Role of Individual Motivations and Privacy Concerns in the Adoption of German Electronic Patient Record Apps-A Mixed-Methods Study.
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ABSTRACT:
SUBMITTER: Henkenjohann R
PROVIDER: S-EPMC8471641 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Despite the availability of a great variety of consumer-oriented wearable devices, perceived usefulness, user satisfaction, and privacy concerns have not been fully investigated in the field of wearable applications. It is not clear why healthy, active citizens equip themselves with wearable technology for running activities, and what privacy and data sharing features might influence their individual decisions. OBJECTIVE:The primary aim of the study was to shed light on motivational and privacy aspects of wearable technology used by healthy, active citizens. A secondary aim was to reevaluate smart technology adoption within the running community in Germany in 2017 and to compare it with the results of other studies and our own study from 2016. METHODS:A questionnaire was designed to assess what wearable technology is used by runners of different ages and sex. Data on motivational factors were also collected. The survey was conducted at a regional road race event in May 2017, paperless via a self-implemented app. The demographic parameters of the sample cohort were compared with the event's official starter list. In addition, the validation included comparison with demographic parameters of the largest German running events in Berlin, Hamburg, and Frankfurt/Main. Binary logistic regression analysis was used to investigate whether age, sex, or course distance were associated with device use. The same method was applied to analyze whether a runner's age was predictive of privacy concerns, openness to voluntary data sharing, and level of trust in one's own body for runners not using wearables (ie, technological assistance considered unnecessary in this group). RESULTS:A total of 845 questionnaires were collected. Use of technology for activity monitoring during events or training was prevalent (73.0%, 617/845) in this group. Male long-distance runners and runners in younger age groups (30-39 years: odds ratio [OR] 2.357, 95% CI 1.378-4.115; 40-49 years: OR 1.485, 95% CI 0.920-2.403) were more likely to use tracking devices, with ages 16 to 29 years as the reference group (OR 1). Where wearable technology was used, 42.0% (259/617) stated that they were not concerned if data might be shared by a device vendor without their consent. By contrast, 35.0% (216/617) of the participants would not accept this. In the case of voluntary sharing, runners preferred to exchange tracked data with friends (51.7%, 319/617), family members (43.4%, 268/617), or a physician (32.3%, 199/617). A large proportion (68.0%, 155/228) of runners not using technology stated that they preferred to trust what their own body was telling them rather than trust a device or an app (50-59 years: P<.001; 60-69 years: P=.008). CONCLUSIONS:A total of 136 distinct devices by 23 vendors or manufacturers and 17 running apps were identified. Out of 4, 3 runners (76.8%, 474/617) always trusted in the data tracked by their personal device. Data privacy concerns do, however, exist in the German running community, especially for older age groups (30-39 years: OR 1.041, 95% CI 0.371-0.905; 40-49 years: OR 1.421, 95% CI 0.813-2.506; 50-59 years: OR 2.076, 95% CI 1.813-3.686; 60-69 years: OR 2.394, 95% CI 0.957-6.183).
| S-EPMC6315235 | biostudies-other
Project description:ObjectiveThe study sought to develop and empirically validate an integrative situational privacy calculus model for explaining potential users' privacy concerns and intention to install a contact tracing mobile application (CTMA).Materials and methodsA survey instrument was developed based on the extant literature in 2 research streams of technology adoption and privacy calculus. Survey participants (N = 853) were recruited from all 50 U.S. states. Partial least squares structural equation modeling was used to validate and test the model.ResultsIndividuals' intention to install a CTMA is influenced by their risk beliefs, perceived individual and societal benefits to public health, privacy concerns, privacy protection initiatives (legal and technical protection), and technology features (anonymity and use of less sensitive data). We found only indirect relationships between trust in public health authorities and intention to install CTMA. Sex, education, media exposure, and past invasion of privacy did not have a significant relationship either, but interestingly, older people were slightly more inclined than younger people to install a CTMA.DiscussionOur survey results confirm the initial concerns about the potentially low adoption rates of CTMA. Our model provides public health agencies with a validated list of factors influencing individuals' privacy concerns and beliefs, enabling them to systematically take actions to address these identified issues, and increase CTMA adoption.ConclusionsDeveloping CTMAs and increasing their adoption is an ongoing challenge for public health systems and policymakers. This research provides an evidence-based and situation-specific model for a better understanding of this theoretically and pragmatically important phenomenon.
| S-EPMC7936517 | biostudies-literature
Project description:BackgroundThe rapid expansion in the use of electronic health records (EHR) has increased the number of medical errors originating in health information systems (HIS). The sociotechnical approach helps in understanding risks in the development, implementation, and use of EHR and health information technology (HIT) while accounting for complex interactions of technology within the health care system.ObjectiveThis study addresses two important questions: (1) "which of the common EHR error types are associated with perceived high- and extreme-risk severity ratings among EHR users?", and (2) "which variables are associated with high- and extreme-risk severity ratings?"MethodsThis study was a quantitative, non-experimental, descriptive study of EHR users. We conducted a cross-sectional web-based questionnaire study at the largest hospital district in Finland. Statistical tests included the reliability of the summative scales tested with Cronbach's alpha. Logistic regression served to assess the association of the independent variables to each of the eight risk factors examined.ResultsA total of 2864 eligible respondents provided the final data. Almost half of the respondents reported a high level of risk related to the error type "extended EHR unavailability". The lowest overall risk level was associated with "selecting incorrectly from a list of items". In multivariate analyses, profession and clinical unit proved to be the strongest predictors for high perceived risk. Physicians perceived risk levels to be the highest ( P<.001 in six of eight error types), while emergency departments, operating rooms, and procedure units were associated with higher perceived risk levels ( P<.001 in four of eight error types). Previous participation in eLearning courses on EHR-use was associated with lower risk for some of the risk factors.ConclusionsBased on a large number of Finnish EHR users in hospitals, this study indicates that HIT safety hazards should be taken very seriously, particularly in operating rooms, procedure units, emergency departments, and intensive care units/critical care units. Health care organizations should use proactive and systematic assessments of EHR risks before harmful events occur. An EHR training program should be compulsory for all EHR users in order to address EHR safety concerns resulting from the failure to use HIT appropriately.
| S-EPMC4890731 | biostudies-literature
Project description:BackgroundThis study's goal is to understand the factors that drive individuals to adopt Electronic Health Record (EHR) portals and to estimate if there are differences between countries with different healthcare models.MethodsWe applied a new adoption model using as a starting point the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) by incorporating the Concern for Information Privacy (CFIP) framework. To evaluate the research model we used the partial least squares (PLS) - structural equation modelling (SEM) approach. An online questionnaire was administrated in the United States (US) and Europe (Portugal). We collected 597 valid responses.ResultsThe statistically significant factors of behavioural intention are performance expectancy ([Formula: see text] total?=?0.285; P?<?0.01), effort expectancy ([Formula: see text] total?=?0.160; P?<?0.01), social influence ([Formula: see text] total?=?0.198; P?<?0.01), hedonic motivation ([Formula: see text] total?=?-0.141; P?<?0.01), price value ([Formula: see text] total?=?0.152; P?<?0.01), and habit ([Formula: see text] total?=?0.255; P?<?0.01). The predictors of use behaviour are habit ([Formula: see text] total?=?0.145; P?<?0.01), and behavioural intention ([Formula: see text] total?=?0.480; P?<?0.01). Social influence, hedonic motivation, and price value are only predictors in the US group. The model explained 53% of the variance in behavioural intention and 36% of the variance in use behaviour.ConclusionsOur study identified critical factors for the adoption of EHR portals and significant differences between the countries. Confidentiality issues do not seem to influence acceptance. The EHR portals usage patterns are significantly higher in US compared to Portugal.
| S-EPMC5499062 | biostudies-literature
Project description:ObjectiveA recent Institute of Medicine report called for attention to safety issues related to electronic health records (EHRs). We analyzed EHR-related safety concerns reported within a large, integrated healthcare system.MethodsThe Informatics Patient Safety Office of the Veterans Health Administration (VA) maintains a non-punitive, voluntary reporting system to collect and investigate EHR-related safety concerns (ie, adverse events, potential events, and near misses). We analyzed completed investigations using an eight-dimension sociotechnical conceptual model that accounted for both technical and non-technical dimensions of safety. Using the framework analysis approach to qualitative data, we identified emergent and recurring safety concerns common to multiple reports.ResultsWe extracted 100 consecutive, unique, closed investigations between August 2009 and May 2013 from 344 reported incidents. Seventy-four involved unsafe technology and 25 involved unsafe use of technology. A majority (70%) involved two or more model dimensions. Most often, non-technical dimensions such as workflow, policies, and personnel interacted in a complex fashion with technical dimensions such as software/hardware, content, and user interface to produce safety concerns. Most (94%) safety concerns related to either unmet data-display needs in the EHR (ie, displayed information available to the end user failed to reduce uncertainty or led to increased potential for patient harm), software upgrades or modifications, data transmission between components of the EHR, or 'hidden dependencies' within the EHR.DiscussionEHR-related safety concerns involving both unsafe technology and unsafe use of technology persist long after 'go-live' and despite the sophisticated EHR infrastructure represented in our data source. Currently, few healthcare institutions have reporting and analysis capabilities similar to the VA.ConclusionsBecause EHR-related safety concerns have complex sociotechnical origins, institutions with long-standing as well as recent EHR implementations should build a robust infrastructure to monitor and learn from them.
| S-EPMC4215044 | biostudies-literature
Project description:BackgroundElectronic Medical Records (EMRs) are one of a range of digital health solutions that are key enablers of the data revolution transforming the health sector. They offer a wide range of benefits to health professionals, patients, researchers and other key stakeholders. However, effective implementation has proved challenging.MethodsA qualitative methodology was used in the study. Interviews were conducted with 12 clinical and administrative staff of a cancer centre at one-month pre-launch and eight clinical and administrative staff at 12-months post-launch of an EMR. Data from the interviews was collected via audio recording. Audio recordings were transcribed, de-identified and analysed to identify staff experiences with the EMR.ResultsData from the pre-implementation interviews were grouped into four categories: 1) Awareness and understanding of EMR; 2) Engagement in launch process; 3) Standardisation and completeness of data; 4) Effect on workload. Data from the post-launch interviews were grouped into six categories: 1) Standardisation and completeness of data; 2) Effect on workload; 3) Feature completeness and functionality; 4) Interaction with technical support; 5) Learning curve; 6) Buy-in from staff. Two categories: Standardisation and completeness of data and effect on workload were common across pre and post-implementation interviews.ConclusionFindings from this study contribute new knowledge on barriers and enablers to the implementation of EMRs in complex clinical settings. Barriers to successful implementation include lack of technical support once the EMR has launched, health professional perception the EMR increases workload, and the learning curve for staff adequately familiarize themselves with using the EMR.
| S-EPMC7789279 | biostudies-literature
Project description:OBJECTIVE: To describe small area variation in ambulatory electronic health record (EHR) adoption and assess evidence of a "digital divide" in whether adoption is lagging in traditionally underserved communities. DATA SOURCES: Survey data on U.S. ambulatory health care sites (261,973 sites representing 716,160 providers) collected by SK&A Information Services in 2011. STUDY DESIGN: We examined cross-sectional variation in two measures of local area EHR adoption: share of providers at sites using an EHR with e-prescribing functionality; and predicted probability of EHR adoption for the average site. Local areas were defined as Public Use Microdata Areas (n = 2,068). Using multivariate regression, we examined the association between adoption and three area characteristics: high concentration of minority population; high concentration of low-income population; and metropolitan status. PRINCIPAL FINDINGS: EHR adoption varied significantly across local areas, ranging from 8 to 88 percent with a median of 41 percent. Adoption was lower in large metropolitan areas; areas with high concentration of minority population in the Northeast and West; and areas with high concentration of low-income population in the Midwest. CONCLUSIONS: Our 2011 estimates suggest there was substantial room for increased EHR adoption across the United States, including some underserved areas with relatively low EHR adoption rates. Further research should monitor policy initiatives in these areas and examine sources of heterogeneity in low- and high-adoption communities.
| S-EPMC3876400 | biostudies-other
Project description:IntroductionPrivacy concerns are an important barrier to adoption and continued use of digital technologies, particularly in the health sector. With the introduction of mobile health applications (mHealth apps), the construct of app information privacy concerns has received increased attention. However, few validated measures exist to capture said concerns in population samples, although they can help to improve public health efforts.MethodsUsing a cross-sectional survey of German adults (mean age = 35.62; 63.5% female), this study examined psychometric properties of the app information privacy concerns scale (AIPC). Analyses comprised confirmatory factor analysis, factorial validity (exploratory factor analysis), internal consistency, convergent validity (i.e., correlations with privacy victimhood, and app privacy concerns), and discriminant validity (i.e., daily app use, adoption intentions, and attitudes toward COVID-19 contact tracing app use).ResultsThe analysis did not support the proposed three-factor structure of the AIPC (i.e., anxiety, personal attitude, and requirements). Instead, a four-factor model was preferable that differentiated requirements regarding disclosure policies, and personal control. In addition, factors mirroring anxiety and personal attitude were extracted, but shared a significant overlap. However, these factors showed good reliability, convergent and discriminant validity.DiscussionThe findings underline the role of app information privacy concerns as a significant barrier to mHealth app use. In this context, anxiety and personal attitudes seemed particularly relevant, which has implications for health communication. Moreover, the observed differentiation of external (disclosure) and internal (control) requirements aligns with health behavior change models and thus is a promising area for future research.
| S-EPMC9355691 | biostudies-literature
Project description:BACKGROUND:The Public Private Interface-Electronic Patient Record (PPI-ePR) system was implemented as a new electronic platform to facilitate collaboration between the public and private sectors in Hong Kong. However, its barriers to participate and benefits have not been comprehensively assessed. OBJECTIVE:This study aimed to evaluate the awareness, acceptance, perceived benefits, and obstacles to participation among private doctors and the general public. METHODS:From December 2012 to January 2013, 2435 telephone interviews were performed by trained interviewers to survey randomly selected patients who were enrolled or not enrolled in the PPI-ePR system. In addition, self-administered surveys were sent by postal mail to 4229 registered doctors in Hong Kong. The questionnaires for both patients and doctors contained questions on subjects' awareness, acceptance, and perceptions of the PPI-ePR, perceived benefits and obstacles of participating in the program, reasons for not using the system after enrolling, and perceived areas for service improvement of the system. RESULTS:More than 53.1% (266/501) of enrolled patients believed that the PPI-ePR system would improve health care quality by reducing duplicate tests and treatments, while more than 76.8% (314/409) of enrolled doctors emphasized timely access to patients' medical records as the biggest benefit of their enrollment. Among nonenrolled patients, unawareness of the project was the most popular obstacle to enrolling in the PPI-ePR system (483/1200, 40.3%). Regarding nonenrolled doctors, the complicated registration process hindered them from participating in the program the most (95/198, 48.0%). Television, newspaper, and magazine advertisements and medical profession newsletters or journals were suggested as the most effective means to encourage participation in the program among surveyed patients (1297/1701, 76.2%) and doctors (428/610, 70.2%), respectively. Lack of clinical indication requiring data extraction from other hospitals was the main reason for low level of PPI-ePR use. CONCLUSIONS:This study comprehensively assessed the popularity, perceived benefits, and hindering factors of enrolling in the PPI-ePR system in Hong Kong. Low levels of awareness, few privacy concerns, and inactive use of the PPI-ePR system were among the key features for patients and physicians. Public promotions, simplified logistics, and a user-friendly online interface were suggested to improve the coverage and effectiveness of health information exchange between private and public health care sectors.
| S-EPMC7171565 | biostudies-literature
Project description:BackgroundDuring the COVID-19 pandemic, contact tracing apps have received a lot of public attention. The ongoing debate highlights the challenges of the adoption of data-driven innovation. We reflect on how to ensure an appropriate level of protection of individual data and how to maximize public health benefits that can be derived from the collected data.ObjectiveThe aim of the study was to analyze available COVID-19 contact tracing apps and verify to what extent public health interests and data privacy standards can be fulfilled simultaneously in the process of the adoption of digital health technologies.MethodsA systematic review of PubMed and MEDLINE databases, as well as grey literature, was performed to identify available contact tracing apps. Two checklists were developed to evaluate (1) the apps' compliance with data privacy standards and (2) their fulfillment of public health interests. Based on both checklists, a scorecard with a selected set of minimum requirements was created with the goal of estimating whether the balance between the objective of data privacy and public health interests can be achieved in order to ensure the broad adoption of digital technologies.ResultsOverall, 21 contact tracing apps were reviewed. In total, 11 criteria were defined to assess the usefulness of each digital technology for public health interests. The most frequently installed features related to contact alerting and governmental accountability. The least frequently installed feature was the availability of a system of medical or organizational support. Only 1 app out of 21 (5%) provided a threshold for the population coverage needed for the digital solution to be effective. In total, 12 criteria were used to assess the compliance of contact tracing apps with data privacy regulations. Explicit user consent, voluntary use, and anonymization techniques were among the most frequently fulfilled criteria. The least often implemented criteria were provisions of information about personal data breaches and data gathered from children. The balance between standards of data protection and public health benefits was achieved best by the COVIDSafe app and worst by the Alipay Health Code app.ConclusionsContact tracing apps with high levels of compliance with standards of data privacy tend to fulfill public health interests to a limited extent. Simultaneously, digital technologies with a lower level of data privacy protection allow for the collection of more data. Overall, this review shows that a consistent number of apps appear to comply with standards of data privacy, while their usefulness from a public health perspective can still be maximized.
| S-EPMC8195202 | biostudies-literature