Transforming the provision of healthcare through emerging technology: A strategic transformation.

Why has the health care delivery paradigm and its integral transactions and interactions been left to muddle through, using archaic, 20th century modes and processes of delivery that are overlaid with byz antine medical record databases that pass for "cut ting-edge" technology? What is stalling the digital revolution in the provision of health care services to consumers? Understanding how and why this has happened requires that we briefly explore the evo lution of health care in the United States. Topics discussed include (1): morbidity and mortality: the public health era: (2) Medicare era: the advance of diagnostic and therapeutic technology; (3) the power of the consumer: patient-centered informatics; and (4) planning and execution of strategic transformation of provision of care informatics. Without an informatics focus, our health care system will continue limping along, costing more money and delivering many years of disability. Our most viable solutions revolve around using informatics to measure, guide and become the transformation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Medicine, Machines, and Medical Education.

While advances in science and technology continue to be at the forefront of the evolution of medical practice, the 21st century is also undergoing a unique and profound cultural shift that is changing the very nature of what it means to be a medical professional, namely humankind's transition to an information-based internet society. Medical care will increasingly depend on computer-generated probabilities guided and supported by a growing variety of individuals in health care-related professions, including statisticians, technologists, and information managers. Perhaps the biggest challenge to the profession will come from the erosion of professional autonomy, driven by smart machines, social networks, and internet search engines. As a result of these and other changes, physicians are facing a systematic loss of control, often without the direct input and leadership of the profession itself. In this commentary, the author urges the profession to adopt several strategies, including shifting its focus from reimbursement to the care patients value most, meaningfully addressing critical issues in health policy, becoming the definitive source for publicly available medical information, reimagining medical education, and overhauling the existing accreditation and licensing systems. Medical education must go beyond a focus on physicians whose professional identity revolves around being the exclusive source of medical knowledge. In the digitized 21st century, medical education should emphasize the centrality of the humanistic interface with patients such that the doctor-patient relationship is paramount in the complex medical world of machines and social media. Removing the roadblocks to successful professional reform is no small task, but the process can begin with a grassroots movement that empowers physicians and facilitates organizational and behavioral change. Failure to take action may well hasten the diminishment of patient care and the profession's trusted role in society.

Assessment of the many faces of PsA: single and composite measures in PsA clinical trials.

PsA is a complex, heterogeneous disease that can place a large burden on patients' psychological and physical well-being. The multifaceted nature of PsA poses a significant assessment challenge, both in randomized control trials and in clinical practice. In recent years, there has been much progress in the development of unidimensional and composite measures of disease activity, as well as of questionnaires that capture the patient's perspective of the condition. Despite these advances, there remains uncertainty around which tools to implement within a research setting. This review aims to summarize the currently available clinical and patient-derived assessment tools, providing a practical and informative resource for the assessment of PsA. This review will also explore recent advancements in digital approaches to the assessment of rheumatological conditions. This will highlight the potential for digitalization in the assessment and monitoring of PsA, outlining innovative means of capturing disease activity and treatment response.

Verifiable fully outsourced attribute-based signcryption system for IoT eHealth big data in cloud computing.

The entrance of Internet of Things (IoT) technologies to healthcare industry has impacted the explosion of eHealth big data. Cloud computing is widely considered to be the promising solution to store this data because of the presence of abundant resources at a lower cost. However, the privacy and security of the IoT generated data cannot be ensured as the data is kept far from the owner's phys- ical domain. In order to resolve the underlined issues, a reassuring solution is to adopt attribute-based signcryption (ABSC) due to the desirable cryptographic properties it holds including fine-grained ac- cess control, authentication, confidentiality and data owner privacy. Nonetheless, executing expensive computation such as pairing and modular exponential operations in resource-constrained IoT device platform can be too taxing and demanding. To address the challenges stated above, we proposed in this paper, a more efficient scheme where computation power is borrowed from the cloud server to process expensive computations while leaving simple operations to local users. In order to realize this, trusted attribute authority, signcryptor and designcryptor outsources to the cloud expensive tasks for key gener- ation, signcryption and designcryption respectively. Moreover, validity and correctness of outsourced computations can be verified by employing outsourcing verification server. Security analysis, compar- isons evaluation and simulation of the proposed scheme is presented. The output demonstrates that it is efficient, secure and therefore suitable for application in resource-constrained IoT devices.

Rural and Urban Differences in the Adoption of New Health Information and Medical Technologies.

BACKGROUND: This statewide survey sought to understand the adoption level of new health information and medical technologies, and whether these patterns differed between urban and rural populations. METHODS: A random sample of 7,979 people aged 18-75 years, stratified by rural status and race, who lived in 1 of 34 Indiana counties with high cancer mortality rates and were seen at least once in the past year in a statewide health system were surveyed. RESULTS: Completed surveys were returned by 970 participants. Rural patients were less likely than urban to use electronic health record messaging systems (28.3% vs 34.5%, P = .045) or any communication technology (43.0% vs 50.8%, P = .017). Rural patients were less likely to look for personal health information for someone else's medical record (11.0% vs 16.3%, P = .022), look-up test results (29.5% vs 38.3%, P = .005), or use any form of electronic medical record (EMR) access (57.5% vs 67.1%, P = .003). Rural differences in any use of communication technology or EMRs were no longer significant in adjusted models, while education and income were significantly associated. There was a trend in the higher use of low-dose computed tomography (CT) scan among rural patients (19.1% vs 14.4%, P = .057). No significant difference was present between rural and urban patients in the use of the human papilloma virus test (27.1% vs 26.6%, P = .880). CONCLUSIONS: Differences in health information technology use between rural and urban populations may be moderated by social determinants. Lower adoption of new health information technologies (HITs) than medical technologies among rural, compared to urban, individuals may be due to lower levels of evidence supporting HITs.

Automated Risk Control in Medical Imaging Equipment Management Using Cloud Application.

Medical imaging equipment (MIE) is the baseline of providing patient diagnosis in healthcare facilities. However, that type of equipment poses high risk for patients, operators, and environment in terms of technology and application. Considering risk management in MIE management is rarely covered in literature. The study proposes a methodology that controls risks associated with MIE management. The methodology is based on proposing a set of key performance indicators (KPIs) that lead to identify a set of undesired events (UDEs), and through a risk matrix, a risk level is evaluated. By using cloud computing software, risks could be controlled to be manageable. The methodology was verified by using a data set of 204 pieces of MIE along 104 hospitals, which belong to Egyptian Ministry of Health. Results point to appropriateness of proposed KPIs and UDEs in risk evaluation and control. Thus, the study reveals that optimizing risks taking into account the costs has an impact on risk control of MIE management.

Secure count query on encrypted genomic data.

Human genomic information can yield more effective healthcare by guiding medical decisions. Therefore, genomics research is gaining popularity as it can identify potential correlations between a disease and a certain gene, which improves the safety and efficacy of drug treatment and can also develop more effective prevention strategies [1]. To reduce the sampling error and to increase the statistical accuracy of this type of research projects, data from different sources need to be brought together since a single organization does not necessarily possess required amount of data. In this case, data sharing among multiple organizations must satisfy strict policies (for instance, HIPAA and PIPEDA) that have been enforced to regulate privacy-sensitive data sharing. Storage and computation on the shared data can be outsourced to a third party cloud service provider, equipped with enormous storage and computation resources. However, outsourcing data to a third party is associated with a potential risk of privacy violation of the participants, whose genomic sequence or clinical profile is used in these studies. In this article, we propose a method for secure sharing and computation on genomic data in a semi-honest cloud server. In particular, there are two main contributions. Firstly, the proposed method can handle biomedical data containing both genotype and phenotype. Secondly, our proposed index tree scheme reduces the computational overhead significantly for executing secure count query operation. In our proposed method, the confidentiality of shared data is ensured through encryption, while making the entire computation process efficient and scalable for cutting-edge biomedical applications. We evaluated our proposed method in terms of efficiency on a database of Single-Nucleotide Polymorphism (SNP) sequences, and experimental results demonstrate that the execution time for a query of 50 SNPs in a database of 50,000 records is approximately 5 s, where each record contains 500 SNPs. And, it requires 69.7 s to execute the query on the same database that also includes phenotypes.

Use and clinical efficacy of standard and health information technology fall risk assessment tools.

OBJECTIVE: To evaluate the health information technology (HIT) compared to Fall Risk for Older Persons (FROP) tool in fall risk screening. METHODS: A HIT tool trial was conducted on the geriatric evaluation and management (GEM, n = 111) and acute medical units (AMU, n = 424). RESULTS: Health information technology and FROP scores were higher on GEM versus AMU, with no differences between people who fell and people who did not fall. Both score completion rates were similar, and their values correlated marginally (Spearman's correlation coefficient 0.33, P < 0.01). HIT and FROP scores demonstrated similar sensitivity (80 vs 82%) and specificity (32 vs 36%) for detecting hospital falls. Hospital fall rates trended towards reduction on AMU (4.20 vs 6.96, P = 0.15) and increase on GEM (10.98 vs 6.52, P = 0.54) with HIT tool implementation. CONCLUSIONS: Health information technology tool acceptability and scoring were comparable to FROP screening, with mixed effects on fall rate with HIT tool implementation. Clinician partnership remains key to effective tool development.

Towards a Framework for Managing Risk Associated with Technology-Induced Error.

Health information technologies (HIT) promised to streamline and modernize healthcare processes. However, a growing body of research has indicated that if such technologies are not designed, implemented or maintained properly this may lead to an increased incidence of new types of errors which the authors have referred to as "technology-induced errors". In this paper, framework is presented that can be used to manage HIT risk. The framework considers the reduction of technology-induced errors at different stages by managing risks associated with the implementation of HIT. Frameworks that allow health information technology managers to employ proactive and preventative approaches that can be used to manage the risks associated with technology-induced errors are critical to improving HIT safety and managing risk associated with implementing new technologies.

The TECH@HOME study, a technological intervention to reduce caregiver burden for informal caregivers of people with dementia: study protocol for a randomized controlled trial.

BACKGROUND: It is estimated that global dementia rates will more than triple by 2050 and result in a staggering economic burden on families and societies. Dementia carries significant physical, psychological and social challenges for individuals and caregivers. Informal caregiving is common and increasing as more people with dementia are being cared for at home instead of in nursing homes. Caregiver burden is associated with lower perceived health, lower social coherence, and increased risk of morbidity and mortality. The aim of this trial is to evaluate the effects of information and communication technology (ICT) on caregiver burden among informal caregivers of people with dementia by reducing the need for supervision. METHODS/DESIGN: This randomized controlled trial aims to recruit 320 dyads composed of people with dementia living in community settings and their primary informal caregivers. In the intervention group, people with dementia will have a home monitoring kit installed in their home while dyads in the control group will receive usual care. The ICT kit includes home-leaving sensors, smoke and water leak sensors, bed sensors, and automatic lights that monitor the individual's behavior. Alerts (text message and/or phone call) will be sent to the caregiver if anything unusual occurs. All study dyads will receive three home visits by project administrators who have received project-specific training in order to harmonize data collection. Home visits will take place at enrollment and 3 and 12 months following installation of the ICT kit. At every home visit, a standardized questionnaire will be administered to all dyads to assess their health, quality of life and resource utilization. The primary outcome of this trial is the amount of informal care support provided by primary informal caregivers to people with dementia. DISCUSSION: This is the first randomized controlled trial exploring the implementation of ICT for people with dementia in a large sample in Sweden and one of the first at the international level. Results hold the potential to inform regional and national policy-makers in Sweden and beyond about the cost-effectiveness of ICT and its impact on caregiver burden. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02733939 . Registered on 10 March 2016.

The Unintended Consequences of Health Information Technology Revisited.

INTRODUCTION: The introduction of health information technology into clinical settings is associated with unintended negative consequences, some with the potential to lead to error and patient harm. As adoption rates soar, the impact of these hazards will increase. OBJECTIVE: Over the last decade, unintended consequences have received great attention in the medical informatics literature, and this paper seeks to identify the major themes that have emerged. RESULTS: Rich typologies of the causes of unintended consequences have been developed, along with a number of explanatory frameworks based on socio-technical systems theory. We however still have only limited data on the frequency and impact of these events, as most studies rely on data sets from incident reporting or patient chart reviews, rather than undertaking detailed observational studies. Such data are increasingly needed as more organizations implement health information technologies. When outcome studies have been done in different organizations, they reveal different outcomes for identical systems. From a theoretical perspective, recent advances in the emerging discipline of implementation science have much to offer in explaining the origin, and variability, of unintended consequences. CONCLUSION: The dynamic nature of health care service organizations, and the rapid development and adoption of health information technologies means that unintended consequences are unlikely to disappear, and we therefore must commit to developing robust systems to detect and manage them.

Use of cloud computing in biomedicine.

Nowadays, biomedicine is characterised by a growing need for processing of large amounts of data in real time. This leads to new requirements for information and communication technologies (ICT). Cloud computing offers a solution to these requirements and provides many advantages, such as cost savings, elasticity and scalability of using ICT. The aim of this paper is to explore the concept of cloud computing and the related use of this concept in the area of biomedicine. Authors offer a comprehensive analysis of the implementation of the cloud computing approach in biomedical research, decomposed into infrastructure, platform and service layer, and a recommendation for processing large amounts of data in biomedicine. Firstly, the paper describes the appropriate forms and technological solutions of cloud computing. Secondly, the high-end computing paradigm of cloud computing aspects is analysed. Finally, the potential and current use of applications in scientific research of this technology in biomedicine is discussed.

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

Using the Analytic Hierarchy Process (AHP) to understand the most important factors to design and evaluate a telehealth system for Parkinson's disease.

BACKGROUND: The assessment of a new health technology is a multidisciplinary and multidimensional process, which requires a complex analysis and the convergence of different stakeholders into a common decision. This task is even more delicate when the assessment is carried out in early stage of development processes, when the maturity of the technology prevents conducting a large scale trials to evaluate the cost effectiveness through classic health economics methods. This lack of information may limit the future development and deployment in the clinical practice. This work aims to 1) identify the most relevant user needs of a new medical technology for managing and monitoring Parkinson's Disease (PD) patients and to 2) use these user needs for a preliminary assessment of a specific system called PERFORM, as a case study. METHODS: Analytic Hierarchy Process (AHP) was used to design a hierarchy of 17 needs, grouped into 5 categories. A total of 16 experts, 6 of them with a clinical background and the remaining 10 with a technical background, were asked to rank these needs and categories. RESULTS: On/Off fluctuations detection, Increase wearability acceptance, and Increase self-management support have been identified as the most relevant user needs. No significant differences were found between the clinician and technical groups. These results have been used to evaluate the PERFORM system and to identify future areas of improvement. CONCLUSIONS: First of all, the AHP contributed to the elaboration of a unified hierarchy, integrating the needs of a variety of stakeholders, promoting the discussion and the agreement into a common framework of evaluation. Moreover, the AHP effectively supported the user need elicitation as well as the assignment of different weights and priorities to each need and, consequently, it helped to define a framework for the assessment of telehealth systems for PD management and monitoring. This framework can be used to support the decision-making process for the adoption of new technologies in PD.