An Ambient Intelligence Framework for End-User Service Provisioning in a Hospital Pharmacy: a Case Study

Martín, Diego; Alcarria, Ramón; Sánchez-Picot, Álvaro

doi:10.1007/s10916-015-0298-z

Cited by 14 publications

(8 citation statements)

References 19 publications

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“…RFID technologies in hospital logistics have been commonly applied in management of pharmaceutical inventories [6], traceability of medication distribution from warehouse to pharmacy [18, 23], and from pharmacy to the patient [12, 19–21]. With a scarcity of empirical studies on RFID use for stock management of high value surgery medical products, our results would support the implementation of a RFID smart cabinet for this aim.…”

Section: Discussionmentioning

confidence: 76%

Implementation and Evaluation of a RFID Smart Cabinet to Improve Traceability and the Efficient Consumption of High Cost Medical Supplies in a Large Hospital

2019

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The efficiency of a smart cabinet with RFID technology to improve the information about inventory management for cardiothoracic surgery as well as for time savings, was assessed in a large reference hospital. In a 6-month study, the implemented operational RFID process (StocKey® Smart Cabinet) consisted of: i) product reception, registration and labelling in the general warehouse; ii) product storage in the cabinet and registered as inputs by radiofrequency; iii) products registered as outputs as required for surgery; iv) product assignment to a patient in the operating room; and v) return of products not used to the cabinet. Stock-outs, stock mismatches, urgent restocking, assignment of high-value medical products to patients, and time allocated by the supervisory staff to the stock management, were assessed on a monthly basis. 0% stock-outs and 0% stock mismatches using RFID were observed during the study. Monthly percentages of products requiring urgent restocking ranged from 0% to 13.3%. No incorrect assignments to patients of surgery products or prostheses were detected. The percentage of correct assignments increased from 36.1%–86.1% to 100% in the first 4–5 months. The total average time allocated by the supervisory staff to the whole logistic chain was reduced by 58% (995 min with the traditional manual system vs. 428 min with RFID). The RFID system showed the ability to monitor both the traceability and consumption per patient of high-value surgery products as well as contributed to significant time savings.

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Section: Discussionmentioning

confidence: 76%

Implementation and Evaluation of a RFID Smart Cabinet to Improve Traceability and the Efficient Consumption of High Cost Medical Supplies in a Large Hospital

2019

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“…Due to the lack of effective top-level design and standard specification requirements, there are great differences in database types and data formats involved in different information systems. At the same time, there are some problems in the construction of business information system of functional departments, such as insufficient function integration and different data interface standards, which leads to the widespread phenomenon of information island [ 4 ]. Traditional medicine management has seriously hindered the sharing of medical information and the improvement of medical service level, restricted the data sharing and resource utilization and allocation efficiency of intelligent pharmacy management information, and affected the time of taking and waiting for drugs and the quality of pharmaceutical care.…”

Section: Introductionmentioning

confidence: 99%

The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy

Tan

Zheng

et al. 2022

Computational Intelligence and Neuroscience

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With the wide application of artificial intelligence and big data technology in the medical field, the problems of high cost and low efficiency of traditional pharmacy management were becoming more and more obvious. Therefore, this paper proposed to use data mining technology to design and develop the dispensing process and equipment of intelligent pharmacy. Firstly, it summarized the existing data mining technology and association rule methods and expounded its application value in the related fields. Secondly, the data standard and integration platform of dispensing in intelligent pharmacy were established. Web service technology was used to design the interactive interface and call it to the intelligent device of pharmacy. Finally, an intelligent pharmacy management system based on association rule mining was constructed through the data mining of intelligent pharmacy equipment, in order to improve the intelligence and informatization of modern pharmacy management. For the emergency dispensing process of intelligent equipment failure, data mining was used to optimize the intelligent pharmacy equipment and dispensing process and change the pharmacy management from traditional prescription to patient drug treatment, so as to improve the dispensing efficiency of intelligent pharmacy equipment. Through the systematic test and analysis, the results showed that through the real-time risk prevention and control, the formula accuracy and operation speed of the intelligent dispensing machine were improved and the dispensing time was shortened. Through intelligent drug delivery, the unreasonable drug use of patients was reduced, the safety and effectiveness of clinical drug use were ensured, and the contradiction between doctors and patients was reduced. This study can not only optimize the medical experience of patients and provide patients with more high-quality and humanized pharmaceutical technical services but also provide some support for the intelligent management of modern hospitals.

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“…In the two last decades, technology innovation has led to intelligent environments [ 1 ] such as smart homes [ 2 ], smart hospitals [ 3 ], or even smart cities [ 4 ]. IT (Information Technology) infrastructures such as sensors enable making decisions by providing real-time information of the environment to end users, leveraging interconnected devices in a huge number of domains.…”

Section: Introductionmentioning

confidence: 99%

Towards Outlier Sensor Detection in Ambient Intelligent Platforms—A Low-Complexity Statistical Approach

Martín

Fuentes-Lorenzo

Bordel

et al. 2020

Sensors

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Sensor networks in real-world environments, such as smart cities or ambient intelligent platforms, provide applications with large and heterogeneous sets of data streams. Outliers—observations that do not conform to an expected behavior—has then turned into a crucial task to establish and maintain secure and reliable databases in this kind of platforms. However, the procedures to obtain accurate models for erratic observations have to operate with low complexity in terms of storage and computational time, in order to attend the limited processing and storage capabilities of the sensor nodes in these environments. In this work, we analyze three binary classifiers based on three statistical prediction models—ARIMA (Auto-Regressive Integrated Moving Average), GAM (Generalized Additive Model), and LOESS (LOcal RegrESSion)—for outlier detection with low memory consumption and computational time rates. As a result, we provide (1) the best classifier and settings to detect outliers, based on the ARIMA model, and (2) two real-world classified datasets as ground truths for future research.

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An Ambient Intelligence Framework for End-User Service Provisioning in a Hospital Pharmacy: a Case Study

Cited by 14 publications

References 19 publications

Implementation and Evaluation of a RFID Smart Cabinet to Improve Traceability and the Efficient Consumption of High Cost Medical Supplies in a Large Hospital

Implementation and Evaluation of a RFID Smart Cabinet to Improve Traceability and the Efficient Consumption of High Cost Medical Supplies in a Large Hospital

The Intervention of Data Mining in the Allocation Efficiency of Multiple Intelligent Devices in Intelligent Pharmacy

Towards Outlier Sensor Detection in Ambient Intelligent Platforms—A Low-Complexity Statistical Approach

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