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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (1): 99-108    DOI: 10.11925/infotech.2096-3467.2017.0946
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Optimizing Layouts of Outpatient Pharmacy Based on Association Rules
He Yue, Wang Aixin(), Feng Yue, Wang Li
Business School, Sichuan University, Chengdu 610065, China
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Abstract  

[Objective] As the number of outpatient visits increases, optimizing the layout of pharmacy drugs can improve its service efficiency. [Methods] Firstly, we chose two departments with the largest number of prescriptions, which were divided into four sub groups with the K-means clustering method. Then, we used Apriori algorithm to explore the association rules among them. Finally, we obtained 31 effective drug layout rules and 18 effective drug class rules. [Results] We designed general layout rules for prescription drugs based on the collected data along with national drug storage and display standards, which were approved by the experts. [Limitations] We only studied prescription records from two departments, which might not yield the best association rules. [Conclusions] The proposed method could reduce the workload of pharmacists and the waiting time of patients, which improve the pharmacy services.

Key wordsAssociation Rule      Cluster Analysis      Pharmacy      Layout Optimization     
Received: 18 September 2017      Published: 05 February 2018
ZTFLH:  TP399  

Cite this article:

He Yue,Wang Aixin,Feng Yue,Wang Li. Optimizing Layouts of Outpatient Pharmacy Based on Association Rules. Data Analysis and Knowledge Discovery, 2018, 2(1): 99-108.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.0946     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I1/99

药品编号 120209Abm3010 140108Aiv1690 110101Abk1605 120502M811682
120209Abm3010 0 493 412 2490
140108Aiv1690 493 0 66 465
…… …… …… …… ……
110101Abk1605 412 66 0 218
120502M811682 2490 465 218 0
第1类 第2类 第3类 第4类
第1类 16.252 0.047 0.085 0.041
第2类 0.047 12.301 0.006 0.002
第3类 0.085 0.006 12.376 0.004
第4类 0.041 0.002 0.004 12.338
规则
ID
后件 前件 前件支持度
(%)
置信度
(%)
规则支持度
(%)
1 020207A532305 = 1 110101Abk1605=1 and 120209Abm3010 = 1 1.559 94.581 1.474
2 020207A532305 = 1 110101Abk1605 = 1 4.362 92.782 4.047
3 120209Abm3010 = 1 140103A180151 = 1 1.014 73.485 0.745
4 090123M092310 = 1 040266AAU0186 = 1 and 150304MCX2705 = 1 1.014 69.318 0.703
5 120209Abm3010 = 1 150403Abo1655 = 1 and 020207A532305 = 1 1.286 68.060 0.875
6 120209Abm3010 = 1 140234A568418 = 1 and 120502M811682 = 1 1.425 66.038 0.941
7 090140A4421AV = 1 090128M0907CE = 1 1.375 63.966 0.879
8 120209Abm3010 = 1 140234A182363 = 1 and 120502M811682 = 1 2.607 63.918 1.666
9 120209Abm3010 = 1 150403Abo1655 = 1 and 120502M811682 = 1 2.964 63.860 1.893
10 120502M811682 = 1 090140A4421AV = 1 and 120209Abm3010 = 1 3.390 61.608 2.089
11 120209Abm3010 = 1 150403Abo1655 = 1 6.385 60.794 3.882
12 040303Abd16Ae = 1 160002A951451 = 1 1.317 60.058 0.791
13 2704CEM172120 = 1 2704bnK251626 = 1 1.421 58.760 0.837
14 160002A951451 = 1 040303Abd16Ae = 1 1.363 58.028 0.791
15 090123M092310 = 1 040266AAU0186 = 1 and 270462Afk0612 = 1 1.490 57.216 0.852
16 120209Abm3010 = 1 090140A4421AV = 1 and 120502M811682 = 1 3.717 56.198 2.089
17 040271Abd2045 = 1 270462Afk0612 = 1 and 120502M811682 = 1 2.020 55.133 1.114
18 150304MCX2705 = 1 040281M252912 = 1 2.861 54.497 1.559
19 120209Abm3010 = 1 150403Abs1655 = 1 and 120502M811682 = 1 2.020 52.281 1.056
20 020207A532305 = 1 040271Abd2045 = 1 and 120209Abm3010 = 1 1.286 51.940 0.668
21 040266AAU0186 = 1 090123M092310 = 1 and 270462Afk0612 = 1 1.651 51.628 0.852
22 120209Abm3010 = 1 120502M811682 = 1 18.572 50.941 9.461
23 120502M811682 = 1 150403Abs1655 = 1 and 120209Abm3010 = 1 2.100 50.274 1.056
规则 ID 后件 前件 前件支持度 (%) 置信度 (%) 规则支持度 (%)
1 030202BIO2547 = 1 070501B800493 = 1 1.766 100.000 1.766
2 070501B800493 = 1 030202BIO2547 = 1 2.027 87.097 1.766
3 160011B240270 = 1 160011B250270 = 1 3.466 73.585 2.551
4 140105A742341 = 1 140106A141815 = 1 1.112 70.588 0.785
5 010109MCE1231 = 1 010304A560403 = 1 1.766 70.370 1.243
6 010202A181696 = 1 090559A262552 = 1 2.158 63.636 1.373
7 160011B250270 = 1 160011B240270 = 1 4.971 51.316 2.551
规则
ID
后件 前件 前件支持度
(%)
置信度
(%)
规则支持度
(%)
1 抗肿瘤药 = 1 血液系统药物 = 1 and
镇痛、解热、抗炎、抗痛风药 = 1
2.164 75.804 1.640
2 镇痛、解热、抗炎、抗痛风药 = 1 调节水盐、电解质及酸碱平衡药 = 1 1.710 73.233 1.252
3 维生素矿物质类及肠内肠外营养药 = 1 激素类及影响内分泌药物 = 1 and
消化系统药物 = 1
6.963 62.986 4.386
4 抗肿瘤药 = 1 血液系统药物 = 1 and 消化系统药物 = 1 1.592 62.069 0.988
5 抗肿瘤药 = 1 血液系统药物 = 1 and
激素类及影响内分泌药物 = 1
2.892 59.367 1.717
6 激素类及影响内分泌药物 = 1 心血管系统药物 = 1 and
维生素矿物质类及肠内肠外营养药 = 1
1.735 59.072 1.025
7 维生素矿物质类及肠内肠外营养药 = 1 激素类及影响内分泌药物 = 1 25.366 58.724 14.896
8 抗肿瘤药 = 1 血液系统药物 = 1 7.358 57.761 4.250
9 抗肿瘤药 = 1 血液系统药物 = 1 and 免疫系统药物 = 1 1.651 56.984 0.941
10 中成药 = 1 抗感染类 = 1 and 呼吸系统药物 = 1 1.102 56.811 0.626
11 维生素矿物质类及肠内肠外营养药 = 1 激素类及影响内分泌药物 = 1 and
消化系统药物 = 1 and 免疫系统药物 = 1
1.940 55.472 1.0763
12 中成药 = 1 治疗精神障碍药物 = 1 1.267 53.468 0.677
13 激素类及影响内分泌药物 = 1 血液系统药物 = 1 and
维生素矿物质类及肠内肠外营养药 = 1
2.834 53.360 1.512
14 维生素矿物质类及肠内肠外营养药 = 1 血液系统药物 = 1 and
激素类及影响内分泌药物 = 1
2.892 52.278 1.512
15 抗肿瘤药 = 1 血液系统药物 = 1 and
维生素矿物质类及肠内肠外营养药 = 1
2.834 51.809 1.468
16 维生素矿物质类及肠内肠外营养药 = 1 抗肿瘤药 = 1 and
激素类及影响内分泌药物 = 1
6.644 51.185 3.401
17 中成药 = 1 调节水盐、电解质及酸碱平衡药 = 1 and
镇痛、解热、抗炎、抗痛风药 = 1
1.252 51.170 0.641
18 激素类及影响内分泌药物 = 1 血液系统药物 = 1 and 抗肿瘤药 = 1 and
维生素矿物质类及肠内肠外营养药 = 1
1.468 50.873 0.747
药品编号 通用名 药品类别
010109MCE1231 阿莫西林胶囊 抗感染类
010202A181696 拉米夫定片 抗感染类
010304A560403 甲硝唑片 抗感染类
020207A532305 甲氨蝶呤片 抗肿瘤药
030202BIO2547 盐酸利多卡因注射液 麻醉药及麻醉辅助用药
040266AAU0186 氯诺昔康片 镇痛、解热、抗炎、抗痛风药
…… …… ……
160011B250270 氯化钠注射液(软袋)(250ml) 调节水盐、电解质及酸碱平衡药
270462Afk0612 荧光素钠注射液 中成药
2704bnK251626 蓝芩口服液 中成药
2704CEM172120 感咳双清胶囊 中成药
271304M640735 生脉胶囊 中成药
271308U752526 复方丹参滴丸 中成药
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