Uppal Harjot Singh, Rozenfeld Sydney Ilana, Hetzel Scott, Hesselbach Kristin Nicole, Ludwig Trisha, Bice Miranda, Williams Seth K
University of Wisconsin School of Medicine and Public Health, Madison, Highland Avenue, Madison, WI 53726, USA.
Biostatistics and Medical Informatics Department, University of Wisconsin-Madison, Walnut Street, Madison, WI 53726, USA.
N Am Spine Soc J. 2022 Jun 20;11:100139. doi: 10.1016/j.xnsj.2022.100139. eCollection 2022 Sep.
A Pain Plan was formulated for all patients undergoing elective spine surgery at our institution. It was based on prior opioid experiences and developed collaboratively between the patient and the surgeon at a preoperative clinic visit. Category 1 patients had no previous opioid experience, Category 2 patients had remote previous opioid experience with acceptable pain control and no side effects, Category 3 patients had remote previous opioid experience with unacceptable pain control and/or side effects, and Category 4 patients had opioid use leading up to surgery.
This is a retrospective cohort study comparing adult patients within four different pain plan categories over one year ( = 313) to determine if categorization is predictive. Demographic data collected included age, gender, ASA class, BMI, smoking status, insurance status, substance abuse, and comorbid psychiatric diagnoses. Demographic factors between categories were compared and controlled for as covariates within analyses. Outcomes measures comprised self-reported pain scores and functional measurements, including inpatient opioid use, outpatient opioid prescription quantities, and postoperative healthcare utilization.
Inpatient and outpatient opioid use were statistically significant amongst the categories, with prescription quantities greatest in Category 4, followed by Categories 2, 3, and 1, respectively. There was no difference in LOS or complexity of communication encounters amongst any of the groups. Patient-reported pain scores showed statistically significant differences and followed the same trend as opioid quantities, 4, 2, 3, and 1. The number of communication encounters was significant exclusively for Category 3 vs. 4.
The use of categorization in Pain Plan formation has been a helpful tool for postoperative pain management at our institution. Categorization is predictive of pain scores and opioid use after surgery, allowing the surgical team to tailor their care and counseling towards individual patients. In addition, the plan's collaborative nature enables patients to be involved in their pain management decisions while also setting limits and expectations.
我们机构为所有接受择期脊柱手术的患者制定了疼痛管理计划。该计划基于之前使用阿片类药物的经验，由患者和外科医生在术前门诊共同制定。1类患者之前没有使用过阿片类药物，2类患者之前有过阿片类药物使用经历，疼痛控制良好且无副作用，3类患者之前有过阿片类药物使用经历，疼痛控制不佳和/或有副作用，4类患者在手术前一直在使用阿片类药物。
这是一项回顾性队列研究，比较了一年内四个不同疼痛管理计划类别的成年患者（n = 313），以确定分类是否具有预测性。收集的人口统计学数据包括年龄、性别、美国麻醉医师协会（ASA）分级、体重指数（BMI）、吸烟状况、保险状况、药物滥用和合并精神疾病诊断。比较了不同类别之间的人口统计学因素，并在分析中作为协变量进行控制。结局指标包括自我报告的疼痛评分和功能测量，包括住院期间阿片类药物的使用、门诊阿片类药物处方量以及术后医疗保健利用率。
不同类别之间住院和门诊阿片类药物的使用在统计学上有显著差异，处方量在4类患者中最大，其次分别是2类、3类和1类。任何一组之间的住院时间或沟通交流的复杂性没有差异。患者报告的疼痛评分在统计学上有显著差异，并且与阿片类药物用量呈现相同趋势，即4类、2类、3类和1类。沟通交流的次数仅在3类和4类之间有显著差异。
在疼痛管理计划制定中使用分类法是我们机构术后疼痛管理的一个有用工具。分类可预测术后疼痛评分和阿片类药物的使用，使手术团队能够针对个体患者调整护理和咨询。此外，该计划的协作性质使患者能够参与疼痛管理决策，同时也设定了限制和期望。
