张立艳
北京北亚骨科医院 北京 102445
【摘要】目的:分析细节体检对改善体检者依从度、提高体检满意度的价值;方法:随机将我院收治的110例体检者纳入对照组(n=55)与观察组(n=55),对照组给予常规护理方式,观察组实施细节护理干预,比较两组体检周期和体检时间,以及体检者依从率和满意率;结果:观察组体检周期和体检时间均明显短于对照组,两组时间差异显著(P<0.05),观察组依从率(98.18%)和满意率(96.36%)均明显高于对照组(87.27%,83.64%),组间差异具有统计学意义(P<0.05);结论:与常规护理方式相比,采用细节护理可改善体检者依从度与满意度。
【关键词】细节体检;体检者;依从度;体检满意度
大量研究调查表明,在患者患病后及早采用适合方式进行治疗,利于提升对患者疾病控制和治疗效果。而体检作为一种及早发现病情有效方式,便于确定体检者身体风险。而在体检期间实施细节护理方式,不仅利于提升体检中心服务水平,而且可促使体检者更加配合有关操作,可使体检者满意度提高[1]。研究对我院收治的110例体检者进行护理研究,对患者进行随机分组后分别采用不同方式进行护理,比较两组护理方式应用结果,对细节体检护理进行具体分析。
1资料及方法
1.1一般资料
研究从体检中心2020年1月至2020年12月收治的体检者中随机选择110例展开护理研究,使用随机数字表法对患者进行分组,并建立对照组与观察组,每组均为55例。其中,对照组:男性32例,女性23例,年龄24-63岁,平均年龄(41.9±2.5)岁;观察组:男性34例,女性21例,年龄23-64岁,平均年龄(42.0±2.9)岁;两组体检者基线资料差异不存在统计学意义(P<0.05)。
1.2方法
对照组:实施常规护理方式。主要措施:通过对体检者进行健康宣教,详细告知体检前相关准备工作以及注意事项,并叮嘱体检者配合进行相关检查,体检后及时告知体检者结果并发放体检报告。
观察组:实施细节护理方式。具体护理措施:(1)环境护理:营造舒适体检环境,保持空间环境干净整洁、空气清新,定时进行消毒通风,并根据体检者需求进行温度和湿度调控,以此帮助体检者放松身心,减少其等待体检或对体检结果担忧产生的焦虑。为患者提供适合休息环境,并提供饮用水和体检、医学等方面读物,加强对体检者体检引导。(2)健康宣教:体检前详细向体检者说明体检项目及相关注意事项,叮嘱患者饮食清淡、睡眠充足和禁烟禁酒,适当进行饮食指导,提升体检者准备效果。并根据体检者学历,采用微信推送、面对面讲解、发放常见疾病防治宣传手册等方式向其普及体检及医学方面知识,提升其对体检相关认知。(3)心理护理:主动与体检者进行交流,并对其进行心理方面评估,耐心解答体检者疑惑,向其说明体检重要性。并利用播放轻音乐、视频等方式,帮助患者平复情绪,以此提升体检者对各项体检操作依从性。(4)查体护理:体检前护理人员应与体检者,针对相关体检项目进行详细沟通,尤其是对年老和体弱体检者,提供一对一全面服务。(5)体检后护理:护理人员及时告知患者领取检查报告,并根据体检者检查结果以及医生诊断结果,帮助患者解答疑惑分析病情,并建立和完善体检者体检档案。
1.3观察指标
(1)体检结果:比较体检周期和体检时间,时间越短体检护理方式应用价值越高。
(2)依从率:使用Frankl治疗依从性量表[2],根据患者配合度确定,完全依从:完全配合护理人员各项操作;较依从:对部分护理操作表示抗拒,不依从:对多数护理操作表示抗拒。总依从率=(完全依从+较依从例数)例数/总例数×100%。
(3)护理满意率:使用科室自拟满意度评价问卷进行统计,由患者根据意愿进行打分,总满意率=(非常满意+较满意)例数/总例数×100%。
1.4统计学方法
采用SPSS21.0对数据进行统计学分析,计量资料用(±s)表示,采用t检验;计数资料以百分数(%)表示,采用检验,以P<0.05为差异显著。
2结果
2.1两组体检周期和体检时间比较
观察组体检周期和体检时间均明显短于对照组(P<0.05),详见表1。
表1 两组体检周期和体检时间比较(±s,d)
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2.2两组体检者依从率比较
观察组总依从率为98.18%高于对照组的87.27%,组间差异明显(P<0.05),详见表2。
表2 两组体检者依从率比较(n,%)
![](data:image/png;base64,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)
2.3两组体检者护理满意率比较
观察组满意率为96.36%明显高于对照组的83.64%(P<0.05),详见表3。
表3两组体检者护理满意率对比(n,%)
![](data:image/png;base64,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)
3讨论
伴随着人民生活水平不断提升,在不良生活习惯和饮食偏好等因素影响下,各种不同疾病发病率呈现明显上升趋势。人们为保证自身身体健康水平,并及早治愈自身疾病,开始重视体检。而在实际参与体检中,受人们思想观念变化影响,体检期间更加关注相应护理模式下体检中心服务水平[3]。因此,体检中心在开展相应工作中,应重视对相应护理措施应用,通过提供良好服务体验,提升体检者对体检中心认可程度。而以往对患者进行护理中采用的常规护理方式已经难以满足体检者需求。目前,细节护理作为一种开始推广护理方案,有着较高使用优势,可营造良好环境和轻松氛围,并提供耐心、细心服务,可提升体检中心服务质量[4]。
本次对体检者细节护理研究结果显示,观察组体检周期、体检时间均明显短于对照组(P<0.05),而观察组依从率(98.18%)高于对照组(87.27%),且体检护理满意率(96.36%)高于对照组(83.64%),组间差异具有统计学意义(P<0.05)。此次体检护理工作开展结果显示,对体检者实施细节护理方式后,可促使其接受体检时间及周期缩短,并增强患者对护理操作配合程度以及满意程度,该护理措施在体检中心中应用价值高于传统常规护理。
综上所述,在对体检中心体检者进行护理中,将各项护理措施落实到细节,实施细节化护理,可缩短体检时间,并提升护理效率,同时可促使体检者更加配合进行护理,相比于常规护理方式,体检者对体检工作开展认可度和满意度更高。
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