OBJECTIVES

To analyze factors associated with the initiation of long-acting reversible contraception (LARC) among adolescent patients in inpatient settings in the United States.

METHODS

This study is a secondary data analysis of the national Kids’ Inpatient Database 2016 data (N = 4200 hospitals). Eligible patients were hospitalized girls 10 to 20 years old. The primary outcome was initiation of LARC (ie, subdermal implant and/or intrauterine device [IUD]) while hospitalized. Covariables included age, race or ethnicity, insurance type, postpregnancy status, geographic region, hospital type (rural or urban), hospital size, and children’s hospital status. Bivariable statistics were calculated by using survey-weighted analysis, and a design-based logistic regression model was used to determine the adjusted odds of LARC initiation and of implant versus IUD initiation.

RESULTS

LARC initiation occurred in 0.4% (n = 3706) of eligible hospital admissions (n = 874 193). There were differences in LARC initiation by patient age, insurance type, race or ethnicity, postpregnancy status, hospital type, and hospital status (all P < .01). In the adjusted model, older age, public insurance, nonwhite race or ethnicity, postpregnancy status, and urban, teaching or larger hospitals were independently associated with LARC initiation (all P < .01). Smaller hospital size and postpregnancy status increased the odds of implant versus IUD initiation after stratifying by hospital region.

CONCLUSIONS

LARC initiation occurred in <1% of adolescent hospitalizations, with 90% of those occurring in postpregnancy adolescents. Addressing LARC capacity in rural, nonteaching, and smaller hospitals is important in increasing access. Future research is needed to identify and close gaps in the number of adolescents desiring and initiating LARC in hospital settings.

Although the adolescent birth rate is decreasing in the United States, it remains the highest among comparable high-income countries.1  Adolescents 15 to 19 years old have the highest rates of unintended pregnancies across all age groups.2  Racial and geographic disparities in adolescent birth rates persist, with higher rates observed among nonwhite adolescents and in Southern states.3  Structural and systemic factors impact both the adolescent pregnancy rates and socioeconomic outcomes; adolescent parents have lower rates of high school graduation and lower socioeconomic status and employment.4 

Long-acting reversible contraception (LARC) includes intrauterine devices (IUDs) and subdermal etonogestrel implants, which provide highly effective pregnancy prevention. Initiation of LARC increased nationally from 2008 to 2014, with 5% to 10% of sexually active contraception-using adolescents choosing LARC in 2014.5,6  Whereas LARC is most often initiated in the outpatient setting, inpatient hospitalizations may provide an important opportunity to increase adolescent access. Inpatient hospitalizations offer critical opportunities for LARC initiation, especially among adolescents with teratogenic medication exposures. In one study, researchers reported that 53% of hospitalized girls aged 14 to 18 years were interested in sexual health services, including contraception.7  Despite hospitalized adolescents’ interest in contraception, only 25% of hospitalized adolescents have a sexual history documented and 8.5% have a contraceptive history documented.8 

Factors associated with inpatient initiation of LARC among female adolescents are not well understood. The objective of this study was to evaluate the frequency of LARC initiation and factors associated with initiation among hospitalized adolescents.

This study is a secondary data analysis of the Kids’ Inpatient Database, Healthcare Cost and Utilization Project (HCUP), and Agency for Healthcare Research and Quality.9  The data set contains deidentified encounter-level information for inpatient medical and psychiatric admissions across 46 states in the United States and is collected every 3 years. In this study, we analyzed the 2016 data (N = 4200 hospitals).

Hospital encounters for girls 10 to 20 years old were eligible for inclusion. The primary outcome was initiation of LARC while hospitalized (ie, presence of International Statistical Classification of Diseases and Related Health Problems, 10th Revision [ICD-10] procedure codes for either IUDs or subdermal etonogestrel implants). Girls with ICD-10 diagnosis codes for active pregnancy but without a postpregnancy code (ie, for birth, delivery, or therapeutic, elective or spontaneous abortion) were excluded. Covariables included age (defined as young adolescents aged 10–13 years, middle adolescents aged 14–17 years, or older adolescents aged 18–20 years), race or ethnicity (white, Black, Hispanic, and “other” [Asian American or Pacific Islander, American Indian, or “other”]), insurance type (Medicaid, private, and “other” [Medicare, self-pay, no charge, or “other”]), postpregnancy status (yes or no), region of hospital location (Northeast, Midwest, South, or West), hospital type (rural or urban, teaching or nonteaching), hospital size (small, medium, or large), and hospital status (children’s or nonchildren’s hospital).

Bivariable statistics were calculated by using survey-weighted analysis10  with χ2 test for homogeneity to examine the distribution of patient-level and hospital-level characteristics across LARC initiation. A design-based, fully adjusted logistic regression model11  using Wald tests analyzed which patient- or hospital-level factors were associated with LARC initiation. Covariates included age, race or ethnicity, payer, postpartum status, region of hospital location, hospital type, hospital size, and hospital status. When studying the odds of implant versus IUD initiation, effect measure modification by hospital region was identified, requiring further stratification of the adjusted logistic regression model by region. Statistical analysis was completed by using Stata SE 16 (Stata Corp, College Station, TX) and SAS 9.4 for Windows (SAS Institute, Inc, Cary, NC).

This study was reviewed and determined by the University of North Carolina Institutional Review Board to be exempt (19-1890).

Overall, LARC initiation occurred in 0.4% (3706 of 874 193) of eligible hospital admissions. Eligible adolescents were older and more frequently white, covered by Medicaid, and had non-postpregnancy diagnoses (Table 1). The top 20 nonpostpartum diagnoses associated with LARC placement can be found in Supplemental Table 4. The majority of eligible admissions was from hospitals in the South, urban teaching hospitals, larger hospitals, and nonchildren’s hospitals. Significant differences in LARC initiation based on patient age, insurance type, race or ethnicity, and postpregnancy status, as well as hospital type and children’s hospital status, were found (all P < .01).

TABLE 1

Characteristics of Adolescent Hospitalizations and Initiation of LARC

Total Admissions, N = 87 193, n (%)LARC Initiation, n = 3706, n (%)IUD Initiation, n = 1130, n (%)Implant Initiation, n = 2576, n (%)Pa
Patient characteristics      
 Age, years at admission      
  10–13: young adolescents 122 269 (14.0) 44 (0.04) 17 (39) 27 (61) <.001 
  14–17: middle adolescents 267 546 (30.6) 1039 (0.39) 281 (27) 758 (73) — 
  18–20: older adolescents 484 379 (55.4) 2626 (0.54) 834 (32) 1792 (68) — 
 Primary insurance      
  Medicaid 493 918 (56.5) 3114 (0.63) 898 (29) 2216 (71) <.001 
  Private 313 931 (35.9) 409 (0.13) 181 (44) 228 (56) — 
  Otherb 64 979 (7.4) 179 (0.28) 49 (27) 130 (73) — 
 Race or ethnicity      
  White 405 563 (46.4) 697 (0.17) 245 (35) 452 (65) <.001 
  Black 161 399 (18.5) 1273 (0.79) 380 (30) 893 (70) — 
  Hispanic 188 824 (21.6) 1288 (0.68) 363 (28) 925 (72) — 
  Otherc 61 035 (7.0) 303 (0.5) 94 (31) 209 (69) — 
 Postpregnancy statusd      
  Yes 367 478 (42.0) 3457 (0.94) 953 (28) 2504 (72) <.001 
  No 506 715 (58.0) 249 (0.05) 178 (71) 71 (29) — 
Hospital characteristics      
 Region of hospital      
  Northeast 134 564 (15.4) 589 (0.44) 242 (41) 347 (59) .85 
  Midwest 199 357 (22.8) 688 (0.35) 254 (37) 434 (63) — 
  South 362 921 (41.5) 1661 (0.46) 390 (23) 1271 (77) — 
  West 177 351 (20.3) 769 (0.43) 245 (32) 524 (68) — 
 Hospital type      
  Rural 80 522 (9.2) 76 (0.09) 30 (39) 46 (61) <.001 
  Urban nonteaching 175 444 (20.1) 121 (0.07) 55 (45) 66 (55) — 
  Urban teaching 618 227 (70.7) 3508 (0.57) 1045 (30) 2463 (70) — 
 Hospital sizee      
  Small 117 431 (13.4) 365 (0.31) 72 (20) 293 (80) .07 
  Medium 231 082 (26.4) 635 (0.27) 186 (29) 449 (71) — 
  Large 525 680 (60.1) 2706 (0.51) 872 (32) 1834 (68) — 
 Children's hospital      
  Yes 106 589 (12.2) 115 (0.11) 56 (49) 59 (51) .005 
  No 767 604 (87.8) 3590 (0.47) 1074 (30) 2516 (70) — 
Total Admissions, N = 87 193, n (%)LARC Initiation, n = 3706, n (%)IUD Initiation, n = 1130, n (%)Implant Initiation, n = 2576, n (%)Pa
Patient characteristics      
 Age, years at admission      
  10–13: young adolescents 122 269 (14.0) 44 (0.04) 17 (39) 27 (61) <.001 
  14–17: middle adolescents 267 546 (30.6) 1039 (0.39) 281 (27) 758 (73) — 
  18–20: older adolescents 484 379 (55.4) 2626 (0.54) 834 (32) 1792 (68) — 
 Primary insurance      
  Medicaid 493 918 (56.5) 3114 (0.63) 898 (29) 2216 (71) <.001 
  Private 313 931 (35.9) 409 (0.13) 181 (44) 228 (56) — 
  Otherb 64 979 (7.4) 179 (0.28) 49 (27) 130 (73) — 
 Race or ethnicity      
  White 405 563 (46.4) 697 (0.17) 245 (35) 452 (65) <.001 
  Black 161 399 (18.5) 1273 (0.79) 380 (30) 893 (70) — 
  Hispanic 188 824 (21.6) 1288 (0.68) 363 (28) 925 (72) — 
  Otherc 61 035 (7.0) 303 (0.5) 94 (31) 209 (69) — 
 Postpregnancy statusd      
  Yes 367 478 (42.0) 3457 (0.94) 953 (28) 2504 (72) <.001 
  No 506 715 (58.0) 249 (0.05) 178 (71) 71 (29) — 
Hospital characteristics      
 Region of hospital      
  Northeast 134 564 (15.4) 589 (0.44) 242 (41) 347 (59) .85 
  Midwest 199 357 (22.8) 688 (0.35) 254 (37) 434 (63) — 
  South 362 921 (41.5) 1661 (0.46) 390 (23) 1271 (77) — 
  West 177 351 (20.3) 769 (0.43) 245 (32) 524 (68) — 
 Hospital type      
  Rural 80 522 (9.2) 76 (0.09) 30 (39) 46 (61) <.001 
  Urban nonteaching 175 444 (20.1) 121 (0.07) 55 (45) 66 (55) — 
  Urban teaching 618 227 (70.7) 3508 (0.57) 1045 (30) 2463 (70) — 
 Hospital sizee      
  Small 117 431 (13.4) 365 (0.31) 72 (20) 293 (80) .07 
  Medium 231 082 (26.4) 635 (0.27) 186 (29) 449 (71) — 
  Large 525 680 (60.1) 2706 (0.51) 872 (32) 1834 (68) — 
 Children's hospital      
  Yes 106 589 (12.2) 115 (0.11) 56 (49) 59 (51) .005 
  No 767 604 (87.8) 3590 (0.47) 1074 (30) 2516 (70) — 

—, not applicable.

a

Refers to comparison of LARC versus no-LARC-eligible admissions; significance defined as P < .05.

b

“Other insurance” includes Medicare, self-pay, no charge, and “other.”

c

“Other race” includes Asian American, Pacific Islander, American Indian, and “other.”

d

Postpregnancy status was defined as having a primary diagnosis code for birth or delivery or for spontaneous, therapeutic, or elective abortion.

e

The definition of hospital bed size varies by region and hospital type.

Several patient factors had significantly higher odds of LARC initiation (Table 2): middle adolescents compared with older adolescents; public insurance compared with private insurance; racial and ethnic minorities compared with white adolescents; and postpregnancy adolescents compared with non-postpregnancy adolescents (all P ≤ .001). Rural or urban nonteaching hospitals had significantly lower odds of LARC initiation compared with urban teaching hospitals, and small or medium sized hospitals had lower odds compared with large hospitals (all P < .01).

TABLE 2

Adjusted Odds of LARC Initiation in Hospitalized Adolescents

OR of LARCa95% CIsPb
Patient characteristics    
 Age, y    
  10–13: young adolescents 0.68 0.45–1.02 .06 
  14–17: middle adolescents 1.50 1.36–1.64 <.001 
  18–20: older adolescents Referent — — 
 Primary insurance    
  Public 1.89 1.61–2.22 <.001 
  Private Referent — — 
 Race or ethnicity    
  Black 2.45 1.72–3.49 <.001 
  Hispanic 1.87 1.15–3.04 .01 
  Otherc 2.00 1.27–3.16 <.001 
  White Referent — — 
Postpregnancy statusd    
  Yes 19.49 12.85–29.54 <.001 
  No Referent — — 
Hospital characteristics    
 Region of hospital    
  Northeast 1.19 0.60–2.38 .61 
  Midwest 1.00 0.49–2.05 .99 
  South 1.13 0.56–2.27 .74 
  West Referent — — 
 Hospital type    
  Rural 0.10 0.05–0.18 <.001 
  Urban nonteaching 0.09 0.04–0.20 <.001 
  Urban teaching Referent — — 
 Hospital sizee    
  Small 0.47 0.24–0.93 .03 
  Medium 0.45 0.25–0.83 .01 
  Large Referent — — 
 Children’s hospital    
  Yes 1.71 0.54–5.44 .36 
  No Referent — — 
OR of LARCa95% CIsPb
Patient characteristics    
 Age, y    
  10–13: young adolescents 0.68 0.45–1.02 .06 
  14–17: middle adolescents 1.50 1.36–1.64 <.001 
  18–20: older adolescents Referent — — 
 Primary insurance    
  Public 1.89 1.61–2.22 <.001 
  Private Referent — — 
 Race or ethnicity    
  Black 2.45 1.72–3.49 <.001 
  Hispanic 1.87 1.15–3.04 .01 
  Otherc 2.00 1.27–3.16 <.001 
  White Referent — — 
Postpregnancy statusd    
  Yes 19.49 12.85–29.54 <.001 
  No Referent — — 
Hospital characteristics    
 Region of hospital    
  Northeast 1.19 0.60–2.38 .61 
  Midwest 1.00 0.49–2.05 .99 
  South 1.13 0.56–2.27 .74 
  West Referent — — 
 Hospital type    
  Rural 0.10 0.05–0.18 <.001 
  Urban nonteaching 0.09 0.04–0.20 <.001 
  Urban teaching Referent — — 
 Hospital sizee    
  Small 0.47 0.24–0.93 .03 
  Medium 0.45 0.25–0.83 .01 
  Large Referent — — 
 Children’s hospital    
  Yes 1.71 0.54–5.44 .36 
  No Referent — — 

CI, confidence interval; OR, odds ratio.

a

OR is for each individual variable, adjusted for all other variables included in the table.

b

Significance defined as P < .05.

c

“Other race” includes Asian American, Pacific Islander, American Indian, and “other.”

d

Postpregnancy status was defined as having a primary diagnosis code for birth or delivery or for spontaneous, therapeutic, or elective abortion.

e

The definition of hospital bed size varies by region and hospital type.

Factors associated with implant versus IUD initiation, specifically postpregnancy status and hospital size, varied regionally (Table 3). Smaller hospital size and postpregnancy status increased the odds of implant initiation (after adjusting for age, insurance, race, and hospital type), especially for small hospitals in the Northeast and West and medium hospitals in the West (all P < .05). Postpregnancy adolescents in the Midwest, South, and West also had increased odds of implant initiation (P < .05).

TABLE 3

Logistic Regression of Patient and Hospital Characteristics Associated With Odds of Initiating Implant (Compared With IUD Initiation), by Hospital Region

RegionaVariableaORbP
Northeast: CT, ME, MA, NJ, NY, PA, RI, VT Postpregnancy status: yes 1.86 .17 
 Postpregnancy status: no Referent — 
 Hospital size: small 5.42 .002 
 Hospital size: medium 1.16 .90 
 Hospital size: large Referent — 
Midwest: IL, IN, IA, KS, MI, MN, MO, NE, ND, OH, SD, WI Postpregnancy status: yes 3.20 .02 
 Postpregnancy status: no Referent — 
 Hospital size: small 3.10 .05 
 Hospital size: medium 1.37 .69 
 Hospital size: large Referent — 
South: AR, DC, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, WV Postpregnancy status: yes 6.95 <.001 
 Postpregnancy status: no Referent — 
 Hospital size: small 1.39 .65 
 Hospital size: medium 1.52 .36 
 Hospital size: large Referent — 
West: AK, AZ, CA, CO, HI, MT, NV, NM, OR, UT, WA, WY Postpregnancy status: yes 3.67 <.001 
 Postpregnancy status: no Referent — 
 Hospital size: small 2.89 .03 
 Hospital size : medium 2.98 .02 
 Hospital size: large Referent — 
RegionaVariableaORbP
Northeast: CT, ME, MA, NJ, NY, PA, RI, VT Postpregnancy status: yes 1.86 .17 
 Postpregnancy status: no Referent — 
 Hospital size: small 5.42 .002 
 Hospital size: medium 1.16 .90 
 Hospital size: large Referent — 
Midwest: IL, IN, IA, KS, MI, MN, MO, NE, ND, OH, SD, WI Postpregnancy status: yes 3.20 .02 
 Postpregnancy status: no Referent — 
 Hospital size: small 3.10 .05 
 Hospital size: medium 1.37 .69 
 Hospital size: large Referent — 
South: AR, DC, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, WV Postpregnancy status: yes 6.95 <.001 
 Postpregnancy status: no Referent — 
 Hospital size: small 1.39 .65 
 Hospital size: medium 1.52 .36 
 Hospital size: large Referent — 
West: AK, AZ, CA, CO, HI, MT, NV, NM, OR, UT, WA, WY Postpregnancy status: yes 3.67 <.001 
 Postpregnancy status: no Referent — 
 Hospital size: small 2.89 .03 
 Hospital size : medium 2.98 .02 
 Hospital size: large Referent — 

aOR, adjusted odds ratio; —, not applicable.

a

Missing data are present: the states of Alabama, Delaware, and Idaho do not participate in HCUP. New Hampshire participates in HCUP but did not provide data in time for the 2016 Kids’ Inpatient Database.

b

Adjusted for age, insurance, race, and hospital type.

In this study, we found that LARC initiation occurred in <1% of adolescent hospitalizations and 90% of LARC placement occurred in adolescents with postpregnancy primary diagnoses. Additionally, middle adolescents (aged 14–17 years), Black and Hispanic adolescents, and adolescents who receive public insurance had higher odds of LARC initiation.

Middle adolescents in particular were more likely to initiate LARC. Although our data cannot elucidate reasons for this, it is possible that more pregnancies at this age were unintended12  or that providers were more proactive in initiating immediate postpregnancy LARC in this age group compared with older adolescents to prevent repeat pregnancies.13  Additionally, this study suggests several barriers to accessing inpatient contraceptive services for nonpregnant adolescents. The low rates of LARC initiation in adolescents hospitalized for medical diagnoses other than pregnancy could represent important missed opportunities for LARC initiation, especially given low rates of contraception provision in adolescents prescribed teratogenic medications in outpatient settings14  and the high rates of readmission for adolescents with chronic diseases.15  Although we were unable to examine this specifically, these findings may suggest that nonobstetric inpatient providers may be less aware of the contraceptive needs of this patient population, may be less comfortable providing LARC to adolescent patients, or may be less aware of the protections offered by minor consent laws and confidentiality related to sexual and reproductive health.

Whereas white adolescents made up the majority of eligible hospital admissions, nonwhite adolescents more frequently initiated LARC after adjusting for age, insurance type, and postpregnancy status. There may be a number of reasons for this difference, including that physicians hoping to reduce unplanned pregnancies in populations with the highest rates may be more mindful to offer LARC methods to those patients.16  Although exploration of physician factors was not possible through the data set used for our study, it is possible that physicians may be disproportionately offering LARC on the basis of biases that stem from the historical, systemic, and structural undervaluation of minority women’s reproductive autonomy.17  Additionally, patient factors may impact acceptance of LARC: nonwhite adolescents may be accepting offered LARC because of poor access outside of the hospital18  or feeling disproportionately pressured to accept LARC from their providers compared with white adolescents.19  Future research is needed to study the differences in contraceptive counseling methods by providers among different racial and ethnic minorities and how LARC initiation is impacted by receipt of preferred counseling methods among racial and ethnic minorities. Furthermore, prospective studies are needed on providers’ use and patients’ perceptions of patient-centered approaches to contraceptive counseling that maximize patient autonomy and promote respect for each individual’s choices about childbearing and contraception use.2022 

Postpregnancy status and smaller hospital size had higher odds of implant initiation compared with IUD initiation, and this association differed by region. Implants may be more likely to be placed because the procedure is less invasive and they are more widely accepted than IUDs by adolescents.23  These findings may also be due to regional variations in provider training and comfort with LARC,24  differences in state-level reimbursement of immediate postpregnancy LARC,25  or preference for implant due to concern for possible expulsion of postpregnancy IUD (notably, the American College of Obstetricians and Gynecologists26  encourages immediate postpregnancy IUD placement for those at greatest risk of not having recommended follow-up). More than 60% of inpatient pediatricians think initiation of LARC in the inpatient setting is appropriate, although they cite insufficient training, insufficient exposure to maintain skills, lack of time, and concerns about follow-up as potential barriers.27  Addressing LARC, and especially IUD, capacity in rural, nonteaching, and smaller hospitals, such as increasing access to training and continuing education opportunities, may be particularly important in improving LARC access.

This study had several limitations. First, we could not measure if adolescents had preexisting LARC or other contraception, and, as such, we may have seen a lower proportion of LARC placement if contraception was previously initiated outpatient. Second, incomplete or inaccurate coding may have resulted in some LARCs not being captured and therefore not included in our analysis. Third, because of the limitations of the data available, we could not measure why LARC may have been placed (eg, for treatment of abnormal uterine bleeding versus for pregnancy prevention) or frequency of LARC in adolescents with associated high-risk diagnoses (eg, mental health or substance use), although this is an important area for future inquiry. Fourth, we could not assess why LARC may not have been placed for an eligible and interested adolescent (eg, if there was provider discomfort in placement of LARC or if a provider intended to initiate LARC but had issues with insurance reimbursement). Relatedly, we were unable to assess which provider specialties were or were not initiating LARCs. Finally, we were unable to conduct state-level analysis because of data use restrictions and so were unable to evaluate if differences in LARC initiation varied by state-determined public insurance reimbursement or parental consent laws.

The results of this study have important implications for both health care providers and policymakers. Hospitalization can be an important opportunity to initiate LARC for adolescents, but inconsistent insurance reimbursement25  may limit LARC placement. Universal coverage of LARC by all insurance companies without cost-sharing,28,29  unbundling postpartum LARC from other maternity care,25  consistent Medicaid reimbursement of immediate postpregnancy LARC,30  and reimbursement for contraceptive counseling31  may increase LARC access. Especially in rural and nonteaching hospital settings, provider discomfort27  and a lack of hospital-based programs32  may decrease access, which may require policy changes, such as increasing provider education and institutional protocols for LARC initiation26  and reducing logistic and administrative barriers to increase supply.25  Future research is needed to clarify the causes of the low rates of inpatient LARC initiation and to identify and close gaps in the number of adolescents desiring and initiating LARC in inpatient settings.

We acknowledge the HCUP Data Partners that contribute to HCUP: Alaska, Arizona, Arkansas, California, Colorado, Connecticut, Delaware, District of Columbia, Florida, Georgia, Hawaii, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Utah, Vermont, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

FUNDING: Partially supported by a Ruth L. Kirschstein National Research Service Award grant from the Health Resources and Services Administration (5 T32 14001). The funder did not participate in the work.

Drs Allison, Flower, and Perry conceptualized and designed the study and drafted the initial manuscript; Mr Ritter conducted the initial analyses and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted.

1.
Martinez
G
,
Copen
CE
,
Abma
JC
.
Teenagers in the United States: sexual activity, contraceptive use, and childbearing, 2006-2010 national survey of family growth
.
Vital Health Stat 23
.
2011
;(
31
):
1
35
2.
Finer
LB
.
Unintended pregnancy among U.S. adolescents: accounting for sexual activity
.
J Adolesc Health
.
2010
;
47
(
3
):
312
314
3.
Martin
JA
,
Hamilton
BE
,
Osterman
MJK
,
Driscoll
AK
.
Births: final data for 2018
.
Natl Vital Stat Rep
.
2019
;
68
(
13
):
1
47
4.
National Conference of State Legislatures
.
Teen pregnancy prevention
.
2018
.
5.
Lindberg
LD
,
Santelli
JS
,
Desai
S
.
Changing patterns of contraceptive use and the decline in rates of pregnancy and birth among U.S. adolescents, 2007-2014
.
J Adolesc Health
.
2018
;
63
(
2
):
253
256
6.
Kavanaugh
ML
,
Jerman
J
.
Contraceptive method use in the United States: trends and characteristics between 2008, 2012 and 2014
.
Contraception
.
2018
;
97
(
1
):
14
21
7.
Riese
A
,
Houck
C
,
Abdullahi
N
,
Davies
AC
,
Baird
J
,
Alverson
B
.
An electronic sexual health module for hospitalized adolescent girls
.
Hosp Pediatr
.
2019
;
9
(
11
):
880
887
8.
Walston
JM
,
Foster
BA
,
Gardner
TA
,
Benchbani
H
,
Noelck
M
,
Austin
JP
.
Sexual history and contraception documentation in hospitalized adolescents: are technology-dependent patients overlooked?
Hosp Pediatr
.
2019
;
9
(
12
):
967
973
9.
Healthcare Cost and Utilization Project
.
Kids’ Inpatient Database (KID)
.
2016. Rockville, MD
:
Agency for Healthcare Research and Quality
10.
Lohr
SL
.
Sampling: Design and Analysis: Design and Analysis
.
2nd ed. Boca Raton, FL
:
CRC Press
;
2019
11.
Chambers
RL
,
Skinner
CJ
.
Analysis of Survey Data
.
1st ed. Hoboken, NJ
:
Wiley
;
2003
12.
Finer
LB
,
Zolna
MR
.
Declines in unintended pregnancy in the United States, 2008–2011
.
N Engl J Med
.
2016
;
374
(
9
):
843
852
13.
ACOG Committee Opinion No. 735: adolescents and long-acting reversible contraception: implants and intrauterine devices
.
Obstet Gynecol
.
2018
;
131
(
5
):
e130
e139
14.
Stancil
SL
,
Miller
M
,
Briggs
H
,
Lynch
D
,
Goggin
K
,
Kearns
G
.
Contraceptive provision to adolescent females prescribed teratogenic medications
.
Pediatrics
.
2016
;
137
(
1
):
e20151454
15.
Dunbar
P
,
Hall
M
,
Gay
JC
, et al
.
Hospital readmission of adolescents and young adults with complex chronic disease
.
JAMA Netw Open
.
2019
;
2
(
7
):
e197613
16.
Balsa
AI
,
McGuire
TG
,
Meredith
LS
.
Testing for statistical discrimination in health care
.
Health Serv Res
.
2005
;
40
(
1
):
227
252
17.
Gubrium
AC
,
Mann
ES
,
Borrero
S
, et al
.
Realizing reproductive health equity needs more than long-acting reversible contraception (LARC)
.
Am J Public Health
.
2016
;
106
(
1
):
18
19
18.
Martins
SL
,
Starr
KA
,
Hellerstedt
WL
,
Gilliam
ML
.
Differences in family planning services by rural-urban geography: survey of title X-supported clinics in great plains and Midwestern states
.
Perspect Sex Reprod Health
.
2016
;
48
(
1
):
9
16
19.
Dehlendorf
C
,
Ruskin
R
,
Grumbach
K
, et al
.
Recommendations for intrauterine contraception: a randomized trial of the effects of patients’ race/ethnicity and socioeconomic status
.
Am J Obstet Gynecol
.
2010
;
203
(
4
):
319.e1
319.e8
20.
Higgins
JA
,
Kramer
RD
,
Ryder
KM
.
Provider bias in long-acting reversible contraception (LARC) promotion and removal: perceptions of young adult women
.
Am J Public Health
.
2016
;
106
(
11
):
1932
1937
21.
Jackson
AV
,
Karasek
D
,
Dehlendorf
C
,
Foster
DG
.
Racial and ethnic differences in women’s preferences for features of contraceptive methods
.
Contraception
.
2016
;
93
(
5
):
406
411
22.
Jackson
A
,
Karasek
D
,
Dehlendorf
C
,
Greene-Foster
D
.
Contraceptive features preferred by black and Latina women
.
Contraception
.
2013
;
88
(
2
):
311
23.
Mestad
R
,
Secura
G
,
Allsworth
JE
,
Madden
T
,
Zhao
Q
,
Peipert
JF
.
Acceptance of long-acting reversible contraceptive methods by adolescent participants in the Contraceptive CHOICE Project
.
Contraception
.
2011
;
84
(
5
):
493
498
24.
Vaaler
ML
,
Kalanges
LK
,
Fonseca
VP
,
Castrucci
BC
.
Urban-rural differences in attitudes and practices toward long-acting reversible contraceptives among family planning providers in Texas
.
Womens Health Issues
.
2012
;
22
(
2
):
e157
e162
25.
Walls
,
Gifford
K
,
Ranji
U
,
Salganicoff
A
,
Gomez
I
.
Medicaid coverage of family planning benefits: results from a state survey
.
2016
.
26.
American College of Obstetricians and Gynecologists’ Committee on Obstetric Practice
.
Committee opinion No. 670: immediate postpartum long-acting reversible contraception
.
Obstet Gynecol
.
2016
;
128
(
2
):
e32
e37
27.
Goldstein
RL
,
Carlson
JL
,
Halpern-Felsher
B
.
Contraception for adolescents and young adults in the inpatient setting: the providers’ perspective
.
Hosp Pediatr
.
2018
;
8
(
4
):
194
199
28.
Winner
B
,
Peipert
JF
,
Zhao
Q
, et al
.
Effectiveness of long-acting reversible contraception
.
N Engl J Med
.
2012
;
366
(
21
):
1998
2007
29.
Eisenberg
D
,
McNicholas
C
,
Peipert
JF
.
Cost as a barrier to long-acting reversible contraceptive (LARC) use in adolescents
.
J Adolesc Health
.
2013
;
52
(
suppl 4
):
S59
S63
30.
Lopez
LM
,
Bernholc
A
,
Hubacher
D
,
Stuart
G
,
Van Vliet
HAAM
.
Immediate postpartum insertion of intrauterine device for contraception
.
Cochrane Database Syst Rev
.
2015
;(
6
):
CD003036
31.
Rosenzweig
C
,
Sobel
L
,
Salganicoff
A
,
Moore
JE
,
Hernandez Gray
AA
.
Medicaid Managed Care and the Provision of Family Planning Services
.
Menlo Park, CA
:
Kaiser Family Foundation
;
2017
32.
Hofler
LG
,
Cordes
S
,
Cwiak
CA
,
Goedken
P
,
Jamieson
DJ
,
Kottke
M
.
Implementing immediate postpartum long-acting reversible contraception programs
.
Obstet Gynecol
.
2017
;
129
(
1
):
3
9

Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Perry is an instructor for Nexplanon; and Dr Allison, Mr Ritter, and Dr Flower have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: Dr Perry is an instructor for Nexplanon; and Dr Allison, Mr Ritter, and Dr Flower have indicated they have no financial relationships relevant to this article to disclose.