A Description of Personal Health Information Management Work With a Spotlight on the Practices of Older Adults: Qualitative e-Delphi Study With Professional Organizers.

BACKGROUND: Personal health information (PHI) is created on behalf of and by health care consumers to support their care and wellness. Available tools designed to support PHI management (PHIM) remain insufficient. A comprehensive understanding of PHIM work is required, particularly for older adults, to offer more effective PHIM tools and support. OBJECTIVE: The primary objective of this study was to use the Patient Work System model to provide a holistic description of PHIM work from the perspective of professional organizers with experience assisting health care consumers, including older adults, in managing their PHI. A secondary objective was to examine how factors associated with 4 Patient Work System components (person, tasks, tools and technologies, and context) interact to support or compromise PHIM work performance. METHODS: A modified e-Delphi methodology was used to complete 3 web-based rounds of open-ended questions and obtain consensus among a panel of 16 experts in professional organizing. Data were collected between April and December 2017. The Patient Work System model was used as a coding schema and guided the interpretation of findings during the analysis. RESULTS: The PHIM work of adults who sought assistance focused on the tasks of acquiring, organizing, and storing 3 classifications of PHI (medical, financial, and reference) and then processing, reconciling, and storing the medical and financial classifications to tend to their health, health care, and health finances. We also found that the complexities of PHI and PHIM-related work often exceeded the abilities and willingness of those who sought assistance. A total of 6 factors contributed to the complexity of PHIM work. The misalignment of these factors was found to increase the PHIM workload, particularly for older adults. The life changes that often accompanied aging, coupled with obscure and fragmented health care provider- and insurer-generated PHI, created the need for much PHIM work. Acquiring and integrating obscure and fragmented PHI, detecting and reconciling PHI discrepancies, and protecting PHI held by health care consumers were among the most burdensome tasks, especially for older adults. Consequently, personal stakeholders (paid and unpaid) were called upon or voluntarily stepped in to assist with PHIM work. CONCLUSIONS: Streamlining and automating 2 of the most common and burdensome PHIM undertakings could drastically reduce health care consumers' PHIM workload: developing and maintaining accurate current and past health summaries and tracking medical bills and insurance claims to reconcile discrepancies. Other improvements that hold promise are the simplification and standardization of commonly used financial and medical PHI; standardization and automation of commonly used PHI acquisition interfaces; and provision of secure, Health Insurance Portability and Accountability Act (HIPAA)-certified PHI tools and technologies that control multiperson access for PHI stored by health care consumers in electronic and paper formats.

Willingness to Adopt Health Information Among Social Question-and-Answer Community Users in China: Cross-sectional Survey Study.

BACKGROUND: COVID-19 has spread around the world and has increased the public's need for health information in the process. Meanwhile, in the context of lockdowns and other measures for preventing SARS-CoV-2 spread, the internet has surged as a web-based resource for health information. Under these conditions, social question-and-answer communities (SQACs) are playing an increasingly important role in improving public health literacy. There is great theoretical and practical significance in exploring the influencing factors of SQAC users' willingness to adopt health information. OBJECTIVE: The aim of this study was to establish an extended unified theory of acceptance and use of technology model that could analyze the influence factors of SQAC users' willingness to adopt health information. Particularly, we tried to test the moderating effects that different demographic characteristics had on the variables' influences. METHODS: This study was conducted by administering a web-based questionnaire survey and analyzing the responses from a final total of 598 valid questionnaires after invalid data were cleaned. By using structural equation modelling, the influencing factors of SQAC users' willingness to adopt health information were analyzed. The moderating effects of variables were verified via hierarchical regression. RESULTS: Performance expectation (ß=.282; P<.001), social influence (ß=.238; P=.02), and facilitating conditions (ß=.279; P=.002) positively affected users' willingness to adopt health information, whereas effort expectancy (P=.79) and perceived risk (P=.41) had no significant effects. Gender had a significant moderating effect in the structural equation model (P<.001). CONCLUSIONS: SQAC users' willingness to adopt health information was evidently affected by multiple factors, such as performance expectation, social influence, and facilitating conditions. The structural equation model proposed in this study has a good fitting degree and good explanatory power for users' willingness to adopt health information. Suggestions were provided for SQAC operators and health management agencies based on our research results.

Health Care Cybersecurity Challenges and Solutions Under the Climate of COVID-19: Scoping Review.

BACKGROUND: COVID-19 has challenged the resilience of the health care information system, which has affected our ability to achieve the global goal of health and well-being. The pandemic has resulted in a number of recent cyberattacks on hospitals, pharmaceutical companies, the US Department of Health and Human Services, the World Health Organization and its partners, and others. OBJECTIVE: The aim of this review was to identify key cybersecurity challenges, solutions adapted by the health sector, and areas of improvement needed to counteract the recent increases in cyberattacks (eg, phishing campaigns and ransomware attacks), which have been used by attackers to exploit vulnerabilities in technology and people introduced through changes to working practices in response to the COVID-19 pandemic. METHODS: A scoping review was conducted by searching two major scientific databases (PubMed and Scopus) using the search formula "(covid OR healthcare) AND cybersecurity." Reports, news articles, and industry white papers were also included if they were related directly to previously published works, or if they were the only available sources at the time of writing. Only articles in English published in the last decade were included (ie, 2011-2020) in order to focus on current issues, challenges, and solutions. RESULTS: We identified 9 main challenges in cybersecurity, 11 key solutions that health care organizations adapted to address these challenges, and 4 key areas that need to be strengthened in terms of cybersecurity capacity in the health sector. We also found that the most prominent and significant methods of cyberattacks that occurred during the pandemic were related to phishing, ransomware, distributed denial-of-service attacks, and malware. CONCLUSIONS: This scoping review identified the most impactful methods of cyberattacks that targeted the health sector during the COVID-19 pandemic, as well as the challenges in cybersecurity, solutions, and areas in need of improvement. We provided useful insights to the health sector on cybersecurity issues during the COVID-19 pandemic as well as other epidemics or pandemics that may materialize in the future.

Patterns and Influencing Factors of eHealth Tools Adoption Among Medicaid and Non-Medicaid Populations From the Health Information National Trends Survey (HINTS) 2017-2019: Questionnaire Study.

BACKGROUND: Evidence suggests that eHealth tools adoption is associated with better health outcomes among various populations. The patterns and factors influencing eHealth adoption among the US Medicaid population remain obscure. OBJECTIVE: The objective of this study is to explore patterns of eHealth tools adoption among the Medicaid population and examine factors associated with eHealth adoption. METHODS: Data from the Health Information National Trends Survey from 2017 to 2019 were used to estimate the patterns of eHealth tools adoption among Medicaid and non-Medicaid populations. The effects of Medicaid insurance status and other influencing factors were assessed with logistic regression models. RESULTS: Compared with the non-Medicaid population, the Medicaid beneficiaries had significantly lower eHealth tools adoption rates for health information management (11.2% to 17.5% less) and mobile health for self-regulation (0.8% to 9.7% less). Conversely, the Medicaid population had significantly higher adoption rates for using social media for health information than their counterpart (8% higher in 2018, P=.01; 10.1% higher in 2019, P=.01). Internet access diversity, education, and cardiovascular diseases were positively associated with health information management and mobile health for self-regulation among the Medicaid population. Internet access diversity is the only factor significantly associated with social media adoption for acquisition of health information (OR 1.98, 95% CI 1.26-3.11). CONCLUSIONS: Our results suggest digital disparities in eHealth tools adoption between the Medicaid and non-Medicaid populations. Future research should investigate behavioral correlates and develop interventions to improve eHealth adoption and use among underserved communities.

[How to adapt qualitative research to confinement contexts]. / Cómo adaptar una investigación cualitativa a contextos de confinamiento.

The confinement of the population, researchers, shows the need to adapt the qualitative methodology, techniques and tools, to the current context generated by COVID-19. The Internet and the social media allow the collection of textual data, sequences, images or narratives about a limited reality for access to it in person. We enter the era of e-research, nuancing and reorienting the observation, conversation, collection and analysis of information. Currently, we are working on techniques and models of good practice in this area. This note includes data collection tools used in qualitative research in health sciences, a selection of techniques for qualitative online research is made, and 10 rules for the design of an e-research of this type are provided.

Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems.

BI-RADS is a communication and data tracking system that has evolved since its inception as a brief mammography lexicon and reporting guide into a robust structured reporting platform and comprehensive quality assurance tool for mammography, ultrasound, and MRI. Consistent and appropriate use of the BI-RADS lexicon terminology and assessment categories effectively communicates findings, estimates the risk of malignancy, and provides management recommendations to patients and referring clinicians. The impact of BI-RADS currently extends internationally through six language translations. A condensed version has been proposed to facilitate a phased implementation of BI-RADS in resource-constrained regions. The primary advance of the 5th edition of BI-RADS is harmonization of the lexicon terms across mammography, ultrasound, and MRI. Harmonization has also been achieved across these modalities for the reporting structure, assessment categories, management recommendations, and data tracking system. Areas for improvement relate to certain common findings that lack lexicon descriptors and a need for further clarification of proper use of category 3. BI-RADS is anticipated to continue to evolve for application to a range of emerging breast imaging modalities.

Consolidating Emergency Department-specific Data to Enable Linkage with Large Administrative Datasets.

INTRODUCTION: The American Hospital Association (AHA) has hospital-level data, while the Centers for Medicare & Medicaid Services (CMS) has patient-level data. Merging these with other distinct databases would permit analyses of hospital-based specialties, units, or departments, and patient outcomes. One distinct database is the National Emergency Department Inventory (NEDI), which contains information about all EDs in the United States. However, a challenge with merging these databases is that NEDI lists all US EDs individually, while the AHA and CMS group some EDs by hospital network. Consolidating data for this merge may be preferential to excluding grouped EDs. Our objectives were to consolidate ED data to enable linkage with administrative datasets and to determine the effect of excluding grouped EDs on ED-level summary results. METHODS: Using the 2014 NEDI-USA database, we surveyed all New England EDs. We individually matched NEDI EDs with corresponding EDs in the AHA and CMS. A "group match" was assigned when more than one NEDI ED was matched to a single AHA or CMS facility identification number. Within each group, we consolidated individual ED data to create a single observation based on sums or weighted averages of responses as appropriate. RESULTS: Of the 195 EDs in New England, 169 (87%) completed the NEDI survey. Among these, 130 (77%) EDs were individually listed in AHA and CMS, while 39 were part of groups consisting of 2-3 EDs but represented by one facility ID. Compared to the individually listed EDs, the 39 EDs included in a "group match" had a larger number of annual visits and beds, were more likely to be freestanding, and were less likely to be rural (all P<0.05). Two grouped EDs were excluded because the listed ED did not respond to the NEDI survey; the remaining 37 EDs were consolidated into 19 observations. Thus, the consolidated dataset contained 149 observations representing 171 EDs; this consolidated dataset yielded summary results that were similar to those of the 169 responding EDs. CONCLUSION: Excluding grouped EDs would have resulted in a non-representative dataset. The original vs consolidated NEDI datasets yielded similar results and enabled linkage with large administrative datasets. This approach presents a novel opportunity to use characteristics of hospital-based specialties, units, and departments in studies of patient-level outcomes, to advance health services research.

Determinants of improved data consistency across routine immunization data tools for health facilities in Kano State, Nigeria.

INTRODUCTION: in this study, determinants of improved data consistency for routine immunization information at health facilities was measured to identify associated factors. METHODS: between June and August 2015, 1055 HFs were visited across 44 Local Government Areas in Kano state. We assessed data consistency, frequency of supportive supervision visits, availability of trained staff and attendance to monthly LGA RI review meetings. We compared RI monthly summary forms (MSF) versus national health management information system summary form (NHMIS) and vaccine management form 1a (VM1a) versus HF vaccine utilization summary monthly summary (HFVUM) for consistency. Data consistency at HF was determined at <+10% between number of children reportedly immunized, and doses of vaccine opened using 3 antigens (BCG, Penta and Measles). Levels of discrepancy <10% were considered as good data consistency. Bivariate and multivariate analysis used to determine association. RESULTS: data Consistency was observed in 195 (18.5%) HFs between (MSF vs NHMIS) and 90 (8.5%) HFs between (VM1a vs HFVUM). Consistency between MSF vs NHMIS was associated with receiving one or more SS visits in the previous month (p=0.001), data collection tools availability (p=0.001), recent attendance to monthly LGA RI review meeting and availability of trained staff. Data consistency between VM1a form and the HF VU summary was associated with a recent documented SS visit (p=0.05) and availability of trained staff (p=0.05). CONCLUSION: low level of data consistency was observed in Kano. Enhanced SS visits and availability of trained staff are associated with improved data quality.

[Whole-course information management in gastrointestinal stromal tumor patients].

Gastrointestinal stromal tumor (GIST) is the most common soft tissue sarcoma of the gastrointestinal tract. With the development of diagnosis and treatment of GIST, the overall survival is significantly prolonged, and GIST may be classified as a "chronic disease". How to effectively manage the patients with whole-course information is an important problem faced by colleagues who are responsible for GIST patients. We believe that every GIST patient has a need for whole-course management, which is also an important factor related to efficacy. The concept of information-based management, the management system in line with the characteristics of GIST disease and full-time managers of GIST disease are the guarantees for the realization of whole-course management, and also the prerequisites for homogeneals diagnosis and treatment of GIST.

Digitalización de historias clínicas: análisis de un proyecto en un contexto real en el Servicio Extremeño de Salud en España / Medical record digitalization: analysis of a real life project involving the Extremadura Health Service in Spain

Se presenta un estudio de caso en el contexto de la gestión de la información clínica sanitaria, en el que, a partir de la revisión de la literatura científica, se detectó que las tecnologías de la información se han ido introduciendo de manera desigual e irregular en la sanidad pública española. El estudio se planteó como objetivo analizar cómo se realiza un proyecto de digitalización de historias clínicas, el cual condujo a las siguientes preguntas de investigación: ¿Cómo se gestiona la información sanitaria? ¿Cómo se realiza un proyecto de digitalización de historias clínicas en un contexto real? ¿Qué formación tienen los profesionales que participan en el proceso y ¿cuál es el papel de los documentalistas? Se siguió una metodología de investigación cualitativa con perspectiva naturalista, además del análisis de la literatura científica, en la que se presentaron los resultados del estudio basados en la dotación de equipamiento, el servicio de consultoría, la gestión documental y de archivo, además del perfil profesional que se plantea para la ejecución de un proyecto de digitalización de historias clínicas. Se concluye que la gestión de la información no satisface las necesidades del personal sanitario; que no existe un procedimiento documentado para la digitalización de las historias clínicas y que no se requiere la participación de profesionales sanitarios ni de documentalistas, a pesar de que la literatura científica resalta la inestimable participación de estos profesionales(AU)

A health information management case study is presented in a which scientific literature review revealed that information technologies have been incorporated into Spanish public health in an uneven, irregular manner. To corroborate this fact we set ourselves the objective of analyzing the way in which a medical record digitalization project is conducted, which led to the following research questions: How is health information managed? How is a medical record digitalization project conducted in a real life context? What is the background of professionals involved in the process and what is the role of documentalists? Besides examination of the scientific literature, a naturalist qualitative analysis was performed in which the results of the study were presented, based on equipment provision, advisory service, document management and archiving, and the professional profile established for the conduct of a medical record digitalization project. It is concluded that information management does not meet the needs of the health personnel, that a documented procedure is not available for medical record digitalization, and that participation of health professionals and documentalists is not requested, despite the scientific literature highlighting the invaluable participation of these professionals(AU)

Untangling the complexity of multimorbidity with machine learning.

The prevalence of multimorbidity has been increasing in recent years, posing a major burden for health care delivery and service. Understanding its determinants and impact is proving to be a challenge yet it offers new opportunities for research to go beyond the study of diseases in isolation. In this paper, we review how the field of machine learning provides many tools for addressing research challenges in multimorbidity. We highlight recent advances in promising methods such as matrix factorisation, deep learning, and topological data analysis and how these can take multimorbidity research beyond cross-sectional, expert-driven or confirmatory approaches to gain a better understanding of evolving patterns of multimorbidity. We discuss the challenges and opportunities of machine learning to identify likely causal links between previously poorly understood disease associations while giving an estimate of the uncertainty on such associations. We finally summarise some of the challenges for wider clinical adoption of machine learning research tools and propose some solutions.

Supporting the health library and information workforce.

As a prelude to his keynote speech at the forthcoming Health Libraries Group conference, Sean McNamara, Head of CILIP Scotland, provides an insight into the work being undertaken with health librarians in Scotland and considers how CILIP Scotland might support the health information sector in the coming years.

COVID-19: comunicación de riesgos y participación comunitaria (CRPC) / COVID-19: risk communication and community participation (CRPC)

La comunicación de riesgos y la participación comunitaria son componentes esenciales de los planes nacionales de respuesta a emergencias en salud. Para las emergencias de salud pública como la pandemia por COVID 19, la comunicación de riesgos incluye la variedad de acciones de comunicación requeridas para la preparación, respuesta y recuperación, a fin de promover la toma de decisiones informadas, el cambio de comportamiento y el mantenimiento de la confianza.

Insights from Adopting a Data Commons Approach for Large-scale Observational Cohort Studies: The California Teachers Study.

BACKGROUND: Large-scale cancer epidemiology cohorts (CEC) have successfully collected, analyzed, and shared patient-reported data for years. CECs increasingly need to make their data more findable, accessible, interoperable, and reusable, or FAIR. How CECs should approach this transformation is unclear. METHODS: The California Teachers Study (CTS) is an observational CEC of 133,477 participants followed since 1995-1996. In 2014, we began updating our data storage, management, analysis, and sharing strategy. With the San Diego Supercomputer Center, we deployed a new infrastructure based on a data warehouse to integrate and manage data and a secure and shared workspace with documentation, software, and analytic tools that facilitate collaboration and accelerate analyses. RESULTS: Our new CTS infrastructure includes a data warehouse and data marts, which are focused subsets from the data warehouse designed for efficiency. The secure CTS workspace utilizes a remote desktop service that operates within a Health Insurance Portability and Accountability Act (HIPAA)- and Federal Information Security Management Act (FISMA)-compliant platform. Our infrastructure offers broad access to CTS data, includes statistical analysis and data visualization software and tools, flexibly manages other key data activities (e.g., cleaning, updates, and data sharing), and will continue to evolve to advance FAIR principles. CONCLUSIONS: Our scalable infrastructure provides the security, authorization, data model, metadata, and analytic tools needed to manage, share, and analyze CTS data in ways that are consistent with the NCI's Cancer Research Data Commons Framework. IMPACT: The CTS's implementation of new infrastructure in an ongoing CEC demonstrates how population sciences can explore and embrace new cloud-based and analytics infrastructure to accelerate cancer research and translation.See all articles in this CEBP Focus section, "Modernizing Population Science."

The impact of an integrated electronic immunization registry and logistics management information system (EIR-eLMIS) on vaccine availability in three regions in Tanzania: A pre-post and time-series analysis.

BACKGROUND: Since 2016, the Government of Tanzania has been implementing TImR, an integrated Electronic Immunization registry-logistics management information system (EIR-LMIS) that includes stock notifications. The objective of this study is to estimate the impact of this intervention on vaccine availability. METHODS: Monthly stock-out data were collected from paper registers at facilities, an Excel-based system at districts, and the new system (TImR) across all 924 health facilities in Arusha, Tanga and Kilimanjaro Regions. Six months of stockout rates pre- and post-introduction, by antigen, were compared via a two-way analysis of variance (ANOVA). A mixed-effects logistic regression model with the TImR data identified predictors of vaccine availability across antigens. FINDINGS: Post-introduction, ANOVA models estimated that overall stock-out rates declined from a monthly average of 7.1% to 2.1% (p < 0.01). Three specific vaccines had fewer stock-outs; OPV's monthly average dropped from 12.5% to 2.1% (p < 0.01), MR from 9.4% to 1.0% (p < 0.01) and DTP-HepB-HiB from 8.1% to 1.7% (p < 0.01). In the mixed-effects logistic regression model, controlling for antigen, odds of stock-out were 4.1% (95% CI: 3.3 - 4.9) lower for each week of tenure. Compared to DTP-HepB-HiB vaccine, odds of BCG vaccine being stocked out were 4.31 as high (95% CI: 3.1 - 5.0). The odds of being stocked-out were 29.7% lower for PCV (95% CI: 8.8 - 45.8) and 26.6% (95% CI: 3.4 - 44.1) lower for rotavirus vaccines compared to DTP-HepB-HiB. The odds of stock out were 37.7% lower for MR vaccine than DTP-HepB-HiB (95% CI: 18.1 - 52.6). CONCLUSIONS: Tanzania's integrated EIR-eLMIS may increase vaccine availability compared to its paper and Excel based system. Post-introduction of an eLMIS, the odds of a vaccine stock-out reduced over time. Further research could determine the impact of this intervention on vaccine wastage and replenishment response times.

[Health record linkage: Andalusian health population database]. / Conexión de registros sanitarios: base poblacional de salud de Andalucía.

OBJECTIVE: To describe the development of an information system that connects data from multiple health records to improve assistance to patients, health services administration, management, evaluation, and inspection, as well as public health and research. METHOD: Deterministic connection of pseudonymized data from a population of 8.5 million inhabitants provided by: a users database, DIRAYA electronic medical records, minimum basic data sets (inpatients, outpatient mayor surgery, hospital emergencies and medical day hospital), mental health information systems, analytical and image tests, vaccines, renal patients, and pharmacy. An automatic coder was used to code clinical diagnoses and 80 chronic pathologies were identified to follow-up. The architecture of the information system consisted of three layers: data (Oracle Database 11g), applications (MicroStrategy BI) and presentation (MicroStrategy Web, JavaScript libraries, HTML 5 and CSS style sheets). Measures for the governance of the system were implemented. RESULTS: Data from 12.5 million health system users between 2001 and 2017 were gathered, including 435.5 million diagnoses, 88.7% of which were generated by the automatic coder. Data can be accessed through predefined reports or dynamic queries, both exportable to CSV files for processing outside the system. Expert analysts can directly access the databases and perform queries using SQL or directly treat the data with external tools. CONCLUSION: The work has shown that the connection of health records opens new possibilities for data analysis.

The desktop, or the top of the desk? The relative usefulness of household features for personal health information management.

Sixty percent of the US population manages at least one chronic illness. For these patients, personal health information management (PHIM) is an integral part of daily life, and largely occurs within the home. However, the way in which the home supports PHIM has not been systematically investigated. The present study examined how members of the diabetic population use features of the home environment to support PHIM. Participants (N = 60) explored a simulated home environment, the VR CAVE, and identified the most useful features for performing three examples of PHIM tasks. The computer was perceived as the most useful feature for PHIM. However, perceived usefulness of features varied based on the PHIM task performed and the rooms in which features appeared. We conclude that a detailed study of the affordances of features is necessary to ease the burden of managing chronic illness, particularly diabetes mellitus, in the sociotechnical system of the home.

Evaluation and design of public health information management system for primary health care units based on medical and health information.

OBJECTIVE: The objective is to understand the role of information management systems in the public health perspective of primary care units more accurately. METHODS: A public health information management system for primary medical units, which is based on electronic health records, virtual private network technology, real-time data storage, and other technologies, is designed on the premise of economical and straightforward operation. Besides, Xinhua Community Health Service Center Around the Wulong Street, Longsha District, Qiqihar City is selected as the experimental unit of the public health information management system, and the work efficiency of the system in the public health perspective of the primary medical unit is evaluated after 12 months of system operation. RESULTS: The public health information management system of primary medical units has following comprehensive management functions: health record management, child health, maternal health, health of the elderly, health of patients with chronic diseases, health of severe psychiatric patients, health education, infectious diseases and public emergencies, health events, health supervision, and management information. In addition, after 12 months of information management system operates in the grassroots units, the results show that patients and doctors have a very high satisfaction rate with the system. The system not only cultivates the excellent health and disease prevention awareness of residents but also improves the efficiency of primary care institutions, as well as reducing the number of patients seeking medical cares. CONCLUSION: The public health information management system of primary health care units based on medical and health information design is rich in functions with prominent work efficiency, which significantly improves the public health of grass-roots medical units. The research is useful and significant for follow-up studies on public health care systems.