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Classification systems in psychiatry are a work in progress. Therefore, continued efforts to improve their validity are necessary. Epidemiology provides a scientific method to assess the extent of psychiatric morbidity in community populations. However, data from epidemiological surveys have also contributed, either directly or indirectly, to many changes in the classification systems. Recent reviews of the current state of psychiatric classification indicate four unresolved issues: 1) the presence of two differing classification systems, 2) the role of the clinical significance criterion in differentiating psychopathology from normality, 3) the relationship of the exclusion criteria to the co-occurrence of psychiatric disorder pairs, and 4) the relative validity of categorical versus dimensional conceptualizations of psychiatric disorders. The current thesis examines these four unresolved issues, using data from a large-scale epidemiological survey of psychiatric disorders. With regard to GAD, differences in diagnostic criteria between DSM-IV and ICD-10 resulted in different types of cases identified, despite similarities in prevalence. The DSM-IV diagnostic criterion for clinical significance impacted, albeit to different degrees, on the prevalence, health service use and impairment of five disorders. The exclusion criteria in both DSM-IV and ICD-10 were significantly related to the patterns of co-occurrence found in the data. Using the example of depression, symptoms were more consistent with a dimensional rather than a categorical structure. A specific research agenda is proposed, the aim of which is to provide possible avenues of research that may benefit revisions to classification systems and the conduct of epidemiological surveys. This research agenda contains a number of suggestions. Future revisions will benefit from an explicit understanding of the differences between the classification systems. Better definitions of the concepts of clinical significance and psychiatric disorder are required. The co-occurrence of disorder pairs in epidemiological data informs understanding of the exclusion criteria, but the validity of these criteria relies on different data. Dimensional models of classification may yield more information than categorical models, and methods for incorporating them in large-scale surveys are proposed. It is concluded that epidemiological data should continue to play a significant part in the refinement of psychiatric classification.

International Classification of Diseases the 10th Revision (ICD-10) was implemented October 1, 2015, and there was little knowledge how the transition to ICD-10 would impact the revenue cycle for intraoperative neurophysiological monitoring medical practices in Oklahoma. This correlational quantitative study examined the changes in dependent variables of reimbursements due to the change from ICD-9 to ICD-10 for independent variables of intraoperative neurophysiological monitoring procedure codes. The reimbursements from 2014 were compared to reimbursements from 2016. Prices were adjusted for inflation to 2016 dollar values. Annual reimbursements decreased for all intraoperative neurophysiological monitoring procedures examined except the remote monitoring code. The intraoperative neurophysiological monitoring procedure with the greatest mean annual decreases in reimbursement was the lower somatosensory evoked potentials. The intraoperative neurophysiological monitoring procedures with the least annual reimbursement decreases were transcranial electrical motor potential monitoring and electromyography. The findings of the budget-impact analysis and cost-effectiveness analysis indicated that reimbursement for procedures has steadily decreased from 2014 to 2016, causing a negative effect on practices' revenue cycle management. The findings of this study could benefit intraoperative neurophysiological monitoring companies in Oklahoma by supporting adjustments essential for healthcare leaders to maintain a financially sustainable intraoperative neurophysiological monitoring medical practice.

<p>The essay investigates the economic burden of skin, soft tissue, bone and lung infections in Sweden 2003. The cost-of-illness method, based on the human capital theory, is used in the estimation. A prevalence approach and a top-down method were chosen for direct as well as indirect costs. Also there is a discussion concerning health economic aspects of antibiotic resistance and evidence of the increasing costs because of it. The lack of data leads to a result within a large interval of uncertainty; the direct costs are estimated to 1 072 million SEK and indirect costs are estimated to 4 655 million SEK.</p>

The essay investigates the economic burden of skin, soft tissue, bone and lung infections in Sweden 2003. The cost-of-illness method, based on the human capital theory, is used in the estimation. A prevalence approach and a top-down method were chosen for direct as well as indirect costs. Also there is a discussion concerning health economic aspects of antibiotic resistance and evidence of the increasing costs because of it. The lack of data leads to a result within a large interval of uncertainty; the direct costs are estimated to 1 072 million SEK and indirect costs are estimated to 4 655 million SEK.

Electronic Health Record (EHR) is an umbrella term encompassing demographics and health information of a patient from many different sources in a digital format. Deep learning has been used on EHRs in many successful studies and there is great potential in future implementations. In this study, diagnosis classification of EHRs with Multi-layer Perceptron models are studied. Two MLPs with different architectures are constructed and run on both a modified version of the EHR dataset and the raw data. A Random Forest is used as baseline for comparison. The MLPs are not successful in beating the baseline, with the best-performing MLP having a classification accuracy of 48.1%, which is 13.7 percentage points lower than that of the baseline. The results indicate that when the dataset is small, this approach should not be chosen. However, the dataset is growing over time and thus there is potential for continued research in the future. / Elektronisk patientjournal (EHR) är ett paraplybegrepp som används för att beskriva en digital samling av demografisk och medicinsk data från olika källor för en patient. Det finns stor potential i användandet av djupinlärning på dessa journaler och många framgångsrika studier har redan gjorts på området. I denna studie undersöks diagnosklassificering av elektroniska patientjournaler med Multi-layer perceptronmodeller. Två MLP-modeller av olika arkitekturer presenteras. Dessa körs på både en anpassad version av EHR-datamängden och på den råa EHR-datan. En Random Forest-modell används som baslinje för jämförelse. MLP-modellerna lyckas inte överträffa baslinjen, då den bästa MLP-modellen ger en klassifikationsnoggrannhet på 48,1%, vilket är 13,7 procentenheter mindre än baslinjens. Resultaten visar att en liten datamängd indikerar att djupinlärning bör väljas bort för denna typ av problem. Datamängden växer dock över tid, vilket gör områdetattraktivt för framtida studier.

Background: Pre-eclampsia (PET) is one of the major causes of maternal and neonatal morbidity and mortality1. Misclassification of PET can lead to biased or erroneous results in epidemiologic studies resulting in false conclusions. Objectives: The objectives of this thesis are to determine the validity of PET diagnosis in pregnant women in administrative database using the ICD-10-CA codes, to explore the nature of misclassification, and to estimate whether misclassification of PET diagnosis in administrative database may result in biased conclusions. Methods: Pregnant women who participated in the Ottawa and Kingston (OaK) Birth Cohort study and delivered in the Ottawa Hospital were included in the study. All cases with hypertensive disorder of pregnancy in the study population were adjudicated to confirm diagnosis of PET. This adjudicated dataset was used as a reference standard. The PET incidence in hospital discharge database was compared with PET incidence calculated from the reference standard database. Results: 2887 of the requested charts were available for review. The PET incidence was much lower in administrative database (1.47%) than in the OaK Birth Cohort Study (3.6%). The results of the study demonstrated that hospital discharge database via ICD-10-CA was not very sensitive to determine incidence of PET since sensitivity of ICD-10-CA diagnostic codes for PET was low (35.92% with 95% Confidence Intervals (CI): 26.7; 45.9) but specificity, PPV, and NPV were high. The majority of misclassified cases belonged to the category (according to the proposed classification) “PET pregnancies coded with incorrect ICD-10-CA code” (78.88%) followed by the category “Pregnancies affected by PET coded as normal” (14.08%). Conclusion: Using hospital discharge database and ICD-10-CA coding to determine incidence of PET in certain settings may yield low sensitivity. Researchers should validate the results when using the hospital discharge database for PET research to ensure that the findings based on analyses of such data demonstrate what they claimed to demonstrate.

Background: Pre-eclampsia (PET) is one of the major causes of maternal and neonatal morbidity and mortality1. Misclassification of PET can lead to biased or erroneous results in epidemiologic studies resulting in false conclusions. Objectives: The objectives of this thesis are to determine the validity of PET diagnosis in pregnant women in administrative database using the ICD-10-CA codes, to explore the nature of misclassification, and to estimate whether misclassification of PET diagnosis in administrative database may result in biased conclusions. Methods: Pregnant women who participated in the Ottawa and Kingston (OaK) Birth Cohort study and delivered in the Ottawa Hospital were included in the study. All cases with hypertensive disorder of pregnancy in the study population were adjudicated to confirm diagnosis of PET. This adjudicated dataset was used as a reference standard. The PET incidence in hospital discharge database was compared with PET incidence calculated from the reference standard database. Results: 2887 of the requested charts were available for review. The PET incidence was much lower in administrative database (1.47%) than in the OaK Birth Cohort Study (3.6%). The results of the study demonstrated that hospital discharge database via ICD-10-CA was not very sensitive to determine incidence of PET since sensitivity of ICD-10-CA diagnostic codes for PET was low (35.92% with 95% Confidence Intervals (CI): 26.7; 45.9) but specificity, PPV, and NPV were high. The majority of misclassified cases belonged to the category (according to the proposed classification) “PET pregnancies coded with incorrect ICD-10-CA code” (78.88%) followed by the category “Pregnancies affected by PET coded as normal” (14.08%). Conclusion: Using hospital discharge database and ICD-10-CA coding to determine incidence of PET in certain settings may yield low sensitivity. Researchers should validate the results when using the hospital discharge database for PET research to ensure that the findings based on analyses of such data demonstrate what they claimed to demonstrate.

The thesis builds up on the significance of the social aspect of the statistics giving direct reference to the standards of the European Union (EU) on statistics. The study concentrates on the modernization, reformation and transformation process of the Turkish Statistical System, particularly the health statistics on the basis of a specific Programme called &ldquo / Upgrading the Statistical System of Turkey&rdquo / funded by the EU and the Law on Turkish Statistics (No: 5429) within the process of the harmonization of the Turkish Statistical System, which aims the integration of the current system to the international one via the EU acquis communautaire. This thesis presents the causes of the death statistics as one of the most significant dimensions of statistics since it is the most extensive and the oldest public health surveillance system in the world. The reformation in the certification process, the classification stage and the analysis of the cause of the death statistics (COD) are examined in detail hereby. Improvement of the coverage, introduction of the International Classification of Diseases-10th Revision (ICD-10), development of institutional coordination and a new formation of the causes of death statistics in line with the EU requirements are analyzed in depth. Based on the findings of this study, it is proposed that the introduction of ICD-10 and improvement of the coverage of the COD statistics are not sufficient to ameliorate the shortcomings of the current death certificate system rested upon on the two documents including the &ldquo / COD forms&rdquo / and the &ldquo / burial licence&rdquo / in Turkey. The study also suggests that solutions to be proposed should be radical and effective since the problems encountered in the death certificate system are deep-rooted. Consequently, with regard to the issues of increasing the coverage of physical autopsy and providing training for the COD forms and with the aim of reducing diversified and complex chain of bureaucratic transactions, it is essential to bring an encompassing new legal base for the current death certificate system.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) surgery is the most common reason for elective pediatric orthopaedic surgery. Minimization of adverse events is an important goal. Institute of Medicine (IOM) outlined 6 facets of healthcare quality improvement within the acronym STEEEP. Two of these facets, Safety and Timeliness for AIS surgery in Canada, are examined in this thesis. METHODS: A three - part study, using clinical records at the largest Canadian pediatric hospital and CIHI national administrative data, determined i) the relationship between surgical wait times and rates of adverse events, along with determination of an empirically derived access target, ii) accuracy of ICD-10 coding of surgical AIS cases along with an optimal search strategy to identify surgical AIS cases, and iii) the volume – outcome relationships for scoliosis surgery using hierarchical and conventional single level multi-variate regression analysis. RESULTS: Access target of 3 months minimized the adverse events related to waiting. Optimal search strategy for AIS surgical cases using ICD-10 coding required combination of codes as each code in isolation was inaccurate due to limitations in coding definitions. There was no significant volume – outcome relationship using appropriate modeling strategies. CONCLUSIONS: Ensuring timeliness of surgical treatment of less than 3 months is important in surgical cases of AIS given the potential for curve progression in higher risk individuals who are skeletally immature with large magnitude curves at time of surgical consent. At the administrative database level, knowledge of coding accuracy and optimal search strategies are needed to capture a complete cohort for analysis. In AIS, several ICD-10 codes need to be combined. AIS surgery cases captured through this optimal search strategy, revealed no significant volume-outcome relationships with appropriate modeling. Based on these results, minimum volume thresholds and regionalization of care for AIS surgery does not appear to be justified. However, a larger sample size was needed to determine whether there was a clinically significant difference in wound infection and blood transfusion rates. Furthermore, clinical variables, not part of an administrative database such as curve pattern were not included.