Unplanned readmissions to acute care from a pediatric postacute care hospital: incidence, clinical reasons, and predictive factors

Post-acute day and night non-invasive respiratory intervention use and outcome: A brief report

PURPOSE

This study aimed to describe daytime and nighttime use and outcome of non-invasive respiratory intervention (NIRI) for infants born prematurely and for children with medical complexity (CMC) during a post-acute care hospital (PACH) admission.

METHODS

Thirty-eight initial PACH admissions (October 2018 through September 2020) for premature infants (< 1 year; n = 19) and CMC (> 1 year; n = 19) requiring NIRI during the day and/or at night were retrospectively examined. Measures included: 1) daytime and nighttime NIRI use by type (supplemental oxygen therapy via low-flow nasal cannula or positive airway pressure [PAP] via high-flow nasal cannula, continuous positive airway pressure, or biphasic positive airway pressure at admission and discharge) and 2) daytime and nighttime NIRI outcome reduction, increase, or no change from admission to discharge.

RESULTS

For the total sample (n = 38), daytime vs nighttime NIRI use was significantly different (p < 0.001). At both admission and discharge, supplemental oxygen was the most common NIRI during the day, while PAP was most common at night. From admission to discharge, seven (18%) infants and children had a positive change (reduced NIRI) during the day, while nine (24%) had a positive change at night. At discharge, 11/38 (29%) infants and children required no daytime NIRI, while 4/38 (11%) required no day or night NIRI.

CONCLUSION

NIRI use differs between day and night at PACH admission and discharge for CMC. Reductions in NIRI were achieved during the day and at night from PACH admission to discharge for both infants born prematurely and for children with varied congenital, neurological, or cardiac diagnoses.

Children dependent on respiratory support: A 10-year review from one pediatric postacute care hospital

OBJECTIVE

Pediatric postacute care hospitals (PACH) provide long-term care for children with medical complexity including children dependent on respiratory support. Descriptions of PACH respiratory care populations and outcomes, however, remain under-reported. Our aim was to describe demographics, respiratory outcome, and longitudinal trend of children with respiratory support admitted to a single PACH in the United States.

METHODS

Using electronic records from 2009 to 2018, data were examined for all children dependent on respiratory support. Children were identified for inclusion using respiratory level of care classifications (type of support) as outlined in hospital policy. Outcome was defined as change in level from first admission to final discharge. Number of admissions by level and year during the study timeframe were analyzed.

RESULTS

There were 1423 admissions for 767 children requiring respiratory support during the study timeframe. Children with higher respiratory classification level (eg, mechanical ventilation) at initial admission had more admissions to PACH (P < .001) and longer length of stays (P < .001). From first admission to final discharge, there was a significant change (reduction) in respiratory level (z = -4.588, P < .001). An increase in the overall number of admissions for children with respiratory support during the study timeframe was noted, with the largest increase for children requiring the highest level of support.

CONCLUSION

There has been a consistent increase in the number of children requiring respiratory support at admission to PACH. Reduction in respiratory support with postacute care occurs but children admitted with a higher level of support stay longer and experience multiple admissions.

[Detection of risk factors for preventable paediatric hospital readmissions]

INTRODUCTION AND OBJECTIVES

Readmission rate is an indicator of the quality of hospital care. The aim of the study is to identify potential preventable factors for paediatric readmission.

MATERIAL AND METHODS

A descriptive, analytical, longitudinal, and single centre study was carried out in the Paediatric Hospitalisation ward of a tertiary hospital during the period from June 2012 to November 2015. Readmission was defined as the one that occurs in the first 30 days of previous admission, as very early readmission if it occurs in the first 48hours, early readmission in the 2-7 days, and late readmission if occurs after 7 days. Preventable readmission is defined as one that takes place in the first 15 days and for the same reason as the first admission. Epidemiological and clinical variables were analysed. A univariate and multivariate study was carried out.

RESULTS

In the study period, 5,459 patients were admitted to the paediatric hospital, of which 226 of them were readmissions (rate of readmission: 4.1%). When the hospital occupation rate was greater than 70%, the overall percentage of readmissions was significantly higher (8.5% vs 2.5%; P<.001). In the multivariate analysis, it was found that having a chronic disease and the number of visits to emergency care units before admission, are predictive factors of preventable readmission.

CONCLUSIONS

The rate of readmissions is greater in the periods of higher care pressure. The readmission of patients with chronic condition is preventable, and therefore strategies must be designed to try to avoid them.

Risk factors associated with paediatric unplanned hospital readmissions: a systematic review

OBJECTIVE

To synthesise evidence on risk factors associated with paediatric unplanned hospital readmissions (UHRs).

DESIGN

Systematic review.

DATA SOURCE

CINAHL, EMBASE (Ovid) and MEDLINE from 2000 to 2017.

ELIGIBILITY CRITERIA

Studies published in English with full-text access and focused on paediatric All-cause, Surgical procedure and General medical condition related UHRs were included.

DATA EXTRACTION AND SYNTHESIS

Characteristics of the included studies, examined variables and the statistically significant risk factors were extracted. Two reviewers independently assessed study quality based on six domains of potential bias. Pooling of extracted risk factors was not permitted due to heterogeneity of the included studies. Data were synthesised using content analysis and presented in narrative form.

RESULTS

Thirty-six significant risk factors were extracted from the 44 included studies and presented under three health condition groupings. For All-cause UHRs, ethnicity, comorbidity and type of health insurance were the most frequently cited factors. For Surgical procedure related UHRs, specific surgical procedures, comorbidity, length of stay (LOS), age, the American Society of Anaesthesiologists class, postoperative complications, duration of procedure, type of health insurance and illness severity were cited more frequently. The four most cited risk factors associated with General medical condition related UHRs were comorbidity, age, health service usage prior to the index admission and LOS.

CONCLUSIONS

This systematic review acknowledges the complexity of readmission risk prediction in paediatric populations. This review identified four risk factors across all three health condition groupings, namely comorbidity; public health insurance; longer LOS and patients<12 months or between 13-18 years. The identification of risk factors, however, depended on the variables examined by each of the included studies. Consideration should be taken into account when generalising reported risk factors to other institutions. This review highlights the need to develop a standardised set of measures to capture key hospital discharge variables that predict unplanned readmission among paediatric patients.

Admissions to Acute Care Within 30 and 90 Days of Discharge Home From a Pediatric Post-acute Care Hospital

OBJECTIVES

Of all hospitalized children, those with medical complexity have the highest likelihood of hospital readmission. Post-acute hospital care could potentially help stabilize the health of these children. We examined the frequency of acute care hospital admissions after discharge home from a post-acute care hospital (PACH).

METHODS

A retrospective cohort analysis of 448 children with medical complexity discharged from a PACH from January 1, 2010, to December 31, 2015, with the main outcomes of acute care hospital readmissions 0 to 30 and 31 to 90 days after discharge home from a PACH. Demographic and clinical characteristics were compared between children with and without acute care readmission and between the 2 readmission groups.

RESULTS

Ninety-nine children (22%) had a readmission to the acute care hospital. Of these readmissions, 61 (62%) occurred between 0 and 30 days and 38 (38%) between 31 and 90 days after PACH discharge. A higher percentage of children readmitted had high medical severity (>3 systems involved or ventilator dependent) compared with children not readmitted (68% vs 31%, P = .04). No differences were found between children who were readmitted and those who were not by sex, race, payer, length of stay, or age at PACH discharge. Additionally, no differences were found between children readmitted within 30 days and children readmitted 31 to 90 days after PACH discharge.

CONCLUSIONS

The majority of children discharged home from a PACH do not require an acute care hospitalization within the first 3 months. Children with greater medical severity are readmitted more often than others.

Effect of a Pediatric Prescription Medication Discharge Program on Reducing Hospital Readmission Rates

OBJECTIVES

To evaluate the pediatric prescription medication discharge delivery and counseling program, implemented at an 186-bed children's hospital integrated within a larger academic medical center, and its effectiveness on reducing hospital readmissions.

METHODS

This study was a retrospective chart review of existing data in the electronic medical record from patients <21 years of age who were discharged from our institution between September 1, 2014, and November 30, 2014. Patients who participated in the pediatric discharge program were compared to non-participants. The primary objective was to determine if the patient was readmitted within 30 days. Secondary objectives included time until readmission, diagnosis at discharge, and hospital unit at discharge.

RESULTS

In total, 1804 patients were assessed. After exclusions, 932 subjects were included in the analysis. In total, 393 (42.2%) patients participated in the pediatric medication discharge and counseling program, and 539 did not participate. Of the patients who participated in the program, 52 were readmitted within 30 days (13.2%), compared with 67 patients (12.4%) who did not participate in the discharge program, p = 0.717. Patients with the diagnoses of malignancy and kidney injury were more likely to be readmitted within this time frame, and those with the diagnoses of heart defects or cardiology disorders and malignancy were more likely to participate in the pediatric prescription medication discharge program.

CONCLUSION

Participation in the pediatric discharge medication delivery and counseling program did not reduce hospital readmission rate within 30 days.

Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression

OBJECTIVES

Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions.

MATERIALS AND METHODS

The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy.

RESULTS

The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have similar performances reaching AUC values 0.783 and 0.779 for traditional Lasso and Tree-Lasso, respectfully. However, information loss of Lasso models is 0.35 bits higher compared to Tree-Lasso model.

CONCLUSIONS

We propose a method for building predictive models applicable for the detection of readmission risk based on Electronic Health records. Integration of domain knowledge (in the form of ICD-9-CM taxonomy) and a data-driven, sparse predictive algorithm (Tree-Lasso Logistic Regression) resulted in an increase of interpretability of the resulting model. The models are interpreted for the readmission prediction problem in general pediatric population in California, as well as several important subpopulations, and the interpretations of models comply with existing medical understanding of pediatric readmission. Finally, quantitative assessment of the interpretability of the models is given, that is beyond simple counts of selected low-level features.

Development and Initial Psychometric Evaluation of the Post-Acute Acuity Rating for Children

The Post-Acute Acuity Rating for Children (PAARC) is the first known acuity rating intended to reflect medical severity based on age, reason for admission, diagnoses, dependence in activities of daily living, and technology reliance for children admitted to post-acute care rehabilitation hospitals. Content validity was tested using an expert panel scoring the Content Validity Index (CVI). Concurrent validity was examined using clinician's opinion of acuity at admission, the Complexity Index, and All Patient Refined Diagnosis Related Group (APR-DRG) codes. Predictive validity was examined with acute care readmission within 30 days. Interrater reliability was assessed using admission histories from closed cases. Content validity was established and concurrent validity was moderate to high with clinician opinion (rho = .76, p < .001), the Complexity Index (rho = .76, p < .001), and APR-DRGs (rho = .349, p = .001). Predictive validity was moderate (rho = .504, p = .005) and returns to acute care within 30 days. Interrater reliability was excellent (ICC = 0.97; 95% CI = 0.92–0.90, p < .001). Experts agreed that the PAARC's content is relevant, simple, and representative of the population. The PAARC measured well against indicators of medical complexity for pediatric outpatient care and medical record coding and was reliable between raters. This work supports proceeding with additional development and validity testing of the PAARC.

Pediatric Post-Acute Hospital Care: Striving for Identity and Value

The landscape of hospital care for children is changing. Hospital clinicians are challenged to provide high-quality care to 2 increasingly complex groups of children: (1) healthy children admitted for high-severity acute illnesses or injury and (2) children admitted with lifelong, and often disabling, chronic conditions. Hospitalizations for both of these groups are becoming more prevalent, lengthy, and costly. In many situations, these children need weeks, or sometimes months, to recover from their illness or injury, with a sustained intensity of daily caregiving needs throughout their recovery period. Pediatric post-acute hospital care is a little-known and underused option in pediatric health care that could substantially help these children stabilize in a less restrictive and less costly environment than acute care hospitals can provide. In this commentary, we (1) propose the need and place for pediatric post-acute care hospitals along the continuum of care, (2) discuss the characteristics of children currently cared for in pediatric post-acute care hospitals, (3) suggest research opportunities and challenges, and (4) present issues related to the cost and value of pediatric post-acute care hospitals.