The use of ALN in tracking student-patient interactions during clinical rotations at geographically dispersed locations

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The use of ALN in tracking student-patient
interactions during clinical rotations at
geographically dispersed locations

• Graham Shaw
• School of Natural Health Sciences and School of
  Graduate Medical Sciences, Barry University,
  Miami Shores, FL

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Coauthors

• Stephen Morewitz, Ph.D
• Stephen J. Morewitz and Associates,
• Buffalo Grove, IL.
• Joel Clark, DPM
• Department of Surgery,
• California School of Podiatric Medicine,
• St Marys Medical Center,
• San Francisco, CA

Journal of the American Podiatric Medical
Association Vol 93. (2) 2003.
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Contents

• Context
• Historical background
• Traditional student logs
• Limitations of traditional system - a need for
  change
• Description of the web-based ALN used to track
  student-patient contact
• Advantages of this model to the student (as well
  as to faculty/administrators)
• Student perceptions of and attitudes toward the
  ALN as described.
• Identify obstacles to the use of the ALN model.
• Applications in other teaching disciplines

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Podiatric Medical EducationThe curriculum

• Years 1 and 2
• Basic Medical Sciences
• Didactic Clinical Sciences
• Some clinical rotations
• Years 3 and 4
• Mostly monthly clinical rotations at distance
  from college
• Learners are geographically dispersed

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During these clinical rotations

• Student patient interaction the learning
  situation.
• Diversity across different clinical disciplines.
• Onsite clinical faculty
• Students collect data about their clinical
  encounters.
• Traditionally in the form of a dairy or
  paper-based log.

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Paper-based log systems

• NO doubt that recording patient-student
  interaction is valuable to both student and
  school.
• Variety of documentation (log) systems in place
  throughout U.S.
• Case books
• Optically scanable forms
• Pocket-sized cards ? Tabular data entry
• Move toward computer based systems
• Hand held/Palm computers
• Email communication of excel spreadsheets

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Information traditionally collected using log
system

• Date
• Location
• Supervisor/Attending clinician
• Student name
• Degree of student responsibility
• Patient name/number, age and gender
• Diagnosis
• Clinical procedures (performed, assisted or
  observed).

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Sample logbook 1
Student name and patient details deleted
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Sample logbook 2
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Limitations of paper-based systems

• Handwritten patient-encounter logs often
  difficult to analyze.
• Data processing requirements staggering.

Dr John Nelson Dean of Clinics Barry
University, SGMS
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Need for change

• Paper-based systems have limitations.
• Students time on rotations is valuable.
• Students need to have access to all their patient
  encounter data.
• Faculty would benefit from access to current
  accurate student data.

So what next?
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A new systemALN used to track student-patient
interactions

• Clinical faculty collaborated with William F.
  Matheny and Associates.
• Developed a web-based delivery system.
• Incorporates drop-down menus of treatments and
  diagnoses.
• Tested by small group of students.
• Refined based on input from focus groups.
• In operation for 1 year.

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Students log into the ALN during their clinical
rotation
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Student options following login
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Students can enter their patient encounter data
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Drop down menus allow rotation location to be
entered
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as well as a diagnosis
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Students can access their activity log to monitor
progress
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This student can access ALN and see that they
saw 27 patients in the selected time frame
Obs Observation only GT 50 Greater than 50
active involvement LT 50 Less than 50 active
involvement
Hypothetical student
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Students can assess the patients they saw during
a given rotation
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This student saw 6 patients during a third year
diabetic clinic rotation
Hypothetical student
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Contact logs can be printed out
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Diagnostic and treatment codes and available for
reference
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Faculty view
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Faculty view on login
Lets click on student log reports to track a
students patient encounters
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Lets first select a class say 2003
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Then a particular student a rotation a location
and a time frame
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Data reproduced with permission
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A total of seven contacts at the 3rd year
diabetic clinic
Personal data omitted
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By selecting activity log usage report
We can see how often each student uses the ALN
system
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Student participation

• For the Class of 2003
• 1/1/2001 6/1/2003
• Compliance 98.5
• Student use of the log varied from 1165 entries
  to 123
• Mean 655 224

Names of students deleted from center column
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Diagnosis Treatment Comparison By Month Report
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Lets see the diversity of patients seen by the
class of 2003 at the 3rd year diabetic clinic
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At the diabetic clinic in 2002

• The class of 2003 recorded 1254 patient
  contacts.
• 105 different diagnoses from abdominal pain ?
  walking difficulties.
• Most common 143 patients with diabetes
  w/neuropathy and 47 with Diabetes w/perif vasc
  dis.
• 53 different treatment from casting ? X rays.

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At the CCPM core site

• The class of 2003 recorded 7961 patient
  contacts.
• 141 different diagnoses from abdominal pain ?
  walking difficulties.
• Most common 767 patients with diabetes
  w/neuropathy.
• 45 different treatments.

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ALN student patient log data

• The frequency with which students used the log.
• Number of diagnoses per student.
• Mean number of treatments per student.
• Mean number of a given type of treatment.
• Mean number of diagnoses per dept/rotation.

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Uses of ALN log data

• Student assessment.
• Evaluating the extent to which rotation
  objectives have been met.
• Program evaluation and accreditation.
• Program development.

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Strengths of the ALN log system

• The system provides a cumulative record for the
  student of actual clinical experiences.
• Increased accuracy of data.
• The data in the ALN can be viewed easily.
• Facilitate report generation.

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Preliminary observations from those using the ALN

• Improvements in the following areas
• Accessibility
• Accuracy of data reporting
• Ease of report generation
• Security and privacy

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Early student perceptions of ALN system

• Helpful in documentation of patient interactions.
• Easy to use.
• Comprehensive.

"The logs helped prepare me for completing the
residency logs and keeping track of my patients
during clinics."
"A great idea that can be developed"
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Possible obstacles to use of ALN system

• Resistance to technology
• Lack of computer knowledge/training
• Lack of confidence
• Access
• Lack of time
• Technical problems with the system

"The student logs were time consuming to
complete."
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Applications of ALN tracking system to other
disciplines

• Any programs that involve students leaving campus
  to learn in the field
• Nursing
• Dietetics
• Veterinary
• Medicine
• Anesthesiology
• Cardiovascular perfusion

Physician Assistant students at Barry University
perform procedures under supervision
(above). Students of cardiovascular perfusion
observe open heart surgery (below)
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Summary

• The traditional paper-based approach to
  maintaining student-patient logs can suffer from
  limitations of accuracy, legibility and workload
  for students and faculty.
• At this early stage it appears that the ALN
  system represents an improvement in all these
  areas and enables more effective student
  monitoring during clinical rotations and report
  generation.
• Early student perceptions of the ALN are
  generally positive.
• Though some students complained about the time
  needed to complete the contact data the
  anticipated obstacles to student use of the ALN
  system did not materialize.
• ALN has applications in any learning environment
  that occurs at a distance to the central campus.

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References and further reading

• Shaw, G.P. et al., (2003). Journal of the
  American Podiatric Medical Association Vol 93.
  (2) 150 156.
• Alderson, T St J and Oswald, N.T (1999). Medical
  Education. 33. 429 433.
• Dolmans et al., (1999). Medical Education 33 (2).
  89 94.
• Vanek, E et al., (1993). Teaching Learning in
  Medicine 5 (3). 164 168.
• Asgari-Jirhandeh, N. and Heywood, J. (1997).
  Medical Education 31 (3). 225 9.