No abstract

The increasing data scales in today’s business sectors coupled with the necessity of risk management raise the importance of business intelligence tools as an integrated solution for the insurance industry. These tools have mostly been used to achieve effective risk management. Although methods of risk management in the insurance industry have been proposed many years ago, the research effort has primarily been focused on predictive analyses. This study aimed to investigate the role of business intelligence as a solution to illustrate its potential in risk management particularly for decision-makers in agricultural insurance. We hypothesized that this would make a preferable decision in uncertain conditions. Sample data from the online transaction process system of Iran agricultural insurance fund were preprocessed in SQL server. Multidimensional online analytical processing architecture was analyzed using Targit business intelligence tool. Our results identified financial risks that lead to a framework of controlling risk based on business intelligence in the agricultural insurance fund.

Background: Knee pain is a major source of distress and disability, with pain progression highly variable between individuals. Previous studies defining pain trajectories have all used a single measure of pain, and these differ across studies.Different measures reflect diverse pain mechanisms. To ascertain the clinical utility of pain trajectories, we explored associations between opioid and non-steroidal anti-inflammatory drug (NSAID) use. Methods:We model pain trajectories using two measures-Intermittent and Constant Osteoarthritis Pain (ICOAP) and the painDETECT, in 2141 participants, across 3 waves (the baseline, 1-and 3-year assessments) of the Knee Pain In the Community (KPIC) cohort.Results: Latent class growth analysis identified six trajectories using ICOAP subscales (High-Stable, Low-Stable, Moderate Worsening, Moderate Recovering, Worsening, and Recovering) and four trajectories using painDETECT (Highstable, Low-stable, Moderate Worsening, and Moderate Recovering). There was a high degree of correspondence between people assigned to pain trajectories between ICOAP intermittent and constant subscales, but less so using painDETECT.Opioid use was associated with ICOAP trajectories only (e.g., High-Stable and Worsening intermittent ICOAP trajectories) and in women. Conclusion:Different measures of pain produce different patterns of pain progression and these are differentially related to medication use. Opioid use is linked to trajectories of pain based on the impact of pain on behavior and not pain symptoms. Thus, managing pain's behavioral impact is more central to understanding opioid use than managing pain symptoms. These findings support more in-depth questioning about the type of pain and its progression in clinical practice. K E Y W O R D S knee pain, knee pain trajectories, latent class growth analysis, osteoarthritis, pain progression | 211 HAYBATOLLAHI eT AL.