Talk from 29th June 2010, IAPT conference London (76 Portland Place).

1. Recognition and identification of People with
Depression - An update
Alex Mitchell ajm80@le.ac.uk
Consultant in Liaison Psychiatry & Psycho-oncology
Implementing the new NICE Guidance in IAPT services (London June 2010)

2. 0. Introduction
Background
Quality of Care

3. Depression Care: Who Provides it?
2/3rds 1/3rd
Primary Care
10% 25%
cg42 cg90 Medical Psychiatry

4. Percentage of U.S. retail psychotropic prescriptions written from August 2006 to jul07
Mark et al. PSYCHIATRIC SERVICES September 2009 Vol. 60 No. 9

5. % Receiving Any treatment for Depression
20
17.9
18 n=84,850 face-to-face interviews
16 15.4
13.8
14
12 11.3
10.9 10.9
10
8.8
8.1
8 7.2
6.8
6 5.6 5.5
4.3
4 3.4
2
0
SA
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a
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er
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ut
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ew
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N
N
Wang P et al (2007) Lancet 2007; 370: 841–50

6. 94.2%
37.4%
8 yrs N= 9282 NCS‐R

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

8. 5 Steps to Improve QoC….and change clinical practice
1. Look Again at Symptoms of Depression
Too complex? Distress?
2. Can We Afford to Detect Depression Routinely
PC vs SC
3. Does Enhanced Detection Work?
Which tool?
4. Depression in medical settings
Special? Somatic symptoms?

9. 1. Symptoms of Depression
Back to Basics

10. Symptom Significance in Depression
Depression ICD10 DSMIV HADs D Score
Severity
Healthy 0 or 1 0 symptom 0-3
symptom
Sub-syndromal 2 or 3 1 or No core 4-7
symptoms symptoms
Mild 4 symptoms 2-4 symptoms 8 -11
(2+2)‫‏‬ (minor)‫‏‬
Moderate (5 or )6 5 symptoms 12 - 15
symptoms (Mj)‫‏‬
Severe (7 or) 8 Unspecified 16 - 21
symptoms
(3+4)‫‏‬

11. “Common” Symptoms of Depression
Item Depressed Frq Non-Depressed Frq
Depressed mood 0.93 0.18
Diminished drive 0.88 0.30
Loss of energy 0.87 0.32
Concentration/indecision 0.87 0.27
Sleep disturbance 0.83 0.32
Diminished concentration 0.82 0.24
Diminished interest/pleasure 0.81 0.12
Insomnia 0.70 0.27
Anxiety 0.69 0.42
Worthlessness 0.61 0.12
Psychic anxiety 0.59 0.33
Thoughts of death 0.56 0.12
Mitchell, Zimmerman et al n=2300

12. “Uncommon” Symptoms
Non-Depressed
Item Depressed Proportion Proportion
Somatic anxiety 0.46 0.25
Decreased appetite 0.45 0.11
Anger 0.44 0.26
Psychomotor agitation 0.34 0.09
Psychomotor retardation 0.28 0.04
Decreased weight 0.23 0.06
Lack of reactive mood 0.22 0.06
Increased appetite 0.19 0.07
Hypersomnia 0.19 0.06
Increased weight 0.16 0.06
Mitchell, Zimmerman et al MIDAS Database. Psychol Med 2009

13. -0.10
0.00
0.10
0.20
0.30
0.40
0.50
A nge
r
A nxie
ty
Decr
ea s e
d app
eti te
Decr
ea s e
d we
ig ht
Depr
es sed
m oo
d
Dimin
is hed
c onc
entr
at ion
identifying non-depressed
Dimin
is hed
dr ive
Dimin
is hed
int er
est /p
leasu
re
Exc e
ss ive
guilt
Help
le
Comment: Slide illustrates added value of each
ss nes
s
symptom when diagnosing depression and when
Hope
le s snes
s
Hy pe
rsom
n ia
Inc re
ased
appe
t ite
Inc re
ased
w eig
ht
Indec
isiv e
ne ss
Ins om
nia
L ac k
of re
act iv
e mo
od
L os s
o f en
erg y
Ps ych
i c an
x iety
Ps ych
omot
or a g
i tatio
n
Ps ych
omot
or c h
ang e
Ps ych
o mot o
r ret a
rdatio
n
Sl eep
dis tu
rban
ce
Soma
ti c a
n x iety
Rule-In Added Value (PPV-Prev)
Thou
g
Rule-Out Added Value (NPV-Prev)
hts o
f dea
th
Wor t
hle s sne
ss

14. 1 Depressed Mood
S Diminished interest/pleasure
e Diminished drive
0.9 n
s Loss of energy
i Sleep disturbance
0.8
t Diminished concentration
i
0.7 v
i
t
0.6 y
0.5
0.4
0.3 Comment: Slide illustrates summary ROC curve
sensitivity/1-specficity plot for each mood
symptom
0.2
0.1
1 - Specificity
0
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
n=1523

15. 2. Recognition in Routine Care
Is “diagnosis as usual” sufficient?

16. Sl e
ep
di s
tur
ban
Los ces
so ; in
fa som
ppe ni a
De ti te ; ea
; ov rly
0
10
20
30
40
50
60
70
80
90
pre
sse ere wa 100
dm a tin ke n
ood g; w ing
; ho e ig
pe ht c
Los Ap les han 86.8
so a th sne ges
f in y; l ss;
ter eth sad
est arg
;w y; t ; gl
oom
ithd
raw
ired
nes y
al ; s; l
55.6 54.4
Los in d ass
so iffe i tud
fe ren e
ner ce;
Los gy; lo n
43.3
so l os eli n
f lib so ess
ido f dr
; lo i ve
36
ss ; bu
An of s rnt
xio ex ou
Sleep
us; dri
ve; t
ag i mp
29.8
itat
ed; Te ote
irri t ars nce
So Fe abl ;w
ma eli n e; r eep
tic; est ing
Appetite
ve g gw l es ; cr
eta ort s, t yi n
tive hl e
ss; ens g
sym gui e; s
pt o l ty; t re
Low
sse
ms
;m lac
ko d
ala f se
i se
26.2 25.6 25.2
Su ;m lf e
i ci d ste
Los ulti
ple em
so e th
ou
GP Asks about:
f co con
Energy
23.8
nce ght sul
ntr s; t ta t
hou ion
atio
n; p ght s
of
24
Dim oor sel
ini s me f in
mo jur
hed ry, y
per poo
f or r th
ma i nk
nce i ng
Em ; in
Los otio abi
21.4 21.2
na li ty
so
fa l la to
cop
Be
ha Los ffec
t; f
bil i
ty; e
vi o so lat mo
ura fe
njo a ff od
l pr ym
ect
; lo sw
ing
obl
em ent ss s
s; a or of e
13.9 12.8
ggr pl e mo
ess asu tion
ive re ;
nes lac
9.5
Pe ko
s; b fh
ssi eh um
mi s avi or
m; our
ne al c
7.2
gat han
Ps ive ges
ych atti
tud
7
Ap om es,
pe oto wo
ara r re rry
nce tar ing
; sp dat
7
eec i on
h; e ; sl
xce He ow
nes
ssi
ve
ada
che s
sm
5.9
He s; d
avy i li n izz
g; v i ne
use ag ss
of a uen
4.8
l co ess
De hol , et
l us , to c.
i on bac
Re co
4.1
s; h
act all u or
ion ci n dru
to p atio gs
rob ns;
2.6
abl con
Fa ec fus
mil aus ion
yo es
or
1.8
r pa life
st h
looking for depression
i sto eve
ry nts
Ob of d
1.8
ses epr
si v ess
e id i on
eat
1.3
i on
; ph
ob
ias
Comment: Slide illustrates which
Lac
symptoms are asked about by GPS
0.9
Pe ko
ri o f in
do sig
f l if ht
e(
0.4
me
no
pau
se )
0.4

17. GP Recognizes:
Proportion of Individual Symptoms Recognised by GPs
80.0 76.1
70.0
60.0
50.0
40.0 36.4
34.6
31.6
30.0
21.6
20.0 16.7
13.3
9.1 8.3 8.3
10.0
0.0
s
ng
a
d
gy
s
ia
st
ty
ism
es
oo
si
ni
ex
re
xie
pi
er
ia
m
ln
m
m
te
Co
or
en
dr
An
so
fu
in
i
An
w
ss
on
ar
In
t
of
Lo
No
of
Pe
Te
ch
ss
ss
po
Lo
Lo
Hy
O’Conner et al (2001) Depression in primary care.
Int Psychogeriatr 13(3) 367-374.

18. GP Detection of Depression – Meta-analysis
Methods
– 140 studies of GP recognition
rate =>
– 90 depression
– 40 interview
– 19 se sp (+2)
– 10 countries

19. Accuracy 2x2 Table
Depression Depression
PRESENT ABSENT
Test +ve True +ve False +ve PPV
Test -ve False -Ve True -Ve NPV
Sensitivity Specificity Prevalence

20. N=35 studies
Accuracy of GP’s Diagnoses
Depression Depression
PRESENT ABSENT
GP +ve 2503 2515 5018
PPV 42.8%
GP -ve 4050 25,125 6678
NPV 85.1%
6553 27,640 9559
Sensitivity Specificity
Prevalence 19%
48% 80.1%

21. N = 100
100 weekly referrals
GP Opinion n = 20 n = 80
20 D 80 ND
Se 50%
GP Assessment Sp 80%
Screen #1 Screen #1
+ve -ve
PPV 28% NPV 88%
TP = 10 TN =64
10TP 10FN FP = 16
64TN 16FP FN = 10
50% TP and 25% FP Offered Treatment
50‐80% accept initial treatment

22. N = 100
100 weekly referrals
GP Notation n = 20 n = 80
20 D 80 ND
Se 30%
GP Assessment Sp 90%
Screen #1 Screen #1
+ve -ve
PPV 50% NPV 80%
TP = 10 TN =64
7TP 13FN FP = 16
72TN 8FP FN = 10
50% TP and 25% FP Offered Treatment
50‐80% accept initial treatment
3/20TP Offered Rx => appropriate treatment rate of 5-20%
2/80FP Offered Rx => inappropriate treatment rate of 1-2%
1/3 of screen positive patients with no treatment well
at follow‐up

23. N = 100
Weekly Population
n = 20 n = 80
Depression No Depression
77%
Se 50%
GP Assessment Sp 80%
Screen #1 Screen #1
+ve -ve
PPV 28% NPV 88%
TP = 10 TN =64
Possible case FP = 16
Probable Non-Case FN = 10
Se 50%
2nd Assessment Sp 80%
Screen #2 Screen #2
+ve +ve
PPV 44% NPV 77%
TP = 56 TN =288
89% Probable Depression FP = 72
Probable Non-Case FN = 84
TN = 728 FP = 72 Se 28% PPV 44%
Cumulative Yield TP = 56 FN = 144 Sp 91% NPV 83%

24. Predictors of Recognition
Prevalence
10% rural 15% mean 20% urban 20% (oncology 25%)
Severity
70% mild 20% moderate 10% severe
International
Low in developing but in Western:
Italy > Netherlands >Australia > UK > US
Contact
Cummulative: 77% single 89% 3-6 months
Appointment Duration

25. 0.05
0.15
0.25
0
0.1
0.2
0.3
Ei
gh
t
N
in
e
Te
n
El
ev
en
Tw
el
ve
Th
irt
ee
HADS-D
n
Fo
ur
te
en
Fi
fte
en
Si
xt
ee
n
Se
ve
nt
Proportion Missed
ee
n
Proportion Recognized
Ei
gh
te
en
N
in
et
ee
n
Tw
en
Tw ty
en
ty
-o
ne

27. 80
74
70 69.6
70
61.5
59.6
60 56.7 56.7 55.6
54.2
50 45.7
43.9
39.7
40
30 28.4
22.2
21
19.3
20
10
0
ns
L
ri s
i
n
a
n
r
go
z
an
ai
a
tle
re
ro
ak
te
TA
ge
ar
n
rli
n
gh
he
lo
Pa
ai
i
ad
ia
ro
at
es
as
ne
k
Be
in
TO
ga
M
nt
An
an
Se
At
Ve
Ib
ch
g
Ja
n
Sa
n
Na
ro
Sh
an
Ba
de
G
M
o
Ri
Recognition from WHO PPGHC Study (Ustun, Goldberg et al)

28. 0.25
65%
0.22
0.21
0.20
0.19
0.20
0.15
0.10
0.05
0.05
0.03
0.02 0.02
0.01 0.01
0.01 0.01 0.01 0.01
0.00
s
s
s
s
s
s
s
s
s
s
s
s
s
s
in
in
in
in
in
in
in
in
in
in
in
in
in
in
m
m
m
m
m
m
m
m
m
m
m
m
m
5m
10
15
20
25
30
35
40
45
50
55
60
65
70

30. Detection in Hospital Settings
CNS in oncology; n=402
Chemotherapy and community nurses
Bayesian analysis

31. 100.0
5.9
11.1
14.3
90.0 Comment: Slide illustrates diagnostic 21.4
accuracy according to score on DT 11.8
25.9
80.0 38.7 38.1
43.5 22.2 14.3
46.7
70.0 59.6
21.4
72.4
60.0 Judgement = Non-distressed
33.3 Judgement = Unclear
19.4 19.0 Judgement = Distressed
50.0
26.1
24.4 82.4
40.0
71.4
66.7
30.0
25.0 57.1
41.9 42.9 40.7
20.0 15.8
30.4 28.9
10.0
15.4
11.8
0.0
Zero One Two Three Four Five Six Seven Eight Nine Ten

32. 1.00
Post-test Probability
GP+
GP-
0.90 Baseline Probability
Nurse+
Nurse-
0.80 Oncologist+
Oncologists-
0.70
0.60
0.50
0.40
0.30 Comment: Doctors appear to be more
successful at ruling-in or giving a
diagnosis, nurses more successful at
0.20 ruling out
0.10
Pre-test Probability
0.00
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

33. 3. Enhanced Detection Strategies
Does Screening Work?

34. Methods to Evaluate Depression
Unassisted Clinician Conventional Scales
Untrained Trained Short (5-10)‫ ‏‬Long (10+)‫‏‬
Other/Uncertain
Ultra-Short (<5)‫‏‬
9%
ICD10/DSMIV
0%
Short QQ
3% Other/Uncertain Other/Uncertain
9% 9%
ICD10/DSMIV ICD10/DSMIV
0% 0%
Short QQ Short QQ
1,2 or 3 Sim ple
3% 3%
QQ
15%
Clinical Skills 1,2 or 3 Sim ple 1,2 or 3 Sim ple
Alone QQ QQ
73% 15% 15%
Clinical Skills Clinical Skills
Alone Alone
73% 73%
Verbal Questions Visual-Analogue Test
PHQ2 Distress Thermometer
WHO-5 Depression Thermometer
Whooley/NICE

36. 1.00 HADS+
Post-test Probability
HADS-
Baseline Probability
0.90
GDS30+
GDS30-
0.80 GDS15+
GHQ28+
HDRS+
0.70
ZUNG+
GDS15-
0.60 GHQ28-
HDRS-
ZUNG-
0.50
PHQ9+
PHQ9-
0.40 WHOOLEY2Q+
WHOOLEY2Q-
BDI+
0.30 BDI-
BDI-SF+
0.20 BDI-SF-
CESD+
CESD-
0.10 1Q+
1Q-
Pre-test Probability
GHQ12+
0.00
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 GHQ12-
Rule-in

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

40. 1.00
Post-test Probability
Clinical+
Clinical-
0.90 Baseline Probability
Screen+
Screen-
0.80
0.70
0.60
0.50
0.40
Comment: Slide illustrates Bayesian
0.30 curve comparison from RCT studies of
clinician with and without screening
0.20 This illustrates ACTUAL gain from
screening in Study from Christensen
0.10
Pre-test Probability
0.00
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

41. 4. Summary
Over and under-diagnosed
Symptoms imperfect and hard to remember
Screening works with enhancements
Quality of care is key

42. =86.4% =82.2%
Beals AGP 2004 =57.6%