Modeling the Cost-Effectiveness of Interventions to Reduce Suicide Risk Among Hospital Emergency Department Patients
Abstract
Objective:
This study estimated the expected cost-effectiveness and population impact of outpatient interventions to reduce suicide risk among patients presenting to general hospital emergency departments (EDs), compared with usual care. Several such interventions have been found efficacious, but none is yet widespread, and the cost-effectiveness of population-based implementation is unknown.
Methods:
Modeled cost-effectiveness analysis compared three ED-initiated suicide prevention interventions previously found to be efficacious—follow-up via postcards or caring letters, follow-up via telephone outreach, and suicide-focused cognitive-behavioral therapy (CBT)—with usual care. Primary outcomes were treatment costs, suicides, and life-years saved, evaluated over the year after the index ED visit.
Results:
Compared with usual care, adding postcards improved outcomes and reduced costs. Adding telephone outreach and suicide-focused CBT, respectively, improved outcomes at a mean incremental cost of $4,300 and $18,800 per life-year saved, respectively. Monte Carlo simulation (1,000 repetitions) revealed the chance of incremental cost-effectiveness to be a certainty for all three interventions, assuming societal willingness to pay ≥$50,000 per life-year. These main findings were robust to various sensitivity analyses, including conservative assumptions about effect size and incremental costs. Population impact was limited by low sensitivity of detecting ED patients’ suicide risk, and health care delivery inefficiencies.
Conclusions:
The highly favorable cost-effectiveness found for each outpatient intervention provides a strong basis for widespread implementation of any or all of the interventions. The estimated population benefits of doing so would be enhanced by increasing the sensitivity of suicide risk detection among individuals presenting to general hospital EDs.
The United States’ Healthy People 2020 goals include a target suicide rate of 10.2 per 100,000 people, representing a 10% reduction from the 2007 rate of 11.3 and a 26% reduction from the 2015 rate of 13.8 (1–3). Reaching this goal requires multiple strategies across different populations and settings (4–7). One key setting is hospital emergency departments (EDs), where at least 500,000 people present annually with self-injury and many more with suicidal ideation. These numbers, along with evidence that self-injury and suicidal ideation are major suicide predictors, suggest that effective ED-initiated suicidality treatment is essential to meeting suicide prevention targets (8–10).
This study examined the current evidence regarding ED-initiated interventions to reduce suicide risk among individuals presenting to general hospital EDs in order to assess whether any such interventions are likely cost-effective enough to support widespread implementation. If so, there is a clinical and economic rationale for adopting such interventions as the new standard of practice, even while researchers develop and test additional suicide prevention interventions.
Several ED-initiated interventions to reduce suicide risk have been found to be efficacious, compared with usual care, in at least one randomized control trial. These vary in approach and intensity, from the “caring letters” approach, which provides messages of psychosocial support to individuals after discharge, to postdischarge telephone contacts that encourage follow-up treatment, to aftercare involving suicide-focused cognitive-behavioral therapy (CBT) (11–19). However, none is yet in widespread use, and the cost-effectiveness of population-based implementation, as well as the potential impact on suicide rates, is currently unknown (17–19). Therefore, we used decision analysis to address these questions, drawing on findings from existing efficacy trials, other available data, and expert opinion regarding suicide risk identification among ED patients (20). We also identified key gaps in existing evidence in order to provide guidance for future research.
Methods
A Markov state-transition model was created to evaluate the cost-effectiveness of three interventions designed to reduce postdischarge suicide risk among adults (ages 18 and older) presenting to general hospital EDs. Patients treated in psychiatric EDs were outside the scope of the study. Our study period was 54 weeks, from the initial (index) ED presentation, divided into nine six-week Markov cycles (for expositional convenience, we report annualized results). The model begins with initial ED presentation; for each subsequent period, each individual can have a new nonfatal suicide event (that is, an attempt or a reattempt), can die by suicide, can die by other manner, or none of these. Our endpoints are case identification, suicide attempts averted, life-years saved, and costs associated with the index visit and any subsequent ED visit and with inpatient and outpatient care following ED presentation. We used TreeAge Pro 15.2.1.0-v20150831 modeling software.
Triage and Case Identification
For tractability, and absent clear empirical guidance, we assumed that each ED patient falls into one of three latent (unobserved) states of suicide risk: high (2.8%), low (9.6%), and none (87.6%). High-risk patients have high near-term risk of suicidal acts, defined here as the next six weeks. Low-risk patients have somewhat elevated suicidal risk, which we define operationally as half the rate of high-risk patients. By definition, no-risk patients have zero near-term suicide risk. Details for all model parameters are presented in Table 1, based on available data and expert opinion (21–28). [A figure illustrating our understanding of patient flow through the ED for high-, low-, and no-risk patients is included in an online supplement to this article.]
| Category | Point estimate | Range | Sourcea |
|---|---|---|---|
| Prevalence | |||
| Suicide risk status at time of index ED visit | |||
| High risk | 2.8% | Author calculation | |
| Low risk | 9.6% | Author calculation | |
| No risk | 87.6% | Author calculation | |
| Triage | |||
| Medical branch patientsb | 93% | 90%–97% | Author calculation |
| As a percentage of general ED population (study cohort) | 13.4% | 12.2%–14.6% | Author opinion and National Hospital Ambulatory Medical Care Survey (NHAMCS), 2008 (21), and NHAMCS, 2011 (22) |
| Hospitalized for medical reasons, no sign of suicidality | 7.04% | Author calculation | |
| No risk | 100% | — | Author calculation |
| Hospitalized for medical reasons, apparent self-injury | 4.5% | 2%–8% | Author opinion |
| High risk | 20% | 15%–25% | Author opinion |
| Low risk | 30% | 25%–35% | Author opinion |
| No risk | 50% | Author calculation | |
| Received medical treatment in ED | 88.46% | Author calculation | |
| High risk | 1.75% | .75%–2.75% | Author opinion and Parkland Hospital, 2015 (23) |
| Low risk | 8% | 6%–10% | Author opinion and Classen and Larkin, 2005 (35), and Parkland Hospital, 2015 (23) |
| No risk | 90.25% | 87.25%–93.25% | Author opinion and Boudreaux et al., 2016 (38) |
| Psych branch patientsc | 7% | 3%–10% | Personal communication, Claassen CA, 2016 |
| High risk | 7.5% | 5%–10% | Author opinion and personal communication, Claassen CA, 2016 |
| Low risk | 25% | 20%–30% | Author opinion and personal communication, Claassen CA, 2016 |
| No risk | 67.5% | 60%–75% | Author opinion and Boudreaux et al., 2016 (38) |
| Sensitivity and specificity | |||
| Medical branch, suicide screening | |||
| Sensitivity, high risk | 30% | 20%–40% | Author opinion |
| Sensitivity, low risk | 3% | 0%–6% | Author opinion |
| Specificity, no risk | 99% | 95%–100% | Author opinion |
| Medical branch, suicide risk assessment among those with positive suicide screening | |||
| Sensitivity, high risk | 95% | 90%–100% | Author opinion |
| Sensitivity, low risk | 66% | 50%–80% | Author opinion |
| Specificity, no risk | 50% | 40%–60% | Author opinion |
| Psych branch, suicide risk assessmentc | |||
| Sensitivity, high risk | 95% | 93%–97% | Author opinion |
| Sensitivity, low risk | 66% | 50%–80% | Author opinion |
| Specificity, no risk | 56% | 46%–66% | Pokorny, 1983 (24) |
| Sensitivity and specificity of identifying suicide risk among patients admitted to hospital from ED for medical reasons | |||
| Sensitivity, high risk | 100% | 100%–100% | Author opinion |
| Sensitivity, low risk | 100% | 100%–100% | Author opinion |
| Specificity, no risk | 50% | 40%–60% | Author opinion |
| Event probability: psychiatric hospitalization | |||
| Medical branch, positive suicide screen and positive suicide assessment | 35% | 25%–45% | Author opinion and Healthcare Cost and Utilization Project (HCUP), 2017 (32) |
| Psych branch, positive suicide assessment | 80% | 70%–90% | Author opinion and HCUP, 2017 (32) |
| Psych branch, negative suicide assessment | 10% | 5%–15% | Author opinion |
| Base costs | |||
| Medical ED visit | |||
| No risk; discharged alive | $675 | $25–$2,850 | Author opinion and HCUP, 2017 (32) |
| High risk or low risk; discharged alive | $890 | $25–$3,350 | Author opinion and HCUP, 2017 (32) |
| Psychiatric ED visit; discharged alive | $695 | $25–$2,950 | Author opinion and HCUP, 2017 (32) |
| Suicide risk assessment | $150 | $100–$200 | Author opinion |
| Medical hospitalization | |||
| No risk; discharged alive | $8,765 | $1,450–$33,500 | Author opinion and HCUP, 2017 (32) |
| No risk; died in hospital | $21,740 | $1,650–$104,000 | Author opinion and HCUP, 2017 (32) |
| High risk or low risk; discharged alive | $11,080 | $1,550–$49,500 | Author opinion and HCUP, 2017 (32) |
| High risk or low risk; died in hospital | $21,460 | $2,650–$123,000 | Author opinion and HCUP, 2017 (32) |
| Psychiatric hospitalization | |||
| Discharged alive | $5,875 | $1,050–$20,500 | Author opinion and HCUP, 2017 (32) |
| Died in hospital by suicide | $18,790 | $1,350–$85,000 | Author opinion and HCUP, 2017 (32) |
| Inpatient suicide treatment | $2,000 | Author opinion | |
| Death and reattempt rates | |||
| Death by nonsuicide manner (in 6 weeks)d | .02044% | WONDER online databases, 2017 (25) | |
| Probability of new suicide attempt (assuming no treatment) | |||
| High risk: 1st Markov cycle after index event | .048 | Author opinion and Qin and Nordentoft, 2005 (26) | |
| High risk: 2nd–4th Markov cycle (each) | .00038 | Author opinion and Qin and Nordentoft, 2005 (26) | |
| High risk: 5th Markov cycle | .00029 | Author opinion and Qin and Nordentoft, 2005 (26) | |
| High risk: 6th–9th Markov cycle (each) | .00020 | Author opinion and Qin and Nordentoft, 2005 (26) | |
| Low risk: no treatment: false negative (distributed by 6-week cycles) | 50% of high rate | Author opinion | |
| No risk | 0% | Author opinion | |
| Ratio of suicides to suicide attempts | 1:13 | Author opinion and American Foundation for Suicide Prevention, 2013 (27) and Centers for Disease Control (CDC) (28) | |
| Years of potential life lost per suicide | 24 | Author opinion and CDC (28) | |
| Interventions: uptake, outcomes, and costs | |||
| Usual care (UC) (also provided to patients who receive inpatient suicide treatment)e | |||
| Uptake (receiving any outpatient suicide treatment) | 35% | 10%–50% | Author opinion |
| Reduction in attempt and reattempt rate versus no treatment | 15% | 10%–20% | Author opinion |
| Costf | $340 | Author opinion and Centers for Medicare and Medicaid Services, 2016 (31) | |
| Postcards | |||
| Uptake | 100% | na | Carter et al., 2013 (11) |
| Reduction in attempt and reattempt rate versus UC | 45% | 35%–55% | Author opinion and Carter et al., 2013 (11) |
| Additional costg | $145 | $135–$500 | Author opinion and Carter et al., 2013 (11) |
| Telephone outreach | |||
| Uptake | 70% | 60%–80% | Author opinion and Vaiva et al., 2006 (12) |
| Reduction in attempt and reattempt rate versus UC | 34% | 25%–45% | Author opinion and Vaiva et al., 2006 (12) |
| Additional costh | $300 | $300–$900 | Author opinion and Vaiva et al., 2006 (12) |
| Cognitive-behavioral therapy | |||
| Uptake | 65% | 55%–75% | Author opinion and Brown et al., 2005 (13) |
| Reduction in attempt and reattempt rate versus UC | 50% | 40%–60% | Author opinion and Brown et al., 2005 (13) |
| Additional costi | $810 | $810–$2,000 | Author opinion and Brown et al., 2005 (13) |
a
Author calculation, estimate calculated by the authors on the basis of available data regarding the prevalence of suicide risk within subgroups of the ED population (that is, the sources cited for the “Triage” category in this table), so that each individual presenting to the ED for the index visit was counted exactly once; author opinion, estimate based on the authors’ opinion because of a lack of data from published sources or any data to use for primary estimation and in some cases, with information from other sources
b
Patient had acute or emergent medical problems and was hospitalized immediately or treated in the ED.
c
All psych-branch patients underwent a full clinical suicide risk assessment. All psych branch patients (100%) were assumed to have a positive suicide screening.
d
Estimated to be the same for all risk categories and treatments; based on the average nonsuicide mortality for men and women (combined) ages 35–44 in the U.S. general population, 2007–2010
e
All patients received usual care, including those who chose not to participate in an offered intervention.
f
Usual care cost based on CPT 90791 (psychiatric diagnostic evaluation) plus two CPT 90834 visits (1 visit is 45 minutes of psychotherapy)
g
Additional cost of postcards intervention based on $10 per person for postcards plus $135 (1.5 CPT 90834 visits) in additional outpatient treatment as a function of receiving the postcards
h
Additional cost of telephone outreach based on $30 for phone calls plus $270 (three CPT 90834 visits) in additional outpatient treatment as a function of receiving the calls
i
Additional cost of suicide-focused cognitive-behavioral therapy based on nine CPT 90834 visits
We assumed that individuals receive a very brief suicide risk screen by the triage nurse and are triaged by whether they have acute or emergent medical problems (“medical branch”) or not (“psych branch”). Medical-branch patients are hospitalized immediately or treated in the ED; they may be rescreened for suicide risk on the basis of self-report of suicidality or nurse judgment. Medical-branch patients screening positive for suicide risk and all psych-branch patients undergo a full clinical suicide risk assessment. Patients who assess positive are hospitalized or are discharged and referred to outpatient treatment—that is, usual care or one of the alternative interventions. Patients screening or assessing negative are considered nonsuicidal, regardless of their “true” risk state. Screening and assessment aim to identify patients with any (high or low) versus no suicide risk. However, the assumed sensitivity and specificity of screening and assessment and probabilities of hospitalization versus discharge differ for high-, low-, and no-risk patients (and by the presence and severity of general medical conditions).
Outpatient Suicide Interventions
We assumed that all patients identified as having suicide risk are offered usual care after ED or hospital discharge. Our operationalized model of aftercare assumes the following: 65% would receive no specific treatment after discharge, and 35% would receive an average of one initial diagnostic evaluation plus two 45-minute psychotherapy sessions during the 12 weeks postdischarge (additional details are provided in Table 1). Our base estimate is that usual care reduces the rate of suicide attempts or reattempts by 5.25% in the target population over the 12 weeks postdischarge, compared with no treatment—that is, a 15% reduction among the 35% who received treatment. After 12 weeks, these effects decline linearly to zero at the end of the study period.
For patients identified as having suicide risk and discharged from the ED, we consider three ED-initiated outpatient interventions delivered in addition to usual care. When we began this research, these were the only three such interventions that had been tested in a randomized controlled trial. For each intervention, we assumed equal effectiveness for persons experiencing suicidal ideation and nonfatal suicidal acts within the respective risk categories. In this study, we assumed that these interventions are not available to patients hospitalized from the ED.
Postcards.
In this intervention, ED or other personnel send patients a total of eight follow-up postcards as psychosocial support, monthly for four months and then bimonthly (11). We assumed that all targeted patients receive this intervention. On the basis of the results of the most relevant trial, which was conducted in a medical ED among self-poisoning cases, our base estimate is that postcards reduce the rate of suicide attempts or reattempts by 45% compared with usual care alone (and approximately 48% compared with no treatment) (11).
Telephone outreach.
In this intervention, ED or other personnel conduct telephone outreach for one to three months after discharge as psychosocial support and to encourage engagement in follow-up outpatient treatment (12). Per the trial results, 70% of targeted patients receive these calls. Our base estimate is that telephone outreach reduces the rate of suicide attempts or reattempts by 34% in this subgroup of patients, compared with usual care alone, across the study period (12).
CBT.
In this intervention, ED or other personnel connect patients to a suicide-focused CBT program (13). We assumed that 65% of targeted patients participate, on the basis of the percentage of patients who agreed to participate in the clinical trial that tested the CBT intervention. Participants receive an average of nine weekly or biweekly psychotherapy sessions as needed. Our base estimate is that CBT reduces the rate of suicide attempts or reattempts by 50% among participants, compared with usual care alone, across our study period (13).
Costs
Interventions can affect costs two ways: the direct cost of delivery, including the intervention per se and any associated health care use, and by altering the incidence of subsequent suicide attempts and deaths. For delivery costs, we used data on health service use reported in the corresponding clinical trial, inferring the relevant CPT codes and assigning costs based on national rates from the 2014 Medicare Physician Fee Schedule (11–13,31). For ED visits and hospitalizations, we calculated average costs on the basis of an analysis of corresponding events in the Healthcare Cost and Utilization Project (HCUP) database, for individuals discharged alive and for those who died while hospitalized (Table 1). We used HCUP data from four states (Arizona, Florida, Nebraska, and Utah) that either mandate reporting of ICD-9 external-cause-of-injury codes or are known to fully report these codes (32,33). General medical costs not associated with ED visits and related hospitalizations were outside this study’s scope.
Outcomes
At the end of each Markov cycle, individuals either die by suicide, die in another manner, experience a suicide attempt or reattempt, or survive the period with no suicide attempt or reattempt. We assumed that one in 13 suicide attempts results in death; the other 12 persons enter the next Markov cycle with a new ED presentation. Some hospitalized patients are at risk of suicide or of death in another manner or both while in the hospital, depending on their general medical and suicide risk state [see online supplement ].
We assumed that individuals maintain the same suicide risk state (high, low, or none) across the study period and that risk of a new suicide event declines with each Markov cycle that does not include such an event. After a new attempt or reattempt, transition probabilities reset to the same levels as after the index event. We assumed that sensitivity and specificity of suicide screening and assessment are the same at the index and any subsequent ED visit.
Results
Cost-Effectiveness
Base case analysis.
Using the base parameter values in Table 1 and the ED patient flow figure in the online supplement , we computed the mean expected costs and life-years per person during the study period for each of the four interventions (usual care, postcards, telephone outreach, and CBT), as well as the incremental costs, life-years, and cost-effectiveness ratio of the three interventions, compared with usual care (Table 2). If there were no deaths in the cohort during the study period, mean life-years would be exactly one.
| Treatment cost ($ per person) | Life-years (per person) | ||||
|---|---|---|---|---|---|
| Strategy | Total | Incremental | Total | Incremental | ICE ($ per life-year) |
| Usual care (reference) | 1,961.812 | 0 | .979321179 | 0 | — |
| Postcards | 1,960.454 | –1.36 | .979693574 | .000372395 | —a |
| Telephone outreach | 1,962.855 | 1.043 | .979565566 | .000244387 | 4,300 |
| Cognitive-behavioral therapy | 1,966.77 | 4.96 | .979584921 | .000263742 | 18,800 |
a
Cost and life saving
Mean costs per patient were $1,962 with usual care. Compared with usual care, mean costs were .07% lower with postcards and .05% and .25% higher with telephone outreach and CBT, respectively. Each intervention reduced mortality, on average. Compared with usual care, the postcards intervention was “dominant”—that is, it had both lower costs and better outcomes. The estimated mean incremental cost per life-year was $4,300 for telephone outreach and $18,800 for CBT.
Monte Carlo simulation.
Figure 1 presents data on incremental costs and outcomes of the enhanced interventions compared with usual care, based on Monte Carlo simulation that accounted for uncertainty across the model inputs. Table 1 lists ranges for each input, and values were assumed to follow a beta distribution. We drew 1,000 samples and computed the expected values of the respective outcomes for each vector of sampled parameters. Although there is no definitive benchmark regarding societal willingness to pay (WTP) to reduce mortality, the sloped line in Figure 1 marks the relatively conservative WTP threshold of $50,000 per life-year (34). Trials to the right of that line represent more favorable incremental cost-effectiveness (ICE). For each comparison, ellipses mark the 95% confidence interval (CI) for the estimated ICE.
FIGURE 1. Incremental costs and outcomes of the three interventions to reduce suicide risk among hospital emergency department patients, compared with usual care (UC)a
aBased on Monte Carlo simulation that accounted for uncertainty across the model inputs
bCompared with usual care, postcards and cognitive-behavioral therapy (CBT) improved outcomes with incremental cost-effectiveness (ICE) below $50,000 per life-year with certainty (100% likelihood).
cCompared with usual care, telephone outreach improved outcomes with ICE below $50,000 per life-year with 99.5% likelihood.
dSaved life-years per emergency department visitor × 10−3
Compared with usual care, postcards and CBT improved outcomes with ICE at or below $50,000 per life-year with certainty, whereas with telephone outreach the probability of improved outcomes at or below this threshold was 99.5%. The probability of postcards dominating usual care was 94%, and the postcards intervention was cost-effective compared with usual care even when WTP was set at $0 per life-year. The probability that telephone outreach was cost-effective compared with usual care was 96% when WTP was $20,000 per life-year and 80% when WTP was $10,000 per life-year [see online supplement ], whereas the probability that CBT was cost-effective compared with usual care was 67% when WTP was $20,000 per life-year and only 1.6% when WTP was $10,000 per life-year.
Sensitivity analysis.
We conducted one-way sensitivity analyses for all inputs, across at least the full range in Table 1. For nearly all inputs, our primary finding—the cost-effectiveness of each intervention compared with usual care when WTP was ≥$50,000 per life-year—remained intact across this range. The sole exceptions were substantial increases in each intervention’s costs and the specificity of suicide risk screening among medical-branch patients. For CBT versus usual care, ICE exceeded $50,000 per life-year if specificity fell from our base rate of 99% (that is, 1% false positives among no-risk patients) to 91% or below. For telephone outreach versus usual care, ICE exceeded this WTP benchmark for specificity below 60%. For postcards versus usual care, incremental costs were positive for specificity below 79%, but ICE remained below $50,000 per life-year even at specificity below 40%. Given our other assumptions, even reducing specificity of suicide risk assessment among medical-branch patients who screened positive and all psych-branch patients to 30% from our base rate of 50% did not raise ICE above $50,000 per life-year for any of the three interventions, compared with usual care.
Given the obvious relevance of each intervention’s effect size and costs, we conducted two-way sensitivity analyses for these parameters (Table 3 and figure in online supplement ). In Table 3, each entry represents an alternative assumption about the cost of the respective intervention; for each cost specified, the table reports the minimum risk-reduction ratio (effect size) necessary for the intervention to remain cost-effective at a WTP threshold of $50,000 per life-year or $100,000 per life-year. For instance, if the cost of telephone outreach tripled to $900 from the base value of $300, the ICE of telephone outreach versus usual care would remain below $50,000 per life-year as long as telephone outreach reduced the suicide rate by at least 26% relative to usual care, compared with our base value of 34%.
| Strategy and cost of delivery ($) | Risk reduction relative to usual care (%) | |
|---|---|---|
| $50,000 | $100,000 | |
| Postcards | ||
| 135a | —b | —b |
| 270 | 3 | 2.5 |
| 500 | 7 | 4.5 |
| Telephone outreach | ||
| 300a | 6 | 3 |
| 600 | 16 | 9 |
| 900 | 26 | 14 |
| Cognitive-behavioral therapy | ||
| 810a | 20 | 10 |
| 1,600 | 45 | 23 |
| 2,000 | 68 | 30 |
a
Base case
b
Cost and life saving
Population Impact
Our findings regarding the relative cost-effectiveness of each intervention were not sensitive to plausible variation in sensitivity of suicide screening or suicide risk assessment. In short, this was because false negatives do not present an opportunity for improved outcomes but also do not incur additional costs (whereas false positives also present no opportunity for improved outcomes but incur additional costs). However, sensitivity of screening and assessment was important for a different aspect of this analysis: the extent that enhanced intervention could reduce suicides in the target population.
On the basis of the parameters in Table 1, we estimated that 12.4% of individuals presenting for the index ED visit were suicidal, with 2.8% at high risk and 9.6% at low risk. Of these, we estimated that approximately 82% of high-risk patients and 26% of low-risk patients would be identified on the basis of our estimates for screening and assessment sensitivity; the rest were false negatives. However, only identified patients who were discharged from the ED were eligible for the enhanced interventions—that is, approximately 26% of high-risk patients and 3% of low-risk patients, following our assumptions about hospitalization—or about 8% of all individuals in the cohort with elevated suicide risk. This estimate represents an upper bound for impact in the target population. When additional estimates of each intervention’s relative effect size were applied, the Monte Carlo simulations yielded an estimated reduction of suicide deaths in the cohort from the interventions of around 2.5% (CI=0%−11%); the differences between postcards, telephone outreach, and CBT were not statistically significant at conventional levels.
Discussion and Conclusions
Our modeled analysis of ED-initiated suicide prevention interventions found that postcards improved outcomes and reduced costs, compared with usual care. Two other interventions, telephone outreach and CBT, improved outcomes at an incremental cost below a WTP of $50,000 per life-year, a conservative estimate of societal WTP for reducing mortality (34). These findings were largely insensitive to plausible variation in model inputs. In our view, this provides a compelling rationale for widespread implementation of any of these interventions, particularly postcards (or, more generally, letters, because postcards per se might raise privacy concerns).
However, even widespread implementation would have limited population impact because of the low sensitivity of detecting ED patients’ suicide risk and because of health system inefficiencies. Although this aspect of our findings should not deter adoption of interventions that are strongly cost-effective even under current circumstances, it suggests additional avenues for increasing intervention benefits, particularly increasing the sensitivity of detecting near-term suicide risk in the ED population, and for improving coordination and continuity of care across delivery settings after patients leave the ED (35–40). Our findings also highlight the importance of ensuring that evidence-based interventions are economically viable and that appropriate training and technical assistance are available.
This study had important limitations. EDs vary considerably in staffing, treatment protocols, and other characteristics. Given available information and the requirements for parsimony inherent in decision analysis, we tried to create a framework reflective of general hospital EDs in the United States. In any case, our main findings were quite robust to alternative assumptions about patient flow through an ED within the parameter ranges in Table 1. This makes our model useful for studying additional improvements in ED practice, such as efforts to improve sensitivity or specificity of suicide screening, and additional interventions that are found to be efficacious or effective via future trials.
We relied on our own opinions to estimate many inputs, because we could find no corresponding published sources or any data to use for primary estimation. Here, too, we are reassured by the robustness of our findings to alternative parameter values. We considered effects on mortality but not improvements in quality of life, which is a conservative assumption.
Only limited evidence exists regarding the effectiveness and costs of the three interventions (and trials have lacked power to assess their impacts on suicide deaths) (11–19). The trials we reference were conducted under conditions that differed somewhat from those in our model (11–13). The interventions using postcards and telephone outreach were tested outside the United States, and the CBT intervention was tested in a highly urban U.S. setting. All trials were small, and none explicitly reported effects on costs. The postcards trial focused on self-poisoning cases, a subset of ED patients with suicide risk, and it found significant reductions in the number of reattempts but not in the fraction of patients who reattempted (11). A separate study of the postcards intervention focused on all types of self-harm, with similar results (41). The telephone outreach trial also focused on self-poisoning, with null intent-to-treat findings but positive as-treated findings (12). In the CBT trial, one-third of invited patients declined to participate, and adherence to the therapy protocol approached 100% among participants (13). These trials found similar effect sizes across substantially different interventions, indicating that some caution is needed regarding the relative dominance of the postcards intervention, although not regarding its cost-effectiveness compared with usual care.
Despite the limitations, each of these interventions appears to be strongly cost-effective. Additional research on these and other interventions to reduce suicide risk among individuals presenting to general hospital EDs may further aid decision makers. For instance, the Emergency Department Safety and Follow-Up Evaluation (ED-SAFE) study reported that detection of at-risk individuals could be doubled by implementing universal screening in eight U.S. EDs (38). ED-SAFE also tested a form of telephone outreach aimed at supporting treatment adherence, with backup crisis support provided by a call center that is part of the National Suicide Prevention Lifeline, and found that universal screening and telephone outreach resulted in a 27% reduction in the risk of a composite outcome of attempts and deaths, compared with usual care alone (29,42). The Attempted Suicide Short Intervention Program trial in Switzerland, which combined elements of the CBT and postcards interventions, reported an 80% reduction in reattempts (43). Together, these findings support enhancing the standard of care for suicide risk in general hospital EDs with the goal of reaching national suicide prevention targets.
Acknowledgments
The authors thank Annette Beautrais, Ph.D., and Gregory Luke Larkin, M.D., for participating in preliminary discussions on a range of approaches to suicide risk detection and prevention in emergency care settings. The views expressed in this paper are those of the authors and are not necessarily those of NIMH, the National Institutes of Health, or the federal government.
Footnote
Support for this research was provided to Dr. Allen, Dr. Claassen, Dr. Currier, and Dr. Zatzick under professional services contracts with NIMH.
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References
1.
Healthy People 2020. Atlanta, Centers for Disease Control and Prevention, National Center for Health Statistics, 2015. http://www.cdc.gov/nchs/healthy_people/hp2020.htm. Accessed April 8, 2016
2.
Increase in Suicide in the United States, 1999–2014. Atlanta, Centers for Disease Control and Prevention, National Center for Health Statistics, 2016. https://www.cdc.gov/nchs/products/databriefs/db241.htm. Accessed March 11, 2017
3.
Drapeau CW, McIntosh JL: USA Suicide: 2015 Official Final Data. Washington, DC, American Association of Suicidology, 2016. http://www.suicidology.org/Portals/14/docs/Resources/FactSheets/2015/2015datapgsv1.pdf?ver=2017-01-02-220151-870. Accessed March 11, 2017
4.
2012 National Strategy for Suicide Prevention: Goals and Objectives for Action. Washington, DC, Department of Health and Human Services, 2012. https://www.surgeongeneral.gov/library/reports/national-strategy-suicide-prevention/full_report-rev.pdf. Accessed March 11, 2017
5.
Pringle B, Colpe LJ, Heinssen RK, et al: A strategic approach for prioritizing research and action to prevent suicide. Psychiatric Services 64:71–75, 2013
6.
Sentinel Event Alert #56: Detecting and Treating Suicide Ideation in All Settings. Chicago, Joint Commission, 2016. https://www.jointcommission.org/sea_issue_56. Accessed May 19, 2016
7.
About Zero Suicide. Waltham, MA, Suicide Prevention Resource Center, 2016. http://zerosuicide.sprc.org/about. Accessed March 11, 2017
8.
Larkin GL, Beautrais AL: Emergency departments are underutilized sites for suicide prevention. Crisis 31:1–6, 2010
9.
Carroll R, Metcalfe C, Gunnell D: Hospital presenting self-harm and risk of fatal and non-fatal repetition: systematic review and meta-analysis. PLoS One 9:e89944, 2014
10.
Ahmedani BK, Simon GE, Stewart C, et al: Health care contacts in the year before suicide death. Journal of General Internal Medicine 29:870–877, 2014
11.
Carter GL, Clover K, Whyte IM, et al: Postcards from the EDge: 5-year outcomes of a randomised controlled trial for hospital-treated self-poisoning. British Journal of Psychiatry 202:372–380, 2013
12.
Vaiva G, Vaiva G, Ducrocq F, et al: Effect of telephone contact on further suicide attempts in patients discharged from an emergency department: randomised controlled study. BMJ 332:1241–1245, 2006
13.
Brown GK, Ten Have T, Henriques GR, et al: Cognitive therapy for the prevention of suicide attempts: a randomized controlled trial. JAMA 294:563–570, 2005
14.
Luxton DD, June JD, Comtois KA: Can postdischarge follow-up contacts prevent suicide and suicidal behavior? A review of the evidence. Crisis 34:32–41, 2013
15.
Motto JA, Bostrom AG: A randomized controlled trial of postcrisis suicide prevention. Psychiatric Services 52:828–833, 2001
16.
Hassanian-Moghaddam H, Sarjami S, Kolahi AA, et al: Postcards in Persia: a twelve to twenty-four month follow-up of a randomized controlled trial for hospital-treated deliberate self-poisoning. Archives of Suicide Research 21:138–154, 2017
17.
Hawton K, Witt KG, Taylor Salisbury TL, et al: Psychosocial interventions for self-harm in adults. Cochrane Database of Systematic Reviews 5:CD012189, 2016
18.
Hawton K, Witt KG, Taylor Salisbury TL, et al: Psychosocial interventions following self-harm in adults: a systematic review and meta-analysis. Lancet Psychiatry 3:740–750, 2016
19.
Zalsman G, Hawton K, Wasserman D, et al: Suicide prevention strategies revisited: 10-year systematic review. Lancet Psychiatry 3:646–659, 2016
20.
How Modeling Can Inform Strategies to Improve Population Health: Workshop Summary. Washington, DC, National Academies Press, 2015. http://www.nationalacademies.org/hmd/Reports/2015/How-Can-Modeling-Inform-Strategies-to-Inform-Population-Health.aspx. Accessed May 4, 2016
21.
National Hospital Ambulatory Medical Care Survey: 2008 Emergency Department Summary Tables. Atlanta, Centers for Disease Control and Prevention, National Center for Health Statistics, 2008. http://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency/2008_ed_web_tables.pdf. Accessed May 19, 2016
22.
National Hospital Ambulatory Medical Care Survey: 2011 Emergency Department Summary Tables. Atlanta, Centers for Disease Control and Prevention, National Center for Health Statistics, 2011. http://www.cdc.gov/nchs/data/ahcd/nhamcs_emergency/2011_ed_web_tables.pdf. Accessed May 19, 2016
23.
More than 150,000 patients screened for suicide risk at Parkland this year. Dallas, Parkland Hospital, 2015. http://www.parklandhospital.com/phhs/news-and-updates/more-than-150000-patients-screened-for-suicide-ris-464.aspx. Accessed March 10, 2017
24.
Pokorny AD: Prediction of suicide in psychiatric patients: report of a prospective study. Archives of General Psychiatry 40:249–257, 1983
25.
WONDER Online Databases. Atlanta, Centers for Disease Control and Prevention, 2017. http://wonder.cdc.gov. Accessed Nov 29, 2015
26.
Qin P, Nordentoft M: Suicide risk in relation to psychiatric hospitalization: evidence based on longitudinal registers. Archives of General Psychiatry 62:427–432, 2005
27.
Suicide Facts and Figures. New York, American Foundation for Suicide Prevention, 2013. http://afsp.donordrive.com/index.cfm?fuseaction=cms.page&id=1226&cmsContentSetID=D5C4DC12-C299-258B-B0B6FCF9EF015CE0. Accessed May 19, 2016
28.
WISQARS Fatal Injury Reports. Atlanta, Centers for Disease Control and Prevention, 2014. http://webappa.cdc.gov/sasweb/ncipc/mortrate10_us.html. Accessed April 8, 2016
29.
Crisis Center Guidance: Follow-Up With Callers and Those Discharged From Emergency Department and Inpatient Settings. Rockville, MD, National Suicide Prevention Lifeline, 2012. http://suicidepreventionlifeline.org/wp-content/uploads/2016/09/Lifeline-Follow-Up-Guidance1214.pdf. Accessed March 11, 2017
30.
Applied Research Toward Zero Suicide Healthcare Systems (R01). Bethesda, MD, National Institutes of Health, 2015. https://grants.nih.gov/grants/guide/rfa-files/RFA-MH-16-800.html. Accessed March 11, 2017
31.
Physician Fee Schedule Search. Baltimore, Centers for Medicare and Medicaid Services, 2016. https://www.cms.gov/apps/physician-fee-schedule/search/search-criteria.aspx. Accessed April 14, 2016
32.
Healthcare Cost and Utilization Project (HCUP). Rockville, MD, Agency for Healthcare Research and Quality, 2017. http://www.hcup-us.ahrq.gov. Accessed April 14, 2016
33.
Claassen C, Smith JP, Kashner TM: Self Harm in the United States: What We Can Learn From National and State-Level Medical Datasets. Presented at National Center for Health Statistics Data Conference, Aug 6–8, 2012. http://www.cdc.gov/nchs/ppt/nchs2012/ss-32_claassen.pdf. Accessed April 14, 2016
34.
Braithwaite RS, Meltzer DO, King JT Jr, et al: What does the value of modern medicine say about the $50,000 per quality-adjusted life-year decision rule? Medical Care 46:349–356, 2008
35.
Claassen CA, Larkin GL: Occult suicidality in an emergency department population. British Journal of Psychiatry 186:352–353, 2005
36.
King CA: Emergency Department Screen for Teens at Risk for Suicide (ED-STARS). Bethesda, MD, National Institutes of Health, Research Portfolio Online Reporting Tools, 2014. https://projectreporter.nih.gov/project_info_description.cfm?aid=8755416&icde=21651658&ddparam=&ddvalue=&ddsub=&cr=3&csb=default&cs=ASC. Accessed May 8, 2016
37.
Horowitz LM, Bridge JA, Teach SJ, et al: Ask Suicide-Screening Questions (ASQ): a brief instrument for the pediatric emergency department. Archives of Pediatrics and Adolescent Medicine 166:1170–1176, 2012
38.
Boudreaux ED, Camargo CA Jr, Arias SA, et al: Improving suicide risk screening and detection in the emergency department. American Journal of Preventive Medicine 50:445–453, 2016
39.
Betz ME, Arias SA, Segal DL, et al: Screening for suicidal thoughts and behaviors in older adults in the emergency department. Journal of the American Geriatrics Society 64:e72–e77, 2016
40.
Chang BP, Tan TM: Suicide screening tools and their association with near-term adverse events in the ED. American Journal of Emergency Medicine 33:1680–1683, 2015
41.
Beautrais AL, Gibb SJ, Faulkner A, et al: Postcard intervention for repeat self-harm: randomised controlled trial. British Journal of Psychiatry 197:55–60, 2010
42.
Miller IW, Camargo CA Jr, Arias SA, et al: Suicide prevention in an emergency department population: the ED-SAFE Study. JAMA Psychiatry 74:563–570, 2017
43.
Gysin-Maillart A, Schwab S, Soravia L, et al: A novel brief therapy for patients who attempt suicide: a 24-months follow-up randomized controlled study of the Attempted Suicide Short Intervention Program (ASSIP). PLoS Medicine 13:e1001968, 2016
Information & Authors
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Cover: Understanding, by Michael Olszewski, 1984. Dyed and pleated silk plain weave with silk embroidery. Philadelphia Museum of Art, gift of Nancy and David Bergman, 2015.
History
Received: 28 July 2016
Revision received: 11 March 2017
Revision received: 24 May 2017
Accepted: 22 June 2017
Published online: 15 September 2017
Published in print: January 01, 2018
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Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
National Institute of Mental Health10.13039/100000025
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