1. Comparing automated mental health screening to manual processes in a health care system
Josh biber

2. Practicing Clinicians
>5,000
Practicing Clinicians
ACCESS
4 Hospitals
12 Community
Clinics 18
Regional Partners
>10% of the
Continental U.S.
$288 Million+
Grants in FY2016
35+
Disease-Causing Genes Identified 6
Members of National Academy of Science or Medicine 1
NCI Comprehensive Cancer Center
DISCOVERY
Nobel Laureate
1.7 MILLION
Patient Visits
$3.2 BILLION
Expense Budget FY16
50%
GROWTH
IN 5 YEARS
EDUCATION
School of Medicine
College of Nursing
College of Pharmacy
College of Health
School of Dentistry
Health Sciences Library

3. “If we look at the future of healthcare in 10 years, we need a better way to measure outcomes that matter. Measurement needs to be patient centered to help inform what was “meaningful” to the patient. Patient Reported Outcome Measures are a key component to this future.”
Robert Pendleton, MD FACP Professor Of Medicine Chief Medical Quality Officer Utah Governor, American College of Physicians

4. Millions of dollars in research and implementation is going into PROMs and has been for decades
ISOQOL (International Society on Quality of Life)
ICHOM (International Consortium for Health Outcomes Measurement)
SMDM (Society of Medical Decision Making)
PHO (PROMIS Health Organization)
AHRQ (Agency for Healthcare Research and Quality)

5. Vision for PROms at University of Utah
Lead the country in systemic collection of PROMs across patients (inpatient & outpatient)
Lead the country in using the PROM data to improve healthcare
Integrate PROM data into VDO (cost)
Use PROM data to inform medical decision making
Use PROM data to predict outcomes
Use PROM data in our population health analyses
What are the “right” PROMs?

6. Is collecting “Depression” data worth it?
We all know the stats about how many patients have depression
Plenty of research shows patients with depression have more complications and cost more
Depression is hard to treat without enough resources and support
US Preventive Services Task force recommends screening all adult
There are QPP metrics based on Depression screening and intervention

7. AIM
Mental Health screening has traditionally been a manual, or ad hoc, process
Patients are screened when a provider identifies them as “at risk”
Technology can be used to standardized screening practices
An automated process provides a more efficient and effective process for screening

8. methods
PROMIS Depression v1.0 instrument is asked as part of a standard PRO assessment through an automated system called mEVAL
Assessments are completed via or in clinic on a tablet
Patients are asked to complete an assessment at least once every 10 months
The PHQ-9 is used as a manual process within the Electronic Medical Record

9. methods
ICD-10 codes were used to identify patients diagnosed with depression
Anti-depressant medications were used to identify patients that are actively being treated for depression
Patients who complete the PROMIS Depression instrument with a score ≥65 are considered ”at risk” for depression
Patients who complete the PHQ-9 instrument with a score ≥15 are considered “at risk” for depression

10. results There were 205,813 unique patient visits during time frame
mEVAL- Automated System Results
33,484 patients screened (16.3%)
2,312 at risk for depression based on score (6.9% of patients screened)
PHQ-9- Manual or Ad Hoc Process
6,039 patients screened (2.9%)
2,212 at risk for depression based on score (36.6% of patients screened)
*All data is from September 2016 through March 2017

11. results Patients screened with depression diagnosis
mEVAL: 7,694 (23%) PHQ-9: 4,107 (68%)
Patients with elevated scores and depression diagnosis
mEVAL: 1,330 (4%) PHQ-9: 1,810 (30%)
Patients screened that are treated with medication
mEVAL: 10,653 (32%) PHQ-9: 4,855 (81%)
Patients with elevated scores and treated
mEVAL: 1,460 (4%) PHQ-9: 1,986 (33%)
*All data is from September 2016 through March 2017

12. results Patients with elevated scores and no depression diagnosis
mEVAL: 982 (3%) PHQ-9: 402 (6%)
Patients with elevated scores and not treated
mEVAL: 852 (2.5%) PHQ-9: 226 (4%)
Amount of patients with a depression diagnosis and not screened with either method: 23,706
Amount of patients on an anti-depressant and not screened with either method: 35,277
*All data is from September 2016 through March 2017

13. results PROMIS Depression PHQ-9 Completed Assessments 38,823 8,044
Unique Patients
33,484
6,039
At Risk for Depression
2,312
2,212
Patients with Depression DX
and Screened
7,694
4,107
Identified as high risk
1,330
1,810
Patients treated with Depression
Medications and Screened
10,653
4,855
Patients Treated with Depression Meds
and Identifed as At Risk
1,460
1,986
Identifed as at Risk and not
Diagnosed
982
402
Identified as at Risk and not
Treated with Meds
852
226
*All data is from September 2016 through March 2017

14. conclusions
The use of an automated PRO platform for mental health screening enables a clinician to identify patients at risk that may have otherwise gone unidentified.
Our automated platform screened more unique patients than a manual process in the same time frame.
The implementation of the automated process is implemented in just under 70% of our total health system’s appointments.
By implementing automated PROs, we hope to identify our total population of patients at risk for mental health conditions.

15. Current Progress From 9/1/16 - 2/28/17
Overall since October 2015 we have gather assessment data from over 75,000 unique patients and on almost 200,000 encounters
From 9/1/16 - 2/28/17

16. Current Progress
We are currently gathering assessments for more that 12,000 encounters a month, and as we roll this out to more clinics we expect this number to grow
The more data we collect the better our ability will be to help patients make educated health care decisions by using this data of similar interventions

17. Next steps
Continue to implement PRO and screen for depression
Link PRO scores to health outcomes
Use PRO data for predictive modeling