Patient Data Management Research Articles

Explicating Artificial Intelligence: Applications in Medicine and Pharmacy

Artificial intelligence (AI) is a broad word that refers to the theory and development of computer systems that can do tasks that would ordinarily require human cognition, such as perception, comprehension, reasoning, learning, planning, and problem solving. Understanding the terminology and methodologies used in AI can help you communicate more effectively with data scientists to work together to design models that will improve patient care. The healthcare and pharmaceutical industries have long been early adopters of technological developments, reaping major benefits as a result. AI is being applied in a range of health-related sectors, including the discovery of novel medications, the invention of new medical treatments, and the management of patient data and records. This review identifies and examines the fundamentals and applications of artificial intelligence in medicine and pharmacy.

35. The development, testing, and validation of an automatic LIMS import method for NGS myeloid panel results

For oncology genetic testing, there is a critical need for patient results to be readily available and accessible for the ordering pathologist's review. After an initial genetic testing workup, emergency treatment or follow-up testing may be required, thus accessibility of results is a key feature in providing patient-focused laboratory testing. Ideally, genetic testing results would be incorporated into a LIMS data management system in order to have a permanent record of testing and to allow for the results to be easily accessible, searchable, and transferable by the clinical or pathology team working on behalf of the patient. For maximum impact, Next Generation Sequencing (NGS) reports should be electronically integrated into the patient's electronic health record. NGS reports uploaded as PDF attachments constrain health record searches. Additionally, data in PDF reports often are not able to be transferred to a comprehensive pathology report and may require cumbersome manual entry. Our team has recently completed a project to create an automatic import method for our Myeloid Complete NGS Panel report into our electronic patient data management system. Our data management system is interfaced with our client's LIMS platform enabling the direct and automatic transfer of orders coming in as well as delivery of the resultant NGS report into the patients' health records. We will present the steps taken to create, test, troubleshoot, and validate the automatic upload system. We will also detail critical components of the NGS LIMS report and challenges that were addressed during this project.

Analyzing Hospital’s Management Information System Based on Patient’s and Employee’s Perception Using EUCS Method

SIMRS is a system built to manage patient data in order to develop resources and improve hospital quality. As one of the newly implemented health support systems, the implementation of SIMRS needs to be observed. One of the indicators in the successful implementation of the system is the satisfaction of the end users of the system. User satisfaction (user satisfaction) is one indicator of the success of the development of information systems. Therefore, the research aims at analyzing the exact topic. EUCS is one of the research instruments that can be used to measure the success of information systems. In this study 5 EUCS instruments were used, namely content, accuracy, format, ease of use of users, timeliness of information systems and 3 additional variables, namely training, user satisfaction (user satisfaction)) and system benefits (net benefit). The results of this study indicate that accuracy (accuracy), format, user convenience (easy to use) timeliness of information systems (timeliness) and training (training) are proven to increase user satisfaction while content (content) has not been proven to have an effect. User satisfaction of integrated information systems has been proven to increase net benefits / organizational performance.

Antecedents of the adoption of blockchain to enhance patients’ health information management in South Africa

Background: Currently, the South African public healthcare system is hampered by a lack of effective patient data management. This leads to, amongst other challenges, a lack of transparency in the management of patients’ health information and unsecure medical records. Blockchain, on the other hand, can make healthcare records more secure, easily auditable, and hence more reliable. These advantages, among others, make Blockchain an appealing technology for managing patients’ health information in the South African context.Objectives: The study investigated the antecedents of the adoption of blockchain technology as a tool to improve the management of patients’ health information in the South African public healthcare sector.Method: The four pillars of a health information system (strong leadership, contingency plan, security and privacy, and IT or vendor support) were adopted as the theoretical grounding for the study. Qualitative data were collected through interviews with IT specialists and healthcare professionals working in the public healthcare sector.Results: The study identified 11 antecedents that can be related to the four pillars of a health information system. These antecedents must be addressed for blockchain to contribute meaningfully to enhancing patients’ health information management in South Africa.Conclusion: Although blockchain can contribute meaningfully to addressing health information management challenges in South Africa, contextual factors need to be considered for it to fulfil its promises. It is anticipated that the study findings will help stakeholders in the South African public healthcare sector to make informed decisions in their quest to deploy technology innovations like blockchain.

Epidemiology, management, and outcome of infection, sepsis, and septic shock in a German emergency department (EpiSEP study).

The adjacent conditions infection, sepsis, and septic shock are among the most common causes of treatment in the emergency department (ED). Most available data come from intensive care units (ICU) and include nosocomial infections acquired during hospitalization. Epidemiological data from German EDs are not yet available, although the ED is one of the first points of contact for patients. The aim of this study was to investigate the epidemiology, causes, diagnosis, mortality, and treatment of patients with infections in the ED. In this retrospective, single-center observational study, routinely collected data from the patient data management system and from the hospital information system were analyzed. All adult patients who presented to the ED in connection with an infection during the study period from 01/01 to 28/02/2019 were included. Exclusion criteria were age ≤ 17 years and incomplete records. Three groups (I. Infection, II. Sepsis, and III. Septic shock) were defined according to SEPSIS-3 definitions. During the study period, a total of 6,607 patients were treated in the ED. Of these patients, 19.3% (n = 1,278) had an infection (mean age 56 ± 23 years, 50% female). The sites of infection were distributed as follows: Respiratory tract 35%, genitourinary tract 18%, maxillofacial/ears/nose/throat 14%, intraabdominal 13%, soft tissues 10%, central nervous system 1%, other cause 3%, or unknown cause 6%. Infection only, sepsis and septic shock were present in 86, 10, and 3%, respectively. There were significant differences in vital signs as well as in the various emergency sepsis scores across the predefined groups [I vs. II vs. III: SOFA (pts.): 1 ± 1 vs. 4 ± 2 vs. 7 ± 3 (p < 0.0001), systolic blood pressure (mmHg): 137 ± 25 vs. 128 ± 32 vs. 107 ± 34 (p < 0.05), heart rate (bpm): 92 ± 18 vs. 99 ± 23 vs. 113 ± 30 (p < 0.05), respiratory rate (min-1): 18 ± 4 vs. 20 ± 7 vs. 24 ± 10 (p < 0.05)]. In the three groups, blood cultures were obtained in 34, 81, and 86%, of cases, respectively and antibiotics were administered in the ED in 50, 89, and 86%, of cases respectively. The 30-day mortality rate in the three groups was 1.6, 12.0, and 38.1%, respectively. This study is the first to show the incidence, management, and outcome of patients classified as infection, sepsis, and septic shock in a German ED. The findings of our real-world data are important for quality management and enable the optimization of treatment pathways for patients with infectious diseases.

Engaging Knowledge Capabilities to Sustain the Application of Information Technology Governance in Healthcare Institutions

The healthcare sector has faced increasing pressures to reduce costs and increase healthcare quality in recent years. Thus, managing knowledge in healthcare organizations is critical to achieving low-cost optimization of higher quality services. Also, information technology (IT) plays an essential and crucial role in providing a central database for managing patient data in the healthcare sector. The current study investigates the effects of three aspects of knowledge capabilities (i.e., individual knowledge capabilities, managerial knowledge capabilities, and collaborative organizational capabilities) on information technology governance in healthcare institutions in the Sultanate of Oman. Data were collected using a non-simple random sampling technique by distributing a questionnaire completed by (325) employees working in (13) public hospitals and medical centers in (8) governorates. The collected data were analyzed using AMOS software and structural equation modeling (SEM). This study indicates that individual knowledge capabilities significantly affect only one dimension of IT governance: IT risk management. Moreover, collaborative knowledge capabilities significantly influence all dimensions of IT governance pillars in healthcare institutions, while managerial knowledge capabilities have no significant effect. The study findings can be used to deeply understand the role of knowledge capabilities in sustaining the IT governance application in the health sector context.

Toward Dynamic Consent for Privacy-Aware Pervasive Health and Well-being: A Scoping Review and Research Directions

Recent advances in sensor-enabled services have facilitated the use of mobile, wearable, and IoT devices; for example, an extensive range of sensor data are used to automatically track symptoms and diagnose health and well-being status of an individual (e.g., depression). As personal data are being continuously and unobtrusively sensed and collected at large scale, this raises privacy concerns in certain contexts (e.g., GPS data collection at privacy-sensitive places). Current one-off informed consent in such pervasive sensing scenarios does not offer context-awareness support that enables selective data disclosure based on a user’s needs or preferences (e.g., disabling GPS data collection when visiting hospitals). A lack of context-awareness support in informed consent would be a critical barrier to user acceptance of data-intensive pervasive computing for health and well-being. As an alternative method, we introduce the concept of “dynamic consent,” a type of informed consent that enables granular data consent and management, initially introduced in biomedical research for patient data management. We explore how this consent practice within biomedical research might inform usable privacy designs in pervasive computing by conducting a scoping review of dynamic consent literature and discussing future research directions.

Integrating AI and Distributed Computing for Advanced Dental Healthcare Management

This research paper delves into the innovative integration of artificial intelligence (AI) and distributed computing within dental healthcare management, marking a pivotal advancement in the field. We explore the synergistic potential of AI algorithms and distributed systems in revolutionizing dental diagnostics, treatment planning, and patient data management. The paper elaborates on the utilization of machine learning models for predictive analytics in oral health, and the implementation of distributed architectures to ensure robust, scalable, and secure data handling. Emphasis is placed on AI-driven customization of patient care, enhancing accuracy and efficiency in dental practices. Challenges such as ethical considerations, data privacy, and the need for seamless human-AI collaboration are critically examined. This comprehensive study not only showcases cutting-edge technological advancements but also paves the way for transformative changes in dental healthcare delivery, underlining the vital role of AI and distributed computing in shaping the future of dentistry

Exploring the ability of child and adolescent mental health services (CAMHS) to respond to new valuable knowledge: the influence of professionals and internal organisational processes

PurposeHealth policies in England highlight the need for child and adolescent mental health services (CAMHS) to embed new knowledge in practice, yet evidence remains scarce about the services’ ability to learn from the external environment. This paper aims to present a critical analysis of the CAMHS’ ability to implement new knowledge through the lens of absorptive capacity, an organisation’s ability to identify, assimilate and use new valuable knowledge.Design/methodology/approachSixteen semi-structured interviews were conducted with staff from the CAMHS department of a mental health organisation in England to explore the services’ absorptive capacity.FindingsProfessionals were identified having an impact on the main absorptive capacity components in the following ways: professional background and perceived reliability of knowledge sources appeared to affect knowledge identification; informal communication was found to facilitate knowledge assimilation and exploitation; trust was found to enable knowledge exploitation, particularly between senior management and frontline professionals. At an organisational level, team meetings and internal reporting were identified as enablers to knowledge assimilation and exploitation, while organisational hierarchy and patient data management systems were identified as barriers to knowledge assimilation. No organisational processes were found regarding knowledge identification, indicating an imbalanced investment in the main components of absorptive capacity.Practical implicationsInvesting in these underpinning factors of absorptive capacity can assist CAMHS with capitalising on new knowledge that is valuable to service provision.Originality/valueThis study offers novel insights into the learning ability of CAMHS through the lens of absorptive capacity.

Design And Development of Help Patient Data Management Information System at Sinergi Atap Negeri Foundation Web-Based Using Codeigniter

The Sinergi Atap Negeri Foundation is a legal and independent non-profit social foundation with the goal of becoming a halfway house facilitator for needy patients and families. The purpose of this study is to create a data management information system for assisted patients to aid in data management, patient submissions, and data transactions at the Sinergi Atap Negeri Foundation, thereby making work more effective and efficient. The waterfall method is used in software development to collect data from previous studies through observations, interviews, and literature studies. The Sinergi Atap Negeri Foundation's patient data management system, according to the analysis, is still manual, whereas previously data management could only be managed by one foundation administrator and accessed by anyone. Given these concerns, researchers are encouraged to develop a web-based application using PHP, the Codeigniter 3 framework, and Mysql as a database. It is hoped that this information system will improve the performance of foundation employees by making data entry easier and faster, as well as avoiding data loss errors from a security standpoint.

Implementation of Medical Record System at UMB Medical Center Bengkulu City

UMB Media Center (UMC) Bengkulu City is a health company owned by the University of Muhammadiyah Bengkulu. Currently, administrative services provided by UMC Bengkulu City to patients or clients, such as data management and data retrieval related to patients and other medical data, are still carried out manually through recording into administrative notebooks and Microsoft office applications. This has an impact on the orderly and slow management of patient medical record data and the presentation of information. system analysis and design using the Waterfall method which has stages of analysis, design, implementation, testing, deployment, and maintenance so that the UMS medical record application was built with the aim of storing track records of patient health quickly and making it easier to manage patient data..

Nurses' knowledge of and attitude to nursing information systems.

The use of a nursing information system (NIS) provides significant benefit to the nurses in the management of real-time patient data and contributes to improving the operational effectiveness of nursing services. To assess the knowledge of, attitude towards and use of an NIS. A prospective cross-sectional study was carried out among 230 hospital nurses in India, using a validated questionnaire including demographic characteristics, and questions on knowledge of, attitude towards and use of an NIS. The study found that more than 70% of nurses had good computer skills and knowledge about the information system. About 75% of the nurses reported that the NIS could be a tool to support them in improving patient care, and medical documentation, although 42% claimed that the use of NIS depersonalises nursing care. Seventy-one per cent of the nurses expressed the need for formal education and training on using an NIS during and after their nursing education. Training and demonstration of NISs during nurse education would improve nurses' knowledge, build confidence and positive attitudes, and enhance the acceptability and sustainability of NISs in healthcare settings.

Readiness to change associated with job performance among health information management professionals during the covid-19 pandemic

Health information management professionals (HIM professionals) are one of the essential health workers during the Covid-19 pandemic in managing patient data in hospitals. Changes in both policies and work systems were felt by HIM professionals during the Covid-19 pandemic. The impact of these changes influences the job performance of HIM professionals. This study aimed to assess the association between readiness to change and job performance among HIM professionals during the Covid-19 pandemic in RSAB Harapan Kita, Indonesia. The indicators of job performance are quality, timeliness, need for supervision, responsibility, cost-effectiveness, quantity, interpersonal impact, and empathy. The readiness to change in this study seen from self-efficacy, appropriateness, management support, and personal benefits. This study applied a mixed-methods design to assess the association between readiness to change and job performance in which respondents fill out a questionnaire independently via Google Form. Furthermore, a focus group discussion was conducted to probe deeper into what changes occurred during the Covid-19 pandemic and how these changes related to the job performance of HIM professionals. The questionnaire used in previous research has been validated. The samples used were all 27 HIM professionals and 11 of them agreed to continue the focus group discussion. Statistical analysis used the chi-square test on SPSS version 26 to assess the association between variables. The results show that readiness to change indicated significant association with job performance (p=0.001). Informants stated that changes that occurred during the Covid-19 pandemic included the use of personal protective equipment, spraying disinfectants on medical forms and workspaces, and adding Covid-19 reporting both internally and externally.

Implementation of the Rapid Application Development Method for Designing an Outpatient Online Registration System in an Independent Doctor's Practice

The use of the website has become a necessity in health services and makes it easier to work in health care facilities. Doctors' independent practice as a health service facility can use the website to assist the outpatient registration process. Outpatient registration services at independent doctor's practices still use a manual system, patients must come to registration, take a queue card printed by the officer, wait according to the queue number obtained so that the process causes patient waiting time at the service to be long. The purpose of this study is to produce an outpatient online registration system in independent doctor’s practices that is able to assist outpatients to register online for outpatients. Development of an Outpatient Online Registration System at this Independent Doctor's Practice using the Rapid Application Development (RAD) method, this development model is used because this model is considered a time-honored model, so the process is relatively faster. This study applies the Rapid Application Development method to produce an outpatient online registration system at independent Practitioners that is able to manage patient data, doctor data, polyclinic queue data, polyclinic data, queue data and outpatient registration data. The Rapid Application Development method has been able to streamline the processing time for making the system to produce an Outpatient Online Registration System.

Towards an Ontology-Based Phenotypic Query Model

Clinical research based on data from patient or study data management systems plays an important role in transferring basic findings into the daily practices of physicians. To support study recruitment, diagnostic processes, and risk factor evaluation, search queries for such management systems can be used. Typically, the query syntax as well as the underlying data structure vary greatly between different data management systems. This makes it difficult for domain experts (e.g., clinicians) to build and execute search queries. In this work, the Core Ontology of Phenotypes is used as a general model for phenotypic knowledge. This knowledge is required to create search queries that determine and classify individuals (e.g., patients or study participants) whose morphology, function, behaviour, or biochemical and physiological properties meet specific phenotype classes. A specific model describing a set of particular phenotype classes is called a Phenotype Specification Ontology. Such an ontology can be automatically converted to search queries on data management systems. The methods described have already been used successfully in several projects. Using ontologies to model phenotypic knowledge on patient or study data management systems is a viable approach. It allows clinicians to model from a domain perspective without knowing the actual data structure or query language.

TELEDerm: Implementing store-and-forward teledermatology consultations in general practice: Results of a cluster randomized trial.

Although teledermatology has been proven internationally to be an effective and safe addition to the care of patients in primary care, there are few pilot projects implementing teledermatology in routine outpatient care in Germany. The aim of this cluster randomized controlled trial was to evaluate whether referrals to dermatologists are reduced by implementing a store-and-forward teleconsultation system in general practitioner practices. Eight counties were cluster randomized to the intervention and control conditions. During the 1-year intervention period between July 2018 and June 2019, 46 general practitioner practices in the 4 intervention counties implemented a store-and-forward teledermatology system with Patient Data Management System interoperability. It allowed practice teams to initiate teleconsultations for patients with dermatologic complaints. In the four control counties, treatment as usual was performed. As primary outcome, number of referrals was calculated from routine health care data. Poisson regression was used to compare referral rates between the intervention practices and 342 control practices. The primary analysis revealed no significant difference in referral rates (relative risk = 1.02; 95% confidence interval = 0.911-1.141; p = .74). Secondary analyses accounting for sociodemographic and practice characteristics but omitting county pairing resulted in significant differences of referral rates between intervention practices and control practices. Matched county pair, general practitioner age, patient age, and patient sex distribution in the practices were significantly related to referral rates. While a store-and-forward teleconsultation system was successfully implemented in the German primary health care setting, the intervention's effect was superimposed by regional factors. Such regional factors should be considered in future teledermatology research.

Modeling Data Journeys to Inform the Digital Transformation of Kidney Transplant Services: Observational Study.

BackgroundData journey modeling is a methodology used to establish a high-level overview of information technology (IT) infrastructure in health care systems. It allows a better understanding of sociotechnical barriers and thus informs meaningful digital transformation. Kidney transplantation is a complex clinical service involving multiple specialists and providers. The referral pathway for a transplant requires the centralization of patient data across multiple IT solutions and health care organizations. At present, there is a poor understanding of the role of IT in this process, specifically regarding the management of patient data, clinical communication, and workflow support.ObjectiveTo apply data journey modeling to better understand interoperability, data access, and workflow requirements of a regional multicenter kidney transplant service.MethodsAn incremental methodology was used to develop the data journey model. This included review of service documents, domain expert interviews, and iterative modeling sessions. Results were analyzed based on the LOAD (landscape, organizations, actors, and data) framework to provide a meaningful assessment of current data management challenges and inform ways for IT to overcome these challenges.ResultsResults were presented as a diagram of the organizations (n=4), IT systems (n>9), actors (n>4), and data journeys (n=0) involved in the transplant referral pathway. The diagram revealed that all movement of data was dependent on actor interaction with IT systems and manual transcription of data into Microsoft Word (Microsoft, Inc) documents. Each actor had between 2 and 5 interactions with IT systems to capture all relevant data, a process that was reported to be time consuming and error prone. There was no interoperability within or across organizations, which led to delays as clinical teams manually transferred data, such as medical history and test results, via post or email.ConclusionsOverall, data journey modeling demonstrated that human actors, rather than IT systems, formed the central focus of data movement. The IT landscape did not complement this workflow and exerted a significant administrative burden on clinical teams. Based on this study, future solutions must consider regional interoperability and specialty-specific views of data to support multi-organizational clinical services such as transplantation.

EHealth challenges in rehabilitation processes - rehabilitation professionals’ experiences in the North Savo region

Aging people are forced to steadily extend their working-lives since the old-age dependency ratio will rise considerably in the near future. Meanwhile, social and healthcare resources will become increasingly scarce, although the need for healthcare and rehabilitation services is bound to increase. The aim of this study was to examine rehabilitation professionals’ experiences related to eHealth and technology in the rehabilitation process in the North Savo region. The research was carried out as a part of the European Social Fund (ESF) funded project ”Expertise and Business Network for Rehabilitation Services in Northern Savo”. 30 rehabilitation workers were interviewed (67% women) in 2020. The participants were aged 24-60 years and their job titles were e.g. doctors, physiotherapists, practical nurses and community sector representatives. The interviews were carried out using a semi-structured format. The interviews were recorded, transcribed, and analysed using the inductive content analysis method. The technology and digitalisation experiences of the rehabilitation workers in North Savo region can be divided into five categories. Technical problems causing challenges in rehabilitation included inadequate information and patient data management, and poor or lacking data-applications, ICT-tools and systems. The cost of technology was perceived as a factor influencing rehabilitation from both an individual and organisational perspective. The emergence of COVID-19 has had a positive impact on the use of technology and digital services. Suitable technology and digital services for rehabilitation need to be developed towards a more individual, client-centric direction. To promote the adoption of technology in the field of rehabilitation and to support positive change in attitudes towards technology, more education is needed. The ever-evolving field of rehabilitation demands effective eHealth applications and processes alongside highly competent rehabilitation professionals to meet the needs of the aging population base in North Savo region. There is a need for more client-centric eHealth and rehabilitation processes, wherein the rehabilitation workers’ needs are met – physically and psychosocially. By bringing together rehabilitation and ICT expertise in North Savo region, it is possible to provide training and education to raise the level of both the rehabilitation processes and level of expertise of rehabilitation workers in the region.

Modern Understanding of Severe Bronchial Asthma

The review provides data on severe bronchial asthma. Frequent exacerbations of asthma significantly reduce the quality of life of patients, cause disability, disability and death. The heterogeneity of severe bronchial asthma fits into the concepts of phenotype and endotype, the identification of which in clinical practice has limitations, but is necessary for personalized therapy. Analysis of the literature reflecting experience in patient data management is needed to form holistic perceptions of severe bronchial asthma and develop ways to optimize therapy.

Responsive neurostimulation of the thalamus improves seizure control in idiopathic generalised epilepsy: initial case series

ObjectivesUp to 40% of patients with idiopathic generalised epilepsy (IGE) are drug resistant and potentially could benefit from intracranial neuromodulation of the seizure circuit. We present outcomes following 2 years...