Electronic Health Literacy among Patients with Dental Diseases

2018 ◽  
Author(s):  
Saeideh Valizadeh-Haghi ◽  
Shahabedin Rahmatizadeh
Keyword(s):  
Decision Making ◽  
Health Information ◽  
Information Quality ◽  
Educational Background ◽  
General Interest ◽  
P Value ◽  
Ehealth Literacy ◽  
Dental Patients ◽  
Dental Diseases ◽  
Electronic Health

To explore eHealth literacy and general interest in using eHealth information among patients with dental diseases. A total of 171 patients with dental diseases completed the survey including the eHEALS. The effect of participants' age, gender and education on eHealth literacy was assessed. Spearman’s correlation coefficient was also used to assess the correlation between the importance of access to health information and the usefulness of the internet for decision-making. The mean score of eHealth literacy in the participants was 30.55 (SD = 4.069) which shows that the participants had a high level of eHealth literacy. The participants' age has significant effect on eHealth literacy level (t = 3.573, P-value = 0.002). Moreover, there was a significant correlation between the total score of eHealth literacy and the importance of access to eHealth information (r = 0.33, n = 171, P < 0.001). The difference in eHealth literacy in terms of educational background showed no statistically significant differences (F = 1.179, P-value = 0.322). Determining eHealth literacy among dental patients leads to a better understanding of their problems in health decision-making. Furthermore, Dental institutions efforts should aim to raise awareness on online health information quality and to encourage patients to use evaluation tools, especially among low electronic health literate patients.

scholarly journals eHealth literacy and general interest in using online Health information: a survey among patients with dental diseases

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Saeideh Valizadeh-Haghi ◽  
Shahabedin Rahmatizadeh
Keyword(s):  
Health Information ◽  
Information Quality ◽  
Educational Background ◽  
Online Health Information ◽  
General Interest ◽  
P Value ◽  
Ehealth Literacy ◽  
Dental Patients ◽  
Dental Diseases ◽  
High Level

Objectives: The aim of the study is to explore the eHealth literacy and general interest in using eHealth information among patients with dental diseases.Methods: A total of 171 patients with dental diseases completed the survey including the eHEALS. The effect of participants' age, gender and education on eHealth literacy was assessed. Spearman’s correlation coefficient was also used to assess the correlation between the importance of access to health information and the usefulness of the internet for decision-making.Results: The mean score of eHealth literacy in the participants was 30.55 (SD=4.069). The participants' age has significant effect on eHealth literacy level (t=3.573, P-value=0.002). Moreover, there was a significant correlation between the total score of eHealth literacy and the importance of access to eHealth information (r=0.33, n=171, P<0.s001). The difference in eHealth literacy in terms of educational background showed no statistically significant differences (F=1.179, P-value=0.322).Discussion: the participants had a high level of eHealth literacy. Determining eHealth literacy among dental patients leads to a better understanding of their problems in health decision-making.Conclusion: Dental institutions efforts should aim to raise awareness on online health information quality and to encourage patients to use evaluation tools, especially among low electronic health literate patients.

Awareness and Use of Electronic Health Information Resources in Teaching, Research and Patient Care

2018 ◽  
Vol 7 (4) ◽  
pp. 45-68
Author(s):  
Samuel Akande Bello
Keyword(s):  
Health Information ◽  
Hypothesis Test ◽  
Information Resources ◽  
Descriptive Statistics ◽  
P Value ◽  
Frequency Of Use ◽  
Electronic Health ◽  
Health Information Resources ◽  
Electronic Health Information ◽  
University Of Ibadan

The central objective of this study was to determine the level of awareness and use of Electronic Health Information Resources (EHIRs) among the Academic Physicians of College of Medicine, University of Ibadan (COMUI), Nigeria. Others were to find out the frequency of use, the purposes and barriers against the use. Two hypotheses formulated and tested. This is a total enumeration research with 265 COMUI Academic Physicians, Nigeria. Questionnaire, designed with nominal and dichotomous questions was used. Data collected was analyzed with SPSS version 20.0. Descriptive statistics was used. Test of Pearson Moment Correlation (PMC) with Independent Sample t – test at 5% p – value used. The Academic Physicians mean age was 37.75. The results obtained indicated variations: 96.0% aware and used HINARI, 94.0% aware and used PubMed/Medline, NCBI was 64.9%. Hypothesis Test between awareness and use of EHIRs signified coefficient of proportionality (r = 218, p &lt; 05).

scholarly journals Veterinarians' information Prescription and Clients' eHealth Literacy

2019 ◽  
Vol 40 (2) ◽  
pp. 32-44 ◽  
Author(s):  
Niloofar Solhjoo ◽  
Nader Naghshineh ◽  
Fatima Fahimnia
Keyword(s):  
Health Information ◽  
Information Quality ◽  
Literacy Skills ◽  
Veterinary Services ◽  
Ehealth Literacy ◽  
Telephone Interviews ◽  
Pet Owners ◽  
Directed Information ◽  
Positive Feelings ◽  
Client Communication

Introduction: The aim of this study is to investigate the relationship between pet owner’s combined knowledge, comfort, and perceived skills at finding, evaluating, applying online pet health information, and the application of the information prescription (IP) provided for pet owners education on the internet. Methods: Thirty telephone interviews were conducted followed by a questionnaire of eHealth Literacy Scale (eHEALS) with pet owners after receiving an IP with a suggested websites in addition to their customary veterinary services in a vet clinic at the center of Tehran, Iran. Qualitative and quantitative data were merged to explore differences and similarities among respondents with different eHealth literacy levels. Results: Results indicate that pet owners with higher score of eHealth literacy more accessed the suggested websites and reported positive feelings about this addition to their veterinary services. Similarly, among the eight-item self-reported eHealth Literacy skills, perceived skills at evaluating and applying, were significantly associated with the use of IPs. Lastly eHealth literacy level was significantly associated with the outcomes of prescribed information, such as veterinarians-client communication outcome and learning outcomes.  Conclusion: Disparities in application of the veterinarian’s IPs for online pet healthcare information, and its outcomes are associated with different eHealth literacy skills. Veterinarians should collaborate with information specialists and librarians to perform education efforts to raise awareness on online pet health information quality and impact of veterinarian directed information prescription especially among low health literate owners.

scholarly journals The Measurements and an Elaborated Understanding of Chinese eHealth Literacy (C-eHEALS) in Chronic Patients in China

2018 ◽  
Vol 15 (7) ◽  
pp. 1553 ◽  
Author(s):  
Angela Chang ◽  
Peter Schulz
Keyword(s):  
Health Literacy ◽  
Health Information ◽  
Health Care Providers ◽  
Computer Literacy ◽  
Strong Association ◽  
Care Providers ◽  
Chronic Patients ◽  
Online Questionnaire ◽  
Ehealth Literacy ◽  
Electronic Health

The rapid rise of Internet-based technologies to disseminate health information and services has been shown to enhance online health information acquisition. A Chinese version of the electronic health literacy scale (C-eHEALS) was developed to measure patients’ combined knowledge and perceived skills at finding and applying electronic health information to health problems. A valid sample of 352 interviewees responded to the online questionnaire, and their responses were analyzed. The C-eHEALS, by showing high internal consistency and predictive validity, is an effective screening tool for detecting levels of health literacy in clinical settings. Individuals’ sociodemographic status, perceived health status, and level of health literacy were identified for describing technology users’ characteristics. A strong association between eHealth literacy level, media information use, and computer literacy was found. The emphasis of face-to-face inquiry for obtaining health information was important in the low eHealth literacy group while Internet-based technologies crucially affected decision-making skills in the high eHealth literacy group. This information is timely because it implies that health care providers can use the C-eHEALS to screen eHealth literacy skills and empower patients with chronic diseases with online resources.

scholarly journals Data Incompleteness Preventing Information Communication from Hospital Information Systems to the Iranian National Electronic Health Record (SEPAS)

2021 ◽  
Vol 10 (1) ◽  
pp. 97
Author(s):  
Reza Abbasi ◽  
Reza Khajouei ◽  
Monireh Sadeghi Jabali ◽  
Moghadameh Mirzaei
Keyword(s):  
Information System ◽  
Information Systems ◽  
Electronic Health Record ◽  
Health Information ◽  
Information Quality ◽  
Clinical Information ◽  
Health Information Systems ◽  
Hospital Information Systems ◽  
Health Record ◽  
Electronic Health

Introduction: One of the well-known problems related to the information quality is the information incompleteness in health information systems. The purpose of this study was to investigate the completeness rate of patients’ information recorded in the hospital information system, sending information from which to Iranian electronic health record system (SEPAS) seemed to be unsuccessful.Methods: This study was conducted in six hospitals associated with Kerman University of Medical Sciences (KUMS) in Iran. In this study, 882 records which had failed to be sent from three hospital information systems to SEPAS were reviewed and the data were collected using a checklist. Data were analyzed using the descriptive and inferential statistics with SPSS.18.Results: A total of 18758 demographic and clinical information elements were examined. The rate of completeness was 55%. The highest completeness rate of demographic information was related to name, surname, gender, nationality, date of birth, father's name, marital status, place of residence, telephone number (79-100%), and in clinical information it was related to the final diagnosis (74%). The completeness rate of some information elements was significantly different among the hospitals (p <0.05). The completeness rate of information communicated to the Iranian national electronic health record was at a moderate level.Conclusion: This study showed that completeness rate is different among hospitals using the same hospital information system. The results of this study can help the health policymakers and developers of the national electronic health record in developing countries to improve completeness rate and also information quality in health information systems.

scholarly journals Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis (Preprint)

2019 ◽  
Author(s):  
Lisa Lynne Hyde ◽  
Allison W Boyes ◽  
Lisa J Mackenzie ◽  
Lucy Leigh ◽  
Christopher Oldmeadow ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Medical Imaging ◽  
Health Information ◽  
Odds Ratio ◽  
Latent Class ◽  
Self Report ◽  
Measurement Tool ◽  
Cut Points ◽  
Ehealth Literacy ◽  
Electronic Health

BACKGROUND Variations in an individual’s electronic health (eHealth) literacy may influence the degree to which health consumers can benefit from eHealth. The eHealth Literacy Scale (eHEALS) is a common measure of eHealth literacy. However, the lack of guidelines for the standardized interpretation of eHEALS scores limits its research and clinical utility. Cut points are often arbitrarily applied to the eHEALS item or at the global level, which assumes a dichotomy of high and low eHealth literacy. This approach disregards scale constructs and results in inaccurate and inconsistent conclusions. Cluster analysis is an exploratory technique, which can be used to overcome these issues, by identifying classes of patients reporting similar eHealth literacy without imposing data cut points. OBJECTIVE The aim of this cross-sectional study was to identify classes of patients reporting similar eHealth literacy and assess characteristics associated within each class. METHODS Medical imaging outpatients were recruited consecutively in the waiting room of one major public hospital in New South Wales, Australia. Participants completed a self-report questionnaire assessing their sociodemographic characteristics and eHealth literacy, using the eHEALS. Latent class analysis was used to explore eHealth literacy clusters identified by a distance-based cluster analysis, and to identify characteristics associated with class membership. RESULTS Of the 268 eligible and consenting participants, 256 (95.5%) completed the eHEALS. Consistent with distance-based findings, 4 latent classes were identified, which were labeled as low (21.1%, 54/256), moderate (26.2%, 67/256), high (32.8%, 84/256), and very high (19.9%, 51/256) eHealth literacy. Compared with the low class, participants who preferred to receive a lot of health information reported significantly higher odds of moderate eHealth literacy (odds ratio 16.67, 95% CI 1.67-100.00; P=.02), and those who used the internet at least daily reported significantly higher odds of high eHealth literacy (odds ratio 4.76, 95% CI 1.59-14.29; P=.007). CONCLUSIONS The identification of multiple classes of eHealth literacy, using both distance-based and latent class analyses, highlights the limitations of using the eHEALS global score as a dichotomous measurement tool. The findings suggest that eHealth literacy support needs vary in this population. The identification of low and moderate eHealth literacy classes indicate that the design of eHealth resources should be tailored to patients’ varying levels of eHealth literacy. eHealth literacy improvement interventions are needed, and these should be targeted based on individuals’ internet use frequency and health information amount preferences.

scholarly journals Electronic Health Literacy Among Magnetic Resonance Imaging and Computed Tomography Medical Imaging Outpatients: Cluster Analysis

10.2196/13423 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e13423 ◽  
Author(s):  
Lisa Lynne Hyde ◽  
Allison W Boyes ◽  
Lisa J Mackenzie ◽  
Lucy Leigh ◽  
Christopher Oldmeadow ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Medical Imaging ◽  
Health Information ◽  
Odds Ratio ◽  
Latent Class ◽  
Measurement Tool ◽  
Class Membership ◽  
Cut Points ◽  
Ehealth Literacy ◽  
Electronic Health

Background Variations in an individual’s electronic health (eHealth) literacy may influence the degree to which health consumers can benefit from eHealth. The eHealth Literacy Scale (eHEALS) is a common measure of eHealth literacy. However, the lack of guidelines for the standardized interpretation of eHEALS scores limits its research and clinical utility. Cut points are often arbitrarily applied at the eHEALS item or global level, which assumes a dichotomy of high and low eHealth literacy. This approach disregards scale constructs and results in inaccurate and inconsistent conclusions. Cluster analysis is an exploratory technique, which can be used to overcome these issues, by identifying classes of patients reporting similar eHealth literacy without imposing data cut points. Objective The aim of this cross-sectional study was to identify classes of patients reporting similar eHealth literacy and assess characteristics associated with class membership. Methods Medical imaging outpatients were recruited consecutively in the waiting room of one major public hospital in New South Wales, Australia. Participants completed a self-report questionnaire assessing their sociodemographic characteristics and eHealth literacy, using the eHEALS. Latent class analysis was used to explore eHealth literacy clusters identified by a distance-based cluster analysis, and to identify characteristics associated with class membership. Results Of the 268 eligible and consenting participants, 256 (95.5%) completed the eHEALS. Consistent with distance-based findings, 4 latent classes were identified, which were labeled as low (21.1%, 54/256), moderate (26.2%, 67/256), high (32.8%, 84/256), and very high (19.9%, 51/256) eHealth literacy. Compared with the low class, participants who preferred to receive a lot of health information reported significantly higher odds of moderate eHealth literacy (odds ratio 16.67, 95% CI 1.67-100.00; P=.02), and those who used the internet at least daily reported significantly higher odds of high eHealth literacy (odds ratio 4.76, 95% CI 1.59-14.29; P=.007). Conclusions The identification of multiple classes of eHealth literacy, using both distance-based and latent class analyses, highlights the limitations of using the eHEALS global score as a dichotomous measurement tool. The findings suggest that eHealth literacy support needs vary in this population. The identification of low and moderate eHealth literacy classes indicate that the design of eHealth resources should be tailored to patients’ varying levels of eHealth literacy. eHealth literacy improvement interventions are needed, and these should be targeted based on individuals’ internet use frequency and health information amount preferences.

scholarly journals Factors Associated to Basic Emergency Obstetric Neonatal Care (BEONC) Nurses' Decision Making Skill

2018 ◽  
Vol 13 (2) ◽  
pp. 64
Author(s):  
Ahsan Ahsan ◽  
Ni Luh Diah Ayu Sita Dewi ◽  
Ali Haedar ◽  
Ike Nesdia Rahmawati
Keyword(s):  
Decision Making ◽  
Critical Thinking ◽  
Employment Status ◽  
Tertiary Education ◽  
Care Center ◽  
Educational Background ◽  
P Value ◽  
Health Care Center ◽  
Emergency Condition ◽  
Condition Recognition

<em><span lang="EN-US">Neonatal mortality rate (NMR) is an indicator to measure health degree of an area, health problem which involves some institutions to take a decision. The postponement of emergency condition recognition, attaining health facilities, and treatment are three theories of neonatal emergency postponement. The prominent problem of postponement of emergency condition recognition is nurse's ability to think critically to take a decision to determine emergency condition in neonatal. Critical thinking skill is an obligation competence for neonatal emergency nurses. Some theories reveal that characteristic of age, gender, educational background, training and tertiary education, working experience, and employment status influence nurses's decision making skill in treating neonatal emergency case. Different curriculum for introduction to critical thinking in treating neonatal emergency is a basis problem to be a neonatal emergency competent nurse. This research aims to analyze age, gender, education, advance training, experience, and employment status towards decision making skill neonatal emergency implementation at community health care center PONED. This research used cross sectional with purposive sampling. One hundred fifty three (153) nurses were invoked to be the subjects of this research. Besides, this research used Closed Ended Instrument. Based on the results of cross table, p value p&gt;0.05 age, training, working experience and employment status were not related to decision making skill in emergency. Furthermore, male and bachelor of nursing science (p&lt;0.05) is decision making skill of nurses in neonatal emergency. It is concluded that gender and nurse's educational background related to situation awareness. The results of this research are expected to encourage on service quality enhancement of neonatal emergency treatment.</span></em>

scholarly journals Citywide quality of health information system through text mining of electronic health records

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Anastasia A. Funkner ◽  
Michil P. Egorov ◽  
Sergey A. Fokin ◽  
Gennady M. Orlov ◽  
Sergey V. Kovalchuk
Keyword(s):  
Electronic Health Records ◽  
Health Information ◽  
Language Processing ◽  
Information Quality ◽  
Medical Information ◽  
Health Information System ◽  
Interconnected System ◽  
Health Records ◽  
Electronic Health

AbstractA system of hospitals in large cities can be considered a large and diverse but interconnected system. Widely applied in hospitals, electronic health records (EHR) are crucially different from each other because of the use of different health information systems, internal hospital rules, and individual behavior of physicians. The unstructured (textual) data of EHR is rarely used to assess the citywide quality of healthcare. Within the study, we analyze EHR data, particularly textual unstructured data, as a reflection of the complex multi-agent system of healthcare in the city of Saint Petersburg, Russia. Through analyzing the data collected by the Medical Information and Analytical Center, a method was proposed and evaluated for identifying a common structure, understanding the diversity, and assessing information quality in EHR data through the application of natural language processing techniques.

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