Literature DB >> 19695779

Multidisciplinary pain management based on a computerized clinical decision support system in cancer pain patients.

Thilo Bertsche1, Vasileios Askoxylakis, Gregor Habl, Friederike Laidig, Jens Kaltschmidt, Simon P W Schmitt, Hamid Ghaderi, Angelika Zabel-du Bois, Stefanie Milker-Zabel, Jürgen Debus, Hubert J Bardenheuer, Walter E Haefeli.   

Abstract

A prospective controlled intervention cohort study in cancer pain patients (n=50 per group) admitted to radiation oncology wards (62 beds, 3 wards) was conducted in a 1621-bed university hospital. We investigated the effect of an intervention consisting of daily pain assessment using the numeric visual analog scale (NVAS) and pain therapy counseling to clinicians based on a computerized clinical decision support system (CDSS) to correct deviations from pain therapy guidelines. Effects on guideline adherence (primary outcome), pain relief (NVAS) at rest and during physical activity (both groups: cross-sectional assessment on day 5; intervention group: every day assessment), co-analgesic prescription, and acceptance rates of recommendations (secondary outcomes) were assessed. The number of patients with at least one deviation from guidelines at discharge was decreased by the intervention from 37 (74%) in controls to 7 (14%, p<0.001). In the intervention group, pain (NVAS) decreased during hospital stay at rest from 3.0 (Delta(0.5) (Q(75%)-Q(25%))=3.0) on admission to 1.5 (Delta(0.5)=1.0) at discharge (p<0.01) and during physical activity from 7.0 (Delta(0.5)=4.0) on admission to 2.5 (Delta(0.5)=3.8) at discharge (p<0.001). At discharge, the number of patients treated with co-analgesics increased from 23 (46%) in controls to 33 (66%) in the intervention group (p=0.04). From 279 recommendations issued in the intervention 85% were fully accepted by the physicians. Deviations from well-established guidelines are frequent in pain therapy. A multidisciplinary pain management increased adherence to pain management guidelines.

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Year:  2009        PMID: 19695779     DOI: 10.1016/j.pain.2009.07.009

Source DB:  PubMed          Journal:  Pain        ISSN: 0304-3959            Impact factor:   6.961


  18 in total

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Review 2.  The impact of health information technology on cancer care across the continuum: a systematic review and meta-analysis.

Authors:  Will L Tarver; Nir Menachemi
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3.  Creating computable algorithms for symptom management in an outpatient thoracic oncology setting.

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Journal:  J Pain Symptom Manage       Date:  2013-05-13       Impact factor: 3.612

Review 4.  Computer-Based Clinical Decision Support Systems and Patient-Reported Outcomes: A Systematic Review.

Authors:  David Blum; Sunil X Raj; Rolf Oberholzer; Ingrid I Riphagen; Florian Strasser; Stein Kaasa
Journal:  Patient       Date:  2015-10       Impact factor: 3.883

5.  Clinical decision support for therapeutic decision-making in cancer: A systematic review.

Authors:  Melissa Beauchemin; Meghan T Murray; Lillian Sung; Dawn L Hershman; Chunhua Weng; Rebecca Schnall
Journal:  Int J Med Inform       Date:  2019-08-12       Impact factor: 4.046

6.  The status of the performance of medication reviews in German community pharmacies and assessment of the practical performance.

Authors:  Claudia Greißing; Katharina Kössler; Johanna Freyer; Lucie Hüter; Peter Buchal; Susanne Schiek; Thilo Bertsche
Journal:  Int J Clin Pharm       Date:  2016-10-25

7.  Impact of a Clinical Decision Support Tool on Cancer Pain Management in Opioid-Tolerant Inpatients.

Authors:  Trevor N Christ; Jeryl J Villadolid; Anish Choksi; Monica Malec; Randall W Knoebel
Journal:  Hosp Pharm       Date:  2017-12-11

8.  A regret theory approach to decision curve analysis: a novel method for eliciting decision makers' preferences and decision-making.

Authors:  Athanasios Tsalatsanis; Iztok Hozo; Andrew Vickers; Benjamin Djulbegovic
Journal:  BMC Med Inform Decis Mak       Date:  2010-09-16       Impact factor: 2.796

9.  Standardising analgesic administration for nurses: a prospective intervention study.

Authors:  Susanne Schiek; Katharina Moritz; Stefanie J Seichter; Mohamed Ghanem; Georg von Salis-Soglio; Roberto Frontini; Thilo Bertsche
Journal:  Int J Clin Pharm       Date:  2016-09-21

10.  Feasibility of using algorithm-based clinical decision support for symptom assessment and management in lung cancer.

Authors:  Mary E Cooley; Traci M Blonquist; Paul J Catalano; David F Lobach; Barbara Halpenny; Ruth McCorkle; Ellis B Johns; Ilana M Braun; Michael S Rabin; Fatma Zohra Mataoui; Kathleen Finn; Donna L Berry; Janet L Abrahm
Journal:  J Pain Symptom Manage       Date:  2014-05-29       Impact factor: 3.612

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