Caring for critically ill patients outside intensive care units due to full units: a cohort study.

OBJECTIVES: This study sought to analyze the clinical and epidemiologic characteristics of critically ill patients who were denied intensive care unit admission due to the unavailability of beds and to estimate the direct costs of treatment. METHODS: A prospective cohort study was performed with critically ill patients treated in a university hospital. All consecutive patients denied intensive care unit beds due to a full unit from February 2012 to February 2013 were included. The data collected included clinical data, calculation of costs, prognostic scores, and outcomes. The patients were followed for data collection until intensive care unit admission or cancellation of the request for the intensive care unit bed. Vital status at hospital discharge was noted, and patients were classified as survivors or non-survivors considering this endpoint. RESULTS: Four hundred and fifty-four patients were analyzed. Patients were predominantly male (54.6%), and the median age was 62 (interquartile range (ITQ): 47 - 73) years. The median APACHE II score was 22.5 (ITQ: 16 - 29). Invasive mechanical ventilation was used in 298 patients (65.6%), and vasoactive drugs were used in 44.9% of patients. The median time of follow-up was 3 days (ITQ: 2 - 6); after this time, 204 patients were admitted to the intensive care unit and 250 had the intensive care unit bed request canceled. The median total cost per patient was US$ 5,945.98. CONCLUSIONS: Patients presented a high severity in terms of disease scores, had multiple organ dysfunction and needed multiple invasive therapeutic interventions. The study patients received intensive care with specialized consultation during their stay in the hospital wards and presented high costs of treatment.

Caring for critically ill patients outside intensive care units due to full units: a cohort study

OBJECTIVES: This study sought to analyze the clinical and epidemiologic characteristics of critically ill patients who were denied intensive care unit admission due to the unavailability of beds and to estimate the direct costs of treatment. METHODS: A prospective cohort study was performed with critically ill patients treated in a university hospital. All consecutive patients denied intensive care unit beds due to a full unit from February 2012 to February 2013 were included. The data collected included clinical data, calculation of costs, prognostic scores, and outcomes. The patients were followed for data collection until intensive care unit admission or cancellation of the request for the intensive care unit bed. Vital status at hospital discharge was noted, and patients were classified as survivors or non-survivors considering this endpoint. RESULTS: Four hundred and fifty-four patients were analyzed. Patients were predominantly male (54.6%), and the median age was 62 (interquartile range (ITQ): 47 - 73) years. The median APACHE II score was 22.5 (ITQ: 16 - 29). Invasive mechanical ventilation was used in 298 patients (65.6%), and vasoactive drugs were used in 44.9% of patients. The median time of follow-up was 3 days (ITQ: 2 - 6); after this time, 204 patients were admitted to the intensive care unit and 250 had the intensive care unit bed request canceled. The median total cost per patient was US$ 5,945.98. CONCLUSIONS: Patients presented a high severity in terms of disease scores, had multiple organ dysfunction and needed multiple invasive therapeutic interventions. The study patients received intensive care with specialized consultation during their stay in the hospital wards and presented high costs of treatment.

Relationship of Hospital Costs With Mortality in Pediatric Critical Care: A Multi-Institutional Analysis.

OBJECTIVE: With increasing emphasis on high "value" care, we designed this study to evaluate the relationship between hospital costs and patient outcomes in pediatric critical care. DESIGN: Post hoc analysis of data from an existing administrative national database, Pediatric Health Information Systems. Multivariable mixed effects logistic regression models were fitted to evaluate association of hospital cost tertiles with odds of mortality after adjusting for patient and center characteristics. SETTING: Forty-seven children's hospitals across the United States. PATIENTS: Patients 18 years old or younger admitted to a PICU at a Pediatric Health Information Systems participating hospital were included (2004-2015). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 917,663 patients from 47 hospitals were included. Median cost per patient was $42,181 in the low-cost hospitals (341,689 patients, 16 hospitals), $56,806 in the middle-cost hospitals (310,293 patients, 16 hospitals), and $82,588 in the high-cost hospitals (265,681 patients, 15 hospitals). In unadjusted analysis, patients cared for in the high-cost tertile hospitals were younger in age, associated with more comorbidities, had higher resource utilization (including extracorporeal membrane oxygenation and nitric oxide), had higher prevalence of cardiac arrest, and were associated with worse outcomes (including mortality). In adjusted analysis, high-cost tertile hospitals were not associated with improved mortality, when compared with low- and medium-cost tertile hospitals (low cost vs high cost: odds ratio, 0.99; 95% CI, 0.79-1.25 and middle cost vs high cost: odds ratio, 1.10; 95% CI, 0.86-1.41). When stratified by diagnoses category, we noted similar trends among cardiac and noncardiac patients. CONCLUSIONS: This large observational study did not demonstrate any relationship between hospital costs and patient outcomes in children with critical illness. Further efforts are needed to evaluate quality-cost relationship and high value care in critically ill children across centers of varying volume by linking data from clinical and administrative databases.

Financial and Social Hardships in Families of Children with Medical Complexity.

OBJECTIVE: To describe hardships experienced by families of children with medical complexity (CMC) and compare them with those experienced by families of children with asthma. STUDY DESIGN: We assessed hardships in a cohort of 167 families of CMC. Surveys assessed sociodemographics and hardships (eg, financial: inability to pay bills; social: limited help from family/friends). CMC cohort hardships were compared with those of an established cohort of children hospitalized with asthma using multivariable logistic regression. RESULTS: CMC had diagnoses in a median of 5 different complex chronic condition categories (most common neurologic/neuromuscular), and the majority (74%) were dependent on technology. Over 80% of families of CMC reported experiencing ≥1 hardship; 68% with financial and 46% with social hardship. Despite higher socioeconomic status than families with asthma, families of CMC often experienced more hardships. For example, families of CMC were significantly more likely to report failure to pay rent/mortgage (aOR 2.6, 95% CI 1.6, 4.3) and the expectation of little to no help from family/friends (aOR 2.9, 95% CI 1.9, 4.7). CONCLUSIONS: Families of CMC frequently report financial and social hardships, often at rates higher than families with asthma who were generally of lower socioeconomic status. Identifying and acting upon hardships may be an important addition to the care of CMC.

Prediction of chronic critical illness in a general intensive care unit / Predição de doença crítica crônica em uma unidade geral de cuidados intensivos resumo

OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score < 15, inadequate calorie intake, and higher body mass index were independent predictors for cci in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI.

OBJETIVO: Avaliar a incidência, custos e mortalidade relacionados a doença crítica crônica (DCC) e identificar seus preditores clínicos em uma unidade de terapia intensiva geral. MÉTODOS: Trata-se de uma coorte observacional prospectiva. Todos pacientes que recebiam tratamento de suporte por mais de 20 dias eram considerados doentes críticos crônicos. Permaneceram 453 pacientes após a aplicação dos critérios de exclusão. RESULTADOS: A incidência de DCC foi de 11%. Permanência hospitalar, custos e mortalidade foram significativamente maiores na população com DCC. Ventilação mecânica, sepse, Glasgow escore < 15, inadequada ingestão calórica e elevado índice de massa corporal foram preditores independentes para dcc em um modelo multivariado de regressão logística. CONCLUSÃO: DCC abrangeumadistintapopulaçãonasunidadesde terapiaintensiva apresentando maiores mortalidade, custos e permanência hospitalar. Alguns fatores presentes na admissão ou durante a primeira semana na unidade de terapia intensiva podem ser usados como preditores de DCC.

Prediction of chronic critical illness in a general intensive care unit.

OBJECTIVE: To assess the incidence, costs, and mortality associated with chronic critical illness (CCI), and to identify clinical predictors of CCI in a general intensive care unit. METHODS: This was a prospective observational cohort study. All patients receiving supportive treatment for over 20 days were considered chronically critically ill and eligible for the study. After applying the exclusion criteria, 453 patients were analyzed. RESULTS: There was an 11% incidence of CCI. Total length of hospital stay, costs, and mortality were significantly higher among patients with CCI. Mechanical ventilation, sepsis, Glasgow score <15, inadequate calorie intake, and higher body mass index were independent predictors for CCI in the multivariate logistic regression model. CONCLUSIONS: CCI affects a distinctive population in intensive care units with higher mortality, costs, and prolonged hospitalization. Factors identifiable at the time of admission or during the first week in the intensive care unit can be used to predict CCI.

Costs of patients under nutritional therapy: from prescription to discharge.

PURPOSE OF REVIEW: This review will discuss the financial cost of the decisions taken regarding the nutritional therapy of hospitalized patients compared with those treated at home. To facilitate comprehension, the authors present a concise introduction to the general concepts of economic health studies, including a glossary of technical terms. RECENT FINDINGS: From a revision of the literature, economic aspects are underscored involving the cost of malnutrition, the maintenance of work in a nutritional support team, the use of nutritional therapy in home-care programmes, and in the use of nutritional therapy as a prophylactic action against surgical complications. SUMMARY: Hospital malnutrition burdens the system financially by provoking a higher rate of surgical complications, mortality and longer hospital stays. Investment in nutritional therapy provides economic returns. The cost of the creation and maintenance of the nutritional support team is easily offset by the resources generated by the team itself. Nutritional therapy in home-care is highly advantageous. In Brazilian trials, groups of surgical patients receiving nutritional therapy within the integrated hospital-home model demonstrated a cost 2.6 times less than the conventional group (exclusively intra-hospital treatment). The adoption of preoperative immunomodulatory nutritional therapy in patients undergoing elective surgery as a prophylactic against postoperative surgical complications presented a 2.24 times reduction in the total treatment cost. The search for the ideal model of nutritional therapy is based on the binomial of quality and cost. The prescription of nutritional therapy has a favourable impact on financial and resource-generating aspects of the institution, when practised by properly trained groups.