Context: Computerized clinical decision support systems (CCDSSs) give practitioners patient-specific care advice and are considered an important increment to electronic clinical documentation and order entry systems. Despite decades of research on CCDSS, results from rigorous clinical evaluations remain mixed and systems vary greatly in design and implementation. Objective: To identify factors differentiating CCDSSs that improve the process of care or patient outcomes from those that do not. Data Sources: We searched major bibliographic databases and scanned reference lists for eligible articles up to January 2010. Study selection: 162 eligible comparisons from randomized controlled trials of CCDSS to non-CCDSS care. We deemed successful those systems that improved either 50% of reported process of care outcomes or 50% of patient outcomes. We extracted system characteristics hypothesized to impact patient care and tested them for association with system effectiveness in logistic models. Results: Our primary analysis showed that CCDSSs presented in electronic health records or order entry systems were less likely to be effective than their counterparts (OR, 0.37; 95% CI, 0.17 to 0.80). Systems more likely to succeed than their counterparts provided advice for patients in addition to practitioners (OR, 2.77; 95% CI, 1.07 to 7.17), required from practitioners a reason to override advice (OR, 11.23; 95% CI, 1.98 to 63.72), or were evaluated by their developers (OR, 4.35; 95% CI, 1.66 to 11.44). These findings remained consistent across different statistical methods, sensitivity analyses, and adjustment for other potentially important factors. Conclusions: We identified several factors that may partially explain why some systems succeed and others fail. Primary studies should investigate the impact and optimal implementation of advice provided to patients and practitioners and advice that requires reasons to be overridden. Researchers should also address the reasons for failure of advice presented within charting and order entry systems. / Master of Science (MSc)

Introduktion: I dagens digitala tidsålder vänder sig många individer till internet som sin första källa till hälsoinformation. Forskning har dock visat att majoriteten av digital hälsoinformation är av låg kvalitet och har bristfällig korrekthet. En stor del av denna information består sannolikt av både desinformation och missinformation. Syfte: Syftet med denna studie var att sammanställa resultaten från peer-review granskade studier som utvärderar korrektheten hos digital hälsoinformation, med särskilt fokus på studier som använder expertgranskade texter utvärderade mot etablerade riktlinjer. Metod: Den 7 april 2024 genomsöktes tre databaser – MEDLINE EBSCO, Scopus och PubMed. Totalt 21 artiklar inkluderades. Resultaten från dessa artiklar kategoriserades och analyserades induktivt utifrån Narro och Tudges neo-ekologiska teori. Resultat: Fyra huvudkategorier skapades gällande informationens korrekthet: god, måttlig, bristfällig och varierande. Av de inkluderade artiklarna bedömdes 3 (14%) ha god korrekthet, 4 (19%) artiklar måttlig korrekthet, 13 (62%) bristfällig korrekthet och 1 (5%) hade varierande. Därtill ansågs 76% av det inkluderade materialet från trovärdiga källor ha bristfällig korrekthet. Slutsats: Majoriteten av de inkluderade studierna och det trovärdiga materialet har bristfällig korrekthet. Dessutom, tenderar studier som uppvisar en högre grad av korrekthet, ha sämre läsbarhet och den övergripande kvaliteten är ofta bristfällig, vilket även gör det svårt för konsumenter att förstå informationen. / Introduction: In today's digital age, many individuals turn to the internet as their initial source of health information. However, research has shown that the majority of online health information is of poor quality and low accuracy. A significant portion of this information likely includes both misinformation and disinformation. Aim: The aim of this study was to synthesize findings from peer-reviewed research assessing the accuracy of online health information, with a particular emphasis on studies that utilize expert-reviewed content evaluated against established guidelines. Method: On 7 April 2024, three databases—MEDLINE EBSCO, Scopus, and PubMed—were searched. A total of 21 articles were included in the systematic review. The results from these articles were categorized and inductively examined through the lens of Narro and Tudge’s neo-ecological theory. Results: Four primary categories were created concerning the accuracy of the information: good, moderate, poor, and varied. Among the included articles, 3 (14%) were deemed to have good accuracy, 4 (19%) articles exhibited moderate accuracy, 13 (62%) demonstrated poor accuracy, and 1 (5%) had varied accuracy. Additionally, 76% of the included material from trustworthy sources were categorized as having poor accuracy. Conclusion: The majority of the included studies and trustworthy material were found to have poor accuracy. Furthermore, even when studies exhibited a higher degree of accuracy, the readability and overall quality were often deficient, making it difficult for consumers to understand.

It is crucial to understand how patient portals are used and adopted among different population groups. This dissertation follows a traditional 5-chapter format that includes three studies with the results of each study presented in an essay format. The first essay provides a systematic literature review of existing research on patient portal adoption, barriers, and predictors. This review reveals a gap in knowledge regarding emerging adults who are transitioning from adult care to self-care settings. The second essay presents an emerging adult patient portal behavioral model, which identifies the factors that impact patient portal usage. Finally, the third essay focuses on patient's trust in providers in secure messaging, which is one of the features available through patient portals. The results of Essay 1 revealed gaps in the literature, highlighting the need for understanding the perceptions of different subgroups of the population towards patient portals to promote their meaningful use. The findings from Essay 2 show that perceived risk and perceived usefulness are significant determinants affecting the behavioral intentions of emerging adults toward the usage of patient portals. Essay 3 describes how information reliability, structural assurance, persuasiveness, perceived ease-of-use, and patients' trusting beliefs in providers are related to the patient's intentions to use secure messaging and patient portals. In addition to addressing existing research gaps, the results of the research in this dissertation inform healthcare providers and developers on how to improve patient portal adoption. By identifying the factors that impact patient portal usage, healthcare providers can optimize the benefits of patient portals for patients and healthcare organizations. Additionally, understanding patients' trust in providers in secure messaging can help improve communication and further lead to better health outcomes.

(1) Background: “Patient health information” promote health literacy. “Patient guidelines” as a sub group reflect the current evidence about illnesses and treatment options adapted to the needs of laypersons. Little is known about factors promoting and hindering their use by people affected by mental illness and their relatives. (2) Methods: Telephone interviews (N = 15; n = 4 adults affected by mental illness, n = 5 relatives, n = 6 both applicable) were conducted according to the Sørensen model of health literacy. Data were recorded, transcribed and content-analyzed following Mayring. (3) Results: Health information is used regularly by individuals affected by mental illness and their relatives, but “patient guidelines” are largely unknown. Yet, there is a great willingness to use them. Main barriers are a lack of statistical knowledge, the complexity of health-related topics and cognitive impairment sometimes accompanying mental illnesses. Target group-oriented adaptation as well as transparent and even-handed presentation of (dis-)advantages of treatment options can increase trust. (4) Conclusions: Health information and guidelines can help affected persons and relatives to make treatment decisions by conveying unbiased, up-to-date knowledge. Target group-specific adaptations should be made for psychiatric illnesses and features specific to mental illnesses compared to physical illnesses should be included. Clinical practice guidelines must be distributed more widely to increase their impact.

Yes / This study explored healthcare quality issues affecting the reporting and investigation levels of digital incident reporting systems. Methods: A total of 38 health information technology-related incident reports (free-text narratives) were collected from one of Sweden’s national incident reporting repositories. The incidents were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the types of issues and consequences. The framework was applied in two fields, ‘event description’ by the reporters and ‘manufacturer’s measures’, to assess the quality of reporting incidents by the reporters. Additionally, the contributing factors, i.e., either human or technical factors for both fields, were identified to evaluate the quality of the reported incidents. Results: Five types of issues were identified and changes made between before-and-after investigations: Machine to software- related issues (n = 8), machine to use-related issues (n = 5), software to software-related issues (n = 5), use to software- related issues (n = 4) and use to use-related issues (n = 1). Over two-thirds (n = 15) of the incidents demonstrated a change in the contributing factors after the investigation. Only four incidents were identified as altering the consequences after the investigation. Conclusion: This study shed some light on the issues of incident reporting and the gap between the reporting and investigation levels. Facilitating sufficient staff training sessions, agreeing on common terms for health information technology systems, refining the existing classifications systems, enforcing mini-root cause analysis, and ensuring unit-based local reporting and standard national reporting may help bridge the gap between reporting and investigation levels in digital incident reporting.

Background An increasing number of patients are seeking health information on the internet. Health literacy and the quality of information are crucial to enable patients to find relevant high-quality information. Objectives To investigate the relevance of quality criteria for health information and to determine the health literacy of skin cancer patients (SC) in comparison to those without skin cancer (NSC). Methods Between December 2021 until February 2022 we undertook an online survey on the importance of multiple criteria to investigate the relevance of quality criteria of online health information. SC and NSC were eligible for participation. The questionnaire assessed participants´ health information-seeking behavior and the evaluation of relevance of quality criteria for health information on a 5-point-LIKERT-Scale. The participants´ health literacy was measured according to the health literacy measurement scale ranging from 0-100. Comparisons between SC and NSC were investigated with t-tests. Results We retrieved data from 268 participants, of whom 98 (38%) were SC. Participants assigned the highest relevance to the health information topics treatment (4.7 ± 0.64) and effects of a disease (4.49 ± 0.76). Participants ranked the content of information with a mean of 4.72 (±0.57) to be the most relevant criterion, followed by objectivity (4.61 ± 0.67) and completeness of the information (4.59 ± 0.61). Participants showed the highest competence in understanding of information (62.4 ± 22.5) and in disease prevention (58.32 ± 22.9). They reached low values in accessing health related information (46.78 ± 25.62) and appraising it (33.16 ± 20.11). Subgroup analysis indicated that SC had a greater need for practical information that is helpful in dealing with a disease compared to NSC. They showed significantly lower health literacy than NSC. Conclusions Our study documents that SC and NSC have a high need for different dimensions of quality of health information. These differences in the importance of criteria should be considered in the development of future targeted health information.

Little is known regarding registered nurse (RN) information management practice in long-term care (LTC) settings. This study identifies LTC RNs’ information management practice and needs, which are important for designing and implementing health information technology (HIT) in LTC settings. Methods: This descriptive qualitative study combines direct observations and semi-structured interviews, conducted at Alberta’s LTC facilities between May 2014 and August 2015. The constant comparative method of joint coding was used for data analysis. Results: Nine RNs from six nursing homes participated in the study. Based on the RNs’ existing information management system requirements, a graphic information flow model was constructed. Conclusion: This baseline study identified key components of LTC RNs’ information management system. The information flow model may assist HIT developers with future design and development of HIT solutions for LTCs, serve as a communication tool between RNs and developers to refine requirements and support further LTC HIT research. / Graduate

This research presents a framework for enhancing and analyzing time-sequenced mammographic images for detection of cancerous tissue, specifically designed to assist radiologists and physicians with the detection of breast cancer. By using computer aided diagnosis (CAD) systems as a tool to help in the detection of breast cancer in computed tomography (CT) mammography images, previous CT mammography images will enhance the interpretation of the next series of images. The first stage of this dissertation applies image subtraction to images from the same patient over time. Image types are defined as temporal subtraction, dual-energy subtraction, and Digital Database for Screening Mammography (DDSM). Image enhancement begins by applying image registration and subtraction using Matlab 2012a registration for temporal images and dual-energy subtraction for dual-energy images. DDSM images require no registration or subtraction as they are used for baseline analysis. The image data are from three different sources and all images had been annotated by radiologists for each image type using an image mask to identify malignant and benign. The second stage involved the examination of four different thresholding techniques. The amplitude thresholding method manipulates objects and backgrounds in such a way that object and background pixels have grey levels grouped into two dominant and different modes. In these cases, it was possible to extract the objects from the background using a threshold that separates the modes. The local thresholding introduced posed no restrictions on region shape or size, because it maximized edge features by thresholding local regions separately. The overall histogram analysis showed minima and maxima of the image and provided four feature types--mean, variance, skewness, and kurtosis. K-means clustering provided sequential splitting, initially performing dynamic splits. These dynamic splits were then further split into smaller, more variant regions until the regions of interest were isolated. Regional-growing methods used recursive splitting to partition the image top-down by using the average brightness of a region. Each thresholding method was applied to each of the three image types. In the final stage, the training set and test set were derived by applying the four thresholding methods on each of the three image types. This was accomplished by running Matlab 2012a grey-level, co-occurrence matrix (GLCM) and utilizing 21 target feature types, which were obtained from the Matlab function texture features. An additional four feature types were obtained from the state of the histogram-based features types. These 25 feature types were applied to each of the two classifications malignant and benign. WEKA 3.6.10 was used along with classifier J48 and cross-validation 10 fold to find the precision, recall, and f-measure values. Best results were obtained from these two combinations: temporal subtraction with amplitude thresholding, and temporal subtraction with regional-growing thresholding. To summarize, the researcher's contribution was to assess the effectiveness of various thresholding methods in the context of a three-stage approach, to help radiologists find cancerous tissue lesions in CT and MRI mammography images.

When face-to-face physical medical exams are not possible, virtual physical exams, in the form of a pictorial medical exam/history, can be substituted, and telemedicine can be the means to deliver these virtual exams. The goal of this work was to determine if presence in the form of a visual and/or pictorial medical history can be of benefit to clinicians in the diagnosis of medical conditions of individuals with developmental disabilities (DDs) and/or intellectual disabilities (IDs), in particular those who cannot, because of their cognitive and/or physical disabilities, verbally relate their illness to a clinician. Virtual exams can also be useful in cases where clinicians may need additional advice from fellow experts, especially if those experts are not physically present. A web-based telemedicine application used for treating persons with DD/IDs was developed. This application includes a visual medical history component incorporated into an electronic medical records application. The purpose is to allow the clinician to use an environment that integrates a written and visual representation of a patient’s medical history and physical findings to aid the clinician in determining a medical diagnosis. Twenty-two clinicians and five direct service aids of a New York State Developmental Disabilities Services Office facility, who deliver healthcare to DD/ID patients on a daily basis, accessed the telemedicine application instead of their traditional hardcopy/paper medical history when examining patients. A comprehensive survey was distributed to the clinicians to determine the effectiveness of the application as well as help answer the primary questions proposed by this research. The results of this study showed that presence in the form of a video medical history is preferred by clinicians rather than having just a written medical history of the patient. Clinicians felt the visual medical history component of the telemedicine application was useful and informative for delivering healthcare to individuals with DD/ID and enabled them in diagnosing a patient as well as lessened the need to transfer patients to the emergency room, resulting in a significant cost savings.

Diabetes is the seventh leading cause of death in the United States. With the population rapidly aging, it is expected that 1 out of 3 Americans will have diabetes by 2050. Mobile devices and mobile applications have the potential to contribute to diabetes self-care by allowing users to manage their diabetes by keeping track of their blood glucose levels. Usability is important for systems that help people self-manage conditions such as diabetes. Age and diabetes-related cognitive decline might intensify the impact of usability issues for the users who need these mobile applications the most. As highlighted by usability researchers, the context of use (i.e. environment, user, task, and technology) has a significant impact on usability. The environment (lighting, temperature, audio and visual distractions, etc.) is of special interest to the mobile usability arena since in the case of mobile devices, is always changing. This dissertation aims to support the claim that context and more specifically environmental distraction such as semantic auditory distractions impact the usability of mobile applications. In doing so, it attempts to answer the following research questions: 1) Does semantic auditory distractions reduce the effectiveness of a blood glucose tracking mobile application? 2) Does semantic auditory distractions reduce the efficiency of a blood glucose tracking mobile application? 3) Does semantic auditory distractions reduce the user satisfaction of a blood glucose tracking mobile application? To answer the study research questions, a true experimental design was performed involving 30 adults with type 2 diabetes. Participants were paired based on their age and experience with smartphones and randomly assigned to the control (no semantic auditory distractions) or experimental (semantic auditory distractions) group. Research questions were tested using the general linear model. The results of this study confirmed that semantic auditory distractions have a significant effect on efficiency and effectiveness, and hence they need to be taken into account when evaluating mobile usability. This study also showed that semantic auditory distractions have no significant effect on user satisfaction. This dissertation enhances the current knowledge about the impact of semantic auditory distractions on the usability of mobile applications within the diabetic senior population.