Standardization of data collection for the Lifetime Surveillance of Astronaut Health (LSAH)

Problems due to the lack of data standardization and data management have lead to work inefficiencies for the staff working with the vision data for the Lifetime Surveillance of Astronaut Health. Data has been collected over 50 years in a variety of manners and then entered into a software. The lack of communication between the electronic health record (EHR) form designer, epidemiologists, and optometrists has led to some level to confusion on the capability of the EHR system and how its forms can be designed to fit all the needs of the relevant parties. EHR form customizations or form redesigns were found to be critical for using NASA's EHR system in the most beneficial way for its patients, optometrists, and epidemiologists. In order to implement a protocol, data being collected was examined to find the differences in data collection methods. Changes were implemented through the establishment of a process improvement team (PIT). Based on the findings of the PIT, suggestions have been made to improve the current EHR system. If the suggestions are implemented correctly, this will not only improve efficiency of the staff at NASA and its contractors, but set guidelines for changes in other forms such as the vision exam forms. Because NASA is at the forefront of such research and health surveillance the impact of this management change could have a drastic improvement on the collection of and adaptability of the EHR. Accurate data collection from this 50+ year study is ongoing and is going to help current and future generations understand the implications of space flight on human health. It is imperative that the vast amount of information is documented correctly.^

Patient-centered medical home technology effects on hypertension and diabetes control

Background: Hypertension and Diabetes is a public health and economic concern in the United States. The utilization of medical home concepts increases the receipt of preventive services, however, do they also increase adherence to treatments? This study examined the effect of patient-centered medical home technologies such as the electronic health record, clinical support system, and web-based care management in improving health outcomes related to hypertension and diabetes. Methods: A systematic review of the literature used a best evidence synthesis approach to address the general question " Do patient-centered medical home technologies have an effect of diabetes and hypertension treatment?" This was followed by an evaluation of specific examples of the technologies utilized such as computer-assisted recommendations and web-based care management provided by the patient's electronic health record. Ebsco host, Ovid host, and Google Scholar were the databases used to conduct the literature search. Results: The initial search identified over 25 studies based on content and quality that implemented technology interventions to improve communication between provider and patient. After further assessing the articles for risk of bias and study design, 13 randomized controlled studies were chosen. All of the studies chosen were conducted in various primary care settings in both private practices and hospitals between the years 2000 and 2007. The sample sizes of the studies ranged from 42 to 2924 participants. The mean age for all of the studies ranged from 56 to 71 years. The percent women in the studies ranged from one to 78 percent. Over one-third of the studies did not provide the racial composition of the participants. For the seven studies that did provide information about the ethnic composition, 64% of the intervention participants were White. All of the studies utilized some type of web-based or computer-based communication to manage hypertension or diabetes care. Findings on outcomes were mixed, with nine out of 13 studies showing no significant effect on outcomes examined, and four of the studies showing significant and positive impact on health outcomes related to hypertension or diabetes Conclusion: Although the technologies improved patient and provider satisfaction, the outcomes measures such as blood pressure control and glucose control were inconclusive. Further research is needed with diverse ethnic and SES population to investigate the role of patient-centered technologies on hypertension and diabetes control. Also, further research is needed to investigate the effects of innovative medical home technologies that can be used by both patients and providers to increase quality of communication concerning adherence to treatments.^

Evaluating the Utility of Clinical Criteria for the Identification of Lynch Syndrome among Endometrial Cancer Patients

Background: Lynch Syndrome (LS) is a familial cancer syndrome with a high prevalence of colorectal and endometrial carcinomas among affected family members. Clinical criteria, developed from information obtained from familial colorectal cancer registries, have been generated to identify individuals at elevated risk for having LS. In 2007, the Society of Gynecologic Oncology (SGO) codified criteria to assist in identifying women presenting with gynecologic cancers at elevated risk for having LS. These criteria have not been validated in a population-based setting. Materials and Methods: We retrospectively identified 412, unselected endometrial cancer cases. Clinical and pathologic information were obtained from the electronic medical record, and all tumors were tested for expression of the DNA mismatch repair proteins through immunohistochemistry. Tumors exhibiting loss of MSH2, MSH6 and PMS2 were designated as probable Lynch Syndrome (PLS). For tumors exhibiting immunohistochemical loss of MLH1, we used the PCR-based MLH1 methylation assay to delineate PLS tumors from sporadic tumors. Samples lacking methylation of the MLH1 promoter were also designated as PLS. The sensitivity and specificity for SGO criteria for detecting PLS tumors was calculated. We compared clinical and pathologic features of sporadic tumors and PLS tumors. A simplified cost-effectiveness analysis was also performed comparing the direct costs of utilizing SGO criteria vs. universal tumor testing. Results: In our cohort, 43/408 (10.5%) of endometrial carcinomas were designated as PLS. The sensitivity and specificity of SGO criteria to identify PLS cases were 32.7 and 77%, respectively. Multivariate analysis of clinical and pathologic parameters failed to identify statistically significant differences between sporadic and PLS tumors with the exception of tumors arising from the lower uterine segment. These tumors were more likely to occur in PLS tumors. Cost-effectiveness analysis showed clinical criteria and universal testing strategies cost $6,235.27/PLS case identified and $5,970.38/PLS case identified, respectively. Conclusions: SGO 5-10% criteria successfully identify PLS cases among women who are young or have significant family history of LS related tumors. However, a larger proportion of PLS cases occurring at older ages with less significant family history are not detected by this screening strategy. Compared to SGO clinical criteria, universal tumor testing is a cost effective strategy to identify women presenting with endometrial cancer who are at elevated risk for having LS.

Diseño e implementación de un algoritmo para la detección de la negación de textos clínicos en español

Vivimos en una época en la que cada vez existe una mayor cantidad de información. En el dominio de la salud la historia clínica digital ha permitido digitalizar toda la información de los pacientes. Estas historias clínicas digitales contienen una gran cantidad de información valiosa escrita en forma narrativa que sólo podremos extraer recurriendo a técnicas de procesado de lenguaje natural. No obstante, si se quiere realizar búsquedas sobre estos textos es importante analizar que la información relativa a síntomas, enfermedades, tratamientos etc. se puede refererir al propio paciente o a sus antecentes familiares, y que ciertos términos pueden aparecer negados o ser hipotéticos. A pesar de que el español ocupa la segunda posición en el listado de idiomas más hablados con más de 500 millones de hispano hablantes, hasta donde tenemos de detección de la negación, probabilidad e histórico en textos clínicos en español. Por tanto, este Trabajo Fin de Grado presenta una implementación basada en el algoritmo ConText para la detección de la negación, probabilidad e histórico en textos clínicos escritos en español. El algoritmo se ha validado con 454 oraciones que incluían un total de 1897 disparadores obteniendo unos resultado de 83.5 %, 96.1 %, 96.9 %, 99.7% y 93.4% de exactitud con condiciones afirmados, negados, probable, probable negado e histórico respectivamente. ---ABSTRACT---We live in an era in which there is a huge amount of information. In the domain of health, the electronic health record has allowed to digitize all the information of the patients. These electronic health records contain valuable information written in narrative form that can only be extracted using techniques of natural language processing. However, if you want to search on these texts is important to analyze if the relative information about symptoms, diseases, treatments, etc. are referred to the patient or family casework, and that certain terms may appear negated or be hypothesis. Although Spanish is the second spoken language with more than 500 million speakers, there seems to be no method of detection of negation, hypothesis or historical in medical texts written in Spanish. Thus, this bachelor’s final degree presents an implementation based on the ConText algorithm for the detection of negation, hypothesis and historical in medical texts written in Spanish. The algorithm has been validated with 454 sentences that included a total of 1897 triggers getting a result of 83.5 %, 96.1 %, 96.9 %, 99.7% and 93.4% accuracy with affirmed, negated, hypothesis, negated hypothesis and historical respectively.

Clinical Phenotyping in the Prediction of Pediatric Acute Kidney Injury

Thesis (Master's)--University of Washington, 2016-06

Behavioral Perspectives on Organizational Change: Practice Adoption, Product Culling, and Technological Search

This dissertation explores the complex process of organizational change, applying a behavioral lens to understand change in processes, products, and search behaviors. Chapter 1 examines new practice adoption, exploring factors that predict the extent to which routines are adopted “as designed” within the organization. Using medical record data obtained from the hospital’s Electronic Health Record (EHR) system I develop a novel measure of the “gap” between routine “as designed” and routine “as realized.” I link this to a survey administered to the hospital’s professional staff following the adoption of a new EHR system and find that beliefs about the expected impact of the change shape fidelity of the adopted practice to its design. This relationship is more pronounced in care units with experienced professionals and less pronounced when the care unit includes departmental leadership. This research offers new insights into the determinants of routine change in organizations, in particular suggesting the beliefs held by rank-and-file members of an organization are critical in new routine adoption. Chapter 2 explores changes to products, specifically examining culling behaviors in the mobile device industry. Using a panel of quarterly mobile device sales in Germany from 2004-2009, this chapter suggests that the organization’s response to performance feedback is conditional upon the degree to which decisions are centralized. While much of the research on product exit has pointed to economic drivers or prior experience, these central finding of this chapter—that performance below aspirations decreases the rate of phase-out—suggests that firms seek local solutions when doing poorly, which is consistent with behavioral explanations of organizational action. Chapter 3 uses a novel text analysis approach to examine how the allocation of attention within organizational subunits shapes adaptation in the form of search behaviors in Motorola from 1974-1997. It develops a theory that links organizational attention to search, and the results suggest a trade-off between both attentional specialization and coupling on search scope and depth. Specifically, specialized unit attention to a more narrow set of problems increases search scope but reduces search depth; increased attentional coupling also increases search scope at the cost of depth. This novel approach and these findings help clarify extant research on the behavioral outcomes of attention allocation, which have offered mixed results.

The Effect of Propofol Versus Isoflurane Anesthesia on Human Cerebrospinal Fluid Markers of Alzheimer's Disease: Results of a Randomized Trial.

BACKGROUND: Preclinical studies have found differential effects of isoflurane and propofol on the Alzheimer's disease (AD)-associated markers tau, phosphorylated tau (p-tau) and amyloid-β (Aβ). OBJECTIVE: We asked whether isoflurane and propofol have differential effects on the tau/Aβ ratio (the primary outcome), and individual AD biomarkers. We also examined whether genetic/intraoperative factors influenced perioperative changes in AD biomarkers. METHODS: Patients undergoing neurosurgical/otolaryngology procedures requiring lumbar cerebrospinal fluid (CSF) drain placement were prospectively randomized to receive isoflurane (n = 21) or propofol (n = 18) for anesthetic maintenance. We measured perioperative CSF sample AD markers, performed genotyping assays, and examined intraoperative data from the electronic anesthesia record. A repeated measures ANOVA was used to examine changes in AD markers by anesthetic type over time. RESULTS: The CSF tau/Aβ ratio did not differ between isoflurane- versus propofol-treated patients (p = 1.000). CSF tau/Aβ ratio and tau levels increased 10 and 24 h after drain placement (p = 2.002×10-6 and p = 1.985×10-6, respectively), mean CSF p-tau levels decreased (p = 0.005), and Aβ levels did not change (p = 0.152). There was no interaction between anesthetic treatment and time for any of these biomarkers. None of the examined genetic polymorphisms, including ApoE4, were associated with tau increase (n = 9 polymorphisms, p > 0.05 for all associations). CONCLUSION: Neurosurgery/otolaryngology procedures are associated with an increase in the CSF tau/Aβ ratio, and this increase was not influenced by anesthetic type. The increased CSF tau/Aβ ratio was largely driven by increases in tau levels. Future work should determine the functional/prognostic significance of these perioperative CSF tau elevations.

ART attrition across health facilities implementing Option B+ in Haiti

Thesis (Master's)--University of Washington, 2016-08

Data protection by design in the e-health care sector: theoretical and applied perspectives

In the digital age, e-health technologies play a pivotal role in the processing of medical information. As personal health data represents sensitive information concerning a data subject, enhancing data protection and security of systems and practices has become a primary concern. In recent years, there has been an increasing interest in the concept of Privacy by Design, which aims at developing a product or a service in a way that it supports privacy principles and rules. In the EU, Article 25 of the General Data Protection Regulation provides a binding obligation of implementing Data Protection by Design technical and organisational measures. This thesis explores how an e-health system could be developed and how data processing activities could be carried out to apply data protection principles and requirements from the design stage. The research attempts to bridge the gap between the legal and technical disciplines on DPbD by providing a set of guidelines for the implementation of the principle. The work is based on literature review, legal and comparative analysis, and investigation of the existing technical solutions and engineering methodologies. The work can be differentiated by theoretical and applied perspectives. First, it critically conducts a legal analysis on the principle of PbD and it studies the DPbD legal obligation and the related provisions. Later, the research contextualises the rule in the health care field by investigating the applicable legal framework for personal health data processing. Moreover, the research focuses on the US legal system by conducting a comparative analysis. Adopting an applied perspective, the research investigates the existing technical methodologies and tools to design data protection and it proposes a set of comprehensive DPbD organisational and technical guidelines for a crucial case study, that is an Electronic Health Record system.

Fascicolo Sanitario Elettronico: Presente e Futuro

La tesi propone un'analisi del Fascicolo Sanitario Elettronico. Il Fascicolo Sanitario Elettronico è uno strumento che, con la telemedicina e le tecnologie ITC, conforma la Sanità Digitale. La sua funzione principale è l'archiviazione di dati e documenti sanitari, ma l'essere una sorta di digitalizzazione delle cartelle cliniche è solo uno dei compiti dell'FSE, la sua utilità comprende una serie di servizi che mirano a facilitare il tracciamento e monitoraggio degli eventi medici che sperimentano i cittadini. Grazie all'FSE è possibile che medici ed operatori sanitari presso diversi ospedali e cliniche possano apprendere l'intera storia clinica del paziente con un click. Nel 2020, con la diffusione del coronavirus, sono stati evidenziati diversi dei problemi che già erano stati riscontrati nel funzionamento dell'FSE, dunque questo documento si pone l'obiettivo di presentare questa tecnologia, il suo funzionamento attuale, le problematiche, e gli obiettivi che mirano al suo miglioramento. Da qualche anno, diversi paesi in giro per il mondo, si sono interessati nello sviluppo di questa tecnologia, con lo scopo di modernizzare e migliorare la salute pubblica, ma, in seguito alla diffusione della pandemia, il fascicolo si è ritrovato al centro dell'attenzione dell'universo sanitario, perciò la decisione di trattare questo tema attualissimo.

Consensus summary statement of the International Multidisciplinary Consensus Conference on Multimodality Monitoring in Neurocritical Care : A statement for healthcare professionals from the Neurocritical Care Society and the European Society of Intensive Care Medicine.

Neurocritical care depends, in part, on careful patient monitoring but as yet there are little data on what processes are the most important to monitor, how these should be monitored, and whether monitoring these processes is cost-effective and impacts outcome. At the same time, bioinformatics is a rapidly emerging field in critical care but as yet there is little agreement or standardization on what information is important and how it should be displayed and analyzed. The Neurocritical Care Society in collaboration with the European Society of Intensive Care Medicine, the Society for Critical Care Medicine, and the Latin America Brain Injury Consortium organized an international, multidisciplinary consensus conference to begin to address these needs. International experts from neurosurgery, neurocritical care, neurology, critical care, neuroanesthesiology, nursing, pharmacy, and informatics were recruited on the basis of their research, publication record, and expertise. They undertook a systematic literature review to develop recommendations about specific topics on physiologic processes important to the care of patients with disorders that require neurocritical care. This review does not make recommendations about treatment, imaging, and intraoperative monitoring. A multidisciplinary jury, selected for their expertise in clinical investigation and development of practice guidelines, guided this process. The GRADE system was used to develop recommendations based on literature review, discussion, integrating the literature with the participants' collective experience, and critical review by an impartial jury. Emphasis was placed on the principle that recommendations should be based on both data quality and on trade-offs and translation into clinical practice. Strong consideration was given to providing pragmatic guidance and recommendations for bedside neuromonitoring, even in the absence of high quality data.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

Electronic return file specifications and record layouts for individual income tax returns, tax year 1999 /

"Rev. 8, 1999."

Leadership and organisational outcomes in healthcare

This research examined to what extent and how leadership is related to organisational outcomes in healthcare. Based on the Job Demands-Resource model, a set of hypotheses was developed, which predicted that the effect of leadership on healthcare outcomes would be mediated by job design, employee engagement, work pressure, opportunity for involvement, and work-life balance. The research focused on the National Health Service (NHS) in England, and examined the relationships between senior leadership, first line supervisory leadership and outcomes. Three years of data (2008 – 2010) were gathered from four data sources: the NHS National Staff Survey, the NHS Inpatient Survey, the NHS Electronic Record, and the NHS Information Centre. The data were drawn from 390 healthcare organisations and over 285,000 staff annually for each of the three years. Parallel mediation regressions modelled both cross sectional and longitudinal designs. The findings revealed strong relationships between senior leadership and supervisor support respectively and job design, engagement, opportunity for involvement, and work-life balance, while senior leadership was also associated with work pressure. Except for job design, there were significant relationships between the mediating variables and the outcomes of patient satisfaction, employee job satisfaction, absenteeism, and turnover. Relative importance analysis showed that senior leadership accounted for significantly more variance in relationships with outcomes than supervisor support in the majority of models tested. Results are discussed in relation to theoretical and practical contributions. They suggest that leadership plays a significant role in organisational outcomes in healthcare and that previous research may have underestimated how influential senior leaders may be in relation to these outcomes. Moreover, the research suggests that leaders in healthcare may influence outcomes by the way they manage the work pressure, engagement, opportunity for involvement and work-life balance of those they lead.