integrating patient data to improve medication adherence · 2016-02-25 · integrating patient data...
TRANSCRIPT
Integrating Patient Data to Improve Medication Adherence
March 1, 2016
Brian E. Dixon, MPA, PhD, FHIMSS
David G. Marrero, PhD
Conflict of Interest
Brian Dixon, MPH, PhD, FHIMSS
Has no real or apparent conflicts of interest to report.
David G. Marrero, PhD
Has no real or apparent conflicts of interest to report.
Agenda
• Background and Significance
• Objective and Study Design
• Technical System Overview
• Results of Pilot Study to Improve Adherence
• Lessons Learned from Conducting Pilot
Learning Objectives
• Identify the challenges to medication adherence in patients with
type 2 diabetes
• Explain the outcomes of a pilot study designed to improve
medication adherence in patients with type 2 diabetes
• Describe the technical, behavioral and system-level challenges to
integrating clinical, pharmacy and patient-reported data to inform
provider-patient conversations about medication adherence
Our HIT Intervention Seeks to
TREATMENT/CLINICAL
Improve management of diabetes as well
as health outcomes
ELECTRONIC INFO/DATA
Enhance communication between providers
and patients regarding compliance and
barriers to self-management
PREVENTION & PATIENT EDUCATION
Engage patients in self-management of
diabetes through better med utilization
http://www.himss.org/ValueSuite
Background and Significance
• Diabetes Mellitus / Type 2 Diabetes
– 285+ affected worldwide
– 4th cause mortality
– Costs are 11% higher for poor control
• Existing data shows that poor control linked to poor medication adherence
– Adherence linked to all-cause mortality
6
Prior Approaches in T2DM
• Many prior mHealth interventions offer narrowly scoped solutions with limited success
• 22 of 52 (42%) interventions resulted in modest improvements in adherence
– Just 9 (17%) improved both adherence and glycemic control
– Sapkota et al. PloS one. 2015;10(2):e0118296.
Innovation
• Diabetes Translational Research Center
– Mission is to promote the prevention and care of diabetes through research on patient and provider education, health services, community participation and policy
• Regenstrief Center for Biomedical Informatics
– International leader in development of health informatics interventions and evaluation
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Eskenazi Health
One of the largest safety net health
systems in the U.S.
Over 1 million served each year
Part of the county public health agency
Includes a single 315-bed hospital and 11 community health centers
Level 1 trauma center; adult burn center
Large outpatient mental health system
Project Objectives
• Develop an integrated dashboard with information relevant to medication adherence
– Recent lab, vitals from the EHR
– Adherence to prescribed medications
– Patient-reported barriers to adherence
• Pilot the dashboard in three (3) Eskenazi Health primary care clinics / PCMH sites
Proportion of Days Covered (PDC)
• PDC is a ratio representing whether the patient possessed a drug or a class of drugs during a defined measurement period
– T2DM drug classes; HTN drug classes
– 180 day measurement period
• Thresholds
– >80% Good / Green
– Between 60% and 80% Okay / Yellow
– <60% Poor / Red
Dixon et al. JMIR Med Inform. 2016
http://medinform.jmir.org/2016/1/e4/
Data Sources
• Physiological data
– Local EHR System – last BP, HbA1c, etc.
• Medication data
– Surescripts network data from HIE
• Patient-reported barriers
– Patient portal / PHR
System Development
• Dashboard developed and implemented in the CareWeb framework and integrated with the CDS Hub and G3 platform
– https://github.com/carewebframework
• Java-based module that provides a Web-based interface into the Regenstrief Medical Record System (RMRS)
14
System Development
• In addition, implement method to collect psychosocial data from patients using a personal health record (PHR) platform
• Designed modules on the OpenMRS platform
– Used in many countries for EHR
– http://openmrs.org/
15
System Architecture
Dixon et al. JMIR Med Inform. 2016
http://medinform.jmir.org/2016/1/e4/
Dixon et al. JMIR Med Inform. 2016
http://medinform.jmir.org/2016/1/e4/
• Recruit CHCs and Physicians
• Collect baseline data
• Train Physicians in situ
Providers
• Recruit patients via phone
• Collect consent and baseline data
Patients • GA monitors clinic
schedules and reminds patients
• Measure usage and challenges
Monitor
Pilot Study Design
End
Results and Lessons Learned
Challenges in Enrollment
2,369 Patients identified by the EHR
906 Called by ResNet
203 Screened
131 Eligible
106 Consented
96 Enrolled
Patient Demographics
Characteristic N (%)
Gender
Male 40 (42%)
Female 56 (58%)
Race
Caucasian / White 47 (49%)
African American / Black 41 (43%)
Unknown 8 (8%)
Account Created 92 (96%)
Completed Pilot 24 (26%)
Patient Characteristics
Variable Mean (Median) Std Dev
Age 53 (52) 11.00
HbA1c (%) 8.79 (8.24) 1.98
LDL (mg/dL) 95.6 (92.5) 34.18
BMI (kg/m2) 39.87 (37.14) 11.95
PCP VISITS 5.45 (5) 4.71
ED VISITS 1.02 (1) 1.35
Change in PDC
Pre Post Difference (p)
Biguanides 74% 88% 14% (<.001)
Thiazolidinediones 77% 93% 16% (0.004)
Sulfonylureas 73% 93% 20% (<.001)
ACE Inhibitors 85% 91% 6% (0.04)
Angiotensin II Receptor
Antagonists (ARB)
80% 93% 13% (0.02)
Calcium Channel
Blockers
87% 95% 8% (0.03)
Beta Blockers 75% 91% 16% (<.001)
Clinical Outcomes
• No change in the following outcomes
– HbA1c
– LDL
– BMI
• Significant changes to the following
– PCP Visits
– ED Visits
Commonly Reported Barriers
Questionnaire Item Mean Score
I just don't like taking medicine in general 5.69 I just forget to take them 5.36 I can't afford them 5.19 I ran out of medication before I could call or visit my doctor or nurse
5.17
My medicines make me feel bad or have side effects I don't like
5.15
Provider Engagement and Use
• Out of 29 eligible providers, 15 volunteers
– At end of study 12 still practiced
• Only 4 of 6 providers reported using the dashboard at least once
• Several providers indicated “neutral” feedback
– Some questioned whether this is necessary
Challenges to Patient Engagement
• Integration into routine life
– Although patients indicated they had routine access to the Internet, often their access was mediated by a family member or the library
– Email was not a good way to get hold of patients
– Access required logging into a portal that was distinct from other health and information systems
– Portal worked best in a browser, not so good on a mobile device
• Integration into clinical workflow
– DM2 visits are challenging with many topics to cover in 15 minutes
• Clinical FTE Target May Be Off
– Physicians may not be the best end user of the integrated portal
– Changing role of nurses, pharmacists, social workers in medicine
Challenges to Patient Engagement
For More Information
Dixon BE, et al. Integration of Provider, Pharmacy, and Patient-Reported Data to Improve Medication Adherence for Type 2 Diabetes: A Controlled Before-After Pilot Study. JMIR Med Inform 2016;4(1):e4
Available for FREE at http://medinform.jmir.org/2016/1/e4/
Acknowledgements
• Research Team
– Abdul M. Jabour (PhD Student, SOIC)
– Abdullah Alzeer (PhD Student, SOIC)
– Erin O’Kelly Phillips (Research Coordinator, DRTC)
• The work presented was supported by a grant from the NIDDK (R34DK092769), U.S. National Institutes of Health (NIH)
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A Summary of Benefits for the Value of Health IT
TREATMENT/CLINICAL
Significant and clinically meaningful
change in medication adherence, yet no
change in T2DM indicators
ELECTRONIC INFO/DATA
Implemented an integrated solution that is
feasible and met with some enthusiasm
but translated into little usage
PREVENTION & PATIENT EDUCATION
Engaging patients using a standalone
portal is challenging
http://www.himss.org/ValueSuite
Questions • Brian E. Dixon, MPA, PhD, FHIMSS
– Assistant Professor, IU Fairbanks School of Public Health;
– Research Scientist, Regenstrief Institute;
– Health Research Scientist, Department of Veterans Affairs
– http://tinyurl.com/fsphbed
– Twitter: @dpugrad01
• David G. Marrero, MD
– J.O. Ritchey Professor, IU School of Medicine
– Director, Diabetes Translational Research Center