OntheFly Data Collection by Hospitalists

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On-the-Fly Data Collection by Hospitalists
Why?
How?
Need good data Limited money

• Informed consent
• Design features

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Methods of Systematic Data Collection
Chart Review
Interview
Patient
Patient
Hospitalist
Hospitalist
Medical Record
Medical Record
Collector
Collector
Database
Database
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Problem with Chart Review Quality of Data
Chart Review
Goldman Model to Predict Major Cardiac Events in
72 Hours
Patient
Hospitalist
Medical Record
Collector
Goldmans Definition of Unstable Angina A
worsening of previously stable angina OR The new
onset of postinfarction angina OR Angina after a
coronary-revascularization procedure OR Pain that
was the same as that associated with a prior
myocardial infarction
Database
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Problem with Prospective Interview Cost
Weekdays 40 hours per week X 20 per hour X 12
weeks 9600 Weekends 10 hours per week X 25
per hour X 12 weeks 3000 Foreign Language
Patients 10 per phone interpreter X 100
patients 1000 TOTAL 13,600
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Methods of Systematic Data Collection
Chart Review
Interview
On-the-Fly
Patient
Patient
Patient
Hospitalist Collector
Hospitalist
Hospitalist
Medical Record
Medical Record
Medical Record
Collector
Collector
Database
Database
Database
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Inconvenient
Impossible
Not Practicable
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1 Minute Script for Requesting Verbal Informed
Consent to Collect Routine Patient Data in Short
Stay Unit

• Done after SSU attending physician finished
  history and physical exam.
• SSU Attending I work in this unit, which is
  called the Short Stay Unit. We are studying
  patients like you who
• Physician are admitted to this unit. The goal
  of this study is to better understand which
  patients are served best by this unit.
• As part of routine care, I have already begun to
  evaluate your case. Now I would like to record
  some of the information that I gathered in a
  protected database for analysis. In addition,
  when you are discharged from the hospital, I
  would like to re-examine your medial record and
  collect some further data about the length of
  this hospital stay and what kind of tests were
  ordered while you were here. Would this be OK?
• If NO, then STOP.
• If YES I am leaving an information sheet to
  remind you of the purpose of this study and to
  give you a phone number to call if you should
  have any questions.
• Thank you.

751 out of 755 patients admitted to the Short
Stay Unit during 4 months agreed to participate.
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The Informed Consent Issue May Resurface
You
IRB
You
Lo and behold! Our results are generalizable!
Will you publish our manuscript?
OK. Then no informed consent is needed.
My systematic data collection project is not
generalizable. It is merely a QI project.
Journal Editor
You
IRB
You must have approval from an Institutional
Review Board, preferably at the site of the
study, and describe your method of informed
consent.
Having no informed consents from research
subjects, can I get your approval to publish this?
Hmm . . .
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SSU Patient Characteristics (n 751)
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SSU Admission Diagnoses (n 751)
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Risk Stratification based on Validated Models for
2 Most Common Diagnoses (n 641)
Abbreviations ACS, acute coronary syndrome. a
Goldman et al. predicts major cardiac events in
72 hours. b Fonarow et al. predicts in-hospital
mortality rate.
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Services received by enrolledshort stay unit
patients (n 738)
a 18 patients received both an ETT and a resting
echocardiogram.
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Hospitalist-Run Short Stay Unit Research Questions

• What types of patients do we admit?
• 94 cardiovascular
• 90 very-low or low risk
• 75 require advanced tests, acute care
  treatments, or consultations
• Which patient characteristics predict when a
  patient has a long stay or requires admission to
  traditional inpatient services?

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Unsuccessful SSU stays Length-of-stay greater
than 72 hours or admission to traditional
inpatient services (n 738)
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Multivariable logistic regression models that
identify factors associated with unsuccessful
stays
a Odds ratios are adjusted for age,
insulin-requiring diabetes mellitus, whether or
not patients were hospitalized during the last
year, short stay unit attending physician, day of
the week of SSU admission, and all other
variables listed.
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Scholarly Projects Made Possible with On-the-Fly

• Hospitalist-Run Short Stay Unit
• Lucas BP, Kumapley R, Mba B, Nisar I, Lee K,
  Ofori-Ntow S, Borkowsky S, Asmar A, Lewis T,
  Bienias JL. A hospitalist-run short stay unit
  features that predict patients length-of-stay
  and eventual admission to traditional inpatient
  services. J Hosp Med. In press.
• Lucas BP, Tchernodrinski S. High recidivism rates
  after discharge from a hospitalist-run short-stay
  unit preparing to reduce the frequent flyer
  effect. J Hosp Med 2007 2(Suppl2)22. Poster
  presentation, National Society of Hospital
  Medicine Meeting, Dallas, Texas.
• Hospitalist-Run Exercise Treadmill Testing
  Laboratory
• Lucas BP, Ezeokoli C, Deshpande A, Borkowsky S,
  Kumapley R, Lee K, Ofori-Ntow S, Patel M, Mba B,
  Baru J, Asmar A, Candotii C. A Hospitalist-Run
  Exercise Treadmill Testing Laboratory in an
  Emergency Department. J Hosp Med 2008
  3(Suppl1)66. Poster presentation, National
  Society of Hospital Medicine Meeting, San Diego,
  California.
• Hospitalist-Run Bedside Procedure Service
• Asbury J, Lucas BP. PICC-ing up the pace a new
  hospitalist service for peripherally inserted
  central catheters. J Hosp Med 2007 2(Suppl2)4.
  Poster presentation, National Society of Hospital
  Medicine Meeting, Dallas, Texas.

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