Does Transfer to Intensive Care Units Reduce Mortality? A Comparison of an Instrumental Variables Design to Risk Adjustment

Keele, Luke; Harris, Steve; Grieve, Richard

doi:10.1097/mlr.0000000000001093

Cited by 12 publications

(9 citation statements)

References 34 publications

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“…Notably, the effect of the instrumental variable on the dependent measure should be entirely mediated via its effect on exposure assignment. In ICU settings, previously used instrumental variables consisted of the bed availability at the time of assessment for ICU transfer [22,23] or the physician's main specialisation [24]. Unfortunately, such instruments were not measured in our study.…”

Section: Discussionmentioning

confidence: 99%

Diagnosis and outcome of acute respiratory failure in immunocompromised patients after bronchoscopy

et al. 2019

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ObjectiveWe wished to explore the use, diagnostic capability and outcomes of bronchoscopy added to noninvasive testing in immunocompromised patients. In this setting, an inability to identify the cause of acute hypoxaemic respiratory failure is associated with worse outcome. Every effort should be made to obtain a diagnosis, either with noninvasive testing alone or combined with bronchoscopy. However, our understanding of the risks and benefits of bronchoscopy remains uncertain.Patients and methodsThis was a pre-planned secondary analysis of Efraim, a prospective, multinational, observational study of 1611 immunocompromised patients with acute respiratory failure admitted to the intensive care unit (ICU). We compared patients with noninvasive testing only to those who had also received bronchoscopy by bivariate analysis and after propensity score matching.ResultsBronchoscopy was performed in 618 (39%) patients who were more likely to have haematological malignancy and a higher severity of illness score. Bronchoscopy alone achieved a diagnosis in 165 patients (27% adjusted diagnostic yield). Bronchoscopy resulted in a management change in 236 patients (38% therapeutic yield). Bronchoscopy was associated with worsening of respiratory status in 69 (11%) patients. Bronchoscopy was associated with higher ICU (40% versus 28%; p<0.0001) and hospital mortality (49% versus 41%; p=0.003). The overall rate of undiagnosed causes was 13%. After propensity score matching, bronchoscopy remained associated with increased risk of hospital mortality (OR 1.41, 95% CI 1.08–1.81).ConclusionsBronchoscopy was associated with improved diagnosis and changes in management, but also increased hospital mortality. Balancing risk and benefit in individualised cases should be investigated further.

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Section: Discussionmentioning

confidence: 99%

Diagnosis and outcome of acute respiratory failure in immunocompromised patients after bronchoscopy

et al. 2019

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“…During data collection, ICU bed availability at the time of assessment for ICU admission was measured for use as an instrument for ICU transfer. [28][29][30][31] That is, if there are few ICU beds available when the patient is assessed, this discourages ICU transfer. In the data, ICU bed availability ranges from 0 to 19 with a median of 4 and an IQR of 4.…”

Section: Application: Is Bed Availability a Valid Instrument For Icu ...mentioning

confidence: 99%

“…Following an earlier analysis, we use a binary measure of the instrument where 1 indicates that fewer than 4 ICU beds were available. 29 The exposure is defined as transfer to and receipt of care in the ICU. Measured confounders include age, gender, septic diagnosis (0/1), and peri-arrest (0/1).…”

Section: Application: Is Bed Availability a Valid Instrument For Icu ...mentioning

confidence: 99%

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Evaluating A Key Instrumental Variable Assumption Using Randomization Tests

Branson¹,

Keele²

2019

Preprint

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Instrumental variable (IV) analyses are becoming common in health services research and epidemiology. Most IV analyses use naturally occurring instruments, such as distance to a hospital. In these analyses, investigators must assume the instrument is as-if randomly assigned. This assumption cannot be tested directly, but it can be falsified. Most falsification tests in the literature compare relative prevalence or bias in observed covariates between the instrument and the exposure. These tests require investigators to make a covariate-by-covariate judgment about the validity of the IV design. Often, only some of the covariates are well-balanced, making it unclear if as-if randomization can be assumed for the instrument across all covariates. We propose an alternative falsification test that compares IV balance or bias to the balance or bias that would have been produced under randomization. A key advantage of our test is that it allows for global balance measures as well as easily interpretable graphical comparisons. Furthermore, our test does not rely on any parametric assumptions and can be used to validly assess if the instrument is significantly closer to being as-if randomized than the exposure. We demonstrate our approach on a recent IV application that uses bed availability in the intensive care unit (ICU) as an instrument for admission to the ICU.

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“…Unsurprisingly, patients who undergo emergency operative treatment are often the sickest patients (Shafi et al 2013). While statistical adjustment for measures of patient frailty may render treated and control groups comparable, such adjustments are often insufficient due to both inadequacies in observed covariates and the potential presence of hidden biases (Keele et al 2019a). Faced with such biases, one alternative is to search for "natural experiments" where an intervention is judged to be allocated in an asif random fashions.…”

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confidence: 99%

Biased Encouragements and Heterogeneous Effects in an Instrumental Variable Study of Emergency General Surgical Outcomes

Fogarty¹,

Lee²,

Kelz³

et al. 2019

Preprint

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Instrumental variable (IV) studies seek to emulate randomized encouragement designs where patients are assigned a random nudge towards a particular treatment. Unfortunately, IV studies may fall short of their experimental ideal due to hidden bias affecting both the proposed instrument and the outcomes. While sensitivity analyses have been developed for IV designs most proceed under an assumption of effect homogeneity, unlikely to hold for many applications. In our case study on the efficacy of surgical versus non-surgical management for two gastrointestinal tract conditions, whether or not surgery will be of greatest benefit strongly depends upon patient-specific physiology. The validity of our proposed instrument, surgeons' tendencies to operate, is plausible but not ironclad, necessitating a sensitivity analysis allowing for effect variation. We present a new sensitivity analysis accommodating arbitrary patterns of non-identified effect heterogeneity. With binary outcomes, we prove that the conventional sensitivity analysis based on McNemar's test is itself asymptotically valid with heterogeneous effects. We then demonstrate that the identified components of effect heterogeneity can, when suitably exploited, improve the performance of a sensitivity analysis through providing less conservative standard error estimators. We further highlight the importance of heterogeneity in determining the power of a sensitivity analysis.

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Does Transfer to Intensive Care Units Reduce Mortality? A Comparison of an Instrumental Variables Design to Risk Adjustment

Abstract: Does transfer to intensive care units reduce mortality? A comparison of an instrumental variables design to risk adjustment.

Cited by 12 publications

References 34 publications

Diagnosis and outcome of acute respiratory failure in immunocompromised patients after bronchoscopy

Diagnosis and outcome of acute respiratory failure in immunocompromised patients after bronchoscopy

Evaluating A Key Instrumental Variable Assumption Using Randomization Tests

Biased Encouragements and Heterogeneous Effects in an Instrumental Variable Study of Emergency General Surgical Outcomes

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