BACKGROUND

Reduction of physical restraint utilization is a goal of high-quality hospital care, but there is little nationally-representative data about physical restraint utilization in hospitalized children in the United States. This study reports the rate of physical restraint coding among hospitalizations for patients aged 1 to 18 years old in the United States and explores associated demographic and diagnostic factors.

METHODS

The Kids’ Inpatient Database, an all-payors database of community hospital discharges in the United States, was queried for hospitalizations with a diagnosis of physical restraint status in 2019. Logistic regression using patient sociodemographic characteristics was used to characterize factors associated with physical restraint coding.

RESULTS

A coded diagnosis of physical restraint status was present for 8893 (95% confidence interval [CI]: 8227–9560) hospitalizations among individuals aged 1 to 18 years old, or 0.63% of hospitalizations. Diagnoses associated with physical restraint varied by age, with mental health diagnoses overall the most frequent in an adjusted model, male sex (adjusted odds ratio [aOR] 1.56; 95% CI: 1.47–1.65), Black race (aOR 1.43; 95% CI: 1.33–1.55), a primary mental health or substance diagnosis (aOR 7.13; 95% CI: 6.42–7.90), Medicare or Medicaid insurance (aOR 1.33; 95% CI: 1.24–1.43), and more severe illness (aOR 2.83; 95% CI: 2.73–2.94) were associated with higher odds of a hospitalization involving a physical restraint code.

CONCLUSIONS

Physical restraint coding varied by age, sex, race, region, and disease severity. These results highlight potential disparities in physical restraint utilization, which may have consequences for equity.

The use of physical restraints to maintain patient and staff safety is a widespread practice in many healthcare facilities, including in the care of children and adolescents. In pediatrics, the definition of physical restraint is uniquely broad given the range of possible interventions by family or staff in the care of a child, which differ substantially for young infants compared with teenagers. For example, acute restraint of infants by parents for procedures like venipuncture is intentionally reframed as “hugging” for both parents and staff,1  and physical interventions, such as elevated crib rails that are routinely used for safety in young children, would be classified as physical restraints in older children or adults. Recognizing the broad range of interventions that may be used to physically restrain youth, the Joint Commission’s Comprehensive Manual for Behavioral Health Care defines physical holding of children and youth as distinct from restraint,2  a distinction that does not apply to adult patients.

The use of physical restraints is the subject of close ethical and medicolegal scrutiny,1,3  especially given the potential for rare but tragic consequences, including death.4  Physical restraints may be used in the setting of agitation and may also be applied for medical indications, such as supplemental feeding5  or the induction of general anesthesia.6  Potential adverse effects of physical restraints include psychological distress and trauma for patients,7  families,8  and hospital staff.9  Morbidity and ethical concerns associated with restraints have led to numerous calls to minimize their use whenever possible.1,3,10,11  As a result, accurately determining the prevalence and characteristics of restraint use in pediatric patients is of prime importance to ensuring appropriate and equitable use.

Current estimates of restraint use in pediatrics are often domain-specific, with most literature focusing on a single clinical area (eg, emergency department, PICU, or behavioral health inpatient unit). Although there has been extensive research into physical restraints predominantly using data derived from the electronic medical records of individual hospitals, none have used national data and so it is unclear if disparities identified in these studies generalize to children treated in other health systems in the United States. Moreover, given reduced numbers of pediatric hospitals between 2009 to 2019 and increasing rates of hospitalizations for mental health conditions (including boarding on pediatric units while awaiting mental health beds),12  community hospitals represent an important care location for which restraint utilization is not well characterized.

The use of administrative claims data is one approach to broadly defining the burden of pediatric disease across multiple centers; this approach has previously been useful in defining the burden of pharmacologic restraint13  and pediatric delirium,14  a common indication for physical restraint. An improved understanding of restraint utilization among hospitalized children could help target interventions toward pediatric patients at the highest risk of receiving physical restraint, which based on existing literature, may include older children, males, individuals with mental health diagnoses, and those of Black race.1518  This study characterizes the occurrence of physical restraint coding in hospitalized children using nationally-representative administrative claims data in pursuit of these goals and describes the sociodemographics and primary diagnoses of patients undergoing physical restraint.

This analysis used the 2019 edition of the Kids’ Inpatient Database (KID), from the Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality. The KID is an administrative claims database including information for patients aged 20 or younger receiving inpatient care at community hospitals in the United States. The KID samples 80% of non-newborn discharges from 3998 nonfederal acute care hospitals in 49 states and is produced every 3 years. Data from 2019 is the most recent available. Data are provided for hospitalizations in a deidentified format, with no mechanism for linking database entries to identified individuals. KID data are not separated by hospital unit, and so data for general wards, ICUs, and psychiatric units within acute care hospitals are included. As this is a deidentified, publicly available database, this study was determined to be Not Human Subjects Research by the Institutional Review Board.

Hospitalizations involving physical restraint coding were identified using International Statistical Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) code Z78.1 “physical restraint status.” This code includes all episodes of physical restraint and does not distinguish the duration of restraint, type of restraint, or primary indication for restraint. Discharges were included in this analysis for patients from ages 1 to 18 years old if Z78.1 was included among the discharge diagnosis codes.

Sociodemographic characteristics are presented descriptively based on data from the KID. The KID is derived from state-level data, which is then recoded into uniform categories standardized during the production of the KID. As a result, there is variability in the underlying sociodemographic data as different hospitals and states report data differently, and it is not possible to know how the racial category was assigned for any given hospitalization in the KID. Race and ethnicity are social constructs subjective to those reporting. The KID combines race and ethnic categories, with values of white, Black, Hispanic, Asian or Pacific Islander, Native American, other, and missing. Given small sample sizes in certain KID race categories, to maintain individual patient privacy as required by the KID data use agreement, the categories of “Asian or Pacific Islander,” “Native American,” and “other” were combined into a single category of “other.”

Primary hospital diagnoses were identified from the discharge diagnoses and classified according to the Pediatric Clinical Classification System (PECCS),19  which groups the 72 446 ICD-10-CM diagnosis codes into 834 clinically distinctive categories for pediatric medical conditions.

The KID is based on a survey design in which hospitals are stratified based on geographic region, hospital ownership, teaching status, and bed size and then discharges are sampled within strata. As a result, all reported variables come with an associated variance. This variance is used to present sample uncertainty for the total number of discharges with a physical restraint code, whereas weighted point estimates are reported for all other analyses. All analyses were conducted on data weighted according to the appropriate KID discharge weight to obtain national estimates.

For the primary statistical analysis, a logistic regression incorporating the KID survey design was performed on the binary outcome of a hospitalization, including discharge a billing code for physical restraint status (compared with hospitalizations not including a physical restraint code). In this model, age (z score), sex (male versus female), race or ethnicity (Black, Hispanic, or other versus white), primary mental health or substance abuse diagnosis (yes versus no), region (Northeast, Midwest, or South versus West), income quartile of the patient’s ZIP code (first, second, or third quartile versus highest quartile), primary payor (Medicare or Medicaid; or other versus commercial insurance), and patient severity (defined based off of All Patient Refined-Diagnosis Related Groups′ Severity of Illness)20,21  were descriptor variables. A term for race was included in this regression given prior literature indicating disparities in race utilization based on race. All analyses were conducted using SPSS (version 29; IBM Software, Inc, Armonk, NY). This study is reported in accordance with the Reporting of Studies Conducted Using Observational Routinely-collected Health Data statement.22 

In the 2019 KID, 8893 hospitalizations (95% confidence interval [CI]: 8227–9560) for patients 1 to 18 years old involved a discharge code for physical restraint status and 1 409 614 (95% CI: 1 367 522–1 469 494) did not, for an overall rate of 0.63% of pediatric hospitalizations involving a code for physical restraints. Demographically, 57.2% of hospitalizations with a restraint code were for male patients and 42.8% for female patients, whereas 47.7% of overall hospitalizations were for male patients. Full demographic information for hospitalizations with and without restraint coding is given in Table 1. Physical restraint coding varied with age, from a low of 0.27% of hospitalizations for 4-year-old patients to a maximum of 0.91% of hospitalizations for 15-year-old patients (Fig 1).

TABLE 1

Demographics of Hospitalizations With And Without a Discharge Diagnosis of Physical Restraint Status in the 2019 KID

RestrainedNot Restrained
N%N%
N 8893 (8227–9560)  1 409 614 (1 367 522–1 469 494) 
Age (y), median, IQR 14 (9–16)  11 (4–16)  
 1–5 1327 14.9 420 088 29.8 
 6–11 1720 19.3 288 292 20.5 
 12–15 2728 30.7 314 942 22.3 
 16–18 3116 35.0 386 291 27.4 
Sex 
 Male 5086 57.2 672 131 47.7 
 Female 3802 42.8 737 318 52.3 
Race 
 Black 2125 23.9 249 977 17.7 
 Hispanic 1455 16.4 305 460 21.7 
 Other 772 8.8 133 556 9.5 
 Missing 522 5.9 69 575 4.9 
 White 4019 45.2 651 046 46.2 
Hospital region 
 Northeast 1906 21.4 240 019 17.0 
 Midwest 2196 24.7 321 990 22.8 
 South 2993 33.6 536 923 38.1 
 West 1799 20.2 310 682 22.0 
Population of county of residence 
 Central metro county > 1 million 3164 35.6 453 101 32.1 
 Fringe metro county > 1 million 2238 25.2 339 803 24.1 
 Metro area 250 000–999 999 1900 21.4 303 522 21.5 
 Metro area 50 000–249 000 633 7.1 118 288 8.4 
 Micropolitan 531 6.0 111 052 7.9 
 Noncore county 378 4.3 76 892 5.5 
Household income quartile for pt ZIP code 
 1 2741 30.8 438 619 31.1 
 2 2139 24.0 341 385 24.2 
 3 2116 23.8 334 493 23.7 
 4 1772 19.9 276 649 19.6 
Discharge quarter 
 Jan–Mar 2058 23.1 364 179 25.8 
 Apr–Jun 2227 25.0 348 769 24.7 
 Jul–Sep 2305 25.9 331 990 23.6 
 Oct–Dec 2297 25.8 364 402 25.9 
Admission type 
 Nonelective 7929 89.2 1 126 271 79.9 
 Elective 952 10.7 280 436 19.9 
Primary service line 
 Maternal and neonatal 25 0.3 96 429 6.8 
 Mental health and substance use 3845 43.2 210 074 14.9 
 Injury 1129 12.7 95 412 6.8 
 Surgical 1012 11.4 213 137 15.1 
 Medical 2881 32.4 794 562 56.4 
Hospital type 
 Children’s hospital 2464 27.7 426 887 30.3 
 Not a children’s hospital 6429 72.3 982 738 69.7 
Injury status 
 No injury diagnosis 6213 69.9 1 249 114 88.6 
 Injury diagnosis is primary 1776 20.0 114 875 8.1 
 Injury diagnosis, nonprimary 904 10.2 45 625 3.2 
Operating room 
 No major procedure on discharge record 7416 83.4 1 117 575 79.3 
 Major or procedure on discharge record 1477 16.6 292 040 20.7 
Primary payor 
 Medicare or Medicaid 5379 60.4 760 542 53.9 
 Commercial insurance 2951 33.2 549 211 39.0 
 Other 547 6.2 97 734 6.9 
Admission status 
 Not transferred in 6056 68.1 1 135 876 80.6 
 Transferred from acute care hospital 2079 23.4 213 873 15.2 
 Transferred from another facility 722 8.1 53 681 3.8 
Patient disposition 
 Discharged 6492 73.0 1 312 204 93.1 
 Transferred to short-term hospital 349 3.9 19 871 1.4 
 Transferred to another facility 1676 18.8 34 981 2.5 
 Home health care 249 2.8 32 677 2.3 
 Against medical advice 51 0.6 4224 0.3 
 Died 62 0.7 4994 0.4 
Hospital length of stay, days (median, IQR) 7 (3–15)  3 (2–5)  
Total charges, $ (median, IQR) $48 568 ($22 445–$128 034)  $23 435 ($12 787–$47 431)  
RestrainedNot Restrained
N%N%
N 8893 (8227–9560)  1 409 614 (1 367 522–1 469 494) 
Age (y), median, IQR 14 (9–16)  11 (4–16)  
 1–5 1327 14.9 420 088 29.8 
 6–11 1720 19.3 288 292 20.5 
 12–15 2728 30.7 314 942 22.3 
 16–18 3116 35.0 386 291 27.4 
Sex 
 Male 5086 57.2 672 131 47.7 
 Female 3802 42.8 737 318 52.3 
Race 
 Black 2125 23.9 249 977 17.7 
 Hispanic 1455 16.4 305 460 21.7 
 Other 772 8.8 133 556 9.5 
 Missing 522 5.9 69 575 4.9 
 White 4019 45.2 651 046 46.2 
Hospital region 
 Northeast 1906 21.4 240 019 17.0 
 Midwest 2196 24.7 321 990 22.8 
 South 2993 33.6 536 923 38.1 
 West 1799 20.2 310 682 22.0 
Population of county of residence 
 Central metro county > 1 million 3164 35.6 453 101 32.1 
 Fringe metro county > 1 million 2238 25.2 339 803 24.1 
 Metro area 250 000–999 999 1900 21.4 303 522 21.5 
 Metro area 50 000–249 000 633 7.1 118 288 8.4 
 Micropolitan 531 6.0 111 052 7.9 
 Noncore county 378 4.3 76 892 5.5 
Household income quartile for pt ZIP code 
 1 2741 30.8 438 619 31.1 
 2 2139 24.0 341 385 24.2 
 3 2116 23.8 334 493 23.7 
 4 1772 19.9 276 649 19.6 
Discharge quarter 
 Jan–Mar 2058 23.1 364 179 25.8 
 Apr–Jun 2227 25.0 348 769 24.7 
 Jul–Sep 2305 25.9 331 990 23.6 
 Oct–Dec 2297 25.8 364 402 25.9 
Admission type 
 Nonelective 7929 89.2 1 126 271 79.9 
 Elective 952 10.7 280 436 19.9 
Primary service line 
 Maternal and neonatal 25 0.3 96 429 6.8 
 Mental health and substance use 3845 43.2 210 074 14.9 
 Injury 1129 12.7 95 412 6.8 
 Surgical 1012 11.4 213 137 15.1 
 Medical 2881 32.4 794 562 56.4 
Hospital type 
 Children’s hospital 2464 27.7 426 887 30.3 
 Not a children’s hospital 6429 72.3 982 738 69.7 
Injury status 
 No injury diagnosis 6213 69.9 1 249 114 88.6 
 Injury diagnosis is primary 1776 20.0 114 875 8.1 
 Injury diagnosis, nonprimary 904 10.2 45 625 3.2 
Operating room 
 No major procedure on discharge record 7416 83.4 1 117 575 79.3 
 Major or procedure on discharge record 1477 16.6 292 040 20.7 
Primary payor 
 Medicare or Medicaid 5379 60.4 760 542 53.9 
 Commercial insurance 2951 33.2 549 211 39.0 
 Other 547 6.2 97 734 6.9 
Admission status 
 Not transferred in 6056 68.1 1 135 876 80.6 
 Transferred from acute care hospital 2079 23.4 213 873 15.2 
 Transferred from another facility 722 8.1 53 681 3.8 
Patient disposition 
 Discharged 6492 73.0 1 312 204 93.1 
 Transferred to short-term hospital 349 3.9 19 871 1.4 
 Transferred to another facility 1676 18.8 34 981 2.5 
 Home health care 249 2.8 32 677 2.3 
 Against medical advice 51 0.6 4224 0.3 
 Died 62 0.7 4994 0.4 
Hospital length of stay, days (median, IQR) 7 (3–15)  3 (2–5)  
Total charges, $ (median, IQR) $48 568 ($22 445–$128 034)  $23 435 ($12 787–$47 431)  

IQR, interquartile range.

FIGURE 1

Percentage of overall hospitalizations that involve a diagnosis of physical restraint status versus the age of the patient.

FIGURE 1

Percentage of overall hospitalizations that involve a diagnosis of physical restraint status versus the age of the patient.

Close modal

Hospitalizations with a coded restraint diagnosis included a wide variation of primary discharge diagnoses, which differed among pediatric patients of different ages. Primary discharge diagnoses, based on PECCS codes, are listed in Table 2. Overall, mood disorders (a category that includes the diagnoses for mood disorders because of known physiologic conditions, other or unspecified mood disorders, and disruptive mood dysregulation disorder) was the most common PECCS category (790 hospitalizations; 9.1%), followed by major depressive disorder (710 hospitalizations; 8.2%), suicide and intentional self-inflicted injury (687 hospitalizations; 7.9%), and respiratory failure insufficiency or arrest (384 hospitalizations; 4.4%). Among patients ages 1 to 5, the most common diagnostic categories for hospitalizations with a restraint code are all primarily medical (with respiratory failure, seizures, sepsis, and bronchiolitis as the top 4 categories), whereas for all other age ranges, the top diagnostic categories are primarily psychiatric in nature, with mood, conduct, and psychotic disorders being among the most frequent. Raw ICD-10-CM codes for primary diagnoses for hospitalizations with a physical restraint code are listed in Supplemental Tables 5–9.

TABLE 2

PECCS Categories for the Primary Discharge Diagnosis of Hospitalizations With a Coded Diagnosis of Physical Restraint Status, Overall and by Age Categories

Overall (N = 8893)N%
Mood disorders 790 9.1 
Mood disorders (major depressive disorder) 710 8.2 
Suicide and intentional self-inflicted injury 687 7.9 
Respiratory failure; insufficiency; arrest 384 4.4 
Schizophrenia and other psychotic disorders 380 4.4 
Mood disorders (bipolar disorder) 350 
Intracranial injury 343 3.9 
Seizures with and without intractable epilepsy 230 2.6 
Attention-deficit hyperactivity disorder 217 2.5 
Septicemia (except in labor) 215 2.5 
Autistic disorder 177 
Oppositional defiant disorder 152 1.7 
Conduct disorder 150 1.7 
Intermittent explosive disorder 148 1.7 
Posttraumatic stress disorder 134 1.5 
Ages 1–5 y (N = 1327) 
 Respiratory failure; insufficiency; arrest 196 15.7 
 Seizures with and without intractable epilepsy 80 6.4 
 Septicemia (except in labor) 67 5.4 
 Acute bronchiolitis 45 3.6 
 Cleft lip and palate 45 3.6 
 Pneumonia 42 3.4 
 Intracranial injury 26 2.1 
 Skull and face fractures 21 1.7 
 Congenital anomalies of skull and face bones 20 1.6 
 Complication of device; implant or graft 19 1.5 
 Partial epilepsy with and without intractable epilepsy 18 1.4 
 Asthma 17 1.4 
 Hypoplastic left heart syndrome 17 1.4 
 Burns 17 1.4 
 Complications of surgical procedures or medical care 16 1.3 
 Stenosis of larynx 15 1.2 
Ages 6–11 y (N = 1720) 
 Mood disorders 324 19.8 
 Attention-deficit hyperactivity disorder 127 7.7 
 Oppositional defiant disorder 73 4.5 
 Conduct disorder 65 
 Mood disorders (major depressive disorder) 63 3.8 
 Respiratory failure; insufficiency; arrest 60 3.7 
 Intermittent explosive disorder 51 3.1 
 Seizures with and without intractable epilepsy 50 3.1 
 Autistic disorder 50 3.1 
 Posttraumatic stress disorder 45 2.7 
 Intracranial injury 38 2.3 
 Septicemia (except in labor) 34 2.1 
 Mood disorders (bipolar disorder) 34 2.1 
 Encephalitis (except that caused by tuberculosis or sexually transmitted disease) 27 1.6 
 Suicide and intentional self-inflicted injury 23 1.4 
Ages 12–15 y (N = 2728) 
 Mood disorders (major depressive disorder) 381 14.5 
 Mood disorders 334 12.7 
 Suicide and intentional self-inflicted injury 292 11.1 
 Mood disorders (bipolar disorder) 106 
 Intracranial injury 87 3.3 
 Attention-deficit hyperactivity disorder 68 2.6 
 Autistic disorder 65 2.5 
 Oppositional defiant disorder 59 2.2 
 Intermittent explosive disorder 54 2.1 
 Posttraumatic stress disorder 53 
 Septicemia (except in labor) 49 1.9 
 Seizures with and without intractable epilepsy 49 1.9 
 Conduct disorder 48 1.8 
 Respiratory failure; insufficiency; arrest 47 1.8 
 Residual codes; unclassified 46 1.7 
Ages 16–18 y (N = 3116) 
 Suicide and intentional self-inflicted injury 375 12.5 
 Schizophrenia and other psychotic disorders 324 10.8 
 Mood disorders (major depressive disorder) 263 8.8 
 Mood disorders (bipolar disorder) 207 6.9 
 Intracranial injury 177 5.9 
 Mood disorders 128 4.3 
 Substance-related disorders 115 3.8 
 Respiratory failure; insufficiency; arrest 79 2.6 
 Septicemia (except in labor) 58 1.9 
 Autistic disorder 58 1.9 
 Crushing injury or internal injury 56 1.9 
 Alcohol-related disorders 54 1.8 
 Poisoning by psychotropic agents 50 1.7 
 Poisoning by other medications and drugs 48 1.6 
 Seizures with and without intractable epilepsy 47 1.6 
Overall (N = 8893)N%
Mood disorders 790 9.1 
Mood disorders (major depressive disorder) 710 8.2 
Suicide and intentional self-inflicted injury 687 7.9 
Respiratory failure; insufficiency; arrest 384 4.4 
Schizophrenia and other psychotic disorders 380 4.4 
Mood disorders (bipolar disorder) 350 
Intracranial injury 343 3.9 
Seizures with and without intractable epilepsy 230 2.6 
Attention-deficit hyperactivity disorder 217 2.5 
Septicemia (except in labor) 215 2.5 
Autistic disorder 177 
Oppositional defiant disorder 152 1.7 
Conduct disorder 150 1.7 
Intermittent explosive disorder 148 1.7 
Posttraumatic stress disorder 134 1.5 
Ages 1–5 y (N = 1327) 
 Respiratory failure; insufficiency; arrest 196 15.7 
 Seizures with and without intractable epilepsy 80 6.4 
 Septicemia (except in labor) 67 5.4 
 Acute bronchiolitis 45 3.6 
 Cleft lip and palate 45 3.6 
 Pneumonia 42 3.4 
 Intracranial injury 26 2.1 
 Skull and face fractures 21 1.7 
 Congenital anomalies of skull and face bones 20 1.6 
 Complication of device; implant or graft 19 1.5 
 Partial epilepsy with and without intractable epilepsy 18 1.4 
 Asthma 17 1.4 
 Hypoplastic left heart syndrome 17 1.4 
 Burns 17 1.4 
 Complications of surgical procedures or medical care 16 1.3 
 Stenosis of larynx 15 1.2 
Ages 6–11 y (N = 1720) 
 Mood disorders 324 19.8 
 Attention-deficit hyperactivity disorder 127 7.7 
 Oppositional defiant disorder 73 4.5 
 Conduct disorder 65 
 Mood disorders (major depressive disorder) 63 3.8 
 Respiratory failure; insufficiency; arrest 60 3.7 
 Intermittent explosive disorder 51 3.1 
 Seizures with and without intractable epilepsy 50 3.1 
 Autistic disorder 50 3.1 
 Posttraumatic stress disorder 45 2.7 
 Intracranial injury 38 2.3 
 Septicemia (except in labor) 34 2.1 
 Mood disorders (bipolar disorder) 34 2.1 
 Encephalitis (except that caused by tuberculosis or sexually transmitted disease) 27 1.6 
 Suicide and intentional self-inflicted injury 23 1.4 
Ages 12–15 y (N = 2728) 
 Mood disorders (major depressive disorder) 381 14.5 
 Mood disorders 334 12.7 
 Suicide and intentional self-inflicted injury 292 11.1 
 Mood disorders (bipolar disorder) 106 
 Intracranial injury 87 3.3 
 Attention-deficit hyperactivity disorder 68 2.6 
 Autistic disorder 65 2.5 
 Oppositional defiant disorder 59 2.2 
 Intermittent explosive disorder 54 2.1 
 Posttraumatic stress disorder 53 
 Septicemia (except in labor) 49 1.9 
 Seizures with and without intractable epilepsy 49 1.9 
 Conduct disorder 48 1.8 
 Respiratory failure; insufficiency; arrest 47 1.8 
 Residual codes; unclassified 46 1.7 
Ages 16–18 y (N = 3116) 
 Suicide and intentional self-inflicted injury 375 12.5 
 Schizophrenia and other psychotic disorders 324 10.8 
 Mood disorders (major depressive disorder) 263 8.8 
 Mood disorders (bipolar disorder) 207 6.9 
 Intracranial injury 177 5.9 
 Mood disorders 128 4.3 
 Substance-related disorders 115 3.8 
 Respiratory failure; insufficiency; arrest 79 2.6 
 Septicemia (except in labor) 58 1.9 
 Autistic disorder 58 1.9 
 Crushing injury or internal injury 56 1.9 
 Alcohol-related disorders 54 1.8 
 Poisoning by psychotropic agents 50 1.7 
 Poisoning by other medications and drugs 48 1.6 
 Seizures with and without intractable epilepsy 47 1.6 

Among primary hospital diagnoses, there is significant variability in the fraction of hospitalizations involving co-occurring physical restraint coding. The primary discharge diagnoses categories that most commonly had a concurrent diagnosis of physical restraint status are listed in Table 3. Among the 1148 hospitalizations involving alcohol-related disorders, 87 (7.6%) also involved a code for physical restraint status, which is the highest rate among all diagnostic categories. Other primary diagnoses most frequently involving physical restraint coding include autistic disorder (6.8%), conduct disorder (6.3%), and intermittent explosive disorder (5.1%). In total, 17 diagnostic categories had a co-occurring physical restraint code for more than 3% of hospitalizations, whereas 117 categories had a restraint utilization rate of ≤0.3% and 600 PECCS categories had no hospitalizations with co-occurring physical restraint coding.

TABLE 3

PECCS Categories for the Primary Discharge Diagnoses With the Highest Fraction of Patients With Physical Restraint Coding

PECCS Description# Restrained# Overall% Restrained
Alcohol-related disorders 87 1148 7.6 
Autistic disorder 177 2606 6.8 
Conduct disorder 150 2396 6.3 
Intermittent explosive disorder 148 2930 5.1 
Intracerebral hemorrhage 27 545 5.0 
Residual codes; unclassified 93 1992 4.7 
Schizophrenia and other psychotic disorders 380 8418 4.5 
Oppositional defiant disorder 152 3617 4.2 
Poisoning by psychotropic agents 75 1851 4.1 
Attention-deficit hyperactivity disorder 217 5657 3.8 
Intracranial injury 343 9035 3.8 
Impulse control disorders NEC 44 1334 3.3 
Posttraumatic stress disorder 134 4073 3.3 
Suicide and intentional self-inflicted injury 687 21 011 3.3 
Encephalitis (except that caused by tuberculosis or sexually transmitted disease) 87 2722 3.2 
Mood disorders 790 26 606 3.0 
Hypoplastic left heart syndrome 20 677 3.0 
PECCS Description# Restrained# Overall% Restrained
Alcohol-related disorders 87 1148 7.6 
Autistic disorder 177 2606 6.8 
Conduct disorder 150 2396 6.3 
Intermittent explosive disorder 148 2930 5.1 
Intracerebral hemorrhage 27 545 5.0 
Residual codes; unclassified 93 1992 4.7 
Schizophrenia and other psychotic disorders 380 8418 4.5 
Oppositional defiant disorder 152 3617 4.2 
Poisoning by psychotropic agents 75 1851 4.1 
Attention-deficit hyperactivity disorder 217 5657 3.8 
Intracranial injury 343 9035 3.8 
Impulse control disorders NEC 44 1334 3.3 
Posttraumatic stress disorder 134 4073 3.3 
Suicide and intentional self-inflicted injury 687 21 011 3.3 
Encephalitis (except that caused by tuberculosis or sexually transmitted disease) 87 2722 3.2 
Mood disorders 790 26 606 3.0 
Hypoplastic left heart syndrome 20 677 3.0 

Shown are all categories with a restraint rate ≥3.0%. NEC, not elsewhere classified.

To explore factors associated with the outcome of having a physical restraint discharge code, we performed a logistic regression on the binary outcome of a hospitalization including a code for physical restraint status (yes or no). In this model, increasing age (adjusted odds ratio [aOR] 1.30; 95% confidence interval: 1.22–1.40), male sex (aOR 1.56; 95% CI: 1.47–1.65), Black race (aOR 1.43; 95% CI: 1.33–1.55), a primary mental health or substance diagnosis (aOR 7.13; 95% CI: 6.42–7.90), Medicare or Medicaid insurance (aOR 1.33; 95% CI: 1.24–1.43), and more severe illness (aOR 2.83; 95% CI: 2.73–2.94) were associated with higher odds of a hospitalization involving a physical restraint code. Hispanic ethnicity (aOR 0.87; 95% CI: 0.79–0.97), and Midwest (aOR 0.78; 95% CI: 0.66–0.92) or South (aOR 0.76; 95% CI: 0.63–0.91) regions were associated with lower odds of physical restraint coding, whereas household income of the patient’s ZIP code was not associated with physical restraint coding (Table 4).

TABLE 4

Logistic Regression on the Binary Outcome of a Hospitalization

ParameteraOR95% CI for aOR
LowerUpper
Age (Z score) 1.30 1.22 1.40 
Sex 
 Male 1.56 1.47 1.65 
 Female 1.00 ref ref 
Race 
 Black 1.43 1.33 1.55 
 Hispanic 0.87 0.79 0.97 
 Other 0.95 0.86 1.06 
 White 1.00 ref ref 
Primary mental health or substance abuse diagnosis 
 Yes 7.13 6.42 7.90 
 No 1.00 ref ref 
Hospital region 
 Northeast 1.13 0.94 1.37 
 Midwest 0.78 0.66 0.92 
 South 0.76 0.63 0.91 
 West 1.00 
Household income quartile for pt ZIP code 
 1 0.94 0.85 1.04 
 2 0.96 0.87 1.05 
 3 0.97 0.89 1.06 
 4 1.00 
Primary payor 
 Medicare or Medicaid 1.33 1.24 1.43 
 Other 1.08 0.95 1.23 
 Commercial 1.00 
 APRDRG severity 2.83 2.73 2.94 
ParameteraOR95% CI for aOR
LowerUpper
Age (Z score) 1.30 1.22 1.40 
Sex 
 Male 1.56 1.47 1.65 
 Female 1.00 ref ref 
Race 
 Black 1.43 1.33 1.55 
 Hispanic 0.87 0.79 0.97 
 Other 0.95 0.86 1.06 
 White 1.00 ref ref 
Primary mental health or substance abuse diagnosis 
 Yes 7.13 6.42 7.90 
 No 1.00 ref ref 
Hospital region 
 Northeast 1.13 0.94 1.37 
 Midwest 0.78 0.66 0.92 
 South 0.76 0.63 0.91 
 West 1.00 
Household income quartile for pt ZIP code 
 1 0.94 0.85 1.04 
 2 0.96 0.87 1.05 
 3 0.97 0.89 1.06 
 4 1.00 
Primary payor 
 Medicare or Medicaid 1.33 1.24 1.43 
 Other 1.08 0.95 1.23 
 Commercial 1.00 
 APRDRG severity 2.83 2.73 2.94 

Logistic regression includes a diagnosis code for physical restraint (yes or no), adjusting for age (z score), sex (male, female), race (Black, Hispanic, other, white), primary mental health or substance abuse diagnosis (yes or no), region, income quartile of the patient’s ZIP code, primary payor (Medicare or Medicaid, commercial insurance, other), and patient severity (defined based off of APR-DRG’s Severity of Illness). Shown are the aOR and corresponding CI. APR-DRG, All Patient Refined-Diagnosis Related Groups′.

Among hospitalizations for patients 1 to 18 years old in the United States in 2019, 8893 (95% CI: 8227–9560) involved a discharge code for physical restraint status, representing 0.63% of overall hospitalizations for patients in this age range. Physical restraints were coded for a variety of primary diagnoses, with psychiatric illnesses including mood, psychotic, and conduct disorders among the most common diagnoses overall for hospitalizations involving a physical restraint code (Table 2). There was an age dependence in the frequency of diagnostic categories associated with restraint, with older patients more likely to have a mental health discharge diagnosis and younger patients more likely to have a medical diagnosis.

The frequency of physical restraint coding found in this study can be contextualized by findings in prior studies focusing on specific areas of care delivery. For instance, in the emergency department (ED) setting, a total of 0.1% of encounters for patients aged 0 to 16 in a New England health care system involved physical restraint, with patients of Black race (relative to white race) and males (relative to females) displaying a higher odds of physical restraint utilization.15  A further analysis of data from this system found an intersectional interaction between race and sex, with larger racial disparities in restraint rates in girls relative to boys.16  A specialized pediatric psychiatric ED in the United States reported an average physical restraint prevalence of 1.94% over a 6-year period, with restraints more common among male patients.23  A further Scandinavian survey showed that 79% of emergency departments use temporary physical restraints for painful pediatric procedures.24  In the psychiatric setting specifically, systematic literature review of psychiatric pediatric inpatients suggests a weighted mean physical restraint prevalence across multiple studies of 29.4%.25  Among critically ill children in the PICU. Sixty eight percent of such units in the United Kingdom employ physical restraint of some type.26  Prevalence of physical restraint use in Japanese PICUs has been estimated at 53% of patients, most often in the form of wrist restraint bands.27  The estimate of the prevalence of physical restraint coding among community hospital inpatient pediatric hospitalizations in the KID is similar to the rate of 0.59% found in a 5-year study of inpatient hospitalizations of patients aged 5 to 20 in a single health system comprised of academic children’s hospitals.17  This difference in estimates is likely attributable to a strong association between the need for physical restraints and either acute agitation secondary to psychiatric illness (in the case of a specialized psychiatric units) or to prevent interference with life-sustaining interventions such as mechanical ventilation (in the case of the ICU).

Multiple demographic factors were associated with differential restraint coding in an adjusted model. Older patients were more likely to have a physical restraint diagnostic code, with 0.81% to 0.91% of hospitalizations in teenagers having a restraint code compared with 0.27% to 0.38% among children aged 1 to 6. The rate of physical restraint coding in teenagers was higher than any adult age range based on a recent administrative claims study.28  The primary diagnostic categories associated with age also differed in this study. Psychiatric disorders including mood disorders, suicidality, conduct disorders, and psychotic disorders were most common in adolescents, whereas among patients aged 1 to 5 respiratory failure, seizures, sepsis, and bronchiolitis were the most common diagnostic categories. This may suggest that restraint use in younger children, although less common than in older children, is associated with critical illness, whereas restraint use in older children is associated with psychiatric illness. This idea is supported by ICU-specific physical restraint data, in which restraints were most commonly used in patients aged 1 to 3.27  In the psychiatric ED, restraint use occurred at similar rates in adolescents versus younger children.23  As hospitalizations in this study were in the community hospital setting, practices, such as boarding of psychiatric patients in the community hospital settings while awaiting mental health placement, may contribute to increased psychiatric acuity in units not specifically designed for such care,29,30  which may place patients at increased risk of restraint.

A significant association was also present between race and physical restraint as a discharge diagnosis, with Black patients having higher odds of physical restraint coding compared with white patients and Hispanic patients having a lower odds relative to white patients. This result was significant, even controlling for other demographic factors and disease severity. Similar disparities in restraint utilization have been identified in the adult emergency department setting.31,32  Data drawn from pediatric ED visits replicates this relationship, with increased use of restraints in Black patients relative to white patients, but not Hispanic patients relative to white patients.15  These data suggest that race-related bias may play a role in utilization of restraints in pediatric populations, highlighting the importance of interventions to reduce disparities in high-risk restraint use. Multidisciplinary quality improvement efforts have been successful at reducing the use of restraints within pediatric general hospitals without increase in staff injury,33,34  and incorporation of such efforts, including standardized admission order sets, increased collaboration with multidisciplinary behavioral health teams, and individualized safety planning, hold promise for sustained reduction in restraint utilization among patients with behavioral health diagnoses.35  It remains unclear, however, whether such efforts mitigate racial and gender-based disparities in restraint utilization, and further research into this is required.

This study is based on, and therefore limited by, observational, routinely collected administrative data. This type of data are nationally representative and reflects the reality of healthcare delivery in the United States through 2019. Strengths of this approach include the minimization of bias compared with studies focusing on single centers, geographic regions, or payment sources. However, the generation of data using real world datasets inherently results in limitations on generalizability and interpretability of conclusions.3638  Because the KID data set is based on claims, it reflects codes used for billing rather than the actual events of each hospitalization, and discrepancies may exist between these 2 records. For example, if physical restraint use was not documented in the patient record or included in the final coding for billing postdischarge, the KID database would not accurately reflect that use of restraints. This may be an alternate explanation for the lower prevalence estimate of restraint use in our study compared with prior pediatric psychiatric or ED-focused studies. Most likely, the presence of coding for restraint use in final billing is a specific indicator that restraints were used, but the absence of such coding is not sensitive for lack of restraint use. Further work to validate these results would require examination of this discrepancy. Additionally, restraint duration and frequency are not captured by billing codes. For example, although clinically, the brief use of physical restraint or a physical hold for 1-time venipuncture is markedly different from prolonged mechanical restraint in the setting of agitation, these differences are not captured by billing codes. Further elucidating the differences between ICU, psychiatric, ED, or general inpatient use of restraints in pediatrics will require understanding of these differences, as well as potential differences in restraint practice or coding in different regions. Moreover, each hospitalization represents a distinct entity in the KID record, and therefore a given individual may represent multiple entries for multiple hospitalizations, introducing a source of bias into our estimate, particularly for demographic data. Finally, indicators for race in the KID database are based on hospital-recorded values, and protocols for collecting this vary by hospital and state. Although not specifically studied for the KID, in other administrative databases there were significant differences between self-reported race and administrative documentation,39,40  which confounds analysis of potential disparities in restraint application.

A coded diagnosis of physical restraint status was present for 8893 (95% CI: 8227–9560) hospitalizations in the 2019 KID among individuals aged 1 to 18 years, or 0.63% of overall hospitalizations for patients in this age range. Restraint coding varied by age, sex, race, region, diagnosis, and disease severity. These results highlight potential disparities in restraint utilization and emphasize the importance of a standardized and equitable approach to physical restraint use, particularly in the context of increasing boarding of patients requiring subspecialty mental health care on general pediatrics units. Validation of restraint coding in claims data are, however, a critical further step in extending this research.

Dr Luccarelli conceptualized and designed the study, conducted the initial analyses, and drafted the initial manuscript; Drs A Kalluri and N Kalluri conducted the initial analyses; Dr McCoy conceptualized and designed the study and supervised data analysis; and all authors critically reviewed and revised the manuscript for important intellectual content, approved the final manuscript as submitted, and agree to be accountable for all aspects of the work.

Data Sharing Statement: Publicly available data sets were analyzed in this study. The data set analyzed for this study can be obtained from the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality at: https://hcup-us.ahrq.gov/db/nation/kid/kiddbdocumentation.jsp

FUNDING: This work was supported by funds from Harvard Medical School. The sponsor had no role in study design, writing of the report, or data collection, analysis, or interpretation.

CONFLICT OF INTEREST DISCLOSURES: Dr Luccarelli receives funding from Harvard Medical School Dupont Warren Fellowship and Livingston Awards, the Rappaport Foundation, the Foundation for Prader-Willi Research, and the National Institute of Mental Health (T32MH112485), and he has received equity in Revival Therapeutics, Inc; Dr Kalluri is funded by the Agency for Healthcare Research and Quality (T32HS000063) as part of the Harvard-Wide Pediatric Health Services Research Fellowship Program; Dr McCoy receives funding from the National Institute of Mental Health, National Human Genome Research Institute Home, Telefonica Alfa, and Springer Nature and the remaining authors have no disclosures to report.

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Supplementary data