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dc.contributor.advisorBurger, J.R.
dc.contributor.advisorSerfontein, J.H.P.
dc.contributor.advisorLubbe, M.S.
dc.contributor.authorSmit, Corlee
dc.date.accessioned2011-06-20T09:23:59Z
dc.date.available2011-06-20T09:23:59Z
dc.date.issued2008
dc.identifier.urihttp://hdl.handle.net/10394/4175
dc.descriptionThesis (M. Pharm. (Pharmacy Practice))--North-West University, Potchefstroom Campus, 2009.
dc.description.abstractBackground: According to the Council of Medical Schemes of South Africa (CMS, 2007:52), nearly seventeen percent of the total benefits paid during 2006 were for medicine. Medicine is thus a cost-driving contributor to total healthcare financing. There are various factors influencing and driving medicine usage and cost patterns, including inter alia provider preference, therapeutic committees, marketing and cost. Objectives: The purpose of this study was to identify the top twenty trade name products according to total cost and prevalence in a section of the private health care sector of South Africa, and to identify cost driving products. Methodology: A quantitative, retrospective drug utilisation review (DUR) study was performed on computerised medication records (medicine claims data) for two consecutive years (i.e. 2005 and 2006) that were obtained from a South African pharmaceutical benefit management company (PBM). The study population consisted of 1 218358 and 1 259 099 patients for 2005 and 2006 respectively. A total of 19 860 679 and 21 473017 medicine items that were claimed during 2005 and 2006 were included in the review. Descriptive statistics were used to describe the data, and were analysed using the Statistical Analysis System® SAS 9.1® programme. The cost prevalence index (CPI), developed by Serfontein (1989:180), was used as an indicator of the relative expensiveness of medicine. Resource- and activity driver products (cost driving products) were identified on the database by calculating the total cost of the product, the CPI of the product as well as the prevalence of the product. Variables for analysis included age, gender, prescriber and provider types. Resurts and discussion: A total number of 8 522 574 and 9 046 138 prescriptions were analysed, with an average of 2.33 ± 1.56 and 2.37 ± 1.58 items per prescription during 2005 and 2006 respectively. The average cost per prescription for the total database was R222.16 ± R463.13 for 2005 and R226.25 ± R557.49 for 2006. Members had to co-pay an average of R26.33 ± R102.70 per prescription in 2005 compared to R29.74 ± R103.96 per prescription in 2006. Children under the age of nine accounted for approximately 13% of the total study population, the adolescent age group < 9 and ≥ 19 years) represented 12%, age group three < 19 and ≥ 45 years) represented 38%, age group four < 45 and ≥ 59 years) represented 21% and the geriatric age group (patients older than 59 years) represented 16% of the total study population on the database. About 44% of the study population were male compared to 56% female patients. The top twenty trade name products ranked according to total cost represented about 13% (N=R1 893376 921.00 and N=R2 046 944382.50 in 2005 and 2006 respectively) of the overall medicine cost. The top five trade name products according to total cost for 2005 in descending order were Upitor 1 Omg and 20mg, Fosamax 70mg, Celebrex 200mg and Prexum 4mg. During 2006 the top five trade name products were similar except for Cipralex 10mg in the place of Celebrex 200mg. The CPls for all these products were above one; these products were also all activity drivers. The top twenty trade name products ranked according to prevalence represented about 11% (N=19 860679 and N=21 473074) of the total medicine prevalence for both study periods. The top five trade name products according to prevalence for both years contained Eltroxin 100mcg, Ecotrin 81 mg, Upitor 10mg and Alcophyllex syrup, with Myprodol capsules in 2005 and Mybulen tablets in 2006. Upitor 1 Omg was the only cost driver product in this list. General medical practitioners prescribed the largest quantity of medicine items and represented about 73% of all the medicine items on the database. The medicine prescribed by general medical prescribers accounted for 65% of the overall medicine expenditure on the database. Pharmacies can be seen as the main providers of medicine items. Pharmacies provided approximately 80% of the medicine items and represented over 91% of the total medicine expenditure. Cardiovascular agents were the main pharmacological group that represented the greatest percentage of the total medicine cost, about 19% in both study years. Cardiovascular agents were also positioned 1st according to prevalence and represented about 14% of the overall medicine prevalence in both the study periods. Conclusions and recommendations: Cost driver products can be seen as the products that drives medicine expenditure in the managed health care environment, thus driving the total cost of medicine treatment in the private health care sector of South Africa. Through the implementation of managed health care information- and management instruments medicine expenditure can be reduced. Recommendations for future research have been made.
dc.language.isoenen_US
dc.publisherNorth-West University
dc.subjectManaged health careen_US
dc.subjectManaged health care instrumentsen_US
dc.subjectGeneric and therapeutic substitutionen_US
dc.subjectDrug utilisation reviewen_US
dc.subjectMedicine prevalenceen_US
dc.subjectTotal medicine costen_US
dc.subjectCost driver productsen_US
dc.subjectResource driversen_US
dc.subjectActivity driversen_US
dc.titleAspects of drug usage in a section of the private health care sector of South Africa : A managed health care approachen
dc.typeThesisen_US
dc.description.thesistypeMastersen_US


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