Health Information Privacy in the Correctional Environment

Information technology is considered a transformative element in health care because it facilitates the transparency and sharing of health information, which have always been central to the practice of medicine and the delivery of high-quality care. The widespread use of electronic health records (EHRs) and electronic health information exchange, among other technologies, is considered essential to improving the quality of care, reducing medical errors, reducing health disparities, and advancing the delivery of patient-centered medical care

Biomedical Informatics Applications for Precision Management of Neurodegenerative Diseases

Modern medicine is in the midst of a revolution driven by “big data,” rapidly advancing computing power, and broader integration of technology into healthcare. Highly detailed and individualized profiles of both health and disease states are now possible, including biomarkers, genomic profiles, cognitive and behavioral phenotypes, high-frequency assessments, and medical imaging. Although these data are incredibly complex, they can potentially be used to understand multi-determinant causal relationships, elucidate modifiable factors, and ultimately customize treatments based on individual parameters. Especially for neurodegenerative diseases, where an effective therapeutic agent has yet to be discovered, there remains a critical need for an interdisciplinary perspective on data and information management due to the number of unanswered questions. Biomedical informatics is a multidisciplinary field that falls at the intersection of information technology, computer and data science, engineering, and healthcare that will be instrumental for uncovering novel insights into neurodegenerative disease research, including both causal relationships and therapeutic targets and maximizing the utility of both clinical and research data. The present study aims to provide a brief overview of biomedical informatics and how clinical data applications such as clinical decision support tools can be developed to derive new knowledge from the wealth of available data to advance clinical care and scientific research of neurodegenerative diseases in the era of precision medicine

EVALUATING THE USE OF HEALTH INFORMATION TECHNOLOGY TO ADVANCE HEALTH EQUITY IN PRIMARY CARE

Introduction: The concept of health equity has recently taken a central position in efforts to improve health care in the United States. With the 2021 National Academies’ report on “Implementing High-Quality Primary Care,” the United States is also experiencing renewed focus on primary health care. Follow up articles to the report highlighted the need for health equity to be centered in primary care and the importance of health information technology (HIT) in promoting high-quality care. Data-driven improvement has long been known to be an important building block of high-performing primary care, but the role of data and technology in advancing health equity is not well understood. Methods: This study aims to investigate the link between data systems and health equity within the context of primary care practices by presenting a case study of a single, high-performing primary care practice selected through reputational sampling. Researchers reviewed the practice’s policy documents related to equity and interviewed a clinic administrator, a physician, and a data specialist at the practice. The Consolidated Framework for Implementation Research (CFIR) was used to analyze interview transcripts. Themes derived from the interviews fell under the CFIR’s five domains, intervention characteristics, outer setting, inner setting, characteristics of individuals, and implementation process. Results: The practice was found to have a robust HIT system which includes an electronic medical record with both collection and analysis capabilities, a data reporting platform, and a data analysis and management team. As described by prior literature, the clinic followed a four-phase data use process which includes collection, analysis, reporting, and action. In addition to themes in each of the other CFIR categories, interviewees reported a number of process facilitators to data use for advancing health equity, including value-based contracting with payers, health equity champions, affiliation with a larger health system and with a university department, partnerships with peer clinics, receptive leadership, pandemic-motivated transitions to virtual care delivery, and external grant funding. Interviewees also reported barriers which included data limitations, data security concerns, staff burden, patient preference for convenience over continuity, and fee-for-service revenue models. Conclusion: We found that the clinic closely followed the proposed theoretical continuum in developing their HIT capabilities and health equity practices. This supports the continuum and offers an evidence-based framework for other primary care practices to follow in advancing equity through data-driven improvement. The facilitators and barriers identified through interviews point to the importance of implementing robust HIT and data collection, analysis, and reporting capabilities to achieving higher levels of clinic performance. Additionally, the findings of this study support the semi-cyclic nature of the proposed continuum where high-performing clinics must undergo continual reanalysis, rereporting, and reaction in order to perpetually improve equitability. Other primary care practices can learn from the facilitators and barriers identified in this study to navigate their own implementation of data-driven practices to advance health equity. Implications for the broader U.S. health care industry include the need for updated data security regulations which align with modern technology and the need for increased value-based care contracting which enables clinics to fund population-health initiatives. Key Words: Health Equity, Data, Information Technology, Primary Care, Quality Improvement, Implementation Research, Social Determinants of Health, Electronic Health Records, Population HealthBachelor of Science in Public Healt

Personal health records and personal health record systems: a report recommendation from the National Committee on Vital and Health Statistics

President Bush and Secretary Leavitt have put forward a vision that, in the Secretary\ue2\u20ac\u2122s words, \ue2\u20ac\u153would create a personal health record that patients, doctors and other health care providers could securely access through the Internet no matter where a patient is seeking medical care.\ue2\u20ac? The National Health Information Infrastructure Workgroup of the National Committee on Vital and Health Statistics (NCVHS) held six hearings on personal health records (PHRs) and PHR systems in 2002-2005. On the basis of those hearings, the Workgroup developed a letter report with twenty recommendations that it sent to the Secretary in September 2005. Citing the role PHR systems could play in improving health and healthcare and furthering the broad health information technology agenda, the letter report urges the Secretary to exercise leadership and give priority to developing PHRs and PHR systems, consistent with the Committee\ue2\u20ac\u2122s recommendations. The present report is a slightly expanded version of the letter report sent to the Secretary. Although substantively unchanged, it adds clarifying information for a broader audience.Acknowledgements -- Executive summary -- Background -- Personal Health records are evolving in concept and practice (Recommendations 1-2) -- Personal health record systems\ue2\u20ac\u2122 value depends on users, sponsors, and functionality -- Privacy (Recommendations 3-7) -- Security requirements (Recommendations 8-9) -- Interoperability (Recommendations 10-14) -- Federal Roles in PHR systems, internal and external (Recommendations 15-16) -- Advancing research and evaluation on PHR systems (Recommendations 17-20) -- Next steps for NCVHS"Developed by the Workgroup on the National Health Information Infrastructure (NHII) of the National Committee on Vital and Health Statistics"--P. 2.Also available via the World Wide Web.Includes bibliographical references

Emerging roles for telemedicine and smart technologies in dementia care

Demographic aging of the world population contributes to an increase in the number of persons diagnosed with dementia (PWD), with corresponding increases in health care expenditures. In addition, fewer family members are available to care for these individuals. Most care for PWD occurs in the home, and family members caring for PWD frequently suffer negative outcomes related to the stress and burden of observing their loved one's progressive memory and functional decline. Decreases in cognition and self-care also necessitate that the caregiver takes on new roles and responsibilities in care provision. Smart technologies are being developed to support family caregivers of PWD in a variety of ways, including provision of information and support resources online, wayfinding technology to support independent mobility of the PWD, monitoring systems to alert caregivers to changes in the PWD and their environment, navigation devices to track PWD experiencing wandering, and telemedicine and e-health services linking caregivers and PWD with health care providers. This paper will review current uses of these advancing technologies to support care of PWD. Challenges unique to widespread acceptance of technology will be addressed and future directions explored.ope

A micro credential for interoperability

In the midst of a global pandemic the need for health and social care providers to commit to, and deliver on, integrated patient-centered care services has been accelerated. Globally, health and social care programme administrators are turning to digital devices and applications to provide supporting infrastructure which can offer safe access to health information at the point of care. Digitalisation is increasingly considered a key requirement to support diagnostics and therapeutic care services in health care delivery. The open source community are responding to this need to advance integrated care and digital services by providing targeted resources to address the interoperability challenge. Addressing interoperability in health systems is a core part of achieving sustainable enterprise wide integrated care. Using Open Innovation 2.0 methods for advancing knowledge on interoperability, this paper describes the development of a micro credential for knowledge transfer on interoperability created by the Centre for eIntegrated Care (CeIC). Designed and developed to signpost interested stakeholders to targeted material and build understanding and capacity on the topic. The design approach and initial resource content are explained through the lens of a specific research project funded by an Elite S Fellowship to advance leadership and standardisation for Information and Communications Technology (ICT) in Europe

Reducing the use of ineffective health care interventions. CHERE Working Paper 2010/5

This report covers international and Australian models for reducing the use of ineffective interventions, also described as disinvestment. Disinvestment is a development of Health Technology Assessment (HTA). Conventionally HTA has focussed on the introduction of new technologies. Although medical technology is advancing rapidly, there remain very many technologies in use which have not been subject to formal HTA. This has stimulated a growing interest in disinvestment. This review identified a number of case studies and pilot projects. There is limited information available on the mechanisms used, and no rigorous evaluations of their impact. The most developed model is that of NICE which has recently embarked on providing guidance for disinvestment. A number of technologies have been reviewed;but there is limited information available on how these were identified, how disinvestment is implemented, or what the effect has been. There is substantial resistance to any active disinvestment. Across the various case studies, appraisal of candidate technologies seems most likely to be triggered by expert opinion. In Australia, disinvestment is also generally passive. Technologies may be removed from funding or reimbursement if new research demonstrating harms or inefficacy becomes public. More generally, technologies fall into disuse, and are gradually replaced by new or improved technologies. Even when guidelines or funding rules are changed, there is generally continued use of an existing technology. This review has found that active disinvestment has generally been removal of funding for ineffective and/or unsafe technologies, usually initiated by new evidence of inefficacy or harm. Disinvestment is more likely to be passive, ie driven by changes in medical practice, as a procedure or treatment gradually falls out of use over time. There are very few instances of disinvestment, or appraisal for disinvestment, driven by considerations of cost-effectiveness. There are considerable difficulties implementing disinvestment in ineffective health care practices. One area of difficulty is an appropriate mechanism for identifying candidate technologies for appraisal. No explicit processes were identified, although there are a number of published criteria for prioritising candidates. The US is embarking on a major new program of HTA, termed Comparative Effectiveness Research. The list of priority topics for appraisal was developed by the Institute of Medicine, using nominations from health professionals, consumer advocates, policy analysts and others. The development of the candidate topics was a major exercise in itself. Studies of medical practice variations can also be used to identify candidate topics for appraisal. To date, there has been relatively little systematic investigation into practice variations in Australia. The availability of rich data sets which allow analysis on the basis of small areas is essential to research in this field, as is the research capacity to allow rigorous analysis. Program Budgeting and Marginal Analysis is a technique which uses HTA methods to drive disinvestment and reinvestment. It is a relatively resource-intensive activity, and requires clinicians to identify activities for disinvestment. Another area of difficulty arises because there are few or no incentives for clinicians in disinvestment. Thus reinforces the problems of identifying technologies for appraisal. As disinvestment will create losses, to clinicians, to consumers and to providers of the technology, there will be strong resistance to any active withdrawal of funding. At the same time, the additional benefits and/or savings from any disinvestments may not be realised for a considerable period of time and there is a risk that, for some products,interventions or services, cost savings, in particular, may not be realised. This increases the cost of pursuing disinvestment. Both HTA and disinvestment can be seen in a much broader context, that is the challenge is to ensure that the additional health spending brings commensurate benefits ? ensuring health system efficiency. Although there is considerable interest in disinvestment, there are problems in identifying which technologies should be considered for disinvestment, and strong incentives to retain existing technologies. Disinvestment does occur, but generally as a result of existing treatments or other interventions falling into disfavour. An alternative approach to proactive disinvestment of specific technologies is to encourage more rapid change in medical practice. There are various strategies for health care reform which can be categorised as changing provider information, such as through the use of clinical guidelines, or the results of practice variations studies; changing incentives, though different payments for clinicians and other providers, or specifically targeted incentives; changing consumer behaviour, by providing more information with or without financial incentives; or changing the structures of health service delivery to provide organisational support and incentives for more efficient purchasing of care.Disinvestment, Health Technology Assessment, Ineffective health care interventions

Multilingualism in healthcare: exploring the lived experience of maternity professionals

Discussions surrounding migration and health in the UK frequently focus on language as a barrier to care, with a range of solutions posited as providing effective facilitation - from professional interpreters and translated patient information through to innovative technology and software. Paradoxically, the linguistic diversity of the NHS workforce remains largely unrecognised and under-utilised, despite the evidential advantages of language concordant care: current NHS guidelines (2018) recommend that additional languages are used for making appointments and Informed by an understanding of language as a fluid and dynamic practice, this study draws on a combination of ethnographic observations and in-depth interviews to investigate the everyday experiences of bi/multilingual NHS healthcare workers who use, or have used, languages in addition to English in the workplace. Initial findings reveal the extent to which individuals (feel able to) draw on personal linguistic repertoires and explore the (dis)advantages that communicative flexibility can be said to bring in terms of comprehension and experience. It becomes clear that strategic utilisation of linguistically skilled individuals may hold the potential for advancing equity of care for migrant patient populations, who are regularly and disproportionally represented in data recording adverse outcomes. This research also holds implications for raising the visibility of multilingual health professionals working within the NHS and prompting professional recognition of language skills

Medication Adherence with Smart Phones: Pharmacists Focused Apps

Medication adherence relates to the concept of compliance to a medicine regimen and is defined as ‘the extent to which a patient acts in accordance with the prescribed interval and dose of a dosing regimen’ (Cramer et al., 2008). Often desired health outcomes are not achieved due to patients, not taking their prescribed medication or taking them incompletely or inconsistently (Miller et al., 1997). This results in higher negative health outcomes and increasing cost of care and is therefore a growing global concern. Tackling the problem of non-adherence requires a collaborative, patient-centric approach and can be guided by modern technologies that offer efficient ways to managing healthcare (Williams et al., 2014). Over the last two decades, the internet has revamped the way information is accessed and mobile devices have taken this a step further by allowing users to access any and every information they want at their fingertips. The availability of over one and a half million applications or apps for download endorses the growing interest in the technology (Bexley et al., 2010). Mobile apps can provide an opportunity for both the healthcare professional and the patient to access user-friendly ways of accessing important medical information quickly, for improving patient health and advancing support and care (Choi et al. 2015; Miller et al., 1997). According to the eMarketer1, 2014, about 58.2% of the global population was using mobile phones in 2012; this percentage increased to 61.1% in 2013 and is further expected to increase to 69.4% of the world’s population by 2017. As of April 2014, 62% of smartphone users have searched for health information using their devices. Evidently, mobile is rapidly becoming the preferred consumer channel for communication including health services. Mobile-HealthNews.com2 highlights that the Apple App Store already has about 6,000 mobile health related apps, indicating consumers’ interest in a more active role in their own health management

Acceptance model of electronic medical record

This paper discusses acceptance issues of Electronic Medical Record System (EMR), particularly in Malaysia. A detailed overview of EMR and its benefits are firstly discussed. A number of acceptance models are scrutinized. Then factors affecting EMR acceptance are put forward. Finally, before proposing an EMR acceptance model, an instrument formed by adapting and then finding its factors loading is presented