BACKGROUND Neonatal pain has been underdiagnosed due to several false beliefs.AIM To determine the status of neonatal pain in newborns who are admitted to intensive care units.METHODS Different databases were searched...BACKGROUND Neonatal pain has been underdiagnosed due to several false beliefs.AIM To determine the status of neonatal pain in newborns who are admitted to intensive care units.METHODS Different databases were searched.Literature reviews and research reports conducted in newborns that were written in English,Spanish,or Portuguese,published between 2010 and 2020,and having free access to the full text were selected.A total of 135 articles were found,and 18 articles were finally reviewed.RESULTS Newborns are exposed to numerous painful procedures.In order to assess their pain levels,several scales have been used,although they are sometimes not correctly interpreted.In terms of pain management,the nursing team plays a very important role based mainly on both pharmacological and non-pharmacological approaches.CONCLUSION Nursing staff members must be well trained in order to identify pain and to interpret the scales correctly.Besides,they have an important role in performing non-pharmacological procedures for pain management.展开更多
In this paper, we propose a new architecture that combines prediction and decision-making in the form of a hybrid framework aimed at providing clinicians with transparent and accurate maps, or charts, to guide and to ...In this paper, we propose a new architecture that combines prediction and decision-making in the form of a hybrid framework aimed at providing clinicians with transparent and accurate maps, or charts, to guide and to support treatment decisions, and to interrogate the clinical patients’ course as it develops. These maps should be patient-specific, with options displayed of possible treatment pathways. They would suggest the optimal care pathways, and the shortest routes to the most efficient care, by predicting clinical progress, testing the ensuing suggestions against the developing clinical state and patient condition, and suggesting new options as necessary. These maps should also mine an extensive database of accumulated patient data, modelled diseases, and modelled patient-responses based on expert-derived rules. These individualized hierarchical targets, which are implemented in order to prevent life-threatening illnesses, will also have to “adapt” to the patient’s altering clinical condition. Therapies that support one system can destabilize others and selecting which specific support to prioritize is an uncertain process, the prioritization of which can vary between clinical experts. Whilst clinical therapeutic decisions can be made with some degree of anticipation of the “likely” outcome (based on the experts’ opinion and judgment), treatment is essentially rooted in the present, and is dependent on analyzing the current clinical condition and available data. The recursive learning approach presented in this paper, allows decision rules to predict the possible future course, and reflects back derived information from such projections to the present time and thus support proactive clinical care rather than reactive clinical care. The proposed framework for such a patient map supports and enables an optimized choice from available options and also ensures that decisions are based on both the available evidence and a database of best clinical practice. Preliminary results are encouraging and it is hoped to validate the approach clinically in the near future.展开更多
目的将基于精细化管理的"6S管理"应用于神经外科重症监护室(Neurosurgical Intensive Care Unit,NICU)仪器设备中,优化NICU仪器设备管理流程,促进NICU仪器设备质量持续改进,同时提高全体人员的操作技能水平,进而更好地服务患...目的将基于精细化管理的"6S管理"应用于神经外科重症监护室(Neurosurgical Intensive Care Unit,NICU)仪器设备中,优化NICU仪器设备管理流程,促进NICU仪器设备质量持续改进,同时提高全体人员的操作技能水平,进而更好地服务患者。方法 2017年1月至2017年12月之间,在医院"三甲复审"仪器管理规定之上进一步建立仪器三级质控管理小组,并与"6S管理"以及"精细管理"有效结合。我们通过建立完善的管理制度及运用科学的管理方法,使NICU所有仪器设备在使用、维修、培训等各个环节形成标准化管理模式,并准确记录仪器故障、维修时限及医护人员使用仪器满意情况。结果实施后,医护人员使用仪器满意度由65.2%升至84.8%,仪器送修维修时间由8.3 d降至4.4 d,仪器设备故障率由31.5%降至18.2%,全科医务人员使用仪器技能及熟练程度明显提高,报废仪器数量也明显减少。结论基于精细化管理的"6S管理"管理模式,可最大限度保证仪器设备临床使用的安全性,同时可进行现场回顾,对存在问题及时整改,能够有效降低仪器故障发生率,缩短仪器维修时间,提高护士使用仪器的满意度,医护人员临床技能也明显提高。展开更多
文摘BACKGROUND Neonatal pain has been underdiagnosed due to several false beliefs.AIM To determine the status of neonatal pain in newborns who are admitted to intensive care units.METHODS Different databases were searched.Literature reviews and research reports conducted in newborns that were written in English,Spanish,or Portuguese,published between 2010 and 2020,and having free access to the full text were selected.A total of 135 articles were found,and 18 articles were finally reviewed.RESULTS Newborns are exposed to numerous painful procedures.In order to assess their pain levels,several scales have been used,although they are sometimes not correctly interpreted.In terms of pain management,the nursing team plays a very important role based mainly on both pharmacological and non-pharmacological approaches.CONCLUSION Nursing staff members must be well trained in order to identify pain and to interpret the scales correctly.Besides,they have an important role in performing non-pharmacological procedures for pain management.
文摘In this paper, we propose a new architecture that combines prediction and decision-making in the form of a hybrid framework aimed at providing clinicians with transparent and accurate maps, or charts, to guide and to support treatment decisions, and to interrogate the clinical patients’ course as it develops. These maps should be patient-specific, with options displayed of possible treatment pathways. They would suggest the optimal care pathways, and the shortest routes to the most efficient care, by predicting clinical progress, testing the ensuing suggestions against the developing clinical state and patient condition, and suggesting new options as necessary. These maps should also mine an extensive database of accumulated patient data, modelled diseases, and modelled patient-responses based on expert-derived rules. These individualized hierarchical targets, which are implemented in order to prevent life-threatening illnesses, will also have to “adapt” to the patient’s altering clinical condition. Therapies that support one system can destabilize others and selecting which specific support to prioritize is an uncertain process, the prioritization of which can vary between clinical experts. Whilst clinical therapeutic decisions can be made with some degree of anticipation of the “likely” outcome (based on the experts’ opinion and judgment), treatment is essentially rooted in the present, and is dependent on analyzing the current clinical condition and available data. The recursive learning approach presented in this paper, allows decision rules to predict the possible future course, and reflects back derived information from such projections to the present time and thus support proactive clinical care rather than reactive clinical care. The proposed framework for such a patient map supports and enables an optimized choice from available options and also ensures that decisions are based on both the available evidence and a database of best clinical practice. Preliminary results are encouraging and it is hoped to validate the approach clinically in the near future.
