scholarly journals Intention to Use Behavioral Health Data from a Health Information Exchange: A Mixed Methods Study (Preprint)

2020 ◽  
Author(s):  
Randyl A. Cochran ◽  
Sue S. Feldman ◽  
Nataliya V. Ivankova ◽  
Allyson G. Hall ◽  
William Opoku-Agyeman
Keyword(s):  
Behavioral Health ◽  
Health Information ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Health Data ◽  
Mixed Methods Study ◽  
Intention To Use ◽  
Coordinated Care ◽  
Related Information ◽  
Health Related

BACKGROUND Patients with co-occurring behavioral health and chronic medical conditions frequently overutilize inpatient hospital services. This pattern of overuse contributes to inefficient healthcare spending. These patients require coordinated care to achieve optimal health outcomes. However, the poor exchange of health-related information between various clinicians renders the delivery of coordinated care challenging. Health information exchanges (HIEs) facilitate health-related information sharing and have been shown to be effective in chronic disease management, but their effectiveness in the delivery of integrated care is less clear. It is prudent to consider new approaches to sharing both general medical and behavioral health information. OBJECTIVE We identified and described factors that influence the intention to use behavioral health information that is shared through HIEs. METHODS A mixed methods study consisting of two phases was conducted. A validated survey instrument was emailed to clinical and non-clinical staff in Alabama and Oklahoma. The survey captured information about the impact of predictors on the intention to use behavioral health data in clinical decision-making. Follow-up interviews were conducted with a subsample of participants to understand the survey results better. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data. Thematic analysis was used to identify themes from the interviews. RESULTS Sixty-two participants completed the survey. 62.91% of the participants were clinicians. Performance expectancy (β= .382, P= .01) and trust (β= .539, P= .00) predicted intention to use behavioral health information shared via HIEs. Interviewees expressed that behavioral health information could be useful in clinical decision-making. However, privacy and confidentiality concerns discourage sharing this information, and it is generally missing from the patient record altogether. The interviewees (n= 5) also stated that training for HIE use was not mandatory, and the training that was provided did not focus on the exchange of behavioral health information specifically. CONCLUSIONS Despite barriers, individuals are willing to use behavioral health information from HIEs if they believe that it will enhance job performance and if the information being transmitted is trustworthy. The findings contribute to our understanding of the role HIEs can play in delivering integrated care, particularly to vulnerable patients.

scholarly journals Intention to Use Behavioral Health Data from a Health Information Exchange: A Mixed Methods Study (Preprint)

10.2196/26746 ◽  
2020 ◽  
Author(s):  
Randyl A. Cochran ◽  
Sue S. Feldman ◽  
Nataliya V. Ivankova ◽  
Allyson G. Hall ◽  
William Opoku-Agyeman
Keyword(s):  
Mixed Methods ◽  
Behavioral Health ◽  
Health Information ◽  
Information Exchange ◽  
Health Information Exchange ◽  
Health Data ◽  
Mixed Methods Study ◽  
Intention To Use

Artificial Neural Learning Based on Big Data Process for eHealth Applications

2016 ◽  
pp. 1524-1540
Author(s):  
Nuno Pombo ◽  
Nuno M. Garcia ◽  
Kouamana Bousson ◽  
Virginie Felizardo
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Healthcare Systems ◽  
Reliable Data ◽  
Computational Learning ◽  
Related Information ◽  
Data Process ◽  
Neural Learning ◽  
Health Related

The complexity of the clinical context requires systems with the capability to make decisions based on reduced sets of data. Moreover, the adoption of mobile and ubiquitous devices could provide personal health-related information. In line with this, eHealth application faces several challenges so as to provide accurate and reliable data to both healthcare professionals and patients. This chapter focuses on computational learning on the healthcare systems presenting different classification processes to obtain knowledge from data. Finally, a case study based on a radial basis function neural network aiming the estimation of ECG waveform is explained. The presented model revealed its adaptability and suitability to support clinical decision making. However, complementary studies should be addressed to enable the model to predict the upper and lower points related to upward and downward deflections.

Artificial Neural Learning Based on Big Data Process for eHealth Applications

2015 ◽  
pp. 291-306 ◽  
Author(s):  
Nuno Pombo ◽  
Nuno M. Garcia ◽  
Kouamana Bousson ◽  
Virginie Felizardo
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Healthcare Systems ◽  
Reliable Data ◽  
Computational Learning ◽  
Related Information ◽  
Data Process ◽  
Neural Learning ◽  
Health Related

The complexity of the clinical context requires systems with the capability to make decisions based on reduced sets of data. Moreover, the adoption of mobile and ubiquitous devices could provide personal health-related information. In line with this, eHealth application faces several challenges so as to provide accurate and reliable data to both healthcare professionals and patients. This chapter focuses on computational learning on the healthcare systems presenting different classification processes to obtain knowledge from data. Finally, a case study based on a radial basis function neural network aiming the estimation of ECG waveform is explained. The presented model revealed its adaptability and suitability to support clinical decision making. However, complementary studies should be addressed to enable the model to predict the upper and lower points related to upward and downward deflections.

scholarly journals THE ROLE OF HEALTH INFORMATION SYSTEM IN MATERNAL AND CHILD HEALTHCARE SERVICES

2017 ◽  
Vol 10 (6) ◽  
pp. 29
Author(s):  
Rakhi Chowdhury ◽  
Leena Kumari ◽  
Subhamay Panda
Keyword(s):  
Health Care ◽  
Information System ◽  
Child Health ◽  
Health Information ◽  
Maternal And Child Health ◽  
Health Information System ◽  
Health Care Sector ◽  
Related Information ◽  
Health Related ◽  
And Child Health

Health information system deals with any system that helps in capturing, storing, transmitting, and managing health-related information of an individual or to demonstrate the activities or organizations working within health-care sector. In the developing countries, maternal and child health is gaining concern due to increasing cases of morbidity and mortality. The disparities among the maternal, infant, and child health are a growing concern in India and are governed by various determinants such as socioeconomic status, literacy, quality of health care, discrimination, and biological and genetic factors. Accurate and reliable health information and data are the basis for decision-making across the health-care sector and are crucial for the development and implementation of health system policy by the policy-makers. Strict monitoring and evaluation of the present program design and its implementation is required at the microlevel to effectively utilize the resources for the improvement of maternal and child health. Our present article focuses on evaluating the coverage gap at the different levels for the provision of health-care facilities to maternal, neonatal, and child health, immunization, and treatment of poor children. Big data plays a major role in providing sound and reliable health-related information and also help in managing and recording structured and unstructured data. More concrete plans are required further to reduce the inequalities in health-care interventions for providing better maternal and child health-care services in our nation.

scholarly journals Datos relativos a la salud y datos genéticos: consecuencias jurídicas de su conceptualización / Health data and Genetic data: the legal consequences of their conceptualization

2018 ◽  
pp. 55-66
Author(s):  
Daniel Jove Villares
Keyword(s):  
Data Protection ◽  
Genetic Data ◽  
Health Data ◽  
General Data Protection Regulation ◽  
Related Information ◽  
Health Related ◽  
General Data ◽  
New Criteria ◽  
Legal Consequences ◽  
Scope Of Protection

Existen determinadas categorías de datos que, por sus características, requieren de un régimen más estricto, regulación que, en ocasiones está necesitada de concreción. El presente trabajo incide en la necesidad de repensar qué datos genéticos y qué informaciones relacionadas con la salud deben considerarse como sensibles, amén de proponer nuevos criterios para su delimitación. La clarificación de la esfera de protección de estas tipologías de datos se hace perentoria en aquellos ordenamientos en que se establezcan limitaciones adicionales para las categorías de datos que protagonizan este artículo. Situación que el Reglamento General de Protección de Datos de la Unión Europea habilita.   There are certain categories of data which, due to their characteristics, require a stricter regime, regulation which, at times, needs to be specified. This paper focuses on the need to rethink which genetic data and health-related information should be considered as sensitive and to propose new criteria for their delimitation. The clarification of the scope of protection of these types of data is urgently needed in those legal systems in which additional limitations are established for the categories of data covered by this article. Situation that the European Union's General Data Protection Regulation enables. 

scholarly journals Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign

2016 ◽  
Vol 3 (2) ◽  
pp. e26 ◽  
Author(s):  
Deborah J Cohen ◽  
Sara R Keller ◽  
Gillian R Hayes ◽  
David A Dorr ◽  
Joan S Ash ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Care ◽  
Clinical Decision ◽  
Health Data ◽  
Lessons Learned

scholarly journals Development of an Instrument to Assess Parents’ Excessive Web-Based Searches for Information Pertaining to Their Children’s Health: The “Children’s Health Internet Research, Parental Inventory” (CHIRPI)

10.2196/16148 ◽  
2020 ◽  
Vol 22 (4) ◽  
pp. e16148
Author(s):  
Antonia Barke ◽  
Bettina K Doering
Keyword(s):  
Health Information ◽  
Health Anxiety ◽  
Chronically Ill ◽  
Children's Health ◽  
Internet Research ◽  
Children’S Health ◽  
Web Based ◽  
Related Information ◽  
Health Related ◽  
Main Effects

Background People often search the internet to obtain health-related information not only for themselves but also for family members and, in particular, their children. However, for a minority of parents, such searches may become excessive and distressing. Little is known about excessive web-based searching by parents for information regarding their children’s health. Objective This study aimed to develop and validate an instrument designed to assess parents' web-based health information searching behavior, the Children’s Health Internet Research, Parental Inventory (CHIRPI). Methods A pilot survey was used to establish the instrument (21 items). CHIRPI was validated online in a second sample (372/384, 96.9% mothers; mean age 32.7 years, SD 5.8). Item analyses, an exploratory factor analysis (EFA), and correlations with parents’ perception of their children’s health-related vulnerability (Child Vulnerability Scale, CVS), parental health anxiety (modified short Health Anxiety Inventory, mSHAI), and parental cyberchondria (Cyberchondria Severity Scale, CSS-15) were calculated. A subset of participants (n=73) provided retest data after 4 weeks. CHIRPI scores (total scores and subscale scores) of parents with a chronically ill child and parents who perceived their child to be vulnerable (CVS+; CVS>10) were compared with 2×2 analyses of variances (ANOVAs) with the factors Child’s Health Status (chronically ill vs healthy) and perceived vulnerability (CVS+ vs CVS−). Results CHIRPI’s internal consistency was standardized alpha=.89. The EFA identified three subscales: Symptom Focus (standardized alpha=.87), Implementing Advice (standardized alpha=.74) and Distress (standardized alpha=.89). The retest reliability of CHIRPI was measured as rtt=0.78. CHIRPI correlated strongly with CSS-15 (r=0.66) and mSHAI (r=0.39). The ANOVAs comparing the CHIRPI total score and the subscale scores for parents having a chronically ill child and parents perceiving their child as vulnerable revealed the main effects for perceiving one’s child as vulnerable but not for having a chronically ill child. No interactions were found. This pattern was observed for the CHIRPI total score (η2=0.053) and each subscale (Symptom Focus η2=0.012; Distress η2=0.113; and Implementing Advice η2=0.018). Conclusions The psychometric properties of CHIRPI are excellent. Correlations with mSHAI and CSS-15 indicate its validity. CHIRPI appears to be differentially sensitive to excessive searches owing to parents perceiving their child’s health to be vulnerable rather than to higher informational needs of parents with chronically ill children. Therefore, it may help to identify parents who search excessively for web-based health information. CHIRPI (and, in particular, the Distress subscale) seems to capture a pattern of factors related to anxious health-related cognitions, emotions, and behaviors of parents, which is also applied to their children.

scholarly journals Exploring the role of the Care and Health Information Exchange (CHIE) in clinical decision-making: a realist evaluation

2020 ◽  
Author(s):  
Philip Scott ◽  
Elisavet Andrikopoulou ◽  
Haythem Nakkas ◽  
Paul Roderick
Keyword(s):  
Decision Making ◽  
Health Information ◽  
Information Exchange ◽  
Healthcare Professionals ◽  
Clinical Decision Making ◽  
Social Care ◽  
Health Information Exchange ◽  
Clinical Decision ◽  
Health And Social Care ◽  
The Impact

Background: The overall evidence for the impact of electronic information systems on cost, quality and safety of healthcare remains contested. Whilst it seems intuitively obvious that having more data about a patient will improve care, the mechanisms by which information availability is translated into better decision-making are not well understood. Furthermore, there is the risk of data overload creating a negative outcome. There are situations where a key information summary can be more useful than a rich record. The Care and Health Information Exchange (CHIE) is a shared electronic health record for Hampshire and the Isle of Wight that combines key information from hospital, general practice, community care and social services. Its purpose is to provide clinical and care professionals with complete, accurate and up-to-date information when caring for patients. CHIE is used by GP out-of-hours services, acute hospital doctors, ambulance service, GPs and others in caring for patients. Research questions: The fundamental question was How does awareness of CHIE or usage of CHIE affect clinical decision-making? The secondary questions were What are the latent benefits of CHIE in frontline NHS operations? and What is the potential of CHIE to have an impact on major NHS cost pressures? The NHS funders decided to focus on acute medical inpatient admissions as the initial scope, given the high costs associated with hospital stays and the patient complexities (and therefore information requirements) often associated with unscheduled admissions. Methods: Semi-structured interviews with healthcare professionals to explore their experience about the utility of CHIE in their clinical scenario, whether and how it has affected their decision-making practices and the barriers and facilitators for their use of CHIE. The Framework Method was used for qualitative analysis, supported by the software tool Atlas.ti. Results: 21 healthcare professionals were interviewed. Three main functions were identified as useful: extensive medication prescribing history, information sharing between primary, secondary and social care and access to laboratory test results. We inferred two positive cognitive mechanisms: knowledge confidence and collaboration assurance, and three negative ones: consent anxiety, search anxiety and data mistrust. Conclusions: CHIE gives clinicians the bigger picture to understand the patient's health and social care history and circumstances so as to make confident and informed decisions. CHIE is very beneficial for medicines reconciliation on admission, especially for patients that are unable to speak or act for themselves or who cannot remember their precise medication or allergies. We found no clear evidence that CHIE has a significant impact on admission or discharge decisions. We propose the use of recommender systems to help clinicians navigate such large volumes of patient data, which will only grow as additional data is collected.

scholarly journals Online Health Information Seeking by Parents for Their Children: Systematic Review and Agenda for Further Research

10.2196/19985 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e19985
Author(s):  
Christian Kubb ◽  
Heather M Foran
Keyword(s):  
Systematic Review ◽  
Conceptual Model ◽  
Health Information ◽  
Information Seeking ◽  
Online Health Information ◽  
Health Information Seeking ◽  
Related Information ◽  
Health Related ◽  
Online Health Information Seeking ◽  
The Web

Background Parents commonly use the internet to search for information about their child’s health-related symptoms and guide parental health-related decisions. Despite the impact of parental online health seeking on offline health behaviors, this area of research remains understudied. Previous literature has not adequately distinguished searched behaviors when searching for oneself or one`s child. Objective The purpose of this review is to examine prevalences and associated variables of parent-child online health information seeking; investigate parents’ health-related online behavior regarding how they find, use, and evaluate information; and identify barriers and concerns that they experience during the search. Based on this analysis, we develop a conceptual model of potentially important variables of proxy online health information seeking, with a focus on building an agenda for further research. Methods We conducted a comprehensive systematic literature review of the PsycINFO, JMIR, and PubMed electronic databases. Studies between January 1994 and June 2018 were considered. The conceptual model was developed using an inductive mixed methods approach based on the investigated variables in the study sample. Results A total of 33 studies met the inclusion criteria. Findings suggest that parents worldwide are heavy online users of health-related information for their children across highly diverse circumstances. A total of 6 studies found high parental health anxiety, with prevalences ranging from 14% to 52%. Although parents reported wishing for more guidance from their pediatrician on how to find reliable information, they rarely discussed retrieved information from the web. The conceptual model of proxy online health information seeking includes 49 variables. Conclusions This systematic review identifies important gaps regarding the influence of health-related information on parents’ health behavior and outcomes. Follow-up studies are required to offer parents guidance on how to use the web for health purposes in an effective way, as well as solutions to the multifaceted problems during or after online health information seeking for their child. The conceptual model with the number of studies in each model category listed highlights how previous studies have hardly considered relational variables between the parent and child. An agenda for future research is presented.

Beyond the Development of Health-Related Quality-of-Life (HRQOL) Measures: A Checklist for Evaluating HRQOL Outcomes in Cancer Clinical Trials—Does HRQOL Evaluation in Prostate Cancer Research Inform Clinical Decision Making?

2003 ◽  
Vol 21 (18) ◽  
pp. 3502-3511 ◽  
Author(s):  
Fabio Efficace ◽  
Andrew Bottomley ◽  
David Osoba ◽  
Carolyn Gotay ◽  
Henning Flechtner ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Clinical Trials ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Cancer Clinical Trials ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

Purpose: The aim of this study was to evaluate whether the inclusion of health-related quality of life (HRQOL), as a part of the trial design in a randomized controlled trial (RCT) setting, has supported clinical decision making for the planning of future medical treatments in prostate cancer. Materials and Methods: A minimum standard checklist for evaluating HRQOL outcomes in cancer clinical trials was devised to assess the quality of the HRQOL reporting and to classify the studies on the grounds of their robustness. It comprises 11 key HRQOL issues grouped into four broader sections: conceptual, measurement, methodology, and interpretation. Relevant studies were identified in a number of databases, including MEDLINE and the Cochrane Controlled Trials Register. Both their HRQOL and traditional clinical reported outcomes were systematically analyzed to evaluate their consistency and their relevance for supporting clinical decision making. Results: Although 54% of the identified studies did not show any differences in traditional clinical end points between treatment arms and 17% showed a difference in overall survival, 74% of the studies showed some difference in terms of HRQOL outcomes. One third of the RCTs provided a comprehensive picture of the whole treatment including HRQOL outcomes to support their conclusions. Conclusion: A minimum set of criteria for assessing the reported outcomes in cancer clinical trials is necessary to make informed decisions in clinical practice. Using a checklist developed for this study, it was found that HRQOL is a valuable source of information in RCTs of treatment in metastatic prostate cancer.

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