Abstract
Background:
Women with disabilities are at risk for poor birth outcomes. Little is known about longer-term health and healthcare utilization of infants of women with disabilities.
Objectives:
We identified women at risk for disability and evaluated their infants’ emergency department (ED) utilization during the first year of life.
Study Design:
This population-based cohort study used Massachusetts 2007–2009 birth certificates linked to 2007–2010 hospital discharge data. Access Risk Classification System categorized ICD-9 CM/CPT codes into disability risk categories. Infant ED visits were evaluated overall and by severity (emergent/intermediate vs. non-emergent). Cox proportional hazards models provided adjusted estimates. Results were stratified by gestational age (preterm, < 37 weeks, term, 37+ weeks).
Results:
Of 218,599 women, 6.7% were at risk of disability. Infants born to women at risk had a higher rate of ED visits in their first year than infants born to women not at risk: 0.85 visits/person-year (95% CI 0.84–0.87) vs. 0.55 (0.55–0.55) for term, 0.74 (0.70–0.77) vs. 0.55 (0.54–0.56) for preterm. Utilization varied by maternal diagnosis. Emergent/intermediate and non-emergent visits were both elevated among infants born to women at risk for disability. In adjusted analyses, term infants of women with musculoskeletal diagnoses (HR=1.3, 95% CI 1.2–1.4) and preterm infants of women with circulatory diagnoses (HR=1.2, 1.0–1.3) had the highest hazards of ED visit vs. infants of women not at risk of disability.
Conclusion:
Maternal disability risk is associated with postnatal infant ED utilization; utilization varies by maternal diagnosis. Interventions to improve health of infants born to women with disabilities are warranted.
Keywords: Intellectual and developmental disability, health serices, maternal and child health
With rising pregnancy rates among women with disabilities,1 there is an urgent need to examine not only the health and health care of these women, but also their infants. A growing body of research demonstrates that infants born to women with physical disabilities or chronic illness are at increased risk of being preterm, small for gestational age, and low birthweight.2–4 Infants born to women with intellectual disabilities and psychiatric disabilities are at similar risk.5–8
Evidence regarding longer-term infant health outcomes and health care utilization of infants born to women with disabilities is more sparse. A number of studies have found motor functioning delays in infants born to women with intellectual disabilities (ID)9,10 and psychiatric diagnoses.11,12 While fewer studies have examined health conditions among infants born to mothers with disabilities, associations between maternal ID and pediatric asthma,13 maternal depression and pediatric infections,14 and several maternal chronic illnesses and infant congenital anomalies15,16 have been identified. With respect to healthcare utilization, studies have demonstrated increased emergency department (ED) visits and other forms of acute healthcare utilization among infants born to mothers with depression or depressive symptoms.17,18 ED utilization is also elevated among infants born to mothers with indicators of low SES,19 a factor correlated with maternal disability.4 To date, however, there has not been any comprehensive, systematic investigation of acute healthcare utilization among infants born to women with a spectrum of disabilities.
Understanding patterns of acute healthcare utilization among infants born to women with disabilities is important in assisting healthcare providers to provide optimal care for this population. Examining ED utilization is particularly useful, as ED use is costly and may indicate presence of medically complex conditions, infectious disease, need for postpartum healthcare and social supports, lack of usual source of care, or trauma.20–23
Our study uses population-based linked administrative data from mothers their and infants to examine the health of infants born to women at risk for disability during the first year of their life. The goals are to: 1) compare ED utilization among infants born to women at risk and not at risk for disability; 2) examine infant ED utilization by maternal disability risk category; and 3) examine ED visit reason and severity by maternal disability risk status and underlying health condition category.
Methods
Data Source and Study Population
The Massachusetts Pregnancy to Early Life longitudinal (PELL) data system, January 1, 2007 to December 31, 2010, was used to examine hospital utilization among infants in the 2007–2009 Massachusetts birth cohort. PELL is a population-based data system that links birth certificate and fetal death records to corresponding delivery and non-delivery hospital discharge records for the mother and infant. Details about PELL can be found elsewhere.24 The study population consisted of infants born to women residing in Massachusetts who delivered in the state during 2007–2009. Birth certificate data were linked to corresponding infant hospital utilization during 2007–2010. We included infants whose birth certificate linked to a hospital discharge delivery record, over 99% of births. This protocol was approved by the authors’ institutional review board.
Measures
Disability risk:
Maternal disability risk status was classified using a modified version of the Access Risk Classification System (ARCS) algorithm.25 ARCS uses International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and Current Procedural Terminology (CPT) codes in medical and pharmacy claims to identify individuals who are likely to have one or more limitations in functioning and may need assistance or accommodations to access routine health services. ARCS classifies individuals based on presumed risk of functional limitation: Level A) no risk, medical needs are emergent or acute; Level B) low risk, one or a few chronic conditions that might cause some functional limitations; Level C) medium risk, one or more chronic conditions that can cause major functional limitations; and Level D) high risk, multiple chronic conditions and complex medical needs that likely severely impair a person’s functional abilities. Two modifications to the algorithm were applied. Pharmacy claims were not available, thus not used to calculate the ARCS score. Non-malignant neoplasm (ICD-9-CM codes 210 – 239) diagnoses were excluded from the algorithm because we presumed these diagnoses alone would be unlikely to cause functional limitations in this population. Women were classified at each delivery based on diagnoses on any claim one year prior to and including delivery. ARCS scores were then categorized as: 1) no/low risk for disability (Levels A and B); and 2) medium/high risk for disability (Levels C and D). This dichotomization demonstrated 88% sensitivity and 30% specificity compared with self-reported disability in a validation study conducted among members ages 18 years of age and older.25
Individuals at medium/high risk for disability were further categorized by the health condition underlying the disability risk, using the 18 condition categories of the Clinical Classification Software (CCS) (Agency for Healthcare Research & Quality, Rockville, MD). The CCS diagnostic classification system is widely used in health services and medical research.26 The four categories with the highest frequencies in the study population were identified: diseases of the circulatory system, which included diagnoses such as hypertension, dysrhythmias, endocarditis, and cardiomyopathy; diseases of the musculoskeletal system and connective tissues, including diagnoses such as lupus, rheumatoid arthritis, and musculoskeletal deformities; diseases of the nervous system/sense organs, which includes epilepsy, retinal disorders, and pain diagnoses; and mental illness, including diagnoses of serious mental illness, other mental illness, and intellectual and developmental disability. The most common diagnoses in each category are provided in the Appendix. Other categories, including diagnoses of the digestive system, genitourinary system, and endocrine system, were grouped in an “other physical diagnosis” category. Individuals were then categorized into seven groups: 1) diseases of the circulatory system only; 2) diseases of the musculoskeletal system and connective tissue only; 3) diseases of the nervous system/sense organs only; 4) other physical diagnoses only; 5) two or more physical diagnoses; 6) mental illness only; and 7) co-occurring mental illness and physical diagnoses.
ED utilization:
ED utilization during the infant’s first year of life was identified in PELL.
Reasons for visit were defined as the CCS category of the primary diagnosis listed for that visit. The New York University (NYU) ED algorithm was used to estimate ED visit severity. Using previously developed methodology, we categorized visits into: 1) emergent/intermediate, which included visits with a greater than or equal to 50% probability that ED care was needed but preventable or avoidable if appropriate ambulatory care had been received, or ED visit was needed and not preventable or avoidable; and 2) non-emergent, visits with < 50% chance that ED care was needed.27
Maternal and infant characteristics:
Maternal demographic characteristics at the time of delivery were derived from the birth certificate and include maternal age, education, race/ethnicity, and health insurance status at delivery. Infant characteristics were derived from the birth certificate and include preterm birth (< 37 weeks gestation), small for gestational age (SGA) (< 10th percentile), plurality, and any congenital abnormality listed on the birth certificate.
Analysis
Demographic characteristics and pregnancy risk factors are presented by disability risk status, and, among women at risk for disability, by underlying disability risk category. Because acute care hospitalization in the first year of life differs by gestational age28, 29 and risk of preterm birth differs by disability risk status and disability risk category,30 results are also presented separately for preterm and term infants. The rate of ED utilization, that is, the number of ED visits per person-year during the year following birth, is presented. Pearson chi-square tested bivariate comparisons of demographic and clinical, characteristics by disability risk status, and Z scores compared rates of ED utilization by disability risk status.
Due to the number of disability risk categories, the large number of between-group comparisons, and the lack of pre-specified hypotheses of differences by disability risk categories, we did not perform tests to identify statistically significant differences in ED utilization between the maternal disability risk categories. Discussion of between-category differences are therefore based on nominal differences and should be considered descriptive in nature.
Cox proportional hazards models with robust standard errors evaluated unadjusted and adjusted hazard ratios and 95% confidence intervals (95% CI) for time to first ED visit during the year following birth for each maternal disability risk category compared with infants born to mothers not at risk for disability. The first adjusted model controlled for maternal demographic characteristics and the second model further adjusted for infant clinical characteristics.
Results:
During 2007 – 2009, 223,658 infants born to 218,599 Massachusetts mothers were identified in the PELL dataset. Of the mothers, 79.2% were categorized in ARCS Level A, 14.2% in Level B, 3.6% in Level C, and 3.0% in Level D. A total of 6.7% of women were classified at risk for disability and 93.3% classified not at risk for disability. Of the 14,542 at risk for disability, the largest diagnostic groups were those classified as having a mental illness (24.2%) a disease of the circulatory system (23.1%), and other physical diagnoses (19.0%). Table 1 presents maternal and infant characteristics by disability risk status and disability risk category. Overall, women at risk for disability were more likely to be under 19 years of age, have lower levels of education, and be white, non-Hispanic or black, non-Hispanic than women not at risk for disability. Women with mental illness and co-occurring mental and physical conditions had the highest percentages of women below 19 years of age and with low levels of education. Women with diseases of the circulatory system, musculoskeletal system, and other physical diagnoses, on the other hand, had demographic profiles most similar to women not at risk for disability. Infants born to women at risk for disability had almost twice the risk of being preterm, were more likely to be a twin or higher order multiple, were more likely to have a congenital abnormality listed on their birth certificate, had a higher risk of being SGA, and had longer hospital stays after delivery compared with infants born to mothers not at risk. Risk of preterm birth was highest among infants born to mothers with two or more physical diagnoses, and risk of SGA and hospital length of stay was highest among infants born to women with co-occurring mental and physical diagnoses.
Table 1:
Maternal and infant characteristics of infants born in Massachusetts, 2007–2009
| Not at risk for Disability | At risk for Disability | P | Circulatory | Musculoskeletal | NS/sense organ | Other physical | 2+ physical | Mental Illness | Mental + physical | Chi-square p | |
|---|---|---|---|---|---|---|---|---|---|---|---|
|
| |||||||||||
| Mothers | N=204,057 | N =14542 | N = 3,359 | N=1,401 | N=1,955 | N=2,768 | N=728 | N=3,524 | N=807 | ||
| N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | |||
| Age (years) | < 0.001 | < 0.001 | |||||||||
|
| |||||||||||
| < 19 | 7604 (3.7) | 611 (4.2) | 66 (2.0) | 44 (3.1) | 67 (3.4) | 63 (2.3) | 18 (2.5) | 321 (9.1) | 32 (4.0) | ||
| 19–34 | 150853 (73.9) | 10744 (73.9) | 2231 (66.4) | 982(70.1) | 1552 (79.4) | 2026 (73.2) | 508 (69.8) | 2795 (79.3) | 650 (80.6) | ||
| 35+ | 45580 (22.3) | 3187 (21.9) | 1062 (31.6) | 375 (26.8) | 336 (17.2) | 679 (24.3) | 202 (27.8) | 408 (11.6) | 125 (15.5) | ||
| Education | < 0.001 | < 0.001 | |||||||||
| Less than HS | 22151 (10.9) | 2233 (15.4) | 325 (9.7) | 152 (10.9) | 289 (14.8) | 262 (9.5) | 80 (11.0) | 915 (26.1) | 210 (26.2) | ||
| HS | 51324 (25.2) | 4837 (33.3) | 972 (29.0) | 378 (27.0) | 662 (34.0) | 745 (26.9) | 255 (35.2) | 1490 (42.4) | 335 (41.7) | ||
| Some college + | 130309 (63.9) | 7437 (51.3) | 2056 (61.3) | 871 (62.2) | 996 (51.2) | 1758 (63.6) | 390 (53.8) | 1108 (31.5) | 258 (32.1) | ||
| Public insurance at delivery | 71389 (35.1) | 7395 (51.1) | 1251 (37.4) | 549 (39.2) | 970 (50.3) | 1003 (36.3) | 352 (48.5) | 2623 (75.1) | 647 (80.4) | ||
| Race/Ethnicity | < 0.001 | < 0.001 | |||||||||
| NH White | 138663 (68.0) | 10238 (70.4) | 2283 (68.0) | 1018 (72.7) | 1421 (72.7) | 1938 (70.0) | 507 (69.6) | 2483(70.5) | 558 (72.9) | ||
| NH Black | 18117 (8.9) | 1650 (11.4) | 465 (13.8) | 131 (9.4) | 181 (9.3) | 335 (12.1) | 88 (12.1) | 371 (10.5) | 79 (9.8) | < 0.001 | |
| Hispanic | 29901 (14.7) | 2163 (14.9) | 472 (14.1) | 202 (14.4) | 287 (14.7) | 376 (13.6) | 114 (15.7) | 589 (16.7) | 123 (15.2) | ||
| Other | 17378 (8.5) | 491 (3.4) | 139 (4.2) | 50 (3.6) | 66 (3.4) | 119(4.3) | 19 (2.6) | 81 (2.3) | 17 (2.1) | ||
| Primaparous | 94,236 (45.2) | 6,734 (44.9) | 0.48 | 1,449 (41.3) | 631 (43.9) | 913 (45.9) | 1,320 (45.4) | 341 (45.0) | 1,724 (48.1) | 356 (43.1) | < 0.0001 |
| 1+ Ed visit in 1st year postpartum | 31,675 (15.2) | 4,329 (28.8) | < 0.001 | 744 (21.2) | 396 (27.6) | 606 (30.5) | 652 (22.4) | 256 (33.8) | 1296 (36.2) | 379 (45.9) | <0.0001 |
|
| |||||||||||
| Infants | N =208,650 | N = 15,008 | N = 3,510 | N=1,436 | N = 1,990 | N = 2907 | N = 758 | N = 3581 | N = 826 | ||
| N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | N (%) | |||
|
| |||||||||||
| PTB (<37 wks) | 18143 (8.7) | 2540 (16.9) | <0.001 | 751 (21.4) | 176 (12.3) | 240 (12.1) | 528 (18.2) | 183 (24.1) | 494 (13.8) | 168 (20.3) | <0.0001 |
| SGA | 22453 (10.8) | 2264(15.1) | 549 (15.6) | 193 (13.4) | 259 (13.0) | 409 (14.1) | 126 (16.6) | 581 (16.2) | 147 (17.8) | <0.0001 | |
| Twin or higher multiple | 9,153 (4.4) | 926 (6.2) | <0.001 | 302 (8.6) | 73 (5.1) | 69 (3.5) | 271 (9.3) | 61 (8.0) | 115 (3.2) | 35 (4.2) | <0.001) |
| Congenital abnormality | 32,959 (15.8) | 3,431 (22.9) | <0.001 | 824 (23.5) | 282 (19.6) | 388 (19.5) | 638 (21.9) | 207 (27.3) | 839 (23.4) | 253 (30.6) | < 0.001 |
| LOS after birth (mean, SD) | 3.68 (7.10) | 5.84 (11.2) | <0.001 | 6.10 (11.7) | 4.2 (7.3) | 4.5 (9.2) | 5.7 (11.2) | 6.8 (12.8) | 6.2 (11.8) | 8.7 (13.9) | 0.43 |
HS: High school; NH: Non-Hispanic; ED: Emergency Department; PTB: Preterm birth; SGA: Small for gestational age; LOS length of stay Other
Table 2 presents infant ED utilization by maternal disability risk status and disability risk category. Infants born to mothers at risk of disability had a higher rate of ED visits in the year following birth than infants born to women not at risk of disability, 0.83 vs. 0.55 visits per person-year, respectively (p<0.0001). Among infants of mothers at risk for disability, the rate of ED visit was highest among infants of mothers with co-occurring mental and physical diagnoses (1.08 visits per person-year) followed by mental illness diagnoses (1.00 visits per person-year).
Table 2.
Emergency department utilization among infants 1 year post-delivery, by disability risk status and type of disability risk category, Massachusetts term and preterm infants born 2007–2009
| Not at risk for Disability n=208,650 Visits/person-year (95% CI) | At risk for Disability N = 15,008 Visits/person-year (95% CI) | P value, z score | Circulatory N = 3,510 Visits/person-year (95% CI) | Musculoskeletal N=1,436 Visits/person-year (95% CI) | NS/sense organ N=1,990 Visits/person-year (95% CI) | Other physical N=2,907 Visits/person-year (95% CI) | 2+ physical N=758 Visits/person-year (95% CI) | Mental Illness N=3,581 Visits/person-year (95% CI) | Mental + physical N=826 (6%) Visits/person-year (95% CI) | |
|---|---|---|---|---|---|---|---|---|---|---|
| Overall | ||||||||||
| Rate (95% CI) | 0.55 (0.55–0.55) | 0.83 (0.82–0.85) | <0.001 | 0.69 (0.66–0.72) | 0.84 (0.79–0.88) | 0.94 (0.89–0.98) | 0.67 (0.64–0.70) | 0.76 (0.70–0.83) | 1.00 (0.97–1.03) | 1.08 (1.01–1.15) |
| Term (>=37 weeks) | 190,507 (91.3) | 12,468 (83.1) | 2759 (78.6) | 1260 (87.7) | 1750 (87.9) | 2379 (81.8) | 575 (75.9) | 3087 (86.7) | 658 (79.7) | |
| Rate (95% CI) | 0.55 (0.55–0.55) | 0.85 (0.84–0.87) | <0.001 | 0.70 (0.67–0.73) | 0.86 (0.81–0.92) | 0.94 (0.89–0.98) | 0.70 (0.67–0.74) | 0.82 (0.75–0.90) | 0.99 (0.95–1.02) | 1.12 (1.08–1.24) |
| Preterm (<37 weeks) | 18,143 (8.7) | 2,540 (16.9) | 751 (21.4) | 176 (12.3) | 240 (12.1) | 528 (18.2) | 183 (24.1) | 494 (13.8) | 168 (20.3) | |
| Rate (95% CI) | 0.55 (0.54–0.56) | 0.74 (0.70–0.77) | <0.001 | 0.64 (0.58–0.69) | 0.63 (0.51–0.75) | 0.93 (0.81–1.06) | 0.52 (0.46–0.58) | 0.58 (0.47–0.69) | 1.10 (1.01–1.20) | 0.77 (0.64–0.91) |
CI: Confidence Interval
Table 2 also presents infant ED utilization separately for term and preterm infants. In both groups infants born to mothers at risk of disability had a higher rate of utilization compared with infants born to women not at risk, although overall ED utilization was lower among preterm infants born to women at risk of disability relative to term infants born to women at risk. Patterns of ED utilization by disability risk category differed somewhat between term and preterm infants, with term infants born to mothers with co-occurring mental and physical illness, and preterm infants born to mothers with mental illness having the highest ED utilization.
Among both preterm and term infants the most frequent reason for visits were for diseases of the respiratory system, followed by symptoms, signs and ill-defined conditions and injury. There was no discernable difference in the reason for the ED visit by disability risk status or disability risk category among either term or preterm infants (data not shown).
Among both term and preterm infants, emergent/intermediate visits and non-emergent visits were both higher among infants born to women at risk of disability compared with infants born to women not at risk. Preterm infants born to mothers at risk of disability had 0.10 emergent/intermediate ED visits per person-year and 0.39 non-emergent visits per person-year vs. 0.07 and 0.29 visits per person-year, respectively, among those born to mothers not at risk. Among term infants, infants born to mothers at risk of disability had 0.09 emergent and 0.48 non-emergent visits per person-year, vs. 0.06 emergent and 0.30 non-emergent visits among those born to mothers not at risk (p < 0.05 for all comparisons). Figures 1a. and 1b. present severity of ED visits for full and preterm infants, respectively, by maternal disability risk category. Among both term and preterm infants, the rate of emergent/intermediate visits was highest for those born to mothers with mental illness or co-occurring mental illness and physical diagnoses. Non-emergent visits were highest for term infants born to mothers with mental and physical co-occurring disorders and infants born to women with nervous system sensory system disorders. Among preterm infants, ED utilization was highest among those born to mothers with mental illness and nervous system/sense organ diagnoses.
Figure 1.
a. Rate and 95% Confidence intervals of ED visits in the first year, by severity, term infants, Massachusetts Births 2007–2009
b. Rate and 95% confidence intervals of ED visits in the first year, by severity, preterm infants, Massachusetts Births 2007–2009
Table 3 presents results for crude and adjusted models depicting the association between maternal disability risk categories and having one or more infant ED visit in the first year. Among term infants, in crude analyses those born to mothers in each of the disability risk categories had a higher hazard of having one or more ED visit compared with infants born to mothers not at risk. The highest hazard ratios were among women with co-occurring mental and physical diagnoses, followed by mental illness diagnoses. Adjusting for demographic variables attenuated the associations between some disability risk categories and having an ED visit. In fully adjusted analyses, infants born to women with musculoskeletal disorders had the highest hazard of having an ED visit, nearly thirty percent higher than infants of women not at risk for disability (HR = 1.29, 95% CI 1.18–1.41), followed by women with nervous system/sense organ diagnoses (HR = 1.20, 95% CI 1.11–1.13). Women with circulatory system diagnoses, mental and physical comorbidity, and other physical conditions also had a statistically significant higher hazard of having a ED visit compared to women not at risk of disability.
Table 3.
Crude and adjusted association between maternal disability risk category and infant emergency department utilization, Massachusetts term and preterm infants born 2007–2009
| Term N = 202,975 | Preterm N = 20,683 | |||||
|---|---|---|---|---|---|---|
|
| ||||||
| Unadjusted HR | Adjusted, demographics*HR | Adjusted, demographics and clinical**, HR | Unadjusted HR | Adjusted, demographics HR | Adjusted, demographics and clinical, HR | |
|
| ||||||
| Circulatory | 1.24 (1.16–1.32) | 1.23 (1.16–1.32) | 1.18 (1.10–1.25) | 1.12 (0.98–1.29) | 1.18 (1.03–1.36) | 1.15 (1.00–1.33) |
| Musculoskeletal | 1.40 (1.28–1.53) | 1.38 (1.27–1.51) | 1.29 (1.18–1.41) | 1.10 (0.83–1.44) | 1.19 (0.90–1.58) | 1.11 (0.84–1.48) |
| NS/sense organ | 1.49 (1.38–1.60) | 1.29 (1.20–1.39) | 1.20 (1.11–1.30) | 1.45 (1.17–1.80) | 1.34 (1.08–1.66) | 1.21 (0.97–1.49) |
| Other physical | 1.24 (1.16–1.33) | 1.21 (1.13–1.30) | 1.14 (1.07–1.23) | 0.89 (0.74–1.06) | 0.98 (0.82–1.18) | 1.04 (0.87–1.24) |
| 2+ physical | 1.38 (1.21–1.57) | 1.26 (1.11–1.44) | 1.13 (0.99–1.29) | 1.07 (0.81–1.41) | 0.93 (0.71–1.23) | 0.87 (0.66–1.15) |
| Mental Illness | 1.61 (1.52–1.70) | 1.08 (1.02–1.15) | 1.00 (0.94–1.05) | 1.73 (1.50–2.00) | 1.19 (1.02–1.39) | 1.10 (0.94–1.28) |
| Mental + physical | 1.95 (1.74–2.17) | 1.35 (1.21–1.52) | 1.17 (1.04–1.32) | 1.32 (1.01–1.72) | 0.96 (0.73–1.27) | 0.91 (0.70–1.19) |
| Not at risk | Reference | Reference | Reference | Reference | Reference | Reference |
HR: Hazard Ratio
Adjusted for maternal age, race/ethnicity, education, insurance at delivery
Adjusted for maternal age, race/ethnicity, education, insurance at delivery, parity, plurality, congenital abnormality, presence of pregnancy risk factor, gestational age at birth, birthweight
Among preterm infants, those born to women with mental illness diagnosis had the highest unadjusted hazard of having one or more ED visit, followed by women with nervous system/sense organ diagnoses. There was also a statistically significant association between mental and physical comorbidity and having one or more ED visit. Adjusting for demographic variables, only preterm infants born to women with circulatory diagnoses, nervous system/sense organ diagnoses, and mental illness diagnosis were more likely to have one or more ED visit than preterm infants born to women not at risk of disability. Further adjusting for clinical factors resulted in only infants born to mothers with circulatory system diagnoses (HR = 1.00, 95% CI 1.00–1.33) having an elevated hazard of having one or more ED visit relative to women not at risk of disability.
Discussion
Our analysis demonstrated that in a population-based single state study, infants born to women at risk for disability had an elevated hazard of having an ED visit in the year following birth. Moreover, we found ED utilization varied by category of underlying maternal health condition, with infants born to mothers who had a diagnosis of mental illness and co-occurring mental and physical illness diagnoses among highest ED utilizers. As depressive diagnoses comprise the largest proportion of the mental illness category, these findings are consistent with others who have found health care service use to be high among infants of mothers with depressive symptoms or depression diagnoses alone or in combination with back pain 17,18, 31
Although infants born to women with mental illness and mental and physical diagnoses had the highest ED utilization, adjusting for demographic characteristics substantially attenuated the association between disability risk category and ED utilization in these groups. Some excess risk may therefore be attributable to the fact that women with mental illness and mental and physical comorbidity were the most likely to have indicators of lower SES indicators. Indicators of low SES have an established association with higher ED utilization among young children,19 a reflection of such factors as lower likelihood of having a source of usual care and higher prevalence of health conditions such as lower respiratory illness.32 We were not able to assess a usual source of care in this study. Further research is needed to understand the factors associated with higher ED utilization in this group of infants.
Demographic disparities, however, do not explain all the excess risk of infant ED utilization. In fully adjusted models, term infants born to mothers with musculoskeletal diagnoses had the highest hazard of ED visit, nearly 30% higher than infants born to mothers not at risk of disability. The most common diagnosis for women in this category was “other disorders of the bone” followed closely by invertebral disc disorders. Nervous system/sense organ diagnoses were also associated with elevated infant ED utilization. Nervous system/sense organs included pain not otherwise classified, epilepsy, multiple sclerosis and other retinal disorders. These diagnoses raise a question about whether a maternal diagnosis of pain could be a factor in the increased likelihood of an ED visit. A maternal diagnosis of pain from various conditions has been found to be associated with an increased risk of mothers bringing a child in for at least one ED visit in a given year.31 One possible explanation for this association has been that pain may make it uniquely challenging for mothers to manage their children’s medical needs at home in addition to their own,31 or that a mother’s own experience with health issues makes her more responsive to her child’s distress. Additionally, it is worth noting that high maternal use of the ED has been found to be associated with high-volume ED use among children.18,33
Circulatory system disorders were a significant predictor for ED visits among both term and preterm infants. The most common diagnosis of the circulatory system disorders was essential hypertension. There is evidence that ED visits for hypertension have been on the rise and that these patients may be utilizing the ED as a source of primary care,34 raising the question of whether this is yet another population in which mothers’ ED utilization both for themselves and for their children is high. This finding suggests a need for further investigation.
We found a difference in ED utilization among preterm and term infants. Overall, preterm infants were less likely to use the ED than term infants, particularly for nonemergent visits. Moreover, we found fewer maternal disability risk categories associated with infant ED utilization among preterm infants. Preterm infants have longer hospital stays after birth, thus allowing less opportunity for ED visits in the year after birth. Preterm infants may be more connected to the healthcare system, thus less likely to use the ED for non-emergent care. The higher prevalence of health conditions among preterm infants born to mothers both at risk and not at risk of disability may be a primary driver of ED utilization among these infants, rather than maternal disability status.
The pattern of ED visits among infants born to women at risk for disability mirrors previous research documenting an increased risk of postpartum ED visits among women in some disability groups35 and indicates the need for more comprehensive postpartum care and coordination of postpartum supports and care and pediatric care. These findings provide further evidence of the need for family-centered pediatric care, sometimes described as “family pediatrics.” As noted in the American Academy of Pediatrics (AAP) 2003 Report of the Task Force on the Family, “The health and well-being of children are inextricably linked to their parents’ physical, emotional and social health, social circumstances, and child-rearing practices.”.36 Additionally, clinicians “need to understand better caregivers’ use of health care services and discuss health care seeking behavior in a family context”.33,37 Family-centered care may be of particular importance when caring for children in families with a mother at risk of disability who may be likely to experience significant health and environmental challenges and therefore would particularly benefit from the more comprehensive, coordinated postpartum care that a family-centered approach could provide.
Our study is subject to several limitations. Identifying individuals with disability from administrative data is difficult because ICD code-based algorithms do not directly measure functional limitation, the defining feature of disability.38 The algorithm we used demonstrated adequate sensitivity compared with self-reported disability in a population of men and women ages 18 years and older. The specificity, however, was low, indicating that many of the individuals identified by the algorithm as being at risk for disability did not have a self-reported disability, likely because some diagnoses included in the disability risk algorithm covered a range of severities and accompanying functional limitations. Such misclassification would result in an underestimate of the association between maternal disability risk category and infant health care utilization. Moreover, the algorithm has not been validated among women of childbearing age, and the instrument may therefore have different sensitivity and specificity in this population. Some diagnoses may be particularly problematic in this age group. Hypertension, the most frequent diagnosis in the circulatory system category, may not limit function in this population.39 Moreover, pre-eclampsia may have been misclassified as essential hypertension in some cases. Nevertheless, the diagnosis could have important physiologic complications. Additionally, we were unable to capture any existing diagnoses, perhaps longstanding, that were not recorded at hospital delivery.
Diagnoses included in each disability risk group are heterogeneous. For example, diagnoses among women in the CCS mental illness category include a wide array of psychiatric diagnoses as well as intellectual disability diagnoses. Women with different diagnoses within the same category may have distinct demographic and clinical profiles and patterns of healthcare utilization and these diverse diagnoses and demographics might affect infant healthcare utilization in widely disparate ways. Future research should aim to elucidate the patterns of healthcare utilization among women with disabilities with specific diagnoses. Although we included specific health-related infant characteristics such as preterm birth, SGA, plurality, congenital abnormalities, and length of stay after birth, we did not include additional information about infant health or disability status in our analysis. These factors could certainly influence infant health care utilization as chronic conditions in children have been associated with higher ED use.40 The evaluation of health conditions of infants born to mothers with disabilities is an area for future research.
Results are also subject to limitations of administrative data. Disability risk categories are identified using ICD-9-CM and CPT codes from hospital discharge records and thus not directly validated against medical records or self-reported data. While these data represent the entire population of women who delivered in Massachusetts during 2007–2009, the findings may not generalize to other time periods or to other states.
Despite limitations, our study has significant strengths. The sample was population based and not subject to selection biases that affect studies using convenience samples. Massachusetts birth certificates have extensive information to supplement the hospital discharge files, providing a rich, longitudinal data set with demographic and clinical information with which to examine antenatal healthcare utilization.
Conclusion
Our findings indicate that infants born to women at risk for disabilities, particularly to women with a diagnosis of mental illness and co-occurring mental and physical illness, are at a heightened risk for ED visits in the year following birth. This paper advances earlier studies by examining the health and health care utilization of infants born to mothers at risk for disability and underscores the need to improve and coordinate the systems of care for the mother and child during the postpartum period. The findings also emphasize the need for effective and evidence-based clinical and policy interventions to improve the health and wellbeing of infants born to women at risk for disability.
Supplementary Material
Acknowledgments
This work was funded by National Institutes of Health (NIH) grant number 1R01HD074581. NIH did not have any role in the study design, analysis, or interpretation of the data. None of the authors have any conflicts of interest to declare.
Footnotes
Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
References
- 1.Horner-Johnson W, Biel FM, Darney BG, Caughey AB. Time trends in births and cesarean deliveries among women with disabilities. Disabil Health J 2017;10(3):376–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Morton C, Le JT, Shahbandar L, Hammond C, Murphy EA, Kirschner KL. Pregnancy Outcomes of Women With Physical Disabilities: A Matched Cohort Study. PM R 2013;5(2):90–8. [DOI] [PubMed] [Google Scholar]
- 3.Kersten I, Lange AE, Haas JP, Fusch C, Lode H, Hoffmann W, et al. Chronic diseases in pregnant women: prevalence and birth outcomes based on the SNiP-study. BMC Pregnancy Childbirth [Internet]. 2014;14(1):75. Available from: 10.1186/1471-2393-14-75 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mitra M, Clements KM, Zhang J, Iezzoni LI, Smeltzer SC, Long-Bellil LM. Maternal characteristics, pregnancy complications, and adverse birth outcomes among women with disabilities. Med Care 2015;53(12):1027–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Brown HK, Cobigo V, Lunsky Y, Vigod SN. Maternal and offspring outcomes in women with intellectual and developmental disabilities: a population-based cohort study. BJOG 2017;124(5):757–65. [DOI] [PubMed] [Google Scholar]
- 6.Mitra M, Parish SL, Clements KM, Cui X, Diop H. Pregnancy outcomes among women with intellectual and developmental disabilities. Am J Prev Med 2015;48(3):300–8. [DOI] [PubMed] [Google Scholar]
- 7.Grigoriadis S, VonderPorten EH, Mamisashvili L, Tomlinson G, Dennis CL, Koren G, et al. The impact of maternal depression during pregnancy on perinatal outcomes: A systematic review and meta-analysis. J Clin Psychiatry 2013;74(4): e321–41. [DOI] [PubMed] [Google Scholar]
- 8.Nilsson E, Hultman CM, Cnattingius S, Olausson PO, Bjork C, Lichtenstein P. Schizophrenia and offspring’s risk for adverse pregnancy outcomes and infant death. Br J Psychiatry 2008;193(4):311–5. [DOI] [PubMed] [Google Scholar]
- 9.Hindmarsh G, Llewellyn G, Emerson E. Mothers with intellectual impairment and their 9-month-old infants. J Intellect Disabil Res 2015;59(6):541–50. [DOI] [PubMed] [Google Scholar]
- 10.Bowling M, Keltner BR. Primary health care for children of mothers with intellectual limitations. Pediatr Nurs 1996;22(4):312–5, 319. [PubMed] [Google Scholar]
- 11.Davalos DB, Yadon CA, Tregellas HC. Untreated prenatal maternal depression and the potential risks to offspring: A review. Arch Womens Ment Health 2012;15(1):1–14. [DOI] [PubMed] [Google Scholar]
- 12.Sameroff A, Seifer R, Zax M, Barocas R. Early indicators of developmental risk: Rochester Longitudinal Study. Schizophr Bull 1987;13(3):383–94. [DOI] [PubMed] [Google Scholar]
- 13.Powell RM, Parish SL, Akobirshoev I. Health of Young Children Whose Mothers Have Intellectual Disability. Am J Intellect Dev Disabil 2016. Jul;121(4):281–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ban L, Gibson JE, West J, Tata LJ. Association between perinatal depression in mothers and the risk of childhood infections in offspring: A population-based cohort study. BMC Public Health 2010;10:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Liu S, Joseph KS, Lisonkova S, Rouleau J, Van den Hof M, Sauve R, et al. Association between maternal chronic conditions and congenital heart defects: a population-based cohort study. Circulation 2013. Aug;128(6):583–9. [DOI] [PubMed] [Google Scholar]
- 16.Chou HH, Chiou MJ, Liang FW, Chen LH, Lu TH, Li CY. Association of maternal chronic disease with risk of congenital heart disease in offspring. CMAJ 2016;188(17–18):E438–46. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Minkovitz CS, Strobino D, Scharfstein D, Hou W, Miller T, Mistry KB, et al. Maternal depressive symptoms and children’s receipt of health care in the first 3 years of life. Pediatrics 2005;115(2):306–14. [DOI] [PubMed] [Google Scholar]
- 18.Flynn HA, Davis M, Marcus SM, Cunningham R, Blow FC. Rates of maternal depression in pediatric emergency department and relationship to child service utilization. Gen Hosp Psychiatry 2004;26(4):316–22. [DOI] [PubMed] [Google Scholar]
- 19.National Center for Health Statistics. Health, United States, 2016: With Chartbook on Long-term Trends in Health. Hyattsville, MD. 2017. [PubMed] [Google Scholar]
- 20.Kuo DZ, Hall M, Agrawal R, Cohen E, Feudtner C, Goodman DM, et al. Comparison of Health Care Spending and Utilization Among Children With Medicaid Insurance. Pediatrics 2015;136(6):e1521–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Hasegawa K, Tsugawa Y, Cohen A, Camargo CAJ. Infectious Disease-related Emergency Department Visits Among Children in the US. Pediatr Infect Dis J 2015;34(7):681–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Rasooly IR, Mullins PM, Alpern ER, Pines JM. US emergency department use by children, 2001–2010. Pediatr Emerg Care 2014;30(9):602–7. [DOI] [PubMed] [Google Scholar]
- 23.Wier LM,Hao Y,Owens P, Washington R. Overview of Children in the Emergency Department, 2010. HCUP Statistical Brief #157. June 2013. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb157.pdf. [PubMed] [Google Scholar]
- 24.Clements KM, Barfield WD, Kotelchuck M, Lee KG, Wilber N. Birth characteristics associated with early intervention referral, evaluation for eligibility, and program eligibility in the first year of life. Matern Child Health J 2006; 10(5):433–41. [DOI] [PubMed] [Google Scholar]
- 25.Palsbo SE, Sutton CD, Mastal MF, Johnson S, Cohen A. Identifying and classifying people with disabilities using claims data: Further development of the Access Risk Classification System (ARCS) algorithm. Disabil Health J 2008;1(4):215–23. [DOI] [PubMed] [Google Scholar]
- 26.Healthcare cost and Utilization Project. Clinical Classifications Software (CCS) for ICD-9-CM. https://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Updated 3/6/17. Accessed 3/14/19.
- 27.Gandhi SO, Sabik L. Emergency department visit classification using the NYU algorithm.Am J Manag Care 2014;20(4):315–20. [PubMed] [Google Scholar]
- 28.Kuzniewicz MW, Parker S, Schnake-mahl A, Escobar GJ. Hospital readmissions and emergency departent visits in moderate preterm, late preterm, and early term infants. Clin Perinatol 2013;40:753–75. [DOI] [PubMed] [Google Scholar]
- 29.Cuevas KD, Silver DR, Brooten D, Youngblut JM, Bobo CM. The cost of prematurity: hospital charges at birth and frequency of rehospitalizations and acute care visits over the first year of life: a comparison by gestational age and birth weight. Am J Nurs 2005;105(7):56–64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Clements KM, Mitra M, Zhang J, Iezzoni LI. Pregnancy Characteristics and Outcomes among Women at Risk for Disability from Health Conditions Identified in Medical Claims. Womens’ Health Issues 2016;26(5):504–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Logan JE, Riley AW, Barker LE. Parental mental and pain-related health and pediatric ambulatory care sensitive emergency department visits and hospitalizations. Health Serv Res 2008;43(2):656–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Lothrop N, Hussaini K, Billheimer D, Beamer P. Community-level characteristics and environmental factors of child respiratory illnesses in Southern Arizona. BMC Public Health 2017;17(1):516. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Zimmer KP, Walker AR, Minkovitz CS. Maternal and child factors affecting high-volume pediatric emergency department use. Pediatr Emerg Care. 2006;22(5):301–8. [DOI] [PubMed] [Google Scholar]
- 34.McNaughton CD, Self WH, Zhu Y, Janke AT, Storrow AB, Levy P. Incidence of hypertension-related emergency department visits in the United States, 2006 to 2012. The American Journal of Cardiology 2015;116(11):1717–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Mitra M, Parish SL, Akobirshoev I, Rosenthal E, Moore Simas TA. Postpartum Hospital Utilization among Massachusetts Women with Intellectual and Developmental Disabilities: A Retrospective Cohort Study. Matern Child Health J 2018;22(10):1492–1501. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.American Academy of Pediatrics, Task Force on the Family. Family pediatrics: report of the Task Force on the Family. Pediatrics 2003;111:1541–1571. [PubMed] [Google Scholar]
- 37.Earls MF. Committee on Psychosocial Aspects of Child and Family Health American Academy of Pediatrics. Incorporating recognition and management of perinatal and postpartum depression into pediatric practice. Pediatrics 2010;126(5):1032–9. [DOI] [PubMed] [Google Scholar]
- 38.Iezzoni LI. Using administrative data to study persons with disabilities. Milbank Quarterly 2002;80(2):347–379. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.American Heart Association. What are the Symptoms of High Blood Pressure? [Internet] [updated 2016 Oct 31; cited 2018 Oct 26] Available at: http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/SymptomsDiagnosisMonitoringofHighBloodPressure/What-are-the-Symptoms-of-High-Blood-Pressure_UCM_301871_Article.jsp#.VkSmgb-301872I301872B.
- 40.Peltz A, Samuels-Kalow ME, Rodean J, Hall M, Alpern ER, Aronson PL, Berry JG, Shaw KN, Morse RB, Freedman SB, Cohen E. Characteristics of children enrolled in Medicaid with high-frequency emergency department use. Pediatrics [Internet] 2017. Aug 1:e20170962. Available at: http://pediatrics.aappublications.org/content/140/3/e20170962.long [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.