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Debate: Clinical risk categorization is valuable in the prevention of suicide and severe violence? Yes Nick O'Connor, John Allan and Charles Scott Australas Psychiatry 2014 22: 7 DOI: 10.1177/1039856213510580 The online version of this article can be found at: http://apy.sagepub.com/content/22/1/7
Published by: http://www.sagepublications.com
On behalf of:
The Royal Australian and New Zealand College of Psychiatrists
Additional services and information for Australasian Psychiatry can be found at: Email Alerts: http://apy.sagepub.com/cgi/alerts Subscriptions: http://apy.sagepub.com/subscriptions Reprints: http://www.sagepub.com/journalsReprints.nav Permissions: http://www.sagepub.com/journalsPermissions.nav
>> Version of Record - Feb 10, 2014 What is This?
Downloaded from apy.sagepub.com at UVI on May 11, 2014
510580
2014
APY22110.1177/1039856213510580Australasian PsychiatryO’Connor et al.
AP
Debate
Editor’s note: The following debate took place at the RANZCP Congress in Sydney in May 2013.
Australasian Psychiatry 2014, Vol 22(1) 7–9 © The Royal Australian and New Zealand College of Psychiatrists 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1039856213510580 apy.sagepub.com
Debate: Clinical risk categorization is valuable in the prevention of suicide and severe violence? Yes
Nick O’Connor Clinical Director North Shore Ryde Mental Health Service, Northern Sydney Local Health District and; Senior Clinical Lecturer, Department of Psychological Medicine, University of Sydney, Sydney, NSW, Australia
John Allan Chief Psychiatrist New South Wales Ministry of Health, Sydney, NSW; Associate Professor, School of Psychiatry University of New South Wales, Sydney, NSW, Australia
Charles Scott Chief, Division of Psychiatry and the Law. Training Director, Forensic Psychiatry Fellowship, Professor of Clinical Psychiatry Department of Psychiatry and Behavioral Sciences University of California, Davis Medical Center, Sacramento, CA, USA
T
he essential element of clinical risk categorization is that the clinician formulates the person as being of high or low risk of a specific outcome: suicide or severe violence. Other forms of risk categorization may include specifiers of risk category: immediate, short-term or long-term risk, high or low levels of changeability and/or uncertainty. The assessment process is informed by corroborative sources and by the clinical team’s knowledge of the person over time, and anticipation of the conditions or scenarios that might make the adverse event more likely. Good risk management involves the person, his/her family and the Mental Health Service taking actions. Clinical risk categorization is a common-sense approach and a societal expectation. Risk categorization is an effective mode of clinical reasoning that reduces the chance of common diagnostic errors. Those who oppose risk categorization will try to confuse matters with rare event statistics, false positive and negative rates and ‘areas under curves’. While there has been no prospective research study of all the essential elements of clinical risk categorization, there is emerging, real-world evidence that risk categorization approaches have led to reductions of suicide rates and prevalence of severe violence incidents in high-risk groups.
Not about prediction Clinical risk assessment is not about prediction of whether a rare event will happen. It is not a crystal ball. However, clinical risk assessment will tell us who is in the ‘high stakes’1 category for serious adverse events.
Mullen:2 Critics of false positive rates in the prediction of dangerousness assume that dangerousness is not a probability but a quality only waiting the right moment to manifest. Good risk management is essentially a formulative, reflective and dynamic process. It marries the knowledge from empirical studies about risk factors with involvement of the person and their family. Further, good risk assessment involves a crucial element of reflective thinking about issues such as the quality of the engagement, uncertainties and changeability.3 Risk is by nature dynamic. Risk assessments and categorization require continual adjustment and revision as new information becomes available, or the clinical condition changes.
All clinicians use risk analysis Physicians, surgeons and psychiatrists make decisions which are informed by some sort of risk analysis every day. How else can we proceed in a world that is by its nature uncertain? Very often such consideration of risk remains a complex judgement in the mind of the clinician, with only the decision about the intervention documented. The introduction of semi-structured risk assessment protocols is an attempt to make this process Correspondence: Nick O’Connor, Clinical Director North Shore Ryde Mental Health Service, Northern Sydney Local Health District and Senior Clinical Lecturer, Department of Psychological Medicine, University of Sydney, Sydney, NSW 2065, Australia. Email: [email protected]
7 Downloaded from apy.sagepub.com at UVI on May 11, 2014
Australasian Psychiatry 22(1)
a considered and explicit exercise and one that can be communicated. The literature on incidents and medical error and the research literature on the way doctors think support a clinical risk categorization approach. Two-thirds of root causes of serious clinical incidents involved cognitive elements: we did not gather the relevant data optimally or we failed to correctly synthesize the available data. Knowledge deficits per se are unusual in experienced clinicians.4 Clinical risk categorization improves the likelihood of a safe patient outcome by structuring the data gathering, inquiry process and ‘disposition decision making’.
The problem of false positives Those who criticize clinical risk assessment have elegantly modelled the sensitivity and specificity of predicting rare events such as homicide or suicide. Large points out that 35,000 patients would need to be detained in order to prevent one person with schizophrenia murdering a stranger.5 It has long been known that psychiatrists cannot predict suicide.6,7 These arguments are not new.2 We contend they are the wrong arguments. Clinical risk management is not about prediction but prevention. It is about mitigating the conditions under which a disaster may occur. Actuarial difficulties in relation to prediction as to whether an event will actually occur are peripheral. Who would not place in involuntary care a person who has been threatening people in the street with serious aggression because he believes they are monitoring, controlling and poisoning him – even though actuarially the chance of this man killing a stranger is extremely remote? We share concerns that clinical risk categorization not become a ‘tick box’ approach that ‘dumbs down’ clinical formulation. Risk categorization frameworks that have been mandated in a number of jurisdictions have unfortunately confused risk assessment proformas with the complex and reflective process of risk formulation and management. Risk categorization reflects a current societal paradigm that even the average man in the street expects to see applied in a range of social service contracts; most importantly in the clinical decision making of cardiologists, surgeons, oncologists and psychiatrists.
Risk categorization in the real world It is disingenuous for clinicians to say that they can abandon all consideration of risk by invoking ‘universal precautions’ and ‘good clinical practice’. In the real world we do concentrate our efforts on those people with high need. In a study across England and Wales looking at suicide rates 1997–2006 before and after the implementation of nine of the 12 evidence-based interventions services could make to change the suicide rate, the more of these changes that services implemented the lower the suicide
rate.8 Recommendations which had the greatest positive effect included introducing a 24-hour crisis service, introducing policies on patients with dual diagnoses, and multidisciplinary review after suicide. The number of recommendations implemented increased from 0.3% per service in 1998 to 7.2 per service in 2006. There were significant falls of up to 20% in the suicide rate for the catchment areas served by these services, but if services did not implement the recommendations there was little reduction. One of the recommendations made by the Inquiry but not measured in this study was that all patients with severe mental illness and a history of self-harm or violence receive the most intensive level of care.9 These are the patients that structured risk assessments would rate as high risk and whom therefore would have received the most intensive treatment. The researchers felt this was so self-evident it would not be a discriminating factor between services. Those patients, who through proper risk assessment, identification and categorization combined with a range of targeted clinical activity to change that risk, had better outcomes. Also, the biggest change in suicide rates were in services with the most deprived catchment areas and the most patients, making it likely their resources were thinly spread. So targeting based on risk makes sense. This study will never be included in a meta-analysis because it involves too many real-world assumptions. Similarly in New South Wales, the Tracking Tragedy Report into inpatient suicides in 200310 noted the lack of standardization of suicide risk assessment and poor protocols based on risk. Structured risk assessment via the Mental Health Outcomes and Assessment Tools was introduced with clear implementation protocols. Over a series of reports in 200811 and 2011,12 it appears that the inpatient suicide rate has halved (unpublished data). Much of this is correctly attributed to efforts in improving observation, decreasing physical risk and eliminating hanging points, but it is also an endorsement of categorizing risk. McDermott et al.13 presented the results of their study that examined the use of the Classification of Violence Risk (COVR) in identifying forensic patients at high or very high risk of aggression. If the COVR successfully identified groups at higher risk of violence and interventions were implemented to address those higher risk patients, then the relationship of COVR scores (i.e. higher risk groups) to subsequent aggression should decrease over time. In this study, 328 patients were administered the COVR and followed for incidents of hospital aggression over a 20-week period. The rate of aggression for those identified at higher risk decreased from 67% to 24% after the COVR was implemented. The researchers concluded that the identification of groups of high risk of aggression resulted in focused treatment for these groups, which resulted in a significant reduction in aggressive acts. The biggest danger is the call to abandon risk assessments because there is no evidence that they are predictive.
8 Downloaded from apy.sagepub.com at UVI on May 11, 2014
O’Connor et al.
In the real world this oversimplification sends a dangerous message. It is tantamount a call to abandon patient safety. We do not use risk categories like a bookmaker to assess the outcome and hedge our bets accordingly; we use them to rig the race in our favour, interfering with the outcome, guiding our efforts and combining them with our clinical acumen.
The problem with Large et al.’s meta-analyses Meta-analyses are a valuable tool to assist clinicians for evidence-based decision making. When choosing which studies to include in a meta-analysis, the researcher must develop inclusion criteria relevant to the research question being addressed. Including even one study that incorporates data that is not in line with the proposed hypothesis can introduce bias into the ultimate findings, even with the most elegant mathematical analyses.14 Large et al.15 cite their meta-analysis of seven studies of inpatient suicides to conclude that depressed mood and a prior history of self-harm are the only well-established independent risk factors for inpatient suicide, and the use of these risk factors would prevent few, if any suicides. Perhaps the authors’ conclusions are correct and other reported risk factors, including active suicidal thoughts, are not clinically meaningful risk factors associated with psychiatric inpatient suicides. However, are the studies included in their meta-analysis truly representative of inpatient suicides? Careful examination of the seven studies used in their meta-analysis of ‘inpatient suicides’ reveal a number of concerns. First, some of the studies included suicides that were not actually classified as suicides. For example, in the study by Powell et al.,16 47% of the men and 46% of the women classified as having committed suicide were ‘open verdicts’, meaning that their death had not been officially determined by the coroner as a suicide. Second, the length of psychiatric inpatient hospitalization of included studies does not represent current acute inpatient psychiatric lengths of stay, and calls into question the applicability to modern practice. To illustrate, in the Hunt et al. study,17 the authors note that the maximum length of admission prior to suicide of included subjects was 436 weeks (over 8 years). Third, many of the studies relied on archival data in case notes. Acknowledging this substantial limitation to their study, Powell et al.16 note, “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 (p. 268).” As a result of their findings from this meta-analysis, Large et al.15 suggest that any type of risk assessment that categorizes patients into high-and low-risk groups should not be included in decision making. The studies included
in their meta-analysis make such assertions premature. We do agree, however, with their conclusion, which reads, “Rational risk management for inpatient suicide involves the careful attention to the safety of hospital environments, the optimal care of each patient’s illness and appropriate responses to each patient’s circumstances.” (p. 512). After all is said and done, isn’t paying careful attention to ‘patient’s circumstances’ just another way of making sure you address the patient’s risks? Disclosure The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.
References 1. O’Connor N. The wrong lessons. Australas Psychiatry 2013; 21: 178. 2. Mullen P. Mental disorder and dangerousness. Aust N Z J Psychiatry 1984; 18: 8–17. 3. O’Connor N, Warby M, Rahael B, et al. Changeability, confidence, common sense and corroboration: comprehensive suicide risk assessment. Australas Psychiatry 2004; 12: 352–360. 4. Graber ML. Educational strategies to reduce diagnostic error: Can you teach this stuff? Adv Health Sci Educ 2009; 14: 63–69. 5. Large M. Does the emphasis on risk in psychiatry serve the interests of patients or the public? No. BMJ [serial on the Internet]. 2013; 346. 6. Pokorny AD. Prediction of suicide in psychiatric patients: A prospective study. Arch Gen Psychiatry 1983; 45: 249–257. 7. Goldstein RB, Black DW, Nasrallah MA, et al. The prediction of suicide. Arch Gen Psychiatry 1991; 48: 418–422. 8. While D, Bickley H, Roscoe A, et al. Implementation of mental health service recommendations in England and Wales and suicide rates, 1997–2006: A cross-sectional and before-and-after observational study. Lancet 2012; 379: 1005–1012. 9. Appleby L, Shaw J, Sherratt J, et al. Safety First. Report of the National Confidential Inquiry into Suicide and Homicide by People with Mental Illness. Manchester UK: British Document Supply Centre, 2001. 10. NSW Mental Health Sentinel Events Review Committee. Tracking Tragedy. A systemic look at suicides and homicides amongst mental health inpatients. Sydney, Australia: NSW Health, http://www0.health.nsw.gov.au/pubs/2003/pdf/serc.pdf 2003 (accessed 21 October 2013). 11. Committee NSER. Tracking Tragedy: A systemic look at homicide and non-fatal serious injury by mental health patients, and suicide death of mental health inpatients. Fourth Report of the Committee. Sydney, Australia: NSW Health, http://www0.health.nsw. gov.au/pubs/2009/pdf/tracking_tragedy_2008_fourth_report.PDF 2008 (accessed 21 October 2013). 12. Commission CE. Clinical Focus Report from Review of RCAs and/or IIMS Data on Inpatient Suicide and Self-Harm Sydney, Australia: Clinical Excellence Commission, 2011. 13. McDermott B, Dualan I, et al. The use of the COVR to identify and treat violence risk in a forensic hospital setting. Tuscon, Arizona: American Academy of Psychiatry and the Law Annual Meeting; 2010. 14. Field AP and Gillet R. Expert tutorial. How to do a meta-analysis. Br J Math Stat Psychol 2010; 63: 665–694. 15. Large M, Ryan C and Nielssen O. The validity and utility of risk assessment for inpatient suicide. Australas Psychiatry 2011; 19: 507–512. 16. Powell J, Geddes J, Deeks J, et al. Suicide in psychiatric hospital in-patients. Br J Psychiatry 2000; 176: 266–272. 17. Hunt IM, Kapur N, Webb R, et al. Suicide in current psychiatric in-patients: A casecontrol study. The National Confidential Inquiry into Suicide and Homicide. Psychol Med 2007; 37: 831–837.
9 Downloaded from apy.sagepub.com at UVI on May 11, 2014
Debate: Clinical risk categorization is valuable in the prevention of suicide and severe violence? Yes Nick O'Connor, John Allan and Charles Scott Australas Psychiatry 2014 22: 7 DOI: 10.1177/1039856213510580 The online version of this article can be found at: http://apy.sagepub.com/content/22/1/7
Published by: http://www.sagepublications.com
On behalf of:
The Royal Australian and New Zealand College of Psychiatrists
Additional services and information for Australasian Psychiatry can be found at: Email Alerts: http://apy.sagepub.com/cgi/alerts Subscriptions: http://apy.sagepub.com/subscriptions Reprints: http://www.sagepub.com/journalsReprints.nav Permissions: http://www.sagepub.com/journalsPermissions.nav
>> Version of Record - Feb 10, 2014 What is This?
Downloaded from apy.sagepub.com at UVI on May 11, 2014
510580
2014
APY22110.1177/1039856213510580Australasian PsychiatryO’Connor et al.
AP
Debate
Editor’s note: The following debate took place at the RANZCP Congress in Sydney in May 2013.
Australasian Psychiatry 2014, Vol 22(1) 7–9 © The Royal Australian and New Zealand College of Psychiatrists 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/1039856213510580 apy.sagepub.com
Debate: Clinical risk categorization is valuable in the prevention of suicide and severe violence? Yes
Nick O’Connor Clinical Director North Shore Ryde Mental Health Service, Northern Sydney Local Health District and; Senior Clinical Lecturer, Department of Psychological Medicine, University of Sydney, Sydney, NSW, Australia
John Allan Chief Psychiatrist New South Wales Ministry of Health, Sydney, NSW; Associate Professor, School of Psychiatry University of New South Wales, Sydney, NSW, Australia
Charles Scott Chief, Division of Psychiatry and the Law. Training Director, Forensic Psychiatry Fellowship, Professor of Clinical Psychiatry Department of Psychiatry and Behavioral Sciences University of California, Davis Medical Center, Sacramento, CA, USA
T
he essential element of clinical risk categorization is that the clinician formulates the person as being of high or low risk of a specific outcome: suicide or severe violence. Other forms of risk categorization may include specifiers of risk category: immediate, short-term or long-term risk, high or low levels of changeability and/or uncertainty. The assessment process is informed by corroborative sources and by the clinical team’s knowledge of the person over time, and anticipation of the conditions or scenarios that might make the adverse event more likely. Good risk management involves the person, his/her family and the Mental Health Service taking actions. Clinical risk categorization is a common-sense approach and a societal expectation. Risk categorization is an effective mode of clinical reasoning that reduces the chance of common diagnostic errors. Those who oppose risk categorization will try to confuse matters with rare event statistics, false positive and negative rates and ‘areas under curves’. While there has been no prospective research study of all the essential elements of clinical risk categorization, there is emerging, real-world evidence that risk categorization approaches have led to reductions of suicide rates and prevalence of severe violence incidents in high-risk groups.
Not about prediction Clinical risk assessment is not about prediction of whether a rare event will happen. It is not a crystal ball. However, clinical risk assessment will tell us who is in the ‘high stakes’1 category for serious adverse events.
Mullen:2 Critics of false positive rates in the prediction of dangerousness assume that dangerousness is not a probability but a quality only waiting the right moment to manifest. Good risk management is essentially a formulative, reflective and dynamic process. It marries the knowledge from empirical studies about risk factors with involvement of the person and their family. Further, good risk assessment involves a crucial element of reflective thinking about issues such as the quality of the engagement, uncertainties and changeability.3 Risk is by nature dynamic. Risk assessments and categorization require continual adjustment and revision as new information becomes available, or the clinical condition changes.
All clinicians use risk analysis Physicians, surgeons and psychiatrists make decisions which are informed by some sort of risk analysis every day. How else can we proceed in a world that is by its nature uncertain? Very often such consideration of risk remains a complex judgement in the mind of the clinician, with only the decision about the intervention documented. The introduction of semi-structured risk assessment protocols is an attempt to make this process Correspondence: Nick O’Connor, Clinical Director North Shore Ryde Mental Health Service, Northern Sydney Local Health District and Senior Clinical Lecturer, Department of Psychological Medicine, University of Sydney, Sydney, NSW 2065, Australia. Email: [email protected]
7 Downloaded from apy.sagepub.com at UVI on May 11, 2014
Australasian Psychiatry 22(1)
a considered and explicit exercise and one that can be communicated. The literature on incidents and medical error and the research literature on the way doctors think support a clinical risk categorization approach. Two-thirds of root causes of serious clinical incidents involved cognitive elements: we did not gather the relevant data optimally or we failed to correctly synthesize the available data. Knowledge deficits per se are unusual in experienced clinicians.4 Clinical risk categorization improves the likelihood of a safe patient outcome by structuring the data gathering, inquiry process and ‘disposition decision making’.
The problem of false positives Those who criticize clinical risk assessment have elegantly modelled the sensitivity and specificity of predicting rare events such as homicide or suicide. Large points out that 35,000 patients would need to be detained in order to prevent one person with schizophrenia murdering a stranger.5 It has long been known that psychiatrists cannot predict suicide.6,7 These arguments are not new.2 We contend they are the wrong arguments. Clinical risk management is not about prediction but prevention. It is about mitigating the conditions under which a disaster may occur. Actuarial difficulties in relation to prediction as to whether an event will actually occur are peripheral. Who would not place in involuntary care a person who has been threatening people in the street with serious aggression because he believes they are monitoring, controlling and poisoning him – even though actuarially the chance of this man killing a stranger is extremely remote? We share concerns that clinical risk categorization not become a ‘tick box’ approach that ‘dumbs down’ clinical formulation. Risk categorization frameworks that have been mandated in a number of jurisdictions have unfortunately confused risk assessment proformas with the complex and reflective process of risk formulation and management. Risk categorization reflects a current societal paradigm that even the average man in the street expects to see applied in a range of social service contracts; most importantly in the clinical decision making of cardiologists, surgeons, oncologists and psychiatrists.
Risk categorization in the real world It is disingenuous for clinicians to say that they can abandon all consideration of risk by invoking ‘universal precautions’ and ‘good clinical practice’. In the real world we do concentrate our efforts on those people with high need. In a study across England and Wales looking at suicide rates 1997–2006 before and after the implementation of nine of the 12 evidence-based interventions services could make to change the suicide rate, the more of these changes that services implemented the lower the suicide
rate.8 Recommendations which had the greatest positive effect included introducing a 24-hour crisis service, introducing policies on patients with dual diagnoses, and multidisciplinary review after suicide. The number of recommendations implemented increased from 0.3% per service in 1998 to 7.2 per service in 2006. There were significant falls of up to 20% in the suicide rate for the catchment areas served by these services, but if services did not implement the recommendations there was little reduction. One of the recommendations made by the Inquiry but not measured in this study was that all patients with severe mental illness and a history of self-harm or violence receive the most intensive level of care.9 These are the patients that structured risk assessments would rate as high risk and whom therefore would have received the most intensive treatment. The researchers felt this was so self-evident it would not be a discriminating factor between services. Those patients, who through proper risk assessment, identification and categorization combined with a range of targeted clinical activity to change that risk, had better outcomes. Also, the biggest change in suicide rates were in services with the most deprived catchment areas and the most patients, making it likely their resources were thinly spread. So targeting based on risk makes sense. This study will never be included in a meta-analysis because it involves too many real-world assumptions. Similarly in New South Wales, the Tracking Tragedy Report into inpatient suicides in 200310 noted the lack of standardization of suicide risk assessment and poor protocols based on risk. Structured risk assessment via the Mental Health Outcomes and Assessment Tools was introduced with clear implementation protocols. Over a series of reports in 200811 and 2011,12 it appears that the inpatient suicide rate has halved (unpublished data). Much of this is correctly attributed to efforts in improving observation, decreasing physical risk and eliminating hanging points, but it is also an endorsement of categorizing risk. McDermott et al.13 presented the results of their study that examined the use of the Classification of Violence Risk (COVR) in identifying forensic patients at high or very high risk of aggression. If the COVR successfully identified groups at higher risk of violence and interventions were implemented to address those higher risk patients, then the relationship of COVR scores (i.e. higher risk groups) to subsequent aggression should decrease over time. In this study, 328 patients were administered the COVR and followed for incidents of hospital aggression over a 20-week period. The rate of aggression for those identified at higher risk decreased from 67% to 24% after the COVR was implemented. The researchers concluded that the identification of groups of high risk of aggression resulted in focused treatment for these groups, which resulted in a significant reduction in aggressive acts. The biggest danger is the call to abandon risk assessments because there is no evidence that they are predictive.
8 Downloaded from apy.sagepub.com at UVI on May 11, 2014
O’Connor et al.
In the real world this oversimplification sends a dangerous message. It is tantamount a call to abandon patient safety. We do not use risk categories like a bookmaker to assess the outcome and hedge our bets accordingly; we use them to rig the race in our favour, interfering with the outcome, guiding our efforts and combining them with our clinical acumen.
The problem with Large et al.’s meta-analyses Meta-analyses are a valuable tool to assist clinicians for evidence-based decision making. When choosing which studies to include in a meta-analysis, the researcher must develop inclusion criteria relevant to the research question being addressed. Including even one study that incorporates data that is not in line with the proposed hypothesis can introduce bias into the ultimate findings, even with the most elegant mathematical analyses.14 Large et al.15 cite their meta-analysis of seven studies of inpatient suicides to conclude that depressed mood and a prior history of self-harm are the only well-established independent risk factors for inpatient suicide, and the use of these risk factors would prevent few, if any suicides. Perhaps the authors’ conclusions are correct and other reported risk factors, including active suicidal thoughts, are not clinically meaningful risk factors associated with psychiatric inpatient suicides. However, are the studies included in their meta-analysis truly representative of inpatient suicides? Careful examination of the seven studies used in their meta-analysis of ‘inpatient suicides’ reveal a number of concerns. First, some of the studies included suicides that were not actually classified as suicides. For example, in the study by Powell et al.,16 47% of the men and 46% of the women classified as having committed suicide were ‘open verdicts’, meaning that their death had not been officially determined by the coroner as a suicide. Second, the length of psychiatric inpatient hospitalization of included studies does not represent current acute inpatient psychiatric lengths of stay, and calls into question the applicability to modern practice. To illustrate, in the Hunt et al. study,17 the authors note that the maximum length of admission prior to suicide of included subjects was 436 weeks (over 8 years). Third, many of the studies relied on archival data in case notes. Acknowledging this substantial limitation to their study, Powell et al.16 note, “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 (p. 268).” As a result of their findings from this meta-analysis, Large et al.15 suggest that any type of risk assessment that categorizes patients into high-and low-risk groups should not be included in decision making. The studies included
in their meta-analysis make such assertions premature. We do agree, however, with their conclusion, which reads, “Rational risk management for inpatient suicide involves the careful attention to the safety of hospital environments, the optimal care of each patient’s illness and appropriate responses to each patient’s circumstances.” (p. 512). After all is said and done, isn’t paying careful attention to ‘patient’s circumstances’ just another way of making sure you address the patient’s risks? Disclosure The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.
References 1. O’Connor N. The wrong lessons. Australas Psychiatry 2013; 21: 178. 2. Mullen P. Mental disorder and dangerousness. Aust N Z J Psychiatry 1984; 18: 8–17. 3. O’Connor N, Warby M, Rahael B, et al. Changeability, confidence, common sense and corroboration: comprehensive suicide risk assessment. Australas Psychiatry 2004; 12: 352–360. 4. Graber ML. Educational strategies to reduce diagnostic error: Can you teach this stuff? Adv Health Sci Educ 2009; 14: 63–69. 5. Large M. Does the emphasis on risk in psychiatry serve the interests of patients or the public? No. BMJ [serial on the Internet]. 2013; 346. 6. Pokorny AD. Prediction of suicide in psychiatric patients: A prospective study. Arch Gen Psychiatry 1983; 45: 249–257. 7. Goldstein RB, Black DW, Nasrallah MA, et al. The prediction of suicide. Arch Gen Psychiatry 1991; 48: 418–422. 8. While D, Bickley H, Roscoe A, et al. Implementation of mental health service recommendations in England and Wales and suicide rates, 1997–2006: A cross-sectional and before-and-after observational study. Lancet 2012; 379: 1005–1012. 9. Appleby L, Shaw J, Sherratt J, et al. Safety First. Report of the National Confidential Inquiry into Suicide and Homicide by People with Mental Illness. Manchester UK: British Document Supply Centre, 2001. 10. NSW Mental Health Sentinel Events Review Committee. Tracking Tragedy. A systemic look at suicides and homicides amongst mental health inpatients. Sydney, Australia: NSW Health, http://www0.health.nsw.gov.au/pubs/2003/pdf/serc.pdf 2003 (accessed 21 October 2013). 11. Committee NSER. Tracking Tragedy: A systemic look at homicide and non-fatal serious injury by mental health patients, and suicide death of mental health inpatients. Fourth Report of the Committee. Sydney, Australia: NSW Health, http://www0.health.nsw. gov.au/pubs/2009/pdf/tracking_tragedy_2008_fourth_report.PDF 2008 (accessed 21 October 2013). 12. Commission CE. Clinical Focus Report from Review of RCAs and/or IIMS Data on Inpatient Suicide and Self-Harm Sydney, Australia: Clinical Excellence Commission, 2011. 13. McDermott B, Dualan I, et al. The use of the COVR to identify and treat violence risk in a forensic hospital setting. Tuscon, Arizona: American Academy of Psychiatry and the Law Annual Meeting; 2010. 14. Field AP and Gillet R. Expert tutorial. How to do a meta-analysis. Br J Math Stat Psychol 2010; 63: 665–694. 15. Large M, Ryan C and Nielssen O. The validity and utility of risk assessment for inpatient suicide. Australas Psychiatry 2011; 19: 507–512. 16. Powell J, Geddes J, Deeks J, et al. Suicide in psychiatric hospital in-patients. Br J Psychiatry 2000; 176: 266–272. 17. Hunt IM, Kapur N, Webb R, et al. Suicide in current psychiatric in-patients: A casecontrol study. The National Confidential Inquiry into Suicide and Homicide. Psychol Med 2007; 37: 831–837.
9 Downloaded from apy.sagepub.com at UVI on May 11, 2014
