Thesis (M. Phil.)--University of Hong Kong, 2005. / Title proper from title frame. Also available in printed format.

Thesis (Ph. D.)--Columbia University, 1936. / Vita. Diagrams on versos of numbered pages, not included in the paging. "Selected references": p. 125-126.

Thesis--University of Wisconsin. / Includes bibliographical references (leaves [298]-300).

Thesis (Ph. D.)--University of Nebraska-Lincoln, 2007. / Title from title screen (site viewed July 12, 2007). PDF text: iv, 153 p. : ill. UMI publication number: AAT 3252439. Includes bibliographical references. Also available in microfilm and microfiche formats.

A dissertation presented to the Faculty of Health, Durban University of Technology, for the Masters Degree in Technology: Chiropractic, 2009. / Background: The International Classification of Diseases (ICD) provides codes to classify diseases in such a manner, that every health condition is assigned to a unique category. Some of the most common diagnoses made by chiropractors are not included in the ICD-10 coding system, as it is mainly medically orientated and does not accommodate these diagnoses. This can potentially lead to reimbursement problems for chiropractors in future and create confusion for medical aid schemes as to what conditions chiropractors actually diagnose and treat. Aim: To determine the level of compliancy of chiropractors, in South Africa, to the ICD-10 coding procedure and the factors that may influence the use of correct ICD-10 codes. As well as to determine whether the ICD-10 diagnoses chiropractors commonly submit to the medical aid schemes, reflect the actual diagnoses made in practice. Method: The study was a retrospective survey of a quantitative nature. A self-administered questionnaire was e-mailed and posted to 380 chiropractors, practicing in South Africa. The electronic questionnaires were sent out four times at two week intervals for the duration of eight weeks; and the postal questionnaires sent once. A response rate of 16.5% (n = 63) was achieved. Raw data was received from the divisional manager of the coding unit of Discovery Health (Pty) Ltd. in the form of an excel spreadsheet containing the most common ICD-10 diagnoses made by chiropractors in South Africa, for the period June 2006 to July 2007, who had submitted claims to the Medical Scheme. The spreadsheet also contained depersonalised compliance statistics of chiropractors to the ICD-10 system from July 2006 to October 2008. SPSS version 15 was used for descriptive statistical data analysis (SPSS Inc., Chicago, Ill, USA). Results: The age range of the 63 participants who responded to the questionnaire was 26 to 79 years, with an average of 41 years. The majority of the participants were male (74.6%, n = 47). KwaZulu-Natal had 25 participants (39.6%), Gauteng 17 (26.9%), Western Cape 12 (19%), Eastern Cape four (6.3%), Free State and Mpumalanga two (3.1%) each and North West one (1.5%). The mean knowledge score for ICD-10 coding was 43.5%, suggesting a relatively low level of knowledge. The total percentage of mistakes for electronic claims was higher for both the primary and unlisted claims (3.93% and 2.18%), than for manual claims iv (1.57% and 1.59%). The total percentage of mistakes was low but increased marginally each year for both primary claims (1.43% in 2006; 1.99% in 2007; 2.33% in 2008) and unlisted claims (0% in 2006; 2.61% in 2007; 3.07% in 2008). CASA members were more likely to be aware of assistance offered, in terms of ICD-10 coding through the medical schemes and the association (p = 0.131), than non-members. There was a non-significant trend towards participants who had been on an ICD-10 coding course (47.6%; n = 30), having a greater knowledge of the ICD-10 coding procedures (p = 0.147). Their knowledge was almost 10% higher than those who had not been on a course (52.4%; n = 33). Most participants (38.1%; n = 24) did not use additional cause codes when treating cases of musculoskeletal trauma, nor did they use multiple codes (38.7%; n = 24) when treating more than one condition in the same patient. Nearly 70% of participants (n = 44) used the M99 code in order to code for vertebral subluxation and the majority (79.4%; n = 50) believed the definition of subluxation used in ICD-10 coding to be the same as that which chiropractors use to define subluxation. According to the medical aid data, the top five diagnoses made by chiropractors from 2006 to 2007 were: Low back pain, lumbar region, M54.56 (8996 claims); Cervicalgia, M54.22 (6390 claims); Subluxation complex, cervical region, M99.11 (2895 claims); Other dorsalgia, multiple sites in spine, M54.80 (1524 claims) and Subluxation complex, sacral region, M99.14 (1293 claims). According to the questionnaire data, the top five diagnoses (Table 4.24) were: Lumbar facet syndrome, M54.56 (25%); Lumbar facet syndrome, M99.13 (23.3%); Cervical facet syndrome, M99.11 (21.7%); Cervicogenic headache, G44.2 (20%) and Cervicalgia, M54.22 (20%). Conclusion: The sample of South African chiropractors were fairly compliant to the ICD-10 coding system. Although the two sets of data (i.e. from the medical aid scheme and the questionnaire) regarding the diagnoses that chiropractors make on a daily basis correlate well with each other, there is no consensus in the profession as to which codes to use for chiropractic specific diagnoses. These chiropractic specific diagnoses (e.g. facet syndrome) are however, the most common diagnoses made by chiropractors in private practice. Many respondents indicated that because of this they sometimes use codes that they know will not be rejected, even if it is the incorrect code. For more complicated codes, the majority of respondents indicated that they did not know how to or were not interested in submitting the correct codes to comply with the level of specificity required by the medical aid schemes. The challenge is to make practitioners aware of the advantages of correct coding for the profession.

published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

Title: Parameterization of claims distribution in non-life insurance Author: Bc. Mária Špaková Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Michal Pešta Ph.D., MFF UK Abstract: This paper deals with the parameterization of claim size distributions in non-life insurance. It consists of the theoretical and the practical part. In the first part we discuss the usual distributions of claims and their properties. One section is devoted to extreme values distributions. Consequently, we mention the most known methods for parameter estimation - the maximum likelihood method, the method of moments and the method of weighted moments. The last theoretical chapter is focused on some validation techniques and goodness-of-fit tests. In the practical part we apply some of the discussed approaches on real data. However, we concentrate mainly on the large claims modeling - firstly, we select a reasonable threshold for our data and then we fit the claims by the generalized Pareto distribution together with the introduced parameterization procedures. Based on the results of the applied validation methods we will choose appropriate models for the biggest claims. Keywords: parameterization, non-life insurance, claims distribution.

published_or_final_version / abstract / toc / Statistics and Actuarial Science / Master / Master of Philosophy

The goal of the project was to use the data in the Workers' Compensation Board (WCB) of British Columbia's data warehouse to develop a statistical model that could predict on an ongoing basis those short-term disability (STD) claims that posed a potential high financial risk to the WCB. We were especially interested in identifying factors that could be used to model the transition process of claims from the STD stratum to the vocational rehabilitation (VR) and long term disability (LTD) strata, and forecast their financial impact on the WCB. The reason for this focus is that claims experiencing these transitions represent a much higher financial risk to the WCB than claims that only progress to the health care (HC) and/or the short term disability (STD) strata. The sample used to investigate the conversion processes of claims consists of all STD claims (323,098) that had injury dates between January 1, 1989 and December 31, 1992. Although high-risk claims represent only 4.2 % of all STD claims, they have received 64.3% ($1.2 billion) of the total payments and awards ($1.8 billion) made to July 1999. Low-risk claims make up 95.8% of all the claims but only receive 35.7% ($651 million) of the payments and awards. Moreover, the average cost of high-risk claims ($86,200) is 41 times higher than the average cost of low-risk claims ($2,100). The main objective of the project was to build a reliable statistical model to identify high-risk claims that can be readily implemented at the WCB and thereby improve business decisions. To identify high-risk claims early on, we used logistic regression modeling. Since ten of the most frequently observed injury types make up 95.72% of all the claims, separate logistic regression models were built for each of them. Besides injury type, we also identified STD days paid and age of claimant as statistically significant predictors. The logistic regression models can be used to identify high-risk claims prior to or at the First Final STD payment date provided we know the injury type, STD days paid and age of claimant. The investigation showed that the more STD days paid and the older the injured worker, the higher the probability of the claim being high-risk.

A dissertation presented to the Faculty of Health, Durban University of Technology, for the Masters Degree in Technology: Chiropractic, 2009. / Background: The International Classification of Diseases (ICD) provides codes to classify diseases in such a manner, that every health condition is assigned to a unique category. Some of the most common diagnoses made by chiropractors are not included in the ICD-10 coding system, as it is mainly medically orientated and does not accommodate these diagnoses. This can potentially lead to reimbursement problems for chiropractors in future and create confusion for medical aid schemes as to what conditions chiropractors actually diagnose and treat. Aim: To determine the level of compliancy of chiropractors, in South Africa, to the ICD-10 coding procedure and the factors that may influence the use of correct ICD-10 codes. As well as to determine whether the ICD-10 diagnoses chiropractors commonly submit to the medical aid schemes, reflect the actual diagnoses made in practice. Method: The study was a retrospective survey of a quantitative nature. A self-administered questionnaire was e-mailed and posted to 380 chiropractors, practicing in South Africa. The electronic questionnaires were sent out four times at two week intervals for the duration of eight weeks; and the postal questionnaires sent once. A response rate of 16.5% (n = 63) was achieved. Raw data was received from the divisional manager of the coding unit of Discovery Health (Pty) Ltd. in the form of an excel spreadsheet containing the most common ICD-10 diagnoses made by chiropractors in South Africa, for the period June 2006 to July 2007, who had submitted claims to the Medical Scheme. The spreadsheet also contained depersonalised compliance statistics of chiropractors to the ICD-10 system from July 2006 to October 2008. SPSS version 15 was used for descriptive statistical data analysis (SPSS Inc., Chicago, Ill, USA). Results: The age range of the 63 participants who responded to the questionnaire was 26 to 79 years, with an average of 41 years. The majority of the participants were male (74.6%, n = 47). KwaZulu-Natal had 25 participants (39.6%), Gauteng 17 (26.9%), Western Cape 12 (19%), Eastern Cape four (6.3%), Free State and Mpumalanga two (3.1%) each and North West one (1.5%). The mean knowledge score for ICD-10 coding was 43.5%, suggesting a relatively low level of knowledge. The total percentage of mistakes for electronic claims was higher for both the primary and unlisted claims (3.93% and 2.18%), than for manual claims iv (1.57% and 1.59%). The total percentage of mistakes was low but increased marginally each year for both primary claims (1.43% in 2006; 1.99% in 2007; 2.33% in 2008) and unlisted claims (0% in 2006; 2.61% in 2007; 3.07% in 2008). CASA members were more likely to be aware of assistance offered, in terms of ICD-10 coding through the medical schemes and the association (p = 0.131), than non-members. There was a non-significant trend towards participants who had been on an ICD-10 coding course (47.6%; n = 30), having a greater knowledge of the ICD-10 coding procedures (p = 0.147). Their knowledge was almost 10% higher than those who had not been on a course (52.4%; n = 33). Most participants (38.1%; n = 24) did not use additional cause codes when treating cases of musculoskeletal trauma, nor did they use multiple codes (38.7%; n = 24) when treating more than one condition in the same patient. Nearly 70% of participants (n = 44) used the M99 code in order to code for vertebral subluxation and the majority (79.4%; n = 50) believed the definition of subluxation used in ICD-10 coding to be the same as that which chiropractors use to define subluxation. According to the medical aid data, the top five diagnoses made by chiropractors from 2006 to 2007 were: Low back pain, lumbar region, M54.56 (8996 claims); Cervicalgia, M54.22 (6390 claims); Subluxation complex, cervical region, M99.11 (2895 claims); Other dorsalgia, multiple sites in spine, M54.80 (1524 claims) and Subluxation complex, sacral region, M99.14 (1293 claims). According to the questionnaire data, the top five diagnoses (Table 4.24) were: Lumbar facet syndrome, M54.56 (25%); Lumbar facet syndrome, M99.13 (23.3%); Cervical facet syndrome, M99.11 (21.7%); Cervicogenic headache, G44.2 (20%) and Cervicalgia, M54.22 (20%). Conclusion: The sample of South African chiropractors were fairly compliant to the ICD-10 coding system. Although the two sets of data (i.e. from the medical aid scheme and the questionnaire) regarding the diagnoses that chiropractors make on a daily basis correlate well with each other, there is no consensus in the profession as to which codes to use for chiropractic specific diagnoses. These chiropractic specific diagnoses (e.g. facet syndrome) are however, the most common diagnoses made by chiropractors in private practice. Many respondents indicated that because of this they sometimes use codes that they know will not be rejected, even if it is the incorrect code. For more complicated codes, the majority of respondents indicated that they did not know how to or were not interested in submitting the correct codes to comply with the level of specificity required by the medical aid schemes. The challenge is to make practitioners aware of the advantages of correct coding for the profession.