Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford
ICRF/NHS Centre for Statistics in Medicine, Institute of Health Sciences, Headington, Oxford
Unit of Health-Care Epidemiology, University of Oxford
![]() |
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Correspondence: Dr John Geddes, Warneford Hospital, Oxford OX37JX. Tel: 01865226480, fax: 01865 793101, e-mail: john.geddes{at}psych.ox.ac.uk
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Aims To identify risk factors for suicide in psychiatric hospital in-patients and to evaluate their predictive power in detecting people at risk of suicide.
Method Using a case-control design, 112 people who committed suicide while in-patients in psychiatric hospitals were compared with 112 randomly selected controls. Univariate analysis and multivariate analyses were used to estimate odds ratios and adjusted likelihood ratios.
Results The rate of suicide in psychiatric in-patients was 13.7 (95% CI 11.7-16.1) per 10 000 admissions. There were five predictive factors with likelihood ratios >2, following adjustment: planned suicide attempt, 4.1; actual suicide attempt, 4.9; recent bereavement, 4.0; presence of delusions, 2.3; chronic mental illness, 2.2; and family history of suicide, 4.6. On this basis, only two of the patients who committed suicide had a predicted risk of suicide above 5%.
Conclusions Although several factors were identified that were strongly associated with suicide, their clinical utility is limited by low sensitivity and specificity, combined with the rarity of suicide, even in this high-risk group.
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
METHOD |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Using the ORLS, control subjects were randomly selected by computer from psychiatric hospital in-patients admitted to the same hospitals in the same period who had not committed suicide. As there are no reliably known risk factors for suicide in in-patients in psychiatric hospitals, controls were unmatched other than for the year of admission. Patients with dementia admitted for respite care were excluded from the control group as they were not considered to be representative of acute psychiatric admissions.
Data collection
Permission to examine clinical records was given by the responsible
consultant psychiatrists and clinical directors. Case notes were obtained from
medical records departments. Clinical and social data were recorded from the
ORLS database and from examination of case notes by one researcher (J.P.),
using a 74-item questionnaire which incorporated characteristics previously
shown or postulated to be factors associated with subsequent suicide
(Appleby, 1992). These factors
were operationally defined for the purposes of the study. To measure the
degree of suicidal ideation, we developed a four-point scale on which patients
were rated (on the evidence of their case notes) as having: no suicidal
ideation; some suicidal ideas but no plan; a plan, but which was not acted
upon; an act of self-harm either leading to, or during, admission.
The questionnaire was developed in a pilot study. The OPCRIT computerised diagnostic classification questionnaire (McGuffin et al, 1991) was completed for all subjects, in addition to the clinical diagnosis recorded from the case notes. Data were recorded anonymously and transferred to a spreadsheet for analysis. It was not feasible for the rater to be blind to whether a subject was a case or a control, because this would have meant excluding important case-note material from the study. Ethical approval for the study was obtained from the local ethics committee.
Statistical analysis
Risk factor analysis
Descriptive analyses were carried out using SPSS
(SPSS, 1997) and EPI-INFO
(Dean et al, 1995).
Univariate and multivariate analyses were carried out using logistic
regression with EGRET and STATA computer software
(StataCorp, 1999;
Statistics and Epidemiology Research
Corporation, 1991). Factors that were statistically significantly
associated with suicide in the univariate analysis were adjusted for the
presence of suicidal ideation, which was strongly associated with suicide.
Results are reported as univariate and multivariate odds ratios with 95%
confidence intervals (CIs).
Likelihood ratio analysis
To estimate the clinical usefulness of the risk factors that were
identified, we calculated likelihood ratios (LRs) for the variables that were
associated with suicide following adjustment for suicidal ideation. LRs
express the predictive value of each risk factor by comparing the probability
that an individual who committed suicide would have that feature, compared
with a control. LRs >1 indicate increased risk of suicide, LRs <1
indicate evidence against suicide; and more extreme values indicate stronger
evidence.
Bayes' theorem states that the post-test odds of a condition, given the
presence of a risk factor, can be found by multiplication of pre-test odds by
the appropriate LR for that risk factor. Direct application of the LRs from
more than one risk factor could be achieved by using extensions of Bayes'
theorem such as:
![]() |
However, such an approach has been termed
naïve or idiot's
Bayes (Feinstein, 1977),
as it does not account for the double counting of evidence from related risk
factors. In practice, it typically overcounts diagnostic or predictive
evidence and produces over-predictive models. A multivariate method to adjust
for such confounding while preserving expression of the results in terms of
LRs has been developed (Spiegelhalter
& Knill-Jones, 1984). Noting that the
naïve Bayes model can be written
in terms of a sum of log likelihood ratios (LLRi):
![]() |
![]() |
Estimates of Si are obtained by logistic regression, and the adjusted LRs can be obtained by back-transformation. Such a model does not account for any interaction of diagnostic elements, solely confounding. A reduced multivariate model was produced by retaining only risk factors with adjusted LRs of 2 or more from the odds ratios logistic regression. Using these with the baseline suicide rate for in-patients allowed us to estimate the post-test probabilities of the predictor variables.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
|
Characteristics of the suicides
As shown in Table 1, more
suicides occurred at the weekend. However, this excess was reduced from 61% to
15% when patients officially on weekend leave were excluded. Seventy-two per
cent (n=70) of suicides of in-patients took place outside the
hospital site; 63% of these patients were absent without leave. The most
common method of suicide was drowning, with 28 drownings in rivers or lakes
and three in baths on the ward. More men than women used violent methods, such
as being hit by a train, or cutting or burning themselves; men were also more
likely to use carbon monoxide or suffocation. The number of suicides by
overdose was small (11%, n=11). Twenty-six per cent (n=25)
of the in-patients not on leave were on formal nursing observations at the
time of suicide, and two in-patients were under continuous observation. One of
these two jumped through a window and deliberately cut his neck with the
broken glass, the other ran to a railway line and was hit by a train.
Comparison of cases and controls
Univariate analyses comparing potential risk factors between cases and
controls are shown in Table 2.
The strongest risk factor for suicide was suicidal thoughts or acts prior to
admission (as recorded in the case notes), and there was a
dose-response between the level of suicidal thoughts or acts and
the degree of risk (likelihood ratio statistic for trend 53.71, 1 d.f.,
P<0.001). Patients who had harmed themselves either before or
during admission were much more likely to commit suicide than control patients
(OR 14.3; 95% CI 6.4-31.8). Other factors that remained significantly
associated with suicide, after adjustment for the degree of suicidal thoughts
or acts, were: recent bereavement (death of significant person in previous 12
months); presence of delusions; hopelessness; previous self-harm (before the
index episode); chronic mental illness of over five years' duration (excluding
diagnosis of personality disorder); previous admission to psychiatric
hospital; and history of suicide in a first-degree relative. Patients with
current drug or alcohol abuse were less likely to kill themselves.
|
Likelihood ratios
The crude LRs (with 95% CI) and LRs adjusted for the variables that were
positively associated with suicide, and the post-test probabilities of each
predictor using the observed pretest probability of 13.7 per 10 000 (0.137%)
are presented in Table 3. The
final model (including factors with adjusted LRs >2) included five
predictors: recent bereavement, presence of delusions, suicidal ideation,
chronic mental illness and a family history of suicide. In principle, these
LRs can be used sequentially. For example, a patient with all five predictors
would have a post-test odds of committing suicide of
(0.137/100-0.137)x4.9x3.9x2.2x2.2x4.6=0.60, or a
probability of suicide of 37%. Only one patient in the data set had all five
risk factors.
|
Assuming a notional level of high risk as being greater than a 5% probability of suicide, the model predicted the cases as shown in Table 4. This table demonstrates that the model is of low sensitivity: only 297 (2%) of patients who committed suicide would have been identified as having a >5% risk of suicide. Twenty-seven per cent (26/97) of the patients who committed suicide had predicted risks of suicide greater than 1%, as did 1% (1/90) of the controls. The estimated median level of risk of suicide in the patients committing suicide was less than 0.5%.
|
If a 5% risk of suicide is considered to be clinically important, then the present data set would suggest that a patient with any three (or delusions plus chronic mental illness plus two others) or more of the five predictors should be considered to be at reasonably high risk. Patients with two (or delusions plus chronic illness plus one other) or more factors have risks of suicide greater than 1%.
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
One weakness of the study is that the rating of the presence of risk factors was not blind to case-control status. However, blinding would have been difficult to achieve: the last entry in all sets of case notes would have to have been removed, in addition to any reference to the suicide - including the writing of deceased on the cover of the notes. The main measures used to avoid observer bias were the prior statement of the putative risk factors of interest, and the use of specific criteria for defining exposure to a potential risk factor.
Another limitation is that the identification of risk factors largely relied on criteria recorded in case notes. We cannot determine how accurate or complete these were, but it is likely that there was a degree of misclassification in the measurement of the risk factors. A prospective study might avoid many of these problems but the rarity of suicide means that such a study would have to be extremely large.
Descriptive data
Our finding that many in-patient suicides occur outside the hospital site
confirms that in previous studies
(Fernando & Storm, 1984; Morgan & Priest, 1991;
Proulx et al, 1997;
Sharma et al, 1998).
The fact that the most common method of suicide was drowning was probably
because this method was easily available: for instance, 22 of 31 drownings
took place in rivers adjacent to or near hospital sites. The high number of
women committing suicide by drowning is striking.
Possible risk factors
The variable with the strongest association with suicide was suicidal
thoughts or acts - there was a dose-response between the
apparent strength of suicidal thoughts, as measured by the extent to which the
patient had acted on the ideation, and the risk of suicide. A recent
descriptive UK study has also identified suicidal ideation as of paramount
importance in the assessment of risk
(Morgan & Stanton, 1997).
Our findings extend those of previous work and confirm the importance of
suicidal thoughts or activity as the most important risk factor for suicide in
psychiatric in-patients.
One of the most striking findings of the study is that some of the factors associated with suicide in the general population (being male, single, living alone, being unemployed, substance abuse) (Charlton et al, 1993), were not associated with suicides by hospital in-patients. This finding, which is clearly important in risk assessment, is consistent with previous case-control studies investigating risk factors for suicide following discharge from psychiatric hospital (Dennehy et al, 1996; Appleby et al, 1999b). The explanation may be that these factors are strongly associated with both admission to psychiatric hospitals and suicidal ideation.
Substance abuse was associated with a reduced risk of suicide: it may be that patients admitted for these problems are not as acutely mentally ill (often being admitted for detoxification) as some other patients and do not have the same suicide risk.
Comparison with similar studies
Although there have been several descriptive studies of in-patient suicide
in the UK (Copas & Robin,
1982; Langley & Bayatti,
1984; Morgan & Priest,
1991), there have been no UK case-control studies. We are aware of
four case-control studies of psychiatric hospital suicides worldwide that
included only in-patients (Modestin et
al, 1992; Read et
al, 1993; Roy &
Draper, 1995; Sharma et
al, 1998). These had fewer cases than our study and applied
univariate analysis only. One was restricted to patients with schizophrenia
(Modestin et al,
1992). In two others the diagnosis of schizophrenia was found to
be a risk factor, while in the fourth the most common diagnosis was a mood
disorder (Read et al,
1993; Roy & Draper,
1995; Sharma et al,
1998). It has been shown that previous self-harm, in particular
during the index admission, is one of the most potent risk factors
(Modestin et al,
1992; Read et al,
1993; Roy & Draper,
1995; Sharma et al,
1998). Compulsory admission was not identified as a risk factor in
our study, but has been in others (Roy
& Draper, 1995; Sharma
et al, 1998). This may be due to differences in the
content and application of mental health legislation. Our study suggests that
a history of suicide in a first-degree relative is a possible risk factor for
in-patient suicide. There was no significant difference between cases and
controls regarding history of psychiatric illness in a first-degree relative.
One other case-control study which investigated family history found that
in-patient suicide cases were more likely to have a family history of
psychiatric problems, but were not significantly different regarding a family
history of suicide (Sharma et al,
1998). It is not clear whether that study restricted the
definition of family history to first-degree relatives.
An association between chronic mental illness and in-patient suicide was shown in one study (Modestin et al, 1992), but not in the other studies that looked at this possibility (Read et al, 1993; Sharma et al, 1998). Other studies have not identified a relationship between abuse of alcohol or illicit drugs and the risk of in-patient suicide (Read et al, 1993; Roy & Draper, 1995).
Prediction and prevention of suicide by in-patients
The reason for identifying factors associated with suicide by in-patients
is that such knowledge may be useful in helping to identify individuals at
risk and to prevent suicides occurring. Previous studies have attempted to
develop models to predict which psychiatric patients might commit suicide
(Pokorny, 1983;
Goldstein et al,
1991), but have been unable to generate models with sufficiently
high sensitivity and specificity to be any good at predicting such a rare
event. In the present study, we have attempted to identify possible risk
factors for suicide in patients in psychiatric hospitals - a particularly
high-risk group.
Our model suggested that 30-40% of in-patients with all five risk factors would commit suicide, as would 5% of those with three or four risk factors. Expressed at the level of the individual patient, a 5% risk means that, for the individual, there is a 1 in 20 risk of suicide while in in-patient care. However, the clinical usefulness of these findings is limited because such combinations of risk factors are extremely rare. Among the 97 suicides included in our data set, only one had all five risk factors and only one other had a predicted risk of suicide of > 5%. Reducing the threshold of concern to a 1% risk of suicide would have identified over 25% of those who committed suicide. The majority of those who committed suicide had predicted risks of suicide below 1%, 14% had no risk factors and 30% had only one risk factor. The model would therefore not have been able to predict the majority of the actual suicides without having an unacceptable (>99%) false positive rate. On the other hand, using the presence of three, four or five predictive factors as rough clinical guides (see Results) may correctly identify a small number of patients as being at high risk. However, the reliability of the predictive model we have developed is uncertain, because it has not been validated in a second independent data set. It should be feasible to test the model in independent data sets derived from other large-scale record linkage studies.
The suicide of a psychiatric hospital in-patient is a rare but important event. As well as the grief caused to family and friends, and the significant effects it can have on other patients, it also raises questions of responsibility and guilt for the professionals involved in caring for the patient. This study suggests that, unless a very high number of false positives is considered acceptable, it is unavoidable that clinicians will fail to identify before-hand a high proportion of suicides, even in a high-risk group such as psychiatric hospital in-patients.
![]() |
Clinical Implications and Limitations |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
LIMITATIONS
![]() |
ACKNOWLEDGMENTS |
---|
We thank Ed Juszczak and Doug Altman for statistical advice during this project.
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Appleby, L., Shaw, J., Amos, J., et al (1999a) Safer Services. Report of the National Confidential Inquiry into Suicide and Homicide by People with Mental Illness. London: Stationery Office.
Appleby, L., Dennehy, J. A., Thomas, C. S., et al (1999b) Aftercare and clinical characteristics of people with mental illness who commit suicide: a case-control study. Lancet, 353, 1397-1400.[CrossRef][Medline]
Blain, P. A. & Donaldson, L. J. (1995) The reporting of inpatient suicides: identifying the problem. Public Health, 109, 293-301.[Medline]
Charlton, J., Kelly, S., Dunnell, K., et al (1993) Suicide deaths in England and Wales: trends in factors associated with suicide deaths. Population Trends, 71, 34-42.
Copas, J. B. & Robin, A. (1982) Suicide in psychiatric in-patients. British Journal of Psychiatry, 141, 503-511.[Medline]
Dean, A. G., Dean, J. A., Coulombier, D., et al (1995) Epi Info, Version 6: A Word-Processing, Database, and Statistics Program for Public Health on IBM-compatible Microcomputers. Atlanta, GA: Centers for Disease Control and Prevention.
Dennehy, J. A., Appleby, L., Thomas, C. S., et al
(1996) Case-control study of suicide by discharged
psychiatric patients. British Medical Journal,
312, 1580.
Feinstein, A. R. (1977) Clinical biostatistics XXXIX: The haze of Bayes, the aerial palaces of decision analysis, and the computerized Ouija board. Clinical Pharmacology and Therapeutics, 21, 482-496.[Medline]
Fernando, S. & Storm, V. (1984) Suicide among psychiatric patients of a district general hospital. Psychological Medicine, 14, 661-672.[Medline]
Geddes, J. R. (1999) Suicide and homicide in
mentally ill patients. British Medical Journal,
318,
1225-1226.
Goldacre, M. J., Simmons, H., Henderson, J., et al (1988) Trends in episode-based and person-based rates of admission to hospital in the Oxford Record Linkage Study area. British Medical Journal, 296, 583-584.[Medline]
Goldstein, R. B., Black, D. W., Nasrallah, A., et al (1991) The prediction of suicide. Sensitivity, specificity, and predictive value of a multivariate model applied to suicide among 1906 patients with affective disorders. Archives of General Psychiatry, 48, 418-422.[Abstract]
Hawton, K. (1987) Assessment of suicide risk. British Journal of Psychiatry, 150, 145-153.[Medline]
Langley, G. E. & Bayatti, N. N. (1984) Suicides in Exe Vale Hospital, 1972-1981. British Journal of Psychiatry, 145, 463-467.[Medline]
McGuffin, P., Farmer, A. E. & Harvey, I. (1991) A polydiagnostic application of operational criteria in studies of psychotic illness: development and reliability of the OPCRIT system. Archives of General Psychiatry, 48, 764-770.[CrossRef][Medline]
Modestin, J., Zarro, I. & Waldvogel, D. (1992) A study of suicide in schizophrenic in-patients. British Journal of Psychiatry, 160, 398-401.[Abstract]
Morgan, H. G. & Priest, P. (1991) Suicide and other unexpected deaths among psychiatric in-patients. The Bristol confidential inquiry. British Journal of Psychiatry, 158, 368-374.[Abstract]
Morgan, H. G. & Stanton, R. (1997) Suicide among psychiatric in-patients in a changing clinical scene. Suicidal ideation as a paramount index of short-term risk. British Journal of Psychiatry, 171, 561-563.[Abstract]
Pokorny, A. D. (1983) Prediction of suicide in psychiatric patients. Report of a prospective study. Archives of General Psychiatry, 40, 249-257.[Abstract]
Proulx, F., Lesage, A. D. & Grunberg, F. (1997) One hundred in-patient suicides. British Journal of Psychiatry, 171, 247-250.[Abstract]
Read, D. A., Thomas, C. S. & Mellsop, G. W. (1993) Suicide among psychiatric inpatients in the Wellington region. Australian and New Zealand Journal of Psychiatry, 27, 392-398.[Medline]
Roy, A. & Draper, R. (1995) Suicide among psychiatric hospital inpatients. Psychological Medicine, 25, 199-202.[Medline]
Sharma, V., Persad, E. & Kueneman, K. (1998) A closer look at inpatient suicide. Journal of Affective Disorders, 47, 123-129.[CrossRef][Medline]
Spiegelhalter, D. J. & Knill-Jones, R. P. (1984) Statistical and knowledge-based approaches to clinical decision-support systems, with an application in gastroenterology. Journal of the Royal Statistical Society, 147, 35-77.
SPSS (1997) SPSS 8.0 for Windows. Chicago, IL: SPSS.
StataCorp (1999) Stata Statistical Software: Release 6.0. College Station, TX: Stata Corporation.
Statistics and Epidemiology Research Corporation (1991) EGRET. Seattle, WA: SERC.
Received for publication March 31, 1999. Revision received August 31, 1999. Accepted for publication September 2, 1999.