Mike Dittemore, RN, BS, eMBA LACIE Executive Director

LACIE 2.0Progression Towards Community Health

Issues LACIE Has Been Challenged to Resolve• Ability to shared more tailored/ granular information• Provide data to payers they are entitled to, while having

process in place that ensures information they are not entitled to is not shared

• Allow organizations to share information between them they may not want to share with others

• More specific and robust alerting of specific activity• Ability to work around EMR vendors that may be cost

prohibitive or have limited resources• While addressing above issues ensure that organizations

have total control over their data

The Journey Begins

• Immediately knew that the current HIO technology in LACIE 1.0 was not developed with the previous goals in mind

• LACIE began working to locate a technology vendor/ partner that would be able to help met the previously shared issues

• Fall of 2014 began due diligence regarding Health Metrics Systems (HMS). HMS was recruited to Kansas City to assist several organizations in the extraction and analysis of data related to a Robert Wood Johnson grant that had been received

• Fall of 2015 formal agreement executed between HMS and LACIE to be technology provider in the Private Exchange

What Is A Private Exchange?• Private Exchange is a more granular way of exchanging

data/ enhancing participant control• Must adhere to all HIPAA requirements for exchange,

fully auditable data trail• Organizations and Providers have full control over the

data they choose to share/ PHIE has no rights to data• Contractual agreements regarding:

• Type of data to be shared – patient cohorts/ alerts/ reporting• Who data will be shared with – clinics/ payers/ hospitals/

ACOs/ research• Frequency of sharing

Key Considerations• Private Exchange is a service – no legal or technical

requirements that an organization also has to be a member of public exchange

• Data is accessed through a virtual cloud based machine we refer to as a HIPAA Control Unit (HCU) that is connected directly to the participating organizations database(s) through a VPN connection that participant has full control over.

• Data can be filtered to a specific payer and plan level as well as filtering out patient information that was not submitted as a claim to insurance; information can be shared in bi-directional manner

Key Considerations Cont.• Eliminates need of interfaces from EMR vendor (Pull versus Push

data gathering)• Data can be normalized prior to being shared with selected

participant(s) and can be sent to Public Exchange if requested• Data can be shared as identified, de-identified, aggregated• Currently vast majority of HIOs do not share PT/OT, Dietary,

Respiratory, Social Worker or Nursing notes limiting the value of the HIO for Long Term Care, Skilled Nursing Facilities, Outpatient Rehab, Home Health. Private Exchange can share notes from anywhere within the EMR with permission.

• Private Exchange can also be used to provide information from non-EMR sources such as registration systems.

Flexibility with Private Exchange• Data can be provided to contracted receiving organization(s)

in various methods• HL7 v.2• CCD• CCDA• PDF• Flat Files

• Permission is now the key determinant if data will be shared not where data is located or the format the data is in

Setting Expectations and Educating are CRITICAL• LACIE 2.0 is an excellent tool for extracting both discrete and textual

data from numerous EMRs and other systems e.g. Registration

• Can aid significantly in identifying gaps of care (tests/ procedures order but not completed)

• Fully capable of performing analytics, but can also send the extracted data to other sources for analysis. Open ended API.

• Specific predictive analytics are not part of the 2.0 offering at this time

• Having clearly defined measures is of utmost importance• Successful population health requires very detailed definition

through measurement criteria on the population to be addressed

Major 2.0 Current Initiatives• Multiple initiatives with Kansas City Metropolitan Physicians

Association - ACO

• Kansas City Internal Medicine

• Area Community Mental Health Centers

• University of Kansas Medical Center – ACO

• BCBSKC

• Providence Medical Center, Saint John Hospital, Children’s Mercy, Olathe Medical Center, Miami County Medical Center

• Kansas Heart and Stroke Collaborative

Kansas Heart and Stroke Collaborative• CMS funded initiative, only initiative to receive unanimous support

from selection committee

• In 3rd year of grant

• Tasked with extracting data from multiple practices and hospitals that utilize numerous different EMRs and workflows. Aggregate the data and use it for identifying patients that have both experienced an MI or CVA, or are at risk of a MI or CVA and ensure they are receiving optimal treatment

• LACIE 2.0 being selected as the data extraction vehicle for the Heart and Stroke Collaborative is directly related to KC Digital Drive

LACIE 2.0/HMS Patient Registries

1) Post AMI 2) Post Stroke 3) At Risk – Heart & Stroke 4) Hypertension 5) Hyperlipidemia 6) Tobacco Use 7) Chronic Kidney Disease (Holding)

Definitions: Cohort – is a registry, or a list of patients identified by specific criteria, i.e. diagnosis codes, medications prescribed or set of demographics for the patient. The most common is that of a diagnosis code, thus identifying patients of a particular disease state.

Folder – is the location of the Cohort, identified in SQI. Roster – is a view of patients, in the cohort folder, where filters may be applied to further analyze patients within the cohort, eg., patients tracking to goal, etc. Concept – is a data element as extracted from an EMR, as identified in appendix D. Derived Concept – is a calculated or derived value from one or more concepts.

1. Post AMI Registry (Cohort)

a. Patients will qualify for this registry based on a diagnosis code of the following:

ICD 9 ICD 10 410.00 I2109 410.01 I2109, I220 410.02 I2109 410.10 I2109

410.11 I2109, I2101, I2102,

I220 410.12 I2109 410.20 I2119 410.21 I2119, I221 410.22 I2119 410.30 I2111 410.31 I2111, I221 410.32 I2111 410.40 I2119

Example of Clearly Defined Measures

a. Views/Rosters will include the following 10 lists:

A.1. Antiplatelet Therapy. % On aspirin (excluding from denominator those not on ASA with documented allergy to aspirin) and/or on antiplatelet therapy, clopidogrel, prasugrel, tricagrelo. (allow filter for aspirin allergy)

B.2. Blood Pressure to Goal. Percent where BP average is <130/80 B.3. Beta Blocker. Percent of those on beta blockers B.4. Ace Inhibitor. Percent on ACE inhibitor, or ARB if intolerant to ACE

C.5. Cholesterol to Goal. %Cholesterol treated to goal (LDL <70) C.5.1 Under 75 – High Intensity Lipid Therapy. Under age of 75, % on high intensity

lipid lowering therapy with statin, treated to goal of LDL < 70 Atorvastatin 40-80 mg

Rosuvastatin 10-40 mg

C.5.2. Over 75 – Low to Moderate Intensity Lipid Therapy. Over age of 75, % on low to moderate intensity lipid lowering therapy with statin, treated to goal of LDL < 70

Low Intensity Drug name and dose Moderate Intensity Drug name and Dose Fluvastatin 20-40 mg Atorvastatin 10-20 mg Lovastatin 20 mg Fluvastatin 40 mg bid Simvastatin 10 mg Fluvastatin XL 80 mg Pitavastatin 1 mg Lovastatin 40 mg Pravastatin 10-20 mg Pitavastatin 2-4 mg Pravastatin 40-(80) mg Rosuvastatin (5)-10 mg Simvastatin 20-40 mg

D.6. Dietary Recommendations. %patients documented dietary recommendation for

specific diet such as DASH or Mediterranean Diet or low carb/fat and portion control focus.

E.7. Exercise Therapy. %patients with documented exercise prescription/tracking(10,000 steps etc.)

S.8. Tobacco Use. %post-MI patients who smoke or use tobacco, including counseling

Example of Clearly Defined Measures cont.

Very detailed metrics

21 pages of definitions to ensure the needed data is being extracted from both discrete and textual data

Approximately 275 specific measures for this initiative,

currently

Result is clean, validated data by organizations from which data is

obtained

Opportunity to Support or Disprove Health Theories• Data can be extracted and analyzed or sent to analytic engine to aid

in proving or disproving health related theories across the community:

• Walking trails/ parks aid in decreasing obesity

• Select marketing to improve proactive health behaviors

• Opioid/ Heroin abuse - overdose

• No longer need to wait multiple months or years to obtain data

Use Case of Private Exchange - Analytics • Private Exchange has capacity to provide analytics at individual

organizational level, or between multiple organizations providing data to centralized HCU.

• Independent hospitals able to share information on patients both have treatment relationship with to assist in reducing 30 day readmissions

• Care gaps can more easily be uncovered – Private Exchange has ability to identify patient cohort based on diagnosis and or problem. Diabetes/ CHF/ etc. Then review data to see if applicable care has been documented and alert if not. Also aid to ensure physician agreement with assigned patients.

• Analytics can be broken down to Organizational/ Group/ Provider/ Support Staff level and assignments made

In Summary• Not dependent on what Electronic Medical Record can “PUSH” to the

exchange.• Ability to “Pull” permissioned/ contractual information from

participants database.• Organizations have full control over the data they share, with whom,

frequency and length of time sharing will take place, as well as how they disseminate data internally.

• Information exchanged can be very specific/ granular compared to Public Exchange where information is “all in” or “all out”.

• Information can be exchanged in a variety of different formats based on what is best for the receiving organization.

• A variety of use cases have been identified for Private Exchange/ “Granular Exchange”

Thank You For The Opportunity!

Questions?

Mike Dittemore RN, BS, eMBAExecutive Director

Lewis And Clark Information Exchange(LACIE)

12200 NW Ambassador Drive Suite 232Kansas City, MO 64163

mike.dittemore@lacie-hie.com