AMIA 2010

The following originally appeared on HIT Shrink.

My first AMIA meeting and I'm finding it filled with all sorts of goodies. There's lots of tweeting going on, too. (Go to TweetChat with hashtag #AMIA2010 to keep up.)

I typed some notes and thought I'd put them here (1) so I can find them again easy and (2) some folks may find them useful (thought maybe somewhat cryptic).

%u25BC AMIA 2010 Susan Dentzer, Editor Health Affairs

2010.11.14

%u25BC "Golden Age" of PPACA (?)

• compared Greek myth of Ae____ to Obama

%u25BC Open up goldmine of data to public

• CHDI website www.hhs.gov—open

• use data to shape community responses to childhood obesity... Children's Optimal Health

%u25BC [] l/u Health Affairs 2010 Nov 29:2047

• rapid-cycle improvement of medical home care @Geisnger

• reductions in risk-adjusted chronically ill hospital admission and readmission rates

%u25BC Three Aims

• 1. Better Health

• 2. Better health care

• 3. Better value

%u25BC IOM study on variations

• look at var in HC spending, pt diversity, MD decisions on what care to give and evidence

%u25BC Shared decision making by pts

• ACA provision

• even informed pts don't exercise their options well

• preference-sensitive care

%u25BCQuotations

• Quotes by George Carlin, Churchill on American People

• Quote by Jerry Garcia re Somebody has to do something and it is pathetic that it must be us

%u25BC Informatics Issues in HIEs

20101114 Rob Kolodner, Session chair

%u25BC Development and use of a Medication history Service Associated with a health information exchange: Architecture and Preliminary findings

M. Frisse, Vanderbilt Center for Better Health; L. Tang; A. Belsito, M. Overhage, Regenstrief Institute

• Memphis HIE in use 4.5 yrs... still a pilot going to full force

• 48% had full med hx; getting retail pharmacies online made a big different

• 36% pt not located

• $4 generics good for pts, bad for accurate HIE data

%u25BC Emergency Medical Services: the frontier in health information exchange

JT Finnell, M. Overhage, Regenstrief Institute

• Project: push HIE data out to EMS staff in 2 counties in Indiana (Siren by Medusa), using ruggedized tablet PC

• Uses LN, FN DOB Gender, can add zip and SSN optional

• Pushes back a pdf with a bunch of data: med list, allergies, DNR status, NOK notification, PMH

• Started at 15% requests to 26% of field pts seen

• 14% of medics never used

• connectivity a problem

• 41% medics nearly always queried system

• 66% said data was important for providing care

• "truth serum" effect (we can look it up if you don't tell us the truth)

• Value with heavy utilizers and pts "found down"

%u25BC Private Medical Record Linkage with Approximate Matching

E. Durham, Y. Xue; M. Kantarcioglu; B. Malin, Vanderbilt University

• Vanderbilt -- Emory: Flaw in current model for sharing de-identified data

• If pts don't match, they can be overcounted

• prob with fragmented data (spelling, missing data, etc)

• Private Record Matching can improve this using a hash function to maintain privacy but compare individuals

• Steps:

• blocking (toss out some)

• field comparison

• similarity function measures degree of similarity using a comparison vector and into a record pair similarity score

• draw a line where scores above a number are considered a match

• record pair comparison and classification

• Fellegi-Sunter probability vectors: uses log function of an agreement weight and a disagreement weight for each field (eg, FN, LN, MOB)

• Sum the similarity scores across all fields

• Used a data corrupter function to mess up experimental data to see if they get rematched

• looked at accuracy vs runtime

• Main thing they did was to use approximate matching rather than binary matching, leading to increase in accurate matches

• Note: they used a centralized approach but hope to extend ot decentralized model.

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