Evidence map›Paper›PMID 42491989›Full record

ArticleJournal of education and health promotion2026

Impact of an algorithm-based postoperative pain management in patients undergoing abdominal surgery-A prospective interventional study.

R Priyanka, Lakshmi Ramamoorthy, Lenin Babu Elakkumanan, Biju Pottakkat, H T Lalthanthuami, Unnikrishnan Puliakkuth

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Article in Journal of education and health promotion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

R PriyankaJawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Lakshmi RamamoorthyCollege of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Lenin Babu ElakkumananDepartment of Anesthesiology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Biju PottakkatDepartment of Surgical Gastro Enterology, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
H T LalthanthuamiCollege of Nursing, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Puducherry, India.
Unnikrishnan PuliakkuthCollege of Nursing, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe fear of pain is ranked next to the fear of death. Globally, 50% to 75% of postoperative patients experience severe postoperative pain. Pain resource nurses function as role models in pain assessment and management. This study aimed to assess the adequacy of pain management and the effect of algorithm-based postoperative pain management following abdominal surgeries. MATERIALS AND

methodsA two-phase study was conducted over 6 months in the Surgical Gastroenterology department of a tertiary care center, involving 70 postoperative patients divided equally between the phases using consecutive sampling. The second phase, the primary focus, employed a one-group, post-test-only design, measuring breakthrough pain with the Numerical Rating Scale. Pain management during this phase was guided by a structured, algorithm-based protocol along with standard care. In contrast, the first phase used a quantitative, cross-sectional observational design with patients receiving routine care. Pain severity, quality indicators, and patient satisfaction were assessed using the ASSIST-Patient Satisfaction Survey at multiple points in both phases. This design enabled a systematic comparison between traditional practices and the targeted intervention implemented in Phase II.

resultsThe study results showed that more patients in group 1 experienced severe pain at specific times after surgery compared to group 2 (24 hours postsurgery: 52.8 ± 30.2 vs. 27.4 ± 13.7,

conclusionThe current study demonstrated that algorithmic pain management can improve the quality indicators of pain management, pain relief, and patient satisfaction scores among postoperative patients.

Indexed as

Breakthrough painpainpain managementpostoperative painquality indicators

Identifiers

PMID42491989
PMCPMC13378867

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.