2018 July JAMIA Journal Club Webinar

July 12, 2018
3:00PM
4:00PM
EST
Fee: 
Free for AMIA members; $50 for non-members
Presenters: 
Benjamin A. Goldstein, PhD

Designing risk prediction models for ambulatory no-shows across different specialties and clinics

Co-author Benjamin Goldstein will discuss this month's JAMIA Journal Club selection:

Ding X, Gellad ZF, Mather C 3rd, Barth P, Poon EG, Newman M, Goldstein BA. Designing risk prediction models for ambulatory no-shows across different specialties and clinics. J Am Med Inform Assoc. 2018 Feb 9.  doi: 10.1093/jamia/ocy002. [Epub ahead of print] 

Presenter

Benjamin A. Goldstein, PhD
Assistant Professor
Department of Biostatistics & Bioinformatics; Duke Clinical Research Institute
Duke University
Durham, NC

Dr. Benjamin A. Goldstein is Assistant Professor of Biostatistics & Bioinformatics at Duke University, joint with the Duke Clinical Research Institute. His research interests are in the meaningful use of Electronic Health Records data. His work sits at the intersection of biostatistics, biomedical informatics, epidemiology and machine learning. He works closely with the Duke University Health System developing and implementing clinical decision support tools. Dr. Goldstein received his PhD in Biostatistics from UC Berkeley. Additionally, he serves as the data science lead for the Children's Health & Discovery Initiative. 

Format

  • 40-minute presentation by article authors considering salient features of the published study and its potential impact on practice.
  • 20-minute discussion of questions submitted by listeners via the webinar tools and moderated by JAMIA Student Editorial Board members

Interactive/Evaluations

  • Follow @AMIAinformatics and #JAMIAJC for Journal Club information.
  • Participants also receive short feedback surveys to evaluate the JAMIA JC webinar.

Managers

JAMIA Journal Club managers are JAMIA Student Editorial Board members:

Lucy Lu Wang, PhD Candidate, Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 


Yinan Zheng, Post-doc, Northwestern University, Center for Population Epigenetics, Evanston, IL



Citation

The PubMed citation for the paper under discussion is:

Ding X, Gellad ZF, Mather C 3rd, Barth P, Poon EG, Newman M, Goldstein BA. Designing risk prediction models for ambulatory no-shows across different specialties and clinics. J Am Med Inform Assoc. 2018 Feb 9.  doi: 10.1093/jamia/ocy002. [Epub ahead of print]  

Students who are not AMIA members, but whose academic institutions are members of the Academic Forum, are eligible for a complimentary JAMIA Journal Club registration. Please contact Susanne Arnold at susanne@amia.org for the discount code. In the email, please include: full name, Academic Department, and the primary Academic Forum representative of that Academic Department. Note that AMIA Student memberships are $50, which allow access to JAMIA, all JAMIA Journal Clubs, and other webinars of interest to the biomedical informatics community. 

Statement of Purpose

The preponderance of data available in electronic health records have been widely used for the development of predictive models. Due to ease of implementation, many predictive models are implemented globally across a health system, without considering whether they need to be tailored to specific patient sub-populations.

Appointment no-shows are a problem in all health-care settings, leading to reduced clinician productivity, and more importantly, contributing to poorer patient outcomes. A predictive model that could help identify those patients at greatest risk for missing or last-minute cancelling of an appointment could help health care facilities reduce the number of no-shows. Moreover, most clinical departments serve different patient populations, each likely having different risk factors for No-Shows.

In this study we considered the different levels at which one could build a risk model for outpatient no-shows. Specifically, we compared models built at the health system, specialty and clinic levels. While clinic level models typically performed best, this result depended on the specific specialty. Moreover, this result did not depend on clinic size suggesting it is more driven by the degree of clinic heterogeneity than statistical power.

These findings highlight the importance of tailoring risk models to the care setting in which they will be employed.  

Target Audience

The target audience for this activity is professionals and students interested in biomedical and health informatics.

Learning Objectives

After this live activity, the participant should be better able to:

  • Weigh variables that are important in creating a risk prediction model for no-shows in one’s institution
  • Assess whether a risk model should be implemented globally or locally across a health-system
  • Consider when to turn a health-system based project into a research project

Faculty

Benjamin A. Goldstein, PhD
Assistant Professor
Department of Biostatistics & Bioinformatics; Duke Clinical Research Institute
Duke University
Durham, NC

Accreditation Statement

The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Credit Designation Statement

The American Medical Informatics Association designates this live activity for a maximum of 1 AMA PRA Category 1 Credit(s)™ Physicians should claim only the credit commensurate with the extent of their participation in the activity. 

Criteria for Successful Completion

Completion of this live activity is demonstrated by:

  • Viewing the live webinar
  • Optional submission of questions via webinar feature
  • Completion of the evaluation survey emailed at the webinar's conclusion, and 
  • Verification of attendance through the participant's electronic report through the individual login to AMIA Central at www.amia.org. 

The physician participant will be able to generate a CME certificate through the AMIA automated system. 
For a certificate of completion, contact Pesha@amia.org.

Commercial Support

No commercial support was received for this activity.

Disclosure Policy

As a provider accredited by the ACCME, AMIA requires that everyone who is in a position to control the content of an educational activity disclose all relevant financial relationships with any commercial interest for 12 months prior to the educational activity.

The ACCME considers relationships of the person involved in the CME activity to include financial relationships of a spouse or partner.

Faculty and planners who refuse to disclose relevant financial relationships will be disqualified from participating in the CME activity. For an individual with no relevant financial relationship(s), the participants must be informed that no conflicts of interest or financial relationship(s) exist.

AMIA uses a number of methods to resolve potential conflicts of interest, including: limiting content of the presentation to that which has been reviewed by one or more peer reviewers; ensuring that all scientific research referred to conforms to generally accepted standards of experimental design, data collection, and analysis; undertaking review of the educational activity by a content reviewer to evaluate for potential bias, balance in presentation, evidence-based content or other indicators of integrity, and absence of bias; monitoring the educational activity to evaluate for commercial bias in the presentation; and/or reviewing participant feedback to evaluate for commercial bias in the activity.

Disclosures for this Activity

These faculty, planners, and staff who are in a position to control the content of this activity disclose that they and their life partners have no relevant financial relationships with commercial interests: 

JAMIA Journal Club Faculty: Benjamin A. Goldstein
JAMIA Journal Club planners: Yinan Zheng; Lucy Lu Wang
AMIA staff: Susanne Arnold, Pesha Rubinstein
JAMIA Student Editorial Board Advisor: Michael Chiang

Instructions for Claiming CME/CE Credit

CME site (MyAMIA) works best with IE 8 or above version, Chrome, Safari, and Firefox.

  • Login to your account at amia.org; in upper right hand corner, click on AMIA Central
  • Go to “My Events" under Membership/Activities
  • Click “Apply for Credits" for this webinar
  • Follow the instructions on the Credit Registration page. Be sure both drop-down menus say “physician”
  • To print out your certificate, go to "My CME/CE Credits" under Membership/Activities.
  • Physicians will be able to print out or save their CME certificates.
  • Other attendees: if you require a certificate of participation, please contact pesha@amia.org

Contact Info

For questions about content or CE, email Pesha@amia.org. For questions about webinar access, email Susanne@amia.org.