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

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

“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

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)

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?

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

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

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 email 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

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

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

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

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

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

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.

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

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

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