Background: Investigators are often interested in using population-level health administrative data in inflammatory bowel disease (IBD) patients to study disease outcomes, risk factors and treatment effects to enhance knowledge, shape clinical practice and influence health care policy. A major limitation of using health administrative data for these purposes is the lack of detailed clinical data to adjust for the confounding effects of differential disease severity on observed associations. Methods to account for disease severity using administrative variables would offer a major advance to population-level studies in IBD patients. Thus, in this study we aimed to use a cohort of IBD patients from The Ottawa Hospital (TOH) to validate a model that was originally developed in Manitoba for estimating clinical disease course in IBD patients through healthcare utilization measures. Objectives: The objectives of this thesis are: 1) To identify and characterize a reference cohort of IBD patients in the ambulatory clinics of four gastroenterologists from TOH on clinical disease course in the preceding year (reference cohort), based on a Manitoba definition of clinical disease course; 2) To fit a partial proportional odds (PPO) model for predicting IBD course, derived using Manitoba health administrative data, to the reference cohort of IBD patients using Ontario health administrative data; 3) To derive new PPO models of IBD disease course for the reference cohort using Ontario administrative variables and compare model performance; and 4) To apply the models to the Ontario Crohn’s and Colitis cohort (OCCC) to estimate IBD course in Ontario, and compare the distribution to that of the Manitoba IBD population.Methods: We first identified a reference cohort of IBD patients in Ontario from the outpatient clinics at TOH during fiscal year 2015. Through chart review, we classified these patients into one of four clinical disease categories (remission, mild, moderate, or severe) using the Manitoba definition. We linked these patients to Ontario health administrative datasets. Given slight differences in data structure and coding between Manitoba and Ontario, we were unable to directly test the Manitoba model and instead fit a PPO model to the Ontario cohort using analogous administrative variables to those used in the final Manitoba model (“adapted model”). We subsequently derived new PPO models using unique Ontario administrative variables under three strategies: 1) Stepwise variable selection (“stepwise model”); 2) Forced fitting of all variables (“all-variables model”); and 3) Using a two-step modelling algorithm that considered IBD-related hospitalizations separate from other administrative variables (“two-step model”). We then compared model performance from the four strategies. Finally, we applied the models to the Ontario IBD population from 2004 to 2016 and compared model estimates to those from Manitoba. Results: We identified 963 patients with IBD from TOH outpatient clinics, of which 52.3% (n=504) were males, 64.6% (n=622) had Crohn's Disease, and 89.2% (n=859) resided in an urban setting. Based on the Manitoba definition, 64.9% of patients within our reference cohort were classified as remission, while 11.4%, 14.1%, and 9.6% were classified as mild, moderate, and severe disease course, respectively. The adapted model (c-statistic 0.77, goodness-fit p-value 0.28) performed comparably to the other models: the stepwise model (c-statistic 0.77, goodness-fit p-value 0.50), the all-variables model (c-statistic 0.77, goodness-fit p-value 0.53), and the two-step model (c-statistic 0.78, goodness-fit p-value 0.75). The adapted model also resulted in overall similar estimates with regards to the disease course distribution among the Ontario IBD population. However, on closer inspection, our two-step model, in which individuals who had been hospitalized for an IBD-related indication within the past year were assumed to have severe disease, performed better with respect to accurately classifying individuals with moderate or severe disease, without sacrificing discriminative ability. Based on the two-step model, from 2004 to 2016, 89.2-91.2% of the Ontario IBD population was in remission, 0% had mild disease, 2.4-3.2% had moderate disease, and 5.9-8.4% had severe disease. Distribution of disease course among IBD patients in Ontario differed considerably than that in Manitoba. Conclusion: In the absence of clinical information within health administrative data, we present and compare four different models that can be used to partially account for the confounding effect of disease course among IBD patients in future population-based studies using Ontario health administrative data. Given that our models did not perform as originally expected, especially with regards to accurately identifying individuals with more active disease states, we advise researchers to use these models at their own discretion.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第18191号 / 社医博第52号 / 新制||社医||8(附属図書館) / 31049 / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 中山 健夫, 教授 佐藤 俊哉, 教授 木村 剛 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18885号 / 医博第3996号 / 新制||医||1009(附属図書館) / 31836 / 京都大学大学院医学研究科医学専攻 / (主査)教授 中山 健夫, 教授 福原 俊一, 教授 小池 薫 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Over the past century, the prevalence of immune-mediated inflammatory diseases (IMIDs) has increased worldwide. It has been identified that exposures to environmental factors early in life are associated with increased risk of these diseases. However, hypothesis-driven analyses do not always identify all risk or protective factors, nor do they adequately explain interactions between variables on the risk of disease. Data mining has the capability of exploring the data without considering specific a priori hypotheses, instead providing possible hypotheses for further analysis. Though, data mining techniques are still not popular among epidemiologists as a trustworthy analytical tool to analyze population-based diseases due to inexplicability of some of the methods (e.g., neural networks), unfamiliarity with, or uncommon use of machine learning and data mining methods in real-world health care applications. At the same time, large amounts of routinely collected health data are amassed as a matter of operating electronic health systems. Routinely collected health data are not collected for research purposes; however, they are great sources of information for research as a secondary use of the data. In this study, following the design science research methodology, we developed a methodology to reliably analyze health administrative data using data mining techniques to provide reproducible, reliable, and trustworthy findings. The reliable data mining methodology on health administrative data was designed in this study to address impartiality, validity, and sustainability concerns in five stages: Data Selection, Preprocessing, Modelling, Evaluation, and Feedback. As part of the main contributions, we developed two unique preprocessing guidelines as the key components of the designed methodology in order to standardize technical steps and address contextual sources of bias. While the proposed methodology is general in its design, to evaluate the designed methodology, we implemented it in several case studies on the real health administrative data housed at ICES, Ontario, first to analyze children suffering with an IMID in Ontario, predict new cases, and, most importantly, generate new hypotheses. The first case study was extended to a second one to narrow focus from all IMIDs to asthma which formed the majority of the IMID cases. Eventually, a third case study was implemented focusing on inflammatory bowel disease (IBD) and systemic autoimmune rheumatic diseases (SARDs) to better compare the findings. We applied both predictive and descriptive modelling techniques such as decision tree, neural network, logistic regression, and k-means clustering on the prepared datasets with more than 700K records and over 80 input variables. We built classification models with notable quality of performance (AUC of 68%), identified the significant factors associated to IMIDs, and extracted multifactorial rules causing protectiveness against or high risk of developing asthma, IBD, and SARDs. The factors that highly contributed to the extracted multifactorial rules were “general childhood infection”, “use of antibiotics”, “streptococcus pyogenes”, “respiratory infection”, “gastroenteritis”, “mother's prevalence of any IMID”, and “baby's sex”. The findings were evaluated and verified by health experts. Most data mining studies which are applied to health data do not handle bias and confounding in their work. However, the systematic errors were identified, and their risks were assessed in these case studies due to following the designed reliable methodology. The results with high risk of bias were reported to disregard. Therefore, this process allowed us to apply data mining techniques to discover new multifactorial rules and identify the factors with the highest impact among the 128 factors observed in the past epidemiological studies, while preserving the trust of domain experts in the results.

Blood sampling causes significant blood loss in intensive care unit (ICU) patients (up to 41 mL per day). Only 10% of the blood collected is used for testing suggesting that volumes can be reduced without compromising patient care or laboratory processes. Blood loss contributes to anemia which is highly prevalent in the ICU (>90% after 3 days) and is associated with major adverse cardiovascular outcomes and death. Diagnostic blood loss increases the likelihood of red blood cell (RBC) transfusion which is administered to about 40% of ICU patients (half are given in absence of hemorrhage) and has significant health risks. Small-volume blood collection tubes, which collect about 50% less blood, are available, but rarely used in adults. They have the same cost as standard-volume tubes and are compatible with laboratory equipment. The rationale for the continued use of standard-volume tubes is a theoretical concern about inadequate volume for testing, and the absence of data showing the benefit of small-volume tube use on an important clinical outcome. A study is needed to show that small-volume tubes reduce blood loss, anemia and RBC transfusion without harms or negative consequences on patient care and hospital procedures compared to standard-volume tubes. If this could be shown, it may lead to practice change regarding blood collection for laboratory testing. A stepped-wedge cluster randomized trial is the ideal study design for this low-risk intervention. By incorporating the small-volume tubes into routine clinical practice and using administrative and hospital electronic medical record data, this study would be a pragmatic, cost-effective way to evaluate effectiveness and implementation. However, prior to conducting a full-scale trial powered on clinical outcomes, a pilot study is needed to determine whether a larger study will be feasible. The goals of this thesis are to (i) summarize the existing evidence regarding small-volume tubes; (ii) discuss cluster randomized trial methodology;(iii) discuss the use of health care administrative data for research; (iv) discuss the role of pilot studies; and (v) present the design of a pilot stepped wedge randomized trial of small-volume versus standard-volume blood collection tubes to evaluate the feasibility of a full-scale trial. / Thesis / Master of Science (MSc) / Blood testing is a preventable cause of blood loss. Patients in the intensive care unit (ICU) have about 41 mL of blood taken per day for testing (like donating 1 unit of blood every 8 days). This contributes to anemia (low red blood cells) and transfusion, which are harmful. About 40% of ICU patients get at least one red blood cell transfusion which is a limited resource with health risks. Most of the blood sent to the laboratory is discarded (up to 90%) suggesting that volumes can be reduced without compromising care. The goals of this thesis are to (i) summarize the evidence for reducing blood loss for laboratory testing; (ii) discuss cluster randomized trials; (iii) discuss use of health care administrative data for research; (iv) discuss the role of pilot studies; and (v) present a pilot stepped wedge cluster randomized trial of small-volume versus standard-volume blood collection tubes in ICU patients.

Background: This study compared patient profiles and clinical courses of SARS-CoV-2 infected inpatients over different pandemic periods. Methods: In a retrospective cross-sectional analysis, we examined administrative data of German Helios hospitals using ICD-10-codes at discharge. Inpatient cases with SARS-CoV-2 infection admitted between 03/04/2020 and 07/19/2022 were included irrespective of the reason for hospitalization. All endpoints were timely assigned to admission date for trend analysis. The first pandemic wave was defined by change points in time-series of incident daily infections and compared with different later pandemic phases according to virus type predominance. Results: We included 72,459 inpatient cases. Patients hospitalized during the first pandemic wave (03/04/2020–05/05/2020; n = 1,803) were older (68.5 ± 17.2 vs. 64.4±22.6 years, p<0.01) and severe acute respiratory infections were more prevalent (85.2 vs. 53.3%, p < 0.01). No differences were observed with respect to distribution of sex, but comorbidity burden was higher in the first pandemic wave. The risk of receiving intensive care therapy was reduced in all later pandemic phases as was in-hospital mortality when compared to the first pandemic wave. Trend analysis revealed declines of mean age and Elixhauser comorbidity index over time as well as a decline of the utilization of intensive care therapy, mechanical ventilation and in-hospital mortality. Conclusion: Characteristics and outcomes of inpatients with SARS-CoV-2 infection changed throughout the observational period. An ongoing evaluation of trends and care pathways will allow for the assessment of future demands

Title: Maternal Mood and Anxiety Disorders and Child School Readiness: A Manitoba Population-Based Study Objective: This study examined the relationship between several features of maternal Mood/Anxiety – timing, recurrence/persistence and severity – and child development on five key areas of school readiness at kindergarten, controlling for health, demographic and socio-economic factors. Methods: Using administrative data to further understand these relationships at a population level and over time, 18,331mother-child pairs were linked using a unique identifier. Maternal Mood/Anxiety was defined using the number of physician visits for mood and anxiety disorders and the number of prescriptions filled for antidepressants or sedatives/hypnotics. The outcome measures were child scores on five domains of the Early Development Instrument, a population-level tool for determining readiness for school at an aggregate level. Structural equation modeling was used to examine the relationship between maternal Mood/Anxiety and child outcomes for individual time periods, Mood/Anxiety recurrence/persistence and Mood/Anxiety severity. Infant health at birth, the family/socio-economic environment, child age and child gender were also entered into the models. Stratified analysis was undertaken to determine whether SES moderates the relationship between Mood/Anxiety and child outcomes. Results: Maternal Mood/Anxiety had a modest significant negative association with EDI scores, particularly for social, emotional and physical development. Prenatal and recurrent Mood/Anxiety were associated with lower scores on all five outcome domains. The influence of maternal Mood/Anxiety was mediated by the family environment, which had a strong, significant association with the outcomes, particularly for language and cognitive development. Infant health at birth was significantly associated with child outcomes, particularly for physical health. Socio-economic status (SES) was a moderator of the relationship between Mood/Anxiety and child outcomes. Conclusion: Using administrative data to define maternal mood and anxiety disorders is a sensitive measure to detect differences in five key areas of child development, particularly for social, emotional and physical outcomes. Family-related variables had a much stronger relationship with child outcomes than mood and anxiety disorders. Findings from this study can be used to design, implement and evaluate high quality clinical, program and policy interventions to support mothers and families and the healthy development of their children.

No description available.

With the inevitable adoption of information technology into all areas of human pursuit, the potential benefits for health care should not be overlooked. In Australia, details of most health care encounters are currently recorded for administrative purposes. This results in an impressive electronic data-bank that could provide a national resource for health service evaluation. ¶ Evaluation of health services has become increasingly important to provide indicators of the benefits, risks and cost-effectiveness of treatments. However, if administrative data are to be used for this purpose, several questions must first be addressed: Are the current data collections accessible? What outcome measures can be derived from these data? Can privacy issues be managed? Could the quality of the data be improved? Is the existing infrastructure adequate to supply data for evaluation purposes? Could the existing system provide a basis for the development of an integrated health information system? ¶ The aims of the project were: · To examine the potential for using administrative data to generate outcome measures and surveillance indicators. · To investigate the logistics of gaining access to these data for the purpose of research. This to be achieved within the current ethical, political and financial framework. · To compare the Australian health-service data system with the current international state-of-the-art. · To develop suggestions for expansion of the present system as part of an integrated health record and information system. This system to manage patient records and provide data for quality management, treatment surveillance and cost-effectiveness evaluation as a routine activity. ¶ The thesis is presented in two parts. In the first part, a historical cohort study is described that involved patients with implantable medical devices. The potential to evaluate outcomes was investigated using all national health-service information currently available in electronic form. Record linkage techniques were used to combine and augment the existing data collections. Australia’s national health databases are to varying degrees, amenable to such linkage and cover doctor visits, pharmaceuticals, hospital admissions and deaths. The study focused on medical devices as an illustrative case but the results are applicable to the routine assessment of all medical and surgical interventions. ¶ For the Australian ‘Medical Devices study’, the records of 5,316 patients who had medical device implants in 1993-94 were selected from the archives of a major private health insurer. Five groups of medical implants were studied: heart valves, pacemakers, hips, vascular grafts and intra-optic lenses. Outcomes for these patients, including death, re-operation and health service utilisation, were compared and analysed. ¶ A comparison study was performed using data from the Manitoba Health database in Winnipeg, Canada. Manitoba provides a very similar demographic group to that found in Australia and is an example of a prototype integrated-health-information system. One of the principal advantages for research is that personally identified data about medical and hospital services are collected for all patients. Selection bias is eliminated because individual consent is not required for this type of research and all selected patients could be included in the study. ¶ The two studies revealed many barriers to the use of administrative data for health outcomes research. Service event data for the Australian cohort could be collected but only after long delays and hospital morbidity data were not available for the entire cohort. In contrast to the situation in Australia, the Manitoba data were both accessible and complete, but were lacking in detail in some areas. ¶ Analysis of the collected data demonstrated that without the addition of clinical data only general indications of trends could be deduced. However, with minimal supplementary clinical data, it was possible to examine differences in performance between brands of medical devices thus indicating one of the uses for this type of data collection. ¶ In the second part of the thesis, conclusions are presented about the potential uses and limitations of the existing system and its use as a basis for the development of a national Integrated Health Record and Information System (IHRIS). The need for the establishment of a systemic quality management system for health care is discussed. ¶ The study shows that linked administrative data can provide information about health outcomes which is not readily available from other sources. If expanded and integrated, the system that is currently used to collect and manage administrative data, could provide the basis for a national health information system. This system would provide many benefits for health care. Benefits would include the monitoring, surveillance and cost-effectiveness analysis of new and existing treatments involving medical devices, drugs and surgical procedures. An integrated health information system could thus provide for both clinical and administrative needs, while in addition providing data for research. ¶ Unfortunately, in Australia, the use of administrative data for this purpose is not currently feasible. The principal barrier is the existence of a culture within the Australian health care system which is not supportive of research and is deficient in quality and safety measures. ¶ Recent initiatives by both the Commonwealth and state governments have supported the introduction of measures to improve quality and safety in health care. It is argued here that an Integrated Health Record and Information System (IHRIS) would provide an essential component of any such scheme. The results of this study have important policy implications for health care management in both the administrative and clinical domains.

Inflammatory bowel disease (IBD), characterized by chronic gastrointestinal inflammation, represents a significant childhood chronic disease. In this thesis, a case ascertainment definition of paediatric-onset IBD was validated using administrative data and developed the Ontario Crohn’s and Colitis Cohort (OCCC). The epidemiology of paediatric IBD in Ontario was described, demonstrating that Ontario has one of the highest worldwide incidence rates. Statistically significant increases in incidence were noted in 0-4 year olds (5.0%/year, p=0.03) and 5-9 year olds (7.6%/year, p<0.0001), but not in other age groups. Lower income children were more likely to be hospitalized at least once (hazard ratio (HR) 1.17, 95% confidence intervals (CI) 1.05-1.30) or visit the ED (HR 1.21, 95% CI 1.09-1.35) and had more IBD-related physician visits (odds ratio (OR) 3.73, 95% CI 1.05-13.27). Lower income children with Crohn's disease (CD) (not ulcerative colitis [UC]) were more likely to undergo intra-abdominal surgery within 3 years of diagnosis (OR 1.22, 95% CI 1.01-1.49), especially if diagnosed after 2000 (OR 1.79, 95% CI 1.27-2.53). Finally, changes in health services utilization and surgical rates were described, as were changes in specialist care provision and immunomodulator use in children with IBD between 1994-2007. The changes to care included increased outpatient care provided by paediatric gastroenterologists, and increased immunomodulator use. Children diagnosed with CD, but not UC, in recent years had lower surgical rates. In CD patients, intra-abdominal surgical rates within three years of diagnosis decreased from 18.8% in children diagnosed in 1994-1997 to 13.6% in those diagnosed in 2001-2004 (P = 0.035). When stratified by age at diagnosis, this decrease was significant in children diagnosed ≥10 years old (OR 0.67, 95% CI 0.48-0.93). The OCCC will continue to be used to investigate the epidemiology and burden of paediatric IBD and to improve the care received by children with IBD in Ontario.