Innovando en la toma de decisiones compartida con pacientes hospitalizados: descripción y evaluación de una herramienta de registro de nivel de intensidad terapéutica / Improving shared decision-making for hospital patients: description and evaluation of a treatment intensity assessment tool

Fundamento y objetivo. La toma de decisiones compartida entre pacientes y profesionales es un elemento clave de la atención centrada en la persona y tiene como objetivo facilitar la adecuada armonización entre los valores y preferencias de los pacientes, los objetivos asistenciales propuestos y la intensidad de las intervenciones realizadas. Pero tan importante como velar por la calidad de este proceso colaborativo es poder disponer de sistemas que permitan registrarlo de forma fiable y sencilla, con el objetivo de preservar la coherencia en las decisiones durante el proceso asistencial. El presente estudio describe un sistema de registro de nivel de intensidad terapéutica (NIT) diseñada para tal fin y evalúa los resultados de su implementación. Material y método. Se comparan los resultados pre-implementación y post-implementación en 2 cohortes de pacientes registrados durante un período de un mes, respectivamente. Resultados. El 6,1% de los pacientes del grupo pre-implementación (n = 673) tienen algún registro de nivel asistencial, frente al 31,6% del grupo post-implementación (n = 832) (p < 0,01), existiendo diferencias entre servicios. La mortalidad intrahospitalaria de ambas cohortes es del 1,9%; el 93,75% de los pacientes del grupo post-implementación que fallecieron tenían registro de NIT. Conclusiones. La disponibilidad de una herramienta hospitalaria específica parece incentivar el proceso de toma de decisiones compartidas entre pacientes y profesionales —multiplicando por más de 5 veces el registro de NIT—, facilita la continuidad asistencial entre equipos y permite monitorizar la personalización de las intervenciones. Serán necesarios más estudios para seguir avanzando en la toma de decisiones compartida con los pacientes hospitalizados (AU)

Background and aim. Shared decision-making between patients and healthcare professionals is crucial to guarantee adequate coherence between patient values and preferences, caring aims and treatment intensity, which is key for the provision of patient-centred healthcare. The assessment of such interventions are essential for caring continuity purposes. To do this, reliable and easy-to-use assessment systems are required. This study describes the results of the implementation of a hospital treatment intensity assessment tool. Material and methods. The pre-implementation and post-implementation results were compared between two cohorts of patients assessed for one month. Results. Some record of care was registered in 6.1% of patients in the pre-implementation group (n = 673) compared to 31.6% of patients in the post-implementation group (n = 832) (P < .01), with differences between services. Hospital mortality in both cohorts is 1.9%; in the pre-implementation group, 93.75% of deceased patients had treatment intensity assessment. Conclusions. In hospital settings, the availability of a specific tool seems to encourage very significantly shared decision-making processes between patients and healthcare professionals —multiplying by more than 5 times the treatment intensity assessment. Moreover, such tools help in the caring continuity processes between different teams and the personalisation of caring interventions to be monitored. More research is needed to continue improving shared decision-making for hospital patients (AU)

[Improving shared decision-making for hospital patients: Description and evaluation of a treatment intensity assessment tool]. / Innovando en la toma de decisiones compartida con pacientes hospitalizados: descripción y evaluación de una herramienta de registro de nivel de intensidad terapéutica.

BACKGROUND AND AIM: Shared decision-making between patients and healthcare professionals is crucial to guarantee adequate coherence between patient values and preferences, caring aims and treatment intensity, which is key for the provision of patient-centred healthcare. The assessment of such interventions are essential for caring continuity purposes. To do this, reliable and easy-to-use assessment systems are required. This study describes the results of the implementation of a hospital treatment intensity assessment tool. MATERIAL AND METHODS: The pre-implementation and post-implementation results were compared between two cohorts of patients assessed for one month. RESULTS: Some record of care was registered in 6.1% of patients in the pre-implementation group (n=673) compared to 31.6% of patients in the post-implementation group (n=832) (P<.01), with differences between services. Hospital mortality in both cohorts is 1.9%; in the pre-implementation group, 93.75% of deceased patients had treatment intensity assessment. CONCLUSIONS: In hospital settings, the availability of a specific tool seems to encourage very significantly shared decision-making processes between patients and healthcare professionals -multiplying by more than 5 times the treatment intensity assessment. Moreover, such tools help in the caring continuity processes between different teams and the personalisation of caring interventions to be monitored. More research is needed to continue improving shared decision-making for hospital patients.

Relationship between volume and survival in closed intensive care units is weak and apparent only in mechanically ventilated patients.

BACKGROUND: Recent studies have found an association between increased volume and increased intensive care unit (ICU) survival; however, this association might not hold true in ICUs with permanent intensivist coverage. Our objective was to determine whether ICU volume correlates with survival in the Spanish healthcare system. METHODS: Post hoc analysis of a prospective study of all patients admitted to 29 ICUs during 3 months. At ICU discharge, the authors recorded demographic variables, severity score, and specific ICU treatments. Follow-up variables included ICU readmission and hospital mortality. Statistics include logistic multivariate analyses for hospital mortality according to quartiles of volume of patients. RESULTS: The authors studied 4,001 patients with a mean predicted risk of death of 23% (range at hospital level: 14-46%). Observed hospital mortality was 19% (range at hospital level: 11-35%), resulting in a standardized mortality ratio of 0.81 (range: 0.5-1.3). Among the 1,923 patients needing mechanical ventilation, the predicted risk of death was 32% (14-60%) and observed hospital mortality was 30% (12-61%), resulting in a standardized mortality ratio of 0.96 (0.5-1.7). The authors found no correlation between standardized mortality ratio and ICU volume in the entire population or in mechanically ventilated patients. Only mechanically ventilated patients in very low-volume ICUs had slightly worse outcome. CONCLUSION: In the currently studied healthcare system characterized by 24/7 intensivist coverage, the authors found wide variability in outcome among ICUs even after adjusting for severity of illness but no relationship between ICU volume and outcome. Only mechanically ventilated patients in very low-volume centers had slightly worse outcomes.

Community-acquired respiratory coinfection in critically ill patients with pandemic 2009 influenza A(H1N1) virus.

BACKGROUND: Little is known about the impact of community-acquired respiratory coinfection in patients with pandemic 2009 influenza A(H1N1) virus infection. METHODS: This was a prospective, observational, multicenter study conducted in 148 Spanish ICUs. RESULTS: Severe respiratory syndrome was present in 645 ICU patients. Coinfection occurred in 113 (17.5%) of patients. Streptococcus pneumoniae (in 62 patients [54.8%]) was identified as the most prevalent bacteria. Patients with coinfection at ICU admission were older (47.5±15.7 vs 43.8±14.2 years, P<.05) and presented a higher APACHE (Acute Physiology and Chronic Health Evaluation) II score (16.1±7.3 vs 13.3±7.1, P<.05) and Sequential Organ Failure Assessment (SOFA) score (7.0±3.8 vs 5.2±3.5, P<.05). No differences in comorbidities were observed. Patients who had coinfection required vasopressors (63.7% vs 39.3%, P<.05) and invasive mechanical ventilation (69% vs 58.5%, P<.05) more frequently. ICU length of stay was 3 days longer in patients who had coinfection than in patients who did not (11 [interquartile range, 5-23] vs 8 [interquartile range 4-17], P=.01). Coinfection was associated with increased ICU mortality (26.2% vs 15.5%; OR, 1.94; 95% CI, 1.21-3.09), but Cox regression analysis adjusted by potential confounders did not confirm a significant association between coinfection and ICU mortality. CONCLUSIONS: During the 2009 pandemics, the role played by bacterial coinfection in bringing patients to the ICU was not clear, S pneumoniae being the most common pathogen. This work provides clear evidence that bacterial coinfection is a contributor to increased consumption of health resources by critical patients infected with the virus and is the virus that causes critical illness in the vast majority of cases.