Running head: ADOLESCENT DEPRESSION

Implementation of Adolescent Depression Care Guidelines into the Electronic Health Record at a
Rural Pediatric Primary Care Clinic
Heather Momberg
Mentor: Diana Jacobson PhD, RN, PPCNP-BC, PMHS, FAANP
Arizona State University

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Abstract

Background: Healthcare providers are encouraged to prepare their practice to effectively
manage the care of mild to moderate adolescent depression. Cost-effective screening, diagnostic,
and newly developed pediatric primary care depression management guidelines have been
established. To integrate guidelines into practice, primary care providers (PCPs) must document
effectively to ensure a complete treatment plan is in place in the patient’s electronic health record
(EHR).
Intervention: Elements from a flowsheet were implemented into the EHR to promote thorough
assessment and documentation of care delivered to adolescents with depression.
Methods: An initial chart review was completed on patients diagnosed with depression. An
updated depression template was implemented within the EHR for six weeks. A follow-up chart
review was completed post-intervention to determine if documentation of elements from the
adolescent depression guidelines improved after the EHR update. Pre-intervention and postintervention surveys were delivered to PCP’s to understand their perspective on adolescent
depression management.
Outcomes: The chart review revealed that baseline PHQ-9 screenings were documented in 91%
(n=43) of the charts reviewed in the pre-intervention timeframe. Only 78% (n=7) of the charts
reviewed during post-intervention included PHQ-9 screenings. Early intervention treatment
options documented in the pre-intervention timeframe included education 100% (n=47),
medication prescriptions 53% (n=25), and psychotherapy referrals 18% (n=18). During postintervention, education 100% (n=9), medication prescriptions 78% (7), and psychotherapy
referrals 22% (n=7) were documented by the PCPs.

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Recommendation: The quality improvement project focused heavily on documentation
completed over a one year pre-intervention timeframe compared to a six-week post-intervention
timeframe. Further evaluation and chart review over the next year will provide a more adequate
comparison of documentation within primary care practice.

Keywords: adolescent depression, electronic health record, pediatric primary care, follow-up

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Implementation of Adolescent Depression Care Guidelines into the Electronic Health Record at a
Rural Pediatric Primary Care Clinic
Since becoming a national leading health indicator, access to behavioral health treatment
in America continues to be of high priority (Office of Disease Prevention and Health Promotion
[ODPHP], 2018). Behavioral health support in childhood and adolescence is vital to growth and
development. Adolescence is a time of challenges and transition to independence before entering
adulthood. Psychosocial development of the adolescent includes focusing thoughts in regards to
the future, exploration of personal identity, adjustment to physical appearance, and examination
of internal and external experiences, and values within peer relationships (Hay, Levin, Deterding,
& Abzug, 2016). Characteristics of the adolescent mood and behavior are linked to their brain
development. Supporting adolescents by identifying their needs at well-visits and when moods or
behaviors change will benefit their overall physical and mental health outcomes.
Background and Significance
Only 15% to 25% of children with psychiatric disorders receive the specialty care they
need (Tyler et al., 2017). Depression is diagnosed in 3.2% of the pediatric population aged 3-17
years, which reflects approximately 1.9 million children (Centers for Disease Control and
Prevention [CDC], 2018). Additionally, 12.8% of adolescent children aged 12-17years have had
at least one depressive episode (National Institute of Mental Health [NIMH], 2017). According
to Healthy People 2020 midcourse review, “Between 2007 and 2013, the suicide rate has
increased and adolescents with a major depressive episode have also increased and have moved
away from the baseline and 2020 target” (Healthy People 2020 as cited in Office of Disease
Prevention and Health Promotion [ODPHP], 2014, p. 2-3).

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United States (U.S.) Department of Health and Human Services (DHHS) (2017) reported
depression symptoms among high school students in California were at 32% compared with 31%
in the U.S. The National Institute of Mental Health (NIMH) (2017) reported “60.1% of
adolescents with major depressive episode did not receive treatment whereas 2.4% received
medication only, 19.6% were seen by a health professional only, and 17.9% were seen by a
health professional and treated with medication in 2017” (p. 7). O’Conner et al. (2016) reported
40% of US adolescents prescribed an antidepressant by a healthcare provider did not receive any
follow-up care in the three months follow the prescription and 68% did not receive follow up or
reassessment of depression symptoms in the three months following initial diagnosis (O’Conner
et al., 2016).
To decrease the number of acute emergency department visits, primary care providers are
encouraged to be knowledgeable regarding adolescent depression treatment and management
clinical guidelines (Costello et al., 2019). Upon completion of patient safety plans in one urban
pediatric psychiatry clinic, the utilization of clinical support tools within the EHR assisted PCPs
in the management of care as a method to improve adherence to clinical guidelines. The support
tools include updated templates, condition-specific order sets, and alerts or reminders to update a
patient’s behavioral health status (Reyes-Portillo, Lake, Kleinman, & Gould, 2018). Investment
in high quality treatment and developing transparent policies about EHR documentation of
depressive symptoms and diagnoses were one recommendation to improve adolescent depression
outcomes (Farley et al. 2020).
Depression Treatment Recommendations
The American Academy of Pediatrics (AAP) has released recommendations for the
assessment and treatment of mild to moderate adolescent depression in the primary care setting

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by PCPs (Cheung et al., 2018). The recommendations include active support or monitoring for
six to eight weeks after initial assessment reveals mild to moderate depression. If depressive
symptomology persists despite a period of active support, primary care management can issue a
referral to a mental health specialist or initiate medication and psychotherapy, monitor for
symptoms, and consider on-going mental health consultation. The cycle of treatment will
continue to be reassessed as needed, along with ongoing evaluations of safety (Cheung et al.,
2018).
Guidelines for the assessment and treatment of adolescent depression in primary care call
for early intervention and primary care management of adolescent depression. Primary care
providers are encouraged to seek education, training, and form support systems to increase
confidence and comfort adolescent depression in care delivery (Zuckerbrot et al., 2018). Factors
affecting treatment adherence by patients include medication side effects, difficulty getting
prescriptions filled, cost of treatment, low social support, lack of access, and negative attitudes
toward treatment (Stafford et al., 2019). In providing care for an adolescent population, it is
important to understand the best approach to provide access and build connections between
healthcare providers and patients.
Internal Evidence
Rural Health Pediatric Clinic in Eastern Sierra Region of California
In a rural California town, 3.5% of approximately 1050 adolescent’s ages 11-17 years old
have limited access to psychiatric specialty providers offering cognitive behavioral therapy
(McEvoy, 2019). As of October 2018, a newly implemented electronic health record (EHR) at
the Rural Health Pediatric Clinic (RHC) has impacted the ability to obtain specific data related to
depression screening, diagnosis, and treatment.

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Depression Screening Process
Following the America Academy of Pediatrics (AAP) preventive pediatric health care
recommendations, adolescents in the rural California clinic over age 12 years old are routinely
screened at every health visit for depression using the Patient Health Questionnaire (PHQ-9).
The PHQ-9 Questionnaire is composed of nine integrated questions adapted from the Diagnostic
and Statistical Manual of Mental Disorders (DSM-V), 5 th edition (DSM-V as cited in The Reach
Institute, 2018). The PHQ-9 is a validated screening tool used specifically to screen and assess
the severity of the depressive symptomology (Kroenke, Spitzer, & Williams, 2001). Results of
the PHQ-9 screening assist the primary care provider to determine the immediacy of care needs
and will support decision making when developing a treatment plan for each patient.
Usual Care Treatment of Depression
Currently, usual care for patients with a positive PHQ-9 screening or diagnosis of
depression involves subsequent appointments based on the needs of the child or adolescent.
Early intervention treatment is currently a provider specific decision without an active policy at
the rural health clinic to guide practitioners in the treatment of depression. Primary care
providers will order referrals for complex mental health services per need, begin active
monitoring and support, and begin medication therapy.
There are currently 13 mental health care providers within a thirty minute drive of the
Eastern Sierra community. Many of the behavioral health resources provided within the Eastern
Sierra mountain area are limited to income or need-based services and do not always meet the
needs of the children or adolescents who could benefit from psychotherapy services especially
cognitive behavioral therapy (McEvoy, 2019). A certified pediatric nurse provider from the rural

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health clinic offers primary care services at a school based clinic for patients and collaborates
with the school based counseling services provided by a counseling internship program.
Behavioral Health Service Gap
Behavioral health access is one problem translating to various settings across the country.
This creates difficulty in connecting patients to referrals with mental health specialty providers.
Primary care providers are often the first contact for patients with a newly diagnosed depressive
disorder. In one urban pediatric psychiatry clinic, the utilization of clinical support tools within
the EHR was used as a method to improve adherence to clinic guidelines. The support tools
include updated templates, condition-specific order sets, and alerts or reminders to update a
patient’s behavioral health status (Reyes-Portillo, Lake, Kleinman, & Gould, 2018). In a large
pediatric care network, 20% of charts reviewed from patients with elevated depression screening
lacked documentation of a follow-up response by their PCPs. Therefore, it is imperative to
streamline documentation of depressive symptoms and diagnoses to meet adolescent behavioral
health needs (Farley et al. 2020).
As a result of this gap in services, PCPs in the rural eastern sierra region have decided to
also explore online-based or technology-based services to better monitor the patients within their
clinics and documentation of the guidelines for adolescent depression in primary care (GLADPC) assessment and treatment recommendations within the EHR to improve primary care
provider adherence to clinical guidelines is the first step in improving care for adolescent patients
with depressive symptomology.
PICOT Question
In an effort to improve the assessment and treatment of adolescents with depressive
symptomology, the following PICOT question has been developed in order to search the

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literature for current evidence: In the (P) pediatric primary care setting, will implementation of
(I) GLAP-PC elements into the EHR compared to (C) usual care increase (O) provider adherence
to EBP recommendations over a 6-week timeframe?
Evidence Synthesis
Arizona State University’s (ASUs) online library provides access to several health
sciences databases. To research components of the PICOT question, three databases were used to
explore literature. Cumulative Index to Nursing and Allied Health Literature (CINAHL),
PUBMED, and PsycInfo were among the three databases searched. Settings prior to each search
were set to obtain publications released from June 2018 to April 2020 as this is the timeframe
after GLAD-PC recommendations were released. Articles were to be peer-reviewed, written in
the English language and if possible, the research study was to be conducted within the U.S.
Adolescent depression in pediatric primary care was the focus of each search. Key terms
searched included: adolescent depression, electronic health record, pediatric primary care, and
follow-up. Of the three search engines, 10 articles were extracted from 110 articles based upon
relevance to primary care, utilization of integrated behavioral health or collaborative care, and
review of the electronic health record. Appendix A, reveals in chronological order, two
randomized controlled trials, two quality improvement projects, and six retrospective reviews of
adolescent primary care practices that were critically appraised to provide evidence for this
Doctor of Nursing Practice (DNP) project.
Critical appraisal and synthesis of the evidence supported the integration of the PHQ-9 as
the most frequently used screening tool in all studies except for two (Appendix B). Of the two
studies that did not use the PHQ-9, Bai et al. (2018) chose the Center for Epidemiologic Studies
Depression Scale (CED- S) as the screening tool in their study. There was no specific screening

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tool mentioned in the Yang et al. (2019) study as it was based on patient navigation and care
collaboration. Instead a survey was used to determine provider’s perceptions of their system as
no specific screening tool was identified.
There were positive outcomes to utilization of collaborative care approaches, educational
methods, and EHR interventions to support the uptake of screening and in some instances,
management of adolescent depression. Strengths of the studies appraised identified six to twelve
month project timeframes within primary care settings and the use of validated screening tools.
Limitations of the studies include majority of sample sizes were of specific ethnicity and lack for
formality of when PHQ-9s were obtained at initial visits and follow-up.
All of the evidence used to support the DNP project included adolescent’s ages within the
12-18 year range and had both male and female participants. Post-intervention data collection
within the studies was completed at six to twelve month intervals.
Theory Application
To advance nursing scholarship and research, theoretical and implementation frameworks
assist in connecting concepts, guiding nursing practice as evidence is searched, appraised,
disseminated, and provide an outline for further research. Nursing theorist Ida Jean Orlando
developed the Nursing Process Discipline Theory, which encourages nurses to meet patients
where they are and provide immediate intervention (Orlando as cited in Nursing-theory, 2016).
To better understand the process of implementing evidence-based practice (EBP)
recommendations into primary care, the Model for Improvement and Plan-Do-Study-Act
(PDSA) framework illustrate the interventions within the project (Institute for Healthcare
Improvement [IHI], n.d.).
Nursing Theory

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Nursing Process Discipline Theory
The function of professional nursing, presenting behavior, immediate reaction, nursing
process discipline, and improvement are concepts of the Orlando’s Nursing Process Discipline
Theory (Orlando as cited in Nursing-theory, 2016) (Appendix C). Evidenced-based practice
recommendations are updated to encourage universal screening at all well child visits. This
aligns with the role of the nurse within Orlando’s model by encouraging PCPs to find and meet
the patient’s immediate needs as a function of professional nursing. A thorough assessment
assists the nurse in determining depression severity as the presenting behavior is relative to the
patient’s symptoms. Utilization of the GLAD-PC recommendations and care protocols or
algorithms, supports the nurse’s immediate care management plans. Upon determining pathways
of care related to the patient, the nursing process discipline supports the nurse in a collaborative
approach with the patient to discover treatment modalities and enact a plan to improve the
patient’s current situation. In the context of adolescent depression, this includes the treatment
and planning interventions such as education, medication, psychotherapy, and continued followup until the patient’s status is improved.
Innovation Model
Model for Improvement
The Institute for Healthcare Improvement (IHI) developed the Model for Improvement
([IHI], n.d.). The Model for Improvement (MFI) is based on the work of W. Edwards Deming
1982 System of Profound Knowledge and released by the associates in process improvement
(Committee on Practice and Ambulatory Medicine, n.d.). The model begins with three
fundamental questions: 1. What are we trying to accomplish?, 2.How will we know that a change
is an improvement?, and 3. What change can we make that will result in improvement? (IHI,

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n.d.) Foundational concepts include forming the team, setting aims, establishing measures,
selecting changes, and testing changes through the plan-do-study-act (PDSA) cycle (Appendix
D).
Methods
Protecting Patient and Provider Privacy
Arizona State University’s (ASU) internal review board (IRB) reviewed and approved
this quality improvement project and administrative support from the rural Californian clinical
site was received. The PCPs at the rural health clinic included two pediatric nurse practitioners,
two pediatricians, and one family medicine physician. Supportive staff within the practice
included medical assistants (MAs) and nurses. The clinic is part of a non-profit health network.
Updating the EHR, has been a goal for the PCPs within the organization to improve decision
making and tracking of higher risk patients receiving treatment.
To protect the privacy of patients and providers during the project period, de-identified
data was collected from the advanced practice health care providers at the pediatric clinic and
from the EHR that is used by the primary care pediatric practice. The pre-intervention chart data
collection included the medical records of 81 adolescents who presented to primary care for
symptoms of depression and anxiety. Of the 81 adolescents, 47 charts were reviewed as these
adolescents were diagnosed with depression only and without other mental health conditions,
including attention deficit hyperactivity disorder (ADHD) and anxiety. Post-intervention data
collection was obtained over six weeks from 23 medical records. Of the 23 patients, only nine
were diagnosed with depression only, without other mental health conditions. Due to the clinical
site located in a small rural community, demographic information on participants was not
obtained in this project to protect patient privacy.

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Project Design
All data that was collected was used to analyze the uptake of adolescent depression care
guidelines by the advance practice healthcare providers after the implementation of enhanced
EHR capabilities and an educational session. Chart reviews were completed within the facility on
a password protected computer. The charts were obtained based on the ICD-10 codes for anxiety
and depression. A chart review data collection tool, developed for this project, did not document
identifying information. The purpose of the chart review tool was to determine if the medical
record contained elements of the GLAD-PC recommendations at each office visit. Information
from the chart review could potentially educate primary care providers to recognize gaps in the
delivery of adolescent depression care within this clinic.
The DNP student designed an educational intervention specific to implementing GLADPC recommendations within an EHR system and provided education regarding the DNP project
and GLAD-PC recommendations to the primary care providers and staff at the clinic. An
educational protocol was developed to support healthcare providers as they gained knowledge
and skills in order to meet ongoing health care needs of adolescents with depressive
symptomology. The EHR was adapted to include an enhancement of the current EHR template
to include questions obtained from the DSM V diagnostic depression criteria, clinical indicators
to support treatment modalities, and a recommended plan of care template based on pre-selected
elements from the assessment.
A survey was sent to the pediatric PCPs before and after the EHR intervention template
change to better understand primary care provider perceptions about clinic processes currently in
place supporting care and management of adolescents diagnosed with depression. The initial
survey was handed out at an employee staff meeting and completed surveys were returned in a

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lockbox held in the provider’s office. The post-intervention survey was sent through an email
containing a link from an internet-based survey website. Survey Monkey™ has the ability to
make survey responses anonymous by not sharing the participant’s names, emails, or IP
addresses in their responses.
Practice Processes and System Changes
Implementation of GLAD-PC diagnostic assessment templates within the EHR was the
first step in transforming the care for adolescents with depression in this practice. Prior to
recruiting healthcare providers and delivering the educational intervention, the DNP student
provided input to develop an updated EHR documentation process, developed a care
management workflow, and helped to connect the clinic with access to referral resources.
Elements from the GLAD-PC guidelines and the data collection tool were introduced to the
clinicians in a brief educational discussion of the newly designed charting method. Once the
EHR templates were implemented, the DNP student was available over the next six weeks to
assist in trouble shooting and educating clinicians concerning the GLAD-PC guidelines, as
needed.
Timeline for DNP Project Implementation
Implementation of the DNP project began after IRB approval with a four-step process.
Within the planning phases, recruitment of participants for the project was obtained during a
scheduled meeting in the pediatric primary care office. A script was provided to introduce the
project and each potential advanced practice provider participant was provided with a consent
letter and given the option to participate. Completion of the pre-intervention survey indicated
willingness to participate. A chart review to obtain baseline EHR documentation currently

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recorded by pediatric PCPs related to assessment of adolescents with depressive symptomology
was completed.
On October 1st, 2018, the facility had begun using a new EHR system. The 81 preintervention charts reviewed were from office visits beginning October 1 st, 2018 until October
21st, 2019. Of the 81 charts, 47 were further identified as having been diagnosed exclusively with
depression. The chart review contained documentation from all of the primary care providers
within the pediatric primary care clinic. Elements from the GLAD-PC recommendations were
used to support newly enhanced EHR templates. The templates were approved by primary care
providers and implemented with help of the information technology (IT) department. Following
the implementation of the updated templates, data collection via the adolescent depression chart
review tool was completed over six weeks.
Two months after the educational intervention and the implementation of the new EHR
templates reflecting GLAD-PC guidelines, an anonymous post-evaluation survey was provided
for participants to complete. Pediatric primary care provider data was analyzed as a group, not by
the individual. Descriptive statistical analysis has been completed on the pre- and postintervention surveys obtained from PCPs within the rural pediatric health clinic.
Budget
There was no funding obtained to implement this DNP project. The cost to the practice
included time for the IT technician, IT nurse, front-office staff, medical assistants (MAs), and
providers to attend the educational intervention and the time to review and develop the template
with the student, and also the time providers took to complete the surveys. The SurveyMonkey™
program used to send surveys to providers was funded by the DNP student at a five dollar per
month subscription.

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Results

All data was analyzed using Intellectus Statistics™ to determine the effectiveness of the
education intervention and the EHR template enhancement. Summary statistics were calculated
for each interval and ratio variable, and frequencies and percentages were calculated for each
nominal variable split by each testing period.
Frequencies and Percentages
Pre-intervention (pre-test) data collection on 47 charts was completed using the chart
review tool. The chart review revealed that, the PHQ-9 depression screening tool was
documented in 91% (n = 43) of office visits. The post-intervention (post-test) phase was after the
educational session and EHR template implementation. Chart reviews using the chart review tool
were completed one week after the project completed. The PHQ-9 depression screening tool was
documented in 78% (n = 7) of the 23 post-test office visits. From the pre-test chart review, the
most frequently observed category of depression severity was mild (n = 10, 29%). For the
posttest chart review, the most frequently observed category of depression severity was mild (n =
4, 57%). Frequencies and percentages are presented in Table 3 (Appendix E).
PHQ-9
The charts were reviewed to determine if a PHQ-9 screen was documented within each of
the charts of those patients diagnosed with adolescent depression comparing the pre-intervention
chart review with the post intervention chart review. The result of the two-tailed independent
samples t-test was not significant based on an alpha value of 0.05, t(47) = 0.39, p = .696. This
finding suggests the mean number of PHQ-9 Screenings was not significantly different between
the Pretest and Posttest. The results are presented in Table 4 (Appendix F).
Depression Severity

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Depression severity is assessed as mild, moderate, moderately severe, and severe. For
pretest, the most frequently observed category of depression severity was mild (n = 10, 23%).
For Posttest, the most frequently observed category of depression severity was mild (n =
4, 44%). Overall pretest and posttest data showed the most frequently observed depression
severity was mild (33.3%), followed by severe (26.2%), moderately severe (21.4%), and
moderate (19%). The results are presented in a graph (Appendix G).
Early Intervention Treatment
Within the GLAD-PC recommendations, three early intervention treatment elements
include education, psychotherapy referrals, and medication prescribed within the initial visit of a
patient who is newly diagnosed with mild to moderate depression. Charts were reviewed to preand post-intervention to determine what treatment modalities were offered in the early
intervention office visit note.
Giving education about depression was documented by primary care provider clinical
notes on anticipatory guidance in charts of patients diagnosed with depression, pre-test (n =
47, 100%) and post-test, (n=9, 100%). From the chart review completed during pre-test data
collection, medication was prescribed in 53% of patients diagnosed with depression (n = 25).
From post-test data collection, medication was prescribed in 78% of the nine patients diagnosed
with depression (n = 7). From the chart review completed during pre-test data collection,
referrals to psychiatry or psychology were recommended in 59% of patients diagnosed with
depression (n = 26). From the chart review completed during post-test data collection, referrals
were recommended in 12% of patients diagnosed with depression (n = 2). The results are
presented in Table 4 (Appendix G).
Qualitative Survey Responses

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The posttest surveys were distributed to all providers but less than half were completed.
Due to the limited data within the surveys, the data reported is expressed from the suggestions
written by the PCPs for the open-ended survey questions. When asked to describe two or three
barriers that providers have had providing care to adolescent patients diagnosed with depression,
participants identified “a need for education regarding anticipatory guidance” and “more
behavioral health resources.” In post-test surveys, the participant responses identified “the need
for more local referral resources” and “it (the EHR template) makes it easier to chart- I don’t
forget to discuss things during visits.” Qualitative participant pre-survey results from the primary
care providers identified, “a need for education regarding anticipatory guidance” and “more
behavioral health resources.” Qualitative results from the survey are presented in Table 5
(Appendix H).
Primary care providers (n=2) who participated in the post-survey were asked, if the
current method of documentation better allowed them to follow GLAD-PC recommendations
and the results showed one provider “somewhat agreed” and another provider “agreed”. In the
post-intervention survey, two respondents agreed that the documentation method allowed them
to follow GLAD-PC recommendations. The enhanced EHR templates for documenting the
assessment and treatment of adolescent depression are one aspect of care the providers can
continue to use. Further evaluation over the next year, will provide a more in-depth assessment
and documentation of the assessment and treatment within this primary care practice. The results
are presented in Table 5 (Appendix I).
Discussion
Documentation within the EHR can help providers determine gaps and assess overall
health of the population they serve. The results from PHQ-9 screening data analysis show PHQ-9

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screenings are being completed within the range of 78% to 91% of office visits. The decrease in
post-intervention PHQ-9 documentation can be attributed to PHQ-9 screening tools not being
uploaded into the EHR or if screening was completed, it was not documented in the designated
template. An initial plan was to add the PHQ-9 to the vital signs section of the EHR but this
could not be completed at the time of EHR enhancement. There was a decrease in PHQ-9
screens documented after EHR depression template introduction and education intervention.
With the majority of adolescent depression patients diagnosed within the mild depression
category, it is promising that all of the patients despite the severity of their depression are
receiving a form of psychoeducation. The second highest depression severity identified overall
was moderately severe and severe, which aligns with rate of early intervention treatment
modalities prescribed or recommended, such as medication and psychotherapy referral orders
which were provided ordered in 78% of adolescents diagnosed with depression in the post-test
timeframe.
The newly designed EHR depression template included a way for providers to document
anticipatory guidance because it was built into the system. Therefore, the need for anticipatory
guidance education occurred and was met as evidenced by a posttest quote stating the new EHR
“makes charting easier by not forgetting to discuss things during visits.” Though the EHR
depression template included elements from the GLAD-PC recommendations, there is still a
perceived need for more behavioral health services by primary care providers.
Limitations
Limitations found in this quality improvement project include the unequal comparison of
pretest and posttest chart review time periods. Specifically, the pretest timeframe included data
from chart reviews of patients with depression seen over an entire year. Data collection was

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conducted over a six week time period after the introduction of the new EHR template and the
primary care educational session. The pediatric primary clinic had an EHR depression and
anxiety template in place prior to the intervention but it was not specific to the elements of the
GLAD-PC recommendations and was not identical to the EHR template used at post-test. Only
elements were that were congruent were analyzed. The pre-test PHQ-9 screening obtained from
the first chart review was not specific to the GLAD-PC guidelines of the assessment that should
occur at annual well visits. The charts provided for chart review were ones obtained from IT and
were specific to the ICD-10 diagnosis of depression. The office visits were often specific chief
complaint regarding adolescent depression. Therefore, a longer period for post-test chart review
should be completed to determine the rate of PHQ-9 screenings documented at annual well visits
by the providers.
Conclusion
Implications for Healthcare Providers
To obtain high-quality, coordinated care, behavioral health integration is becoming a
recommendation for all pediatric primary care clinics. Updated EHR systems improve the ability
for healthcare organizations to meet integrated patient-centered care goals (Agency for
Healthcare Research and Quality, n.d.). Primary care clinicians who manage adolescent
depression should pursue additional training regarding screening and diagnosis of the disorder.
Practice and systems changes are encouraged to be completed throughout the organization. This
includes front office staff training related to the importance of inputting screening within the
EHR, continued improvements to EHR documentation, and implementation of automated
tracking systems which could assist in overall behavioral health referrals within the facility
(Cheung et al., 2018). Evidence also recommends establishing linkages with mental health

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services within the facility, within the general local area, or establishing connections to
telemedicine in behavioral health providers are only available at a distance (Cheung et al., 2018).
Updating the EHR is one step in improving the management of adolescent depression in primary
care by preparing clinical practice with convenient ways to document adherence to evidence
based guidelines. However, more work has to be done to connect rural primary care practices
with certified behavioral health specialists when more severe cases of adolescent depression are
identified.

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References

Associates of Process Improvement. (n.d.). W. Edwards Deming. Retrieved from
https://www.apiweb.org/
Bai, S., Zeledon, L. R, D'Amico, E. J., Shoptaw, S., Avina, C., LaBorde, A. P., Anderson, M.,
Fitzpatrick, O. M., & Asarnow, J. R. (2018). Reducing health risk behaviors and
improving depression in adolescents: A randomized controlled trial in primary care
clinics. Journal Pediatric Psychology, 43(9). doi: 10.1093/jpepsy/jsy048.
Centers for Disease Control and Prevention. (2018). Data and statistics on children’s mental
health. Retrieved from https://www.cdc.gov/childrensmentalhealth/data.html
Cheung, A., Zuckerbrot, R. A., Jensen, P. S., Laraque, D., & Stein, R. E. K. (2018). Guidelines
for adolescent depression in primary care (GLAD-PC): Part II. Treatment and ongoing
management. Pediatrics, 141(3), 1-18. https://doi.org/10.1542/peds.2017-4082
Chowdhury, T. & Champion, J.D. (2020). Outcomes of depression screening for adolescents
accessing pediatric primary care-based services. Journal of Pediatric Nursing 2(52). doi:
10.1016/j.pedn.2020.02.036.
Committee On Practice And Ambulatory Medicine. (2017). Recommendations for preventive
pediatric health care. Pediatrics, 139(4). doi: 10.1542/peds.2017-0254
Costello, L. H., Suh, C., Burnett, B., Kelsay, K., Bunik, M., & Talmi, A. (2019). Addressing
adolescent depression in primary care: Building capacity through psychologist and
pediatrician partnership. Journal of Clinical Psychology in Medical Settings. Retrieved
from https://doi.org/10.1007/s10880-019-09680-w

ADOLESCENT DEPRESSION

23

Duffy, F., Sharpe, H., & Schwannauer, M. (2019). Review: The effectiveness of interpersonal
psychotherapy for adolescents with depression – A systematic review and meta‐
analysis. Child and Adolescent Mental Health,
doi: http://dx.doi.org.ezproxy1.lib.asu.edu/10.1111/camh.12342
Fallucco, E.M., James, L., Smotherman, C., & Greco, P. (2019). Impact of experiential training
with standardized patients on screening and diagnosis of adolescent depression in
primary care. Journal of Adolescent Health, 65(1), 57-62. doi:
10.1016/j.jadohealth.2018.12.022
Farley, A. M., Gallop, R. J., Brooks, E. S., Gerdes, M., Bush, M. L., & Young, J. F.
(2020). Identification and management of adolescent depression in a large pediatric care
network. Journal of Developmental Behavioral Pediatrics, 41(2), 85-94. doi:
10.1097/DBP.0000000000000750.
Harder, V. S., Barry, S. E., French, S., Consigli, A. B., & Frankowski, B. (2019). Improving
adolescent depression screening in pediatric primary care. Academy of Pediatrics, 19(8),
925-933. doi: 10.1016/j.acap.2019.02.014
Hay, W., Levin, M., Deterding, R., & Abzug, M. (2016). Current diagnosis and treatment
pediatrics (23RD Edition). United States: McGraw-Hill.
Higa-McMillan, C. K., Francis, S. E., Rith-Najarian, L., & Chorpita, B. F. (2016). Evidence base
update: 50 years of research on treatment for child and adolescent anxiety. Journal of
Clinical Child & Adolescent Psychology, 45(2), 91-113.
doi:10.1080/15374416.2015.1046177
Institute for Healthcare Improvement. (n.d.). Science of improvement: how to improve.
Retrieved from

ADOLESCENT DEPRESSION

24

http://www.ihi.org/resources/Pages/HowtoImprove/ScienceofImprovementHowtoImprov
e.aspx
Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001) The PHQ-9: Validity of a brief depression
severity measure. Journal of General Internal Medicine, 16(9), 606-613. Retrieved
from https://doi.org/10.1046/j.1525-1497.2001.016009606.x
McEvoy, C. (2019, January). Personal interview.
Melnyk, B. M., & Fineout-Overholt, E. (2015). Evidence-based practice in nursing and
healthcare: a guide to best practice (3rd edition). Philadelphia, PA: Lippincott Williams
& Wilkins.
National Institute of Mental Health (2017) Major depression. Retrieved from
https://www.nimh.nih.gov/health/statistics/major-depression.shtml
Nursing-Theory. (2016). Orlando's nursing process discipline theory. Retrieved from
https://nursing-theory.org/theories-and-models/orlando-nursing-process-disciplinetheory.php
Office of Disease Prevention and Health Promotion. (2018). Mental health. Retrieved from
https://www.healthypeople.gov/2020/data-search/midcourse-review/lhi
Office of Disease Prevention and Health Promotion. (2014). Healthy People 2020 leading health
indicators: Mental health. Retrieved from
https://www.healthypeople.gov/sites/default/files/HP2020_LHI_Mental_Hlth.pdf
REACH Institute. (2018). Guidelines for adolescent depression in primary care GLAD-PC
toolkit. Retrieved from http://www.gladpc.org
Simon, G. E., Johnson, E., Lawrence, J. M., Rossom, R. C., Ahmedani, B., Lynch, F. L., Beck,
A., Waitzfelder, B., Ziebell, R., Penfold, R. B., & Shortreed, S. M. (2018). Predicting

ADOLESCENT DEPRESSION

25

suicide attempts and suicide deaths following outpatient visits using electronic health
records. American Journal of Psychiatry, 175(10), 951-960. doi:
10.1176/appi.ajp.2018.17101167
Thompson, H., Faig, W., Gupta, N., Lahey, R., Golden, R., Pollack, M., & Karnik, N.
(2019). Collaborative care for depression of adults and adolescents: Measuring the
effectiveness of screening and treatment uptake. Psychiatric Services, 70(7), 604607. doi: 10.1176/appi.ps.201800257.
Tyler, E. T., Hulkower, R. L., & Kaminski, J. W. (2017). Behavioral health integration in
pediatric primary care: considerations and opportunities for policymakers, planners, and
providers. Milbank Quarterly, Retrieved
fromhttps://www.milbank.org/publications/behavioral-health-integration-in-pediatricprimary-care-considerations-and-opportunities-for-policymakers-planners-and-providers/
Valleley, R. J., Meadows, T. J., Burt, J., Menousek, K., Hembree, K., Evans, J., Gathje, R.,
Kupzyk, K., Sevecke, J.R., & Lancaster, B. (2020). Demonstrating the impact of
colocated behavioral health in pediatric primary care. Clinical Practice in Pediatric
Psychology, 8(1), 13-24. http://dx.doi.org.ezproxy1.lib.asu.edu/10.1037/cpp0000284
Wright, D. R., Haaland, W. L., Ludman, E., McCauley, E., Lindenbaum, J., & Richardson, L. P.
(2016). The costs and cost-effectiveness of collaborative care for adolescents with
depression in primary care settings: A randomized clinical trial. JAMA Pediatrics,
170(11), 1048-1054. doi: 10.1001/jamapediatrics.2016.1721
Yang, Y., Dillon, E. C., Li, M., Li, J., Erlich, K. J., Heneghan, A. M., & Becker, D. F.
(2019). Primary care provider utilization and satisfaction with a health system navigation

ADOLESCENT DEPRESSION

26

program for adolescents with behavioral health needs. Translational Behavioral
Medicine, 9(3), 549-559. doi: 10.1093/tbm/ibz049. PubMed PMID: 31094446.
Zuckerbrot, R. A., Cheung, A., Jensen, P. S., Stein, R. E. K., Laraque, D. (2018). Guidelines for
adolescent depression in primary care (GLAD-PC): Part I. Practice preparation,
identification, assessment, and initial management. Pediatrics, 141(3), 1-21. doi:
https://doi.org/10.1542/peds.2017-4081

ADOLESCENT DEPRESSION

27
Appendix A

Table 1
Evaluation Table
Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables
Studied and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Wright et al.
(2016). The
costs and costeffectiveness
of
collaborative
care for
adolescents
with
depression in
primary care
settings
Country:
U.S.

Collaborative
care
intervention
model

RCT

PC

IV: usual care

Cost and QALYs

N=101
(IG=50)
(uc=51)

DV: ROAD CC
intervention

Mean
incremental
CE ratio was
$18239 (95%
CI, dominant
to $24408)

LOE: level I

Purpose:
Evaluate costs
and costeffectiveness
of a
collaborative
care model for
tx of MDD in
PC.

STATA, Vers.
12
STATACorp,
LP

Strengths:
RCT, 12 month collaborative care
intervention.
limitations:
sample white race, single NW PC
Out of pocket payees excluded
from study.
Conclusions:
CCI is cost effective method to tx
Adol depression.

Funding:
NS
Bias:
NS

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

28

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables
Studied and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Bai et al.
(2018).
Reducing
Health Risk
Behaviors and
Improving
Depression in
Adolescents: A
Randomized
Controlled
Trial in
Primary Care
Clinics

Integrated
care model

Design:
RCT

N = 187

IV:
UC

HRBI

Stata Vers. 14
Multi-level
mixed-effects

AR:
6mos
IV: 89%
DV1:88%

Level of Evidence: LOE I

Country:
U.S.
Funding:
NS
Bias:
NS

Purpose:
To decrease
and prevent
HRB in
adolescents
selected for
depression,
and to
determine
whether this
approach
would have
benefits on
HRBs and
depression
levels.

Urban
PC

DV1:
BHI

t-tests
χ2 test

12 mo
IV:61%
DV1: 65%
DepSym:
decreased

Strengths:
Sample size 187, 12 months
follow-up
Weaknesses:
Urban, Hispanic/Latino
community, participation rate
low.
Conclusions:
Links between HRBs and
depressive sx support monitoring
for HRBs and depression in PC to
allow for effective intervention.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

29

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables
Studied and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Simon et al.
(2018)
Predicting
Suicide
Attempts and
Suicide deaths
following
outpatient
visits using
electronic
health record.

LASSO

Design:
Retrospective
review

SA: N= 24,233
SD: N=1240

IV:
SA
SD

10: PHQ-9 (ninth
question)
20: LASSO

GLMNET (27)

Risk scores in
top 5%
accounted for
43% of SA
and 48% SD.

Level of Evidence: LOE II

Country:
US
Funding:
unknown
Bias:
NS

Purpose:
To develop
and validate
models using
EHR to predict
suicide attempt
and suicide
death
following an
outpatient
visit.

Demographics:
M age: 46
f: 62%
Setting:
Primary care
Mental health
primary care

DV1:
Hx previous MH
disturbances i.e.,
Prior SA, MH & SUD
dx, medical dx,
psychiatric
medications
dispensed.
DV2: post-MH OV
DV2: post-PC OV

FOREACH
(28) packages
for the R
statistical
package Vers.
3.4.0

Strengths:
Large sample size, EHR data
from seven health symptoms,
multiple
Weaknesses:
Evidence open to adults >18yo.
Not specific to adolescent
population.
Conclusions:
Prediction models incorporating
both health
record data and responses to selfreport questionnaires
substantially outperform existing
suicide risk prediction tools.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

30

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables
Studied and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Yang et al.
(2019). PCP
utilization and
satisfaction
with a health
system
navigation
program for
adolescents
with BH
needs.

Integrated
BH model

Design:
Quality
improvement

Primary Care
Eligible PCPS
N = 411
Referring PCPs
N= 290

IV: PCC

Surveys
DV1:
OD - referrals
(dates, reasons,
referring PCPS),
and PII
DV2:
Demographics,
BH dx, Referrals
with HSNP
DV3: PCP
demographics

Descriptive
statistics

90% PCPs
rated
communicati
on with
HSNP above
average or
excellent.

Level of Evidence: LOE II

Country:
U.S.

Purpose:
Evaluate PCP
adoption of
BH navigation
program

PCP Demographics:
f- 72%
Pediatricians – 56%
>10years practice –
62%
Patient
demographics:
Pts. Referred
N= 3912
f- 60%
white – 43%
Asian – 28%
M age – 15.24

DV1: HSNP

SAS
Enterprise 5.1
and STATA
14.1

91% agreed
HSNP
enhanced
their practice

Strengths:
Decent Sample size, evaluation at
12Mo and 2.5 Yrs.
limitations:
Pt. outcomes, HSNP turnover
during
Conclusions:
Study reflects a need for BH
navigation services

Setting:
36 Bay area,
California PC
Inclusion:
Referral eligibility

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

31

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables
Studied and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Harder et al.
(2019)
Improving
adolescent
depression
screening in
Pediatric
Primary Care

IHI’s
Collaborative
Model for
Achieving
Breakthrough
Improvement

Design: QI

Sample:
N = 39 CHAMP PC
practices

IV:
PCPs

Chart review

Stata, version 15

Level of Evidence: LOE V

N = 1772 patients

DV1:
Screening method

improvement
in depression
screening at all
17 practices,
from 34% to
97% over 7
months.
Participating
practices had
3.5 times
greater odds
(95%
confidence
interval [CI],
1.14−10.98, P
= .03) of being
screened for
depression and
37.5 times
greater odds
(95% CI,
7.67−183.48,
P < .0005) of
being screened
with a
validated tool
than
adolescents
at control
practices,
accounting for
patient
characteristics

Country:
U.S.
Funding:
VDH
Bias:
ns

PDSA

Purpose:
1.) Increase
adolescent
depression
screening at
health
supervision
visits to at
least 95%,
and
2.) increase
initial plans
of care
among
those
screening
positive to
at least
95%.

PHQ-9

DV2: education
Setting:
Champ Network
PC in Vt.

MHPRI

Strengths:
Validated tools, sustainable
assessment, randomly sampled larger
medical record review.
Limitations: convenience sampling,
no participation for family medicine.
Conclusions:
Significant within practice increases
in adolescent depression screening
after a QI learning collaborative,
as well as in comparison with control
practices 1 year later.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION
Theory/
Conceptual
Framework

Citation
Fallucco et al.
(2019) Impact
of Experiential
Training With
Standardized
Patients on
Screening and
Diagnosis of
Adolescent
Depression in
Primary Care
Country:
USA
Funding:
SAMSHA
Grant #
5U79SM0599
39-04
Bias:
NS

NS

32

Design/
Method/
Purpose

Sample/Setting Major Variables

Measurement/
Instrumentatio
n

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Design:
retrospective
review
Purpose:
examine the
long-term
impact of PCP
training with
standardized
patients on
screening and
diagnosis of
adolescent
depression in
PC.

Sample:
N= 25 PCPs

outcome data
continuously
over a 12-month
period before and
a
12-month period
after intervention
rather than at
several
discrete points in
time.
Furthermore,
outcome indices
were
measured
objectively
through medical
record and billing
record
review

Descriptive
summaries of
frequencies
and
percentages.

Depression
screening rate
increased
significantly
after
training from
51% to 80%
of
adolescents
seen at wellvisits

LOE: Level V

Studied and
Their Definitions

Setting:
Florida PC
14 different
practices in the 2year study period

IV:
PCPs doing wellvisits
DV1:
Training

GLIMMIX
procedure in
SAS Windows
Version 9.4

Strengths
Use of validated screening tools.
Limitations
Pre-post study design limits the
ability to draw causal conclusions
study measured only one
treatment
option, prescription rates of
antidepressant medication
Use of billing codes
to measure depression screening.
Conclusion
Participating PCPs more likely to
screen for and diagnose
adolescent depression in the 12
months after training

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

Citation
Thompson et
al. (2019)
Collaborative
Care for
Depression of
Adults and
Adolescents:
Measuring the
Effectiveness
of Screening
and Treatment
Uptake.
Country: U.S.

33

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting Major Variables

Collaborative
care model

Design:
Retrospective
review
Purpose:
Identify any
screening and
tx disparities
along the axes
f gender, race,
ethnicity, and
age cohorts.

Sample:
Eligible patients
N= 25,369
Adol eligible for
PHQ9
N = 196 (12%)
Adol screened
N= 203 (20%)
Demographics:
M age = (20%,
N=4912)
12 25
F: N= 15,966,
(63%)
Setting:
Urban PC clinics
(network 10
clinics)

Studied and
Their Definitions

Measurement/
Instrumentatio
n

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

IV: usual care Adol
depression
management

Validated
Screening tool
PHQ-9

Data R,
version 3.5.1

LOE: Level IV

D1:
Collaborative care
team

Eligibility
algorithm

Adol
associated
with
disproportion
ate PHQ-9
screenings
and with tx.
Disengageme
nt

D2
PHQ-2 and PHQ-9
EHR prompt

demographics

PHQ-9
screening
rose from 7%
to 80%.

Strengths
Large network and team
intervention, validated tools,
Limitations
Selection bias (healthier patients
likelier to use patient care)
Data extraction may be
incomplete if providers did not
register screening.
f/u PHQ-9 scores were
inconsistent and not standard in
collaborative care workflow.
Conclusion
Intervention shows promise in
expanding access to care &
reducing disparities. > access to
psychotherapies and tx modalities
may improve tx. Integration of
screening in EHR effective.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

Citation
Farly et al.
(2020)
Identification
and
Management of
Adolescent
Depression in a
Large Pediatric
Care Network.
Country: USA
Funding:
Intervention
grant CFDA
93.767
Study: not
associated with
grant.
Bias: NS

34

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting Major Variables

Studied and
Their Definitions

Measurement/
Instrumentatio
n

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

collaborative
care

Design:
retrospective
study

N= 10,713

IV:
Well child visits

codebook for chart
review

Descriptive
statistics.

Level of Evidence: LOE V

D1:
PHQ-9 screening

PHQ-9

Approximately
, One quarter
of screens were
elevated (6.7%
mild, 19.2%
moderate to
severe)
Over one year:
40% screened
in mild range
received f/u
care.

Purpose:
PC Adole
depression
identification
and f/u care
when elevated
symptoms were
identified.

Demographics:
F: N= 5323
Setting:
Large pediatric
network PC
.

Strengths:
Large sample
Validated tools
Limitations:
Screens at 16 year well child
Conclusions:
Adol depression screening feasible
across diverse PC sites. Most patients
with elevated scores were not already
receiving behavioral
health services, suggesting screening
identified previously undetected
concerns.
Gaps in follow-up care demonstrate
the need for greater investment in
primary care–based behavioral health
services to support high-quality
treatment and ultimately decrease the
burden of adolescent depression.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

Citation
Valleley et al.
(2020)
Demonstrating
the Impact of
Colocated
Behavioral
Health in
Pediatric
Primary Care.
Country
Canada
Funding
NS
Bias
NS

35

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting Major Variables

colocated
model

Design:
retrospective
review
Method
Patient Chart
review

Sample:
N = 694 (new
patients)

Purpose:
To provide
demonstration
data for
colocated BH
services within
the pediatric
medical home

Studied and
Their Definitions

Demographics:
M age: 9.2yrs.

Setting:
Michigan,
Nebraska,
and Pennsylvania
participated in this
study. One urban,
three suburban, and
five rural
clinics comprised
the sample.

IV: PC
DV1:
Level 4–Close
Collaboration
with Some System
Integration collocated
care

Measurement/
Instrumentatio
n

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Site SelfAssessment
Evaluation Tool
(SSAES):
18 items
rated on a 10-point
Likert scale and
measures

IBM
SPSS Version
22 software

Across all
sites, 85% of
referred
patients
attended their
first
appointment,
and 84% of
Patients
showed
improvement
over a 6-month
period.

LOE: Level V
Strengths:
Large sample size, well designed,
validated testing tools.
Limitations:
Access to services cannot be fully
addressed with this data. Data were
not available for the
number of patients that were referred
but failed
to schedule an initial appointment.
Demographics not available re:
race/ethnicity
Conclusion:
first to provide outcome data
demonstrating the effectiveness of the
colocated model for
delivering BH services in primary
care. Data provide information on the
relationship
between patient outcomes and
adherence to recommendations
delivered during colocated
BH treatment. High attendance rates
at initial appointment and overall
improvement ratings
were observed, suggesting the
colocated BH model is a feasible
model to improve access
and outcomes in pediatric BH
services

BH provider at
each site completed
the SSAET
CGI-I
7-point Likert
Clinicians collected
at
the beginning of
each session parent
and/or
patient CGI ratings
(CBCL-PRF)
Parents completed
the CBCL
Chart review

Although
multiple tests
were evaluated,
as an
exploratory
analysis, a
conventional
alpha level of
.05 was used to
indicate
statistical
Significance.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

ADOLESCENT DEPRESSION

36

Citation

Theory/
Conceptual
Framework

Design/
Method/
Purpose

Sample/Setting

Major Variables Studied
and
Their Definitions

Measurement/
Instrumentation

Data
Analysis

Findings/
Results

Level of evidence/
Decision for Use/Application to
Practice

Chowdhury &
Champion
(2020)

Donabedian
model
Plan-DoStudy-Act
(PDSA)

Design:
Retrospective
chart review

Sample:
N =600

IV1: PC usual care

Depressive
symptoms
PHQ-9 : screening
BDI-II : baseline,
8/16 week follow
up
Peer violence
CTS-2 :screening,
8/16 week follow
up
Participant
satisfaction
CSQ-8: screening
Qualitative
feedback
8 weeks

Statistical
Package for the
Social Sciences
(SPSS version
24.0) for
descriptive
statistical data
analyses

82.5% of those
with PHQ-9
scores >5 were
not currently
receiving
tx.
Referrals by
physicians
(45.8%) and
NPs (42.9%)
were
equivalent with
more
referrals for
adolescents
with moderatesevere
depression.
NPs provided
more
counseling
than
physicians
among
adolescents
with mild to
moderate
depression.

LOE: Level V

Country
US
Funding

Bias

Purpose
Assess
outcomes of
depression
screening
among
adolescents
accessing
pediatric
primary carebased
Services.
Findings will
contribute to
development of
clinical
protocols for
depression
screening and
intervention
in primary care
settings.

DV1: PHQ-9 screening

Setting:
Pediatric primary
care based clinic in
the Southwestern
United States.

Self-reporting
RedCAP survey

Strengths:
Decent sample size, validated
screening tool.
Limitations:
limited documentation of the MH
referrals and follow
up. PHQ-9 assessments were only
available for the well adolescent
encounters,
as the PHQ-9 was not administered at
sports physicals or
other episodic visits.
Conclusions/Feasibility:
Adolescent MH necessitates an
enhanced continuum of care. PCbased interventions
provided by PNPs are imperative to
address adolescent MH needs.
Findings provide practical means to
incorporate protocols for depression
PC-based MH access.
Practice implications:
Future study for comparison of
methods (phone/text reminder,
follow up appointment, online
resource reminder, telehealth),
indicated to enhance follow-up care
for adol experiencing depression.

Adol – Adolescents, AgR – Age Range, BH: behavioral health, CBCL-PRF -Achenbach Child Behavior Checklist- Parent Report Form, CES-D- Center for Epidemiologic Studies Depression Scale
CGI-I - Clinical Global Impression–Improvement Scale CG – Control group, CI – Confidence interval, CLIN – Clinic based treatment, DepSym – depression symptoms, DNMIC - Did not meet
inclusion criteria, DSM-IV– Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition, DV1 – Dependent variable 1, DV2 – Dependent variable 2, DV3 – Dependent variable 3, Dx –
Diagnosis, Edu – Education, f – female, F/U – Follow Up, HRB- health risk behaviors, HSNP – Health system navigation program, IG - Intervention group, , IV – Independent variable, LOE – level of
evidence, MDD- major depressive disorder, m – Male, mgmt.- management M –Mean, Med- Medication, MH – mental health, MI – motivational interviewing, Mo - months, N – Sample
(population), n - Sample size (studies), nd – no data, NS – Not stated, NPs- nurse practitioner, OD - Operational data, PII – Patient insurance information, PCP – Primary care providers, PS – Patient
satisfaction, Pt – Patient, PHQ-9- Patient health questionnaire, PHQ-A – Patient health questionnaire for adolescents, PNPs- pediatric nurse practitioners, QALYs- quality adjusted life years, SA –
Substance Abuse, SAS - Statistical Analysis Software, SPSS - Statistical Package for the Social Sciences, S- TOFHLA - Short Test of Functional Health Literacy in Adults, SI – Suicidal Ideation,
SUD- substance use disorder, sx – symptoms, Tx - treatment, Vers – version, U.S. – United States of America, Vt. – Vermont, VDH – Vermont Department of Health, Yrs. – years, 10 – Primary, 20 –
Secondary, # - Number of, > - greater than.

Running head: ADOLESCENT DEPRESSION
Appendix B
Table 2
Synthesis Table

Farly et al.

Valleley
et al.

Chowdhury
&
Champion
.

Study

Wright et al.

Bai et al.

Simon et al.

Yang et al.

Harder et al.

Fallucco et al.

Thompson
et al.

Year

2016

2018

2018

2019

2019

2019

2019

2020

2020

2020

Study Design

RCT

RCT

Review

QI

QI

Review

Review

Review

Review

Review

187

SA: 24,233
SD: 1240

290

PCP: 39
Patients: 1772

PCPs @
training: 25
Adolescents:

203

10,713

694

600

N

101

7,108

Setting

U.S.

U.S

U.S

U.S

U.S

U.S

U.S

U.S

U.S

U.S

Primary care

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

X

Intervention
EHR review
EHR update
Collaborative
care

X

X

Usual care

X

X

Length of
project period

12 months

12 months

X
X
Review: 90 days
before the visit,
within 1 year
before, and
within 5 years
before.

11 months

7 months

X

2 years

14 months

2.5 years

6 months

3 months

ADOLESCENT DEPRESSION

Study

Wright et al.

Bai et al.

38

Simon et al.

Additional
education
Parent
Education

X

F/U
interval

6 month
12 month

Thompson
et al.

Yang et al.

Harder et al.

Fallucco et al.

Farly et al.

X

X

X

X

12 months
2.5 years

12 months

12 months

12 months

Valleley
et al.

Chowdhury
&
Champion
.

X
6 month
12 months

Demographics
AgR

13-17 years

M age: 16.06

M age: 46

Practicing
PCPS
5-15yrs

Adolescent

M age: 14.3

m/f

28/73

80/107

F 62%

81/209

Not stated

3675/3433

Measurement
tools

QALYs
Child
Depression
Rating Scale –
revised
PHQ-9
SCARED

(CES-D)

+

+/-

PHQ-9 (ninth
question)

MHPRI scores
Survey

LASSO

12-17

16yo
Wellchild
visits

1-18
years

12–18 years

5390/5323

402/292

49.5%/50.5%

PHQ-9

PHQ-9

PHQ-9

+

+

PHQ-9
PHQ-9

PHQ-9
screening

Outcomes
improvement

+

+

+

+

+

AgR- age range, CES-D- Center for Epidemiologic Studies Depression Scale EHR – electronic health record, f- female, LASSO- least absolute shrinkage and selection operator, m- male, MHPRIMental Health Practice Readiness Inventory N- population sample, PHQ-9- patient health questionnaire, PCP- primary care provider, QALYs- quality adjusted life years, QI- quality improvement,
RCT- randomized control trial, SA- suicide attempt, SCARED – The screen for child anxiety related disorders, SD- suicide death, U.S.- United States,

Running head: ADOLESCENT DEPRESSION
Appendix C
Figure 1
Orlando’s Nursing Process Discipline Theory

ADOLESCENT DEPRESSION

40
Appendix D

Figure 2
Model for Improvement

\

ADOLESCENT DEPRESSION

41

Appendix E
Table 3
Chart Review elements completed during pre- and post-intervention

Variable

Pre-test

Post-test

Y

43 (91%)

7 (78%)

N

3 (6%)

2 (22%)

Refused screening

1 (2%)

0 (0%)

47 (100%)

9 (100%)

Y

25 (53%)

7 (78%)

N

22 (47%)

2 (22%)

N

18 (41%)

7 (78%)

Y

26 (59%)

2 (22%)

PhQ_9_Complete

Education
Y
Medication

Referral

ADOLESCENT DEPRESSION

42
Appendix F

Table 4
Two-Tailed Independent Samples t-Test for PHQ_9_Score by Testing Period

Note. N = 49. Degrees of Freedom for the t-statistic = 47. d represents Cohen's d.

ADOLESCENT DEPRESSION

43
Appendix G

Graph 1
Depression Severity

ADOLESCENT DEPRESSION

44
Appendix H

Table 5
Qualitative Survey Results

Pre-test Questions and Responses
Question 14: What are two or three barriers you have had providing care to adolescent patients
diagnosed with depression?
 Guidance tool for anticipator guidelines
 Scope of practice regarding medication for depression
 Guidance for follow-up
Question 15: How has the implementation of GLAD-PC recommendations into the EHR
benefited your practice?
 Make it easier to document
 Provide guidance for appointments and follow up
Post-test Questions and Responses
Question 14: What are two or three barriers you have had providing care to adolescent patients
diagnosed with depression?
 Lack of referral providers is primary barrier
 Lack of mental health services
Question 15: How has the implementation of GLAD-PC recommendations into the EHR
benefited your practice?


It makes charting easier- I don’t forget to discuss things during visits.

ADOLESCENT DEPRESSION

45
Appendix I

Table 6
Survey Results
Variable

Pretest
N(%)

Posttest
N(%)

Your current method of documentation allows you to follow GLAD-PC
recommendations?
3
5
Your current method of documentation is
efficient.

1 (50%)
1 (50%)

0 (0%)
2 (100%)

4
5
Your current method of documentation is user
friendly.

2 (100%)
0 (0%)

1 (50%)
1 (50%)

4
5
Process changes to the EHR will benefit the clinical management of my
patients

1 (50%)
1 (50%)

0 (0%)
2 (100%)

2
5
In your experience, utilization of case management supports your
practice

0 (0%)
2 (100%)

1 (50%)
1 (50%)

0
2
5
My referral process allows me to efficiently contact other agencies.

0 (0%)
1 (50%)
1 (50%)

1 (50%)
0 (0%)
1 (50%)

1 (50%)
1 (50%)
0 (0%)

1 (50%)
0 (0%)
1 (50%)

4
5
Contacting Case management is easy for
you

1 (50%)
1 (50%)

0 (0%)
2 (100%)

1
2
3
4
A flowsheet will benefit clinical management of my patients.

1 (50%)
0 (0%)
0 (0%)
1 (50%)

0 (0%)
1 (50%)
1 (50%)
0 (0%)

0 (0%)
0 (0%)
2 (100%)

1 (50%)
1 (50%)
0 (0%)

2
3
4
Your current documentation allows you to quickly obtain data from recent office
visits?

2
3
5

ADOLESCENT DEPRESSION

46

The process to make referrals is straight forward.
2
3
4
5
Case management in your practice is wellutilized

1 (50%)
1 (50%)
0 (0%)
0 (0%)

0 (0%)
0 (0%)
1 (50%)
1 (50%)

1
2
4
My referral process uses closed-loop
communication

1 (50%)
1 (50%)
0 (0%)

1 (50%)
0 (0%)
1 (50%)

2 (100%)
0 (0%)

2 (100)
0 (0%)

3
5

The referral process is typically updated within the electronic health record for the duration of acute management of my
patients.
2
3

1 (50%)
0 (0%)

0 (0%)
2 (100)

4

1 (50%)

0 (0%)

Key: 0: No answer, 1: Disagree, 2: Somewhat Disagree, 3: Neither Agree nor Disagree, 4. Somewhat Agree, 5. Agree

Note. Due to rounding errors, column wise percentages may not equal 100%.