Association Between Telepsychiatry Capability and Treatment of Patients With Mental Illness in the Emergency Department
Abstract
Objective:
Because of limited access to psychiatrists, patients with acute mental illness in some emergency departments (EDs) may wait days for a consultation in the ED or as a medical-surgical admission. The study assessed whether telepsychiatry improves access to care and decreases ED wait times and hospital admissions.
Methods:
ED visits with a primary diagnosis of mental illness were identified from 2010–2018 Medicare claims. A total of 134 EDs across 22 states that implemented telepsychiatry between 2013 and 2016 were matched 1:1 with control EDs without telepsychiatry on several characteristics, including availability of in-person psychiatrist consultations. Outcomes included patients’ likelihood of admission to a medical-surgical or psychiatric bed, mental illness spending, prolonged ED length of stay (LOS) (two or more midnights in the ED), 90-day mortality, and outpatient follow-up care. Using a difference-in-difference design, changes in outcomes between the 3 years before telepsychiatry adoption and the 2 years after were examined.
Results:
There were 172,708 ED mental illness visits across the 134 matched ED pairs in the study period. Telepsychiatry adoption was associated with increased admissions to a psychiatric bed (differential increase, 4.3 percentage points; p<0.001), decreased admissions to a medical-surgical bed (differential decrease, 2.0 percentage points; p<0.001), increased likelihood of a prolonged ED LOS (differential increase, 3.0 percentage points; p<0.001), and increased mental illness spending (differential increase, $292; p<0.01).
Conclusions:
Telepsychiatry adoption was associated with a lower likelihood of admission to a medical-surgical bed but an increased likelihood of admission to a psychiatric bed and a prolonged ED LOS.
HIGHLIGHTS
•
Telepsychiatry adoption by emergency departments (EDs) was associated with fewer medical-surgical admissions, increased psychiatry admissions, and a higher likelihood of a prolonged ED length of stay.
•
These changes may reflect higher quality of care if consulting psychiatrists identified more patients requiring inpatient psychiatric care who would have otherwise been admitted to a medical-surgical bed or discharged from the ED.
•
Future work should assess the impact of telepsychiatry on hospital finances and longer-term patient outcomes.
Between 2006 and 2014, mental illness–related emergency department (ED) visits increased by 40%, and the subset of visits for suicide attempts or suicidal ideation more than quadrupled (1). This growth has exacerbated challenges in providing specialty care for ED patients with mental illness. When caring for patients with acute mental illness, ED physicians rely on consultation from a psychiatrist. Unfortunately, many EDs are not routinely staffed by psychiatrists (2). Patients often wait a long time to be assessed in the ED or may be unnecessarily admitted to a medical-surgical bed awaiting evaluation (3, 4).
Telepsychiatry, a technology now adopted in 20% of EDs in the United States, could address the gap between psychiatry capacity and growing need in EDs nationally (2). In the telepsychiatry model, the ED provider evaluates the patient and decides whether there is a need for a psychiatrist consultation. The remote psychiatrist interviews the patient via videoconference and provides recommendations to the ED provider. EDs with limited psychiatrist capacity have introduced telepsychiatry to improve access and quality of care, reduce ED length of stay (LOS), decrease hospitalizations, and increase outpatient follow-up care (5, 6).
Prior studies evaluating the impact of telepsychiatry have mixed findings in terms of hospital admissions, ED LOS, mental illness outpatient follow-up care, and inpatient spending (6–9). These important studies have had limitations, including a focus on only a single health system, geographic area, or telepsychiatry program. Other limitations have included not addressing temporal trends in outcomes or focusing only on patients who receive a telepsychiatry consultation, because of selection bias in who receives a consultation and who does not. It remains unclear whether telepsychiatry, as implemented on a national scale across EDs, is associated with improved outcomes for patients with acute mental illness presenting to the ED.
We assessed the impact of telepsychiatry adoption in 134 EDs across 22 states between 2013 and 2016 on the likelihood of admission to a medical-surgical bed, admission to a psychiatric bed, mental illness spending, ED LOS, mental illness outpatient follow-up care, and mortality.
Methods
We evaluated the impact of telepsychiatry by examining patterns of care for patients with a mental illness diagnosis who presented to EDs with telepsychiatry capacity and patients in matched control EDs that did not have telepsychiatry (10). We included all ED visits in our analysis regardless of whether the patient received a telepsychiatry consultation.
We employed a difference-in-difference approach, comparing the change in patterns of care in the 3 years before to the 2 years after in EDs that adopted telepsychiatry with the change in such patterns over the same period in EDs that did not adopt telepsychiatry (control EDs).
This study was conducted from December 15, 2019, through February 1, 2021. The Harvard Faculty of Medicine Institutional Review Board exempted this study from review.
Telepsychiatry in EDs
Telepsychiatry provides patients with a real-time video telecommunication consultation with a psychiatrist. The psychiatrist conducts a standard history and mental status examination and has access to the medical record. The psychiatrist writes a consultant note that provides recommendations for acute management. Management is facilitated by local ED staff, which includes mental health specialists (e.g., social workers). If psychiatric hospitalization is required, the bed search is conducted by local ED staff. EDs may use telepsychiatry for all consultations or for consultations when a psychiatrist is unavailable (e.g., evenings and weekends).
Identifying EDs With Telepsychiatry Capacity
No comprehensive list exists of which EDs use telepsychiatry and when it was introduced. We used data from InTouch, a telemedicine company that provides infrastructure for EDs that want to deploy telepsychiatry, including software and bedside videoconferencing equipment. The consulting psychiatrists, who are chosen by the local ED, can work in local health systems or academic institutions or for private companies. InTouch provided the names and dates of telepsychiatry adoption for 134 EDs in 22 states across multiple health systems between 2013 and 2016. The data did not capture information on how each ED used telepsychiatry (e.g., evenings, weekends, or 24/7) or who the consulting psychiatrists were.
Data Sources and Study Sample
We used 2010–2018 deidentified data for Medicare fee-for-service beneficiaries 18 years and older: outpatient facility and inpatient claims for all beneficiaries and professional claims for a 20% sample. Telepsychiatry was introduced between 2013 and 2016 for each ED studied, which allowed us to look at 3 years before adoption and 2 years after adoption.
Our analysis focused on all ED visits to short-term acute care and critical access hospitals with a primary diagnosis of mental illness (substance use disorders were excluded). Mental illnesses were identified and categorized by using the Agency for Healthcare Research and Quality Clinical Classification system and ICD-9-CM and ICD-10-CM diagnoses (11). (A table listing the diagnoses is included in an online supplement to this article.) Mental illness diagnoses that occurred less frequently were grouped into a single “other” category. Patients could have more than one ED visit in the sample.
Treatment of mental illness may involve transfers from one facility to another. To capture “episodes” across multiple facilities, we linked ED and inpatient claims records with a mental illness primary diagnosis for the same beneficiary if the dates of service overlapped or immediately followed one another (12). For example, if a patient presented to one hospital’s ED, was kept overnight on an observation stay, and was then transferred to another hospital’s psychiatric bed for an inpatient stay, these data were combined into a single episode and assigned to the first hospital where the patient received care.
Patient and Hospital Characteristics
Using Medicare enrollment files, we characterized patients on the basis of age group, gender, dual enrollment in Medicaid, original reason for Medicare enrollment (old age versus disability or end-stage renal disease), primary diagnosis for ED visit (anxiety disorders, mood disorders, schizophrenia and other psychotic disorders, suicide and self-inflicted injury, and other), and having one or more inpatient stays or ED visits in 90 days prior to their ED visit. Data on race-ethnicity were not captured. For each patient characteristic, we measured the standardized difference in means between the telepsychiatry ED and control ED visits to ensure they did not exceed 0.10, a threshold that signifies minimal difference (13).
We characterized hospitals based on number of beds, census region, availability of in-person psychiatrist care in the ED, rurality, location in a Medicaid expansion state, and number of baseline mental illness ED visits. Survey data from the 2018 American Hospital Association (AHA) (14) were used to determine the availability of in-person ED psychiatrist care and were based on whether the hospital reported in-person psychiatric consultation services or in-person psychiatric ED care. Hospitals were classified as rural if they were located outside a metropolitan statistical area (15). The number of baseline mental illness ED visits was measured in 2010–2012, the 3 years prior to telepsychiatry adoption in our sample.
Hospital Matching
We performed a 1:1 match based on hospital characteristics that we hypothesized had an impact on either the adoption of telepsychiatry or the study outcomes: hospital size, census region, rural status, state Medicaid expansion status, availability of ED in-person psychiatrist care, and the number of baseline mental illness ED visits (Table 1).
| Telepsychiatry EDs (N=134) | Control EDs (N=134) | All potential control EDs (N=3,350)b | ||||
|---|---|---|---|---|---|---|
| Characteristic | N | % | N | % | N | % |
| Availability of in-person psychiatrist for care in the EDc | ||||||
| No | 86 | 64 | 86 | 64 | 1,948 | 58 |
| Yes | 48 | 36 | 48 | 36 | 1,402 | 42 |
| Hospital size (beds)c | ||||||
| 0–99 | 59 | 44 | 59 | 44 | 1,659 | 50 |
| 100–400 | 64 | 48 | 64 | 48 | 1,455 | 43 |
| >400 | 11 | 8 | 11 | 8 | 236 | 7 |
| Ruralityc | ||||||
| Metropolitan area | 90 | 67 | 90 | 67 | 1,800 | 54 |
| Rural area | 44 | 33 | 44 | 33 | 1,550 | 46 |
| Census regionc | ||||||
| Northeast | 0 | — | 0 | — | 434 | 13 |
| Midwest | 33 | 25 | 33 | 25 | 991 | 30 |
| South | 44 | 33 | 44 | 33 | 1,315 | 39 |
| West | 57 | 43 | 57 | 43 | 610 | 18 |
| Medicaid expansion statec | ||||||
| No | 57 | 43 | 57 | 43 | 1,274 | 38 |
| Yes | 77 | 57 | 77 | 57 | 2,076 | 62 |
| N of ED visits per year at baseline (M±SD)d | 120.2±151.8 | 119.6±141.8 | 131.3±169.1 | |||
a
Standardized difference between telepsychiatry EDs and matched control EDs was .00 for each hospital characteristic, below the .10 threshold signifying minimal difference consistent with established methodology.
b
Universe of acute care hospitals from which the control EDs were selected. These EDs did not have telepsychiatry services via InTouch in the data and had at least one ED visit with a primary mental illness diagnosis in each 6-month period from 2010–2018.
c
Variable on which exact matching was conducted.
d
Mean number of ED visits with a mental illness primary diagnosis per year during the 3-year baseline period of January 1, 2010, to December 31, 2012.
Control EDs were sampled from all short-term acute care hospitals and critical access hospitals that did not implement telepsychiatry via InTouch that had at least one ED visit with a primary mental illness diagnosis in each 6-month period from 2010 to 2018. To conduct the match, we used cardinality matching with the R “designmatch” package (16–22).
Identification of ED Visits in Telepsychiatry and Control Hospitals
ED visits were included in our analyses if they occurred at telepsychiatry EDs or matched control EDs in the 3 years prior to telepsychiatry adoption or the 2 years after, with one exception: we excluded visits in the 6-month transition period in which telepsychiatry was adopted. Each calendar year was divided into 6-month blocks to facilitate the matching. For example, if the ED in hospital A adopted telepsychiatry in February 2013 and was matched to control hospital B, then for both hospitals the 3-year preadoption period would be January 2010 to December 2012, the 6-month transition period would be January to June 2013, and the 2-year postadoption period would be July 2013 to June 2015.
Study Outcomes
Our five outcomes were disposition from the ED (discharge, medical-surgical admission, or admission to a psychiatric specialty bed), prolonged ED LOS, 90-day mental illness institutional spending (defined below), mental illness outpatient follow-up care, and 90-day mortality. Admission to a psychiatric specialty bed included admission to a psychiatric hospital or a psychiatric unit within an acute care hospital.
Our data provided only the day of admission and discharge, and we could not measure ED LOS in hours. As in prior work (7), we captured prolonged ED LOS with a dichotomous measure of whether the patient spent two or more midnights in the ED prior to discharge or admission. ED visits that result in admission do not provide the date of admission to the hospital. In these cases, we measured the number of midnights between presentation to the ED and the date of the first professional claim for a hospital admission note. There was no admission note for 8.2% of ED visits that resulted in an admission. To address these missing data, we used multiple imputation (Stata’s mi impute) to impute prolonged LOS by using the patient characteristics listed above. This outcome was limited to the random 20% of beneficiaries for whom we had professional claims.
Mental illness institutional spending encompassed payments to hospitals for mental illness inpatient and ED care (23–26) incurred during the 90 days from ED presentation, because our hypothesis was that telepsychiatry would decrease admission rates. Payments to a hospital for admission to a medical-surgical bed would be included in mental illness institutional spending if the primary diagnosis was for mental illness.
As in prior work (27–29), mental illness outpatient follow-up care was the receipt of a visit with a mental illness diagnosis in the primary or secondary diagnostic field with a specialty mental health provider (psychiatrist, psychologist, or social worker) within 2 weeks of ED discharge. Because follow-up care after an inpatient hospitalization would be unlikely to be affected by an ED telepsychiatry consultation, this measure was limited to the subset of patients discharged from the ED and the 20% random sample of persons with professional claims.
Statistical Analysis
We performed a difference-in-differences analysis to measure changes in the outcomes among patients in telepsychiatry EDs versus the matched control EDs. To minimize bias from differential changes over time in the patient population at telepsychiatry EDs and control EDs, we adjusted our estimates for differences in patient characteristics in each time period.
To measure change, we used a series of logistic and linear regression models (appropriate for the outcome) that included an indicator for the postadoption period, for treatment (i.e., telepsychiatry ED), and an interaction of the two terms. We clustered standard errors at the hospital level, because care patterns were likely correlated within hospitals. We estimated our models in Stata, version 15, and we report the average marginal effects of telepsychiatry adoption.
We conducted subgroup analyses to assess heterogeneity of associations among patients with greater severity of illness versus those without greater severity (one or more mental illness hospitalizations in the prior 90 days). In a sensitivity analysis, we compared the unadjusted versus adjusted differential changes. We also tested the parallel-trends assumption for each outcome in the 3 years prior to telepsychiatry adoption, a key assumption for difference-in-difference analyses (see online supplement).
Results
Telepsychiatry and Control EDs
Most EDs adopting telepsychiatry lacked in-person psychiatrist care (64%), were located in urban areas (67%), had fewer than 400 hospital beds (92%), and had a mean±SD of 120.2 mental illness ED visits per year at baseline (Table 1).
Characteristics of ED Patients With a Mental Illness Diagnosis
As shown in Table 2, during the 3-year preadoption period at telepsychiatry EDs and control EDs, there were 50,420 and 51,445 mental illness ED visits, respectively, and during the 2-year postadoption period, there were 35,861 and 34,982 visits, respectively. These visits accounted for 2.4% of all ED visits across telepsychiatry EDs and control EDs in the pre- and postadoption periods. Patient characteristics for visits at telepsychiatry EDs and control EDs were similar in the preadoption period. However, modest differences were noted in the fraction of ED visits with a primary diagnosis of suicidal ideation and intentional self-injury: 7% and 6% of ED visits at telepsychiatry EDs and control EDs, respectively, in the preadoption versus 14% and 11%, respectively, in the postadoption period.
| 3 years (preadoption period) | 2 years (postadoption period) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Telepsychiatry EDs (N=50,420) | Control EDs (N=51,445) | Telepsychiatry EDs (N=35,861) | Control EDs (N=34,982) | |||||||
| Characteristic | N | % | N | % | Std. diff.a | N | % | N | % | Std. diff.a |
| Total N of ED visits (all diagnoses) | 2,121,688 | 2,106,154 | 1,517,705 | 1,476,989 | ||||||
| Sex | ||||||||||
| Female | 27,832 | 55 | 26,881 | 52 | .05 | 19,292 | 54 | 18,343 | 52 | .03 |
| Male | 22,588 | 45 | 24,564 | 48 | .05 | 16,569 | 46 | 16,639 | 48 | .03 |
| Age group | ||||||||||
| 18–29 | 3,436 | 7 | 3,328 | 6 | .01 | 2,344 | 7 | 2,365 | 7 | .01 |
| 30–39 | 7,645 | 15 | 6,856 | 13 | .05 | 5,666 | 16 | 5,145 | 15 | .03 |
| 40–49 | 8,994 | 18 | 9,214 | 18 | .01 | 6,249 | 17 | 5,943 | 17 | .01 |
| 50–59 | 10,364 | 21 | 10,872 | 21 | .01 | 7,373 | 21 | 7,065 | 20 | .01 |
| 60–64 | 3,553 | 7 | 3,574 | 7 | .01 | 2,772 | 8 | 2,905 | 8 | .02 |
| ≥65 | 16,428 | 33 | 17,601 | 34 | .05 | 11,457 | 32 | 11,559 | 33 | .02 |
| Original reason for Medicare enrollment | ||||||||||
| Older age | 12,302 | 24 | 13,094 | 25 | .04 | 8,226 | 23 | 8,277 | 24 | .02 |
| Disabilityb | 38,118 | 76 | 38,351 | 75 | .04 | 27,635 | 77 | 26,705 | 76 | .02 |
| Dual enrollment in Medicaid | 33,352 | 66 | 34,819 | 68 | .02 | 24,328 | 68 | 24,287 | 69 | .03 |
| Primary diagnosisc | ||||||||||
| Anxiety disorder | 13,705 | 27 | 13,244 | 26 | .02 | 9,926 | 28 | 9,048 | 26 | .04 |
| Mood disorder | 15,082 | 30 | 15,336 | 30 | .01 | 8,843 | 25 | 9,175 | 26 | .04 |
| Schizophrenia and other psychotic disorders | 14,432 | 29 | 16,423 | 32 | .07 | 9,508 | 27 | 10,693 | 31 | .09 |
| Suicide and intentional self-inflicted injury | 3,318 | 7 | 2,791 | 6 | .05 | 4,925 | 14 | 3,734 | 11 | .09 |
| Otherd | 3,883 | 8 | 3,651 | 7 | .03 | 2,659 | 7 | 2,332 | 7 | .03 |
| ≥1 inpatient stays with a mental illness primary diagnosis in 90 days prior to ED visit | 10,286 | 20 | 11,835 | 23 | .05 | 8,111 | 23 | 8,617 | 25 | .05 |
| ≥1 ED visits with a mental illness primary diagnosis in 90 days prior to ED visit | 11,278 | 22 | 10,554 | 21 | .04 | 9,464 | 26 | 8,196 | 23 | .07 |
a
Standardized difference between patients who presented with mental illness to telepsychiatry EDs versus matched control EDs, ≤.07 for each patient characteristic, below the .10 threshold signifying minimal difference consistent with established methodology.
b
Beneficiaries with end-stage renal disease are included in this category.
c
Mental illnesses were grouped with the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM and ICD-10-CM diagnosis (see online supplement for details).
d
Low-volume diagnoses were grouped into a single category (see online supplement for details).
Differential Change in Adjusted Outcomes at Telepsychiatry EDs and Control EDs
The admission rate to a psychiatric bed in the preadoption period was 20.2% at telepsychiatry EDs and 23.8% at control EDs. The admission rate increased by 3.0 percentage points at telepsychiatry EDs and decreased by 1.2 percentage points at control EDs (Table 3 and Figure 1). After the analysis controlled for patient characteristics, there was a net differential increase in admission rate to a psychiatric bed of 4.3 percentage points at telepsychiatry EDs (Table 3). In contrast, telepsychiatry adoption was associated with a differential decrease in admission to a medical-surgical bed (−2.0 percentage points). After the analysis controlled for changes in patient characteristics, there was a differential increase of 2.3 percentage points in admission of any type (95% confidence interval [CI]=1.5%–3.1%, p<0.001).
| Outcome and ED | Total N of ED visits (both periods) | 3 years (pre- adoption period) (% or $) | 2 years (post- adoption period) (% or $) | Pre- post change (% or $) | |||
|---|---|---|---|---|---|---|---|
| Difference in differencesa | |||||||
| % or $ | 95% CI | p | |||||
| ED visits resulting in admission or transfer to a psychiatric specialty bed | 4.30 | 3.5, 5.0 | <.001 | ||||
| Telepsychiatry | 86,281 | 20.2 | 23.2 | 3.0 | |||
| Control | 86,427 | 23.8 | 22.7 | –1.2 | |||
| ED visits resulting in admission or transfer to a medical-surgical bed | –2.00 | –2.8, –1.3 | <.001 | ||||
| Telepsychiatry | 86,281 | 20.3 | 19.4 | −.9 | |||
| Control | 86,427 | 15.3 | 16.5 | 1.1 | |||
| Prolonged ED length of stayb,c | 3.00 | 1.8, 4.1 | <.001 | ||||
| Telepsychiatry | 17,156 | 7.6 | 10.5 | 2.9 | |||
| Control | 16,828 | 9.6 | 9.6 | −.1 | |||
| Institutional spending on mental illness 90 days from ED visit (M±SD $)d | 292±107 | 83, 501 | <.01 | ||||
| Telepsychiatry | 86,281 | 6,939 | 7,734 | 795 | |||
| Control | 86,427 | 7,542 | 8,045 | 503 | |||
| Mortality in 90 days after ED visit | .20 | –.1, .4 | .27 | ||||
| Telepsychiatry | 86,281 | 2.0 | 1.9 | −.1 | |||
| Control | 86,427 | 2.2 | 1.9 | −.3 | |||
| Mental illness outpatient follow-up care in 2 weeks after ED dischargeb | −.70 | –3.3, 1.9 | .54 | ||||
| Telepsychiatry | 9,494 | 22.9 | 25.4 | 2.6 | |||
| Control | 8,245 | 21.3 | 24.6 | 3.3 | |||
a
Difference-in-difference estimates adjusted for changes in patient characteristics.
b
For these outcomes, a smaller sample was analyzed, because data were available only for the 20% random sample of Medicare beneficiaries.
c
Excessive length of stay defined as an ED stay that exceeded two midnights.
d
Institutional spending encompassed payments to hospitals for inpatient and ED care incurred during the 90 days from ED presentation.
Telepsychiatry adoption was associated with a differential increase in the fraction of ED visits with prolonged ED LOS (3.0 percentage points, 95% CI=1.8%–4.1%) and mental illness institutional spending ($292, 95% CI=$83–$501) (Table 3). In a sensitivity analysis, we measured changes in total institutional spending regardless of the primary diagnosis and found a similar differential increase at telepsychiatry ED hospitals ($352, 95% CI=$66–$639).
No difference was noted between telepsychiatry EDs and control EDs in 2-week outpatient follow-up visits and 90-day mortality. Our sensitivity analysis found no substantive differences between the unadjusted versus adjusted differential changes.
In subgroup analyses, a greater increase in admissions to a psychiatric bed was noted for patients with severe mental illness, compared with those without severe mental illness (5.3 versus 3.8 percentage points, p<0.001) (Table 4). In addition, for patients with severe mental illness, a greater decrease in admission to a medical-surgical bed was noted (−2.4 versus –1.9 percentage points, p<0.001), along with a greater increase in prolonged ED LOS (5.4 versus 2.5 percentage points, p<0.001) and a greater increase in mental illness spending ($700 versus $216, p=0.02).
| Outcome and presence of severe mental illnessa | Total N of ED visits (both periods) | Pre-post change | Difference in differencesb | |||
|---|---|---|---|---|---|---|
| Telepsychiatry EDs (% or $) | Control EDs (% or $) | % or $ | 95% CI | p | ||
| ED visits resulting in admission or transfer to a psychiatric specialty bed | ||||||
| No | 133,859 | 3.10 | −.80 | 3.80 | 3.1, 4.6 | <.001 |
| Yes | 38,849 | 2.70 | –2.60 | 5.30 | 3.8, 6.8 | <.001 |
| ED visits resulting in admission or transfer to a medical-surgical bed | ||||||
| No | 133,859 | −.50 | 1.50 | –1.90 | –2.7, –1.2 | <.001 |
| Yes | 38,849 | –2.60 | −.20 | –2.40 | –4.2, –.5 | <.001 |
| Prolonged ED length of stayc,d | ||||||
| No | 26,569 | 2.70 | .20 | 2.50 | 1.3, 3.8 | <.001 |
| Yes | 7,424 | 4.40 | –1.00 | 5.40 | 2.3, 8.4 | <.001 |
| Institutional spending on mental illness 90 days from ED visit (M±SD $)e | ||||||
| No | 133,859 | 817 | 601 | 216±105 | 9, 423 | .04 |
| Yes | 38,849 | 776 | 76 | 700±302 | 109, 1292 | .02 |
| Mortality in 90 Days after ED visit | ||||||
| No | 133,859 | −.10 | −.30 | .20 | –.1, .5 | .23 |
| Yes | 38,849 | .00 | .00 | .00 | –.4, .4 | .96 |
| Mental illness outpatient follow-up care in 2 weeks after ED dischargeb | ||||||
| No | 15,338 | 3.20 | 3.80 | −.60 | –3.3, 2.0 | .6 |
| Yes | 2,401 | .20 | –1.30 | 1.50 | –6.3, 9.3 | .7 |
a
More severe mental illness defined as having one or more inpatient stays in 90 days prior to ED visit.
b
Difference-in-difference estimates adjusted for changes in patient characteristics.
c
For these outcomes, a smaller sample was analyzed, because data were available only for the 20% random sample of Medicare beneficiaries.
d
Excessive length of stay defined as an ED stay that exceeded two midnights.
e
Institutional spending encompassed payments to hospitals for inpatient and ED care incurred during the 90 days from ED presentation.
Discussion
In the first large national examination of telepsychiatry in EDs, we found that telepsychiatry adoption was associated with fewer medical-surgical admissions, increased psychiatry admissions, and prolonged ED LOS.
Our finding that the overall admission rate (medical-surgical or psychiatric bed) was higher is consistent with one prior evaluation of telepsychiatry in 13 critical access hospitals (8, 9). However, it conflicts with a study of 30 rural South Carolina EDs that found an overall decrease in admissions (6) and another study of 18 New York EDs that reported no change in admissions (30) (both studies did not differentiate by type of admission). It is unclear what drives the conflicting findings. One potential driver may be differences in the patient populations, because other studies did not focus on ED visits among Medicare fee-for-service beneficiaries. Another possibility could be differences in the quality of consultation or biases in the selection of patients to receive a telepsychiatry consultation. For example, the South Carolina study was limited to EDs being served by one telepsychiatry group and to patients who received a telepsychiatry consultation.
One potential underlying mechanism for the changes we observed is that consulting psychiatrists may have been more likely to recommend admission to a psychiatric bed. We found a slight differential increase in diagnoses of suicidal ideation and intentional self-injury at the telepsychiatry EDs. It is possible that the consulting psychiatrists identified more patients at risk of harming themselves or requiring more intensive psychiatric care, leading to a larger fraction of patients with prolonged ED LOS and increases in spending. Given national shortages of inpatient psychiatric beds (31), finding an inpatient bed for a patient with mental illness could take time. These patients may otherwise have been discharged from the ED, indicating that increased admissions to a psychiatric bed may reflect a higher quality of care in EDs with telepsychiatry. We believe that the decrease in the rate of medical-surgical admissions is a mark of higher-quality care.
Telepsychiatry may be beneficial financially for local EDs. From the perspective of an administrator at an acute care hospital, having fewer patients with psychiatric diagnoses who are being boarded as medical admissions may be preferable, given limited bed supply, and psychiatric admissions could be viewed as less lucrative than medical-surgical admissions. Also, given the low number of mental illness visits per week at many EDs, it may not be financially feasible to have in-person psychiatric capacity, and telepsychiatry may be the only option. Nevertheless, the increase in ED LOS and admission rates may lead to overcrowding in EDs.
We found no differential change in outpatient follow-up care. Further changes may be needed to help local ED providers initiate outpatient follow-up between the patient and a local mental health provider.
Our analysis had several limitations. First, ED LOS was measured as midnights in the ED, because claims data did not provide admission and discharge times. Thus our analysis captured prolonged ED LOS. Second, we knew only that telepsychiatry was available in an ED but did not know how it was used (e.g., during weekends or for 24 hours a day) and the frequency of its use. We believe that this “intention-to-treat” framework was less likely to have been biased by the selection of patients to receive a telepsychiatry consultation and captured the population-level question of what impact adoption of telepsychiatry has on ED patterns of care. Third, our analysis was unable to capture the extent to which in-person psychiatric care was available in each ED. The AHA survey provides only a yes-no question about the availability of such care. Fourth, our analysis did not include measures of whether telepsychiatry improved clinical outcomes for patients presenting with acute mental illness. Fifth, our sample of 134 EDs across 22 states was a convenience sample, and we do not know how results would generalize to all EDs with telepsychiatry. Sixth, we did not know the characteristics of psychiatrists involved in providing these services, because these data were not provided. Seventh, our study period included the transition from ICD-9 to ICD-10. Prior research shows an increase in identification of intentional self-injury diagnoses following this transition (32). Finally, our findings were limited to Medicare beneficiaries and might not be generalizable to other populations, such as those with commercial insurance or those covered by Medicaid but not dually eligible for Medicare (33).
Conclusions
Telepsychiatry adoption was associated with fewer medical-surgical admissions, increased psychiatry admissions, and prolonged ED LOS. These changes may reflect higher quality of care if consulting psychiatrists identified more patients requiring inpatient psychiatric care who would have otherwise been discharged. Future work should assess the impact of telepsychiatry on quality of care, including longer-term patient outcomes.
Acknowledgments
The authors thank Rebecca Shyu, B.S., for contributing to manuscript preparation and data analysis.
Supplementary Material
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Information & Authors
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History
Received: 12 March 2021
Revision received: 27 April 2021
Accepted: 27 May 2021
Published online: 19 August 2021
Published in print: April 01, 2022
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Competing Interests
The authors report no financial relationships with commercial interests.
Funding Information
This project was supported by grant K23 AG058806-01 from the National Institute on Aging and by grants R01 MH112829-01 and T32MH019733 from the National Institute of Mental Health.
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