Modeling a decision support system to prevent adverse drug events

2002 ◽  
Author(s):  
G.D. Fiol ◽  
B.H.S.C. Rocha ◽  
P. Nohama
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Adverse Drug Events

scholarly journals 1074. Evaluation of a Pharmacist-led Antimicrobial and Anticoagulant Monitoring Initiative

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S380-S381
Author(s):  
Wei Hsiang Lin ◽  
Amanda Binkley ◽  
Christo L Cimino ◽  
Naasha J Talati ◽  
Jimish M Mehta ◽  
...  
Keyword(s):  
Renal Function ◽  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Dose Adjustment ◽  
Adverse Drug Events ◽  
Medical Center ◽  
Clinical Decision

Abstract Background Adverse drug events are associated with an increase in hospital stay and cost. Risks from these events are minimized by adjusting a medication’s dose or frequency, and changes in renal function may necessitate adjustments. Currently, there is no formal procedure for a prospective audit of renal function over the weekend at our institution. This pharmacist-driven initiative will evaluate if a prospective review identified by real-time clinical decision support alerts over the weekend will reduce the time from change in renal function to dose adjustment of select antimicrobials and/or anticoagulants. Methods This monitoring initiative is comprised of a pre- and post-cohort population. The pre-cohort population included patients admitted to Penn Presbyterian Medical Center (PPMC) from January to March of 2018 on select antimicrobials and/or anticoagulants, who were identified to have a change in renal function (serum creatinine change of 0.3 mg/dL or greater) over the weekend. The post-cohort population was identified with a clinical decision support system (ILÚM Health Solutions, Kenilworth, NJ) and included patients admitted to PPMC from January to March of 2019. A pharmacy resident reviewed alerts in the clinical decision support system over the weekend and contacted providers with dose adjustment recommendations. The Mann–Whitney U test was used to analyze the primary endpoint while descriptive statistics were used for the secondary endpoints Results Eighteen interventions were completed within the 3-month post-cohort intervention period, with a time to dose adjustment between the pre/post-cohort being reduced by 50 hours (P = 0.0001) resulting in a median time to change of 11 hours in the post-cohort. All pharmacy recommendations were accepted by the provider, and 94% of medication adjustments were antimicrobials. Conclusion The application of this prospective weekend initiative utilizing a clinical decision support system demonstrated a clinically and statistically significant reduction in the time to dose adjustments for antimicrobials and/or anticoagulants. Implementation of this initiative will further establish a role for pharmacist-led evaluations and could potentially be expanded to other clinical areas. Disclosures All authors: No reported disclosures.

An Ontology-based Mediator of Clinical Information for Decision Support Systems

2008 ◽  
Vol 47 (06) ◽  
pp. 549-559 ◽  
Author(s):  
K. Ohe ◽  
Y. Kawazoe
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Data ◽  
Support System ◽  
Adverse Drug Events ◽  
Clinical Information ◽  
Temporal Information ◽  
Temporal Abstraction ◽  
Alert System ◽  
Data Repositories

Summary Objective: We have been developing a decision support system that uses electronic clinical data and provides alerts to clinicians. However, the inference rules for such a system are difficult to write in terms of representing domain concepts and temporal reasoning. To address this problem, we have developed an ontologybased mediator of clinical information for the decision support system. Methods: Our approach consists of three steps: 1) development of an ontology-based mediator that represents domain concepts and temporal information; 2) mapping of clinical data to corresponding concepts in the mediator; 3) temporal abstraction that creates high-level, interval-based concepts from time-stamped clinical data. As a result, we can write a concept-based rule expression that is available for use in domain concepts and interval-based temporal information. The proposed approach was applied to a prototype of clinical alert system, and the rules for adverse drug events were executed on data gathered over a 3-month period. Results: The system generated 615 alerts. 346 cases (56%) were considered appropriate and 269 cases (44%) were inappropriate. Of the false alerts, 192 cases were due to data inaccuracy and 77 cases were due to insufficiency of the temporal abstraction. Conclusion: Our approach enabled to represent a concept-based rule expression that was available for the prototype of a clinical alert system. We believe our approach will contribute to narrow the gaps of information model between domain concepts and clinical data repositories.

Decision Support System Development Based On Android Using Analytical Hierarchy Process (AHP) Method For Determining The Middle Small Business Development Priority In Sorong City

2019 ◽  
Vol 5 (2) ◽  
pp. 25-39
Author(s):  
Luluk Suryani ◽  
Raditya Faisal Waliulu ◽  
Ery Murniyasih
Keyword(s):  
Decision Support ◽  
Small Business ◽  
Decision Support System ◽  
Support System ◽  
Analytical Hierarchy Process ◽  
System Development ◽  
Business Development ◽  
Ahp Method ◽  
Small Business Development ◽  
Hierarchy Process

Usaha Kecil Menengah (UKM) adalah salah satu penggerak perekonomian suatu daerah, termasuk Kota Sorong. UKM di Kota Sorong belum berkembang secara optimal. Ada beberapa penyebab diantaranya adalah mengenai finansial, lokasi, bahan baku dan lain-lain. Untuk menyelesaikan permasalah tersebut peneliti terdorong untuk melakukan pengembangan Aplikasi yang dapat membantu menentukan prioritas UKM yang sesuai dengan kondisi pelaku usaha. Pada penelitian ini akan digunakan metode Analitycal Hierarchy Process (AHP), untuk pengambilan keputusannya. Metode AHP dipilih karena mampu menyeleksi dan menentukan alternatif terbaik dari sejumlah alternatif yang tersedia. Dalam hal ini alternatif yang dimaksudkan yaitu UKM terbaik yang dapat dipilih oleh pelaku usaha sesuai dengan kriteria yang telah ditentukan. Penelitian dilakukan dengan mencari nilai bobot untuk setiap atribut, kemudian dilakukan proses perankingan yang akan menentukan alternatif yang optimal, yaitu UKM. Aplikasi Sistem Pendukung Keputusan yang dikembangkan berbasis Android, dimana pengguna akan mudah menggunakannya sewaktu-waktu jika terjadi perubahan bobot pada kriteria atau intensitas.  Hasil akhir menunjukkan bahwa metode AHP berhasil diterapkan pada Aplikasi Penentuan Prioritas Pengembangan UKM.

THE ACCURACY OF THE SPORTS TALENT IDENTIFICATION DECISION SUPPORT SYSTEM FOR YOUNG ATHLETES

2014 ◽  
Author(s):  
Kamaruzaman S. ◽  
◽  
A. H. Omar ◽  
Muhammad Iqbal Tariq Idris ◽  
Izwyn Z. ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Young Athletes ◽  
Talent Identification ◽  
Identification Decision
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