Biomedical Informatics
2010 Year in Review
Notable publications and events in Informatics
since the 2009 AMIA Symposium
Daniel R. Masys, MD
Professor and Chair
Department of Biomedical Informatics
Professor of Medicine
Vanderbilt University School of Medicine
Content for this session is at:
http://dbmichair.mc.vanderbilt.edu/amia2010/
including citation lists and links
and this PowerPoint
Index to all Years in Review
http://dbmichair.mc.vanderbilt.edu/amia/
Design for this Session
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Modeled on American College of Physician
“Update” sessions
Emphasis on ‘what it is’ and ‘why it is
important’
Audience interaction for each category of
item discussed
Source of Content for Session
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Literature review of RCTs indexed by MeSH
term “Medical Informatics”, “Telemedicine” &
descendents or main MeSH term
“Bioinformatics”, and Entrez date between
November 2009 and October 2010 further
qualified by involvement of >100 providers or
patients
Poll of American College of Medical
Informatics fellows list
Thanks to:
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Rebecca Jerome
David Bates
George Hripcsak
Ken Goodman
Bill Hersh
Nancy Lorenzi
Betsy Humphreys
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Don Detmer
Blackford Middleton
Bonnie Kaplan
Nancy Lorenzi
Jim Anderson
Charlie Safron
Dean Sittig
Session components
Representative New Literature
 Notable Events – the ‘Top Five’ list
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New Literature Highlights:
Clinical Informatics
Clinical Decision Support
 Telemedicine
 The practice of informatics
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New Literature Highlights:
Bioinformatics and
Computational Biology
Human Health and Disease
 The practice of bioinformatics
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Clinical Decision
Support
49 new RCTs published
meeting search criteria
November 2009 – October 2010
Clinical Decision Support for Providers
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Reference
 Atlas SJ et. al.. J Gen Intern Med. 2010 Sep 15.[Mass General
Hospital, Boston MA]
Title
 A Cluster-Randomized Trial of a Primary Care Informatics-Based
System for Breast Cancer Screening.
Aim
 To evaluate whether a primary care network-based informatics
intervention can improve breast cancer screening rates.
Methods
 Cluster-randomized controlled trial of 12 primary care practices
conducted from March 20, 2007 to March 19, 2008.
 Women 42-69 years old with no record of a mammogram in the prior 2
years.
 In intervention practices, a population-based informatics system was
implemented that: connected overdue patients to appropriate care
providers, presented providers with a Web-based list of their overdue
patients in a non-visit-based setting, and enabled "one-click"
mammography ordering or documented deferral reasons.
Clinical Decision Support for Providers
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Reference
 Atlas SJ et. al.. J Gen Intern Med. 2010 Sep 15..
Methods, cont’d
 Patients selected for mammography received automatically generated
letters and follow-up phone calls. All practices had electronic health
record reminders about breast cancer screening available during
clinical encounters.
 The primary outcome was the proportion of overdue women
undergoing mammography at 1-year follow-up.
Results
 Baseline mammography rates in intervention and control practices did
not differ (79.5% vs 79.3%, p = 0.73). Among 3,054 women in
intervention practices and 3,676 women in control practices overdue
for mammograms, intervention patients were somewhat younger, more
likely to be non-Hispanic white, and have health insurance.
 Most intervention providers used the system (65 of 70 providers,
92.9%).
Clinical Decision Support for Providers
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Reference
 Atlas SJ et. al.. J Gen Intern Med. 2010 Sep 15.
Results, cont’d
 Action was taken for 2,652 (86.8%) intervention patients [2,274
(74.5%) contacted and 378 (12.4%) deferred]. After 1 year,
mammography rates were significantly higher in the intervention arm
(31.4% vs 23.3% in control arm, p < 0.001 after adjustment for baseline
differences; 8.1% absolute difference, 95% CI 5.1-11.2%).
 All demographic subgroups benefited from the intervention.
Intervention patients completed screening sooner than control patients
(p < 0.001).
Conclusions
 A novel population-based informatics system functioning as part of a
non-visit-based care model increased mammography screening rates
in intervention practices.
Clinical Decision Support for Providers
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Reference
 Atlas SJ et. al.. J Gen Intern Med. 2010 Sep 15.
Importance
 Contributes to literature use of prompting systems for preventive care,
using a population based rather than visit based approach to identify
those overdue for the preventive measure.
 Represents ‘second generation’ CDS alerts and reminders: one-click
reponse to solve problem or document override. (But not third
generation: ‘closed loop’ CDS with outcome tracking).
Clinical Decision Support for Providers
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Reference
 Herasevich V et. al.. Crit Care Med. 2010 Oct 14. [Mayo Clinic and UT
HSC Houston]
Title
 Limiting ventilator-induced lung injury through individual electronic
medical record surveillance.
Aim
 To improve the safety of ventilator care and decrease the risk of
ventilator-induced lung injury,
Methods
 Authors designed and tested an electronic algorithm that incorporates
patient characteristics and ventilator settings, connected to near-realtime notification of bedside providers about potentially injurious
ventilator settings, in three Mayo Clinic ICU’s.
 Computer system alerted bedside providers via the text paging
notification about potentially injurious ventilator settings.
 Alert criteria included ventilator settings, CXR findings, various real
time ventilator pressures.
Clinical Decision Support for Providers
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Reference
 Herasevich V et. al.. Crit Care Med. 2010 Oct 14..
Methods, cont’d
 Ventilator-induced lung injury risk was compared before and after the
introduction of ventilator-induced lung injury alert. .
Results
 Prevalence of acute lung injury was 42% (n = 490) among 1,159
patients receiving >24 hrs of invasive ventilation.
 System sent 111 alerts for 80 patients, with a positive predictive value
of 59%.
 Exposure to potentially injurious ventilation decreased after the
intervention from 40.6 ± 74.6 hrs to 26.9 ± 77.3 hrs (p = .004).
Conclusions
 Electronic medical record surveillance of mechanically ventilated
patients accurately detects potentially injurious ventilator settings and
is able to influence bedside practice at moderate costs.
Clinical Decision Support for Providers
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Reference
 Herasevich V et. al.. Crit Care Med. 2010 Oct 14.
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Conclusions, cont’d
 System implementation was associated with decreased patient
exposure to potentially injurious mechanical ventilation settings.
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Importance, cont’d
 Extends literature on ‘critical’ and ‘panic’ alerting technologies with
combination of real time data streams from ventilator, natural
language processing of CXR text, and real time messaging.
Clinical Decision Support for Providers
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Reference
 Co JP et. al.. Pediatrics. 2010 Aug;126(2):239-46. Epub 2010 Jul 19..
[Mass General Hospital for Children, Boston]
Title
 Electronic health record decision support and quality of care for
children with ADHD.
Aim
 To assess the effect of electronic health record (EHR) decision
support on physician management and documentation of care for
children with attention-deficit/hyperactivity disorder (ADHD).
Methods
 Study of 79 general pediatricians in 12 pediatric primary care
practices that use the same EHR who were caring for 412 children
who were aged 5 to 18 years and had a previous diagnosis of ADHD.
 A cluster randomized trial of EHR-based decision support that
included (1) clinician reminders to assess ADHD symptoms every 3 to
6 months and (2) an ADHD note template with structured fields for
symptoms, treatment effectiveness, and adverse effects.
Clinical Decision Support for Providers
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Reference
 Co JP et. al.. Pediatrics. 2010 Aug;126(2):239-46.
Methods, cont’d
 The main outcome measures were (1) proportion of children with visits
during the 6-month study period in which ADHD was assessed and (2)
quality of documentation of ADHD assessment..
Results
 Children at intervention sites were more likely to have had a visit
during the study period in which their ADHD was assessed.
 The ADHD template was used at 32% of visits at which patients were
scheduled specifically for ADHD assessment.
 Template use was associated with improved documentation of
symptoms, treatment effectiveness, and treatment adverse effects.
Conclusions
 EHR-based decision support improved the likelihood that children with
ADHD had visits for as well as care related to managing this condition.
Clinical Decision Support for Providers
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Reference
 Co JP et. al.. Pediatrics. 2010 Aug;126(2):239-46.
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Conclusions, cont’d
 Better understanding of how to optimize provider use of the decision
support and templates could promote additional improvements in care.
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Importance, cont’d
 Extends literature on patient-specific reminders contributing to
improved consistency and follow-up.
 Another study showing that templates improve comprehensiveness of
documentation, and the majority of practitioners choose not to use
them.
Clinical Decision Support for Providers
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Reference
 Longhurst CA et. al. Pediatrics. 2010 Jul;126(1):14-21. Epub 2010
May 3. [Stanford University School of Medicine, Palo Alto]
Title
 Decrease in hospital-wide mortality rate after implementation of a
commercially sold computerized physician order entry system.
Aim
 To determine the effect on the hospital-wide mortality rate after
implementation of CPOE at an academic children's hospital..
Methods
 A cohort study with historical controls at a 303-bed, freestanding,
quaternary care academic children's hospital.
 All nonobstetric inpatients admitted between January 1, 2001, and
April 30, 2009, were included.
 A total of 80,063 patient discharges were evaluated before the
intervention (before November 1, 2007), and 17,432 patient
discharges were evaluated after the intervention (on or after
November 1, 2007).
Clinical Decision Support for Providers
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Reference
 Longhurst CA et. al. Pediatrics. 2010 Jul;126(1):14-21..
Methods, cont’d
 On November 4, 2007, the hospital implemented locally modified
functionality within a commercially sold electronic medical record to
support CPOE and electronic nursing documentation..
Results
 After CPOE implementation, the mean monthly adjusted mortality rate
decreased by 20% (1.008-0.716 deaths per 100 discharges per month
unadjusted [95% confidence interval: 0.8%-40%]; P = .03).
 With observed versus expected mortality-rate estimates, results
suggested that CPOE implementation may have resulted in 36 fewer
deaths over the 18-month post-implementation time frame..
Conclusions
 Implementation of a locally modified, commercially sold CPOE system
was associated with a statistically significant reduction in the hospitalwide mortality rate at a quaternary care academic children's hospital.
Clinical Decision Support for Providers
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Reference
 Longhurst CA et. al. Pediatrics. 2010 Jul;126(1):14-21.
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Importance
 Most CPOE results in the informatics literature are from customized
home-grown systems. Paper shows positive results obtainable from a
commercial system.
 “Big bang” implementation similar to a widely reported ‘unintended
consequences article by Han in 2005 that showed increased mortality
in academic pediatric hospital. That was a media event. This paper
was not.
Clinical Decision Support for Providers
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Reference
 Schnipper JL et. al. Endocr Pract. 2010 Mar-Apr;16(2):209-18.
[Brigham and Women’s hospital, Boston]
Title
 Effects of a computerized order set on the inpatient management of
hyperglycemia: a cluster-randomized controlled trial.
Aim
 To determine the effects of a computerized order set on the inpatient
management of diabetes and hyperglycemia..
Methods
 Cluster-randomized controlled trial on general medical service of an
academic medical center staffed by residents and hospitalists.
 Consecutively enrolled patients with diabetes mellitus or inpatient
hyperglycemia were randomized on the basis of their medical team to
usual care (control group) or an admission order set built into the
hospital's computer provider order entry (CPOE) system (intervention
group).
 All teams received a detailed subcutaneous insulin protocol and casebased education.
Clinical Decision Support for Providers
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Reference
 Schnipper JL et. al. Endocr Pract. 2010 Mar-Apr;16(2):209-18.
Methods, cont’d
 The primary outcome was the mean percent of glucose readings per
patient between 60 and 180 mg/dL.).
Results
 Between April 5 and June 22, 2006, there were 179 eligible study
subjects.
 Mean percent of glucose readings per patient between 60 and 180
mg/dL was 75% in the intervention group and 71% in the usual care
group (adjusted relative risk, 1.36; 95% CI, 1.03 to 1.80).
 In comparison with usual care, the intervention group had a lower
patient-day weighted mean glucose (148 mg/dL versus 158 mg/dL, P =
.04), less use of sliding-scale insulin by itself (25% versus 58%, P =
.01), and no significant difference in the rate of severe hypoglycemia
(glucose <40 mg/dL; 0.5% versus 0.3% of patient-days, P = .58).
Clinical Decision Support for Providers
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Reference
 Schnipper JL et. al. Endocr Pract. 2010 Mar-Apr;16(2):209-18.
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Conclusions
 Use of an order set built into a hospital's CPOE system led to
improvements in glycemic control and insulin ordering without causing
a significant increase in hypoglycemia.
Importance
 Glycemic control is a big problem in hospitalized patients.
 Extends literature showing that structured CPOE via order sets is a
useful technical approach to guiding care where more than one
element is needed for the intended outcome.
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Clinical Decision Support for Providers
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Reference
 Riggio JM et. al. Acad Med. 2009 Dec;84(12):1719-26. [Thomas
Jefferson University, Philadelphia]
Title
 Effectiveness of a clinical-decision-support system in improving
compliance with cardiac-care quality measures and supporting
resident training.
Aim
 To improve compliance with quality measures for patients with
myocardial infarction and heart failure, at hospital discharge.
Methods
 A clinical-decision-support system (CDSS) using an electronic
checklist was developed.
 The CDSS prompts clinicians at every training level to consistently
create comprehensive discharge instructions addressing quality
measures.
 Compliance with discharge medication prescribing guidelines was
measured during 15-month preintervention and postintervention
periods.
Clinical Decision Support for Providers
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Reference
 Riggio JM et. al. Acad Med. 2009 Dec;84(12):1719-26.
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Results
 Delivery of discharge instructions showed significant improvement
from the preintervention period to the postintervention period (37.2% to
93.0%; P < .001).
 Compliance with prescription of ACEI or ARB also improved
significantly for HF (80.7% to 96.4%; P < .001) and AMI (88.1% to
100%; P = .014) patients.
 Compliance with the remaining measures was higher before
intervention, and, thus, the modest improvement in the
postintervention period was not statistically significant (AMI patients:
aspirin, 97.5% to 98.8%; P = .43; and beta-blocker, 97.9% to 98.7%; P
= .78; HF patients: LVSF, 99.3% to 99.1%; P = .78).
Clinical Decision Support for Providers
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Reference
 Riggio JM et. al. Acad Med. 2009 Dec;84(12):1719-26..
Conclusions
 Implementation of a CDSS with computerized electronic prompts
improved compliance with selected cardiac-care quality measures.
 The design of quality-improvement decision-support tools should
incorporate educational missions in their message and design.
Importance
 Although a concurrent randomized design is superior to a sequential
design, significant improvements in outcomes of CDSS
implementation can be found with either.
 Overall compliance with best practice in the 95-100% range is
refreshing in an otherwise often dismal literature that tends to focus on
percent change because the baseline prevalence of best practice is
low.
Clinical Decision Support for Providers
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Reference
 Ledwich LJ et. al. Arthritis Rheum. 2009 Nov 15;61(11):150510.[Geisinger Medical Center, Danville, PA]
Title
 Improved influenza and pneumococcal vaccination in rheumatology
patients taking immunosuppressants using an electronic health record
best practice alert.
Aim
 To examine whether an electronic health record (EHR) best practice
alert (BPA), a clinical reminder to help guideline adherence, improved
vaccination rates in rheumatology patients receiving
immunosuppressants.
Methods
 A vaccination BPA was developed based on immunosuppressant
treatment, age, and prior vaccinations.
 At site 1, a hospital-based academic practice, physicians ordered
vaccinations. At site 2, a community-based practice, physicians
signed orders placed by nurses.
 Demographics, vaccination rates, and documentation (vaccination or
no administration) were measured. .
Clinical Decision Support for Providers
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Reference
 Ledwich LJ et. al. Arthritis Rheum. 2009 Nov 15;61(11):1505-10.
Methods, cont’d
 Vaccination and documentation rates were compared for October 1
through December 31, 2006 (preBPA), and October 1 through
December 31, 2007 (postBPA).
 Determined odds ratio of improvement across the years between the
sites.
Results
 PostBPA influenza vaccination rates significantly increased (47% to
65%; P < 0.001), with significant improvement at both sites.
 PostBPA pneumococcal vaccination rates likewise significantly
increased (19% to 41%; P < 0.001).
 PostBPA documentation rates for influenza and pneumococcal
vaccinations also increased significantly.
Clinical Decision Support for Providers
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Reference
 Ledwich LJ et. al. Arthritis Rheum. 2009 Nov 15;61(11):1505-10. .
Results, cont’d
 Site 2 (nurse-driven) had significantly higher preBPA vaccination rates
for influenza (69% versus 43%; P < 0.001) and pneumococcal (47%
versus 15%; P < 0.001)..
Conclusions
 The use of a BPA significantly increased influenza and pneumococcal
vaccination and documentation rates in rheumatology patients taking
immunosuppressants.
 A nurse-driven process offered higher efficacy.
 An EHR programmed to alert providers is an effective tool for
improving quality of care for patients receiving immunosuppressants..
Importance
 Extends CDSS literature showing better outcomes by sending CDSS
alerts to persons other than physicians.
Clinical Decision Support for Providers
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Reference
 Hug BL et. al. J Gen Intern Med. 2010 Jan;25(1):31-8. Epub 2009 Nov
6.[Brigham & Women’s, Boston, MA]
Title
 Adverse drug event rates in six community hospitals and the potential
impact of computerized physician order entry for prevention.
Aim
 To assess the incidence of adverse drug events (ADEs) in six
community hospitals.
Methods
 Multicenter, retrospective cohort study of six Massachusetts
community hospitals with 100 to 300 beds.
 From 109,641 adult patients hospitalized from January 2005 through
August 2006, a random sample of 1,200 patients was drawn, 200 per
site.
 Measured ADEs and preventable ADEs. Presence of an ADE was
evaluated using an adaptation of a trigger instrument developed by
the Institute for Health Care Improvement.
Clinical Decision Support for Providers
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Reference
 Hug BL et. al. J Gen Intern Med. 2010 Jan;25(1):31-8.
Methods, cont’d
 Independent reviewers classified events by preventability, severity,
and potential for preventability by computerized physician order entry
(CPOE)...
Results
 180 ADEs occurred in 141 patients (rate, 15.0/100 admissions).
 Overall, 75% were preventable. ADEs were rated as serious in 49.4%
and life threatening in 11.7%.
 Patients with ADEs were older (mean age, 74.6 years, p < 0.001),
more often female (60.3%, p = 0.61), and more often Caucasian
(96.5%, p < 0.001) than patients without ADEs.
 Of the preventable ADEs, 81.5% were judged potentially preventable
by CPOE.
Clinical Decision Support for Providers
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Reference
 Hug BL et. al. J Gen Intern Med. 2010 Jan;25(1):31-8. .
Conclusions
 The incidence of ADEs in these community hospital admissions was
high, and most ADEs were preventable, mostly through CPOE.
 Data suggest that CPOE may be beneficial in this setting.
Importance
 Findings regarding ADE’s and potential of CDSS from academic
centers extrapolate to community settings.
 Reinforces the value of progressive Meaningful Use criteria for EMRs
with respect to CDSS
Clinical Decision Support for Patients
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Reference
 Fals-Stewart and Lam WK. Exp Clin Psychopharmacol. 2010
Feb;18(1):87-98.[University of Rochester, Rochester, NY]
Title
 Computer-assisted cognitive rehabilitation for the treatment of patients
with substance use disorders: a randomized clinical trial.
Aim
 To examine the comparative efficacy of cognitive rehabilitation as an
intervention for substance misuse.
Methods
 Patients with substance use disorders entering long-term residential
care (N = 160) randomly assigned to one of two conditions: (a)
standard treatment plus computer-assisted cognitive rehabilitation
(CACR), designed to improve cognitive performance in areas such as
problem solving, attention, memory, and information processing
speed; or (b) an equally intensive attention control condition consisting
of standard treatment plus a computer-assisted typing tutorial (CATT).
 Participants were assessed at baseline, during treatment, at treatment
completion, and 3-, 6-, 9-, and 12-month follow-up.
Clinical Decision Support for Patients
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Reference
 Fals-Stewart and Lam WK. Exp Clin Psychopharmacol. 2010
Feb;18(1):87-98.
Results
 Intent-to-treat analyses showed that, compared with those randomized
to CATyping Tutorial, patients who received CA Cognitive Rehab were
significantly more engaged in treatment (e.g., higher ratings of positive
participation by treatment staff, higher ratings of therapeutic alliance),
more committed to treatment (e.g., longer stays in residence) and
reported better long-term outcomes (e.g., higher percentage of days
abstinent after treatment).
 There was a positive comparative effect of CA Cognitive Rehab on
abstinence during the year after treatment that was mediated by
treatment engagement and length of stay in residence.
Clinical Decision Support for Providers
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Reference
 Fals-Stewart and Lam WK. Exp Clin Psychopharmacol. 2010
Feb;18(1):87-98. .
Importance
 Either computer assisted cognitive rehabilitation contributes to drug
rehab, or forcing patients to learn typing makes them think drugs aren’t
so bad after all. ;-)
CDSS Unintended Consequences
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Reference
 Strom BL et al. Arch Intern Med. 2010 Sep 27;170(17):1578-83.
[University of Pennsylvania, Philadelphia PA]
Title
 Unintended effects of a computerized physician order entry nearly
hard-stop alert to prevent a drug interaction: a randomized controlled
trial..
Aim
 To evaluate the effectiveness of a nearly "hard stop" CPOE
prescribing alert intended to reduce concomitant orders for warfarin
and trimethoprim-sulfamethoxazole.
Methods
 Randomized clinical trial conducted at 2 academic medical centers in
Philadelphia.
 1981 clinicians were assigned to either an intervention group receiving
a nearly hard stop alert or a control group receiving the standard
practice.
 The study duration August 9, 2006, through February 13, 2007..
CDSS Unintended Consequences
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Reference
 Strom BL et al. Arch Intern Med. 2010 Sep 27;170(17):1578-83
Results
 Proportion of desired responses (ie, not reordering the alert-triggering
drug within 10 minutes of firing) was 57.2% (111 of 194 hard stop
alerts) in the intervention group and 13.5% (20 of 148) in the control
group (adjusted odds ratio, 0.12; 95% confidence interval, 0.0450.33).
 However, the study was terminated early because of 4 unintended
consequences identified among patients in the intervention group: a
delay of treatment with trimethoprim-sulfamethoxazole in 2 patients
and a delay of treatment with warfarin in another 2 patients.
Conclusions
 An electronic hard stop alert as part of an inpatient CPOE system was
extremely effective in changing prescribing.
 However, the intervention precipitated clinically important treatment
delays in 4 patients who needed immediate drug therapy.
 Results illustrate the importance of formal evaluation and monitoring
for unintended consequences of programmatic interventions intended
to improve prescribing habits.
CDSS Unintended Consequences
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Reference
 Persell SD et al. Ann Intern Med. 2010 Feb 16;152(4):225-31.
[Northwestern University, Chicago, IL]
Title
 Frequency of inappropriate medical exceptions to quality measures.
Aim
 To implement computerized decision support with mechanisms to
document medical exceptions to quality measures and to perform peer
review of exceptions and provide feedback when appropriate.
Methods
 Observational study of large internal medicine practice involving
patients eligible for 1 or more quality measures.
 A peer-review panel judged medical exceptions to 16 chronic disease
and prevention quality measures as appropriate, inappropriate, or of
uncertain appropriateness.
 Medical records were reviewed after feedback was given to determine
whether care changed.
CDSS Unintended Consequences
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Reference
 Persell SD et al. Ann Intern Med. 2010 Feb 16;152(4):225-31.
Results
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Physicians recorded 650 standardized medical exceptions during 7
months. The reporting tool was used without any medical reason 36
times (5.5%).
Of the remaining 614 exceptions, 93.6% were medically appropriate,
3.1% were inappropriate, and 3.3% were of uncertain
appropriateness.
Frequencies of inappropriate exceptions were 7 (6.9%) for coronary
heart disease, 0 (0%) for heart failure, 10 (10.8%) for diabetes, and 2
(0.6%) for preventive services.
After physicians received direct feedback about inappropriate
exceptions, 8 of 19 (42%) changed management.
The peer-review process took less than 5 minutes per case, but for
each change in clinical care, 65 reviews were required..
CDSS Unintended Consequences
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Reference
 Persell SD et al. Ann Intern Med. 2010 Feb 16;152(4):225-31.
Conclusions
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Physician-recorded medical exceptions were correct most of the time.
Peer review of medical exceptions can identify myths and
misconceptions, but the process needs to be more efficient to be
sustainable.
7 New CDSS RCTs showing no difference
for intervention vs. control
1.
Xu C et al. A randomized controlled trial of an interactive voice
response telephone system and specialist nurse support for childhood
asthma management. J Asthma. 2010 Sep;47(7):768-73. [University of
Queensland, Australia]
2.
Williams LK et al. A cluster-randomized trial to provide clinicians
inhaled corticosteroid adherence information for their patients with
asthma. J Allergy Clin Immunol. 2010 Aug;126(2):225-31, 231.e1-4.
Epub 2010 May 31. [Henry Ford Health System, Detroit, MI]
3.
Strom BL et al. Randomized clinical trial of a customized electronic
alert requiring an affirmative response compared to a control group
receiving a commercial passive CPOE alert: NSAID--warfarin coprescribing as a test case. J Am Med Inform Assoc. 2010 JulAug;17(4):411-5. [University of Pennsylvania, Philadelphia]
4.
Walsh MN et al. Electronic health records and quality of care for heart
failure. Am Heart J. 2010 Apr;159(4):635-642. [Care Group,
Indianapolis, IN]
7 New CDSS RCTs showing no difference
for intervention vs. control, cont’d
5.
Singh H et al. Notification of abnormal lab test results in an electronic
medical record: do any safety concerns remain? Am J Med. 2010
Mar;123(3):238-44. [Houston VA and Baylor College of Medicine,
Houston, TX]
6.
Tamblyn R et al. Increasing the detection and response to adherence
problems with cardiovascular medication in primary care through
computerized drug management systems: a randomized controlled
trial. Med Decis Making. 2010 Mar-Apr;30(2):176-88. Epub 2009 Aug
12. [McGill University, Montreal, Quebec]
7.
Maclean CD. The Vermont diabetes information system: a cluster
randomized trial of a population based decision support system. J Gen
Intern Med. 2009 Dec;24(12):1303-10. Epub 2009 Oct 28. [University
of Vermont, Burlington, VT]
Clinical Decision
Support
Questions and Comments
Telemedicine
13 new RCTs published
November 2009 – October 2010
•2 diabetes
•4 psychiatric conditions
•1 each: smoking cessation, acne,
hypertension, infertility, congestive heart
failure, malaria
Telemedicine - diabetes
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Reference
 Stone RA et. al. Diabetes Care. 2010 Mar;33(3):478-84. Epub 2009
Dec 15. [Dept of Biostatistics, University of Pittsburgh]
Title
 Active care management supported by home telemonitoring in
veterans with type 2 diabetes: the DiaTel randomized controlled
trial.
Aim
 To compare short-term efficacy of home telemonitoring coupled with
active medication management by a nurse practitioner with a
monthly care coordination telephone call on glycemic control in
veterans with type 2 diabetes and entry A1C > or =7.5%..
Methods
 Veterans in VA Pittsburgh Healthcare System, June 2004 to
December 2005, who were taking oral hypoglycemic agents and/or
insulin for > or =1 year, and who had A1C > or =7.5% at enrollment
 Randomly assigned to either active care management with home
telemonitoring (ACM+HT group, n = 73) or a monthly care
coordination telephone call (CC group, n = 77).
Telemedicine - diabetes


Reference
 Stone RA et. al. Diabetes Care. 2010 Mar;33(3):478-84.
Methods, cont’d
 Both groups received monthly calls for diabetes education and selfmanagement review. ACM+HT group participants transmitted blood
glucose, blood pressure, and weight to a nurse practitioner using
the Viterion 100 TeleHealth Monitor
 Nurse practitioner adjusted medications for glucose, blood pressure,
and lipid control based on established American Diabetes
Association targets.
 Measures were obtained at baseline, 3-month, and 6-month visits.
Telemedicine - diabetes

Reference
 Stone RA et. al. Diabetes Care. 2010 Mar;33(3):478-84.
Telemedicine - diabetes

Reference


Results



Baseline characteristics were similar in both groups, with mean
A1C of 9.4% (CC group) and 9.6% (ACM+HT group).
Compared with the CC group, the ACM+HT group
demonstrated significantly larger decreases in A1C at 3 months
(1.7 vs. 0.7%) and 6 months (1.7 vs. 0.8%; P < 0.001 for each),
with most improvement occurring by 3 months.
Conclusions



Stone RA et. al. Diabetes Care. 2010 Mar;33(3):478-84.
Compared with the CC group, the ACM+HT group
demonstrated significantly greater reductions in A1C by 3 and 6
months.
However, both interventions improved glycemic control in
primary care patients with previously inadequate control.
Importance
 Extends literature showing home health measurement
devices work for chronic conditions
Telemedicine – psychiatric conditions
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
Reference
 Pyne JM et. alArch Gen Psychiatry. 2010 Aug;67(8):812-2. [Central
Arkansas VA, North Little Rock, AR]
Title
 Cost-effectiveness analysis of a rural telemedicine collaborative
care intervention for depression.
Aim
 To examine the cost-effectiveness of a rural telemedicine-based
collaborative care depression intervention.
Methods
 Randomized controlled trial of intervention vs usual care.
 Seven small (serving 1000 to 5000 veterans) Veterans Health
Administration community-based outpatient clinics serving rural
catchment areas in 3 mid-South states.
 Each site had interactive televideo dedicated to mental health but no
psychiatrist or psychologist on site.
Telemedicine – psychiatric conditions


Reference
 Pyne JM et. alArch Gen Psychiatry. 2010 Aug;67(8):812-2. [Central
Arkansas VA, North Little Rock, AR]
Methods, cont’d
 395 patients enrolled from April 2003 to September 2004.
 360 (91.1%) completed a 6-month follow-up and 335 (84.8%)
completed a 12-month follow-up.
 Intervention was a stepped-care model for depression treatment
was used by an off-site depression care team to make treatment
recommendations via electronic medical record.
 The team included a nurse depression care manager, clinical
pharmacist, and psychiatrist. Depression care manager
communicated with patients via telephone and was supported by
computerized decision support software.
Telemedicine – psychiatric conditions



Reference
 Pyne JM et. alArch Gen Psychiatry. 2010 Aug;67(8):812-2.
Methods, cont’d
 Base case cost analysis included outpatient, pharmacy, and
intervention expenditures.
 Effectiveness outcomes were depression-free days and qualityadjusted life years (QALYs) calculated using the 12-Item Short
Form Health Survey standard gamble conversion formula.
Results
 Incremental depression-free days outcome was not significant
(P = .10); therefore, further cost-effectiveness analyses were
not done.
 The incremental QALY outcome was significant (P = .04) and
the mean base case incremental cost-effectiveness ratio was
$85,634/QALY.
 Results adding inpatient costs were $111,999/QALY to
$132,175/QALY..
Telemedicine – psychiatric conditions



Reference
 Pyne JM et. al Arch Gen Psychiatry. 2010 Aug;67(8):812-2.
Conclusions
 In rural settings, a telemedicine-based collaborative care
intervention for depression is effective and expensive.
 The mean base case result was $85,634/QALY, which is
greater than cost per QALY ratios reported for other, mostly
urban, depression collaborative care interventions..
Importance
 One of few (and perhaps the first VA) telemedicine studies
among many involving telepsychiatry that focuses on both
assessment of efficacy and cost-effectiveness.
Telemedicine – psychiatric conditions

Two other studies from VA:
Kroenke K et al. Effect of telecare management on pain and
depression in patients with cancer: a randomized trial. JAMA. 2010
Jul 14;304(2):163-71. [Indianapolis]
Morland LA et al. Telemedicine for anger management therapy in a
rural population of combat veterans with posttraumatic stress
disorder: a randomized noninferiority trial. J Clin Psychiatry. 2010
Jul;71(7):855-63. Epub 2010 Jan 26. [Honolulu]

Both showed effectiveness without associated cost analysis
Telemedicine – psychiatric conditions

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
Reference
 Wiegand B et. al. Curr Med Res Opin. 2010 Apr;26(4):991-1002.
[Johnson & Johson, Inc. Ft. Washington PA]
Title
 Efficacy of a comprehensive program for reducing stress in women:
a prospective, randomized trial.
Aim
 To evaluate the efficacy of a comprehensive stress management
program in reducing perceived stress among women who reported
moderate-to-high stress levels.
Methods
 562 highly motivated females, aged 25-45, with moderate to high
stress levels, were enrolled in a 14-week study.
 Participants randomized into one of three groups: Group 1 included
Internet-based coaching focusing on behavior modification, daily
use of proprietary olfactive-based personal care products, and
periodic feedback reports; Group 2 consisted of only online
coaching; and Group 3 had no active stress management program.
Telemedicine – psychiatric conditions

Reference
 Wiegand B et. al. Curr Med Res Opin. 2010 Apr;26(4):991-1002.

Methods, cont’d
 Participants in the three groups filled out validated psychometric
assessments at baseline and throughout the study period to assess
changes in subject-perceived stress, stress-related comorbidities,
and sleep quality and to evaluate overall program efficacy.
Results
 At the end of the 14-week study period, subjects in Group 1 had
statistically significant improvement in the PSS score vs. Group 3 (p
< 0.01).
 There were statistically significant improvements in other efficacy
outcomes such as POMS total mood disturbance, TICS work
overload and social responsibility subscales, STAI and in the
number of night awakenings, assessed by the SMS questionnaire (p
< 0.05).
 Self-reported program efficacy was also significantly higher for
Group 1 (p < 0.001).

Telemedicine – psychiatric conditions

Reference
 Wiegand B et. al. Curr Med Res Opin. 2010 Apr;26(4):991-1002.

Conclusions

Despite study limitations, including reduction of stress in Group 3,
study demonstrated that the comprehensive stress management
program [with ofactive-base personal care products] is effective in
reducing stress among women with moderate to high stress
levels.
6 New Telemedicine RCTs showing no
difference for intervention vs. control
1.
Dalta SK, et al. Economic analysis of a tailored
behavioral intervention to improve blood pressure
control for primary care patients. Am Heart J. 2010
Aug;160(2):257-63 [VA Durham, NC]
2.
Palmas W et al. Medicare payments, healthcare service
use, and telemedicine implementation costs in a
randomized trial comparing telemedicine case
management with usual care in medically underserved
participants with diabetes mellitus (IDEATel). J Am Med
Inform Assoc. 2010 Mar-Apr;17(2):196-202. [Columbia
Univ. NYC]
3.
Watson AJ et al. A randomized trial to evaluate the
efficacy of online follow-up visits in the management of
acne. Arch Dermatol. 2010 Apr;146(4):406-11. [Center
for Connected Health, Boston, MA]
6 New Telemedicine RCTs showing no
difference for intervention vs. control
4.
Haemmerli K et al. Internet-based support for infertile
patients: a randomized controlled study. J Behav Med.
2010 Apr;33(2):135-46. Epub 2009 Dec 29. [University of
Bern, Switzerland]
5.
Copeland LA et al. An intervention for VA patients with
congestive heart failure. Am J Manag Care. 2010
Mar;16(3):158-65.[VA San Antonio, TX]
6.
Ollivier L et al. Use of short message service (SMS) to
improve malaria chemoprophylaxis compliance after
returning from a malaria endemic area. Malar J. 2009 Oct
23;8:236. [Tropical Medicine Service, Marseille, France]
Telemedicine
Questions and Comments
Practice of Informatics
Practice of Informatics
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
Reference
 Poon EG et. al.. N Engl J Med. 2010 May 6;362(18):1698707.[Brigham and Women’’s, Boston MA]
Title
 Effect of bar-code technology on the safety of medication
administration.
Aim
 To assess impact of bar-code verification technology within an
electronic medication-administration system (bar-code eMAR).
Methods
 Before-and-after, quasi-experimental study in an academic medical
center that was implementing the bar-code eMAR.
 Assessed rates of errors in order transcription and medication
administration on units before and after implementation of the barcode eMAR. Errors that involved early or late administration of
medications were classified as timing errors and all others as
nontiming errors.
 Two clinicians reviewed the errors to determine their potential to harm
patients and classified those that could be harmful as potential
adverse drug events..
Practice of Informatics


Reference
 Poon EG et. al.. N Engl J Med. 2010 May 6;362(18):1698-707..
Results
 14,041 medication administrations and 3082 order transcriptions
reviewed.
 Found 776 nontiming errors in medication administration on units that
did not use the bar-code eMAR (an 11.5% error rate) versus 495 such
errors on units that did use it (a 6.8% error rate)--a 41.4% relative
reduction in errors (P<0.001).
 The rate of potential adverse drug events (other than those associated
with timing errors) fell from 3.1% without the use of the bar-code eMAR
to 1.6% with its use, representing a 50.8% relative reduction
(P<0.001).
 The rate of timing errors in medication administration fell by 27.3%
(P<0.001), but the rate of potential adverse drug events associated
with timing errors did not change significantly.
Practice of Informatics




Reference
 Poon EG et. al.. N Engl J Med. 2010 May 6;362(18):1698-707..
Results
 Transcription errors occurred at a rate of 6.1% on units that did not use
the bar-code eMAR but were completely eliminated on units that did
use it.
Conclusions
 Use of the bar-code eMAR substantially reduces rate of errors in order
transcription and in medication administration as well as potential
adverse drug events, although it does not eliminate such errors.
 Data show that the bar-code eMAR is an important intervention to
improve medication safety.
Importance
 Self evident…
Practice of Informatics


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
Reference
 Anderson JG et. al.. Health Care Manag Sci. 2010 Mar;13(1):7483..[Purdue University, West Lafayette, IN]
Title
 Reporting trends in a regional medication error data-sharing system..
Aim
 To examine trends in information reported by hospitals participating in
a regional reporting system for medication errors.
Methods
 A coalition of hospitals in southwestern Pennsylvania, under the
auspices of the Pittsburgh Regional Healthcare Initiative (PRHI),
implemented a voluntary system for quarterly sharing of information
about medication errors.
 Over a 12-month period, 25 hospitals shared information about 17,000
medication errors.
 Using latent growth curve analysis, authors examined longitudinal
trends in the quarterly number of errors and associated corrective
actions reported by each hospital.
Practice of Informatics



Reference
 Anderson JG et. al.. Health Care Manag Sci. 2010 Mar;13(1):74-83.
Results
 Controlling for size, teaching status, and JCAHO accreditation score,
for the hospitals as a group, error reporting increased at a statistically
significant rate over the four quarters.
 Error reporting increased at similar rates across hospitals over
subsequent quarters.
 In contrast, the reporting of corrective actions remained unchanged.
However, the baseline levels of corrective actions reporting were
significantly different across hospitals.
Conclusions
 Although data sharing systems promote error reporting, it is unclear
whether they encourage corrective actions.

If data sharing is intended to promote root-cause-analysis and
process improvement, then the design of the reporting system should
emphasize data about these processes as well as errors.
Practice of Informatics
Questions and Comments
New Literature Highlights:
Bioinformatics and
Computational Biology
Human Health and Disease
 The practice of bioinformatics

Bioinformatics: Human Health & Disease

Reference
 . www.genome.gov/GWAStudies

Title
 NHGRI Genome-wide Association Studies Catalog.

Summary features

904 published genome-wide association studies showing genomewide significance for 165 traits.
GWAS methods

Measure 500,000 to 2 million DNA features



Most are Single Nucleotide Polymorphisms
(SNPs)
Increasingly includes copy number variation (gene
dose)
In principle, look for DNA changes that are
statistically associated with the condition of
interest, relative to a suitable comparison
group.


Best case: autosomal dominant Mendelian trait
More common: complex trait with any individual
SNP conferring small elevated risk
Published Genome-Wide Associations through 6/2010,
904 published GWA at p<5x10-8 for 165 traits
NHGRI GWA Catalog
www.genome.gov/GWAStudies
Published Genome-Wide Associations through 6/2010,
904 published GWA at p<5x10-8 for 165 traits
Clinical relevance of genomic associations

The product of minor allele frequency (MAF)
and odds ratio (elevated or decreased risk
relative to comparison population) of
condition of interest when the minor allele is
present.
MAF x OR

High MAF or high OR or both can make a
genetic finding clinically relevant
Example

CYP2C19 gene converts clopidigrel (Plavix)
to active metabolite.




1/3 of persons of European descent and 40% of
persons of African or Asian descent have loss of
function or gain of function variant alleles
Loss of function allele carriers have threefold
increased risk of stent thrombosis (2.9% vs. 0.9%)
Gain of function allele carriers have twofold increase
risk of bleeding
MAF (.3-.4) x OR (2-3) x observed risk in
comparison group with major allele
Bioinformatics: Human Health & Disease




Reference
 Plata G et al. Mol Syst Biol. 2010 Sep 7;6:408.[Columbia
University, NYC
Title
 Reconstruction and flux-balance analysis of the Plasmodium
falciparum metabolic network.
Aim
 To construct a genome-scale metabolic reconstruction of the
malaria parasite.
Methods
 Create an in-silico model of all gene products and their interactions
for P. falciparum
 Enzyme-gene associations were established for 366 genes and
75% of all enzymatic reactions.
Bioinformatics: Human Health & Disease


Reference
 Plata G et al. Mol Syst Biol. 2010 Sep 7;6:408.[Columbia
University, NYC
Results
 Create an in-silico model of all gene products and their interactions
for P. falciparum
 Enzyme-gene associations were established for 366 genes and
75% of all enzymatic reactions.
 The model was able to reproduce phenotypes of experimental
gene knockout and drug inhibition assays with up to 90% accuracy.
 Identified 40 enzymatic drug targets (i.e. in silico essential genes),
with no or very low sequence identity to human proteins.
 To demonstrate that the model can be used to make clinically
relevant predictions, authors experimentally tested one of the
identified drug targets, nicotinate mononucleotide
adenylyltransferase, using a recently discovered small-molecule
inhibitor.
Bioinformatics: Human Health & Disease

Reference
 Plata G et al. Mol Syst Biol. 2010 Sep 7;6:408.[Columbia
University, NYC

Importance

Clinically relevant example of the emerging field of systems
biology, starting with genome and predicting majority of the
molecular metabolism of a parasite cell.

Authors found a potential cure for drug-resistant malaria, identifying
a drug approved for other purposes.
Bioinformatics: Model Systems





Reference
 Barash Y et al. Mol Syst Biol. 2010 Sep 7;6:408.[University of
Toronto, Canada]
Title
 Deciphering the splicing code.
Aim
 To understand how alternative splicing of gene products explains
the disparity between numbers of genes and numbers of proteins
produced by those genes.
Methods
 Developed algorithm capable of predicting splice variants by tissue
type.
Results
 Detected a class of exons that promote genes during
embryogeneis and by alternative splicing silence same genes in
adulthood.
The Practice of Bioinformatics





Reference
 Eriksson N et al. PLoS Genet. 2010 Jun
24;6(6):e1000993..[23andMe, Mountain View, California]
Title
 Web-based, participant-driven studies yield novel genetic
associations for common traits.
Aim
 Describe new genetic findings discovered by conducting voluntary
surveys of persons who purchased their own genotypes.
Methods
 Examination of 22 common traits by approximately 10,000
participants.
Results
 Replicated published findings for hair color, eye color, freckling.
 Discovered novel gene associations for hair morphology, ability to
smell asparagus metabolites in urine, and photic sneeze reflex.
The Practice of Bioinformatics

Reference
 Eriksson N et al. PLoS Genet. 2010 Jun
24;6(6):e1000993..[23andMe, Mountain View, California]

Importance

Recreational genomics is capable of scientific discovery.
The Practice of Bioinformatics




Reference
 Denny JC et al. Bioinformatics. 2010 May 1;26(9):1205-10. Epub
2010 Mar 24. [Vanderbilt University, Nashville, TN]
Title
 PheWAS: demonstrating the feasibility of a phenome-wide scan to
discover gene-disease associations.
Aim
 Create a novel discovery method using genome scans combined
with longitudinal EMR data.
Methods
 “Turn GWAS on its head” using EMR-derived phenotype data to
perform correlations between genetic variation and clinically
important conditions.
 Developed a code translation table to automatically define 776
different disease populations and their controls using prevalent
ICD9 codes derived from EMR data.
 Beginning with SNPs known to be associated with a single disease,
look for other expected and unexpected disease associations.
The Practice of Bioinformatics



Reference
 Denny JC et al. Bioinformatics. 2010 May 1;26(9):1205-10. Epub
2010 Mar 24. [Vanderbilt University, Nashville, TN]
Results
 Four of seven known SNP-disease associations using the PheWAS
algorithm were replicated with P-values between 2.8 x 10(-6) and
0.011.
 The PheWAS algorithm also identified 19 previously unknown
statistical associations between these SNPs and diseases at P <
0.01.
Importance
 Takes advantage of unique strength of EMR systems (natural cooccurrence of diseases) to correlate genomic scanning (all possible
observable genotypes) with all possible diseases as represented in
EMR systems.
 Shows EMRs can be used both for validation of research findings
in real world settings, and for discovery of new genetic
associations.
Computational Biology
and Bioinformatics
Questions and Comments
Top Five List of
Notable Events
in the Past 12 months
“Top Five” Events
5. October 27, 2010. First phase of 1000 genomes project
data released. Of 180 complete genomes sequence, each
has 50-100 variants associated with disease. “No human
carries a perfect set of genes.”
“Top Five” Events
“Top Five” Events
5. October 27, 2010. First phase of 1000 genomes project
released. Of 180 complete genomes sequence, each has
50-100 variants associated with disease. “No human
carries a perfect set of genes.”
4. AMIA’s profile and impact on national policy continues to
grow: ONC, Institute of Medicine, NCVHS
“Top Five” Events
5. October 27, 2010. First phase of 1000 genomes project
released. Of 180 complete genomes sequence, each has
50-100 variants associated with disease. “No human
carries a perfect set of genes.”
4. AMIA’s profile and impact on national policy continues to
grow: ONC, Institute of Medicine, NCVHS
3. ONC funding for informatics R&D flows through SHARPs,
BEACONs, state HIE’s, and for Advancing Clinical
Decision Support
“Top Five” Events
5. October 27, 2010. First phase of 1000 genomes project
released. Of 180 complete genomes sequence, each has
50-100 variants associated with disease. “No human
carries a perfect set of genes.”
4. AMIA’s profile and impact on national policy continues to
grow: ONC, Institute of Medicine, NCVHS
3. ONC funding for informatics R&D flows through SHARPs,
BEACONs, state HIE’s, and for Advancing Clinical
Decision Support
2. July 28, 2010. Final Rule for Standards, Implementation
Specifications, and Certification Criteria for Electronic
Health Record Technology published
And the #1 top event of
2010 is…
“Top Five” Events
5. October 27, 2010. First phase of 1000 genomes project
released. Of 180 complete genomes sequence, each has
50-100 variants associated with disease. “No human
carries a perfect set of genes.”
4. AMIA’s profile and impact on national policy continues to
grow: ONC, Institute of Medicine, NCVHS
3. ONC funding for informatics R&D flows through SHARPs,
BEACONs, state HIE’s, and for Advancing Clinical
Decision Support
2. July 28, 2010. Final Rule for Standards, Implementation
Specifications, and Certification Criteria for Electronic
Health Record Technology published
1. July 13, 2010. Meaningful Use Final Rule published
2010: Informatics’ Big Chance Continues
Content for this session is at:
http://dbmichair.mc.vanderbilt.edu/amia2010/
including citation lists and links
and this PowerPoint