Mortality and functional outcomes in intensive care

By Alex Yartsev - Apr 14, 2017

As one attempts to asses the outcomes of critically ill patients, one is confronted by the question of how to measure them, and which ones are important. A range of options exist. For instance, one may measure "hard" outcomes (mortality) - a straightforward metric which can be collected at different time intervals. Alternatively, one may collect "POEM" data (Patient Oriented Endpoint that Matters) which is more interested in quality of life, functional status and other more subjective issues like "satisfaction".

Question 25 from the first paper of 2013 asked the trainees to discuss the advantages and limitations of commonly used endpoints as a measure of quality of critical care. A question like this probably lends itself better to a tabulated answer, and so I went ahead and tabulated it (the table is made available below, and is identical to the table in the discussion section of Question 25).

Possible reading material for this topic may include the following resources:

The LITFL article on this topic is probably enough for the time-poor candidate
A good discussion of "at what point do we measure mortality" can be found at the AIHW statement on Measuring and reporting mortality in hospital patients (page 6, ch. 2.4.2).
As a good guideline for other ICU outcome measures which should be used to assess the outcomes of Phase II trials, ANZICS has published this statement in 2012 (the 2013 update is for some reason not available for free).
A good discussion of ICU outcome measures and some of their limitations can also be found in the 1999 workshop publication of the American Thoracic Society.

As an interesting aside, a recent (2016) report by Turbull et al remarked that "peer-reviewed publications reporting patient outcomes after hospital discharge for ICU survivors have grown from 3 in the 1970s to more than 300 since 2000", and complained that "the ability to compare results across studies remains impaired by the 250 different instruments used" which means that virtually every second study used a different instrument (in total 425 eligible articles were reviewed).

A Comparison of Outcome Measures in Intensive Care Research
Outcome measure	Advantages	Disadvantages
ICU mortality	Mortality is simple and cheap to measure It is an important outcome measure It is already being recorded in hospital databases It can be used to track the performance of an ICU, as it may detect true deficiencies in quality of care	The definition of "ICU" is different across different hospitals ICU mortality neglects the influence of pre-hospital and emergency medical care on mortality Perimortem patients can be discharged from the ICU before they die, thus "shifting" the statistics out into the hospital wards. Selection of low-risk patients in order to improve the statistics for mortality is known among cardiac surgeons. Conversely, critically ill peri-mortem patients can be transferred to the ICU, increasing ICU mortality, thus shifting the mortality statistic into the ICU. This is called "transfer bias". Mortality does not necessarily equate with quality of care - some patients receive good-quality appropriate palliation in ICU
Hospital mortality	Avoids the statistic-skewing practice of discharging palliated patients out of ICU Avoids the problem posed by different definitions of what an "ICU" is. Reflects the performance of the whole hospital, rather than just the ICU Reasonable surrogate for 90day mortality	Many effects of hospital care on mortality do not become evident until after discharge from hospital Like ICUs, hospitals may discharge poor prognosis patients home, thus reducing in-hospital mortality artificially Hospital mortality as a measure of ICU care quality brings in confounders- ward care might negatively influence outcomes after ICU discharge Mortality is not a surrogate for functional outcome - hospitals may discharge patients who are alive, but who are in a state of severe functional impairment (eg. persistent vegetative state).
90-day mortality	Avoids the statistic-skewing practice of discharging palliated patients out of ICU and out of hospital Easy to measure through the record of births and deaths	The 90 day timeline is completely arbitrary 90 days may not be an adequate duration during which the full effects of ICU and hospital care manifest themselves Some patients may be lost to follow-up Confounders such as quality of home care and community follow-up are introduced, which affect mortality
1-year functional outcome	Patient-centered outcome measure (i.e. it matters to the patients) A more accurate estimate of the long-term health cost of critical illness	Scoring systems of functional outcome are not without their flaws Functional outcome scores may score some functional domains better than others, and broadly speaking they all have poor validity. Much of the time focus is on respiratory and cardiovascular function surrogate measures (such as exercise tolerance and FEV₁) Some patients may be lost to follow-up This sort of data collection is neither cheap not easy This is an invasive data collection technique - patients need to be contacted 1 year after their diascharge, which may be an unethical invasion of their privacy for the purposes of research The natural history of the disease acts as a confounder, as it may influence functional outcome. The influence of ICU care and hospital care may become obscured by the progression of the disease.

References

Young, Paul, et al. "End points for phase II trials in intensive care: Recommendations from the Australian and New Zealand clinical trials group consensus panel meeting." Critical Care and Resuscitation 15.3 (2013): 211. - this one is not available for free, but the 2012 version still is:

Young, Paul, et al. "End points for phase II trials in intensive care: recommendations from the Australian and New Zealand Clinical Trials Group consensus panel meeting." Critical Care and Resuscitation 14.3 (2012): 211.

Suter, P., et al. "Predicting outcome in ICU patients." Intensive Care Medicine20.5 (1994): 390-397.

Martinez, Elizabeth A., et al. "Identifying Meaningful Outcome Measures for the Intensive Care Unit." American Journal of Medical Quality (2013): 1062860613491823.

Tipping, Claire J., et al. "A systematic review of measurements of physical function in critically ill adults." Critical Care and Resuscitation 14.4 (2012): 302.

Gunning, Kevin, and Kathy Rowan. "Outcome data and scoring systems." Bmj319.7204 (1999): 241-244.

Woodman, Richard, et al. Measuring and reporting mortality in hospital patients. Australian Institute of Health and Welfare, 2009.

Vincent, J-L. "Is Mortality the Only Outcome Measure in ICU Patients?."Anaesthesia, Pain, Intensive Care and Emergency Medicine—APICE. Springer Milan, 1999. 113-117.

Rosenberg, Andrew L., et al. "Accepting critically ill transfer patients: adverse effect on a referral center's outcome and benchmark measures." Annals of internal medicine 138.11 (2003): 882-890.

Burack, Joshua H., et al. "Public reporting of surgical mortality: a survey of New York State cardiothoracic surgeons." The Annals of thoracic surgery 68.4 (1999): 1195-1200.

Hayes, J. A., et al. "Outcome measures for adult critical care: a systematic review." Health technology assessment (Winchester, England) 4.24 (1999): 1-111.

RUBENFELD, GORDON D., et al. "Outcomes research in critical care: results of the American Thoracic Society critical care assembly workshop on outcomes research." American journal of respiratory and critical care medicine 160.1 (1999): 358-367.

Turnbull, Alison E., et al. "Outcome Measurement in ICU Survivorship Research From 1970 to 2013: A Scoping Review of 425 Publications." Critical care medicine (2016).

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