specialists replied with advice or facilitated expedited appointments. Specialist response times, referral rates, wait times, and completion rates for specialty visits were tracked. PCPs and specialists also completed a survey to evaluate feasibility and satisfaction. ResultsA total of 82 PCPs placed 510 consults during the pilot period. Specialists responded to 88% of requests within 3 business days. Eighteen percent of specialty visits were deferred and 21% were expedited. Wait times for specialty appointments to both departments significantly decreased, from 48 to 34 days (P < .001), and completion rates improved from 58% to 70% (P < .01), but referral volumes remained stable (25 per month to 23 per month; P = .29). Most PCPs said the Shared Care system facilitated better communication with specialists (89%) and enabled them to provide superior patient care (92%). Specialists reported that the system required a minimal amount of time and enabled them to educate PCPs and triage referrals. ConclusionsImplementation of an electronic referral and consultation system was feasible and provided timely access to specialty care, but did not affect referral volume. This system could serve as a model for other health care organizations and specialties.

Health Management Information System (HMIS) in Medicare –Patients’ Experience at ESIC main Hospital and Dispensaries in Tirunelveli sub- Region

The rapid growth in Information and Communication Technology (ICT), and the power of internet has strongly impacted the business and service delivery models of today‘s global environment. E-Hospital Management Systems provide the benefits of streamlined operations, enhanced administration and control, superior patient care, strict cost control and improved profitability. The concept of patient care can be defined as the creation of more value for patients through the removal of all non-value-added steps or actions. An important precondition of optimal patient care is that patient information is completely and accurately recorded and accessible. In this paper, we examine the implementation of an electronic health information system called the Health Management Information System (HMIS) and its effects on patient care in the ESIC main hospital and dispensaries in Tirunelveli sub-region. Two models -the Technology Acceptance Model (TAM) and TAM2 -were used to examine the transition from a paper to electronic environment and to assess processes and outcomes at the patient levels. Empirically, this paper discusses a qualitative research undertaken in the ESIC main hospital and dispensaries in Tirunelveli sub-region, with the participation of ESIC patients in the HMIS adoption process. A deductive reasoning approach was applied to collect data from patients in the sample. Deductive reasoning usually commences with generalizations, and seeks to see if these generalizations apply to specific instances. From this case study, the success factors and challenges faced in successful HMIS adoption among patients are highlighted. Some of the other mandatory factors are also discussed in detail for clarity on health information system implementation and adoption.

The Department of Dermatology, Huashan Hospital of Fudan University.

Huashan Hospital in one of the top public general hospitals in China that enjoys high nation-wide reputation by its superior patient care service and research. Among multiple characteristic departments in Huashan Hospital, the department of dermatology has been well known in the world for over 80 years. As the main educational foundation in the area of dermatology, it is one of the first units to offer MD/PhD degrees in China. According to the data of one Chinese statistical authority (the Hospital Management Institute of Fudan University), it has been ranked no. 1 among all departments of dermatology in China for five consecutive years since 2009.

Functional and Dysfunctional Sensorimotor Anatomy and Imaging

The sensorimotor system of the human brain and body is fundamental only in its central role in our daily lives. On further examination, it is a system with intricate and complex anatomical, physiological, and functional relationships. Sensorimotor areas including primary sensorimotor, premotor, supplementary motor, and higher order somatosensory cortices are critical for function and can be localized at routine neuroimaging with a familiarity of sulcal and gyral landmarks. Likewise, a thorough understanding of the functions and dysfunctions of these areas can empower the neuroradiologist and lead to superior imaging search patterns, diagnostic considerations, and patient care recommendations in daily clinical practice. Presurgical functional brain mapping of the sensorimotor system may be necessary in scenarios with distortion of anatomical landmarks, multiplanar localization, homunculus localization, congenital brain anomalies, informing diffusion tensor imaging interpretations, and localizing nonvisible targets.

Forceps-Assisted Vaginal Deliveries in West Texas

INTRODUCTION: The incidence of operative vaginal delivery was 10–15% in the United States in 2000. By 2006, the rate had fallen to less than 5%, of which less than 1% were forceps deliveries. Questions have arisen regarding whether the volume of procedures is sufficient to train residents. The objective of this study was to review the training and experience with forceps deliveries of residents graduating from a major southwestern residency program that focuses on training for forceps-assisted vaginal deliveries. METHODS: This was a retrospective chart review of forceps deliveries performed by nine residents who graduated from the Texas Tech University Health Sciences Center Department of Obstetrics and Gynecology residency program from July 1, 2007, through June 30, 2013. Annual and cumulative experience with forceps deliveries was recorded for each resident. Indication, classification, and type of forceps used were noted in all cases. Pertinent maternal and neonatal outcomes were obtained from the maternal medical record only. Important aspects of training that may have contributed to those salutary outcomes will be evaluated. RESULTS: A total of 303 procedures were identified. The mean number of procedures per resident was 33.7; the median was 29. The cumulative number of forceps deliveries by year of training was recorded. The mean (median) number of forceps deliveries by year of training (year 1–year 4) was 3.4 (3), 7.1 (6), 12.3 (9), and 12.3 (10), respectively. Indications for the forceps deliveries included 171 fetal, 95 maternal, and 37 not recorded. The majority of deliveries were classified as low forceps (187), with some outlet (38) and very few midforceps (9). The incidence of third- and fourth-degree perineal lacerations was 8.5%. CONCLUSION: Forceps have been used for hundreds of years to assist in the safe delivery of neonates. It is believed that the special emphasis placed on forceps-assisted deliveries in this program as well as the number of forceps-assisted deliveries performed combine to give residents the confidence needed to use this important mode of delivery when necessary for superior patient care.

Enhanced patient care through collaborative team play: An orthodontist and an OMF.Radiologist’s collective perspective

The overarching theme of patient-centric care should serve as the fundamental basis for our treatment plans. Treatment plans that best utilize knowledge; training and technology must be developed on current evidence that rests on soundly researched principles. In orthodontics, the evolution of cone beam computed tomography as a new three-dimensional imaging modality has brought a paradigm shift in the radiographic evaluation of the maxillofacial structures. However, the coming of new technology does not warrant its use in routine practice and tight imaging protocols must be developed to include and promote the evidence-based patient-centric approach. This principle is best approached if the effort is a collaborative one. Collaboration between all the disciplines that contribute to patient care must act as a unified force to deliver superior care. In this editorial, we present a successful collaborative effort between orthodontics and oral and maxillofacial radiology that have engaged in collaborative efforts to deliver superior patient care, better predoctoral and postdoctoral training programs and how this effort has yielded excellent contribution to research.

Role of Emerging Technology for Building Smart Hospital Information System

For last couple of year emerging technologies had changed our life drastically, specially with advances in smart mobile and faster and cheaper internet. As a result of research & development activities we have various kinds of sensors like Digital Biosensing Surface, ECG (Electrocardiogram) to gather information, smarter equipment like Tablets, any Smart Phone Apps to process and present them; with these we have robust ways of communication to interconnect all these system to provide complete new user experience. Currently various hospitals are using computerized information system known as HIS (Hospital Information System). But with changing technologies there is scope for delivering smarter information system to deliver enhanced administration, superior patient care, and streamlined operations and improve profitability. The study is focus on analyzing current information system, finding key areas for improvement, identifying newer technologies to fit requirement.

E –Hospital Management &amp; Hospital Information Systems – Changing Trends

The rapid growth in Information & Communication Technology (ICT), and the power of Internet has strongly impacted the business and service delivery models of today's global environment. E-Hospital Management Systems provide the benefits of streamlined operations, enhanced administration & control, superior patient care, strict cost control and improved profitability. Globally accepted health care systems need to comply with Healthcare Insurance Portability and Accountability Act (HIPAA) standards of the US and that has become the norm of the Healthcare industry when it comes to medical records management and patient information privacy. The study is focused on understanding the performance indicators of Hospital information systems (HIS), summarizing the latest commonly agreed standards and protocols like Health Level Seven (HL7) standards for mutual message exchange, HIS components, etc… The study is qualitative and descriptive in nature and most of the data is based on secondary sources of survey data. To arrive at a conclusive idea of the larger picture on E- Hospital Management and Hospital information systems, existing survey data and specific successful case studies of HIS are considered in the study. With so many customized versions of E - hospital management solutions (E - HMS) and Hospital Information systems (HIS) available in the market, a generic module wise version of E - Hospital management system is charted out to give a clear understanding for researchers and industry experts. From the specific successful case studies analyzed in the study, the success factors and challenges faced in successful E-HMS implementation are highlighted. Some of the mandatory standards like HIPAA are discussed in detail for clarity on Healthcare system implementation