PHARMACOECONOMIC STUDY RESULTS OF THE ACCESS

Open Access Research Journal, www.pieb.cz Medical and Health Science Journal, MHSJ ISSN: 1804-1884 (Print) 1805-5014 (Online) Volume 5, 2011, pp. 107-111 PHARMACOECONOMIC STUDY RESULTS OF THE ACCESS TO DRUGS AND TREATMENT AMONG PATIENTS WITH ALLERGIC RHINITIS IN UZBEKISTAN The paper discusses survey results made among 104 leading physicians of specialized offices with indication of forms and dose for drugs widely used for allergic rhinitis. The aim of the inquiry was carrying out VEN- analysis to define groups of drugs which efficacy should provide their more wide use in treatment of allergic rhinitis in near future. NIZOM SUYUNOV Tashkent Pharmaceutical Institute Uzbekistan Keywords: Allergic rhinitis, choice of drugs, expert evaluation, VEN-analysis. UDC: 616.211-002 Nowadays chronic rhinitis is one of the most wide-spread diseases of the man. About half of this disease forms are allergic rhinitis, the incidence of chronic rhinitis has risen in 1.5 times for the last two decades (Chernyac et al., 2002). The essential characteristic of allergic rhinitis, except high prevalence, is their association with bronchial asthma. The cause of close interconnection of allergic rhinitis and bronchial asthma is conditioned by common mechanism of allergic inflammation process in mucous membrane of upper and lower respiratory ways. This interconnection is also accustomed by various rhino bronchial interrelations such as bronchial hyper reactivity, being often detected at allergic rhinitis without any clinical manifestation of bronchial asthma (ARIA et al., 2001). Epidemiological studies showed that prevalence of allergic rhinitis is high (up to 40%); the disease symptoms in different populations vary from 1% to 39.7%, and there is a tendency of growth in last decades. Prevalence of allergic rhinitis in Uzbekistan varies from 12% to 24%. In treatment of these diseases the physicians very often make mistakes in prescribing effective drugs; this makes important determining the most effective drugs for treatment allergic rhinitis. Therefore, we carried out inquiry to select effective list of modern and the most effective and safe antiallergic drugs. The study data included material of various medical institutions in Uzbekistan 1. VEN-analysis was planned to determine priorities of selection and purchasing drugs according to their classification: vital and improving life quality drugs (Vital-V), necessary (Essential-E), secondary (Non-essential-N). The assignment of drugs to the appropriate classes was made through specific recommendations of highly skilled physicians (Kolenchic et al., 2007; Rasdorskaya et al., 2008). VEN-analysis was carried out by the way of expert evaluation. To do this, experts were suggested a questionnaire containing the names of drugs. Evaluation of drugs assumed 3-point scale method: 3 points were assigned to vital and improving quality of life drugs (medicines needed to save the life of patient, frequently taking to sustain life); 2 points - to essential drugs (drugs that are effective for the treatment of less hazardous, but serious illness); 1 point - to minor drugs (drugs for treatment of light diseases and having uncertain effectiveness, expensive drugs with symptomatic indications). 1 Republican Specialized Allergic Research Center, Republican Specialized Scientific Practical Medical Center in Phthisiatry and Pulmonology, Republican Specialized Scientific Practical Medical Rehabilitation, Ist Clinic of Tashkent Medical Academy, IInd Clinic of Tashkent Medical Academy, Main Department of Public Health in Tashkent city Khokimiya, Tashkent city Clinical Hospital of Emergency Medical Care, Main Department of Public Health in Tashkent City, Ibn Sino named Tashkent City Clinical Hospital. - 107 -

One of the study aims was to determine a competence level of specialists giving expert assessment of drug use efficacy. Intellectual data analysis methods were used for general estimation of the competence level of specialists in distributing drugs to VEN groups (Ignatyev et al., 2005; Ignatyev et al., 2003; Adilova et al., 2010). A problem was stated in calculating aggregated estimation parameters without evident measure units, such as severity of the disease, competency level, etc. (Kayshieva et al., 2009). In calculation of general estimators by methods of intellectual data analysis based on the technology of neuron networks, information was used from object-property tables. In our case objects were drugs, signs (features) - their classification given by experts in VENanalysis. Mathematic statement of the problem was formulated as following. The fixed set of objects E 0={S 1,,S m} contains representatives of two disjoint classes K 1, K 2. The objects were described using n nominal signs (features) (expert answers), each of those having 3 grades - 1. 2. 3 (according to VEN groups, respectively). The necessity of two-class recognition task solution is related to the fact that any general assessment of parameters is relative. Objects of each class are opposed to objects from the opposite class (for example, class represented by expert assessment of drugs by allergologists and pulmonologists, to that by therapists). For our case general estimator of object S was calculated by the formula: R ( S ) = n 1 2 = αij αij vi 1 K K 1 2 i 2 Where, α ij1, α ij - the number of j-th gradation of i-th sign (features) in the description of object S in classes K1 and K2, respectively; v i - weight determined by interclass difference and inner class similarity of i-th sign (features) values; K i - the number of objects in class, i = 1,2. K i The drugs were preliminary assigned to VEN groups taking into account graded assessment of experts (K 0 column, Table 2). Three independent experiments were carried out to calculate general estimator of drug assignment to class K 1 as opposite to class K 2, to assess the expert competence in classification. In the first experiment drugs from V group were classified into class K 1 with remaining ones into K 2. General estimator of assigning drugs to class K 1, presented in [0, 1] scale, is given in V column of Table 2, where 1 denotes absolute assignment of the drug to the class. In the second and third experiments drugs of E and N groups were classified to class K 1 (E and N columns, Table 2). For carry out VEN-analysis of drugs the inquiry was developed, and the permission from Ministry of Public Health was received on distribution inquiries among physicians specialists. Corresponding specialists of medical institutions were given 104 inquiries; 36 of them were noted as non-satisfactory and were redesigned with follow-up distribution among the medical specialists. 23 allergologists, 13 otolaryngologists, 44 pulmonologists, 24 therapeutists were engaged in treatment allergic rhinitis, and they filled all categories in 104 inquiries (Table 1). Their distribution according to work experience in specialty was the following: specialists having work experience from 10 to 20 years made 29.81%, from 20 to 30 years - 24.04%, more 30 years - 8.65%. Physicians having high professional category made 55.77%, those having scientific degrees (candidates of medical sciences) comprised 20.19%. - 108 -

TABLE 1. CHARACTERISTICS OF EXPERTS-PHYSICIANS AND EVALUATION OF INDICES IN SCORES Characteristics of experts Index Number of experts abs % Scores Profile of specialty allergologist 23 22.11 20 otolaryngologists 13 12.50 15 pulmonologist 44 42.31 10 therapeutist 24 23.08 5 Work experience in Public Health (years) Work experience in speciality (years) to5 years 9 8.65 1 from 5 to 10 years 19 18.27 2 from 10 to 20 years 28 26.92 3 from 20 to 30 years 30 28.85 4 more 30 years 18 17.31 5 to 5 years 16 15.38 4 from 5 to 10 years 23 22.12 8 from 10 to 20 years 31 29.81 12 from 20 to 30 years 25 24.04 16 more 30 years 9 8.65 20 Qualification category high 58 55.77 10 first 18 17.31 8 second 2 1.92 6 without category 26 25.00 4 Academic degree doctor of medical sciences 6 5.77 15 candidate of medical 21 20.19 5 sciences without degree 77 74.04 1 Academic rank professor 7 6.73 20 docent 7 6.73 10 without rank 90 86.54 1 Level of getting acquainted with AR Certification practical experience 25 24.04 2 practical experience and theoretical knowledge on drugs 79 75.96 5 specialists with the 93 89.42 3 certificate without certificate 11 10.58 1 Practical experience and theoretical knowledge on drugs had 75.96% of physicians, certificate was available at 89.42% specialists. Using category criterion the competence of specialists was evaluated (Kayshieva et al., 2009; Suyunov et al., 2006). Objective and subjective opinions of main allergologists and specialists with the experience were also considered during the observation. 104 inquiries were processed by intellectual method and all survey data were analyzed. Table 2 suggests the generalized estimation of drugs placed to one or another group. Using the maximum principle the redistribution of drugs to VEN groups was carried out. As it is seen from processed data, 23 drugs (51.11%) were in group V, 12 (26.67%) - in group E, 10 (22.22%) - in group IV (column Kr, Table 2). From the drugs using for treatment of allergic rhinitis 12 were attributed to group V; among them glucocorticoid means such as Nasonex, Nasobek, Flutinex. It was revealed that the drugs as spray and tablets are the most effective at treatment allergic rhinitis. The essential group of drugs (group E) made 18 drugs, that was a high index. Among them such drugs as Vibrocil, Diasolin, Loratadin, Dexametason had particularly high index. The secondary drugs (group N) had 15 names, among them: Polcortolon, Solu-Medrol, Metipred, Dexametason. - 109 -

International names TABLE 2. OPTIMUM LIST OF DRUGS FOR ALLERGIC RHINITIS Trade names of drugs packing dosage, Drug forms VEN experiments R(C) K0 V-E,N E-V,N N-V-E Kr Pharmacotherapeutic group Glucocorticoid means Mometasone Nasonex 50 mgr, 120 doses spray V 1.00 0.00 0.19 V Beklometazon Nasobek 50mkg/1 dose, 200 doses spray V 0.99 0.02 0.10 V Fluticasone Flutinex 50 mkg /dose, 120 doses spray V 0.68 0.40 0.28 V propionate Flutinex 50 mkg/dose, 120 doses spray V 0.67 0.39 0.22 V Dexametason Dexametason 0.4% 2 ml 10 sol. for inj. E 0.17 0.89 0.61 E Dexametason-Darnitsa 0.4% 1 ml 5 sol. for inj. E 0.18 0.82 0.58 E Dexametason 0.5 mgr 10 sol. for inj. E 0.12 0.81 0.74 E Dexametason phosphate 0.4% 1ml 10 sol. for inj. V 0.28 0.79 0.49 E Dexametason 0.4% 1 ml 5 sol. for inj. E 0.25 0.76 0.55 E Prednisolon 30 mgr/ml, 1 ml 3 sol. for inj. E 0.16 0.68 0.64 E Beklometazon Aldecin 50mkg/dose, 200 doses aerosol V 0.38 0.59 0.46 E Triamcinolone Polcortolon 4mgr 50 tabl. N 0.07 0.49 1.00 N Methylprednisolone Solu-Medrol 500mgr, 7.8 ml sol. for inj. N 0.15 0.40 0.99 N Solu-Medrol 125 mgr/1ml sol. for inj. N 0.17 0.36 0.98 N Methypread 4 mgr 30 tabl. N 0.10 0.49 0.95 N Sotu-Medrol 40mgr/1ml sol. for inj. N 0.14 0.52 0.88 N Dexametason Dexametason - GT 0.4% 1ml 5 sol. for inj. N 0.30 0.37 0.82 N Dexametason - 4mgr/m/ 1ml 25 sol. for inj. N 0.41 0.32 0.66 N Prednisolon Prednisolon5 mgr 100 tabl. N 0.10 0.53 0.89 N Prednisolon 0.005 gr 10 tabl. N 0.11 0.52 0.89 N Prednisolon Nikomed 25mgr/l 50 sol. for inj. E 0.11 0.70 0.74 N Cetirizin Analegin 10mgr 30 tabl. V 0.84 0.37 0.00 V Analegin 10 mgr 10 tabl. V 0.83 0.34 0.09 V Cetirinax 10 mgr 10 tabl. V 0.77 0.41 0.13 V Loratadin Lomilan 10 mgr 10 tabl. V 0.81 0.23 0.24 V Claritin 10 mgr/ml 10 tabl. V 0.71 0.,34 0.,24 V Claritin 1 mgr/ml120 ml syrup V 0.69 0.42 0.22 V Loratal 10 mgr/ml 10 tabl. V 0.65 0.52 0.16 V Liofilisat bacterium Cromoglin 20 mgr/ml, 15ml spray V 0.66 0.37 0.36 V Mebhydrolin Diasolin 0.05 gr 20 liqueur bonb-s E 0.00 0.92 0.63 E Diasolin 0.1 gr 10 tabl. E 0.10 0.79 0.61 E Loratadin Loratadin CMP 0.01 gr 10 tabl. V 0.44 0.94 0.03 E Loratadin 0.01 gr 10 tabl. V 0.49 0.88 0.03 E Loratadin 10 mgr 100 tabl. V 0.54 0.82 0.02 E Lord 10 mgr 2 tabl. V 0.49 0.75 0.19 E Dimetindenmaleat Fenistil 0.1% 20ml drops E 0.23 0.78 0.55 E Histoglobulin dry Histoglobulin dry 1 dose 5 lyoph. for inj. E 0.46 0.64 0.33 E Chloropyramin Suprastin 20 mgr 1x5ml sol. for inj. V 0.36 0.59 0.45 E Klemastin Tavegil 1mgr 20 tabl. N 0.03 0.71 0.81 N Tavegil 1mgr ml2ml 5 sol. for inj. N 0.06 0.70 0.71 N Chloropyramin Suprastin 25 mgr 20 tabl. V 0.31 0.47 0.65 N Ketotifen Ketotifen 1m gr tabl. V 0.36 0.46 0.59 N Ketotifen 0.001 30 tabl. V 0.46 0.30 0.57 N Dimetinden maleat, Vibrocil 10 ml spray E 0.18 1.00 0.43 E phenylefrin Note: combined drugs; solution for injection; lyophilized for solution of injections (bottles); in set with water dilution for injections 7.8 ml, 15.6 ml (bottles). - 110 -

TABLE 3. PHYSICIANS COMPETENCY LEVEL VEN-analysis, experiments Physicians competency {K1} {K2} Middle (0.5- Non High (0.7-1) Low (<0.5) 0.7) competency (0) Specialists Allergologists abs % Abs % abs % abs % {V} {E,N} 12 52.18 5 21.74 5 21.74 1 4.34 {E} {V,N} 3 13.05 5 21.74 14 60.87 1 4.34 {N} {V,E} - - 3 13.05 18 78.26 2 8.69 Otolaryngologists {V} {E,N} 2 15.38 4 30.77 7 53.85 - - {E} {V,N} 5 38.46 5 38.46 3 23.08 - - {N} {V,E} - - 2 15.38 11 84.62 - - Pulmonologists {V} {E,N} 22 50.00 10 2.73 11 25.00 1 2.27 {E} {V,N} 10 22.73 9 20.45 24 54.55 1 2.27 {N} {V,E} 2 4.55 5 11.36 33 75.0 4 9.09 Therapists {V} {E,N} 14 58.34 8 33.33 2 8.33 - - {E} {V,N} 1 4.17 7 29.17 16 66.6 - - {N} {V,E} - - 35 12.50 18 75.00 3 12.50 Using competence evaluation data (Table 3) the following describes the participated physicians. Particularly, allergologists could be considered as high competitive specialists in attributing drugs to group V - their percentage was 52.18%; also, therapists (58.34%), pulmonologists (50%) and otolaryngologists (15.38%) could be considered as qualified experts in assigning drugs to group V. Allergologists performed as low competitive specialists in classifying group E drugs - their share made 60.87%, and group N drugs (78.26%). In attributing drugs to groups E and N, low competency indexes were assigned to otolaryngologists (23.08% and 84.62%, correspondingly), pulmonologists (54.55% and 75%), therapists (66.66% and 75%). References Adilova, F., Madrahimov, Sh., 2010. The Approach to individualized teleconsultations of patients with arterial hypertension, Global Telemedicine and e Health Updates Knowledge Resources, Vol.3, pp.372-76. ARIA, 2001. Allergic rhinitis and its influence on bronchial asthma, Allergology [Allergologija], in Russian, No.3, pp.43-56. Chernyac, B., Tyarenkova, S., Buynova, S., 2002. Allergic rhinitis in Eastern Siberia: Prevalence, etiological characteristics and interconnection with bronchial asthma in different age groups, Allergology [Allergologija], in Russian, No.2, pp.3-9. Ignatyev, N., 2005. About factors synthesis in artificial neurons nets, Computer technologies [Vichisliteljnie tehnologii], in Russian, Тashkent, No.3, pp.32-38. Ignatyev, N., Madrahimov, Sh., 2003. About some ways of raise transparency of neurons nets Computer technologies [Vichisliteljnie tehnologii], in Russian, Тashkent, No.6, pp.31-37. Kayshieva, N., Kayshieva, S., Fyodorova, L., Luzic, E., Telitsin, V., Hachatryan, M., 2009. Improvement of drug supply patients with mental diseases, New drug store [Novaya Apteka], in Russian, No.5, pp.54-62. Kolenchic, O., Bredneva, N., Zevakova, V., 2007. Pharmacoeconomic study of drug supply patients with multiple sclerosis, Pharmacy [Farmacija], in Russian, No.6, pp.23-25. Rasdorskaya, I., Filina, I., 2008. Оptimization of drug supply medical prophylactic offices in Orlov region, Pharmacy [Farmacija], in Russian, No.4, pp.41-42. Suyunov, N., 2006. Expert evaluation of drugs quality at treatment of bronchial asthma, Medical journal of Uzbekistan [Uzbekiston tibbiyot jurnali], in Uzbek, No.5, pp.49-52. - 111 -