Dataset Information

Transition from in-hospital ventilation to home ventilation: process description and quality indicators.

ABSTRACT: The current demographic development of our society results in an increasing number of elderly patients with chronic diseases being treated in the intensive care unit. A possible long-term consequence of such a treatment is that patients remain dependent on certain invasive organ support systems, such as long-term ventilator dependency. The main goal of this project is to define the transition process between in-hospital and out of hospital (ambulatory) ventilator support. A further goal is to identify evidence-based quality indicators to help define and describe this process. This project describes an ideal sequence of processes (process chain), based on the current evidence from the literature. Besides the process chain, key data and quality indicators were described in detail. Due to the limited project timeline, these indicators were not extensively tested in the clinical environment. The results of this project may serve as a solid basis for proof of feasibility and proof of concept investigations, optimize the transition process of ventilator-dependent patients from a clinical to an ambulatory setting, as well as reduce the rate of emergency re-admissions.

SUBMITTER: Kastrup M

PROVIDER: S-EPMC5738500 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transition from in-hospital ventilation to home ventilation: process description and quality indicators.

Kastrup Marc M Tittmann Benjamin B Sawatzki Tanja T Gersch Martin M Vogt Charlotte C Rosenthal Max M Rosseau Simone S Spies Claudia C

German medical science : GMS e-journal 20171219

The current demographic development of our society results in an increasing number of elderly patients with chronic diseases being treated in the intensive care unit. A possible long-term consequence of such a treatment is that patients remain dependent on certain invasive organ support systems, such as long-term ventilator dependency. The main goal of this project is to define the transition process between in-hospital and out of hospital (ambulatory) ventilator support. A further goal is to id ...[more]

PMID: 29308061

Similar Datasets

Project description:BackgroundResults of associations between process and mortality indicators, both used for the external assessment of hospital care quality or public reporting, differ strongly across studies. However, most of those studies were conducted in North America or United Kingdom. Providing new evidence based on French data could fuel the international debate on quality of care indicators and help inform French policy-makers. The objective of our study was to explore whether optimal care delivery in French hospitals as assessed by their Hospital Process Indicators (HPIs) is associated with low Hospital Standardized Mortality Ratios (HSMRs).MethodsThe French National Authority for Health (HAS) routinely collects for each hospital located in France, a set of mandatory HPIs. Five HPIs were selected among the process indicators collected by the HAS in 2009. They were measured using random samples of 60 to 80 medical records from inpatients admitted between January 1st, 2009 and December 31, 2009 in respect with some selection criteria. HSMRs were estimated at 30, 60 and 90 days post-admission (dpa) using administrative health data extracted from the national health insurance information system (SNIIR-AM) which covers 77% of the French population. Associations between HPIs and HSMRs were assessed by Poisson regression models corrected for measurement errors with a simulation-extrapolation (SIMEX) method.ResultsMost associations studied were not statistically significant. Only two process indicators were found associated with HSMRs. Completeness and quality of anesthetic records was negatively associated with 30 dpa HSMR (0.72 [0.52-0.99]). Early detection of nutritional disorders was negatively associated with all HSMRs: 30 dpa HSMR (0.71 [0.54-0.95]), 60 dpa HSMR (0.51 [0.39-0.67]) and 90 dpa HSMR (0.52 [0.40-0.68]).ConclusionIn absence of gold standard of quality of care measurement, the limited number of associations suggested to drive in-depth improvements in order to better determine associations between process and mortality indicators. A smart utilization of both process and outcomes indicators is mandatory to capture aspects of the hospital quality of care complexity.

Project description:Reporting the results of quality indicators can narrow the gap in the quality of care between hospitals. While most studies rely on outcome indicators, they may not accurately measure the quality of care. Process indicators are not only strongly associated with treatment outcomes, but are also more sensitive to whether patients are treated accurately, enabling timely intervention. Our study aims to investigate whether process indicators provide a more reasonable assessment of hospital quality of care compared to outcome indicators. Data were sourced from the Specific Disease Medical Service Quality Management and Control System in China. A total of 113,942 patients with breast cancer treated in 298 hospitals between January 2019 and April 2023 were included in this retrospective study. The rankability of 11 process indicators was calculated and used as a weight to create a new composite indicator. The composite indicators and outcome measures were compared using the O/E ratio categories. Finally, in order to determine the impact of different years on the results, a sensitivity analysis was conducted using bootstrap sampling. The rankability ( ρ ) values of the eleven process indicators showed significant differences, with the highest ρ value for preoperative cytological or histological examination before surgery (0.919). The ρ value for the outcome indicator was 0.011. The rankability-weighting method yielded a comprehensive score ( ρ = 0.883). The comparison with categorical results of the outcome indicator has different performance classifications for 113 hospitals (37.92%) for composite scores and 140 (46.98%) for preoperative cytological or histological examinationbefore surgery. Process indicators are more suitable than outcome indicators for assessing the quality of breast cancer care in hospitals. Healthcare providers can use process indicators to identify specific areas for improvement, thereby driving continuous quality improvement efforts.

Project description:IntroductionFrailty in Older people: Rehabilitation, Treatment, Research Examining Separate Settings (the FORTRESS study) is a multisite, hybrid type II, stepped wedge, cluster, randomised trial examining the uptake and outcomes of a frailty intervention. The intervention is based on the 2017 Asia Pacific Clinical Practice Guidelines for the Management of Frailty and begins in the acute hospital setting and transitions to the community. The success of the intervention will require individual and organisational behaviour change within a dynamic health system. This process evaluation will examine the multiple variables at play in the context and mechanism of the frailty intervention to enhance understanding of the outcomes of the FORTRESS study and how the outcomes can be translated from the trial into broader practice.Methods and analysisThe FORTRESS intervention will recruit participants from six wards in New South Wales and South Australia, Australia. Participants of the process evaluation will include trial investigators, ward-based clinicians, FORTRESS implementation clinicians, general practitioners and FORTRESS participants. The process evaluation has been designed using realist methodology and will occur in parallel to the FORTRESS trial. A mixed-method approach will be used with qualitative and quantitative data collected from interviews, questionnaires, checklists and outcome assessments. Qualitative and quantitative data will be examined for CMOCs (Context, Mechanism, Outcome Configurations) and programme theories will be developed, tested and refined. This will facilitate development of more generalisable theories to inform translation of frailty intervention within complex healthcare systems.Ethics and disseminationEthical approval for the FORTRESS trial, inclusive of the process evaluation, has been obtained from the Northern Sydney Local Health District Human Research Ethics Committees reference number 2020/ETH01057. Recruitment for the FORTRESS trial uses opt-out consent. Dissemination will be via publications, conferences and social media.Trial registration numberACTRN12620000760976p (FORTRESS trial).

Dataset Information

Transition from in-hospital ventilation to home ventilation: process description and quality indicators.

Publications

Transition from in-hospital ventilation to home ventilation: process description and quality indicators.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets