OBJECTIVE:

To assess the frequency and completeness of adolescent psychosocial screening documentation for adolescents and young adults hospitalized to a pediatric hospitalist medicine service.

METHODS:

All patients 12 to 21 years old on the hospital medicine service in an urban, academic, free standing children’s hospital in the Mid-Atlantic United States from January 1, 2014, to December 31, 2015, were identified. A retrospective review was conducted to assess the frequency of documentation of a complete psychosocial screening using the Home, Education, Activities, Drugs, Sex, Suicide assessment within 48 hours of admission. Differences in screening rates according to race, sex, age, patient’s medical complexity, and whether they required transfer to a higher level of care were assessed through logistic regression analyses.

RESULTS:

Only 5.3% (24 of 435 patients) had all 6 domains of the Home, Education, Activities, Drugs, Sex, Suicide psychosocial assessment documented. Controlling for patient characteristics (demographic, medical complexity, and level of care), the odds of being screened for sensitive domains (drugs, sex, and suicide) were higher in female patients, patients ≥16 years old, and those transferred to a higher level of care. Those considered high medical complexity were screened less across all domains.

CONCLUSIONS:

Overall, pediatric hospitalist documentation lacked adolescent psychosocial screening. Potential opportunities exist through screening early in the hospitalization to connect youth with services that influence health outcomes.

Adolescence is a time of significant psychological, cognitive, emotional, and developmental changes that has unique implications for care provided in a hospital setting.1,2  Hospitalists answering the recent call to examine factors beyond the acute illness that influence admission risk and discharge quality must consider screening each adolescent or young adult (AYA) for health behaviors and risk factors within each youth’s cultural and economic context.2  Psychosocial screening of AYA patients by medical providers early in a hospitalization is a potential strategy to obtain this information because it can lead to timely and adequate use of ancillary services and consults. Researchers in previous studies have shown that psychosocial screening of hospitalized AYA is not routinely done by medical providers despite patients’ receptiveness in nontraditional settings and availability of guidelines for health promotion and screening of AYA in primary care settings that can be adapted.35  With this study, we add to existing studies assessing psychosocial screening documentation rates by medical providers in hospitalized adolescents and expand on previous work of health risk screening in hospitalized adolescents that focuses solely on reproductive health or suicide.3,6  We aimed to determine the frequency and completeness of adolescent psychosocial screening documentation for AYA hospitalized to a pediatric hospitalist medicine service.

A retrospective chart review of patients 12 to 21 years old hospitalized to a pediatric hospital medicine service in an urban, academic, freestanding children’s hospital in the Mid-Atlantic United States from January 1, 2014, to December 31, 2015, was performed. These patients are not routinely seen by the adolescent medicine service unless consulted. Adolescents hospitalized on specialty services were excluded to focus this pilot study on 1 large academic pediatric hospital medicine division.

Patients were identified by using Oracle Endeca Information Discovery software, an administrative searchable database that includes patient demographics, diagnoses, and clinical documents from the hospital’s electronic medical record. This institution’s institutional review board approved this study.

The Home, Education, Activities, Drugs, Sex, Suicide (HEADSS) assessment version 1.0, a tool that provides a framework for conducting a comprehensive, psychosocial interview, was used as a reference.7  This version was chosen to align with the mnemonic that is taught to trainees during their adolescent medicine rotation and used at the study institution when conducting psychosocial screening of adolescent patients.

To assess completeness of psychosocial documentation in inpatient notes, charts were reviewed for the 6 HEADSS domains documented anywhere within the physician admission history and physical note or subsequent 2 progress notes within 48 hours of admission. This time period was chosen to measure early identification of factors that may impact health outcomes beyond the acute illness or facilitate connection to services during the hospitalization (eg, sexually transmitted infection screening and mental health consultation). All patient charts were reviewed by an attending, regardless of initial clinical assessment and chart documentation by a medical trainee. Data were not stratified by trainee’s involvement in documentation. Notes written by ancillary staff, subspecialty consults, and emergency department providers were excluded to focus on documentation by inpatient hospital medicine providers. The frequency of documentation of each of the 6 HEADSS domains was scored dichotomously (yes or no) on the basis of a key adapted from the HEADSS interview questions (Table 1). Complete chart review was conducted by the principal investigator. For internal consistency, 20 charts were randomly selected and checked by a coinvestigator in the study group before the completion of the review. No prompts, pop-ups, or structured templates for the HEADSS assessment tool were active in the inpatient electronic medical record, Cerner PowerChart (Kansas City, MO).8 

TABLE 1

HEADSS Domain Documentation by Category

DomainTotal (N = 453)Percent Documented, %
Home 290 64.0 
Education 204 45.0 
Activities 92 20.3 
Drugs 144 31.8 
Sex 135 29.8 
Suicide 84 18.5 
H+E+A 64 14.1 
D+S+S 46 10.1 
All 6 domains 24 5.3 
DomainTotal (N = 453)Percent Documented, %
Home 290 64.0 
Education 204 45.0 
Activities 92 20.3 
Drugs 144 31.8 
Sex 135 29.8 
Suicide 84 18.5 
H+E+A 64 14.1 
D+S+S 46 10.1 
All 6 domains 24 5.3 

Domain key: Home: where do you live? or who do you live with? Education: what is the name of your school or work? Activities: do you participate in any sports or other activities? Drugs: have you ever used in your lifetime tobacco, alcohol, or other drugs? Sex: have you ever had sex? Suicide: do you have current or past suicide ideation? D+S+S, drugs plus sex plus suicide; H+E+A, home plus education plus activities.

Data were collected and managed by using the Research Electronic Data Capture tool hosted at the study institution.9,10  Demographic covariates previously associated with disparities in health care delivery were extracted (sex, age, and race or ethnicity).1113  Age was dichotomized (≥16 or <16 years old) on the basis of cognitive processing skills. Previous studies have revealed that the ability to reason logically matures by age 16.14  Additional variables evaluated included complexity of medical history based on consensus definitions from the Center of Excellence on Quality of Care Measures for Children with Complex Needs as outlined in Table 2 and whether the patient was transferred to a higher level of care (eg, ICU) within 48 hours of admission.15  The extent of psychosocial history documentation within a patients chart was characterized according to the total number of HEADSS topics addressed and ranged from 0 to 6 components documented.

TABLE 2

Unadjusted (OR) and Adjusted (aOR) Analyses of Variables Associated with HEADSS Domain Documentation

DomainHomeEducationActivitiesDrugsSexSuicide
Variable OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) 
Race and ethnicity             
 White reference reference reference reference reference — reference — reference reference reference — 
 AA 1.45 (0.92–2.27) 1.45 (0.92–2.27) 1.00 (0.64–1.58) 0.96 (0.61–1.52) 0.91 (0.52–1.60) — 1.80 (1.07–3.03) — 2.24 (1.28–3.89) 1.84 (0.99–3.39) 0.81 (0.45–1.43) — 
 Other 2.33 (1.25–4.31) 2.33 (1.26–4.31) 2.23 (1.25–3.98) 2.09 (1.15–3.77) 1.74 (0.90–3.36) — 2.58 (1.37–4.78) — 3.20 (1.66–6.16) 2.13 (1.03–4.40) 1.18 (0.59–2.36) — 
Sex             
 Male reference — reference — reference — reference reference reference reference reference reference 
 Female 1.13 (0.75–1.69) — 1.37 (0.92–2.03) — 0.99 (0.61–1.60) — 2.13 (1.35–3.34) 2.41 (1.44–4.02) 2.29 (1.44–3.67) 2.58 (1.50–4.43) 3.24 (1.75–5.99) 2.75 (1.44–5.25) 
Age, y             
 <16 reference — reference — reference — reference reference reference reference reference — 
 ≥16 0.89 (0.6–1.33) — 0.78 (0.53–1.15) — 1.24 (0.78–1.98) — 1.76 (1.17–2.66) 1.92 (1.22–3.05) 2.14 (1.41–3.27) 2.27 (1.39–3.70) 1.28 (0.78–2.09) — 
Medical complexitya             
 Low reference — reference reference reference reference reference reference reference reference reference  
 Medium 0.81 (0.51–1.28) — 0.93 (0.60–1.44) 1.01 (0.64–1.58) 0.72 (0.43–1.19) 0.72 (0.43–1.19) 0.57 (0.36–0.89) 0.43 (0.27–0.70) 0.58 (0.37–0.92) 0.45 (0.27–0.74) 1.55 (0.92–2.64) 1.30 (0.74–2.28) 
 High 0.64 (0.38–1.05) — 0.44 (0.26–0.74) 0.48 (0.28–0.82) 0.27 (0.13–0.56) 0.27 (0.13–0.56) 0.03 (0.01–0.10) 0.01 (0.01–0.10) 0.01 (0.002–0.08) 0.01 (0.001–0.08) 0.26 (0.10–0.64) 0.2 (0.10–0.63) 
Level of care             
 Not transferred reference — reference reference reference — reference — reference — reference reference 
 Transferred 1.17 (0.55–2.47) — 2.03 (0.98–4.20) 2.27 (1.08–4.79) 0.51 (0.17–1.49) — 1.49 (0.72–3.10) — 1.91 (0.93–3.95) — 4.36 (2.09–9.10) 4.98 (2.22–11.14) 
DomainHomeEducationActivitiesDrugsSexSuicide
Variable OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) OR (95% CI) aOR (95% CI) 
Race and ethnicity             
 White reference reference reference reference reference — reference — reference reference reference — 
 AA 1.45 (0.92–2.27) 1.45 (0.92–2.27) 1.00 (0.64–1.58) 0.96 (0.61–1.52) 0.91 (0.52–1.60) — 1.80 (1.07–3.03) — 2.24 (1.28–3.89) 1.84 (0.99–3.39) 0.81 (0.45–1.43) — 
 Other 2.33 (1.25–4.31) 2.33 (1.26–4.31) 2.23 (1.25–3.98) 2.09 (1.15–3.77) 1.74 (0.90–3.36) — 2.58 (1.37–4.78) — 3.20 (1.66–6.16) 2.13 (1.03–4.40) 1.18 (0.59–2.36) — 
Sex             
 Male reference — reference — reference — reference reference reference reference reference reference 
 Female 1.13 (0.75–1.69) — 1.37 (0.92–2.03) — 0.99 (0.61–1.60) — 2.13 (1.35–3.34) 2.41 (1.44–4.02) 2.29 (1.44–3.67) 2.58 (1.50–4.43) 3.24 (1.75–5.99) 2.75 (1.44–5.25) 
Age, y             
 <16 reference — reference — reference — reference reference reference reference reference — 
 ≥16 0.89 (0.6–1.33) — 0.78 (0.53–1.15) — 1.24 (0.78–1.98) — 1.76 (1.17–2.66) 1.92 (1.22–3.05) 2.14 (1.41–3.27) 2.27 (1.39–3.70) 1.28 (0.78–2.09) — 
Medical complexitya             
 Low reference — reference reference reference reference reference reference reference reference reference  
 Medium 0.81 (0.51–1.28) — 0.93 (0.60–1.44) 1.01 (0.64–1.58) 0.72 (0.43–1.19) 0.72 (0.43–1.19) 0.57 (0.36–0.89) 0.43 (0.27–0.70) 0.58 (0.37–0.92) 0.45 (0.27–0.74) 1.55 (0.92–2.64) 1.30 (0.74–2.28) 
 High 0.64 (0.38–1.05) — 0.44 (0.26–0.74) 0.48 (0.28–0.82) 0.27 (0.13–0.56) 0.27 (0.13–0.56) 0.03 (0.01–0.10) 0.01 (0.01–0.10) 0.01 (0.002–0.08) 0.01 (0.001–0.08) 0.26 (0.10–0.64) 0.2 (0.10–0.63) 
Level of care             
 Not transferred reference — reference reference reference — reference — reference — reference reference 
 Transferred 1.17 (0.55–2.47) — 2.03 (0.98–4.20) 2.27 (1.08–4.79) 0.51 (0.17–1.49) — 1.49 (0.72–3.10) — 1.91 (0.93–3.95) — 4.36 (2.09–9.10) 4.98 (2.22–11.14) 

High: children with complex chronic disease. Significant chronic conditions in ≥2 body systems or a progressive condition that is associated with deteriorating health with a decreased life expectancy in adulthood or continuous dependence on technology for at least 6 months. Medium: children with noncomplex chronic disease. Chronic conditions that last at least 1 year: Conditions are commonly lifelong but can be episodic with periods of good health between episodes. Low: children without chronic disease. Acute nonchronic conditions or healthy, no acute chronic health conditions. —, not applicable.

a

Medical complexity.13 

Descriptive statistics were used to report rates of HEADSS domain documentation. Logistic regression analyses were used to estimate the relative odds of having psychosocial screening documented after adjustment for demographic covariates, medical complexity, and level of care. Statistical analyses were performed by using statistical software SAS software (SAS Institute, Inc, Cary, NC).16  A P value <.05 was considered significant.

A total of 453 patient hospitalizations met inclusion criteria for the analysis. The majority of the study population was African American, ≥16 years old, and classified as low medical complexity (Table 3). Only 5.3% (n = 24) of all patient charts documented a complete psychosocial assessment (Table 1). Although over half of all records included documentation of home environment, fewer than half of the records included documentation of any other domains. Suicidality risk was recorded least frequently (18.5%).

TABLE 3

Characteristics of Sample Population (N = 453)

Patient Characteristicn (%)
Race and ethnicity  
 African American 246 (54.3) 
 White 122 (26.9) 
 LatinX 32 (7.1) 
 Asian American 3 (0.7) 
 Other 50 (11.0) 
Sex  
 Female 288 (63.6) 
 Male 165 (36.4) 
Age, y  
 ≥16 39 (8.6) 
 <16 414 (91.3) 
Medical complexity  
 Low 176 (38.9) 
 Medium 167 (36.9) 
 High 110 (24.3) 
Transferred to higher level of care  
 No 419 (92.5) 
 Yes 34 (7.5) 
Patient Characteristicn (%)
Race and ethnicity  
 African American 246 (54.3) 
 White 122 (26.9) 
 LatinX 32 (7.1) 
 Asian American 3 (0.7) 
 Other 50 (11.0) 
Sex  
 Female 288 (63.6) 
 Male 165 (36.4) 
Age, y  
 ≥16 39 (8.6) 
 <16 414 (91.3) 
Medical complexity  
 Low 176 (38.9) 
 Medium 167 (36.9) 
 High 110 (24.3) 
Transferred to higher level of care  
 No 419 (92.5) 
 Yes 34 (7.5) 

In bivariate analysis, African Americans patients had greater odds than white patients of having drugs (odds ratio [OR] = 1.80; 95% confidence interval [CI]: 1.07–3.03) and sex (OR = 2.24; 95% CI: 1.28–3.89) domains documented, respectively (Table 2).

In regression analysis, there was almost 2 times greater adjusted odds of documentation of home, education, and sex domains among patients classified as “other” race or ethnicity, which included Asian American (n = 3; 0.7%), LatinX (n = 32; 7.1%), and those without notation or fit into the noted categories (n = 50; 11%). With regards to sex differences, female more than male patients had at least 2 times greater adjusted odds of having documentation of drugs (adjusted odds ratio [aOR] = 2.41; 95% CI: 1.44–4.02), sex (aOR = 2.58; 95% CI: 1.50–4.43), and suicide domains (aOR = 2.75; 95% CI: 1.44–5.25). Patients 16 years of age or older had ∼2 times greater adjusted odds of documentation of drugs (aOR = 1.92; 95% CI: 1.22–3.05), and sex (aOR = 2.27; 95% CI: 1.39–3.70) domains (Table 2). Patients with high medical complexity had statistically significant lower odds of documentation of all domains except for the home domain. Patients transferred to the ICU within 48 hours of had 5 times greater adjusted odds of suicide domain documentation (aOR = 4.98; 95% CI: 2.22–11.14) and 2 times greater adjusted odds of having the education domain documented (aOR = 2.27; 95% CI: 1.08–4.79) compared with those who were not transferred.

Psychosocial screening of AYA is an important strategy for identifying health behaviors and risk factors that should be considered by medical providers in nontraditional settings, such as during hospitalization. AYA have expressed willingness to be screened in the hospital setting, which may be the only opportunity for interaction with the health care system among those who lack a medical home or usual source of care.3 

In this study, complete psychosocial screening documentation by medical providers was lacking for 95% of hospitalized adolescents, highlighting missed opportunities in the hospital setting. These data are consistent with a smaller inpatient study that revealed low (7%) documentation of a complete HEADSS screening.17  Controlling for patient characteristics (demographic, medical complexity, and level of care) the odds of being screened for sensitive domains (drugs, sex, and suicide) was higher in female patients, patients ≥16 years old, and those transferred to a higher level of care in this study. Those considered high medical complexity were screened less across all domains.

Unlike in other studies in which researchers support racial bias in screening, the differential documentation rates of drug and sex domains between white and African American adolescents did not persist in our study when controlled for other variables.2,18  There was a sex difference in documentation of the drug, sex, and suicide domains with ∼2 times lesser odds for male patients. This is consistent with outpatient literature documenting male adolescent health care gaps regarding mental health screening and reproductive health in both outpatient and hospital settings.4,11 

As seen in other studies, patients ≥16 years old had greater odds of having the sex domain documented. Similar results were reported in other studies in which only 50% of hospitalized adolescents had a sexual history documented, and only 4% of 12-year-old patients had sexual activity documented in a hospital setting.3,19  Researchers have suggested screening AYA for sexual activity in nontraditional settings creates an additional opportunity for providers to discuss reproductive health and that this discussion is welcomed by hospitalized youth of both sexes, regardless of previous sexual experience or reason for hospitalization.3,4,6 

Patients with high medical complexity had much lower odds of documentation of nearly all HEADSS domains (except home). A common misconception is that AYAs who are medically complex do not engaged in high-risk health behaviors.20  However, they engage in sexual activity at similar rates as their nonmedically complex peers. Despite this fact, they are less likely to receive information on contraception and screening for sexually transmitted illnesses and are less likely to have a sexual history documented.19,20 

Finally, within our study, patients who were transferred to a higher level of care within 48 hours of admission had greater odds of having the suicide domain documented. Higher acuity of presenting complaint may have triggered screening for suicide to investigate cause of injury of presenting condition.

Limitations of this study include that it was conducted at a single institution and the majority of the chart review was performed by a single reviewer. Data were not collected on admission diagnosis or severity of complaint, which could have affected documentation rates. Furthermore, absence of documentation in the hospitalist’s records within 48 hours of admission may not reflect lack of screening. Rather, screening may have been performed in the emergency department, by ancillary services, after 48 hours of admission, or documented in a noncentralized area of the patient record. Referral and resource use data were not collected as part of this pilot study. Finally, there were not granular data available to determine what races or ethnicities made up the category of “other.” These data may be worthy of future collection for additional analysis.

At only 5%, we found significant gaps in complete psychosocial screening of hospitalized adolescents. Odds of individual domain documentation differed on the basis of race and ethnicity, sex, age, medical complexity, and level of care. Low documentation rates may signify that the hospital setting is perceived as playing a lesser role in preventive health or that psychosocial issues may be perceived as less important or relevant than acute medical problems.

Potential next steps include assessing providers attitudes regarding psychosocial screening in hospitalized adolescents and assessing if psychosocial screening leads to an increase in use and linkage to ancillary services, such as social work or mental health.

The authors thank Linda Fu MD, MS for her critical review of the manuscript.

Dr Addison conceptualized and designed the study, designed the data collection instrument, performed data collection, drafted the initial manuscript, and approved the final manuscript as submitted; Dr Bokor conceptualized and designed the study, drafted the initial manuscript, critically reviewed and revised the manuscript, and approved the final manuscript as submitted; Dr Tuchman critically reviewed and revised the manuscript, and approved the final manuscript as submitted; Ms Herrera conducted the initial analyses and approved the final manuscript as submitted; and all authors approved the final manuscript as submitted.

FUNDING: No external funding.

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.