Table II.

Logistic Regression Model Examining Variability in Scheduled In-Person (Pre-COVID-19) and Telehealth (Mid-COVID-19) Integrated Behavioral Health Consultation

VariablesB (S.E.)pOdds ratio (95% CI)
Attendance1.398 (0.427).0014.048 (1.754, 9.343)
Primary referral concern
 Externalizing vs. internalizing1.021 (0.430).0182.776 (1.194, 6.453)
 Externalizing vs. other0.217 (0.399).5871.242 (0.569, 2.713)
Health insurance type0.520 (0.419).2151.681 (0.740, 3.822)
Race/ethnicity
 White vs. Black−1.048 (0.396).0080.351 (0.161, 0.763)
 White vs. Hispanic−0.808 (0.500).1060.446 (0.167, 1.188)
 White vs. Other−0.570 (0.507).2600.565 (0.209, 1.526)
Language−0.368 (0.513).4730.692 (0.253, 1.890)
Age0.218 (0.357).5411.224 (0.618, 2.506)
Sex−0.445 (0.332).1800.641 (0.334, 1.228)
Primary care provider for visit1.145 (0.308).0003.143 (1.718, 5.752)
Appointment type0.701 (0.477).1422.015 (0.791, 5.131)
VariablesB (S.E.)pOdds ratio (95% CI)
Attendance1.398 (0.427).0014.048 (1.754, 9.343)
Primary referral concern
 Externalizing vs. internalizing1.021 (0.430).0182.776 (1.194, 6.453)
 Externalizing vs. other0.217 (0.399).5871.242 (0.569, 2.713)
Health insurance type0.520 (0.419).2151.681 (0.740, 3.822)
Race/ethnicity
 White vs. Black−1.048 (0.396).0080.351 (0.161, 0.763)
 White vs. Hispanic−0.808 (0.500).1060.446 (0.167, 1.188)
 White vs. Other−0.570 (0.507).2600.565 (0.209, 1.526)
Language−0.368 (0.513).4730.692 (0.253, 1.890)
Age0.218 (0.357).5411.224 (0.618, 2.506)
Sex−0.445 (0.332).1800.641 (0.334, 1.228)
Primary care provider for visit1.145 (0.308).0003.143 (1.718, 5.752)
Appointment type0.701 (0.477).1422.015 (0.791, 5.131)

Notes. N =226. Reference category is “0” for all variables. Attendance is coded as 0 = “attended” and 1 = “did not attend.” Primary referral concern is coded as 0 = “externalizing,” 1 = “internalizing,” and 2 = “other” (including developmental delay, medical concern, obsessive/habitual behavior, feeding/elimination problem, trauma/adjustment). Health insurance type is coded as 0 = “Medicaid/self-pay” and 1 = “commercial.” Race/ethnicity is coded as 0 = “White,” 1 = “Black,” 3 = “Hispanic,” and 3 = “other” (including Asian and multiracial). Language is coded as 0 = “English proficiency” and 1 = “limited English proficiency.” Sex is coded as 0 = “male” and 1 = “female.” Age is coded as 0 = “pre-school age” and 1 = “school age and older.” The control variable ‘primary care provider’ for visit is coded as 0 = “saw assigned or familiar PCP” and 1 = “unfamiliar PCP OR does not have assigned PCP.” The other control variable, appointment type, is coded as 0 = “initial joint consult” and 1 = “follow-up joint consult.” The dependent variable service delivery modality is coded as 0 = “in-person (pre-COVID-19)” and 1 = “telehealth (mid-COVID-19).”

Table II.

Logistic Regression Model Examining Variability in Scheduled In-Person (Pre-COVID-19) and Telehealth (Mid-COVID-19) Integrated Behavioral Health Consultation

VariablesB (S.E.)pOdds ratio (95% CI)
Attendance1.398 (0.427).0014.048 (1.754, 9.343)
Primary referral concern
 Externalizing vs. internalizing1.021 (0.430).0182.776 (1.194, 6.453)
 Externalizing vs. other0.217 (0.399).5871.242 (0.569, 2.713)
Health insurance type0.520 (0.419).2151.681 (0.740, 3.822)
Race/ethnicity
 White vs. Black−1.048 (0.396).0080.351 (0.161, 0.763)
 White vs. Hispanic−0.808 (0.500).1060.446 (0.167, 1.188)
 White vs. Other−0.570 (0.507).2600.565 (0.209, 1.526)
Language−0.368 (0.513).4730.692 (0.253, 1.890)
Age0.218 (0.357).5411.224 (0.618, 2.506)
Sex−0.445 (0.332).1800.641 (0.334, 1.228)
Primary care provider for visit1.145 (0.308).0003.143 (1.718, 5.752)
Appointment type0.701 (0.477).1422.015 (0.791, 5.131)
VariablesB (S.E.)pOdds ratio (95% CI)
Attendance1.398 (0.427).0014.048 (1.754, 9.343)
Primary referral concern
 Externalizing vs. internalizing1.021 (0.430).0182.776 (1.194, 6.453)
 Externalizing vs. other0.217 (0.399).5871.242 (0.569, 2.713)
Health insurance type0.520 (0.419).2151.681 (0.740, 3.822)
Race/ethnicity
 White vs. Black−1.048 (0.396).0080.351 (0.161, 0.763)
 White vs. Hispanic−0.808 (0.500).1060.446 (0.167, 1.188)
 White vs. Other−0.570 (0.507).2600.565 (0.209, 1.526)
Language−0.368 (0.513).4730.692 (0.253, 1.890)
Age0.218 (0.357).5411.224 (0.618, 2.506)
Sex−0.445 (0.332).1800.641 (0.334, 1.228)
Primary care provider for visit1.145 (0.308).0003.143 (1.718, 5.752)
Appointment type0.701 (0.477).1422.015 (0.791, 5.131)

Notes. N =226. Reference category is “0” for all variables. Attendance is coded as 0 = “attended” and 1 = “did not attend.” Primary referral concern is coded as 0 = “externalizing,” 1 = “internalizing,” and 2 = “other” (including developmental delay, medical concern, obsessive/habitual behavior, feeding/elimination problem, trauma/adjustment). Health insurance type is coded as 0 = “Medicaid/self-pay” and 1 = “commercial.” Race/ethnicity is coded as 0 = “White,” 1 = “Black,” 3 = “Hispanic,” and 3 = “other” (including Asian and multiracial). Language is coded as 0 = “English proficiency” and 1 = “limited English proficiency.” Sex is coded as 0 = “male” and 1 = “female.” Age is coded as 0 = “pre-school age” and 1 = “school age and older.” The control variable ‘primary care provider’ for visit is coded as 0 = “saw assigned or familiar PCP” and 1 = “unfamiliar PCP OR does not have assigned PCP.” The other control variable, appointment type, is coded as 0 = “initial joint consult” and 1 = “follow-up joint consult.” The dependent variable service delivery modality is coded as 0 = “in-person (pre-COVID-19)” and 1 = “telehealth (mid-COVID-19).”

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