RESUMO
OBJECTIVE: To determinate the adherence and barriers of our early mobilization protocol in patients who had received mechanical ventilation >48h in routine daily practice through clinical information system during all Intensive Care Unit (ICU) stay. DESIGN: Observational and prospective cohort study. SETTING: Polyvalent ICU over a three-year period (2017-2019). PATIENTS: Adult patients on mechanical ventilation >48h who met the inclusion criteria for the early mobilization protocol. INTERVENTIONS: None. MAIN VARIABLES OF INTEREST: Demographics, adherence to the protocol and putative hidden adherence, total number of mobilizations, barriers, artificial airway/ventilatory support at each mobilization level and adverse events. RESULTS: We analyzed 3269 stay-days from 388 patients with median age of 63 (51-72) years, median APACHE II 23 (18-29) and median ICU stay of 10.1 (6.2-16.5) days. Adherence to the protocol was 56.6% (1850 stay-days), but patients were mobilized in only 32.2% (1472) of all stay-days. The putative hidden adherence was 15.6% (509 stay-days) which would increase adherence to 72.2%. The most common reasons for not mobilizing patients were failure to meeting the criteria for clinical stability in 241 (42%) stay-days and unavailability of physiotherapists in 190 (33%) stay-days. Adverse events occurred in only 6 (0.4%) stay-days. CONCLUSIONS: Data form Clinical Information System showed although adherence was high, patients were mobilized in only one-third of all stay-days. Knowing the specific reason why patient were not mobilized in each stay-day allow to develop concrete decisions to increase the number of mobilizations.
Assuntos
Deambulação Precoce , Unidades de Terapia Intensiva , Adulto , Humanos , Pessoa de Meia-Idade , Idoso , Estudos Prospectivos , Deambulação Precoce/métodos , Tempo de Internação , Sistemas de Informação , Estudos Observacionais como AssuntoRESUMO
OBJECTIVES: To extract data from clinical information systems to automatically calculate high-resolution quality indicators to assess adherence to recommendations for low tidal volume. DESIGN: We devised two indicators: the percentage of time under mechanical ventilation with excessive tidal volume (>8mL/kg predicted body weight) and the percentage of patients who received appropriate tidal volume (≤8mL/kg PBW) at least 80% of the time under mechanical ventilation. We developed an algorithm to automatically calculate these indicators from clinical information system data and analyzed associations between them and patients' characteristics and outcomes. SETTINGS: This study has been carried out in our 30-bed polyvalent intensive care unit between January 1, 2014 and November 30, 2019. PATIENTS: All patients admitted to intensive care unit ventilated >72h were included. INTERVENTION: Use data collected automatically from the clinical information systems to assess adherence to tidal volume recommendations and its outcomes. MAIN VARIABLES OF INTEREST: Mechanical ventilation days, ICU length of stay and mortality. RESULTS: Of all admitted patients, 340 met the inclusion criteria. Median percentage of time under mechanical ventilation with excessive tidal volume was 70% (23%-93%); only 22.3% of patients received appropriate tidal volume at least 80% of the time. Receiving appropriate tidal volume was associated with shorter duration of mechanical ventilation and intensive care unit stay. Patients receiving appropriate tidal volume were mostly male, younger, taller, and less severely ill. Adjusted intensive care unit mortality did not differ according to percentage of time with excessive tidal volume or to receiving appropriate tidal volume at least 80% of the time. CONCLUSIONS: Automatic calculation of process-of-care indicators from clinical information systems high-resolution data can provide an accurate and continuous measure of adherence to recommendations. Adherence to tidal volume recommendations was associated with shorter duration of mechanical ventilation and intensive care unit stay.