Embed Size (px)
Citation preview
3/26/2015
1
The Challenges and Opportunities in Using Data for Population Management
L Gordon Moore MD
Senior Medical Director
3M Health Information Systems
Objectives
Describe different data sources for population health management
Identify strengths and weaknesses of several typical sources of data
Provide examples of other provider systems’ data strategies
3/26/2015
2
Objectives
• This session will describe common challenges and possible solutions related to integrated data support for population management including investments in EMR and IT infrastructure, analytic limitations of existing IT systems , working with multiple EMRs, and providing timely and actionable data to clinicians to drive performance improvement
The Role of Data in Population Health Management
Modeling
– Cost trends
– Attributed populations
– Networks
Scorecard
– Total cost of care
– Quality
Opportunity
3/26/2015
3
Common Challenges
The EMR has what we need
The health plan will provide all claims data
We can analyze our data
– Cost
– Expertise
We know where to look for opportunity
Office of the National Coordinator for Health
Information Technology
“Electronic health information is also not sufficiently standardized to allow seamless interoperability, as it is still inconsistently expressed with vocabulary, structure, and format, thereby limiting the potential uses of the information to improve health and care.”
ONC Whitepaper Connecting Health and Care for the Nation: A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure June 5, 2014
3/26/2015
4
Health information technology leaves a lot to be desired
Richardson, Joshua E., Joshua R. Vest, Cori M. Green, Lisa M. Kern, Rainu Kaushal, and the HITEC
Investigators. “A Needs Assessment of Health Information Technology for Improving Care Coordination in
Three Leading Patient-Centered Medical Homes.” Journal of the American Medical Informatics
Association, March 20, 2015, ocu039. doi:10.1093/jamia/ocu039.
A collection of medical concepts, organized to support synonyms and other lexical characteristics
• concept: a unique, definable idea or object that has a very specific, known meaning
Sodium
Lab ResultLab Test Chem 4
Potassium
ChlorideGlucoseGLUCGLC
Why is it so hard?Medical Vocabulary
© 3M 2014. All Rights
3/26/2015
5
Concept
Representation
Concept
Domain
Concept
Definition
Concept ID
a sensory
perception
a pulmonary
diagnosis
an upper
respiratory
viral infection
“I’m feeling
cold”
Chronic
Obstructive
Lung Disease
“I have a
cold”
68215 1005480 1005313
How machines understand concepts
COLDCOLDCOLD
© 3M 2014. All
Rights
Lab, Rx, Radiology, Dental, Demographics, etc.• 2.6 million concepts• 17.9 million representations• 15.9 million relationships
• A collection of medical concepts, organized to support synonyms and other lexical characteristics
• Concept: a unique, definable idea or object that has a very specific, known meaning
Lab Test
Chem 4
Sodium
Lab Result
Potassium
Chloride
Glucose
Concept-based Semantic Network
© 3M 2014. All Rights
3/26/2015
6
Lab Test
Chem 4
Sodium
is-a
Lab Result
Potassium
Chloride
Glucose
is-component-of
Knowledge Base / Relationships
© 3M 2014. All
Rights
Drugs
Antibiotics
Ampicillin
Analgesics
Penicillins Cephalosporins
Amoxicillin
is-a
Medication Knowledge Base
3/26/2015
7
Ampicillin
Ampicillin trihydrate
Ampicillin trihydrate250mg capsule (Allscripts 40 ea.)NDC
54569-1719-0
Ampicillin sodium
Ampicillin trihydrate250mg capsule
Ampicillin trihydrate500mg capsule
Ampicillin trihydrate250mg capsule (PD-Rx
100 ea.)NDC 55289-023-40
is-aContinuing from previous relationship
Medication Knowledge Base
Lots of languages in HIT
UMLS
LOINC
NDC
RxNorm
ICD-9-CM
ICD-10-CM
ICD-10-PCS
DRG
APC
APDRG
CPT
HCFA HCPCS
CDT
SNOMED CT
HL7
OMB Race/Ethnicity Standards
Commercial Interface Terminologies
Provider Taxonomy
Revenue Codes
© 3M 2014. All Rights
3/26/2015
8
… and more…
HL7 CVX
GEMs
Kaiser Permanente CMT
© 3M 2014. All Rights
HDD HIE
Crimson
EDW
Cerner
Siemens
LOINC
SNOMED
Point-to-Point Mapping for 9 sources = n(n-1)/2 = 36 mapsAdding 1 more source adds 9 maps
Challenge is not only in the creation, but the maintenance
all of these mappings
Mapping to a terminology server for 9 sources = n = 9 maps
Adding 1 source adds 1 map
Centralized maintenance and distribution of content
VS.
Epic
Siemens
HIE
CrimsonEDW
2
)1( −nn
maps
LOINC
SNOMED
RxNormRxNorm
Epic
Cerner
Interoperability is difficult
© 3M 2014. All Rights
3/26/2015
9
Epic
Cerner
Point-to-point mappingis difficult to maintain:102 sites – 5151 “fixes”
Centralized mapping is simple to maintain:1 “fix”
VS.
Cerner
RxNorm RxNorm
Crimson
HIE
HIE
LOINC
LOINC
SNOMED
SNOMED
HDD
EDW
Siemens
Epic
Siemens
EDWCrimson
If a Mapping Changes . . .
© 3M 2014. All
Rights
Claims and EMR
3/26/2015
10
A Registry Example
Diabetics in
registry, 7,000
Diabetics not in
registry, 26,000
0
500
1000
1500
2000
2500
3000
Th
ou
sa
nd
s o
f m
ea
su
re
s in
th
e d
ata
se
t
Th
ou
sa
nd
s
Registry Example –
frequency of specific findings
3/26/2015
11
Bernstein, Richard H. “New Arrows in the Quiver for Targeting Care Management: High-Risk versus
High-Opportunity Case Identification.” The Journal of Ambulatory Care Management 30, no. 1 (March
2007): 39–51
People with Diabetes Segmented by Total
Illness Burden
3/26/2015
12
Bernstein, Richard H. “New Arrows in the Quiver for Targeting Care Management: High-Risk versus
High-Opportunity Case Identification.” The Journal of Ambulatory Care Management 30, no. 1 (March
2007): 39–51
Rates of Hospital Admission per 1000
People with Diabetes
People with two or more conditions
Outcomes are Predicted Better by Total Illness Burden Than by Diagnosis Alone
3/26/2015
13
Some Real World Examples
Colorado Medicaid – Accountable Care Collaborative
Montefiore Care Management Organization
North Carolina Medicaid – Community Care of North Carolina
Data As Opportunity
3/26/2015
14
3/26/2015
15
3/26/2015
16
Patient reported data
3/26/2015
17
Patient-reported data is a strong predictor of
readmissions
“Higher patient satisfaction with inpatient care and discharge planning is associated with lower 30-day readmission rates even after controlling for hospital adherence to evidence-based practice guidelines.
Patient-centered information can have an important role in the evaluation and management of hospital performance.”
Boulding, William, Seth W Glickman, Matthew P Manary, Kevin A Schulman, and Richard Staelin. “Relationship between Patient Satisfaction with Inpatient Care and Hospital Readmission within 30 Days.” The American Journal of Managed Care 17, no. 1
(January 2011): 41–48.
Evans RG, Stoddart GL. Producing health, consuming health care. Soc Sci Med 1990;31(12):1347-63.
3/26/2015
18
Low confidence individuals also report the following: Adjusted Odds Ratio*
Hospitalization or ED for a chronic conditionᵻ 1.552
More than one hospitalization or ED visit** 1.865
Hospitalization or ED use perhaps unnecessary** 1.609
Time lost from work due to emotional or physical problem 4.049
Medication for chronic illness maybe causing some illnessᵻ 2.882
Do not have enough money to buy things for everyday life 2.787
Fair to poor info received from MD on chronic diseaseᵻ 2.566
Patient-reported confidence (a.k.a. “activation”)—a strong indicator of risk
All ORs were statistically significant
* Adjusted for Age, Sex, and 3M™ Clinical Risk Group (CRG) weightᵻ Based on a question asking about chronic conditions
** Based on a question asking about overnight hospital stays
Socio-Economic Status and Factors Supporting Good Health
Data Source: Demo Commercial Data, 2010/07 – 2011/06 and Census data
SES should be considered when developing patient interventions.
Technical notes:
• Treo Solutions Proprietary SES score, calculated using
census data at the zip code level based on income and
education levels.
• Darker regions signify a higher SES relative to the state
average.
Technical notes:
• Darker regions denote healthier counties, in quartiles within the
state.
• Based on CDC’s Behavioral Risk Factor Surveillance System (BRFSS)
Health Factors Score, which reflects aspects of health behaviors,
clinical care, social and economic factors, and the physical
environment.
Data Source: www.countyhealthrankings.org
3/26/2015
19
L Gordon Moore MD
Senior Medical Director
3M Health Information Systems
