1. Care Coordination and Interoperable Health IT Systems
Unit 12: Data Driven Care Coordination Strategy
Welcome to Care Coordination and Interoperable Health IT Systems, Data Driven Care Coordination Strategy. This is Lecture b-Interoperability and Care Coordination.
This unit provides data-driven care coordination strategies for successful transfer of patient care information through improved use of technology and analytics.
It covers the definition of, opportunities for and challenges facing achieving interoperability.
Lecture b – Interoperability and Care Coordination
This material (Comp 22 Unit 12) was developed by The University of Texas Health Science Center at Houston, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number 90WT0006.
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2. Data Driven Care Coordination Strategy Learning Objectives
Objective 1: Identify care coordination data sources (Lecture a)
Objective 2: Demonstrate care coordination effectiveness using analytics (Lecture a)
Objective 3: Evaluate interoperability opportunities and challenges (Lecture b)
The Objectives for this Unit, Data-Driven Care Coordination Strategy, Lecture b, are to:
Evaluate interoperability opportunities and challenges.

3. Evaluate an Intervention 1: Consider a PCMH Standard
Consider the following required standard from the patient-centered medical home model (PCMH):
“Improved access is intended to improve continuity of care with the patient’s provider and reduce use of the emergency room (ER) and other sites of care.”
As an example consider one of the standards the medical home model requires below:
Improved access is intended to improve continuity of care with the patient’s provider and reduce use of the emergency room (ER) and other sites of care.
Consider the process the pathway described above and linking implementation to outcomes for PCMH expanded access.

4. Evaluate an Intervention 2: Test the Standard
If the intervention you are evaluating tests this standard, consider how medical home practices will expand access:
Will the practices use extended hours, and telephone interactions
Or will a nurse or physician be on call after hours?
How will the practices inform patients of the new options and any details about how to use them?
If the intervention you are evaluating tests this standard, you could consider how the medical home practices will expand access:
Will the practices use extended hours, and telephone interactions, or have a nurse or physician on call after hours?
How will the practices inform patients of the new options and any details about how to use them?

5. Evaluate an Intervention 3: Specify Process Indicators
The logic model should specify process indicators to document how the practices implemented the approach
For example, some process indicators for practices that use interactions to increase access could include:
Patients were notified about the option by mail or during visit
Overall number of s sent to and from different practice staff
Number and distribution by provider and per patient
Time spent by practice staff initiating and responding to s
Because nearly all interventions are adapted locally during implementation, and many are not implemented fully, the logic model should specify process indicators to document how the practices implemented the approach.
For practices that use interactions to increase access, some process indicators could include how many patients were notified about the option by mail or during a visit, the overall number of s sent to and from different practice staff, the number and distribution by provider and per patient, and time spent by practice staff initiating and responding to s.

6. Which Process Indicators to Collect?
Consider which process indicators reflect critical activities that must occur to reach intended outcomes
Balance critical activity process indicators with the resources needed to collect data
Beware impact of collection on patient care and provider workflow
Assess process indicators easiest to collect
In deciding which measures to collect, consider those likely to reflect critical activities that must occur to reach intended outcomes, and balance this with an understanding of the resources needed to collect the data and the impact on patient care and provider workflow.
Assess which process indicators are easiest to collect, depending on the available data systems and the feasibility of setting up new ones

7. Analyzing Reimbursement Data
Fee-for-service
Practices reimbursed under existing arrangement with health plan
Fixed transformation payments
NCQA-recognized practices receive between $3.50 and $6.00/patient/month
Incentive payments
Practices receive a share of actual savings generated
When analyzing reimbursement data, health care payment data may be a mixture of:
Fee-for-service, for example where primary care practices continue to be reimbursed under their existing fee-for-service delivered types of payment arrangements with health plans;
Fixed transformation payments, where primary care practices with NCQA recognition receive a per patient per month fee (paid semi-annually) between $3.50 and $ Part of this payment is invested into care coordination;
And incentive payments where primary care practices that have reported on a set of clinical quality and utilization measures, receive a share of actual savings generated by reducing total cost of care through improved patient outcomes (this is the shared savings).

8. Improving Interoperability among Systems
Ongoing collaboration is necessary for interoperability
Information-sharing must be enabled to save more patients
Proprietary concerns inhibit sharing
Large entities can pledge to work toward interoperability
According to HIMSS, “Interoperability describes the extent to which systems and devices can exchange data, and interpret that shared data. For two systems to be interoperable, they must be able to exchange data and subsequently present that data such that it can be understood by a user.”
As such, ongoing collaboration is necessary for interoperability. Information-sharing must be enabled to save more patients’ lives.
However, various corporations’ concerns surrounding proprietary systems and software can inhibit working together and sharing interface information or data. Larger entities are requested to pledge working toward interoperability, even if it means sharing data with competitors’ systems.

9. Top Challenges to Interoperability
Meaningful Use is not uniformly applied to all care settings:
Home health and hospice care
Lack of policy regulations
Some of the challenges to interoperability include the non-uniform application of meaningful use in all care settings. Home health and hospice care may not meaningfully use electronic health records. A lack of policy oversight enables this environment, and jeopardizes interoperability.

10. Top Challenges to Interoperability (Cont’d – 1)
Technical challenges persist:
Certification criteria on how to read application programming interfaces (APIs)
No payment adjustments standard
Slow, but continued, movement towards regulating health technology in the future
ONC Task Force working on connecting tech sector
Additionally challenges with technology hinder interoperability. For example:
There is limited certification criteria on how to read APIs;
Lack of standard payment adjustments means avoiding of negative payment adjustments and qualifying almost three-times the amount of positive adjustments;
Trends show slow but continued movement towards regulating health technology in the future;
A ONC Task Force is still working on connecting tech sector.

11. Top Challenges to Interoperability (Cont’d – 2)
Patient privacy and security
Securing data to meet the Health Insurance Portability and Accountability Act (HIPAA) regulations to protect patient health information (PHI) across systems
For example, compliance to HIPAA regulations for using personal apps technology
Encryption and cyber-security breaches
Top challenges to Interoperability include Securing data to meet the Health Insurance Portability and Accountability Act (HIPAA) regulations across systems for example, compliance to HIPAA regulations for using personal apps – consider the many innovative personal applications in information technology, that can be any application in the use of any technology, system, or product to support interoperability.
Another challenge is Ecryption and cyber-security breaches:
Electronic PHI has been encrypted as specified in the HIPAA Security Rule by “the use of an algorithmic process to transform data into a form in which there is a low probability of assigning meaning without use of a confidential process or key” (45 CFR definition of encryption) and such confidential process or key that might enable decryption has not been breached.  To avoid a breach of the confidential process or key, these decryption tools should be stored on a device or at a location separate from the data they are used to encrypt or decrypt.  Interoperability must respect and conform to the encryption processes that officially have been tested by the National Institute of Standards and Technology (NIST) and judged to meet the standard.

12. Considerations for Interoperability
Patients and families take charge of care coordination
Drive their own apps to connect to physicians
mHealth: encourage consumers to discover opportunities
Health startups do not wait on big businesses
The possibility of patients and families taking charge of their own data and care coordination is something to consider about the future of interoperability.
Consumers can drive the creation of their own applications used to connect with physicians and care coordination teams.
For example, amongst mobile healthcare (mHealth) circles, consumers are encouraged to discover and fill opportunity gaps.
Furthermore, health startups don’t wait on big businesses to create systems and products. Smaller businesses in health innovation or wearables may act as catalysts for interoperability.
Health IT Workforce Curriculum Version 4.0

13. Interoperability and the Pace of Change
Quick movements in new technology
New care coordination systems are cropping up
Landscape in 1-2 years from now could be very different than today’s
Refer to Component 22, Unit 3 for more information on Barriers to Interoperability
Also, we must consider that the pace of change in technology affects interoperability. Quick movement in the field of technology often renders older systems obsolete, and new players constantly enter the space. Thus, the landscape for interoperability may look very different in just one to two years from today.
Refer to Component 22, Unit 3 for more information on Barriers to Interoperability.
Health IT Workforce Curriculum Version 4.0

14. There are various ways to evaluate interventions in care coordination
Unit 12: Data Driven Care Coordination Strategy Summary – Lecture b – Interoperability and Care Coordination
Analytic tools can be employed to evaluate the efficiency of coordination strategies
There are various ways to evaluate interventions in care coordination
Rapid changes in industry present many opportunities and challenges for increasing interoperability
This concludes Lecture b-Interoperability and Care Coordination of Unit 12: Data Driven Care Coordination Strategy.
In summary, this lecture covered:
Analytic tools can be employed to evaluate the efficiency of coordination strategies
There are various ways to evaluate interventions in care coordination
Rapid changes in industry present many opportunities and challenges for increasing interoperability
Health IT Workforce Curriculum Version 4.0

15. Unit 12 Summary: Data Driven Care Coordination Strategy
There are a variety of data sources that can be used to coordinate patient care
Various analytic tools can be used to evaluate efficiency of care coordination strategies
Rapid changes in industry present many opportunities and challenges for increasing interoperability
This concludes Unit 12, Data Driven Care Coordination Strategy.
In summary,
There are a variety of data sources that can be used to coordinate patient care.
Various analytic tools can be used to evaluate efficiency of care coordination strategies.
Rapid changes in industry present many opportunities and challenges for increasing interoperability.
Health IT Workforce Curriculum Version 4.0

16. Unit 12:Data Driven Care Coordination Strategy References – Lecture b
A., Peikes, D., Ph.D., M.P.A., Taylor, E. F., Ph.D, M.P.P, Genevro, J., Ph.D., & Meyers, D., M.D. (2014, October). A Guide to Real-World Evaluations of Primary Care Interventions: Some Practical Advice. Retrieved March 07, 2016, from
Healthcare Information and Management Systems Society. (2016). What is Interoperability? Retrieved March 09, 2016, from
Innovation Network, Inc. Logic Model Workbook. Washington, DC: Innovation Network, Inc.; n.d. 
Institute for Healthcare Improvement. (n.d.). Retrieved March 07, 2016, from
Petersen D, Taylor EF, Peikes D. Logic Models: The Foundation to Implement, Study, and Refine Patient-Centered Medical Home Models. AHRQ Publication No EF. Rockville, MD: Agency for Healthcare Research and Quality; March
W.K. Kellogg Foundation. Logic Model Development Guide. Battle Creek, MI: W.K. Kellogg Foundation; December 2001:35-48. 
No Audio.
Health IT Workforce Curriculum Version 4.0

17. Unit 12: Data Driven Care Coordination Strategy Lecture b – Interoperability and Care Coordination
This material was developed by The University of Texas Health Science Center at Houston, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information Technology under Award Number 90WT0006.
No Audio.
Health IT Workforce Curriculum Version 4.0