MACMLA 2016: Diversity and Disparities: Opportunities and Challenges for 21st-Century Health Care

  • Under-represented groups represent 34% of the total population
  • Diversity in health care work force
    • Physicians: 7%
    • Nurses: 3%
    • Pharmacists: 3%
  • No Ivy League schools are among top medical schools that American Indians, Alaska Natives, or African Americans apply
  • Top medical schools for Hispanic or Latino schools are all in Puerto Rico
  • Business case for diversity in science
    • Birds of a feather research together — and produce research in journals with lower impact factors and less cited
  • Implicit association test 
  • 16% of NIH grant applications from black researchers succeed vs 29% from whites
  • AAMC report on state of women in medicine lacked any mention of intersectionality
  • Four patterns of gender bias
    • Feel need to “prove” our competence
    • Walking the tightrope between too aggressive vs too feminine/weak
    • Motherhood penalty
    • Queen bee syndrome (women who refuse to mentor the next generation)
  • JHU Institutional Plan to address
    • Faculty Diversity Action Plan
    • Diversity Advocate
    • $25M JHU Diversity Initiative
    • 54 URM Faculty hired in FY15-16
    • 3 women dept directors
    • 3 URM dept directors
    • Pipeline programs -HCOP, SARE

MACMLA 2016: Paper Session 1

Building a Critical Mass of Systematic Review Authors and Teachers: A Collaboration between Librarians and Faculty

  • What is the rate of systematic reviews for comparable institutions (those without med schools)?
  • Need to meet with Deans, Directors, Faculty to determine needs
  • Work with researchers on currently publishing SRs & MAs
  • Interest in non-HS programs like Educational Technology, Psychology/Counseling, Statistics, & College of Liberal Arts (ex: Health Care Ethics)
  • Grant from NNLM for on-campus event for training on SRs
  • Created LibGuide and online community for on-going support (basic focus but decent guide usage even before official launch)
  • Speakers were a combination of experts and local researchers
  • Workshop topics
    • Importance of SRs, process
    • Breakout sessions on meta-analysis, integrating EBP into teaching
    • Panel discussion on opportunities and barriers
  • Librarian training
    • 3 options: UofMichigan workshop, Pitt program, applied project for university conference
  • Workshop attendance filled in days (n=27)
  • SRs in Education
    • class presentation, UG research symposium, critically appraised topics, IPE Health Research Skills course

Assessing Value of Library Services on Research, Clinical Practice, Education, and Administration

  • Had done Library Values survey 5 years prior
  • Benefits of informationists services (overall results, but different audiences have different rates per category)
    • information search (56%)
    • point of use instruction (19%)
    • citation management (9%)
    • publication/grant prep (4%)
  • students rank coursework as the highest indicator for intended use of library resources
  • What resources people used with and without informationists
    • with Informationists, more likely to use more resources, and resources like CINAHL, Embase, etc
    • without, more likely to use Google or Dynamed

MEDLIB 2011-2016

  • 5 year analysis of content and comparison with 1997 article analysis
  • as of 2016, MEDLIB-L has ~2000 subscribers (35% education domains, 23% healthcare orgs/hospitals)

One systematic review software to rule them all — NOT!

  • EndNote web works terribly for researchers across different institutions
  • Mendeley sinks beautifully across users but does not have as much space for PDF space (without payment)
  • RefWorks crashed with large RIS file due to timeout
  • SRAssistant deduplication – unsure how well it works
  • **checkout expert searching listserv
  • RefMan only available to Cochrane reviewers
  • SRDR wonderful but clunky due to framing
  • Covidence – can’t have more than 1 person assigned to an article; after 2nd reviewer, then the article moves out of the pool of review


MACMLA 2016: Using Data to Improve Clinical Outcomes — Examples and Lessons Learned from Cleveland OH

  • Started with EHR in 1999 (some patients have up to 17 years  worth of data in the EHR)
  • Broader use with 2012 for enterprise-wide EHR adoption – starting with Meaningful Use 1 and progressed forward
  • Paper health records:Hammer :: Electronic health records:Power nail gun — increased power due to tech, but also large potential for more problematic outcomes
  • Case #1 of EHR’s potential – identifying the significant underdiagnosis of hypertension in children — data was available but just not applied
    • Response: Put in an alert to better identify/highlight existence of data
    • Baking the evidence based guidelines into the EHR (CDSS)
      • 38% decrease in false positives
      • 100% increase in provider recognition of abnormal blood pressure
    • Answer: Alerting helps, but not the total fix
  • Case #2 – Immunizations
    • Over 300 immunization rules for children — how do you know if your patient has completed their schedule?
    • Messaging algorithm to reach out to patients using TeleVox about immunization follow up
    • Messages helped increase results by 1/4, but not a perfect fix for the other 3/4
    • Number needed to message 4 people to get 1 immunized
    • $5k in messaging costs led to $200k clinical revenue
    • Personal Health Records
      • Patients will be the biggest amount of EHR users in the future
      • PHR allows for reminders, health info exchange (ex: immunization)
  • Case #3 – Meeting referral drop-off between obesity clinic to specialist
    • 76% referred but never seen
    • So what is the actual appointment follow through within a month after referral? 48%
    • Solutions: self-scheduling + giving specialists a list of patients so they know who is referred and they can take over outreach
    • Moved to 61% after new interventions (6700/month initial consults = $1mil
  • Case #4 – Depression Screening
    • Advanced CDSS for subjective data
    • Use PHQ-9
  • Case #5 – Health Information Exchange
    • Who is likely to have their data exchanged?
      • Older people, female, African Americans, Medicare/Medicaid
    • +1 mil patient records a day exchanged among those on EPIC system
  • Case #6 – Longitudinal diabetes data
    • Synopsis report of data overtime

Q&A notes

  • Information is getting smarter to not just be one click away to Micromedex or UpToDate as a general resource, but one click away from the specific drug entry in Micromedex or UpToDate
  • People in health care do not value information and its integration well into clinical practice — how do we change this paradigm? Informaticists
  • What are the opportunities for librarians to offer education on informatics/EHR competencies
  • Re: alert fatigue – who should the alert be going to? Is adding more info to the 15 min visit overload? What would be a better time? How actionable are these alerts that are provided in the visit?
  • 100% of privacy/security is not realistic, but we need processes in place like credit reports to help manage the inevitable

Follow up readings

PRIM&R’s Primer on the Notice of Proposed Rulemaking (NPRM) Webinar

The following notes stem from the proposed rulemaking for the Federal Policy for the Protection of Human Subjects (Sept. 8, 2015)

MLA 2015: Plenary Session IV: Eszter Hargittai

Web of Opportunity or Web of Confusion? The Role of Skills in Internet Use

  • we can intervene and focus on skill development
  • generational myths
    • all young people are digitally savvy
    • young people are savvier than older people
  • who benefits most from their digital media uses?
    • social mobility vs social reproduction
    • digital divide
  • web-use skills
    • awareness and understanding
    • efficient info seeking
    • credibility assessment
    • participation
      • joining communities
  • what are the outcomes of these — get jobs, get involved in policy making, better health outcomes?
  • main data sources for studying Internet skills
    • in-person
    • observations and inteviews
    • surveys
  • waves of data overtime
  • use an attention check question
  • 34% of students didn’t know what BCC was about
  • 88% of students could not correctly identify a reliable URL
  • gender and skill (ex: reading) — women rate themselves lower, but it might be self-perception errors vs objective evaluation, but the perception still affects skill and behavior online
  • more skilled people tend to be more active online

MLA 2015: Joseph Leiter NLM/MLA Lecture: Ann McKee

Boxing, Football, and the Brain – Ann McKee

MLA 2015: Top Tech Trends

What Will These Technologies Look Like Twenty Years from Now? (aka How 1995 technologies look in 2015)- Eric Schnell

The Quantified Self – Jon Goodell, AHIP

The Internet of Things – Kimberley Barker

Zombie Emergency!: A Tool for Gamification and Promotion – Jason Bengtson

Apple Watch – Dale Prince

  • it is not intuitive
  • it has 5 inputs, 4 outputs
  • Siri works better on the watch than the phone
  • better dictation on the watch than the phone
  • the speaker isn’t that great but it is enough to disrupt a meeting
  • phone battery drains more quickly
  • watch has no GPS, so you have to have your phone with you to use things like MapMyRun
  • the watch can tell you how far you ran by itself
  • dictation does not give you an option to edit incorrect words
  • emails – you can mark it as unread, flag it, or trash it — not respond to it
  • there are games – TicTacToe

MLA 2015: Open Access and the Library Infrastructure

Open Access Roles for the Library – Anneliese S. Taylor

  • UCSF – 2nd highest recipient of NIH Funding
  • 2014 was when compliance reports went out and issues were identified
  • 160-170 consultation requests in response (~55 hours)
  • also reaching out via instruction sessions
  • provides monthly updates on webpage regarding compliance rate
  • UCSF Open Access Policy passed in 2012
  • UC-wide policy passed in 2013
  • Publication harvester live in October 2014
  • UCSF participation began in 2015
  • manual system = 1 article deposit; harvester system = 400 articles deposited
  • OA publishing fund with funds from Academic Senate
  • DataShare – open data repository for data searching; depositing is restricted to UCSF; the platform is format and subject agnostic, but not a curated system

Replicability and Reproducibility of Research Using an Open Data Set – Bart Ragon

  • Looked at the “The value of library and information services in patient care” dataset in ODUM
  • looked at the specific items of UpTodate, MD Consult,
  • role, age, and gender didn’t have any effect
  • challenges with the dataset
    • no codebook
    • tech download issues that required going back to data creators who had to go back to IT
    • age data collapsed into larger categories (0-45 vs 45+) to protect identities of participants — made it not possible for him to replicate the study results since he didn’t have the same raw data
  • in comparison to public access policy trends, we may be looking at being 10 years out before really regulating open data policies

Promoting Open Educational Resources and Other Alternatives to Traditional Textbooks – Lea Leininger

  • some matching between OER textbooks and topics; mostly helpful for Humanities
  • SPARC presentation along with bookstore representative
  • mini-grants provided for faculty to develop during 2015-2016 ($1k each)

When “How hard can it be?” becomes “a Sisyphean task”: Framing a data-sharing platform for developmental health outcomes – Cunera M. Buys, Pamela L. Shaw

  •  Data Repository Needs Assessment Team (DRNAT) = 6-month project
  • used Purdue Data Curation Profiles Toolkit for 5 researcher interviews
  • 3 out of 5 = data dictionary
  • 4 out of 5 = code book
  • although some had code books or data dictionaries, some still didn’t think the data was described enough to be understood by others
  • “scooping” concerns
  • literature review from July-Nov 2014

MLA 2015: Legislative Update