Video Abstract

Video Abstract

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BACKGROUND:

An increasing proportion of pediatric hospital days are attributed to technology-dependent children. The impact that a pediatric home care nursing (HCN) shortage has on increasing length of hospital stay and readmissions in this population is not well documented.

METHODS:

We conducted a 12-month multisite prospective study of children with medical complexity discharging with home health. We studied the following 2 cohorts: new patients discharging for the first time to home nursing and existing patients discharging from the hospital to previously established home nursing. A modified delay tool was used to categorize causes, delayed discharge (DD) days, and unplanned 90-day readmissions.

RESULTS:

DD occurred in 68.5% of 54 new patients and 9.2% of 131 existing patients. Lack of HCN was the most frequent cause of DD, increasing costs and directly accounting for an average length of stay increase of 53.9 days (range: 4–204) and 35.7 days (3–63) for new and existing patients, respectively. Of 1582 DDs, 1454 (91.9%) were directly attributed to lack of HCN availability. DD was associated with younger age and tracheostomy. Unplanned 90-day readmissions were due to medical setbacks (96.7% of cases) and occurred in 53.7% and 45.0% of new and existing patients, respectively.

CONCLUSIONS:

DD and related costs are primarily associated with shortage of HCN and predominantly affect patients new to HCN. Medical setbacks are the most common causes of unplanned 90-day readmissions. Increasing the availability of home care nurses or postacute care facilities could reduce costly hospital length of stay.

What’s Known on This Subject:

Reports increasingly implicate a shortage of pediatric home care nurses with prolonged length of hospitalization for children with medical complexity. The magnitude of this problem as well as the contribution of home care failures to hospital readmission is largely unknown.

What This Study Adds:

A home care nursing shortage is the primary cause of delayed hospital discharge for children discharging to home care, resulting in increased length of stay and costs. Medical setbacks, not failed home care, accounted for most nonelective 90-day readmissions.

Children with medical complexity (CMC) account for one-third of all pediatric health care costs, and 80% of that is spent on hospitalization.1 Decreasing health care use by CMC must address inefficiencies in the use of inpatient and ICU resources.2 The impact a shortage of home care nursing (HCN) has on hospital length of stay (LOS) for this population in a region without postacute or long-term care facilities is inadequately studied.

Technology-dependent CMC often require extended hours of HCN to facilitate a safe transition to home, minimize family burnout, and reduce the risk of readmissions. The demand for HCN has increased in recent decades3,7 with the largest increases for children <5 years of age.8 The increase is due in part to technological innovations that have augmented survival of CMC and pressures to shift care from hospital to community settings.3,9,11 

Although nonclinical factors such as discharge planning, home care funding and availability, and family training9,12,21 may delay discharge of CMC, most delayed discharge (DD) studies have been focused on children requiring mechanical ventilation.9,12,14 Using a modified version of a Delay Tool,22,24 this study prospectively documents causes, frequency, days, and costs associated with DD in CMC deemed medically ready for discharge with HCN. Causes and frequency of readmissions are also documented to study the role home care failures have on rehospitalization.

This was a 12-month prospective study that involved CMC discharged with HCN. The study occurred from April 1, 2016, through March 31, 2017, from 4 children’s hospitals in Minnesota (Children’s Minnesota, University of Minnesota Masonic Children’s Hospital, Mayo Clinic, and Gillette Children’s Specialty Healthcare). Care coordinators identified CMC after admission that met inclusion criteria (Supplemental Table 3) for study personnel. However, inconsistencies exist in defining CMC25; for this study, the defining factor for inclusion was the need for ≥8 hours per week of HCN at hospital discharge. Eligible patients were stratified as new or existing. A new patient was defined as a newborn or child not deemed medically complex before hospitalization who met inclusion criteria at discharge requiring HCN. An existing patient was previously defined as medically complex with established HCN before admission and continued to meet inclusion criteria at discharge to HCN. Care coordinators actively involved in patient care communicated with attending physicians and study personnel regarding the time line for when a patient was deemed medically ready for discharge. Patients were excluded if discharge occurred after the 12-month study period, if parents or guardians declined chart review for any research purposes, or if death occurred before discharge. This study was approved by each hospital’s institutional review board with a waiver of consent.

Data were collected on worksheets (Supplemental Information) and entered by study site personnel after discharge into a secure encrypted Web site. Designated individuals at each participating study site were issued user identifications and access passwords. Patient identification numbers assigned to eligible patient cases were specific to the study site and designated individuals. Data were deidentified before entry, and only the designated individuals could link data records to patient medical records. For patients who remained hospitalized after being deemed medically ready for discharge, a modified delay tool (Supplemental Information) was used to identify causes and number of delayed days. The number of DD days attributed to the availability of HCN to staff a patient at home was specifically assessed. Causes of unplanned same-hospital readmissions within 7 and 90 days postdischarge from the index hospitalization were assessed by study site personnel through hospital medical records. Readmissions were not used as index hospitalizations. Unplanned readmissions were categorized as medical setback, home care failure with nursing staff, medical equipment failure, or inability of the family to care for the child at home.

We estimated the resource implications of DD due to availability of HCN as the difference between avoidable hospital cost and the cost of HCN had patients been discharged to HCN when they were medically ready for discharge. For each DD day, we estimated hospital cost on the basis of recent studies of CMC.26,29 Inflating estimates from these studies to 2017 dollars using the Consumer Price Index for hospital and related services, we estimated the cost per hospital day for CMC at $3932. The cost of HCN is based on Medicaid reimbursement rates for home care in Minnesota. We estimated HCN cost at $40.72 per hour, given the mix of registered nurse and licensed practical nurse hours.

Data were entered, downloaded, and converted to SAS version 9.4 (SAS Institute, Inc, Cary, NC) for analysis. Patients were identified as new or existing regarding HCN. Differences between these 2 patient groups were assessed by using χ2 for categorical variables (race, age group, primary diagnosis, and causes of DD) or Student’s t test for continuous or binary variables (average hospital LOS, total discharge days, discharge days attributable to lack of home care nurse availability). An additional analysis examining the association between the allocation of HCN hours and patient care needs (invasive ventilation and tracheostomy) was conducted by using χ2 analysis. Statistical significance was set as P < .05 for all tests.

An exploratory data approach using classification and regression tree (CART) analysis was used to examine the association between 2 defined outcomes of interest (discharged when medically ready and 90-day readmissions) and hospitalization episode attributes (patient demographic variables, LOS, and medical treatments). CARTs are machine-learning methods for constructing prediction models from data that will detect potential interactions of significance.30 The models are obtained by recursively partitioning the data space and fitting a simple prediction model within each partition to allow for the identification of variables that are most efficient in classifying levels of the outcome under investigation.

Study patients consisted of 54 new and 131 existing patients. New patients were younger than existing patients. There was no statistical difference between these groups by sex, race, primary language, need for an interpreter, location of residence, and private insurance (Table 1). Clinically, new and existing patients had similar rates of chromosomal abnormality or syndrome but differed by the primary diagnosis. Specifically, new patients most likely had a primary diagnosis of lung or airway obstruction disorder, whereas brain injury or central nervous system disorder was the most likely diagnosis for existing patients (Table 1). The CART analysis (Fig 1) revealed that age, insurance, tracheostomy, and sex, but not rural residence or prescribed HCN hours, were the discriminating factors for determining if patients were discharged when medically ready. Discharge delay for new patients was more likely due to waiting for home care nurses than for existing patients. For existing patients, patient or family and social situations were as likely causes of DD as waiting for home care nurses (Table 1). Average days for all discharge delays was significantly different between new (26.5 days) and existing (1.1 days) patients. Waiting for home care nurses accounted for 94.1% and 71.3% of total DD days for new and existing patients, respectively. Among study patients, 175 were discharged from the hospital with their families, 9 to medical foster care, and 1 to an alternate hospital.

TABLE 1

Comparison of New and Existing Patients

New Patients, n (%)Existing Patients, n (%)Difference, %P
No. patients, n 54 131 — — 
Demographic characteristics     
 Male 27 (50.0) 63 (48.1) 1.9 .816 
 Race    .341 
  White 37 (68.5) 97 (74.0) −5.5  
  African American 5 (9.3) 16 (12.2) −3.0  
  Other or unknown 12 (22.2) 18 (13.7) 8.5  
 Age at discharge, y    <.001 
  <1 34 (63.0) 11 (8.4) 54.6  
  1–4 15 (27.8) 56 (42.7) −15.0  
  ≥5 5 (9.3) 64 (48.9) −39.6  
 English language 47 (87.0) 117 (89.3) −2.3 .661 
 Interpreter needed 5 (9.3) 13 (9.9) −0.7 .891 
 Patient residence in Twin Cities metropolitan counties 36 (66.7) 77 (58.8) 7.9 .322 
 Private insurance 27 (50.0) 53 (40.5) 9.5 .238 
Clinical characteristics     
 Chromosomal abnormality and/or syndrome 16 (29.6) 43 (32.8) −3.2 .675 
 Primary diagnosis for inpatient admission    .006 
  Brain injury and/or central nervous system disorder 8 (14.8) 55 (42.0) −27.2  
  Lung or airway obstruction disorder 23 (42.6) 26 (19.8) 22.7  
  Neuromuscular disorder 4 (7.4) 10 (7.6) −0.2  
  Cardiac 4 (7.4) 7 (5.3) 2.1  
  Gastrointestinal 3 (5.6) 8 (6.1) −0.6  
  Other 12 (22.2) 25 (19.1) 3.1  
Discharge characteristics     
 Discharged to home with family 52 (96.3) 123 (93.9) 2.4 .516 
 Patients with DD 37 (68.5) 12 (9.2) 59.4 <.001 
 Causes of DD    .019 
  Patients waiting for home care nurses 25 (46.3) 3 (2.3) 44.0  
  Patient or family 4 (7.4) 3 (2.3) 5.1  
  Social situation 2 (3.7) 4 (3.1) 0.7  
  Other 6 (11.1) 2 (1.5) 9.6  
 Average hospital LOS, d 124.9 11.5 113.4 <.001 
  LOS before DD, d 98.4 10.3 88.0 <.001 
  LOS after medically ready for discharge, d 26.5 1.1 25.4 <.001 
 DD d, total of all patients 1432 150 — — 
  Due to waiting for home care nurses 1347 (94.1) 107 (71.3) 22.7 <.001 
 90-d same-hospital readmission rate 29 (53.7) 59 (45.0) 8.7 .288 
New Patients, n (%)Existing Patients, n (%)Difference, %P
No. patients, n 54 131 — — 
Demographic characteristics     
 Male 27 (50.0) 63 (48.1) 1.9 .816 
 Race    .341 
  White 37 (68.5) 97 (74.0) −5.5  
  African American 5 (9.3) 16 (12.2) −3.0  
  Other or unknown 12 (22.2) 18 (13.7) 8.5  
 Age at discharge, y    <.001 
  <1 34 (63.0) 11 (8.4) 54.6  
  1–4 15 (27.8) 56 (42.7) −15.0  
  ≥5 5 (9.3) 64 (48.9) −39.6  
 English language 47 (87.0) 117 (89.3) −2.3 .661 
 Interpreter needed 5 (9.3) 13 (9.9) −0.7 .891 
 Patient residence in Twin Cities metropolitan counties 36 (66.7) 77 (58.8) 7.9 .322 
 Private insurance 27 (50.0) 53 (40.5) 9.5 .238 
Clinical characteristics     
 Chromosomal abnormality and/or syndrome 16 (29.6) 43 (32.8) −3.2 .675 
 Primary diagnosis for inpatient admission    .006 
  Brain injury and/or central nervous system disorder 8 (14.8) 55 (42.0) −27.2  
  Lung or airway obstruction disorder 23 (42.6) 26 (19.8) 22.7  
  Neuromuscular disorder 4 (7.4) 10 (7.6) −0.2  
  Cardiac 4 (7.4) 7 (5.3) 2.1  
  Gastrointestinal 3 (5.6) 8 (6.1) −0.6  
  Other 12 (22.2) 25 (19.1) 3.1  
Discharge characteristics     
 Discharged to home with family 52 (96.3) 123 (93.9) 2.4 .516 
 Patients with DD 37 (68.5) 12 (9.2) 59.4 <.001 
 Causes of DD    .019 
  Patients waiting for home care nurses 25 (46.3) 3 (2.3) 44.0  
  Patient or family 4 (7.4) 3 (2.3) 5.1  
  Social situation 2 (3.7) 4 (3.1) 0.7  
  Other 6 (11.1) 2 (1.5) 9.6  
 Average hospital LOS, d 124.9 11.5 113.4 <.001 
  LOS before DD, d 98.4 10.3 88.0 <.001 
  LOS after medically ready for discharge, d 26.5 1.1 25.4 <.001 
 DD d, total of all patients 1432 150 — — 
  Due to waiting for home care nurses 1347 (94.1) 107 (71.3) 22.7 <.001 
 90-d same-hospital readmission rate 29 (53.7) 59 (45.0) 8.7 .288 

—, not applicable.

FIGURE 1

Partitioning or discriminating factors for determining discharged when medically ready. For the outcome “discharged when medically ready,” 4 variables were found to partition the study population. The approximate R2 for these 4 factors was 32.3%. Age at discharge, with a split at 2 years of age, was the most important factor. Thirty-seven children <2 years of age (54%) experienced a DD; 31 of these children had a tracheostomy. Among these 31 children, 24 (77%) more frequently experienced a DD. Among children 2 years of age and older, only 12 (10%) experienced a DD. All 12 had nonprivate insurance with more male patients experiencing DD than female patients.

FIGURE 1

Partitioning or discriminating factors for determining discharged when medically ready. For the outcome “discharged when medically ready,” 4 variables were found to partition the study population. The approximate R2 for these 4 factors was 32.3%. Age at discharge, with a split at 2 years of age, was the most important factor. Thirty-seven children <2 years of age (54%) experienced a DD; 31 of these children had a tracheostomy. Among these 31 children, 24 (77%) more frequently experienced a DD. Among children 2 years of age and older, only 12 (10%) experienced a DD. All 12 had nonprivate insurance with more male patients experiencing DD than female patients.

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Figure 2 shows the distribution of HCN hours. The allotment of nursing hours was not significantly different between the 2 groups, and 72.2% and 80.9% of new and existing patients, respectively, received >40 hours per week. Extended hours of nursing care >120 hours per week were prescribed for 100% (16 of 16) of new patients with invasive ventilation compared with 55.5% (15 of 27) of existing patients. The allocation of HCN hours was associated with invasive ventilation and/or tracheostomy (P < .001).

FIGURE 2

Weekly HCN hours at discharge for patients with and without DD. A, New patients. B, Existing patients.

FIGURE 2

Weekly HCN hours at discharge for patients with and without DD. A, New patients. B, Existing patients.

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Medical devices and therapies prescribed at discharge are shown in Fig 3. DD in new patients was associated with the presence of a tracheostomy tube (Fig 1).

FIGURE 3

Medical equipment and/or therapies for new patients with and without DD and reason for DD. Of the 54 new patients, 25 had DD waiting for HCN, 12 had DD for reasons other than waiting for HCN, and 17 did not have DD. GT, gastrostomy tube; JT, jejunostomy tube; NG, nasogastric tube.

FIGURE 3

Medical equipment and/or therapies for new patients with and without DD and reason for DD. Of the 54 new patients, 25 had DD waiting for HCN, 12 had DD for reasons other than waiting for HCN, and 17 did not have DD. GT, gastrostomy tube; JT, jejunostomy tube; NG, nasogastric tube.

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There were 1454 DD days across 28 patients with DD who waited for HCN. This was an average of 51.9 days per patient. We estimated that the hospital cost for DD days across patients who waited for HCN was $5.72 million for all patients, with most of that attributable to new patients (Table 2). The hospital costs would have been avoided had these patients’ discharges not been delayed if HCN was available when they were medically ready. In contrast, they would have incurred HCN costs estimated at $769 326 over the comparable time period. Hence, the net costs avoided would have been $4.95 million across 28 patients or $170 954 per patient with DD.

TABLE 2

Cost of DD Due to Waiting for HCN

New PatientsExisting PatientsAll patients
Patients with DD due to waiting for home care nurses 25 28 
Total DD d waiting for home care nurses 1347 107 1454 
Hospital costs for DD waiting for home care nurses $5 296 404 $420 724 $5 717 128 
Average home care nurse h per d 15.7 15.5 15.7 
Home care costs for DD d $713 398 $55 927 $769 326 
Hospital cost less home care cost $4 583 006 $364 797 $4 947 802 
 Percent 86.5% 86.7% 86.5% 
Averages per patient with DD waiting for home care nurses    
 DD d 53.9 35.7 51.9 
 Hospital costs for DD waiting for home care nurses $211 856 $140 241 $204 183 
 Home care costs for DD d $34 511 $22 546 $33 229 
 Hospital costs less home care cost $177 345 $117 695 $170 954 
New PatientsExisting PatientsAll patients
Patients with DD due to waiting for home care nurses 25 28 
Total DD d waiting for home care nurses 1347 107 1454 
Hospital costs for DD waiting for home care nurses $5 296 404 $420 724 $5 717 128 
Average home care nurse h per d 15.7 15.5 15.7 
Home care costs for DD d $713 398 $55 927 $769 326 
Hospital cost less home care cost $4 583 006 $364 797 $4 947 802 
 Percent 86.5% 86.7% 86.5% 
Averages per patient with DD waiting for home care nurses    
 DD d 53.9 35.7 51.9 
 Hospital costs for DD waiting for home care nurses $211 856 $140 241 $204 183 
 Home care costs for DD d $34 511 $22 546 $33 229 
 Hospital costs less home care cost $177 345 $117 695 $170 954 

Hospital costs per day were estimated at $3932. The reimbursement or cost for HCN was estimated at $40.72 per hour.

Unplanned readmissions were similar between new and existing patients. New patients, 29 of 54 (53.7%), had a total of 48 readmissions within 90 days, and 19% of those readmissions occurred within 7 days of discharge. Existing patients, 59 of 131 (45%), had a total of 102 readmissions within 90 days, and 12.7% occurred within 7 days of discharge. Collectively between both groups, 47.7% of readmitted patients had >1 readmission within 90 days. Medical setbacks were the cause for 96.7% of readmissions. The remaining readmissions were due to medical equipment failures (n = 3), home care failure (n = 1), and inability of the family to care for the child (n = 1). CART analysis of factors determining unplanned readmissions (Fig 4) identified a higher proportion of readmissions occurred in patients residing outside the Twin Cities metropolitan area (61%) versus patients residing in the metropolitan area (39%).

FIGURE 4

Partitioning or discriminating factors for determining unplanned readmission within 90 days. For the outcome “unplanned readmission within 90 days,” 4 factors were found to partition the study population. The approximate R2 for these 4 factors was 9.2%. The location of residence was the most important factor. There were 88 children with an unplanned readmission within 90 days, with 72 residing outside the Twin Cities metropolitan area. Among these children, 44 (61%) experienced an unplanned readmission, with a greater proportion of unplanned readmissions among female patients than male patients. Among the 113 children residing in the Twin Cities metropolitan area, 44 (39%) had an unplanned readmission. For these children, an LOS of 5 days or longer with no airway clearance technology had a higher probability of an unplanned readmission.

FIGURE 4

Partitioning or discriminating factors for determining unplanned readmission within 90 days. For the outcome “unplanned readmission within 90 days,” 4 factors were found to partition the study population. The approximate R2 for these 4 factors was 9.2%. The location of residence was the most important factor. There were 88 children with an unplanned readmission within 90 days, with 72 residing outside the Twin Cities metropolitan area. Among these children, 44 (61%) experienced an unplanned readmission, with a greater proportion of unplanned readmissions among female patients than male patients. Among the 113 children residing in the Twin Cities metropolitan area, 44 (39%) had an unplanned readmission. For these children, an LOS of 5 days or longer with no airway clearance technology had a higher probability of an unplanned readmission.

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Approximately 5% to 7% of pediatric hospital discharges include home health care, and these patients are more likely to have multiple chronic conditions and technology assistance.31,32 Our prospective study involved only CMC being discharged with home health care to quantify the impact a home health nursing shortage25,33,34 may have on impeding discharge. We found that unavailability of HCN was the primary cause for 57.1% of discharge delays, accounted for 91.9% of DD days, and contributed to lengthier delays. Other studies involving children with home mechanical ventilation had wide-ranging delay estimates from 19 days to 9.6 months.3,12,14 What our study adds is an estimate of the average length of DD and the average length of delay specifically attributable to the lack of HCN among pediatric patients discharged to HCN in a region without postacute or long-term care facilities.

The Minnesota Olmstead Plan requires that individuals with disabilities receive care and services in the most integrated setting. Currently, Minnesota has no postacute or long-term care facilities for CMC, and the focus is on discharge to home or community-based alternatives. Pediatric long-term care facilities extend medical care or services for CMC who can no longer be cared for in the home. Conceivably, availability of these alternatives might shorten acute care hospitalization. Authors of 1 report35 identified that 25% of DDs were due to the lack of HCN in a region without a postacute care facility. Children with tracheostomy spend fewer days in acute care hospitals when postacute care facilities are used.31,36 The lack of postacute care facilities37 or transition centers to provide services for children still needing time to stabilize contributes to prolonged hospitalization in acute care hospitals.

Although DD, specifically attributable to the lack of HCN, occurred with new and existing home care patients, we found most delays were associated with patients new to HCN. Differences are likely attributable to established HCN for existing patients that reduces the likelihood and length of delays as well as parental familiarity caring for their child when HCN is unavailable. Having established HCN minimized associated discharge delays. In a previous report14 that identified home care funding and medical foster care placement as the greatest barriers to discharge for ventilator-assisted children, the time from medical stability to discharge accounted for 73% ± 29% of the entire LOS. In our study, the number of days from medical stability to discharge averaged 21.2% of LOS for new patients with DD who waited for HCN. This prompted other institutions to implement discharge planning pathways for children as soon as they are identified as becoming technology dependent.15,19,38 

Discharge delays due to pediatric HCN shortage have worsened since 2001, when a Minnesota report33 found a lack of HCN, or pending insurance approval, accounted for 205 delay days among 29 CMC. The demand for pediatric home care has increased in recent decades and will continue as medical advances for severely ill children increase life expectancy but without restoration of full function.3,8 As this population of CMC grows, there is a proportionate increase in the degree of intensive medical technology use,2 and this may impart a trade-off in mortality for morbidity.9,34 As an example, bronchopulmonary dysplasia has recently been associated with a 3% chance for survivors to be discharged from the hospital on mechanical ventilation,39 commonly with HCN.

A unique outcome metric available for comparison from our study was the allotment of HCN hours. Authors of a 1991 report40 from Minnesota identified that 64.5% of families received >9 hours per day, and 16% received 24 hours per day. HCN varied between 8 and 24 hours per day from other studies of tracheostomized children.14,34 In our study, >70% of patients received >40 hours of nursing per week, and as expected, new patients were more likely to receive more extended hours of care (>120 hours per week) than existing patients.

As the population of CMC continues to grow, there is a concomitant need for home care nurses. A reported shortage of pediatric HCN41 is multifactorial. New graduate nurses often perceive home care as a stepping stone for experience needed to gain hospital employment with better benefits and an hourly wage increase of $10.33 Authors of a recent study of pediatric chronic respiratory failure cases, which are likely cases for discharge to home care, found that increased LOS correlated with economic conditions when unemployment was low.26 Although many home care nurses find their jobs rewarding, several factors impact retaining nurses beyond monetary factors.42 The job is socially isolating, not all families are welcoming, and as the level of acuity increases for CMC so does the intensity of nursing care needs. Prolonged and unplanned rehospitalizations of a home care nurse’s assigned patient(s) may contribute to extended periods of unemployment and subsequent migration to other opportunities for employment. This latter concept contributed to DD of patients who had preestablished nursing in our study.

From a value perspective, DDs have substantial financial implications, which we have estimated at $170 954 per patient for this study. In some respects, this estimated an upper bound on avoidable costs because increasing the availability of HCN would require an increase in the home care reimbursement rate, which would increase the cost of home care for all patients. However, children discharged to HCN may experience less hospitalization than comparable children discharged without HCN.43 Rehospitalization would increase costs avoided by the use of postdischarge HCN. DD has negative effects beyond increased costs for CMC. Prolonged hospitalization may affect child development contributing to health care disparities44 and increase risk for iatrogenic errors.45 

Prolonged hospitalization in an acute care facility beyond what is necessary for the diagnosis and treatment of the acute medical problem leads to challenges in facility planning, bed use, and other resources. Technology-dependent children with recurrent or chronic medical problems are typically admitted to ICUs for stabilization and management because other areas of the hospital are not equipped to care for patients requiring ventilation. In many children’s hospitals, patients who are ventilator dependent remain in NICUs or PICUs until discharge, occupying a scarce community resource and precluding the admission of other acutely ill patients. As reimbursement moves to a diagnosis-related–group system for payment, additional costs of caring for children in an ICU who do not require ICU-level care will become a greater drain on institutional resources. Postacute care or transition facilities may extend care outside of acute care hospitals before unification with family at home and may be an acceptable solution for some families. A strong partnership between acute, postacute, and long-term care pediatric health care organizations must be a priority to provide the best care in the most appropriate physical and psychological setting for children.

With our study, we found 90-day readmission rates of 53.7% and 45% for new and existing patients, respectively. There are no other studies with readmission rates specifically for CMC discharged with extended hours of HCN. The high readmission rates in our study likely reflect the inherent medical fragility of a population discharged with extended hours of nursing care. Without the option for discharge to a postacute care facility, our population was discharged only after acquiring HCN. Conceivably, children who are technology dependent discharged to a postacute care facility may have a greater degree of medical supervision and stability before being discharged from the hospital than children discharged directly from an acute care hospital to HCN. Many of these readmissions may have been potentially preventable in our population.

Limitations of the study included an underestimation of the problem because some regional hospital systems involved in discharging comparable CMC patients were not included in the study. In addition, patients were excluded if they remained hospitalized at the end of the study or if parents or guardians declined chart review for any research purposes. The study included only same-hospital readmissions, but because these are CMC who are best served in tertiary children’s hospitals, this underestimation may be small. Families of existing patients may have been willing to discharge 1 or 2 days earlier and provide care before scheduled nursing shifts could be staffed. Costs not fully captured in our estimate of hospital costs include physician and ancillary charges, which if included, would have increased our estimate of avoidable costs. Lastly, this study was undertaken in a region without the option of postacute or long-term care facilities.

In a setting without postacute or long-term care pediatric facilities, lack of HCN accounted for the greatest obstacle to discharging a population of CMC with prescribed HCN. The inability to staff medically stable CMC at home prolonged hospitalization and increased health care expenditures to a greater degree in new patients discharging for the first time to HCN than patients with preexisting home care. DD was associated with tracheostomy and younger age but not the number of prescribed HCN hours or rural residence. Expanding the availability of home care resources or postacute care facilities for this population could impact LOS. Unplanned 90-day readmissions were due to medical setbacks, not home care failures. The high prevalence of unplanned 90-day readmissions in our populations may have been potentially preventable but likely reflects the underlying fragility of patients discharging with extended hours of nursing care.

     
  • CART

    classification and regression tree

  •  
  • CMC

    children with medical complexity

  •  
  • DD

    delayed discharge

  •  
  • HCN

    home care nursing

  •  
  • LOS

    length of stay

Dr Maynard conceptualized, designed, and supervised the study and drafted the initial manuscript and subsequent revisions; Dr Wheeler conceptualized and designed the study and critically reviewed the manuscript; Dr Christensen reviewed the study design, contributed to the initial draft, including statistical analysis, and reviewed and revised the manuscript; Drs Ouellette and Schiltz reviewed the study design, acquired data, and reviewed and revised the manuscript; Drs Jacob, Podgorski, and Schwantes reviewed the study design and reviewed and revised the manuscript; Dr Cady reviewed and contributed to the study design, acquired data, and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted.

FUNDING: No external funding.

COMPANION PAPER: A companion to this article can be found online at www.pediatrics.org/cgi/doi/10.1542/peds.2018-2960.

We thank Leslie Loeding, MS, Mary Pat Osborne, RN, Josalan Sullivan, and Becca Mitchell for data collection and entry. We thank Edwin Simpser, MD, and David Steinhorn, MD, for their critical review of the article.

1
Berry
JG
,
Agrawal
RK
,
Cohen
E
,
Kuo
DZ
;
Children’s Hospital Association
. The landscape of medical care for children with medical complexity. 2013. Available at: https://www.childrenshospitals.org/issues-and-advocacy/children-with-medical-complexity/issue-briefs-and-reports/the-landscape-of-medical-care-for-children-with-medical-complexity. Accessed January 9, 2018
2
Chan
T
,
Rodean
J
,
Richardson
T
, et al
.
Pediatric critical care resource use by children with medical complexity.
J Pediatr
.
2016
;
177
:
197
203.e1
[PubMed]
3
Wallis
C
,
Paton
JY
,
Beaton
S
,
Jardine
E
.
Children on long-term ventilatory support: 10 years of progress.
Arch Dis Child
.
2011
;
96
(
11
):
998
1002
[PubMed]
4
Amin
R
,
Sayal
P
,
Syed
F
,
Chaves
A
,
Moraes
TJ
,
MacLusky
I
.
Pediatric long-term home mechanical ventilation: twenty years of follow-up from one Canadian center.
Pediatr Pulmonol
.
2014
;
49
(
8
):
816
824
[PubMed]
5
McDougall
CM
,
Adderley
RJ
,
Wensley
DF
,
Seear
MD
.
Long-term ventilation in children: longitudinal trends and outcomes.
Arch Dis Child
.
2013
;
98
(
9
):
660
665
[PubMed]
6
Chau
SK
,
Yung
AW
,
Lee
SL
.
Long-term management for ventilator-assisted children in Hong Kong: 2 decades’ experience.
Respir Care
.
2017
;
62
(
1
):
54
64
[PubMed]
7
Paulides
FM
,
Plötz
FB
,
Verweij-van den Oudenrijn
LP
,
van Gestel
JP
,
Kampelmacher
MJ
.
Thirty years of home mechanical ventilation in children: escalating need for pediatric intensive care beds.
Intensive Care Med
.
2012
;
38
(
5
):
847
852
[PubMed]
8
Benneyworth
BD
,
Gebremariam
A
,
Clark
SJ
,
Shanley
TP
,
Davis
MM
.
Inpatient health care utilization for children dependent on long-term mechanical ventilation.
Pediatrics
.
2011
;
127
(
6
). Available at: www.pediatrics.org/cgi/content/full/127/6/e1533
[PubMed]
9
Fraser
J
,
Henrichsen
T
,
Mok
Q
,
Tasker
RC
.
Prolonged mechanical ventilation as a consequence of acute illness.
Arch Dis Child
.
1998
;
78
(
3
):
253
256
[PubMed]
10
Chatwin
M
,
Tan
HL
,
Bush
A
,
Rosenthal
M
,
Simonds
AK
.
Long term non-invasive ventilation in children: impact on survival and transition to adult care.
PLoS One
.
2015
;
10
(
5
):
e0125839
11
Perrin
JM
.
Health services research for children with disabilities.
Milbank Q
.
2002
;
80
(
2
):
303
324
[PubMed]
12
Rafferty
A
,
Knight
D
,
Bew
S
,
Knight
L
.
Retrospective, cross-sectional review of delayed discharge after paediatric tracheostomy.
J Laryngol Otol
.
2012
;
126
(
12
):
1247
1253
[PubMed]
13
Edwards
EA
,
O’Toole
M
,
Wallis
C
.
Sending children home on tracheostomy dependent ventilation: pitfalls and outcomes.
Arch Dis Child
.
2004
;
89
(
3
):
251
255
[PubMed]
14
DeWitt
PK
,
Jansen
MT
,
Ward
SL
,
Keens
TG
.
Obstacles to discharge of ventilator-assisted children from the hospital to home.
Chest
.
1993
;
103
(
5
):
1560
1565
[PubMed]
15
Sobotka
SA
,
Hird-McCorry
LP
,
Goodman
DM
.
Identification of fail points for discharging pediatric patients with new tracheostomy and ventilator.
Hosp Pediatr
.
2016
;
6
(
9
):
552
557
[PubMed]
16
Elias
ER
,
Murphy
NA
;
Council on Children With Disabilities
.
Home care of children and youth with complex health care needs and technology dependencies.
Pediatrics
.
2012
;
129
(
5
):
996
1005
[PubMed]
17
Noyes
J
.
Barriers that delay children and young people who are dependent on mechanical ventilators from being discharged from hospital.
J Clin Nurs
.
2002
;
11
(
1
):
2
11
[PubMed]
18
Jardine
E
,
O’Toole
M
,
Paton
JY
,
Wallis
C
.
Current status of long term ventilation of children in the United Kingdom: questionnaire survey.
BMJ
.
1999
;
318
(
7179
):
295
299
[PubMed]
19
Baker
CD
,
Martin
S
,
Thrasher
J
, et al
.
A standardized discharge process decreases length of stay for ventilator-dependent children.
Pediatrics
.
2016
;
137
(
4
):
e20150637
[PubMed]
20
Statile
AM
,
Schondelmeyer
AC
,
Thomson
JE
, et al
.
Improving discharge efficiency in medically complex pediatric patients.
Pediatrics
.
2016
;
138
(
2
):
e20153832
[PubMed]
21
Tearl
DK
,
Cox
TJ
,
Hertzog
JH
.
Hospital discharge of respiratory-technology-dependent children: role of a dedicated respiratory care discharge coordinator.
Respir Care
.
2006
;
51
(
7
):
744
749
[PubMed]
22
Selker
HP
,
Beshansky
JR
,
Pauker
SG
,
Kassirer
JP
.
The epidemiology of delays in a teaching hospital. The development and use of a tool that detects unnecessary hospital days.
Med Care
.
1989
;
27
(
2
):
112
129
[PubMed]
23
Klein
JD
,
Beshansky
JR
,
Selker
HP
.
Using the delay tool to attribute causes for unnecessary pediatric hospital days.
Med Care
.
1990
;
28
(
10
):
982
989
[PubMed]
24
Srivastava
R
,
Stone
BL
,
Patel
R
, et al
.
Delays in discharge in a tertiary care pediatric hospital.
J Hosp Med
.
2009
;
4
(
8
):
481
485
[PubMed]
25
Cohen
E
,
Kuo
DZ
,
Agrawal
R
, et al
.
Children with medical complexity: an emerging population for clinical and research initiatives.
Pediatrics
.
2011
;
127
(
3
):
529
538
[PubMed]
26
Christensen
EW
,
Maynard
RC
.
Do changing labor market conditions affect the length of stay for chronic respiratory failure hospitalizations?
Home Health Care Manage Pract
.
2017
;
29
(
4
):
235
241
27
Gold
JM
,
Hall
M
,
Shah
SS
, et al
.
Long length of hospital stay in children with medical complexity.
J Hosp Med
.
2016
;
11
(
11
):
750
756
[PubMed]
28
Berry
JG
,
Hall
M
,
Neff
J
, et al
.
Children with medical complexity and Medicaid: spending and cost savings [published correction appears in Health Aff (Millwood). 2015;34(1):189].
Health Aff (Millwood)
.
2014
;
33
(
12
):
2199
2206
29
Cohen
E
,
Berry
JG
,
Camacho
X
,
Anderson
G
,
Wodchis
W
,
Guttmann
A
.
Patterns and costs of health care use of children with medical complexity.
Pediatrics
.
2012
;
130
(
6
). Available at: www.pediatrics.org/cgi/content/full/130/6/e1463
[PubMed]
30
Loh
W-Y
.
Classification and regression trees.
WIREs Data Mining Knowl Discov
.
2011
;
1
(
1
):
14
23
31
Feudtner
C
,
Villareale
NL
,
Morray
B
,
Sharp
V
,
Hays
RM
,
Neff
JM
.
Technology-dependency among patients discharged from a children’s hospital: a retrospective cohort study.
BMC Pediatr
.
2005
;
5
(
1
):
8
[PubMed]
32
Berry
JG
,
Hall
M
,
Dumas
H
, et al
.
Pediatric hospital discharges to home health and postacute facility care: a national study.
JAMA Pediatr
.
2016
;
170
(
4
):
326
333
[PubMed]
33
Page
DR
.
Pediatric home care: nursing the shortage.
Caring
.
2001
;
20
(
6
):
46
47
[PubMed]
34
Pollack
MM
,
Holubkov
R
,
Funai
T
, et al;
Eunice Kennedy Shriver National Institute of Child Health and Human Development Collaborative Pediatric Critical Care Research Network
.
Pediatric intensive care outcomes: development of new morbidities during pediatric critical care.
Pediatr Crit Care Med
.
2014
;
15
(
9
):
821
827
[PubMed]
35
Graf
JM
,
Montagnino
BA
,
Hueckel
R
,
McPherson
ML
.
Children with new tracheostomies: planning for family education and common impediments to discharge.
Pediatr Pulmonol
.
2008
;
43
(
8
):
788
794
[PubMed]
36
Berry
JG
,
Graham
DA
,
Graham
RJ
, et al
.
Predictors of clinical outcomes and hospital resource use of children after tracheotomy.
Pediatrics
.
2009
;
124
(
2
):
563
572
[PubMed]
37
O’Brien
JE
,
Berry
J
,
Dumas
H
.
Pediatric post-acute hospital care: striving for identity and value.
Hosp Pediatr
.
2015
;
5
(
10
):
548
551
[PubMed]
38
Tamasitis
J
,
Shesser
L
.
A hospital-to-home program for ventilator-dependent children sets the standard of care.
AARC Times
.
2012
;
33
(
6
):
44
52
39
Jackson
W
,
Hornik
CP
,
Messina
JA
, et al
.
In-hospital outcomes of premature infants with severe bronchopulmonary dysplasia.
J Perinatol
.
2017
;
37
(
7
):
853
856
[PubMed]
40
Leonard
BJ
,
Brust
JD
,
Sielaff
BH
.
Determinants of home care nursing hours for technology-assisted children.
Public Health Nurs
.
1991
;
8
(
4
):
239
244
[PubMed]
41
Boss
RD
,
Williams
EP
,
Henderson
CM
, et al
.
Pediatric chronic critical illness: reducing excess hospitalizations.
Hosp Pediatr
.
2017
;
7
(
8
):
460
470
42
Nageswaran
S
,
Golden
SL
.
Factors associated with stability of health nursing services for children with medical complexity.
Home Healthc Now
.
2017
;
35
(
8
):
434
444
[PubMed]
43
Gay
JC
,
Thurm
CW
,
Hall
M
, et al
.
Home health nursing care and hospital use for medically complex children.
Pediatrics
.
2016
;
138
(
5
):
e20160530
[PubMed]
44
Sobotka
SA
,
Agrawal
RK
,
Msall
ME
.
Prolonged hospital discharge for children with technology dependency: a source of health care disparities.
Pediatr Ann
.
2017
;
46
(
10
):
e365
e370
[PubMed]
45
Ahuja
N
,
Zhao
W
,
Xiang
H
.
Medical errors in US pediatric inpatients with chronic conditions.
Pediatrics
.
2012
;
130
(
4
). Available at: www.pediatrics.org/cgi/content/full/130/4/e786
[PubMed]

Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Maynard is employed as a medical director for a home care company. He is also a consultant for the mass casualty ventilator project for Philips Respironics; the other authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: Dr Maynard is employed as a medical director for a home care company; the other authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data