Magister Commercii - MCom / This study aimed to understand the readiness and perceptions of Electronic Health Record (EHR) adoption among dentists in the public service of the Western Cape. A qualitative study design was chosen due to a lack of understanding of the phenomena. Additionally, the research sought to identify the factors that would potentially influence readiness and perceptions in order to identify how these factors could potentially influence EHR adoption among dentists.

Yes / Purpose: The purpose of this paper is to investigate the potential of using primary care optometry data to support ophthalmic public health, research and policy making. Methods: Suppliers of optometric electronic patient record systems (EPRs) were interviewed to gather information about the data present in commercial software programmes and the feasibility of data extraction. Researchers were presented with a list of metrics that might be included in an optometric practice dataset via a survey circulated by email to 102 researchers known to have an interest in eye health. Respondents rated the importance of each metric for research. A further survey presented the list of metrics to 2000 randomly selected members of the College of Optometrists. The optometrists were asked to specify how likely they were to enter information about each metric in a routine sight test consultation. They were also asked if data were entered as free text, menus or a combination of these. Results: Current EPRs allowed the input of data relating to the metrics of interest. Most data entry was free text. There was a good match between high priority metrics for research and those commonly recorded in optometric practice. Conclusions: Although there were plenty of electronic data in optometric practice, this was highly variable and often not in an easily analysed format. To facilitate analysis of the evidence for public health purposes a UK based minimum dataset containing standardised clinical information is recommended. Further research would be required to develop suitable coding for the individual metrics included. The dataset would need to capture information from all sectors of the population to ensure effective planning of any future interventions.

Indiana University-Purdue University Indianapolis (IUPUI) / Periodontal disease (PD) affects 42% of US population resulting in compromised quality of life, the potential for tooth loss and influence on overall health. Despite significant understanding of PD etiology, limited longitudinal studies have investigated PD change in response to various treatments. A major barrier is the difficulty of conducting randomized controlled trials with adequate numbers of patients over a longer time. Electronic dental record (EDR) data offer the opportunity to study outcomes following various periodontal treatments. However, using EDR data for research has challenges including quality and missing data. In this dissertation, I studied a cohort of patients with PD from EDR to monitor their disease status over time. I studied retrospectively 28,908 patients who received comprehensive oral evaluation at the Indiana University School of Dentistry between January 1st-2009 and December 31st-2014. Using natural language processing and automated approaches, we 1) determined PD diagnoses from periodontal charting based on case definitions for surveillance studies, 2) extracted clinician-recorded diagnoses from clinical notes, 3) determined the number of patients with disease improvement or progression over time from EDR data. We found 100% completeness for age, sex; 72% for race; 80% for periodontal charting findings; and 47% for clinician-recorded diagnoses. The number of visits ranged from 1-14 with an average of two visits. From diagnoses obtained from findings, 37% of patients had gingivitis, 55% had moderate periodontitis, and 28% had severe periodontitis. In clinician-recorded diagnoses, 50% patients had gingivitis, 18% had mild, 14% had moderate, and 4% had severe periodontitis. The concordance between periodontal charting-generated and clinician-recorded diagnoses was 47%. The results indicate that case definitions for PD are underestimating gingivitis and overestimating the prevalence of periodontitis. Expert review of findings identified clinicians relying on visual assessment and radiographic findings in addition to the case definition criteria to document PD diagnosis. / 2021-08-10

Melanoma is one of the fastest growing cancers in the world, and can affect patients earlier in life than most other cancers. Therefore, it is imperative to be able to identify patients at high risk for melanoma and enroll them in screening programs to detect the cancer early. Electronic health records collect an enormous amount of data about real-world patient encounters, treatments, and outcomes. This data can be mined to increase our understanding of melanoma as well as build personalized models to predict risk of developing the cancer. Cancer risk models built from structured clinical data are limited in current research, with most studies involving just a few variables from institutional databases or registries. This dissertation presents data processing and machine learning approaches to build melanoma risk models from a large database of de-identified electronic health records. The database contains consistently captured structured data, enabling the extraction of hundreds of thousands of data points each from millions of patient records. Several experiments are performed to build effective models, particularly to predict sentinel lymph node metastasis in known melanoma patients and to predict individual risk of developing melanoma. Data for these models suffer from high dimensionality and class imbalance. Thus, classifiers such as logistic regression, support vector machines, random forest, and XGBoost are combined with advanced modeling techniques such as feature selection and data sampling. Risk factors are evaluated using regression model weights and decision trees, while personalized predictions are provided through random forest decomposition and Shapley additive explanations. Random undersampling on the melanoma risk dataset shows that many majority samples can be removed without a decrease in model performance. To determine how much data is truly needed, we explore learning curve approximation methods on the melanoma data and three publicly-available large-scale biomedical datasets. We apply an inverse power law model as well as introduce a novel semi-supervised curve creation method that utilizes a small amount of labeled data. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Electronic Health Record (EHR) systems could make healthcare delivery safer by providing benefits such as timely access to accurate and complete patient information, advances in diagnosis and coordination of care, and enhancements for monitoring patient vitals. This study explored the nature of EHR adoption in U.S. hospitals and their patient safety performance in relation to one hospital acquired condition: postoperative sepsis – a condition that complicates hospitalizations, increases lengths of stay, and leads to higher mortality rates. Administrative data from several sources were utilized in order to obtain comprehensive information about the patient, organizational, and market characteristics of hospitals, their EHR adoption patterns, and the occurrence of postoperative sepsis among their patients. The study sample consisted of 404 general, short-term, acute care, non-federal, and urban hospitals based in six states, which provided longitudinal data from 2005 to 2009. Hospital EHR and the EHR’s sophistication level were measured by the presence of eight clinical applications. Econometric techniques were used to test six hypotheses that were derived from macro-organizational theories and frameworks. After controlling for potential confounders, the study’s key findings suggested that hospitals had a significant increase in the probability of having EHR as the percent of other hospitals having the most sophisticated EHR (i.e., EHRS3) in the market increased. Conversely, hospitals had a significant decrease in the probability of having EHR when the percent of Medicaid patients increased within a hospital or when the hospital belonged to centralized or moderately centralized systems. Also, the study findings suggested that EHR was associated with a higher rate of postoperative sepsis. Specifically, the intermediate EHR sophistication level (i.e., EHRS2) and the most sophisticated EHR level (i.e., EHRS3) were associated with a significantly higher rate of postoperative sepsis when compared to hospitals that did not have such EHR sophistication. The study results, however, did not support the hypotheses that higher degrees of fit between hospitals’ EHR sophistication level and specific structural dimensions were associated with greater reductions in postoperative sepsis outcomes vis-à-vis hospitals that did not have these types of fit.

By the end of 2015, Medicare-eligible physicians at primary care practices (PCP) who do not use an electronic health record (EHR) system will incur stiff penalties if they fail to meet the deadline for using EHRs. Yet, less than 30% of rural primary clinics have fully functional EHR systems. The purpose of this phenomenology study was to explore rural primary care physicians and physician assistants' experiences regarding overcoming barriers to implementing EHRs. Complex adaptive systems formed the conceptual framework for this study. Data were collected through face-to-face interviews with a purposeful sample of 21 physicians and physician assistants across 2 rural PCPs in the southeastern region of Missouri. Participant perceptions were elicited regarding overcoming barriers to implementing EHRs under the American Recovery and Reinvestment Act, Health Information Technology for Economic and Clinical Health, and the Patient Protection and Affordable Care Act legislation. Interview questions were transcribed and processed through qualitative software to discern themes of how rural PCP physicians and physician assistants might overcome barriers to implementing electronic health records. Through the exploration of the narrative segments, 4 emergent themes were common among the participants: (a) limited finances to support EHRs, (b) health information exchange issues, (c) lack of business education, and (d) lack of transformation at rural medical practices. The implications for positive social change include the potential implementation of EHRs particularly in physician practices in rural communities, which could provide cost-efficient health care services for those communities and a more sustainable future at primary care practices.

Urinary incontinence affects up to 70% of residents living in a long-term care facility and can affect their quality of life. Specifically, urinary incontinence has a direct impact on older adults in regards to self-esteem, pressure ulcer development, falls, urinary tract infections, and psychosocial wellbeing. The goal of this quality improvement pilot project was to determine if an electronic health record (EHR) assessment tool could help older adults remain continent longer and assist in maintaining an independent lifestyle. Orem's self-care deficit theory and social cognitive theory were used to determine how the electronic health record incontinence template could be used to monitor residents for incontinence and affect the incidence of incontinence. Out of 25 residents, 13 met the requirements for inclusion in the pilot study. Quantitative data were collected and documented in the EHR for 4 weeks and compared to the immediate 4 week period post-implementation of the EHR template. Descriptive analyses of pre- and post-implementation EHR assessments showed there were no EHR assessments completed pre-implementation and 2 residents out of 13 had EHR assessments completed post-implementation. The available data suggested that the EHR template, if edited, could be effective for tracking incontinence. The template needed to address bladder incontinence only rather than bowel and bladder. Feedback from nursing staff indicated that a future study should be conducted over a longer period than 4 weeks to see if results would remain consistent. Nurses working in the long term care environment would benefit from reading this project. This study contributes to social change as evidenced by the residents who remained continent longer by having individual toileting plans partially developed by the template; therefore, they remained a viable part of the community.

There is a marked trend of using information technologies to improve healthcare. Among all the health IT, electronic health record (EHR) systems hold great promises as they modernize the paradigm and practice of care provision. However, empirical studies in the literature found mixed evidence on whether EHRs improve quality of care. I posit two explanations for the mixed evidence. First, most prior studies failed to account for system use and only focused on EHR purchase or adoption. Second, most existing EHR systems provide inadequate clinical decision support and hence, fail to reveal the full potential of digital health. In this dissertation I address two broad research questions: a) Does meaningful use of EHRs improve quality of care? and b) How do we advance clinical decision making through innovative computational techniques of healthcare analytics? To these ends, the dissertation comprises four essays. The first essay examines whether meaningful use of EHRs improve quality of care through a natural experiment. I found that meaningful use significantly improve quality of care, and this effect is greater in historically disadvantaged hospitals such as small, non-teaching, or rural hospitals. These empirical findings present salient practical and policy implications about the role of health IT. On the other hand, in the other three essays I work with real-world EHR data sets and propose healthcare analytics frameworks and methods to better utilize clinical text (Essay II), integrate clinical guidelines and EHR data for risk prediction (Essay III), and develop a principled approach for multifaceted risk profiling (Essay IV). Models, frameworks, and design principles proposed in these essays advance not only health IT research, but also more broadly contribute to business analytics, design science, and predictive modeling research.

Η παρούσα διπλωματική εργασία πραγματοποιήθηκε υπό την επίβλεψη του καθηγητή Νικολάου Παλληκαράκη, Διευθυντή του Μεταπτυχιακού προγράμματος στη Βιοιατρική Τεχνολογία του πανεπιστημίου Πατρών και ΕΜΠ. Ασχολείται με την ανάπτυξη πρότυπων μοντέλων αναφοράς, αναπαράστασης γνωστικής πληροφορίας και επίσης αναφέρονται διάφοροι σχεδιαστικοί περιορισμοί και προδιαγραφές για τον χώρο της υγείας και συγκεκριμένα για τον ηλεκτρονικό ιατρικό φάκελο. Τι εννοούμε με την έννοια ηλεκτρονικός ιατρικός φάκελος; Πρόκειται για μια δομημένη συλλογή ηλεκτρονικών δεδομένων που αφορούν μια περιοχή της υγείας και παρέχεται με σκοπό τη συνεχή, αποτελεσματική και ποιοτική παροχή φροντίδας. Η υπάρχουσα κατάσταση στο τομέα της ιατρικής πληροφορικής, εξαιτίας του μεγάλου πλήθους των προτύπων που αναπτύσσονται από διάφορους οργανισμούς, σε εθνικό αλλά και παγκόσμιο επίπεδο, καθιστά αδύνατη την εφαρμογή ενός κοινά αποδεκτού προτύπου. Στα πλαίσια της εργασίας αυτής παρουσιάζονται αρχικά τα βασικά μέρη του ηλεκτρονικού ιατρικού φακέλου όπως κυκλοφορούν τα διάφορα μοντέλα στο εμπόριο, έπειτα γίνεται μια σύντομη ιστορική αναδρομή και κατόπιν παρουσιάζονται λεπτομερώς τα διάφορα μοντέλα για τρεις μεγάλους, παγκόσμιους οργανισμούς και συγκεκριμένα για τους: CEN, ISO και HL7. Συγκεντρωτικά τα αποτελέσματα για το κάθε μοντέλο περιγράφονται στα κεφάλαια 4, 5 και 6. Η συλλογή των δεδομένων έγινε μετά από την εξέταση διαφόρων εργασιών και την πλοήγηση σε διαφορετικές ιστιοσελίδες στο διαδίκτυο, τα αποτελέσματα τα οποία αναφέρονται στην τελική τους μορφή στο τμήμα της αναφοράς. Στο τέλος της διπλωματικής εργασίας γίνεται λόγος για τη διαλειτουργικότητα και την εναρμόνιση των προτύπων δυο έννοιες που πρόκειται να αποτελέσουν οδηγό για την εφαρμογή ενός κοινά αποδεκτού προτύπου σε κάποια χρονική στιγμή στο σύντομο μέλλον. / Reference information model for the organizations cen/tc251, iso/tc215, hl7, what why mean with the object electronic health record

The overall aim of this thesis was to investigate predefined headings in a Swedish county council multi-professional EHR system in terms of their shared application, what aspects of health and health care they reflected, and their correspondence to legal requirements. An analysis of 3 596 predefined headings, applied to 20 398 104 occasions by eight professional groups, was conducted. Less than 2% of the predefined headings were applied by all eight professional groups, whereas 60% were not shared at all between the professional groups. A classification of the predefined headings revealed that 13% were “Specialist terms”, which were the least ambiguous predefined headings, 46% were “Terms for specific purposes”, which are less ambiguous than the “Common words” (28%), which were the most ambiguous predefined headings according to the sociolinguistic method employed. The remaining predefined headings (13%) were sorted into “Unclassified headings”. A qualitative content analysis of the predefined headings yielded 23 subcategories grouped into five categories: Description of the patient, Health care process, Resources employed, Administrative documentation, and Development and research. A comparison of the 23 subcategories to the Patient Data Act showed, first, that 15 of 23 subcategories corresponded to four legal requirements, second, that there were legal requirements with a focus on patient rights that were not being met, and third, that there were eight subcategories of predefined headings that could not be attributed to the legal provisions of the Patient Data Act. In conclusion, the proportion of shared predefined headings in the EHRs was limited. The predefined headings in the multi-professional EHRs did not constitute a joint language for specific purposes. A meaningful structure comprising categories and subcategories of different aspects of health and health care as reflected in the applied predefined headings was identified. The structure reflected a wide range of health and health care. No subcategory corresponded to the three legal requirements concerning patient rights. Future research should include professionals’ and patients’ understanding of predefined headings, the correspondence of documented notes to predefined headings and how the documentation in the EHR has had an impact on patient safety.