Progress (?) Toward Reducing Pediatric Readmissions.

Many children's hospitals are actively working to reduce readmissions to improve care and avoid financial penalties. We sought to determine if pediatric readmission rates have changed over time. We used data from 66 hospitals in the Inpatient Essentials Database including index hospitalizations from January, 2010 through June, 2016. Seven-day all cause (AC) and potentially preventable readmission (PPR) rates were calculated using 3M PPR software. Total and condition-specific quarterly AC and PPR rates were generated for each hospital and in aggregate. We included 4.52 million hospitalizations across all study years. Readmission rates did not vary over the study period. The median seven-day PPR rate across all quarters was 2.5% (range 2.1%-2.5%); the median seven-day AC rate across all quarters was 5.1% (range 4.3%-5.3%). Readmission rates for individual conditions fluctuated. Despite significant national efforts to reduce pediatric readmissions, both AC and PPR readmission rates have remained unchanged over six years.

Children's Hospital Characteristics and Readmission Metrics.

BACKGROUND AND OBJECTIVE: Like their adult counterparts, pediatric hospitals are increasingly at risk for financial penalties based on readmissions. Limited information is available on how the composition of a hospital's patient population affects performance on this metric and hence affects reimbursement for hospitals providing pediatric care. We sought to determine whether applying different readmission metrics differentially affects hospital performance based on the characteristics of patients a hospital serves. METHODS: We performed a cross-sectional analysis of 64 children's hospitals from the Children's Hospital Association Case Mix Comparative Database 2012 and 2013. We calculated 30-day observed-to-expected readmission ratios by using both all-cause (AC) and Potentially Preventable Readmissions (PPR) metrics. We examined the association between observed-to-expected rates and hospital characteristics by using multivariable linear regression. RESULTS: We examined a total of 1 416 716 hospitalizations. The mean AC 30-day readmission rate was 11.3% (range 4.3%-19.6%); the mean PPR rate was 4.9% (range 2.9%-6.9%). The average 30-day AC observed-to-expected ratio was 0.96 (range 0.63-1.23), compared with 0.95 (range 0.65-1.23) for PPR; 59% of hospitals performed better than expected on both measures. Hospitals with higher volumes, lower percentages of infants, and higher percentage of patients with low income performed worse than expected on PPR. CONCLUSIONS: High-volume hospitals, those that serve fewer infants, and those with a high percentage of patients from low-income neighborhoods have higher than expected PPR rates and are at higher risk of reimbursement penalties.

Feasibility of using a pediatric call center as part of a quality improvement effort to prevent hospital readmission.

The primary aim of this intervention was to assess the feasibility of using call center nurses who are experts in telephone triage to conduct post discharge telephone calls, as part of a quality improvement effort to prevent hospital readmission. Families of patients with bronchiolitis were called between 24 and 48 hours after discharge. The calls conducted by the nurses were efficient (average time was 12 minutes), and their assessments helped to identify gaps in inpatient family education. Overall, the project demonstrated the efficacy in readmission prevention by using nurses who staff a call center to conduct post-hospitalization telephone calls.

Rates and impact of potentially preventable readmissions at children's hospitals.

OBJECTIVE: To assess readmission rates identified by 3M-Potentially Preventable Readmissions software (3M-PPRs) in a national cohort of children's hospitals. STUDY DESIGN: A total of 1 719 617 hospitalizations for 1 531 828 unique patients in 58 children's hospitals from 2009 to 2011 from the Children's Hospital Association Case-Mix Comparative database were examined. Main outcome measures included rates, diagnoses, and costs of potentially preventable readmissions (PPRs) and all-cause readmissions. RESULTS: The 7-, 15-, and 30-day rates by 3M-PPRs were 2.5%, 4.1%, and 6.2%, respectively. Corresponding all-cause readmission rates were 5.0%, 8.7%, and 13.3%. At 30 days, 60.6% of all-cause readmissions were considered nonpreventable by 3M-PPRs, more than one-half of which were related to malignancies. The percentage of readmissions rated as potentially preventable was similar at all 3 time intervals. Readmissions after chemotherapy, acute leukemia, and cystic fibrosis were all considered nonpreventable, and at least 80% of readmissions after index admissions for sickle cell crisis, bronchiolitis, ventricular shunt procedures, asthma, and appendectomy were designated potentially preventable. Total costs for all readmissions were $1.7 billion; PPRs accounted for 27.3% of these costs. The most costly readmissions were associated with ventricular shunt procedures ($26.5 million/year), seizures ($15.5 million/year), and sickle cell crisis ($15.0 million/year). CONCLUSIONS: Rates of PPRs were significantly lower than all-cause readmission rates more than one-half of which were caused by exclusion of malignancies. Annual costs of PPRs, although significant in the aggregate, appear to represent a much smaller cost-savings opportunity for children than for adults. Our study may help guide children's hospitals to focus readmission reduction strategies on areas where the financial vulnerability is greatest based on 3M-PPRs.

PEDSnet: a National Pediatric Learning Health System.

A learning health system (LHS) integrates research done in routine care settings, structured data capture during every encounter, and quality improvement processes to rapidly implement advances in new knowledge, all with active and meaningful patient participation. While disease-specific pediatric LHSs have shown tremendous impact on improved clinical outcomes, a national digital architecture to rapidly implement LHSs across multiple pediatric conditions does not exist. PEDSnet is a clinical data research network that provides the infrastructure to support a national pediatric LHS. A consortium consisting of PEDSnet, which includes eight academic medical centers, two existing disease-specific pediatric networks, and two national data partners form the initial partners in the National Pediatric Learning Health System (NPLHS). PEDSnet is implementing a flexible dual data architecture that incorporates two widely used data models and national terminology standards to support multi-institutional data integration, cohort discovery, and advanced analytics that enable rapid learning.

Resource utilization for observation-status stays at children's hospitals.

BACKGROUND AND OBJECTIVE: Observation status, in contrast to inpatient status, is a billing designation for hospital payment. Observation-status stays are presumed to be shorter and less resource-intensive, but utilization for pediatric observation-status stays has not been studied. The goal of this study was to describe resource utilization characteristics for patients in observation and inpatient status in a national cohort of hospitalized children in the Pediatric Health Information System. METHODS: This study was a retrospective cohort from 2010 of observation- and inpatient-status stays of ≤2 days; all children were admitted from the emergency department. Costs were analyzed and described. Comparison between costs adjusting for age, severity, and length of stay were conducted by using random-effect mixed models to account for clustering of patients within hospitals. RESULTS: Observation status was assigned to 67 230 (33.3%) discharges, but its use varied across hospitals (2%-45%). Observation-status stays had total median costs of $2559, including room costs and $678 excluding room costs. Twenty-five diagnoses accounted for 74% of stays in observation status, 4 of which were used for detailed analyses: asthma (n = 6352), viral gastroenteritis (n = 4043), bronchiolitis (n = 3537), and seizure (n = 3289). On average, after risk adjustment, observation-status stays cost $260 less than inpatient-status stays for these select 4 diagnoses. Large overlaps in costs were demonstrated for both types of stay. CONCLUSIONS: Variability in use of observation status with large overlap in costs and potential lower reimbursement compared with inpatient status calls into question the utility of segmenting patients according to billing status and highlights a financial risk for institutions with a high volume of pediatric patients in observation status.

Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity.

Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names. The combined model was used to rank the patient population for medical complexity. As a result, simple, objective admission screens for predicting the complexity of patients based on the number and type of medications were implemented.

Implementation of filmarray respiratory viral panel in a core laboratory improves testing turnaround time and patient care.

The FilmArray respiratory virus panel detects 15 viral agents in respiratory specimens using polymerase chain reaction. We performed FilmArray respiratory viral testing in a core laboratory at a regional children's hospital that provides service 24 hours a day 7 days a week. The average and median turnaround time were 1.6 and 1.4 hours, respectively, in contrast to 7 and 6.5 hours documented 1 year previously at an on-site reference laboratory using a direct fluorescence assay (DFA) that detected 8 viral agents. During the study period, rhinovirus was detected in 20% and coronavirus in 6% of samples using FilmArray; these viruses would not have been detected with DFA. We followed 97 patients with influenza A or influenza B who received care at the emergency department (ED). Overall, 79 patients (81%) were given oseltamivir in a timely manner defined as receiving the drug in the ED, a prescription in the ED, or a prescription within 3 hours of ED discharge. Our results demonstrate that molecular technology can be successfully deployed in a nonspecialty, high-volume, multidisciplinary core laboratory.

Standards for health information technology to ensure adolescent privacy.

Privacy and security of health information is a basic expectation of patients. Despite the existence of federal and state laws safeguarding the privacy of health information, health information systems currently lack the capability to allow for protection of this information for minors. This policy statement reviews the challenges to privacy for adolescents posed by commercial health information technology systems and recommends basic principles for ideal electronic health record systems. This policy statement has been endorsed by the Society for Adolescent Health and Medicine.

Pediatric observation status: are we overlooking a growing population in children's hospitals?

BACKGROUND: Inpatient administrative datasets often exclude observation stays, as observation is considered to be outpatient care. The extent to which this status is applied to pediatric hospitalizations is not known. OBJECTIVE: To characterize trends in observation status code utilization and 1-day stays among children admitted from the emergency department (ED), and to compare patient characteristics and outcomes associated with observation versus inpatient stays. DESIGN: Retrospective longitudinal analysis of the 2004-2009 Pediatric Health Information System (PHIS). SETTING: Sixteen US freestanding children's hospitals contributing outpatient and inpatient data to PHIS. PATIENTS: Admissions to observation or inpatient status following ED care in study hospitals. MEASUREMENTS: Proportions of observation and 1-day stays among all admissions from the ED were calculated each year. Top ranking discharge diagnoses and outcomes of observation were determined. Patient characteristics, discharge diagnoses, and return visits were compared for observation and 1-day stays. RESULTS: The proportion of short-stays (including both observation and 1-day stays) increased from 37% to 41% between 2004 and 2009. Since 2007, observation stays have outnumbered 1-day stays. In 2009, more than half of admissions from the ED for 6 of the top 10 ranking discharge diagnoses were short-stays. Fewer than 25% of observation stays converted to inpatient status. Return visits and readmissions following observation were no more frequent than following 1-day stays. CONCLUSIONS: Children admitted under observation status make up a substantial proportion of acute care hospitalizations. Analyses of inpatient administrative databases that exclude observation stays likely result in an underestimation of hospital resource utilization for children.

Differences in designations of observation care in US freestanding children's hospitals: are they virtual or real?

OBJECTIVE: To characterize practices related to observation care and to examine the current models of pediatric observation medicine in US children's hospitals. DESIGN: We utilized 2 web-based surveys to examine observation care in the 42 hospitals participating in the Pediatric Health Information System database. We obtained information regarding the designation of observation status, including the criteria used to admit patients into observation. From hospitals reporting the use of observation status, we requested specific details relating to the structures of observation care and the processes of care for observation patients following emergency department treatment. RESULTS: A total of 37 hospitals responded to Survey 1, and 20 hospitals responded to Survey 2. Designated observation units were present in only 12 of 31 (39%) hospitals that report observation patient data to the Pediatric Health Information System. Observation status was variably defined in terms of duration of treatment and prespecified criteria. Observation periods were limited to <48 hours in 24 of 31 (77%) hospitals. Hospitals reported that various standards were used by different payers to determine observation status reimbursement. Observation care was delivered in a variety of settings. Most hospitals indicated that there were no differences in the clinical care delivered to virtual observation status patients when compared with other inpatients. CONCLUSIONS: Observation is a variably applied patient status, defined differently by individual hospitals. Consistency in the designation of patients under observation status among hospitals and payers may be necessary to compare quality outcomes and costs, as well as optimize models of pediatric observation care.

Development and order set utilization in ambulatory pediatric specialty care.

One of the keys to any successful CPOE implementation is the development, deployment, and maintenance of well designed order sets that promote evidence based best practice. At Seattle Children's we implemented ambulatory CPOE in multiple subspecialty pediatric clinics. Using our previous experience with inpatient CPOE, we translated our order set process to the ambulatory setting, making sure to understand the unique features of ambulatory subspecialty practice.

Polymerase chain reaction diagnosis of primary human herpesvirus-6 infection in the acute care setting.

OBJECTIVE: To evaluate the potential utility of identifying primary human herpesvirus (HHV)-6 infection in an emergency department setting by determining the frequency of HHV-6 viremia, diagnostic testing, and empiric treatment of serious bacterial infection (SBI) in HHV-6 viremic children, and concurrent SBI and HHV-6 viremia. STUDY DESIGN: Children under age 2 years and who had a blood specimen taken for evaluation of fever were tested for HHV-6 by polymerase chain reaction (PCR). HHV-6 viremia was defined as detection of HHV-6 DNA in acute plasma. RESULTS: A total of 32 of the 181 subjects (18%) had HHV-6 viremia. Children with HHV-6 viremia frequently underwent procedures for diagnosis and empiric treatment of SBI: 60% had bladder catheterizations, 6% had lumbar punctures, 47% had radiographs, 32% received empiric antibiotics, and 34% were hospitalized. Four of the 32 children with HHV-6 viremia (12.5%) were diagnosed with SBI, although none had a positive culture of blood or cerebrospinal fluid. CONCLUSIONS: Rapid diagnosis of HHV-6 viremia may not serve to adequately differentiate infants with and without SBI in acute care settings. Although no children with HHV-6 viremia had bacteremia or meningitis, it appears that additional criteria are needed to increase the specificity of HHV-6 PCR testing before withholding evaluation for SBI.

Computerized provider order entry implementation: no association with increased mortality rates in an intensive care unit.

OBJECTIVE: Our goal was to determine if there were any changes in risk-adjusted mortality after the implementation of a computerized provider order entry system in our PICU. METHODS: Study was undertaken in a tertiary care PICU with 20 beds and 1100 annual admissions. Demographic, admission source, primary diagnosis, crude mortality, and Pediatric Risk of Mortality III risk-adjusted mortality were abstracted retrospectively on all admissions from the PICUEs database for the period October 1, 2002, to December 31, 2004. This time period reflects the 13 months before and 13 months after computerized provider order entry implementation. Pediatric Risk of Mortality III mortality risk adjustment was used to determine standardized mortality ratios. RESULTS: During the study period, 2533 patients were admitted to the PICU, of which 284 were transported from another facility. The 13-month preimplementation mortality rate was 4.22%, and the 13-month postimplementation mortality rate was 3.46%, representing a nonsignificant reduction in the risk of mortality in the postimplementation period. The standardized mortality ratio was 0.98 vs 0.77, respectively, and the mortality rate for the transported patients was 9.6% vs 6.29%. This yields a nonsignificant mortality risk reduction in the postimplementation period. The standardized mortality ratio was 1.10 preimplementation versus 0.70 postimplementation. Analysis of the 13-month preimplementation versus 5-month postimplementation periods showed a non-statistically significant trend in reduction of mortality for all PICU patients and for transported patients. CONCLUSIONS: Implementation of a computerized provider order entry system, even in the early months after implementation, was not associated with an increase in mortality. Our experience suggests that careful design, build, implementation, and support can mitigate the risk of implementing new technology even in an ICU setting.

Nonfebrile illness seizures: a unique seizure category?

PURPOSE: To describe the clinical characteristics of children with a first-time nonfebrile seizure in the setting of mild illness and to test the hypothesis that these seizures are associated with illness characterized by diarrhea. METHODS: This retrospective cohort study was performed in a pediatric emergency department. Patients ages 6 months to 6 years who were evaluated with first-time seizures were eligible for inclusion. Subjects were divided into three groups on the basis of symptoms accompanying their seizure: febrile (temperature, >38.0 degrees C with seizure), unprovoked (no symptoms of illness), and nonfebrile illness (no fever at the time of seizure, but other symptoms of illness present). RESULTS: Of the 323 children with first-time seizures, 247 (76%) had febrile seizure, 37 (12%) had unprovoked seizures, and 39 (12%) had nonfebrile illness seizures. Children with nonfebrile illness seizures were more likely than children with febrile seizures to have diarrheal illnesses accompanying their seizure (44 vs. 16%; p=0.001). Frequency of cough, rhinorrhea, and rash did not differ significantly between children with febrile and nonfebrile illness seizures. Diagnostic testing for infectious etiologies was not performed frequently in either group. CONCLUSIONS: Nonfebrile illness seizures may represent a distinct group of seizures with unique epidemiology. Further study to define this seizure group better is warranted.

Postobstructive pulmonary edema in children.

Children with either acute or chronic upper airway obstruction are at risk for postobstructive pulmonary edema. Appropriate diagnosis and management are important in leading to a good outcome for the patient. We describe 2 cases of postobstructive pulmonary edema caused by brief acute upper airway obstruction. In the first case, a child choked on a hot dog and in the second on a "jawbreaker." Both children developed symptoms of complete upper airway obstruction and were managed initially with the Heimlich maneuver and subsequently developed increased work of breathing associated with an oxygen requirement after relief of the obstruction. Both children were managed in the pediatric intensive care unit and were discharged after resolution of symptoms without sequelae.

A comparison of time to positive culture and time to clinical identification of serious bacterial infection in infants.

To compare the time to positive culture with the time to clinical detection of serious bacterial infection (SBI) in young infants, a retrospective case series of 949 infants age 0-60 days, who had a body fluid cultured in the emergency department or within 24 hours of admission was analyzed. Times to first report of positive culture and first clinical diagnosis of SBI were compared. Of 44 infants with positive cultures, 48% were clinically diagnosed with SBI at first evaluation. Of 21 infants with cultures reported positive after 24 hours, 14 were already diagnosed with SBI. Infections that altered therapy were identified after 24 and 36 hours in 4 infants and 1 infant, respectively. In infants with SBIs, the time to positive culture is longer than the time to identification of infection.