Clinically useful predictors for premature mortality among psychiatric patients visiting a psychiatric emergency room

Abstract

Objective:

The aim of this study was to examine changes in the distribution of causes of death and mortality rates among psychiatric patients visiting a psychiatric emergency room (PER), to determine clinically useful predictors for avoiding premature mortality among these patients and to discuss possible interventions.

Method:

The study was designed as a historical prospective record linkage study of patients with at least one visit to a Danish PER in 1995–2007. Five consecutive 3-year cohorts of individuals aged 20 to <80 years were identified. Data from the Danish Civil Registration System were linked to the Cause of Death Register and the Central Psychiatric Research Register, and logistic predictor analyses for premature death were performed.

Results:

The standardised mortality ratio (SMR) of all visitors compared to the general Danish population was approximately 5. Overall, patients with drug and/or alcohol use disorder experienced at least a twofold increase in SMR compared to patients without substance use disorder. In the case of patients with schizophrenia and a concurrent substance use disorder, the SMR increased considerably. During the period, substance use disorder was the strongest predictor of premature death among visitors to a PER (odds ratio (OR) = 1.8; 95% confidence interval (CI) = 1.5, 2.2).

Conclusion:

Persons visiting the PER had an increased SMR and substance use disorders were the strongest predictor of premature death within 3 years. However, death caused by substance use disorder is preventable, and PERs are ideal points of early intervention. Systematic screening for substance use disorder at the PER and/or crisis intervention teams may be effective intervention strategies.

Keywords

Alcohol-induced disorders dual diagnosis (psychiatry)psychiatric emergency services mortality substance-related disorders

Introduction

Persons affected by psychiatric disorders have a greatly increased risk of premature death compared to the general population. The highest risk of premature mortality is for substance abuse and organic mental disorders (Harris & Barraclough, 1998; Hiroeh et al., 2008; Wahlbeck et al., 2011). Large, often national, registry studies have identified increased mortality rates for specific diagnostic categories, such as major psychiatric disorders (Laursen et al., 2007), schizophrenia (Brown, 1997; Crump, Winkleby, et al., 2013), bipolar disorder (Crump, Sundquist, et al., 2013; Miller & Bauer, 2014) and substance use disorder (Innamorati et al., 2013; Nyhlen et al., 2011; Westman et al., 2014). However, studies of different groups of mental health service users have also indicated increased mortality rates, such as hospitalised patients (Hamer et al., 2008; Sohlman & Lehtinen, 1999), long-stay patients (Räsänen et al., 2003, 2005), patients in community care (Grigoletti et al., 2009), involuntarily admitted patients (Crisanti & Love, 1999) or patients visiting acute hospital wards (Honkonen et al., 2008).

The excess mortality among psychiatric patients is partly explained by increased somatic morbidity. More unhealthy lifestyles, including substance abuse (Hjorthøj et al., 2015), and adverse effects of certain psychotropic medication, especially antipsychotics, hypnotics and/or sedatives (De Hert et al., 2011; Lahti et al., 2012; Tiihonen et al., 2012), may result in metabolic syndrome (Casey, 2005; Grundy et al., 2004; Kølbæk et al., 2014) and cardiovascular disease (Kilbourne et al., 2009; Laursen et al., 2009). Persons affected by psychiatric disorder have more severe somatic disorders, but there is an insufficient awareness of the somatic/medical morbidity in the health-care system, and these patients receive less intensive treatment, which leads to increased morbidity and excess mortality rates (Frasch et al., 2013; Laursen et al., 2009, 2014).

Suicide is the largest single unnatural cause of excess mortality among persons affected by psychiatric disorder (Brown, 1997; Crump, Sundquist, et al., 2013; Crump, Winkleby, et al., 2013; Harris & Barraclough, 1998); however, variations in the reported levels of risk most probably depend on study designs and sampling strategies.

The psychiatric emergency services have undergone extensive changes following a significant downsizing of the number of psychiatric hospital beds during the past decades (Brown, 2005). To our knowledge, no studies have examined mortality rates of visitors at psychiatric emergency rooms (PERs). PERs are ideal points of early intervention, but the burden on the PERs has increased because of increasing substance abuse and overuse by a relatively small group of frequent visitors (Aagaard et al., 2014; Chaput & Lebel, 2007). Causes of death and mortality rates are useful indicators of the effectiveness of social policy and health service provision in these burdened health-care settings. Studies of psychiatric patients’ risk of premature death are typically based on long periods of follow-up. We hypothesise that a study based on shorter follow-up periods will allow the identification of predictors of premature death that are more relevant for planning clinical intervention in PERs.

Aims of the study

The aims of the study were to examine causes of death and mortality rates among psychiatric patients visiting a Danish PER from 1995 to 2007, to determine clinically useful predictors for premature mortality among these patients and to discuss possible interventions.

Materials and methods

Setting

The PER at Aarhus University Hospital, Risskov, Denmark, has open access 24 hours/day. A total of 10 beds are available for short-term stays of maximum 2 days. Most visitors are resident in the Eastern part of Central Denmark Region, and it is the only PER in this area. The Danish health-care system is a public health-care system financed by means of general taxes.

During the data collection period, a significant reduction in psychiatric beds took place and the severity of illness among the hospitalised increased (van Hoof et al., 2011). Furthermore, an increase in outpatient services, including community psychiatry, occurred. These organisational changes meant that the PER experienced an increased gate-keeping function of controlling and filtering patients to hospitalisation, outpatient clinics or general practitioners (GPs) through assessment and referral procedures.

In 2007, the number of visits to the PER increased to 5,970 from 2,304 in 1995. About two-thirds of all visits were self-referrals and about one-third of all visits led to a hospital admission (Bartels & Andersen, 2008). The vast majority of the inhabitants in Aarhus Municipality are Caucasian. Compared to the Danish population in general, Aarhus has not only a relatively high proportion of persons in the lower wage categories but also a relatively high proportion of highly educated persons. This is probably related to the fact that Aarhus is a university city (van Hoof et al., 2011). The average distance to Aarhus University Hospital, Risskov, for patients residing outside Aarhus Municipality, but within Eastern Central Region Denmark, is 15 km.

In the case of drug-related psychosis, affective disorder, anxiety or other secondary psychiatric conditions demanding acute intervention, patients with drug use disorder can be admitted to one of the 10 beds at the PER. If the alcohol use disorder is complicated by delirium (International Classification of Diseases, 10th Edition (ICD-10), F10.4) or by alcohol-related psychotic disorders (ICD-10, F10.5), the patient is usually transferred to an inpatient ward at the university hospital.

Register data

The following data were obtained from national registers including the Danish Psychiatric Central Research Register (Mors et al., 2011): visits to the PER in 1995–2007 including 3 years of follow-up, types of admission, outpatient services, diagnoses (ICD-10; World Health Organization (WHO), 1993), departed from the register, sheltered housing with 24-hour support and, if any, date of death and cause of death (Juel & Helweg-Larsen, 1999; Sundhedsstyrelsen, 2011).

Cause of death was classified in the following ICD-10 diagnostic groups: (1) Cardiovascular (I), (2) Cancer (C–D48), (3) Respiratory (J), (4) Endocrine (E), (5) Digestive (K), (6) Natural death, others (A, B, D50–99, F, G, H, L–R), (7) Suicide (X60–84) and (8) Unnatural death, others (V01–X59, Y00–99).

Severe mental illness (SMI) is an Assertive Community Treatment (ACT) target group (Aagaard & Kølbæk, 2015; Aagaard & Muller-Nielsen, 2011) defined as follows: during the last 2 years having had as primary diagnosis ICD-10: F20, F22, F25 or F30–31; at least four admissions or 50 inpatient days; or secondary diagnosis within ICD-10: F10–19.9 or Z04.6.

The diagnostic data in the Psychiatric Central Research Register are routinely validated against the diagnosis in the discharge letter. The diagnostic data in the Cause of Death Register are validated against the death certificate. These data are delayed for at least 3 years.

Sample

Five cohorts were defined from the register data including individuals aged 20 to <80 years, residing in the Eastern part of Central Denmark Region (previously named Aarhus County), having had at least one visit to the PER in 1995, 1998, 2001, 2004 or 2007, respectively. Each of the five cohorts was followed for 3 years and analysed for predictors of outcome. The outcome measure was death within 3 years in each of the five cohorts. The relatively short 3-year follow-up period was defined in order to identify predictors relevant for designing clinical intervention.

The cohorts were defined based on the Psychiatric Central Research Register and the Civil Registration System (Pedersen et al., 2006). The five cohorts included 1,103–2,700 cases, of which 74–163 had died and 3–19 had departed. Departed means that these persons were withdrawn from the register, for example, because of immigration. All the departed cases were excluded from analyses; see exact counts in Tables 1 and 5.

Table 1.

Socio-demographic, diagnostic and service use data for individuals with at least one visit to PER, Aarhus University Hospital (AUH), Risskov, during the years 1995 (n = 1,100), 1998 (n = 1,695), 2001 (n = 2,327), 2004 (n = 2,756) and 2007 (n = 2,525), aged 20 to <80 years and resident in the Eastern part of Central Denmark Region, previously named Aarhus County.

	1995		1998		2001		2004		2007
	n	%	n	%	n	%	n	%	n	%
Sex
Men	578	52.5	817	48.2	1,173	50.4	1,361	49.4	1,275	50.5
Age group (years)
20–34	379	34.5	581	34.3	857	36.8	934	33.9	938	37.1
35–54	555	50.5	866	51.1	1,115	47.9	1,363	49.5	1,129	44.7
55–79	166	15.1	248	14.6	355	15.3	459	16.7	458	18.1
Address
Sheltered housing^a	30	2.7	48	2.8	69	3.0	75	2.7	77	3.0
Primary diagnosis^b
F20	188	17.1	341	20.1	318	13.6	362	13.1	368	14.6
F2-residual	85	7.7	137	8.1	168	7.2	146	5.3	130	5.1
F30–31	109	9.9	201	11.9	196	8.4	228	8.3	193	7.6
F3-residual	169	15.4	333	19.6	476	20.5	566	20.5	576	22.8
F4 + F6	208	18.9	269	15.9	528	22.7	628	22.8	507	20.1
F-residual	341	31.0	414	24.4	641	27.5	826	30.0	751	29.7
Other diagnosis^c
F10	314	28.5	417	24.6	613	26.3	736	26.7	623	24.7
F1-residual	83	7.5	106	6.3	157	6.7	210	7.6	205	8.1
Z04.6	16	1.5	49	2.9	81	3.5	151	5.5	184	7.3
Status 31.12.x
SMI^d	228	20.7	465	27.4	457	19.6	476	17.3	456	18.1
Not attached	684	62.2	936	55.2	1,478	63.5	1,799	65.3	1,708	67.6
During the year
Involuntary admissions
Forensic	8	0.7	5	0.3	15	0.6	19	0.7	30	1.2
Involuntary	41	3.7	40	2.4	39	1.7	85	3.1	99	3.9
Heavy use
PER^e	73	6.6	107	6.3	175	7.5	228	8.3	187	7.4
Hospital^f	273	24.8	490	28.9	549	23.6	553	20.1	467	18.5

PER: psychiatric emergency room; SMI: severe mental illness.

With 24-hour support.

Primary diagnosis at last contact in the year. F20 Schizophrenia; rest of F2 chapter; F30–31 Bipolar disorder; rest of F3 chapter; F4 + F6 Anxiety or personality disorder; rest of F chapters, except F1.

Substance use disorder (F1) or Forensic diagnosis (Z04.6). The last substance use disorder diagnosis in the year is classified as F10: Alcohol use disorder or F1-residual: Drug use disorder.

SMI. During at least 2 years of primary diagnosis as F20, F22, F25 or F30–31 and at least four admissions or 50 inpatient days or secondary diagnosis as F1 or Z04.6.

PER ⩾ 5 visits during the year.

⩾3 admissions or ⩾60 bed days during the year.

The selection of data was based on a hypothesis regarding possible predictors of death within the 3 years of follow-up. These predictors had been identified in the literature (see the ‘Introduction’ section). Predictors included the following: (1) sex; (2) age; (3) sheltered housing; (4) the primary diagnosis at last contact before the index date, each cohort commenced: ICD-10, F20 Schizophrenia, the rest of the F2 chapter, F30–31 Bipolar, the rest of the F3 chapter, F4–6 Anxiety or personality disorder, all remaining F chapters, except chapter F1; (5) ICD-10, F10–19 Substance use disorder as primary or secondary diagnosis at least once during the previous year, at the last contact during the year classified as F10 Alcohol use disorder or as the rest of the F1 Drug use disorder chapter, including F19 Mixed substance use disorder; (6) ICD-10: Z04.6 Forensic psychiatric diagnosis as primary or secondary diagnosis at least once during the previous year; (7) SMI on 31.12 the year before each cohort commenced; (8) not using psychiatric services on 31.12; (9) admission status on 31.12 the year before each cohort commenced; (10) involuntary admission types in previous year; and (11) consumption variables in previous year: heavy use of PER (⩾5 visits during the year), heavy use of the hospital (⩾3 admissions or ⩾60 bed days during the year).

All patients with substance use disorder, who had a diagnosis of F10 Alcohol use disorder or of F1-residual Drug use disorder at the index visit to PER, were examined in the nationwide Psychiatric Central Research Register for previous substance use diagnosis. Regarding patients with substance use disorder (F1) at the index visit, if the index diagnosis was F10, then 92%–95% of all previous substance use diagnoses were F10, and if the index diagnosis was in the rest of the F1 chapter, then 71%–77% of all previous substance use diagnoses were in the rest of the F1 chapter.

Statistical analyses

Analyses were carried out using the software package Stata 11.2 (StataCorp, 2009) and with a nominal significance level of 5%. Using stepwise forward inclusion followed by backward elimination, the statistically most important combination of dichotomous predictors was found by logistic regression. Exploratory logistic regressions were also carried out within cohorts to explore differences in prediction models over the years. Changes of predictor distributions over the years (i.e. trends over cohorts) were investigated with an age corrected logistic regression taking the predictor of interest as response and cohort as explanatory variable. Sandwich estimator of variances was applied to account for interpersonal correlation from patients entering multiple cohorts.

Standardised mortality ratios (SMRs) with 95% confidence intervals (CIs) were calculated by indirect standardisation of 3-year mortality rates, using sex and age specifically, observed in the corresponding Danish population (http://statistikbanken.dk).

Results

As shown in Table 1, the number of individuals with at least one visit to the PER increased from 1,100 in 1995 to 2,525 in 2007, an increase of 130%. In 1995, 6.6% of visitors had heavy use of PER, and in 2007 this figure was 7.4%. The gender and age distribution did not change during the period.

Patients living in sheltered housing used the emergency room more frequently, from 30 patients in 1995 to 77 in 2007. The number of people living in sheltered housing did not increase in this period (Aagaard et al., 2008).

The percentage of visitors who were diagnosed F20 Schizophrenia, the rest of the F2 chapter or F30–31 Bipolar had a significant (p < .001) declining trend, but the percentage of other affective states, the rest of the F3 chapter, increased significantly (p < .001). The proportion of F4 + F6 Anxiety or personality disorders also increased significantly (p < .01). There was no significant change in the proportion of visitors with alcohol use (F10) nor change in proportion of visitors with drug use disorder (the rest of the F1 chapter),

but there was a large and significant (p < .001) increase in the number of patients having a Z04.6 Forensic diagnosis, from 16 patients in 1995 to 184 in 2007. Throughout the period, the number of patients assigned a forensic arrangement in Denmark increased by approximately 6% per year (Kramp & Gabrielsen, 2009).

Patients with SMI showed some fluctuation in frequency of contact to the PER from 1995 to 2007. The prevalence of SMI in this period did not increase in the catchment area (Aagaard et al., 2008). Patients with a forensic arrangement can, according to legislation, be admitted to a psychiatric hospital voluntarily or involuntarily, and the number of those involuntarily admitted increased from 8 in 1995 to 30 in 2007, that is, this increase was not comparable to the total increase in the number of patients with a forensic arrangement (Z04.6). Involuntary admissions for non-forensic patients had the same low number throughout the whole period, corresponding to the general figures in Denmark including the Central Denmark Region, where a maximum 5% of all admissions are involuntary (Aagaard et al., 2008).

Table 2 shows causes of death less than 3 years after a visit to the PER for each of the five cohorts. The percentages of deaths show a decline from 6.7% in the first cohort to 5.4% in the last cohort.

Table 2.

Cause of death in 3 years for each of the five cohorts of individuals with at least one visit to PER, Aarhus University Hospital (AUH), Risskov, during the years 1995, 1998, 2001, 2004 or 2007 aged 20 to <80 years and resident in the Eastern part of Central Denmark Region, previously named Aarhus County.

Cause of death	1995		1998		2001		2004		2007
	n	%	n	%	n	%	n	%	n	%
Cardiovascular^a	12	16.2	16	15.1	18	14.5	23	14.1	17	12.6
Cancer^b	6	8.1	11	10.4	13	10.5	24	14.7	11	8.1
Respiratory^c	4	5.4	4	3.8	7	5.6	10	6.1	11	8.1
Endocrine^d	0	0	3	2.8	1	0.8	8	4.9	9	6.7
Digestive^e	6	8.1	12	11.3	16	12.9	23	14.1	8	5.9
Natural death, others^f	14	18.9	27	25.5	27	21.8	31	19	36	26.7
Suicide^g	14	18.9	16	15.1	22	17.7	20	12.3	19	14.1
Unnatural death, others^h	17	23.0	17	16	20	16.1	24	14.7	20	14.8
Missing	1	1.4	0	0.0	0	0.0	0	0.0	4	3.0
Death in each cohort	74	100	106	100	124	100	163	100	135	100
Death %	6.73		6.25		5.33		5.91		5.35

PER: psychiatric emergency room.

Classifications of diseases and causes of death, National Board of Health (International Classification of Diseases, 10th Edition (ICD-10)): (a) I; (b) C–D48; (c) J; (d) E; (e) K; (f) A, B, D50–99, F, G, H and L–R; (g) X60–84; (h) V01–X59 and Y00–99.

In each of the cohorts, approximately 15% of deaths had a cardiovascular cause. Death from cancer was less frequent in the first part of the period, but increased during the period to the same level as cardiovascular death. Respiratory, endocrine or digestive causes of death

were not frequent, but there were an increasing proportion of deaths due to digestive disorders. The proportion of patients committing suicide or dying other unnatural deaths was relatively high, but with a decline during the period. Patients with substance use more frequently had their cause of death labelled as ‘digestive’ or ‘unnatural death, others’ than patients without substance use (data not shown).

Table 3 shows an age-adjusted logistic regression of significant dichotomous predictors of death the following 3 years for each of the five cohorts. Only predictors with at least one independent significant effect – positive or negative – in at least one cohort are tabulated.

Table 3.

Age adjusted logistic regression analyses of significant dichotomous predictors for death in 3 years for each of five cohorts of individuals with at least one visit to PER, Aarhus University Hospital (AUH), Risskov, during the years 1995, 1998, 2001, 2004 or 2007 aged 20 to <80 years and resident in the Eastern part of Central Denmark Region, previously named Aarhus County.

Predictor	1995		1998		2001		2004		2007
	OR (95% CI)	p-values	OR (95% CI)	p-values	OR (95% CI)	p-values	OR (95% CI)	p-values	OR (95% CI)	p-values
Men	1.9 (1.2, 3.2)	.008			1.7 (1.2, 2.5)	.003	1.8 (1.3, 2.6)	<.001	1.5 (1.0, 2.1)	.031
F20^a			0.5 (0.3, 1.0)	.034	1.9 (1.2, 3.1)	.017
F30–31^b							0.4 (0.2, 0.9)	.012
F3-residual^c			0.5 (0.3, 0.8)	.005			0.5 (0.3, 0.8)	<.001	0.3 (0.2, 0.5)	<.001
F4 + F6^d					0.3 (0.2, 0.7)	<.001
F1^e			2.5 (1.7, 3.8)	<.001	2.2 (1.5, 3.1)	<.001	2.4 (1.7, 3.3)	<.001	2.6 (1.8, 3.7)	<.001
Z04.6^f							2.1 (1.1, 3.9)	.034	2.8 (1.6, 4.7)	<.001
SMI^g					1.7 (1.1, 2.6)	.014
PER^h			2.1 (1.1, 4.0)	.049	1.9 (1.1, 3.4)	.040
Hospitalⁱ					1.7 (1.2, 2.6)	.009

PER: psychiatric emergency room; OR: odds ratio; CI: confidence interval; SMI: severe mental illness.

Schizophrenia.

Bipolar disorder.

Affective disorder other than Bipolar disorder.

Anxiety or Personality disorder.

Substance use disorder.

Forensic diagnosis.

SMI. During at least 2 years of primary diagnosis as F20, F22, F25 or F30–31 and at least four admissions or 50 inpatient days or secondary diagnosis as F1 or Z04.6.

PER ⩾ 5 visits during the year.

⩾3 admissions or ⩾60 bed days during the year.

The mean age at each index date, was compared between those that died during the 3-year follow-up period, and those still alive: 1995 cohort death M = 49.3 (standard deviation (SD) = 14.5) and still alive M = 41.0 (SD = 12.1); 1998 cohort death M = 48.5 (SD = 13.9) and still alive M = 41.0 (SD = 12.5); 2001 cohort death M = 49.5 (SD = 13.1) and still alive M = 41.1 (SD = 13.0); 2004 cohort death M = 51.6 (SD = 12.7) and still alive M = 40.5 (SD = 13.1); 2007 cohort death M = 50.3 (SD = 13.5) and still alive M = 40.4 (SD = 13.4). In each of the cohorts, the age at index date was significantly higher for those dying during follow-up than those still alive after 3 years (p < .001).

Table 4 shows a logistic regression analysis, where patients from the five cohorts are seen as a whole, and where both positive and negative statistically significant predictors of death are incorporated into the model. Higher age gives the dominant prediction of death, than substance use, male gender, forensic diagnoses and high hospital usage. The effect of age is here shown in terms of a 5-year difference. Affective disorder other than Bipolar disorders and Anxiety or Personality disorder had a diminishing effect in the model.

Table 4.

Logistic regression analyses for significant predictors of death within 3 years.

	OR	95% CI	p-values
Age (per 5 years)	1.3	1.3–1.4	<.001
F1^a	1.8	1.5–2.2	<.001
F3-residual^b	0.6	0.4–0.7	<.001
F4 + F6^c	0.6	0.5–0.9	.002
Men	1.3	1.1–1.6	.002
Z04.6^d	1.5	1.0–2.1	.030
Hospital^e	1.2	1.0–1.5	.033

OR: odds ratio; CI: confidence interval.

The sample consisted of all patients in the five cohorts aged 20 to <80 years and resident in the Eastern part of Central Denmark Region, previously named Aarhus County. Sandwich estimator of variances was used to adjust for the correlation induced by persons entering multiple cohorts.

Substance use disorder.

Affective disorders other than Bipolar disorders.

Anxiety or Personality disorder.

Forensic diagnosis.

⩾3 admissions or ⩾60 bed days during the year.

Table 5 shows SMR for 3 years’ mortality in all patients from each of the five cohorts, for the subgroup of patients with substance use and for the subgroup of patients with coinciding schizophrenia and substance use. As only the number of deceased patients is tabulated, the exact figures for schizophrenia and substance use are stated in the text.

Table 5.

Standardised mortality ratios (SMRs) for 3 years of mortality in each of the five cohorts of individuals with at least one visit to PER, Aarhus University Hospital (AUH), Risskov, during the years 1995, 1998, 2001, 2004 or 2007 aged 20 to <80 years and resident in the Eastern part of Central Denmark Region, previously named Aarhus County.

Cohorts	All patients			Patients with substance use			Schizophrenia and substance use
	Deaths	SMR	95% CI	Deaths	SMR	95% CI	Deaths	SMR	95% CI
1995	74	4.5	3.6–5.8	28	6.4	4.4–9.3	3	15.3	4.9–47.4
1998	106	5.0	4.2–6.1	51	10.1	7.7–13.3	4	11.5	4.3–30.7
2001	124	4.4	3.7–5.2	63	6.7	5.3–8.6	7	16.2	7.7–34.0
2004	163	5.2	4.5–6.1	92	7.8	6.3–9.5	6	12.6	5.7–28.1
2007	135	5.00	4.2–5.9	77	7.9	6.3–9.8	9	18.0	9.4–34.7

PER: psychiatric emergency room; CI: confidence interval.

SMR calculated for all visitors and for the subgroup of patients with substance use disorder as primary or secondary diagnosis and for the subgroup of patients with schizophrenia as primary diagnosis and abuse as secondary diagnosis.

In the 1995 cohort, 188 had a primary diagnosis of schizophrenia, of which 10 died and 3 had substance use. In the 1998 cohort, 341 had schizophrenia, of which 11 died and 4 had substance use. In the 2001 cohort, 318 had schizophrenia, of which 22 died and 7 had substance use. In the 2004 cohort, 362 had schizophrenia, of which 17 died and 6 had substance use. In the 2007 cohort, 368 had schizophrenia, of which 19 died and 9 had substance use.

SMR for all visitors in the PER was around 5 in each of the cohorts. Substance use as a primary or secondary diagnosis, which about one-third of the patients had, increased SMR in each of the cohorts, but if substance abuse coincided with schizophrenia the SMR increase was even larger.

Discussion

This study is among the first to examine cause of death and mortality rates among users of PER. It confirms earlier findings that compared to the general population, psychiatric disorder is associated with remarkably high mortality, and that substance use disorders, with or without a mental illness (dual diagnosis), increase SMRs significantly (Harris & Barraclough, 1998; Hiroeh et al., 2008; Honkonen et al., 2008; Wahlbeck et al., 2011). PERs are ideal points of early intervention, and the identification of predictors of premature death within 3 years is highly relevant for designing clinical interventions.

An explanation for the increased mortality rates discovered in Denmark, but also in other European countries for this risk group, might be insufficient awareness of the somatic/medical morbidity in psychiatric patients (Frasch et al., 2013; Laursen et al., 2009, 2014). This seems especially to affect patients with substance use disorders, and patients with substance use disorders co-occurring with an SMI, such as schizophrenia (Hiroeh et al., 2008; Hjorthøj et al., 2015). Increased awareness of medical morbidity in this risk group must be ensured, as well as securing continuity in treatment for this group after a visit to the PER.

A key challenge is to identify this group of patients in the PER (Hansen et al., 2000). Among patients with psychotic illness, only 20% of the substance use disorder patients self-reported substance use (Claassen et al., 1997). Frasch et al. (2013) recommended early detection of substance use disorder and that integration of substance use disorder patients into programmes targeting physical comorbidity should be a priority in organising mental health care. Cherpitel and Ye (2008) concluded that patients with drug use are overrepresented in emergency room settings due to health problems associated with their drug use, and suggest that the PER is a window of opportunity to screen these patients for medical disorders, and to offer treatment to prevent risk of death.

However, an obstacle to offering psychiatric patients with substance use screening for medical disorders and follow-up to decrease mortality is the insufficient screening procedure in the PER (Hansen et al., 2000), despite the fact that valid instruments exist for this purpose (Aalto et al., 2006). A screening for substance use in the PER will enable physicians to identify the risk group of substance users and psychiatric patients with a dual diagnosis problem in order to address the increased risk of somatic illness and death. An effort to strengthen the screening and identification of substance use problems in primary practice would further enable a preventive effort concerning the medical health of this group of risk patients.

The study has some limitations that need to be considered. First, we have examined users of PER in a specific Danish context and, therefore, the results cannot be generalised to users of other mental health-care settings. Second, the decision to divide the dataset into five cohorts with 3 years of follow-up allowed an examination of trends throughout the period, and other divisions of the dataset would allow other relevant analyses. Third, number of deaths from specific causes is too small in some cohorts for reliable assessment of trends over time. Fourth, data were register-based clinical data, which could be considered less valid than research-based data because local categorisation practices vary. However, the Danish personal identification number allows unique linkage between registers (Munk-Jorgensen & Ostergaard, 2011), and several validation studies of the Danish Psychiatric Central Research Register have been carried out with good results (Mors et al., 2011; Uggerby et al., 2013). For example, Uggerby et al. (2013) tested the validity of the schizophrenia diagnosis (ICD-10 codes F20.0–20.3 and F20.9) in the Danish Psychiatric Central Research Register. This was done by comparing register diagnoses against diagnoses from a review of case records and the study concluded that the validity of the schizophrenia diagnosis was 89.7%.

Clinical implications

Padwa et al. (2012) advocated integration of substance use disorder services with primary care to improve access to substance use disorder treatment. Mueser & Gingerich (2013) and Drake et al. (2007) advocated special service options (integrated treatment) for psychiatric patients with substance use in order to help them use health services appropriately. In Denmark, patients with substance use disorders have usually been treated in social settings and by social workers. The availability of or access to medical treatment by a GP in Denmark is usually high, but cooperation between social treatment settings (addiction services) and GPs in the study area is not extensive

Improved communication between the PER and the GP concerning identification of substance use problems enabling patients’ somatic problems to be evaluated will also be of importance concerning this preventive effort. Our first suggestion for patients with substance use disorder visiting the PER is to elaborate a complex, coordinated treatment plan together with the patient. The plan covers care and cure, concerning abuse, somatic and mental illness and social deficits. The patient gives informed consent and receives a copy of the plan. The plan has contact information of involved staff (region, municipalities, GP), the patient and relatives. A mutual obligation exists to inform each other corresponding to the principles in the Danish psychiatric legislation concerning discharge agreement. The principle of this type of treatment plan in Denmark needs to be a part of a health agreement between the region and the municipalities. Finally, a national guideline is recommended to be elaborated for the treatment of this risk group (van Hoof et al., 2011).

Our second suggestion for patients with substance use disorder visiting the PER is to establish a type of Crisis Resolution Team (CRT) (Murphy et al., 2012) based at PER with two types of function for this group of patients: (1) when discharged from the PER, the CRT is responsible for making sure that the patient establishes therapeutic contact with relevant external partners; (2) the CRT is responsible for visiting the patient at home in case of mental health crisis, to encourage establishment of relevant treatment and to offer a short-term stay in the PER for reassessment and treatment if needed. There is some evidence indicating that increased cooperation between stakeholders in the complex treatment of substance use disorders, including the somatic health-care system, decreases overall treatment costs and results in less use of inappropriate treatment options in the PER and in decreased SMR rate in this group (Chi et al., 2011).

Footnotes

Declaration of Conflicting Interests

The authors report no conflict of interest. The authors alone are responsible for the content and writing of the paper.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was financially supported by funds for strengthening psychiatric research in Central Denmark Region. Programmer Søren Skadhede prepared the dataset for analysis.

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