# Presentation: 713839

## BioSense: Data Elements, Parsing and Binning Routes

- Roseanne English
- Senior Data Analyst
- Craig Hales MD, MPH
- Medical Epidemiologist
- Colleen Martin, MSPH
- Team Lead, BioIntelligence Center
- Division of Emergency Preparedness and Response
- National Center for Public Health Informatics
-  Centers for Disease Control and Prevention

## Topics

- What are the sources of BioSense data?
- What kind of data elements does BioSense currently receive?
- How does BioSense aggregate chief complaint and ICD-9-CM data into syndromes and sub-syndromes?

## Data Source Overview

- DoD
- VA
- LabCorp
- BioWatch
- Hospital (RT)

## DoD Data

- Department of Defense (DoD) ambulatory care Medical Treatment Facilities (n~490)
- ICD-9 CM diagnosis codes
- CPT procedure codes
- Patient demographics
- Patient zip code
- Disposition
- Latency 3-7 days
- Relatively fast for ICD-9 data
- No patient ID
- Makes public health follow up difficult

## VA Data

- Veterans Affairs (VA) outpatient medical centers and clinics (n~890)
- ICD-9 CM diagnosis codes
- CPT procedure codes
- Patient demographics
- Patient zip code
- Latency 3-7 days
- Relatively fast for ICD-9 data

## LabCorp Data

- Laboratory Corporation of America
- Reason for test orders (ICD-9-CM)
- Often unrelated to the test at hand or do not make sense (i.e. prostate problems for females)
- Diagnostic test orders (no results)
- Patient demographics
- Patient zip code
- Latency 2-4 days
- No patient ID
- Makes public health follow up difficult

## Hospital (RT) Data

**Source **
**State/local surveillance systems**
**Individual hospitals/hospital systems**
**Real-time data**
**Latency varies by data type – real-time can be a misnomer for some data types**
**Foundational (ADT and census)**: demographics, chief complaint, diagnoses
- Chief complaints tend to be very timely (latency = 0-2 days)
- Diagnoses tend not to be timely (latency >= 7 days)
- Hospital census is daily

## Hospital (RT) Data

**ED Clinical**
**Laboratory**: microbiology orders and results
**Pharmacy**: medication orders
**Radiology**: orders and interpretation results

## Laboratory Data Processing

- Work in progress.  Data not currently visualized in the BioSense application
- Mapping LOINC and SNOMED codes to BT agents, notifiable diseases, other diseases of interest, common pathogens (not syndromes or sub-syndromes)
- Some labs send only text results – requires text parsing

## Radiology Data Processing

- Work in progress.  Displayed in Patient Detail module of BioSense application, but not currently queriable.
- Mapping free text radiology impressions to pneumonia and fractures (not syndromes and sub-syndromes)
- Requires text parsing (no coded data)

## Pharmacy Data Processing

- Work in progress.  Displayed in Patient Detail module of BioSense application, but not currently queriable.
- Mapping drug names  (mostly uncoded) to categories of interest - in progress
- Data most complete for inpatient class.  Only 20-40% of ED visits have Rx data (likely due to transactions occurring outside the hospital pharmacy system)

## RT Facilities Sending Data

- Total 376 facilities
- 5 sending Census only
- 371 send Admit/Transfer/Discharge data
- 295 from state Syndromic systems, “lite” ADT data
- 76 sending fuller ADT data

## RT Facilities Sending Data

- Total 371 facilities sending visits
- Early Indicator Data:	366
- Working Diagnosis:	104
- Final Diagnosis:		96

## RT Facilities Sending Data

- Total 371 facilities sending visits
- Emergency:		364
- Inpatient:		91
- Outpatient:		90

## “Bucket” Definitions

| Bucket ID | Patient Class | Category Type |
| --- | --- | --- |
| 11 | E | Chief complaint |
| 12 | E | Working diagnosis |
| 13 | E | Final diagnosis |
| 14 | I | Reason for Admit |
| 15 | I | Working diagnosis |
| 16 | I | Final diagnosis |
| 17 | O | Reason for visit |
| 18 | O | Working diagnosis |
| 19 | O | Final diagnosis |

## RT Facilities Sending DataBucket Sources

- Emergency (364)
- Chief Complaint:		359
- ADT messaging		353
- ED Clinical messaging	26
- Working Diagnosis:	97
- Final Diagnosis:		95
- ADT Messaging		94
- ED Clinical messaging	17

## RT Facilities Sending DataBucket Sources

- Inpatient (91)
- Reason for Admit :	91
- Working Diagnosis:	63
- Final Diagnosis:		71

## RT Facilities Sending DataBucket Sources

- Outpatient (90)
- Reason for Visit :		87
- Working Diagnosis:	61
- Final Diagnosis:		70

## RT Facilities Sending DataExtended Data Types

- Add on to foundational ADT data
- Limited to the 76 fuller sites
- _ED Clinical_ observations
- 26 Total
- 26 provide Emergency Chief Complaint
- 17 provide Emergency Final Diagnosis
- _Laboratory _Data
- 27 send microbiology orders
- 31 send results

## RT Facilities Sending DataExtended Data Types

- Add on to foundational ADT data
- _Radiology_ Data
- 30 send orders
- 41 send results
- _Pharmacy_ Orders
- 32 send orders

## RT Facilities Sending DataExtended Data Types

- Lab Tests Targeted
- IMM: Immunology
- MB: Micro
- MCB: Mycobacteriology
- MYC: Mycology
- OSL: Outside Lab (mostly microbiology)
- SR: Serology
- VR: Virology

## ED Clinical FeedsObservation Messages (OBR/OBX)-Tied to ER systemsInfluences Binning

- ED Clinical FeedsObservation Messages (OBR/OBX)-Tied to ER systemsInfluences Binning

## ED Clinical FeedsObservation Messages (OBR/OBX)Tied to ER systems

- ED Clinical FeedsObservation Messages (OBR/OBX)Tied to ER systems

***Used in parsing/binning to Emergency Chief Complaint and Emergency Final Diagnosis Buckets***

## Percent of Visits with non-blank valuesBased on Visits July 2007(all RT sites)

- Patient Class		95%
- Patient Zip		98%
- Patient State		92%
- *Patient County	92%
- Birth yr/mo		94%
- *Age			90%
- Gender		99%
- Race		44%
- Ethnicity		19%
- *Calculated via internal CDC process if not reported

- Admit Date		87%
- Medical Specialty	44%
- Admit Source		35%
- Discharge Disposition	26%
- Discharge Date	30%
- POC			25%
- Admit Type		24%
- Acuity		3%
- Work Related		<1%
- Admit Level of Care	0%
- Occupation
- Site 1		73%
- Site 2		48%
- Others		0%
- Industry		0%
- Identity Unknown	0%

## Percent of Visits with non-blank valuesBased on Visits July 2007Excluding State Syndromic Sites(noted differences)

- Medical Specialty	78%
- Admit Source		61% (96% in Inpatient setting)
- POC			44% (94% in Inpatient setting)
- Admit Type		43% (67% in Inpatient setting)
- Discharge Disposition	45% (71% in Inpatient setting)
- Discharge Date		51% (76% in Inpatient setting)

## Mortality Data 

- Facility Counts/Visits Counts
- Facilities sending Visits:	366
- Sending Census Death Indicator		77
- Sending one or more Visits Death Indictors	72
- Total 17 million visits
- Deaths indicated in Census:			19,098
- Deaths Indicated in Visits:			22,021

## Mortality Data Visits Death Indicators

- Two Core Indicators in Visits data
- Disposition Code
- Patient Death Indicator

## Mortality Data

## Mortality Data # of DeathsStratified by various Visits Death Indicators 

- Mortality Data # of DeathsStratified by various Visits Death Indicators

## Mortality Data # of DeathsStratified by various Visits Death Indicators 

- Mortality Data # of DeathsStratified by various Visits Death Indicators

**Data Feed mapping problems result in Patient Death Flag being inaccurate**

## October 23, 2003 

- October 23, 2003** **

**Botulism-like**
**Hemorrhagic Illness**
**Lymphadenitis**
**Localized Cutaneous Lesion**
**Gastrointestinal**
**Respiratory**

**Neurological**
**Rash**
**Specific Infection**
**Fever**
**Severe Illness or Death**

## Slide 32

## Syndrome

**Sub-syndrome**

**Sub-syndrome**

**Sub-syndrome**

## Data Types Mapped to Syndromes and Sub-syndromes

- Outpatient
- Reason for visit
- Working diagnosis
- Final diagnosis
- ED
- Chief complaint
- Working diagnosis
- Final diagnosis
- Inpatient
- Reason for admit
- Working diagnosis
- Final diagnosis

- Note: Data must have a valid patient class (Outpatient, ED, or Inpatient) and data type (Reason for Visit, Chief Complaint, Reason for Admit, Admit Diagnosis, Working Diagnosis, Final Diagnosis) to be visualized in the application.

## Sub-syndrome to Syndrome Mapping

- Botulism-like
- Paralysis
- Speech disturbance
- Dysphagia
- Fever
- Fever
- Septicemia and bacteremia
- Viral infection, unspecified

- Gastrointestinal
- Abdominal pain
- Anorexia
- Diarrhea
- Food poisoning
- Intestinal infections, ill-defined
- Nausea and vomiting

## Sub-syndrome to Syndrome Mapping

- Hemorrhagic
- Coagulation defects
- Gastrointestinal hemorrhage
- Hemorrhage
- Purpura and petechia
- Cutaneous lesion
- Insect bites
- Skin infection
- Lymphadenitis
- Lymphadenopathy

- Neurological
- Alteration of consciousness
- CNS, inflammatory disease
- Convulsions
- Gait abnormality
- Headache
- Meningismus
- Photophobia

## Sub-syndrome to Syndrome Mapping

- Respiratory
- Asthma
- Bronchitis and bronchiolitis
- Chest pain
- Cough
- Cyanosis and hypoxemia
- Dyspnea
- Influenza-like illness
- Otitis media
- Pleurisy
- Pneumonia and lung abscess

- Respiratory (continued)
- Respiratory failure
- RSV
- Upper respiratory infections
- Hemoptysis
- Rash
- Rash
- Severe Illness and Death
- Coma
- Death
- Shock

## Other Sub-syndromes (Not Mapped to Syndromes)

- Bites, animal
- Burns
- Carbon monoxide poisoning
- Falls
- Fractures and dislocation
- Heat, excessive
- Injury, NOS
- Motor vehicle traffic accidents
- Open wound
- Poisoning by medicines
- Sprains and strains
- Cerebrovascular disease
- COPD
- Diabetes mellitus
- Heart disease, ischemic
- Hypertension
- Neoplasms

- Allergy
- Anemia
- Cardiac dysrhythmias
- Dehydration
- Dizziness
- Edema
- Hypotension
- Jaundice
- Malaise and fatigue
- Mental disorders
- Migraine
- Myalgia
- Numbness
- Pregnancy, childbirth complications
- Syncope and collapse
- Urinary tract infection
- Visual impairment

## Syndrome

**Chief Complaint Keywords**

**ICD-9-CM**

**Sub-syndrome**

**ICD-9-CM**

**Diagnosis Keywords**

## ICD-9 to Sub-syndrome: Pneumonia and Lung Abscess

- ICD-9-CM
- 480.X Viral Pneumonia
- 481 Pneumococcal Pneumonia
- 482.X Other bacterial pneumonia
- 483.X Pneumonia due to other specified organism
- 484.X Pneumonia in other infectious disease
- 485 Bronchopneumonia, organism unspecified
- 486 Pneumonia, organism unspecified
- 513.X Abscess of lung and mediastinum

## Free Text CC to Sub-syndrome: Pneumonia and Lung Abscess

| atelectasis | w |
| --- | --- |
| empyema | w |
| infiltr | w |
| infiltrate | w |
| lung problem | i |
| pna | w |
| pne | w |
| pnemonia | i |
| pneumonia | i |
| pnumonia | i |
| pneumonitis | w |

## Free Text Diagnosis to Sub-syndrome: Pneumonia and Lung Abscess

| abscess + lung  | i |
| --- | --- |
| abscess + pulmonary  | i |
| bronchiectasis | i |
| bronchopneumonia | i |
| lung + inflam | i |
| mediasti + inflam | i |
| pneumonia  | i |
| pneumonitis  | i |
| pulmonary + inflam | i |

## Slide 43

## Emergency: Chief Complaint

**Emergency: Chief Complaint**
**Outpatient: Reason for Visit**

**Emergency, Outpatient, Inpatient**
** ****Working Diagnosis**
** ****Final Diagnosis**
** ****Other Diagnosis**

**Inpatient: Reason for Admit**

**Emergency, Outpatient, Inpatient**

## Accounting for Vaccinations

- We want to exclude vaccination events from contributing to syndromes and sub-syndromes
- Ex: A patient is vaccinated for anthrax and receives a final ICD-9 code for anthrax, as well as an ICD-9 or CPT code indicating that the patient also received an anthrax vaccination. If we use our mapping rules as they are, this patient will be mapped to a syndrome based on their anthrax diagnosis. Since this was really a vaccination event, we do not want to count this patient as meeting our syndrome definition. We need to exclude this patient based on a defined set of rules.
- Completed for the VA and DoD data for all vaccine preventable diseases
- Completed for the hospital data for influenza only
- More complicated due to both free text and coded data
- Full implementation targeted for a future release

## BioSense: Data Elements, Parsing and Binning Routes

- Roseanne English
- Senior Data Analyst
- Craig Hales MD, MPH
- Medical Epidemiologist
- Colleen Martin, MSPH
- Team Lead, BioIntelligence Center
- Division of Emergency Preparedness and Response
- National Center for Public Health Informatics
-  Centers for Disease Control and Prevention