Category: Electronic Medical Records

Replace Us With Computers!

In a preview to the future – who performs better at predicting outcomes, a physician, or a computer?

Unsurprisingly, it’s the computer – and the unfortunate bit is we’re not exactly going up against Watson or the hologram doctor from the U.S.S. Voyager here.

This is Jeff Kline, showing off his rather old, not terribly sophisticated “attribute matching” software.  This software, created back in 2005-ish, is based off a database he created of acute coronary syndrome and pulmonary embolism patients.  He determined a handful of most-predictive variables from this set, and then created a tool that allows physicians to input those specific variables from a newly evaluated patient.  The tool then finds the exact matches in the database and spits back a probability estimate based on the historical reference set.

He sells software based on the algorithm and probably would like to see it perform well.  Sadly, it only performs “okay”.  But, it beats physician gestalt, which is probably better ranked as “poor”.  In their prospective evaluation of 840 cases of acute dyspnea or chest pain of uncertain immediate etiology, physicians (mostly attendings, then residents and midlevels) grossly over-estimated the prevalence of ACS and PE.  Physicians had a mean and median pretest estimate for ACS of 17% and 9%, respectively, and the software guessed 4% and 2%.  Actual retail price:  2.7%.  For PE, physicians were at mean 12% and median 6%, with the software at 6% and 5%.  True prevalence: 1.8%.

I don’t choose this article to highlight Kline’s algorithm, nor the comparison between the two.  Mostly, it’s a fascinating observational study of how poor physician estimates are – far over-stating risk.  Certainly, with this foundation, it’s no wonder we’re over-testing folks in nearly every situation.  The future of medicine involves the next generation of similar decision-support instruments – and we will all benefit.

“Clinician Gestalt Estimate of Pretest Probability for Acute Coronary Syndrome and Pulmonary Embolism in Patients With Chest Pain and Dyspnea.”
http://www.ncbi.nlm.nih.gov/pubmed/24070658

Death From a Thousand Clicks

The modern physician – one of the most highly-skilled, highly-compensated data-entry technicians in history.

This is a prospective, observational evaluation of physician activity in the Emergency Department, focusing mostly the time spent in interaction with the electronic health record.  Specifically, they counted mouse clicks during various documentation, order-entry, and other patient care activities.  The observations were conducted for 60-minute time periods, and then extrapolated out to an entire shift, based on multiple observations.

The observations were taken from a mix of residents, attendings, and physician extenders, and offer a lovely glimpse into the burdensome overhead of modern medicine: 28% of time was spent in patient contact, while 44% was spent performing data-entry tasks.  It requires 6 clicks to order an aspirin, 47 clicks to document a physical examination of back pain, and 187 clicks to complete an entire patient encounter for an admitted patient with chest pain.  This extrapolates out, at a pace of 2.5 patients per hour, to ~4000 clicks for a 10-hour shift.

The authors propose a more efficient documentation system would result in increased time available for patient care, increased patients per hour, and increased RVUs per hour.  While the numbers they generate from this sensitivity analysis for productivity increase are essentially fantastical, the underlying concept is valid: the value proposition for these expensive, inefficient electronic health records is based on maximizing reimbursement and charge capture, not by empowering providers to become more productive.

The EHR in use in this study is McKesson Horizon – but, I’m sure these results are generalizable to most EHRs in use today.

“4000 Clicks: a productivity analysis of electronic medical records in a community hospital ED”
http://www.ncbi.nlm.nih.gov/pubmed/24060331

New South Wales Dislikes Cerner

The grass is clearly greener on the other side for these folks at Nepean Hospital in New South Wales, AUS.  This study details the before-and-after Emergency Department core measures as they transitioned from the EDIS system to Cerner’s FirstNet.  As they state in their introduction, “Despite limited literature indicating that FirstNet has decreased performance” and “reports of problems with Cerner programs overseas”, FirstNet was foisted upon them – so it’s clear they have an agenda with this publication.


And, a retrospective, observational study is the perfect vehicle for an agenda.  You pick the criteria you want to measure, the most favorable time period, and voilà!  These authors picked a six month pre-intervention period and a six-month post-intervention period.  Triage categories were similar for that six month period.  And then…they present data on a three-month subset.  Indeed, all their descriptive statistics are of only a three-month subset excepting ambulance offload waiting time – for which they have full six month data.  Why choose a study period fraught with missing data?

Then, yes, by every measure they are less efficient at seeing patients with the Cerner product.  The FirstNet system had been in place for six months by the time they report data – but, it’s still not unreasonable to suggest they’re somewhat suffering the growing pains of inexperience.  Then, they also understaff the ED by 3.2 resident shifts and 3.5 attending shifts per week.  An under-staffed ED for a relatively new implementation of a product with low physician acceptance?  

As little love I have for Cerner FirstNet, I’m not sure this study gives it a fair shot.


“Effect of an electronic medical record information system on emergency department performance”
www.ncbi.nlm.nih.gov/pubmed/23451963

TPA is Dead, Long Live TPA

I’m sure this saturating the medical airwaves this morning, but yesterday’s NEJM published a study which they succinctly summarize on Twitter as “In trial of 75 pts w/ acute ischemic #stroke, tenecteplase assoc w/ better reperfusion, clin outcomes than alteplase.”


Well, that’s very exciting!  It’s still smashing a teacup with a sledgehammer, but it does appear to be a more functional sledgehammer.  Particularly encouraging were the rates of sustained complete recanalization – which were 36% at 24 hours for alteplase and 58% for tenecteplase – and the rates of intracranial hemorrhage – which were 20% for alteplase and 6% for tenecteplase.


However, the enthusiasm promoted by NEJM, and likely the rest of the internet, should be tempered by the fact that there were only 25 patients in each arm, and there is enough clinical variability between groups that it is not yet practice changing.  This was a phase 2B trial, and it is certainly reasonable evidence to proceed with a phase III trial.


Unfortunately, in a replay of prior literature, the authors are all affiliated with Boehringer Ingelheim, the manufacturer of tenecteplase.


“A Randomized Trial of Tenecteplase versus Alteplase for Acute Ischemic Stroke”
http://www.nejm.org/doi/full/10.1056/NEJMoa1109842

Addendum:  As Andy Neil appropriately points out, tenecteplase has been studied before – 112 patients over several years, terminated early due to slow enrollment – without seeing a significant advantage.

ED Geriatric CPOE Intervention – Win?

It does seem as though this intervention had a measure of success – based on their primary outcome – but there’s more shades of grey throughout the article.

This is a prospective, controlled trial of a contextual computer decision-support (CDS) incorporated into the computerized provider order entry (CPOE) system of their electronic health record (EHR).  They do a four-phase On/Off intervention where the CPOE either suggests alternative medications or dose reductions in patients >65 years of age.  They look at whether the intervention changed the rate at which medication ordering was compliant with medication safety in the elderly, and then, secondarily, at the rate of 10-fold errors, medication cancellations, and adverse drug event reports.

The oddest part of this study is their choice of primary outcome measure.  Ideally, the most relevant outcome is the patient-oriented outcome – which, in this case, ought to be a specific decrease in adverse drug events in the elderly.  However, and I can understand where they’re coming from, they chose to specifically evaluate the usability/acceptability of the CDS intervention to verify the mechanism of intervention.  There are lots of studies out there documenting “alert fatigue”, resulting in either no change or even increasing error rates.

As far as the main outcome measure goes, they had grossly positive findings – 31% of orders were compliant during the intervention periods vs. 23% of orders during the control periods.  But, 92.5% of recommendations for alternative medications were ignored during the intervention periods – most commonly triggered by diazepam, clonazepam, and indomethacin.  The intervention was successful in reducing doses for NSAIDs and for opiates, but had no significant effect on benzodiazepine or sedative-hypnotic dosing.

However, bizarrely, even though there was just a small difference in guideline-concordant ordering, there was a 4-fold reduction in adverse drug events – most of which occurred during the initial “off” period.  As a secondary outcome, there’s much to say about it other than “huh”.  None of their other secondary outcomes demonstrated any differences.

So, it’s an interesting study.  It is consistent with a lot of previous studies – most alerts are ignored, but occasionally small positive effect sizes are seen.  Their primary outcome measure is one of mostly academic interest – it would be better if they had chosen more clinically relevant outcomes.  But, no doubt, if you’re not already seeing a deluge of CDS alerts, just wait a few more years….

“Guided medication dosing for elderly emergency patients using real-time, computerized decision support”
http://www.ncbi.nlm.nih.gov/pubmed/22052899

Does EHR Decision Support Make You More Liable?

That’s the question these JAMA article authors asked themselves, and they say – probably.  The way they present it, it’s probably true – using the specific example of drug-drug interactions.  If you put an anticoagulated elderly person on TMP-SMX and they come back a few days later bleeding with an INR of 7, you might be in trouble for clicking away the one important drug alert out of the one hundred you’re inundated on your shift.  The authors note how poorly designed the alerts are, how few are relevant, and “alert fatigue” – but really, if you’re getting any kind of alerts or have any EHR tools available to you during your practice, each time you dismiss one, someone could turn it around against you.

The authors potential solutions are an “expert” drug-drug interaction list or legislative legal safe harbors.

“Clinical Decision Support and Malpractice Risk.”
www.ncbi.nlm.nih.gov/pubmed/21730245

Badgering Your Consultants to Death

This article describes a fascinating and absolutely untenable situation with numbers that just defy comprehension.

At an academic teaching hospital in Korea, 75% required consultation towards their admission rate of 36% – and their ED LOS median was seven hours.  Then, they implemented this brutal system in which an automated computer protocol paged out a consultation – and then, at the three hour mark – if there was still no disposition, they autopaged every resident in the consulted department.  Then, at the six hour mark, a page went out to every resident and faculty member in the consulted department regarding the disposition delay.  And their median ED LOS and time to disposition basically each improved by an hour and a half with this intervention.

So, this situation is insane.  Their admission rate is pretty high, but I still cannot fathom consulting on 75% of my patients.  And, these time to disposition numbers are equally alien, especially to a community emergency physician.  At my hospital, if a consultation goes over one hour in our EDIS, the badgering begins – but it’s more likely friendly, desperate begging as opposed to this hospital’s automated irritant spam.

So, shed a tear for Korea and their dysfunctional ED.

http://www.ncbi.nlm.nih.gov/pubmed/21496143

News Flash – Better Electronic Medical Records Are Better

In this article, providers are asked to complete a simulated task in their standard EMR – which is Mayo’s LastWord supplemented by Chart+ – vs a “novel” EMR redesigned specifically for a critical care environment with reduced cognitive load and increased visibility for frequently utilized elements and data.  In their bleeding patient scenario, their novel EMR was faster and resulted in fewer errors.  So, thusly, a better EMR design is better.

While it seems intuitively obvious – you still need studies to back up your justification for interface design in electronic medical records.  Their approach in testing is one I’d like to see expanded – and perhaps even implemented as a regulatory standard – evaluation on cognitive load and a certain level of task-based completion testing with error rates at a certain level.  Electronic medical records should be treated like medical devices/medications/equipment that should be rigorously failure tested.  While EMRs are far more complicated instruments, studies such as this one, illustrate that an EMR with interfaces designed for specific work environments to aid in effective and efficient task-completion save time and reduce errors.

The main issue I see with EMR these days is that the stakeholders and motivators behind this initial wave of implementation in financial – systems in place to capture every last level of service provided to a patient in order to increase revenues.  Now, the next generation and movement with EMRs is to look at how they can increase patient safety, particularly in light of threats of non-payment for preventable medical errors.  Again, financial motivation, but at least this financial motivation is going to motivate progress and maturation of medical records as tools to protect patients, not simply to milk them for profits.

http://www.ncbi.nlm.nih.gov/pubmed/21478739