Substance Use Disorder Detection Among Providers of Medical Inpatients Kristin Serowik, PhD Interprofessional Fellowship in Advanced Addiction Treatment VA Connecticut Healthcare System Do Not Disseminate Without Permission from the Author
Rates are higher than general population Poor medical outcomes Why is detection so Higher healthcare utilization and costs important for this Direct optimal medical treatment population? Referral for addiction treatment
Provider detection Alcohol: 37%-64% Illicit Drugs: 11%-56.5% Nicotine: 65%
Primary aims for the current study • Update provider detection rates • DSM-5 • Contemporary clinical issues (opioid epidemic, marijuana laws) • Examine the relationship between patient characteristics and detection rates • Explore detection during the current hospitalization
Participants (1076) • Recruited during admission • 13 general medical units at a large teaching hospital • 18+ years of age • Problematic use of nicotine, alcohol, illicit drugs, or prescription medications in past 28 days • Expected length of stay of a minimum of 2-3 days • Larger study examined the effectiveness of 3 distinct implementation strategies to promote the use of motivational interviewing
Measures • Substance use diagnoses (SUD) • MINI • Provider detection • Medical record review (admission, until discharge) • Age, race/ethnicity, education, gender • Demographics questionnaire • Severity of use • Addiction Severity Index • Heaviness of Smoking • Mental and physical health-related quality of life • SF-12 • Motivation • Motivation to Change Scale • Length of stay (LOS) • Medical record review
Mean (SD) % N Range Age 46.0 (13.7) Race/ethnicity White 55.2% 594 Black 31.3% 337 Hispanic 12.6% 135 Other 1.0% 10 Male 54.5% 586 SUD (MINI) Patient Nicotine 73.8% 794 Alcohol 50.6% 544 Characteristics Cannabis 15.1% 163 Cocaine 12.2% 131 Opioid 13.2% 142 Other Drug 8.4% 90 Education 12.9 (2.3) LOS 7.0 (7.2) SF-12 Physical 41.5 (12.4) 0-100 SF-12 MH 35.8 (11.1) 0-100 Motivation 7.2 (2.7) 0-10 Heaviness of Smoking 2.3 (1.6) 1-6 ASI – Drugs 0.129 (0.131) 0-1 ASI – Alcohol 0.204 (0.294) 0-1
0.94 0.93 0.93 0.89 0.89 0.87 0.86 0.84 0.84 0.80 0.74 0.74 0.72 0.65 0.61 0.54 0.51 0.26 NICOTINE ALCOHOL CANNABIS COCAINE OPIOID OTHER DRUG sensitivity specificity accuracy
N I C O T I N E U S E D I S O R D E R A L C O H O L U S E D I S O R D E R ( N = 5 4 4 ) C A N N A B I S U S E D I S O R D E R ( N = 1 6 1 ) I L L I C I T D R U G U S E D I S O R D E R ( N = 7 9 4 ) ( N = 3 7 7 ) OR p OR p OR p OR p (CI) (CI) (CI) (CI) 1.01 0.046 1.03 <0.001 1.00 0.682 0.99 0.190 Age (1.00, 1.02) (1.02, 1.04) (0.97, 1.02) (0.96, 1.01) Black 0.79 0.668 0.42 0.983 0.74 0.380 0.46 0.880 (0.56, 1.11) (0.29, 0.60) (0.36, 1.63) (0.25, 0.85) 1.04 0.532 0.27 0.183 0.79 0.507 0.50 0.969 Hispanic (0.63, 1.72) (0.14, 0.53) (0.30, 2.07) (0.21, 1.17) Other 0.71 0.756 0.27 0.510 2.37 0.466 0.25 0.527 (0.13, 3.95) (0.05, 1.51) (0.14, 39.82) (0.02, 4.08) 1.12 0.479 3.23 <0.001 1.16 0.675 1.24 0.448 Male (0.82, 1.53) (2.26, 4.62) (0.57, 2.37) (0.71, 2.18) Education 1.01 0.828 1.03 0.438 0.98 0.801 0.89 0.099 (0.94, 1.08) (0.96, 1.11) (0.82, 1.17) (0.78, 1.02) 1.00 0.809 1.01 0.203 1.00 0.815 1.03 0.036 SF-12 (0.99, 1.02) (1.00, 1.03) (0.97, 1.04) (1.00, 1.06) Physical SF-12 1.00 0.748 0.98 <0.001 1.00 0.714 1.00 0.341 (0.99, 1.02) (0.96, 0.99) (0.97, 1.02) (0.96, 1.01) MH Motivation 0.98 0.455 1.18 <0.001 1.20 0.009 1.05 0.363 (0.92, 1.04) (1.11, 1.27) (1.05, 1.38) (0.94, 1.17) 1.20 0.001 1.61 <0.001 1.25 0.100 1.38 0.003 Addiction (1.08, 1.33) (1.48-1.74) (0.96-1.62) (1.11-1.70) Severity LOS 1.03 0.055 1.02 0.146 1.03 0.543 1.08 0.020 (1.00, 1.06) (0.99, 1.04) (0.95, 1.11) (1.01, 1.15) # SUDs 0.97 0.674 0.96 0.597 1.10 0.538 1.37 0.017 (0.84,1.12) (0.82,1.12) (0.82,1.47) (1.06,1.78)
NICOTINE USE DISORDER ALCOHOL USE DISORDER CANNABIS USE DISORDER COCAINE USE DISORDER OPIOID USE DISORDER detected at admission detecteced during hospital stay
Summary of findings • Provider detection varies, depending on substance • Detection rates for nicotine and alcohol comparable to prior research • Improvement in illicit drug use detection (51-65% vs. 11-56%) • Low overall detection for cannabis use disorder • Severity was most consistently linked to improved detection • The majority of SUD was detected during hospital admission
Clinical Implications Barriers still exist to inpatient provider detection • Prompt in EHR are helpful • Training, supervision, consultation • Increase confidence and comfort discussing substance use with patients Shifting views on detrimental effects of use • Legalization of marijuana • Opioid epidemic
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