Alex Mitchell ajm80@le.ac.uk

Consultant in Liaison Psychiatry & Psycho-oncology

Recognition and identification of People with

Depression - An update

Implementing the new NICE Guidance in IAPT services (London June 2010)

0. Introduction

Background

Quality of Care

Depression Care: Who Provides it?

2/3rds 1/3rd

25%Psychiatry

10%Medical

Primary Care

cg90cg42

Percentage of U.S. retail psychotropic prescriptions written from August 2006 to jul07

Mark et al. PSYCHIATRIC SERVICES September 2009 Vol. 60 No. 9

% Receiving Any treatment for Depression

10.911.3

8.18.8

4.3

5.6

10.9

13.8

6.8

17.9

3.4

5.5

15.4

7.2

0

2

4

6

8

10

12

14

16

18

20

High Inc

omeBelg

ium

France

German

y

Israe

l

Italy

Japa

nNeth

erlan

dsNew

Zeala

nd

Spain USALow

Inco

me

ChinaColom

biaSouth

Afri

caUkra

ine

Wang P et al (2007) Lancet 2007; 370: 841–50

n=84,850 face-to-face interviews

94.2%

37.4%

8 yrs N= 9282 NCS‐R

N=23 studies; 50% some treatment 33% minimal treatment N=19 studies; 30% 1 in 1/12; 10% 3 in 3 months

5 Steps to Improve QoC….and change clinical practice

1. Look Again at Symptoms of DepressionToo complex? Distress?

2. Can We Afford to Detect Depression RoutinelyPC vs SC

3. Does Enhanced Detection Work?Which tool?

4. Depression in medical settingsSpecial? Somatic symptoms?

1. Symptoms of Depression

Back to Basics

Symptom Significance in Depression

(7 or) 8 symptoms ‏(3+4)

(5 or )6 symptoms

4 symptoms ‏(2+2)

2 or 3 symptoms

0 or 1 symptom

ICD10

16 - 21UnspecifiedSevere

12 - 155 symptoms (Mj)‏

Moderate

8 -112-4 symptoms (minor) ‏

Mild

4 - 71 or No core symptoms

Sub-syndromal

0 - 30 symptomHealthy

HADs D ScoreDSMIVDepression Severity

“Common” Symptoms of Depression

0.120.56Thoughts of death

0.330.59Psychic anxiety

0.120.61Worthlessness

0.420.69Anxiety

0.270.70Insomnia

0.120.81Diminished interest/pleasure

0.240.82Diminished concentration

0.320.83Sleep disturbance

0.270.87Concentration/indecision

0.320.87Loss of energy

0.300.88Diminished drive

0.180.93Depressed mood

Non-Depressed FrqDepressed FrqItem

Mitchell, Zimmerman et al n=2300

“Uncommon” Symptoms

0.060.16Increased weight

0.060.19Hypersomnia

0.070.19Increased appetite

0.060.22Lack of reactive mood

0.060.23Decreased weight

0.040.28Psychomotor retardation

0.090.34Psychomotor agitation

0.260.44Anger

0.110.45Decreased appetite

0.250.46Somatic anxiety

Non-Depressed ProportionDepressed ProportionItem

Mitchell, Zimmerman et al MIDAS Database. Psychol Med 2009

-0.10

0.00

0.10

0.20

0.30

0.40

0.50A

nger

Anx

iety

Dec

reas

ed a

ppet

ite

Dec

reas

ed w

eigh

t

Dep

ress

ed m

ood

Dim

inis

hed

conc

entr

atio

n

Dim

inis

hed

driv

eD

imin

ishe

d in

tere

st/p

leas

ure

Exce

ssiv

e gu

ilt

Hel

ple

ssne

ss

Hop

eles

snes

s

Hyp

erso

mni

a

Incr

ease

d ap

peti

te

Incr

ease

d w

eigh

t

Inde

cisi

vene

ss

Inso

mni

aLa

ck o

f re

acti

ve m

ood

Loss

of

ener

gy

Psyc

hic

anxi

ety

Psyc

hom

otor

agi

tati

on

Psyc

hom

otor

cha

nge

Psyc

hom

otor

ret

arda

tion

Slee

p di

stur

banc

e

Som

atic

anx

iety

Thou

ghts

of

deat

h

Wor

thle

ssne

ss

Rule-In Added Value (PPV-Prev)Rule-Out Added Value (NPV-Prev)

Comment: Slide illustrates added value of each symptom when diagnosing depression and when identifying non-depressed

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Depressed Mood

Diminished drive

Diminished interest/pleasure

Loss of energy

Sleep disturbanceDiminished concentration

Sensitivity

1 - Specificity

n=1523

Comment: Slide illustrates summary ROC curve sensitivity/1-specficity plot for each mood symptom

2. Recognition in Routine Care

Is “diagnosis as usual” sufficient?

86.8

55.6 54.4

43.3

36

29.826.2 25.6 25.2 23.8 24

21.4 21.2

13.9 12.89.5

7.2 7 7 5.9 4.8 4.1 2.6 1.8 1.8 1.3 0.9 0.4 0.40

10

20

30

40

50

60

70

80

90

100

Slee

p di

stur

banc

es; i

nsom

nia;

ear

ly w

aken

ing

Loss

of a

ppet

ite; o

vere

atin

g; w

eigh

t cha

nges

Dep

ress

ed m

ood;

hop

eles

snes

s; s

ad; g

loom

y

Apat

hy; l

etha

rgy;

tire

dnes

s; la

ssitu

de

Loss

of i

nter

est;

with

draw

al; i

ndiff

eren

ce; l

onel

ines

s

Loss

of e

nerg

y; lo

ss o

f driv

e; b

urnt

out

Loss

of l

ibido

; los

s of

sex

driv

e; im

pote

nce

Tear

s; w

eepi

ng; c

ryin

g

Anxi

ous;

agi

tate

d; ir

ritab

le; r

estle

ss, t

ense

; stre

ssed

Feeli

ng w

orth

less

; gui

lty; l

ack

of s

elf e

stee

m

Som

atic

; veg

etat

ive

sym

ptom

s; m

alai

se; m

ultip

le c

onsu

ltatio

ns

Suici

de th

ough

ts; t

houg

ht o

f sel

f inj

ury

Loss

of c

once

ntra

tion;

poo

r mem

ory,

poo

r thi

nkin

g

Dim

inis

hed

perfo

rman

ce; i

nabi

lity to

cop

e

Emot

iona

l labi

lity;

moo

d sw

ings

Loss

of a

ffect

; fla

t affe

ct; l

oss o

f em

otio

n

Loss

of e

njoy

men

t or p

leas

ure;

lack

of h

umor

Beha

viou

ral p

robl

ems;

agg

ress

iven

ess;

beh

avio

ural

cha

nges

Pess

imis

m; n

egat

ive

attit

udes

, wor

ryin

g

Psyc

hom

otor

reta

rdat

ion;

slow

ness

Hea

dach

es; d

izzi

ness

Appe

aran

ce; s

peec

h; e

xces

sive

sm

iling

; vag

uene

ss, e

tc.

Hea

vy u

se o

f alc

ohol

, tob

acco

or d

rugs

Del

usio

ns; h

alluc

inat

ions

; con

fusi

on

Reac

tion

to p

roba

ble

caus

es o

r life

eve

nts

Fam

ily o

r pas

t his

tory

of d

epre

ssio

n

Obs

essi

ve id

eatio

n; p

hobi

asLa

ck o

f ins

ight

Perio

d of

life

(men

opau

se)

Comment: Slide illustrates which symptoms are asked about by GPS looking for depression

GP Asks about:Sleep

AppetiteLow

Energy

GP Recognizes:Proportion of Individual Symptoms Recognised by GPs

76.1

36.4 34.631.6

21.616.7

13.39.1 8.3 8.3

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

Low m

ood

Insomnia

Hypoc

hondri

asis

Loss

of in

terest

Tearfu

lness

Anxiety

Loss

of en

ergy

Pessim

ism

Anorex

ia

Not Copin

g

O’Conner et al (2001) Depression in primary care.Int Psychogeriatr 13(3) 367-374.

GP Detection of Depression – Meta-analysis

Methods– 140 studies of GP recognition

rate =>

– 90 depression– 40 interview– 19 se sp (+2)– 10 countries

Accuracy 2x2 Table

PrevalenceSpecificitySensitivity

NPVTrue -VeFalse -VeTest -ve

PPVFalse +veTrue +veTest +ve

DepressionABSENT

DepressionPRESENT

Accuracy of GP’s Diagnoses

955927,6406553

667825,1254050GP -ve

501825152503GP +ve

DepressionABSENT

DepressionPRESENT

Sensitivity48%

PPV 42.8%

Specificity80.1%

NPV 85.1%

Prevalence 19%

N=35 studies

100 weekly referrals

GP Assessment

10TP 10FN

20 D

Screen #1+ve

n = 20 80 ND

Sp 80%

Se 50%

n = 80

N = 100

TP = 10

FP = 1664TN 16FP TN =64

FN = 10

PPV 28% NPV 88%

Screen #1-ve

GP Opinion

50% TP and 25% FP Offered Treatment

50‐80% accept initial treatment

100 weekly referrals

GP Assessment

7TP 13FN

20 D

Screen #1+ve

n = 20 80 ND

Sp 90%

Se 30%

n = 80

N = 100

TP = 10

FP = 1672TN 8FP TN =64

FN = 10

PPV 50% NPV 80%

Screen #1-ve

50% TP and 25% FP Offered Treatment

50‐80% accept initial treatment

1/3 of screen positive patients with no treatment well at follow‐up

GP Notation

3/20TP Offered Rx => appropriate treatment rate of 5-20%

2/80FP Offered Rx => inappropriate treatment rate of 1-2%

Weekly Population

GP Assessment

Possible case

Depression

Screen #1+ve

n = 20 No Depression

Sp 80%

Se 50%

n = 80

N = 100

TP = 10

FP = 16Probable Non-Case TN =64

FN = 10

PPV 28%

2nd Assessment Sp 80%

Se 50%

NPV 88%

Probable Depression TP = 56

FP = 72Probable Non-Case TN =288

FN = 84

PPV 44% NPV 77%

Screen #1-ve

Screen #2+ve

Screen #2+ve

Cumulative YieldTP = 56

TN = 728

FN = 144

FP = 72

NPV 83%

PPV 44%

Sp 91%

Se 28%

77%

89%

Predictors of Recognition

Prevalence10% rural 15% mean 20% urban 20% (oncology 25%)

Severity70% mild 20% moderate 10% severe

InternationalLow in developing but in Western:Italy > Netherlands >Australia > UK > US

ContactCummulative: 77% single 89% 3-6 monthsAppointment Duration

0

0.05

0.1

0.15

0.2

0.25

0.3

Eight

Nine Ten

Eleven

Twelv

eTh

irtee

nFo

urtee

n

Fiftee

nSixt

een

Seven

teen

Eighteen

Ninetee

n

Twen

tyTw

enty-

one

Proportion MissedProportion Recognized

HADS-D

Recognition from WHO PPGHC Study (Ustun, Goldberg et al)

7470 69.6

61.5 59.656.7 56.7 55.6 54.2

45.7 43.939.7

28.4

22.2 21 19.3

0

10

20

30

40

50

60

70

80

Santia

go

Verona

Manch

ester

Paris

Groningen

Berlin

Seattle

Mainz

TOTALBangalo

reRio de J

aneir

o

Ibadan

Ankara

Athen

sShan

ghaiNagas

aki

0.03

0.19

0.210.22

0.20

0.05

0.02 0.020.01 0.01

0.010.01 0.01 0.01

0.00

0.05

0.10

0.15

0.20

0.25

5mins

10mins

15mins

20mins

25mins

30mins

35mins

40mins

45mins

50mins

55mins

60mins

65mins

70mins

65%

Detection in Hospital Settings

CNS in oncology; n=402

Chemotherapy and community nurses

Bayesian analysis

Comment: Slide illustrates diagnostic accuracy according to score on DT

11.815.4

30.4 28.9

41.9 42.9 40.7

57.1

82.4

66.771.4

15.8

25.0

26.124.4

19.4 19.0

33.3

21.4

11.8

22.2 14.3

72.4

59.6

43.546.7

38.7 38.1

25.921.4

5.911.1

14.3

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

Zero One Two Three Four Five Six Seven Eight Nine Ten

Judgement = Non-distressedJudgement = UnclearJudgement = Distressed

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pre-test Probability

Pos

t-tes

t Pro

babi

lity

GP+GP-Baseline ProbabilityNurse+Nurse-Oncologist+Oncologists-

Comment: Doctors appear to be more successful at ruling-in or giving a diagnosis, nurses more successful at ruling out

3. Enhanced Detection Strategies

Does Screening Work?

1,2 or 3 Simple QQ15%

Clinical Skills Alone73%

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

Methods to Evaluate Depression

Unassisted Clinician Conventional Scales

Verbal Questions Visual-Analogue Test

PHQ2

WHO-5

Whooley/NICE

Distress Thermometer

Depression Thermometer

Ultra-Short (<5)‏Short (5-10)‏ Long (10+)‏Untrained Trained

1,2 or 3 Simple QQ15%

Clinical Skills Alone73%

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

1,2 or 3 Simple QQ15%

Clinical Skills Alone73%

ICD10/DSMIV0%

Short QQ3%

Other/Uncertain9%

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pre-test Probability

Post

-test

Pro

babi

lity HADS+

HADS-

Baseline Probability

GDS30+

GDS30-

GDS15+

GHQ28+

HDRS+

ZUNG+

GDS15-

GHQ28-

HDRS-

ZUNG-

PHQ9+

PHQ9-

WHOOLEY2Q+

WHOOLEY2Q-

BDI+

BDI-

BDI-SF+

BDI-SF-

CESD+

CESD-

1Q+

1Q-

GHQ12+

GHQ12-

Rule-in

Comment: Slide illustrates actual gain in meta-analysis of screening implementation in primary care

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Pre-test Probability

Pos

t-tes

t Pro

babi

lity

Clinical+Clinical-Baseline ProbabilityScreen+Screen-

Comment: Slide illustrates Bayesian curve comparison from RCT studies of clinician with and without screening

This illustrates ACTUAL gain from screening in Study from Christensen

4. Summary

Over and under-diagnosed

Symptoms imperfect and hard to remember

Screening works with enhancements

Quality of care is key

=86.4% =82.2%

=57.6%Beals AGP 2004