A toolbox to improve algorithms for insulin-dosing decision support

被引：3

作者：

Donsa, K. ^{[1
]}

Beck, P. ^{[1
]}

Plank, J. ^{[2
]}

Schaupp, L. ^{[2
]}

Mader, J. K. ^{[2
]}

Truskaller, T. ^{[1
]}

Tschapeller, B. ^{[1
]}

Hoell, B. ^{[1
]}

Spat, S. ^{[1
]}

Pieber, T. R. ^{[1
,2
]}

机构：

[1] JOANNEUM RES Forsch Gesell mbH, HLTH Inst Biomed & Hlth Sci, Graz, Austria

[2] Med Univ Graz, Dept Internal Med, Div Endocrinol & Metab, Graz, Austria

来源：

APPLIED CLINICAL INFORMATICS | 2014年 / 5卷 / 02期

关键词：

clinical decision support systems; workflow; algorithms; computer simulation; diabetes mellitus type 2; MANAGEMENT; HYPERGLYCEMIA; THERAPY; BOLUS;

D O I：

10.4338/ACI-2014-04-RA-0033

中图分类号：

R-058 [];

学科分类号：

摘要：

Background: Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions. Objective: To develop a toolbox for improving clinical decision-support algorithms. Methods: The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) Analysis: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients. Results: Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms. Conclusion: These results are a first step towards individualized algorithm modifications for specific patient subgroups.

引用

页码：548 / 556

页数：9

共 50 条

[41] Effects of clinical decision support on initial dosing and monitoring of tobramycin and amikacin
Cox, Zachary L.
Nelsen, Cori L.
Waitman, Lemuel R.
McCoy, Jacob A.
Peterson, Josh F.
[J]. AMERICAN JOURNAL OF HEALTH-SYSTEM PHARMACY, 2011, 68 (07) : 624 - 632
[42] Assessment of Different Methods for Pediatric Meningitis Dosing Clinical Decision Support
Stultz, Jeremy S.
Taylor, Perry
McKenna, Sean
[J]. ANNALS OF PHARMACOTHERAPY, 2019, 53 (01) : 35 - 42
[43] Electronic clinical decision support tool for hydroxychloroquine dosing guideline adherence
Chen, Rebecca
Kuo, Blanche
Kalur, Aneesha
Muste, Justin
Singh, Rishi P.
[J]. INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2021, 62 (08)
[44] Understanding Responses to a Renal Dosing Decision Support System in Primary Care
Cho, Insook
Slight, Sarah P.
Nanji, Karen C.
Seger, Diane L.
Dykes, Patricia
Bates, David W.
[J]. MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 : 931 - 931
[45] Methods and algorithms of strategic planning for decision support systems
Eremeyev, AP
Nedelina, AY
[J]. KNOWLEDGE-BASED SOFTWARE ENGINEERING, 2004, 108 : 247 - 252
[46] Decision support in merchandise placement using genetic algorithms
Meyer, M
[J]. OPERATIONS RESEARCH PROCEEDINGS 2000, 2001, : 483 - 489
[47] Decision support in Petri nets via genetic algorithms
Hofmann, F.
Berkhahn, V.
Milbradt, P.
[J]. EWORK AND EBUSINESS IN ARCHITECTURE, ENGINEERING AND CONSTRUCTIO N, 2009, : 301 - 306
[48] Decision support for watershed management using evolutionary algorithms
Muleta, MK
Nicklow, JW
[J]. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2005, 131 (01) : 35 - 44
[49] DEVELOPMENT OF DECISION-SUPPORT ALGORITHMS FOR COMMODITY MANAGEMENT
Iurasov, A.
Ivashko, L.
Maksymov, O.
[J]. FINANCIAL AND CREDIT ACTIVITY-PROBLEMS OF THEORY AND PRACTICE, 2021, 1 (36): : 260 - 269
[50] ADAPTIVE DECISION AIDS - USING FALLIBLE ALGORITHMS TO SUPPORT DECISION-MAKING
LEHNER, PE
MULLIN, TM
COHEN, MS
[J]. 1989 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-3: CONFERENCE PROCEEDINGS, 1989, : 893 - 894

← 1 2 3 4 5 →