BioMedical Informatics CoreUpdate

ICON Annual Meeting, April 22, 2013

Ron Horswell, PhDAssociate Professor

Pennington Biomedical Research Center

BMI Core Functions

• Design, Create, Maintain data entry packages for projects requiring prospective data collection. – Largely done with RedCap– Connie Murla (PBRC)– Daniel Lorio (PBRC)

• Extractions of data from large, existing databases.– Largely from the LSU HCSD’s DMED warehouse– Ron Horswell (PBRC)– Elizabeth Chesteen (PBRC)– San Chu (PBRC)– Jay Besse (HCSD)– Yong Yi (HCSD)

• PI’s, Co-PI’s for some projects• Participate in ICON “interest groups”

BMI Core Functions

• Design, Create, Maintain data entry packages for projects requiring prospective data collection. – Largely done with RedCap – Connie Murla (PBRC)– Daniel Lorio (PBRC)

• Extractions of data from large, existing databases.– Largely from the LSU HCSD’s DMED warehouse– Ron Horswell (PBRC)– Elizabeth Chesteen (PBRC)– San Chu (PBRC)– Jay Besse (HCSD)– Yong Yi (HCSD)

• PI’s, Co-PI’s for some projects• Participate in ICON “interest groups”

RedCap used or under development for 10 of 33 current ICON projects.

DMED extracts conducted or under development for 28 of 33 current ICON projects.

PI’s or Co-PI’s on 6 of 33 projects

RedCap

RedCap

Data Extracts

Data Extracts

table_name key field_name field_description valid_valuesThe opencounters_expand table has one record for each outpatient encounter.This table has 1 or more records for each record on the demos table.

Table Field Name Field Description Valid Valuespeds_opencounters_expandkey id_created Unique identifying number for subject positive integerspeds_opencounters_expandkey sms_number Artificial number used to link tables positive integers

peds_opencounters_expand insurancestatus Subject insurance type

Medicare, Medicaid, Commercial, Free, Self pay, prisoner, _missing

peds_opencounters_expand encounterdate Date of outpatient encounterpeds_opencounters_expand ctype_ed Flag indicating emergency department encounter 0 or 1, 1 = ED encounterpeds_opencounters_expand ctype_pcadult Flag indicating a adult primary care clinic encounter 0 or 1, 1 = PC encounter

peds_opencounters_expand ctype_otherFlag indicating other type of outpatient encounter; i.e., not primary care and not emergency department

0 or 1, 1 = other encounter

peds_opencounters_expand visitflag Flag indicating encounter was a visit with a clinician 0 or 1, 1 = clinician visitpeds_opencounters_expand totalcharge Total charges associated with the encounter

peds_opencounters_expand tobuser30Flag indicating if patient is a tobacco user (within past 30 days) 0 or 1, 1 = tobacco user

peds_opencounters_expand weight_kg Patient weight in kilograms Positive numberspeds_opencounters_expand height_cm Patient height in centimeters Positive numberspeds_opencounters_expand bmi Patient Body Mass Index in kg/meter2 Positive numberspeds_opencounters_expand bp_sys Patient's systolic blood pressure Positive numberspeds_opencounters_expand bp_dias Patient's diastolic blood pressure Positive numbers

Data Extracts

Calculation of Prevalence or Incidence from data extracts

[date] of as n][populatioin people of #

[date] of as ][condition with people of #][condition of Prevalence

span] [timeover populationin years-person of #

span] [timeover ][condition of cases new of # ][condition of Incidence

Data Extracts

The prev_denomfile_hfonly table has one record for each unique study subject in our population for each yyyymm time period.

Table Field Name Field Description

icd_prev_denomfile_hfonly facility LSU Health siteicd_prev_denomfile_hfonly key id_created Unique identifying number for subjecticd_prev_denomfile_hfonly firstvisit3yr Year and month of first medical home visit in past 3 yearsicd_prev_denomfile_hfonly lastvisit3yr Year and month of last medical home visit in past 3 yearsicd_prev_denomfile_hfonly key yyyymm Year and month for longitudinal denominator use.

icd_prev_denomfile_hfonly probinMH_useProbability that patient is in the medical home patient population as of yyyymm.

icd_prev_denomfile_hfonly gender Subject gendericd_prev_denomfile_hfonly race Subject raceicd_prev_denomfile_hfonly age Subject age

Data Extracts

The paceicd_final table has one record for each pacemaker or ICD event.The event might be a pacemaker or ICD-related diagnosis, or a pacemaker or ICD-related procedure, or both.

Table Field Name Field Description

icd_paceicd_final facility LSU Health siteicd_paceicd_final key id_created Unique identifying number for subject

icd_paceicd_final key eventdateDate of device event (either a diagnosis and/or a procedure)

Data Extracts

FOR prev_dx1_meds by year, total population

year prev_dx1_meds npeople nraw sterr _lower _upper pvalue 2009 0.0216 23911 30366 0.0008 0.0200 0.0233 0.378 2010 0.0254 25264 31713 0.0008 0.0238 0.0270 0.000 2011 0.0267 26327 32394 0.0008 0.0251 0.0283 0.000 2012 0.0270 27319 33546 0.0008 0.0255 0.0286 0.000 TEST FOR ANY DIFFERENCES ACROSS , p-value = 0.000

Diabetes Interest Group

• Implementing Screening for Diabetes and Pre-diabetes (nearing completion)

• Design of Diabetes/Pre-diabetes Screening Protocols (in progress)

• Hepatitis B Immunization for Diabetes Patients (protocol completed)

• Treatment protocols for pre-diabetes patients (future)

Challenges

1. Intersection of Informatics with Design & Analysis.

2. Data extracts for LSU-Shreveport projects

3. Federated data warehouse concept

Federated Data Warehouses

EMR-1

EMR-2

EMR-n

DW-1

DW-2

DW-n

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Common Analytic Programs

Common Structure Warehouses

Federated Data Warehouses

EMR-1

EMR-2

EMR-n

DW-1

DW-2

DW-n

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Common Analytic Programs

Common Structure Warehouses

Advantages:

•Efficiency in analysis

•Supports true population analyses

•Valid comparisons

•Supports research

•Supports data marts

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