RESUMO
Spinal anesthesia is an option for patients during total knee arthroplasty (TKA) procedures. Spinal anesthesia can offer advantages and disadvantages to the patient's experience and outcomes. We conducted an evidence-based, quality improvement project comparing mepivacaine 2% and isobaric bupivacaine 0.5% and retrospectively assessed specific intraoperative and postoperative outcomes that were of interest to the staff at the hospital where the project was completed. Primary outcome measures of interest included intraoperative heart rate, blood pressure, vasopressor use, fluid resuscitation, postoperative pain scores, use of opioid analgesic medications, and time to ambulation after administration of the spinal anesthetic. Compared with patients receiving isobaric bupivacaine 0.5% (n = 30), patients receiving mepivacaine 2% (n = 30) had greater intraoperative hemodynamic stability (defined as heart rate and blood pressure maintained within 20% of baseline values) during the first 30 minutes after anesthetic administration (P < .05 for multiple time points). They also required less opioid medication for postoperative pain management (25 vs 50 mcg fentanyl) and were able to ambulate sooner after the procedure (mean [standard deviation], 452.2 [218.5] vs 681.0 [476.6] minutes; P = .006). In conclusion, mepivacaine 2% was the higher-performing local primary spinal anesthetic for patients undergoing TKA.
Assuntos
Raquianestesia , Artroplastia do Joelho , Humanos , Bupivacaína , Mepivacaína/uso terapêutico , Raquianestesia/métodos , Estudos Retrospectivos , Anestésicos Locais , Dor Pós-Operatória/tratamento farmacológico , Dor Pós-Operatória/prevenção & controle , Analgésicos OpioidesRESUMO
Visualization is a Big Data method for detecting and validating previously unknown and hidden patterns within large data sets. This study used visualization techniques to discover and test novel patterns in public health nurse (PHN)-client-risk-intervention-outcome relationships. To understand the mechanism underlying risk reduction among high risk mothers, data representing complex social interventions were visualized in a series of three steps, and analyzed with other important contextual factors using standard descriptive and inferential statistics. Overall, client risk decreased after clients received personally tailored PHN services. Clinically important and unique PHN-client-risk-intervention-outcome patterns were discovered through pattern detection using streamgraphs, heat maps, and parallel coordinates techniques. Statistical evaluation validated that PHN intervention tailoring leads to improved client outcomes. The study demonstrates the importance of exploring data to discover ways to improve care quality and client outcomes. Further research is needed to examine additional factors that may influence PHN-client-risk-intervention-outcome patterns, and to test these methods with other data sets.
RESUMO
Big data are large volumes of digital data that can be collected from disparate sources and are challenging to analyze. These data are often described with the five "Vs": volume, velocity, variety, veracity, and value. Perioperative nurses contribute to big data through documentation in the electronic health record during routine surgical care, and these data have implications for clinical decision making, administrative decisions, quality improvement, and big data science. This article explores methods to improve the quality of perioperative nursing data and provides examples of how these data can be combined with broader nursing data for quality improvement. We also discuss a national action plan for nursing knowledge and big data science and how perioperative nurses can engage in collaborative actions to transform health care. Standardized perioperative nursing data has the potential to affect care far beyond the original patient.
Assuntos
Coleta de Dados/métodos , Registros Eletrônicos de Saúde , Enfermagem Perioperatória , Infecções Relacionadas a Cateter/epidemiologia , Tomada de Decisão Clínica , Coleta de Dados/normas , Atenção à Saúde , Documentação , Humanos , Transferência da Responsabilidade pelo Paciente , Úlcera por Pressão/epidemiologia , Melhoria de Qualidade , Infecções Urinárias/epidemiologia , Trombose VenosaRESUMO
Informatics is a new science within healthcare and anesthesia that leverages computer technology to improve patient safety, the quality of care provided, and workload efficiency. In clinical anesthesia practice, appropriate application of informatics promotes data standardization and integrity, and supports clinical decision-making. This article describes current issues in anesthesia information management to support the critical need for Certified Registered Nurse Anesthetists (CRNAs) to influence functionality, adoption, and use of an anesthesia information management system. The use of informatics tools and concepts should enable CRNAs to enhance their bedside vigilance, align their practice with evidence-based clinical guidelines, and provide cost-effective care for patients and healthcare systems.