Mental health

Evaluatingtheeffectivenessofcommunityandhospitalmedicalrecordintegrationonmanagementofbehavioralhealthintheemergencydepartment.

REQUIREMENTS 

1. Select a scholarly nursing or research article (published within the last five years) related to mental health nursing, which includes content related to evidence‐based practice. *** You may need to evaluate several articles before you find one that is appropriate. *** 

2. Ensure that no other member of your clinical group chooses the same article. Submit the article for approval. 

Write a 2–3 page paper (excluding the title and reference pages) using the following criteria. Your answers should be below each question not a discussion essay which is mixed up. Ensure that you write 550 or more words. Not less. 

a. Write a brief introduction of the topic and explain why it is important to mental health.  

b. Cite statistics to support the significance of the topic. 

c. Summarize the article; include key points or findings of the article. 

d. Discuss how you could use the information for your practice; give specific examples. 

e. Identify strengths and weaknesses of the article. 

f. Discuss whether you would recommend the article to other colleagues. g. Write a conclusion. 

4. Paper must follow APA format. Include a title page and a reference page; use 12‐point Times Roman font; and include in‐text citations (use citations whenever paraphrasing, using statistics, or quoting from the article). Please refer to your APA Manual as a guide for in‐text citations and sample reference pages

Evaluating the Effectiveness of Community
and Hospital Medical Record Integration
on Management of Behavioral Health
in the Emergency Department

Stephanie Ngo, MD
Mohammad Shahsahebi, MD, MBA
Sean Schreiber, MSED, LPC
Fred Johnson, MBA
Mina Silberberg, PhD

Abstract

This study evaluated the correlation of an emergency department embedded care coordinator
with access to community and medical records in decreasing hospital and emergency
department use in patients with behavioral health issues. This retrospective cohort study
presents a 6-month pre-post analysis on patients seen by the care coordinator (n=524). Looking
at all-cause healthcare utilization, care coordination was associated with a significant median
decrease of one emergency department visit per patient (p G 0.001) and a decrease of 9.5 h in
emergency department length of stay per average visit per patient (pG0.001). There was no
significant effect on the number of hospitalizations or hospital length of stay. This intervention
demonstrated a correlation with reducing emergency department use in patients with behavioral
health issues, but no correlation with reducing hospital utilization. This under-researched
approach of integrating medical records at point-of-care could serve as a model for better
emergency department management of behavioral health patients.

Address correspondence to Mohammad Shahsahebi, MD, MBA, Department of Community and Family Medicine, Duke
University, Durham, NC, USA. Phone: (919) 342-8845; Email: mo.s@duke.edu.

Stephanie Ngo, MD, Department of Community and Family Medicine, Duke University, Durham, NC, USA.
Fred Johnson, MBA, Department of Community and Family Medicine, Duke University, Durham, NC, USA.
Mina Silberberg, PhD, Department of Community and Family Medicine, Duke University, Durham, NC, USA.
Mohammad Shahsahebi, MD, MBA, Northern Piedmont Community Care, Durham, NC, USA. Phone: (919) 342-8845;

Email: mo.s@duke.edu
Fred Johnson, MBA, Northern Piedmont Community Care, Durham, NC, USA.
Sean Schreiber, MSED, LPC, Alliance Behavioral Health, Raleigh, NC, USA.

Journal of Behavioral Health Services & Research, 2017. 651–658. c)2017 National Council for Behavioral Health. DOI
10.1007/s11414-017-9574-7

Evaluating the effectiveness of community NGO ET AL. 651

Introduction

Background

Patients with behavioral health issues often require more resource-intensive care and are more
likely to be frequent users of health services.1–7 Brennan et al. found that patients with at least one
primary psychiatric visit to the emergency department (ED) were 4.6 times more likely than those
without a primary psychiatric visit to be classified as high utilizers of health services overall, and
that on average, high utilizers with a primary psychiatric visit had a significantly higher number of
ED visits than non-psychiatric high utilizers.7

Furthermore, Bboarding^ of patients with behavioral health issues has become a serious problem
for patients who require psychiatric attention and has overburdened EDs that already struggle with
overcrowding and lack of sufficient resources.1,8,9 Boarding is often defined as the length of stay
(LOS) in the ED greater than 4h after medical clearance and is normally due to awaiting placement
at another inpatient facility.8,9 EDs are poorly equipped at providing mental healthcare, and
boarding leads to substandard quality of patient care, poor patient and provider satisfaction, and
lost hospital revenue and negatively impacts patient throughput. 1,3,8–10.

Patients with behavioral health issues have been disproportionately affected by boarding due to a
national decrease in psychiatric inpatient facilities and lack of appropriate increase in community-
based resources.1–3,10 Patients with behavioral health needs are a vulnerable population who can be
particularly difficult to serve because of their complex needs and scarcity in resources for their
care. The quality of care that these patients receive can potentially improve with better integration
and coordination among medical services, mental health care, and community resources. Case
management is defined as Ba collaborative process of assessment, planning, facilitation, care
coordination, evaluation, and advocacy for options and services to meet an individual’s and
family’s comprehensive health needs through communication and available resources to promote
quality, cost-effective outcomes,^ and can be utilized in initiatives focused on coordinating patient
care.8,11 In studies targeting high utilizer populations, the results have been mixed but generally,
case management and care coordination has been found to reduce hospital costs, decrease
healthcare utilization, and improve clinical (e.g., alcohol and substance use, psychiatric symptoms,
mortality) and social outcomes (e.g., homelessness, insurance status, social security support).12–14

With the development of new information technology systems, there is the potential for case
managers and care coordinators to have simultaneous access to a broader range of patient data than
has been available in the past and, therefore, be more effective. This specific intervention of
information sharing has not been studied in depth. Though integrated access may not be a novel
intervention, many barriers such as privacy concerns and EHR fragmentation have prevented
broadscale implementation, thus limiting the quantification of its impact. This paper reports an
evaluation of an intervention that allowed a case manager to have integrated access to multiple
community stakeholder records to improve care coordination and to alleviate the psychiatric
boarding burden and frequent ED use often associated in patients with behavioral health issues.
The goal of this study was to evaluate whether an embedded ED care coordinator with access to
multiple electronic health records (EHRs) is effective in reducing hospital and ED utilization in
patients with behavioral health issues using a pre-post analysis.

Methods

Study Setting and Program Description

Duke University Hospital (DUH), a part of the Duke University Health System (DUHS), is a
teaching hospital and tertiary and quaternary care hospital with 938 beds. It is the designated Level
1 Trauma Center for Durham County. The ED has approximately 65,000 visits per year.

652 The Journal of Behavioral Health Services & Research 45:4 October 2018

DUHS is the predominant medical provider in Durham County and the sole provider of
emergency and inpatient care. Like many insurance entities, North Carolina Medicaid separates
behavioral healthcare from traditional medical care. As a result, few patients receive the totality of
their care within one health system or EHR.

A collaboration was developed in Durham, NC, between Alliance Behavioral Healthcare (ABH),
a community mental health managed care organization; North Piedmont Community Care (NPCC),
an organization owned and operated by Duke Health System and one of Community Care North
Carolina (CCNC) networks (the North Carolina Medicaid medical home and population health
management organization); and DUHS. A care coordinator, funded and employed collectively by
these entities was embedded into the DUH ED from February 2013 to April 2014. Of note, the
position was filled again in July 2014 and the care coordinator continues to provide services at the
DUH ED. The program has since been expanded to include pediatric ED patients. Patients with
behavioral health needs who visited the DUH ED and were referred to the ED psychiatry team
received services from the care coordinator as part of the standard of care.

At the highest level, patients who receive services from a provider within the Alliance network
range from 3years old and up are either Medicaid eligible or are considered indigent, defined by
Alliance as at or below 300% of the federal poverty level. In order to receive services beyond an
assessment or psychological testing, during the time of the study, they must have a behavioral
health diagnosis under the International Classification of Diseases, 9th Revision (ICD-9) of 219 to
317. If a consumer was previously served in the care coordination program, in addition to a
behavioral health diagnosis, including intellectual and developmental disabilities, they would need
to have a history of crisis service utilization, a recent history of incarceration, and a recent history
of inpatient psychiatric services, pregnancy, and substance abusing or enrolled in the Innovations
waiver, meaning the individual’s functioning made them eligible for an institutional level of care in
an intermediate care facility.

The care coordinator had traditional case management duties, such as making community and
medical referrals, assisting with inpatient or community placement, and coordinating appropriate
follow up. However, this position was unique in that the care coordinator was able to enhance
patient care by accessing the separate EHRs and claims data of ABH, CCNC, and DUHS in order
to give ED providers information regarding patients’ outpatient providers, current medications,
community resources, etc. This can be especially important for patients who are in active
psychiatric crisis and are unable or unwilling to provide a history. Therefore, the care coordinator
was poised to Bconnect the dots^ when providers were unfamiliar with the care a patient was
receiving in the community.

The goal of the care coordinator was to act as a bridge between the different community and
medical entities. By having an understanding of these different entities with access to their separate
records, the care coordinator aimed to improve the ED team’s ability to provide care and determine
the most proper patient disposition, which would then translate to increased quality of care and
efficiency in serving patients.

The data accessible on the DUH medical record systems included medical notes, labs, imaging,
and other studies done in encounters with DUHS. Many patients saw psychiatric providers outside
of DUHS, so these records were not available to the ED psychiatric providers. The additional data
that the care coordinator had access to included these patient assessments, outside hospital
discharge summaries, and other psychological testing.

Study Design

This study was a retrospective, observational cohort study using patients as their own controls
and was reviewed and approved by the Institutional Review Board of Duke University. Approval
was also granted by Alliance Behavioral Healthcare.

Evaluating the effectiveness of community NGO ET AL. 653

Data were obtained via Duke Enterprise Data Unified Content Explorer (DEDUCE), a web-
based research query tool and centralized database that collects encounter-level data from hospitals
and clinics within DUHS. We did not obtain data from the outside community and hospital
providers or claim data from payers for the purposes of this evaluation.

DUHS, ABH, and NPCC worked collaboratively on this study.

Population

The cohort consisted of patients whom the care coordinator served as part of the Duke ED
psychiatry team (n=527). Since data collection predated the evaluation, there were some
discrepancies in how the data were recorded, although these were small. Patients who could not
be identified in the electronic medical record system via chart review using the recorded patient
information were removed from the analysis (n=3) giving a final sample size of n=524.

Measures and Outcomes

Integration was achieved by giving the care coordinator access to both EHRs. Unfortunately, the
two EHR systems were not allowed to directly interface or share information. Currently, providers
in the DUH ED do not have access to the majority of these patients behavioral health history at the
point-of-care. Though release of information is typically requested, the pace and 24-h nature of ED
care make it less likely that this information is available to the ED teams in a timely manner. The
primary benefit of the current, siloed system is protection of patient health data. This, however,
may negatively impact the ability to provide whole-person care.

DUH and Alliance employ similar strategies to ensure restricted access. The Alliance consumer
management system uses a role-based security system where users are granted access to parts of
the system based on their role within the agency. Care coordinators typically have access to all
clinical data within the system, unless there is a reason to restrict access to an identified consumer’s
record. The system has the ability to lockdown these records and limit access to specific users.
While the care coordination staff have access to clinical data, they are not permitted to see
consumer grievances or network provider details beyond information need to facilitate referrals. In
the DUH EHR, a password re-entry and reason must be given prior to accessing behavioral health
records. Both systems require users to change their password every 90days and require all users to
undergo annual privacy training and client rights training.

Data from patients seen by the care coordinator from February 2013 to April 2014 were utilized,
with their first recorded encounter with the care coordinator as the enrollment date. For each
patient, 6months of data before and after his/her enrollment date were collected, giving a total time
frame for the data of August 2012 to October 2014.

Data collected included demographic information (age, gender, race, and ethnicity); patient
comorbidity, as determined by the International Classification of Diseases, Ninth Revision (ICD-9)
codes in all diagnostic fields (primary and secondary diagnoses) in all ED and inpatient encounters in the
patient’s 12-month time frame; and encounter visit types (hospitalizations, ED visits, and LOS).

The primary outcomes examined were number of ED visits, number of inpatient hospitalizations,
ED length of stay (LOS) (measured in hours), and hospital LOS (measured in days). Length of stay
was averaged as opposed to calculated as a sum total time due to lack of LOS data for some
encounters.

Data Analysis

To assess the impact of care coordination on health utilization, a pre-post analysis was performed
comparing outcome measures in the 6months before and after the patients’ initial contact with the

654 The Journal of Behavioral Health Services & Research 45:4 October 2018

care coordinator (enrollment date). Wilcoxon signed-rank tests between the pre and post data were
utilized to obtain the median difference for each metric, reported with interquartile ranges (IQR)
due to lack of normality of data distribution. A probability p value of G0.05 was considered
significant. Statistical analysis was conducted using R 3.2.0 software package.

Results

During February 2013 to April 2014, the care coordinator served 527 patients, with a total of
524 patients included in the analysis. The cohort was predominantly male (59%) and Black/African
American (62%), and had a mean age of 40.3years (Table 1).

The most prevalent psychiatric diagnoses among this cohort were substance-related and
addictive disorders (58%); schizophrenia and other psychotic disorders (48%); depressive disorders
(47%); disruptive, impulse-control, and conduct disorders (30%); and bipolar disorders (28%)
(Table 2).

During the 6-month pre period, there was a range of 0–116 ED visits and 0–37 hospitalizations.
The 6-month pre-intervention medians were one hospitalization/patient, 0.5days for LOS of
hospitalization/patient, two ED visits/patient, and 15.4h for LOS of ED visit/patient. Analysis of
the 6-month pre-post all-cause healthcare utilization data demonstrated a strongly significant
median decrease of one ED visit per patient (pG0.001) and a decrease of 9.5 h in the emergency
department length of stay per average visit per patient (pG0.001) (Table 3). There was no
significant change in either median difference of hospitalizations (median = 0, p=0.17) or median
difference in hospital LOS (median = 0, p=0.21) (Table 3).

Discussion

The goal of this study was to assess the impact of a care coordinator with increased EHR access
on ED and hospital utilization. We found that there was an associated reduction in ED utilization
with a decrease in both number of ED visits and ED LOS. This is consistent with the majority of
studies that have looked at a variety of case management intervention strategies in reducing ED

Table 1
Demographic characteristics (n=524)

Number (%)

Age, mean 40.3±13.9
Male gender 309 (5%)
Race

Black/African American 325 (62%)
White/Caucasian 152 (29%)
Multiracial 15 (2.9%)
American Indian 4 (0.8%)
Asian 2 (0.4%)
Other/unknown/declined 26 (5%)

Ethnic group
Hispanic/Latino 19 (4%)
Other/Unknown/Declined 505 (96%)

Percentages may not add up to 100% due to rounding

Evaluating the effectiveness of community NGO ET AL. 655

use.12,13 The decrease in ED LOS may be related to the ability of the care team to more effectively
and efficiently plan disposition and follow up for patients not requiring immediate psychiatric
hospitalization. Fewer ED visits could be a result of better coordination of behavioral health care
leading to less frequent crises. Reductions in ED visits and LOS for this population can translate to
the ED’s ability to decrease overcrowding and increase patient throughput, which can ultimately
lead to a reduction in lost revenue, reduction in wait times, and improved delivery of care. This
intervention may assist in alleviating the psychiatric boarding burden that many EDs face.

However, it appears that the impact on healthcare utilization was limited to ED use. We found no
significant change in all-cause hospital utilization in either difference in pre-post hospitalizations
and hospital LOS. Fewer studies have looked at hospital utilization as an outcome than ED, but
most, like ours, report a lack of significant change.12,13 These results looked at all-cause
hospitalizations, not only psychiatric-related hospitalizations. Because the care coordinator targeted
patients specifically when they interacted with the psychiatry ED team and had minimal interaction
with medically related ED visits, the lack of change in hospitalizations may be due to patients that

Table 2
Psychiatric comorbidities

Percentage (n)

Substance-related and addictive disorders 58% (294)
Schizophrenia and psychotic disorders 48% (243)
Depressive disorders 47% (239)
Disruptive, impulse-control, and conduct disorders 30% (151)
Bipolar disorders 28% (143)
Trauma- and stressor-related disorders 22% (110)
Neurodevelopmental disorders 21% (109)
Anxiety disorders 19% (98)
Personality disorders 19% (96)
Neurocognitive disorders 10% (53)
Obsessive compulsive disorders 2% (11)
Somatic symptom and related disorders 1% (6)

Psychiatric comorbidities were determined using the psychiatric diagnosis classifications and associated ICD-9
codes in the Diagnostic and Statistical Manual of Mental Disorders (DSM) IV.17

Table 3
Median pre-post difference in health utilization

Pre Post Difference p value

Number of hospitalizations 1 (0 to 2) 1 (0 to 2) 0 (−1 to 1) 0.17
Hospital LOS (days) 0.5 (−1.7 to 2.7) 0.3 (−1.2 to 1.8) 0 (−1.5 to 1.5) 0.21
Number of ED visits 2 (1 to 3) 1 (0 to 2) −1 (−2 to 0) G0.001*
ED LOS (hours) 15.4 (2.3 to 28.5) 2.6 (−10.6 to 15.8) −9.3 (−36.5 to 17.9) G0.001*

BPre^ indicates the 6-month period before enrollment date; BPost^ indicates the 6-month period after
enrollment date. Results are from paired t tests (pre-post)
*Indicates statistical significance with p value G0.05

656 The Journal of Behavioral Health Services & Research 45:4 October 2018

were medically complex. This would be consistent with Billings et al.’s finding that high utilizer
patients have high rates of complex medical comorbidities.15

In addition, since hospitalization is more of a reflection on the severity of illness in a patient than
is ED use, it is possible that care coordination is more successful at redirecting ED utilization to
community and ambulatory resources and less effective at improving overall patient burden of
disease. A more intensive, community-based intervention may be more effective at impacting
burden of disease since this intervention is limited to only providing services when the patient
interacted with the ED.

Limitations

There were several limitations to this study.
The program evaluation began after the intervention had taken place and the intervention was

implemented as a new standard of care; therefore, patients were not separated into control or
intervention groups as part of the intervention design. Because patients were used as their own
controls, it is pertinent that we consider regression to the mean as a possible explanation for our
results. Regression to the mean is a commonly described phenomenon whereby extreme cases
represent a brief period of atypical activity that then eventually normalize. Studies looking at
patterns of ED use have observed regression to the mean, making it more difficult to be certain of
the validity of positive results.16 Our results would therefore be strengthened with the inclusion of a
comparable control group, most likely via propensity score methodologies, since it would be
ethically difficult to consent patients into intervention and control groups while in active
psychiatric crisis and since the care coordinator has been established as a standard of care.

This study was restricted in looking at provider-centered outcomes as opposed to patient-
centered outcomes, such as quality of life, patient satisfaction, and severity of disease. Decreasing
rates of ED use and hospitalizations imply improved health; however, it would be valuable to
include direct patient-centered metrics in future analyses.

Also, as a retrospective cohort study, we were unable to control for other potential confounders
and we cannot definitively relate the introduction of the care coordinator with increased EHR
access to the reduction in ED utilization.

Future Directions

It was initially intended to incorporate community and ambulatory level data into this study;
however, the ability to share data was delayed due to legal review and contractual obligation. Due
to this limitation, we were unable to include community and ambulatory level data as possible
metrics of continuity of care and impact on ambulatory service utilization. Such results would be
useful in gaining better insights into the scope of effect of the intervention. Further research is also
required to better understand the lack of impact on hospitalizations.

A qualitative component of the study would also provide a deeper understanding on the impact
of the addition of the care coordinator on the ED psychiatric team. Outcomes to consider in a
qualitative study include impact on ED workflow, provider satisfaction, and patient satisfaction.

Improved integration of the community and hospital EHRs may include getting more ED providers
access to the Alliance EHR. Ultimately, the idea solution would be the bilateral exchange of information
seamless between the two EHR platforms so that providers can efficiently work in one space.

Implications for Behavioral Health

Health care services have traditionally been siloed, requiring tremendous effort in order to share
information or work collaboratively. Institutional barriers perpetuate this and can be a significant

Evaluating the effectiveness of community NGO ET AL. 657

detriment to patient care. The care coordinator intervention sought to cross these boundaries and
work towards a more cohesive model of care for entities that collectively serve the same group of
patients. Patients with behavioral health issues are a particularly vulnerable group that may struggle
more in navigating a fragmented system, leading them to rely on acute settings such as the
emergency department when they fall into the gaps. The implementation of integrated services may
prove beneficial in closing these gaps and improving the quality of care these patients receive. This
study suggests that there is potential for such interventions, particularly for reducing ED utilization.
More research and implementation of innovative integration strategies are needed to better assess
this potential.

Compliance with Ethical Standards

Conflict of Interest The authors declare that they have no conflict of interest.

References

1. Nolan JM, Fee C, Cooper BA, et al. Psychiatric boarding incidence, duration, and associated factors in United States emergency
departments. Journal of Emergency Nursing. 2015;41(1):57–64. https://doi.org/10.1016/j.jen.2014.05.004.

2. Stephens RJ, White SE, Cudnik M, et al. Factors associated with longer length of stay for mental health emergency department
patients. The Journal of Emergency Medicine. 2014;47(4):412–419. https://doi.org/10.1016/j.jemermed.2014.04.040.

3. Nicks BA., Manthey DM. The impact of psychiatric patient boarding in emergency departments. Emergency Medicine International.
2012;2012:1–5. https://doi.org/10.1155/2012/360308.

4. Minassian A, Vilke GM, Wilson MP. Frequent emergency department visits are more prevalent in psychiatric, alcohol abuse, and dual
diagnosis conditions than in chronic viral illnesses such as hepatitis and human immunodeficiency virus. The Journal of Emergency
Medicine. 2013;45(4):520–525. https://doi.org/10.1016/j.jemermed.2013.05.007.

5. Locker TE, Baston S, Mason SM, et al. Defining frequent use of an urban emergency department. Emergency Medicine Journal : EMJ.
2007;24(6):398–401. https://doi.org/10.1136/emj.2006.043844.

6. Byrne M, Murphy AW, Plunkett PK, et al. Frequent attenders to an emergency department: a study of primary health care use, medical
profile, and psychosocial characteristics. Annals of Emergency Medicine. 2003;41(3):309–318. https://doi.org/10.1067/mem.2003.68.

7. Brennan JJ, Chan TC, Hsia RY, et al. Emergency department utilization among frequent users with psychiatric visits. Academic
Emergency Medicine : Official Journal of the Society for Academic Emergency Medicine. 2014;21(9):1015–1022. https://doi.org/
10.1111/acem.12453.

8. Alakeson V, Pande N, Ludwig M. A plan to reduce emergency room BBoarding^ of psychiatric patients. Health Affairs.
2010;29(9):1637–1642. https://doi.org/10.1377/hlthaff.2009.0336.

9. Misek RK, DeBarba AE, Brill A. Predictors of psychiatric boarding in the emergency department. The Western Journal of Emergency
Medicine. 2015;16(1):71–75. https://doi.org/10.5811/westjem.2014.10.23011.

10. Wharff EA, Ginnis KB, Ross AM, et al. Predictors of psychiatric boarding in the pediatric emergency department: implications for
emergency care. Pediatric emergency care. 2011;27(6):483–489. https://doi.org/10.1097/PEC.0b013e31821d8571.

11. Case Management Society of America. What is a case manager?. http://www.cmsa.org/Home/CMSA/WhatisaCaseManager/tabid/224/
Default.aspx. Accessed 13 Nov 2014.

12. Kumar GS, Klein R. Effectiveness of case management strategies in reducing emergency department visits in frequent user patient
populations: a systematic review. Journal of Emergency Medicine. 2013;44(3):717–729. https://doi.org/10.1016/
j.jemermed.2012.08.035.

13. Althaus F, Paroz S, Hugli O, et al. Effectiveness of interventions targeting frequent users of emergency departments: a systematic
review. Annals of Emergency Medicine. 2011;58(1):41–52.e42. https://doi.org/10.1016/j.annemergmed.2011.03.007.

14. Shumway M, Boccellari A, O’Brien K, et al. Cost-effectiveness of clinical case management for ED frequent users: results of a
randomized trial. The American Journal of Emergency Medicine. 2008;26(2):155–164. https://doi.org/10.1016/j.ajem.2007.04.021.

15. Billings J, Raven MC. Dispelling an urban legend: frequent emergency department users have substantial burden of disease. Health
affairs (Project Hope). 2013;32(12):2099–2108. https://doi.org/10.1377/hlthaff.2012.1276.

16. Mandelberg JH, Kuhn RE, Kohn M. Epidemiologic analysis of an urban, public emergency department’s frequent users. Academic
Emergency Medicine. 2000;7(6):637–646. https://doi.org/10.1111/j.1553-2712.2000.tb02037.x.

658 The Journal of Behavioral Health Services & Research 45:4 October 2018

https://dx.doi.org/10.1016/j.jen.2014.05.004

https://dx.doi.org/10.1016/j.jemermed.2014.04.040

https://dx.doi.org/10.1155/2012/360308

https://dx.doi.org/10.1016/j.jemermed.2013.05.007

https://dx.doi.org/10.1136/emj.2006.043844

https://dx.doi.org/10.1067/mem.2003.68

https://dx.doi.org/10.1111/acem.12453

https://dx.doi.org/10.1111/acem.12453

https://dx.doi.org/10.1377/hlthaff.2009.0336

https://dx.doi.org/10.5811/westjem.2014.10.23011

https://dx.doi.org/10.1097/PEC.0b013e31821d8571

http://www.cmsa.org/Home/CMSA/WhatisaCaseManager/tabid/224/Default.aspx

http://www.cmsa.org/Home/CMSA/WhatisaCaseManager/tabid/224/Default.aspx

https://dx.doi.org/10.1016/j.jemermed.2012.08.035

https://dx.doi.org/10.1016/j.jemermed.2012.08.035

https://dx.doi.org/10.1016/j.annemergmed.2011.03.007

https://dx.doi.org/10.1016/j.ajem.2007.04.021

https://dx.doi.org/10.1377/hlthaff.2012.1276

https://dx.doi.org/10.1111/j.1553-2712.2000.tb02037.x

Journal of Behavioral Health Services & Research is a copyright of Springer, 2018. All Rights
Reserved.

• Evaluating the Effectiveness of Community and Hospital Medical Record Integration on Management of Behavioral Health in the Emergency Department

Abstract
Introduction
Background
Methods
Study Setting and Program Description
Study Design
Population
Measures and Outcomes
Data Analysis
Results
Discussion
Limitations
Future Directions
Implications for Behavioral Health
Compliance with Ethical Standards
References