in this issue , zanier and colleagues   conducted a study showing that although computer - monitored end - hour data is accurately reflected by the nurses ' chart value , more complex summary measures ( such as the detection of an intracranial pressure ( icp ) of more than 20 mmhg ) are less accurate . their finding that at least one - third of secondary insults for raised icp are not identified from the nursing chart is similar to that reported by corrie and colleagues , who also found a similar detection error rate for other signals such as blood pressure , particularly the events of shorter duration . importantly , zanier 's paper has further shown that when data are categorised in terms of percentage of time spent with raised icp , the patients exhibiting instability in icp were most prone to underesitmation of icp insults . the data sampling rate may be pertinent here : zanier 's study sampled at 600 samples per minute , whereas other studies used 1 sample per minute   or as few as 4 samples per hour . the article by bates and gawande   describes several trials of technology that have reduced medication errors , decreased errors of omission from poor handoffs between clinicians and provided earlier detection of adverse events . for example , kupermann and colleagues , in a randomized controlled trial of technology for the early detection of adverse events , showed an 11% reduction in time to treatment and a 29% reduction in the duration of dangerous conditions to patients . rosenfield and colleagues   conducted a study of information technology - based remote monitoring of a 10-bed intensive care unit and reported a reduction in mortality of more than 40% and a reduced length of stay of 30% in comparison with historical controls . critics of this type of research point out that better resolution of events is of no value unless their direct management influences clinical outcome . single - centre studies with small numbers of patients are not suited to answer such questions , and multi - centre randomised controlled trials validating information technology - driven management are neither readily funded nor easily justified as a research priority . paradoxically , the patient populations that may benefit most from better information technology - based event detection , such as patients with brain injury , are the most challenging in which to conduct a controlled management trial because of a continuing inter - centre management variation   fostered in large part by a lack of evidence for any type of effective therapy . nevertheless , indirect evidence is available and continues to come forward . there are increasing numbers of reports indicating the importance of providing specialist neuro - critical care in the management of patients with traumatic brain injury [ 10 - 12 ] . for example , the report by patel and colleagues   on 2,300 patients treated in non - neurosurgical hospitals showed a 2.15-fold increase in the odds of death compared with those treated in a neurosurgical centre . these studies do not indicate which aspects of critical care management are crucial , but management ( whether surgically or medically focused ) aimed at the earlier detection and treatment of adverse events must be partly responsible . in support of this , and at the risk of annoying enthusiasts of evidence - based medicine , neurointensive care centres with a track record in the aggressive management of secondary insults continue to report improvements in outcome statistics of patients compared with historical controls . the brain monitoring with information technology ( brainit ) group have been strong proponents for the adoption of information technology methods for the early detection and management of secondary insults in patients with brain injury . analyses in progress by this group on 200 head - injured patients ' minute - by - minute physiological data obtained from 22 neurointensive care centres across europe also may indicate that more complex summary measures , such as the pressure  time index , relate better to clinical outcome than do simple measures such as the mean or the median . we continue to hope for definitive controlled trial evidence that information technology - led management yields improved patient outcome , but our experience so far of funding and conducting such studies has been poor . surely our research time and funds are better spent on trialling new forms of management without the need to conduct controlled trials of new health care support systems as well ? i am inclined to agree with the sentiments of socrates as portrayed in the ' letter of dissent ' , when arguing against ' enthusiasticus ' ( for evidence - based medicine ) , that perhaps the loudest supporters of evidence - based medicine are the hospital accountants keen to keep health care costs down . there is no question that we need better monitoring and event detection technology for health care and that we need more research into optimising that technology , but should their adoption depend upon large - scale clinical trials ? perhaps now the questions we need to focus upon are no longer if but when , and no longer why but how .
there is accruing evidence that information technology can improve patient health care , with several trials of technology showing smaller numbers of medication errors , or can provide earlier detection of adverse events . 
 critics of this type of research point out that better resolution of events is of no value unless their direct management influences clinical outcome . nevertheless , indirect evidence is available , such as reports indicating the importance of providing specialist neuro - critical care in the management of patients with traumatic brain injury . 
 these studies do not indicate which aspects of critical care management are crucial , but management aimed at the earlier detection and treatment of adverse events must be partly responsible . 
 we continue to hope for definitive controlled trial evidence that information technology - led management yields improved patient outcome , but our experience so far of funding and conducting such studies has been poor . 
 there is no question that we need better monitoring and event detection technology for health care and that we need more research into optimising that technology , but should their adoption depend on large - scale clinical trials ? 
 perhaps now the questions we need to focus upon are no longer if but when , and no longer why but how .