Depression CDSS
description
Transcript of Depression CDSS
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Depression CDSS
Charles Kitzman, Barbary Baer, Sudha Poosa
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The Project
To maximize BH efficiencies while maintaining quality care
Workflow optimization FQHC integrated BH model Strategic partnership Continuity of care/chart sharing Advanced primary care practice
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Environment
FQHC northern CA county Woefully inadequate BH services
PH contractual outpatient Demand > Access Obligation to have streamlined services Filter inadequate referrals Time for appropriate patients
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Backdrop
Higher rates for Suicide >50% 65 or older
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Conditions leading to death -rates in Shasta County
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County crisis stabilization
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Rank by county
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Bottling the ends
Our approach sought to narrow scope Why? It’s a diverse field with lots of
variability. Makes it difficult to study Many tools, many interpretations Depression is our focus PQH-9 and lab results respectively
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Rationale for screening
Only half of depressed patients are diagnosed by their primary care physician
Patients with serious mental illness are 23% more likely to have a non-psychiatric hospitalization compared to the rest of the population. At $6000/admission, this adds $16 million to California’s Medi-Cal program
Depression is associated with greater health service use, greater morbidity & mortality, increased medical costs, not to mention unnecessary suffering
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Screening Triggers
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PHQ-9
Advantages Self-administered Freely available Short (9 items) Has been validated in Spanish
Sensitivity: from 94.4% (cutoff point >= 9) to 88.9% (cutoff point >= 13) Specificity: from 73.3% (cutoff point >= 9) to 86.7% (cutoff point >= 13)
Original study: Sensitivity for major depression: 88% for scores > 10 Specificity for major depression: 88% Scores of 5, 10, 15, 20 represented mild, moderate, moderately
severe, severe depression respectively
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PHQ-9 Questionnaire
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Depression CDSS flowchart
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Depression CDSS Mindmap
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System : Input
Demographics Chief complaint HPI (History of present illness)
Other illnesses Medications Life events
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System : Architecture and Interface
Enterprise wide client-server based architecture Architecture will comprise database and the rules engine Compliant with standards – HIPAA, LOINC, HL7, etc. Use of drop menus and logic checks Use of clinic reminders and alerts Capability of creating individual care plans with self-
management information and disease severity rating Linked with, but not a substitute for electronic medical
records. Will be integrated at the point of care PHQ-9 entry can be made by the patient, nurse or the
clinician
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System : Output & Workflow
Context-specific decision support in real time
Test score & risk stratification
Treatment regimen Whom to refer the patient to (level of BH clinician)
When should the patient be tested / re-evaluated
When to administer medications to the patient
Treatment options No treatment
Watchful waiting
Psychotherapy / counseling
Anti-depressant medication
Combination therapies
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System : Output & Workflow
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Evaluation
Audit of inappropriate referrals with an expectation of declining numbers
Increased access or an increase in encounters per clinic hour for BH staff
Increase in consistent use of screening tools by PC staff
Log trigger results to check provider compliance with tool suggestions
Better outcomes
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Conclusions
Difficult to separate operations from clinical decision piece
BH is very complex field to understand Actually will beta-test in the clinic with a few
providers
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Q & A