Jurnal Teknologi USING ASSOCIATION RULES TO STUDY PATTERNS OF MEDICINE USE IN THAI ADULT DEPRESSED PATIENTS. Full Paper

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1 Jurnal Teknolog USING ASSOCIATION RULES TO STUDY PATTERNS OF MEDICINE USE IN THAI ADULT DEPRESSED PATIENTS Chumpoonuch Sukontavaree, Verayuth Lertnattee * Faculty of Pharmacy, Slpakorn Unversty, Nakhon Pathom, 73000, Thaland Full Paper Artcle hstory Receved 16 June 2015 Receved n revsed form 17 September 2015 Accepted 18 December 2015 *Correspondng author verayuths@hotmal.com Graphcal abstract Abstract Depresson s a mental dsorder whch s characterzed by feelng of gult, sucdal tendences and dsturbed bodly functons. In 2002, depresson s ranked as the fourth of dsease burden n worldwde and t wll be changed to the second rank n Furthermore, more than 350 mllon people worldwde suffer from depresson. Clncan staffs must take care of patents closely because these patents have medcaton adherence problem. To allevate ths problem, an adherence tranng program s ntroduced. Due to the lmtaton of budget and clncal stuffs, t s hard to educate all depressed patents. To deal wth ths problem, a method for fndng rules of medcne use s proposed n three steps, The frst step s fndng the commonly used medcnes wth ther adherences. In the second step, two groups of patents are classfed,.e., adherence and non-adherence groups for each commonly used medcnes. For the last step, assocaton rules are appled on each group of patents. From results, fluoxetne s a popular medcne for treatment depresson. The numbers of medcnes for a non-adherent group are more than those of an adherent group. Several patterns of drug nteractons are found. These patterns should be reported to clncal staffs. In concluson, results from the proposed method are appled for selectng a set of patents and drugs, whch are flled n the adherence tranng program. Keywords: Assocaton rules, data mnng, depressed, adherence, medcne 2016 Penerbt UTM Press. All rghts reserved 1.0 INTRODUCTION Depresson s a mental dsorder whch characterzed by feelng of gult, sucdal tendences and dsturbed bodly functons. Furthermore, these persst for weeks [1]. Depresson may be caused by decreased level of the neurotransmtters whch are norepnephrne (NE), serotonn (5-HT), and dopamne (DA) n bran [2]. In present tme, depressed patents have more than 350 mllon people worldwde. Depresson s one of the major causes of the one mllon sucdes commtted every year [3]. In 2002, the depresson ranked fourth n the burden of dseases worldwde. It s predcted that by 2030, t wll rank second [4]. In Thaland, depresson ranked thrd for burden of dseases n women and tenth n men as the cause loss of dsablty adjusted lfe years (DALYs) [5]. One of the major problems for treatment of depresson s medcaton adherence. Odds are three tmes greater than a depressed patent wll become medcaton non-adherent than ther non-depressed counterparts [6]. Accordng to the Tha medcal database, depressed patents classfed as medcaton adherent patents, are only 23 percent [7]. Ths s an extremely mportant ssue because f patents don t take ther medcne as prescrbed, ther dsease wll most certanly escalate. Consequently, t becomes ncreasngly dffcult for ther physcans and clncal staffs to manage ther llness effectvely. To allevate ths problem, an adherence tranng program, whch s crtcally mportant for non-adherent patents, needs to be 78:5 6 (2016) eissn

2 102 Chumpoonuch Sukontavaree & Verayuth Lertnattee / Jurnal Teknolog (Scences & Engneerng) 78:5 6 (2016) mplemented. Due to budget constrants and lmted clncal staffs, not all depressed patents can be educated at ths tme. Ths research proposes a method for fndng rules of medcne use n depressed patents accordng to ther medcaton adherence. To fnd patterns of medcne use, the assocaton rule technque, a data mnng technque s usually used. The patterns of drug tems, used for treatment were collected and analyzed. The results can be used to mplement an adherence tranng program for a set of patents and drugs. In the rest of ths paper, medcnes n depressed patents, assocaton rules, fndng patterns of medcne use by assocaton rules, expermental settngs and expermental results, as well as concluson and future work are gven n detal. 2.0 EXPERIMENTS 2.1 Background Medcnes n Depressed Patents In ths secton, some groups of medcne used for depressed patents, are descrbed. The detal of man groups s descrbed as follow. Selectve serotonn reuptake nhbtors (SSRIs) nhbt the reuptake of 5-HT nto the presynaptc neuron. They are generally chosen as frst-lne antdepressants because of ther safety n overdose and mproved tolerablty compared to earler agents. Examples of medcnes for ths group are fluoxetne, sertralne and esctalopram [2]. Trcyclc antdepressants (TCAs) such as amtrptylne, mpramne and nortrptylne are effectve for all depressve subtypes, but ther use has dmnshed because of the avalablty of equally effectve therapes that are safer on overdose and better tolerated [2]. Tetracyclc antdepressants such as mansern are potent alpha-2 adrenoceptor antagonsts whch cause an enhanced release of noradrenalne [1]. The trazolopyrdnes, e.g., trazodone and nefazodone, are antagonsts at the 5- HT2 receptor and nhbt the reuptake of 5-HT. They can also enhance 5- HT1A neurotransmsson [2]. Depressed patents may use other medcnes because they may have assocated wth anxety and/or psychotcs symptoms. These medcnes are perphenazne, haloperdol, chlorpromazne, rsperdone, amobarbtal, flupentxol and meltracen. Due to varous medcnes can be appled on a patent, drug nteractons may be occurred. For example, the treatment of patents by fluoxetne and amtrptylne, ncreases rsk of toxcty from trcyclc antdepressants (ncrease causng an abnormal heart rhythm) Assocaton Rules Assocaton rule learnng, a data mnng technque, s a popular and well researched method for fndng patterns of nterestng assocatons and correlatons between tem sets n large databases. The result from assocaton rules found the trend of data whch s used to plan project or strategy. Medcal research works develop mnng technques on assocaton rule learnng such as [10, 11]. Assocaton rules have an assocated confdence and support for a rule. Rule confdence s condtonal probablty of one nterestng focus. The support for a rule s mnmum percentage n database. There are crtera to flter nterestng data or mpact data [8]. Ths s a two-step process. The frst step s tem set generaton. The rule create s not less than mnmum rule confdence. Next step, assocaton rules generated relatonal data between frst rule and second rule. The rules have percentage of change not less than mnmum support rule [8]. In ths paper, a set of medcnes for depressed patents s consdered as a set of tems. For example, a prescrpton for treatment a depressed patent, fluoxetne also tends to assocate wth perphenazne. Ths can be represented n assocaton rule below: Fluoxetne Perphenazne [support=20%, confdence=80%] A support of 20% ndcates that 20% of all the transactons n all prescrpton suggest that both fluoxetne and perphenazne are found together. A confdence of 80% means that 80% of the total number of prescrpton whch s composed of fluoxetne, s also found perphenazne. In ths research, a set of rules generated on both adherent and non-adherent patents, provdes useful knowledge for each group of patents. These can be used to set adherence tranng programs for depressed patents. A set of medcnes whch s caused problems or drug nteracton, s ncluded n the tranng program. 2.2 Expermental Settngs The ncluson crtera for selectng patents and medcnes were as follow. I. Patents were outpatents of Somdet Chaopraya Insttute of Psychatry who vsted more than one tme. II. Patents were Tha depressed patents who were dagnosed depresson usng Internatonal Classfcaton of Dseases, Tenth Edton Tha Modfcaton (ICD-10TM) codes as F32 (Depressve epsodes), F33 (Recurrent depressve dsorder) and F34.1 (Dysthyma). III. Patents were receved manly medcnes for treatment depressed patents whch were groups of natonal lst of essental medcnes 2011 as antpsychotc drugs, antmanc drugs and 4.3 antdepressant drugs. Moreover, there were tablets and capsules and method of medcne use n prescrptons were not prn. (pro re nata, when necessary for)

3 103 Chumpoonuch Sukontavaree & Verayuth Lertnattee / Jurnal Teknolog (Scences & Engneerng) 78:5 6 (2016) IV. Number of medcnes was not more than 10% of medcaton possesson. Ths study was retrospectve cross sectonal descrptve study used electronc medcal record from a database of the Somdet Chaopraya Insttute of Psychatry, Thaland durng the perod between June 10, 2004 and August 14, Ths ncluded 7,346 depressed outpatents. However, 2,834 depressed outpatents were selected accordng to the ncluson crtera. For medcnes, the total numbers of medcnes were 40 tems. Data of medcnes and patents are recorded n a database whch s constructed by PostgreSQL, open source database management software and PHP language s used for calculatng medcaton and patent adherences. Assocaton rules of medcne use were analyzed by apror technque. 2.3 Fndng Patterns of Medcne Use by Assocaton Rules In order to apply assocaton rule fndng medcne usng patterns, two lsts of transactons of medcne use are generated. The frst lst s the transactons of adherent patents and the other one s for nonadherent patents. To classfy a patent nto adherent and non-adherent group, the method for calculatng MPR from a database of medcne use, s proposed. The apror method s presented to fnd patterns of medcne use n both adherent and non-adherent depressed patents. Adherence: Data of medcne uses from database were calculated adherence by Medcaton Possesson Rato (MPR). The MPR method was approprate measurng adherence for long-term treatment medcatons. The MPR can be calculated wth ths equaton (MPR = Number of days suppled wthn refll nterval/number of days n refll nterval). The concept of MPR n our proposed method can be represented n the equaton 1. NM 1 when the s 0. 8 MPR rato (1) ND 0 when the rato s 0.8 Here, the MPR of the th medcne for the j th patent s defned as the number of days suppled the th medcne for the j th patent (NM)/ the number of treatment day for the th medcne for the j th patent (ND). In ths paper, a medcne s a sets of drug wth same generc names for all strengths. For example, two strengths are avalable for Fluoxetne,.e., 20 mg. and 40 mg. These two strengths are grouped as the same medcne. If the value of the rato n the equaton 1 s greater than or equal to 0.8, the MPR s set to 1. On the opposte, when the value of the rato s less than 0.8, the MPR s set to 0. Wth the MPR, two types of adherence are proposed n the papers,.e., medcaton adherence by patent and medcaton adherence by medcne. The detal of each type of adherence s descrbed. Measurng Medcaton Adherence by Patent (MA-P): Ths s the rato of medcaton possesson by equaton 1 from all medcnes for a patent to the number of medcnes whch were taken by the patent. The MA- P can be represented n the equaton 2. MA MPR Pj (2) TM j Here, MA-Pj s the medcaton adherence of the j th patent and TMj s the total number of medcnes that were taken by the j th patent. If the value of MA-Pj s greater than or equal to 0.8, the j th patent s accepted as a medcaton-adherent patent. MA M j MPR TP (3) Here, MA-M s the medcaton adherence of the th medcne and TP s the total number of patents who took the th medcne. If the value of MA-M s greater than or equal to 0.8, the th medcne s accepted as the drug s a medcaton-adherent medcne. The patterns of medcne use of these two groups (adherent and non-adherent patents) are analyzed by an assocaton rules technque. Assocaton Rules: The lsts of medcne uses for each vst of patents for both groups,.e., adherent and non-adherent patents, are used. The apror algorthm, whch s the standard algorthm for assocaton rule s appled n the work. Due to the varetes of medcnes use for depressed patents, the value of support s set to 10%. 3.0 RESULTS AND DISCUSSION 3.1 Commonly Used Medcnes n Depressed Patents In the frst step, the percentages of medcaton adherence by medcne were calculated from data n the database usng equaton 1 and 3. The top ten most commonly used medcnes are sorted by ther supports n descendng order. The result s shown n Table 1. From the result, some observatons can be made. Medcnes use n some depressed patents, were not only antdepressants but also antpsychotcs, e.g., amtrptylne and perphenazne. The top ranked common medcnes used n depressed patents were fluoxetne (49.75%), amtrptylne (23.82%), perphenazne (15.81%) and mansern (14.57%). The percentages of adherence for these medcnes were 48.23%, 52.30%, 41.52% and 54.00%, respectvely. The result suggests that the group of medcnes whch s the most commonly used group s Selectve Serotonn Reuptake Inhbtors (SSRIs), e.g., fluoxetne, sertarne and esctalopram. The most commonly used medcne s fluoxetne whch obtaned low percentage of medcaton adherence. In contrast,

4 104 Chumpoonuch Sukontavaree & Verayuth Lertnattee / Jurnal Teknolog (Scences & Engneerng) 78:5 6 (2016) sertralne s more advantage than fluoxetne and esctalopram n term of medcaton adherence. Therefore, sertralne may be consdered for treatment of choce on depressed patents who had adherence problem. Moreover, a set of tranng program for applyng these medcnes should be set for depressed patents. Average of medcaton tems use were 1.50 tems for adherent group and 2.08 tems for non-adherent patents. Ths suggests that non-adherent patents have taken medcnes more than those of adherent patents. Table 1 The top ten commonly used medcnes sorted by ther supports No. Generc name Percentage of support (%) Percentage of adherence (%) 1 Fluoxetne Amtrptylne Perphenazne Mansern Trazodone Haloperdol Nortrptylne Impramne Sertralne Esctalopram Table 2 The results of assocaton rules by medcne adherence s group Rule No. DI sg. ratng Assocated medcne 1 2 Amtrptylne Fluoxetne (21.9, 29.9) 2 2 Fluoxetne Amtrptylne (46.9, 62.1) 3 1 Trazodone Fluoxetne (15.3, 19.0) 4 2 Nortrptylne Fluoxetne (12.5, 14.8) 5 2 Impramne Fluoxetne (<10.0, 11.4) 6 1 Trazodone, Fluoxetne Amtrptylne (<10.0, 13.9) 7 1 Trazodone, Fluoxetne Perphenazne (11.8, 16.1) 8 1 Trazodone, Fluoxetne Mansern (10.0, 21.0) 9 2 Impramne, Fluoxetne Perphenazne (<10.0, 10.4) 10 2 Impramne, Fluoxetne Mansern (<10.0, 10.0) 11 2 Nortrptylne, Fluoxetne Perphenazne (<10.0, 11.5) 12 2 Nortrptylne, Fluoxetne Mansern (<10.0, 12.6) 13 1 Cholrpromazne, Fluoxetne Perphenazne (<10.0, 13.2) 3.2 Fndng Patterns of Medcne Use n Depressed Patents. In the second step, four medcnes from Table 1,.e., fluoxetne, amtrptylne, perphenazne and mansern have supports greater than 10%. Therefore, patterns of medcne usage of these four medcnes were dvded nto two groups based on calculaton from equaton 1 and 2,.e., adherent patents group and non-adherent patents group. Transactons of medcne use for each group were analyzed by apror algorthm n the last step. Assocated medcnes caused of drug nteracton ratng (DI sg. rate) 1 and 2 wth these four medcnes are shown n Table 2. The percentage of supports for adherent patents group and non-adherent patents group, are presented n parenthess, respectvely. From the result n Table 2, these patterns have the support of non-adherent group more than adherent group. Moreover, the popular assocated medcne was fluoxetne. Serous drug nteractons (sgnfcance ratng 1, rsk of death) are found, e.g., fluoxetne assocated wth trazodone as well as fluoxetne and chlorpromazne assocated wth perphenazne. The most popular pattern of assocated medcnes whch s the cause of drug nteracton sgnfcance ratng 1 s Trazodone Fluoxetne. These have support values of 15.3% and 19.0% n adherent and non-adherent patents, respectvely. Ths means depressed patents who are good adherence uses trazodone assocated wth fluoxetne. Ths rule occurs 15.3% from patents who use fluoxetne. These patterns appears 19.0% from patents who use fluoxetne n non-adherent patents. Although fluoxetne and chlorpromazne assocated wth perphenazne does not frequently use, t should be aware because the serous drug nteract may occur. If patents take these medcnes together, clncal staffs should montor closely. 4.0 CONCLUSION Due to the lmtaton of budget and clncal stuffs, t was hard to educate all depressed patents to apply ther medcne effectvely. A set of methods for constructng an adherence tranng program was ntroduced n ths paper. In the frst step, a method for

5 105 Chumpoonuch Sukontavaree & Verayuth Lertnattee / Jurnal Teknolog (Scences & Engneerng) 78:5 6 (2016) fndng medcaton adherence by medcnes was used. From ths step, a set of medcnes commonly used n depressed patents wth ther percentage of ther medcaton adherences were nvestgated and selected. In the next step, patents were classfed nto two groups usng medcaton adherence by patents,.e., adherent group and non-adherent group for each commonly used medcne. In the last step, a method for fndng rules of medcne use n non-adherent patents was appled. From the results, Tha adult depressed patent s low adherence. Fluoxetne s the most popular assocated medcne. Numbers of medcnes from non-adherent group were more than those of adherent group. Several drug nteractons among medcnes for treatment depressed patents were found. Some patterns of medcne use can cause severe drug nteractons and these should be concerned. The tranng program about common medcnes whch are obtaned low percentage of medcaton adherence by medcnes should be set wth hgh prorty, especally n non-adherent patents. Ths tranng program wll mprove patent adherence, effectve of treatment, patent s safety and reduce cost of treatment. In ths paper, a support s the man parameter to select a set of medcnes and assocaton rules. For future work, other parameters, e.g., confdence and lft, should be appled. Acknowledgement References [1] Leonard, B Fundamentals Of Psychopharmacology. Thrd Edton. Wley. [2] Wells, B., J. Dpro, T. Schwngnammer, and C. Dpro Pharmacotherapy Handbook. Seventh edton. The Mcgraw-hll. [3] World health organzaton. [Onlne]. From: on/defnton/en/. [Acessed on 5 March 2012]. [4] Mathers, C., and D. Loncar Projectons Of Global Mortalty And Burden Of Dsease From 2002 To Plos Medcne. 3: [5] Bundhamcharoen, K., O. Patarapan, S. Phulkerd, and V. Tangcharoensathen Burden Of Dsease In Thaland: Changes In Health Gap Between 1999 And Journal of Bomed Central. 11: 1-9. [6] DMatteo, M., H. Lepper, and T. Croghan Depresson Is A Rsk Factor For Noncomplance Wth Medcal Treatment: Meta-Analyss Of The Effects Of Anxety And Depresson On Patent Adherence. Journal of Archves of Internal Medcne. 160: [7] Prukkanone, B., T. Vos, P. Burgess, N. Chayakunapruk, and M. Bertram Adherence To Antdepressant Therapy For Major Depressve Patents In A Psychatrc Hosptal In Thaland. Journal of Bomed Central. 10: 1-5. [8] Roger, R., and M. Geatz Data Mnng A Tutoral Base Prmer. Addson Wesley. [9] Suh, S Practcal Applcatons Of Data Mnng. Texas: A&M Unversty. [10] Chen, Y., L. Pedersen, and W. Chu Drug Exposure Sde Effects from Mnng Pregnancy Data. Journal of Sgkdd Exploratons. 9: [11] Ta, Y., and H. Chu Comorbdty Study of ADHD: Applyng Assocaton Rule Mnng (ARM) to Natonal Health Insurance Database of Tawan. Journal of Medcal Informatcs. 78: Ths research s partally supported by Faculty of Pharmacy and Graduate of Slpakorn Unversty as well as the Research and Creatve Fund, Faculty of Pharmacy, Slpakorn Unversty.