Multicomponent Support Program for Secondary Prevention of Stroke Using Digital Health Technology: Co-Design Study With People Living With Stroke or Transient Ischemic Attack.

BACKGROUND: Few individuals (<2%) who experience a stroke or transient ischemic attack (TIA) participate in secondary prevention lifestyle programs. Novel approaches that leverage digital health technology may provide a viable alternative to traditional interventions that support secondary prevention in people living with stroke or TIA. To be successful, these strategies should focus on user needs and preferences and be acceptable to clinicians and people living with stroke or TIA. OBJECTIVE: This study aims to co-design, with people with lived experience of stroke or TIA (referred to as consumers) and clinicians, a multicomponent digital technology support program for secondary prevention of stroke. METHODS: A consumer user needs survey (108 items) was distributed through the Australian Stroke Clinical Registry and the Stroke Association of Victoria. An invitation to a user needs survey (135 items) for clinicians was circulated via web-based professional forums and national organizations (eg, the Stroke Telehealth Community of Practice Microsoft Teams Channel) and the authors' research networks using Twitter (subsequently rebranded X, X Corp) and LinkedIn (LinkedIn Corp). Following the surveys, 2 rounds of user experience workshops (design and usability testing workshops) were completed with representatives from each end user group (consumers and clinicians). Feedback gathered after each round informed the final design of the digital health program. RESULTS: Overall, 112 consumers (male individuals: n=63, 56.3%) and 54 clinicians (female individuals: n=43, 80%) responded to the survey; all items were completed by 75.8% (n=85) of consumers and 78% (n=42) of clinicians. Most clinicians (46/49, 94%) indicated the importance of monitoring health and lifestyle measures more frequently than current practice, particularly physical activity, weight, and sleep. Most consumers (87/96, 90%) and clinicians (41/49, 84%) agreed that providing alerts about potential deterioration in an individual's condition were important functions for a digital program. Intention to use a digital program for stroke prevention and discussing the data collected during face-to-face consultations was high (consumers: 79/99, 80%; clinicians 36/42, 86%). In addition, 7 consumers (male individuals: n=5, 71%) and 9 clinicians (female individuals: n=6, 67%) took part in the user experience workshops. Participants endorsed using a digital health program to help consumers manage stroke or TIA and discussed preferred functions and health measures in a digital solution for secondary prevention of stroke. They also noted the need for a mobile app that is easy to use. Clinician feedback highlighted the need for a customizable clinician portal that captures individual consumer goals. CONCLUSIONS: Following an iterative co-design process, supported by evidence from user needs surveys and user experience workshops, a consumer-facing app that integrates wearable activity trackers and a clinician web portal were designed and developed to support secondary prevention of stroke. Feasibility testing is currently in progress to assess acceptability and use.

Timing and Causes of Common Pediatric Readmissions.

OBJECTIVE: To evaluate and compare readmission causes and timing within the first 30 days after hospitalization for 3 acute and 3 chronic common pediatric conditions. STUDY DESIGN: Data from the 2013 to 2014 Nationwide Readmissions Database were used to examine the daily percentage of readmissions occurring on days 1-30 and the leading causes of readmission after hospitalization for 3 acute (appendicitis, bronchiolitis/croup, and gastroenteritis) and 3 chronic (asthma, epilepsy, and sickle cell) conditions for patients aged 1-17 years (n = 2 753 488). Data were analyzed using Cox proportional hazards regression. RESULTS: The 30-day readmission rates ranged from 2.6% (SE, 0.1) after hospitalizations for appendectomy to 19.1% (SE, 0.5) after hospitalizations for sickle cell anemia. More than 50% of 30-day readmissions after acute conditions occurred within 15 days after discharge, whereas readmissions after chronic conditions occurred more uniformly throughout the 30 days after discharge. Higher numbers of patient comorbidities were associated with increased risk of readmission at days 1-7, 8-15, and 16-30 after discharge for all conditions examined. Most 30-day readmissions after chronic conditions were for the same diagnosis or closely related conditions as the index admission (67% for asthma, 65% for seizure disorder, and 82% for sickle cell anemia) in contrast with 50% or fewer readmissions after acute conditions (46% for appendectomy, 47% for bronchiolitis/croup, and 19% for gastroenteritis). CONCLUSIONS: The timing and causes of pediatric readmissions vary greatly across pediatric conditions. To be effective, strategies for reducing readmissions need to account for the index diagnosis to better target the highest risk period and causes for readmission.

Annual Variation in 30-Day Risk-Adjusted Readmission Rates in U.S. Children's Hospitals.

OBJECTIVE: Reducing pediatric readmissions has become a national priority; however, the use of readmission rates as a quality metric remains controversial. The goal of this study was to examine short-term stability and long-term changes in hospital readmission rates. METHODS: Data from the Pediatric Health Information System were used to compare annual 30-day risk-adjusted readmission rates (RARRs) in 47 US children's hospitals from 2016 to 2017 (short-term) and 2016 to 2019 (long-term). Pearson correlation coefficients and weighted Cohen's Kappa statistics were used to measure correlation and agreement across years for hospital-level RARRs and performance quartiles. RESULTS: Median (IQR) 30-day RARRs remained stable from 7.7% (7.0-8.3) in 2016 to 7.6% (7.0-8.1) in 2019. Individual hospital RARRs in 2016 were strongly correlated with the same hospital's 2017 rate (R2 = 0.89 [95% confidence interval (CI) 0.80-0.94]) and moderately correlated with those in 2019 (R2 = 0.49 [95%CI 0.23-0.68]). Short-term RARRs (2016 vs 2017) were more highly correlated for medical conditions than surgical conditions, but correlations between long-term medical and surgical RARRs (2016 vs 2019) were similar. Agreement between RARRs was higher when comparing short-term changes (0.73 [95%CI 0.59-0.86]) than long-term changes (0.45 [95%CI 0.27-0.63]). From 2016 to 2019, RARRs increased by ≥1% in 7 (15%) hospitals and decreased by ≥1% in 6 (13%) hospitals. Only 7 (15%) hospitals experienced reductions in RARRs over the short and long-term. CONCLUSIONS: Hospital-level performance on RARRs remained stable with high agreement over the short-term suggesting stability of readmission measures. There was little evidence of sustained improvement in hospital-level performance over multiple years.

The Association of the Childhood Opportunity Index on Pediatric Readmissions and Emergency Department Revisits.

OBJECTIVE: Reutilization following discharge is costly to families and the health care system. Singular measures of the social determinants of health (SDOH) have been shown to impact utilization; however, the SDOH are multifactorial. The Childhood Opportunity Index (COI) is a validated approach for comprehensive estimation of the SDOH. Using the COI, we aimed to describe the association between SDOH and 30-day revisit rates. METHODS: This retrospective study included children 0 to 17 years within 48 children's hospitals using the Pediatric Health Information System from 1/1/2019 to 12/31/2019. The main exposure was a child's ZIP code level COI. The primary outcome was unplanned readmissions and emergency department (ED) revisits within 30 days of discharge. Primary outcomes were summarized by COI category and compared using chi-square or Kruskal-Wallis tests. Adjusted analysis used generalized linear mixed effects models with adjustments for demographics, clinical characteristics, and hospital clustering. RESULTS: Of 728,997 hospitalizations meeting inclusion criteria, 30-day unplanned returns occurred for 96,007 children (13.2%). After adjustment, the patterns of returns were significantly associated with COI. For example, 30-day returns occurred for 19.1% (95% confidence interval [CI]: 18.2, 20.0) of children living within very low opportunity areas, with a gradient-like decrease as opportunity increased (15.5%, 95% CI: 14.5, 16.5 for very high). The relative decrease in utilization as COI increased was more pronounced for ED revisits. CONCLUSIONS: Children living in low opportunity areas had greater 30-day readmissions and ED revisits. Our results suggest that a broader approach, including policy and system-level change, is needed to effectively reduce readmissions and ED revisits.

Safety Events in Children's Hospitals During the COVID-19 Pandemic.

BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has impacted hospitals, potentially affecting quality and safety. Our objective was to compare pediatric hospitalization safety events during the pandemic versus previous years. METHODS: In this retrospective cohort study of hospitalizations in the Pediatric Health Information System, we compared Pediatric Quality Indicator (PDI) rates from March 15 to May 31, 2017-2019 (pre-COVID-19), with those from March 15 to May 31, 2020 (during COVID-19). Generalized linear mixed-effects models with adjustment for patient characteristics (eg, diagnosis, clinical severity) were used. RESULTS: There were 399 113 discharges pre-COVID-19 and 88 140 during COVID-19. Unadjusted PDI rates were higher during versus pre-COVID-19 for overall PDIs (6.39 vs 5.05; P < .001). In adjusted analyses, odds of postoperative sepsis were higher during COVID-19 versus pre-COVID-19 (adjusted odds ratio 1.28 [95% confidence interval 1.04-1.56]). The remainder of the PDIs did not have increased adjusted odds during compared with pre-COVID-19. CONCLUSIONS: Postoperative sepsis rates increased among children hospitalized during COVID-19. Efforts are needed to improve safety of postoperative care for hospitalized children.

Hospital Observation Status and Readmission Rates.

BACKGROUND: In several states, payers penalize hospitals when an inpatient readmission follows an inpatient stay. Observation stays are typically excluded from readmission calculations. Previous studies suggest inconsistent use of observation designations across hospitals. We sought to describe variation in observation stays and examine the impact of inclusion of observation stays on readmission metrics. METHODS: We conducted a retrospective cohort study of hospitalizations at 50 hospitals contributing to the Pediatric Health Information System database from January 1, 2018, to December 31, 2018. We examined prevalence of observation use across hospitals and described changes to inpatient readmission rates with higher observation use. We described 30-day inpatient-only readmission rates and ranked hospitals against peer institutions. Finally, we included observation encounters into the calculation of readmission rates and evaluated hospitals' change in readmission ranking. RESULTS: Most hospitals (n = 44; 88%) used observation status, with high variation in use across hospitals (0%-53%). Readmission rate after index inpatient stay (6.8%) was higher than readmission after an index observation stay (4.4%), and higher observation use by hospital was associated with higher inpatient-only readmission rates. When compared with peers, hospital readmission rank changed with observation inclusion (60% moving at least 1 quintile). CONCLUSIONS: The use of observation status is variable among children's hospitals. Hospitals that more liberally apply observation status perform worse on the current inpatient-to-inpatient readmission metric, and inclusion of observation stays in the calculation of readmission rates significantly affected hospital performance compared with peer institutions. Consideration should be given to include all admission types for readmission rate calculation.

Development of Hospitalization Resource Intensity Scores for Kids (H-RISK) and Comparison across Pediatric Populations.

BACKGROUND: In the Medicare population, measures of relative severity of illness (SOI) for hospitalized patents have been used in prospective payment models. Similar measures for pediatric populations have not been fully developed. OBJECTIVE: To develop hospitalization resource intensity scores for kids (H-RISK) using pediatric relative weights (RWs) for SOI and to compare hospital types on case-mix index (CMI). DESIGN/METHODS: Using the 2012 Kids' Inpatient Database (KID), we developed RWs for each All Patient Refined Diagnosis Related Group (APR-DRG) and SOI level. RW corresponded to the ratio of the adjusted mean cost for discharges in an APR-DRG SOI combination over adjusted mean cost of all discharges in the dataset. RWs were applied to every discharge from 3,117 hospitals in the database with at least 20 discharges. RWs were then averaged at the hospital level to provide each hospital's CMI. CMIs were compared by hospital type using Kruskal- Wallis tests. RESULTS: The overall adjusted mean cost of weighted discharges in Healthcare Cost and Utilization Project KID 2012 was $6,135 per discharge. Solid organ and bone marrow transplantations represented 4 of the 10 highest procedural RWs (range: 35.5 to 91.7). Neonatal APRDRG SOIs accounted for 8 of the 10 highest medical RWs (range: 19.0 to 32.5). Free-standing children's hospitals yielded the highest median (interquartile range [IQR]) CMI (2.7 [2.2-3.1]), followed by urban teaching hospitals (1.8 [1.3-2.6]), urban nonteaching hospitals (1.1 [0.9-1.5]), and rural hospitals (0.8 [0.7-0.9]; P < .001). CONCLUSIONS: H-RISK for populations of pediatric admissions are sensitive to detection of substantial differences in SOI by hospital type.

Extra-articular distal-third diaphyseal fractures of the humerus. A comparison of functional bracing and plate fixation.

BACKGROUND: There are strong advocates for both operative and nonoperative treatment of distal-third diaphyseal fractures of the humerus, but there are few comparative data. We performed a retrospective comparison of these two treatment methods. METHODS: Fifty-one consecutive patients with a closed, extra-articular fracture of the distal one-third of the humeral diaphysis were identified from an orthopaedic trauma database. Forty patients were followed for at least six months or until healing of the fracture. Eleven patients were excluded because of inadequate follow-up. Nineteen patients had been managed with plate-and-screw fixation, and twenty-one had been managed with functional bracing. RESULTS: Among the operatively treated patients, one had loss of fixation, one had a postoperative infection, and one required tendon transfers for the treatment of a preoperative radial nerve palsy that did not resolve. Three new postoperative radial nerve palsies developed, and one had not resolved when the patient was last evaluated, three months after surgery. All operatively treated fractures healed with <10 degrees of angular deformity, and one patient lost 20 degrees of shoulder or elbow motion. Among the nonoperatively treated fractures, two were converted to plate fixation because of the treating surgeons' concern regarding alignment and radial nerve palsy. Only one patient had >30 degrees of malalignment in any plane. Two patients had development of skin breakdown during treatment and completed treatment in a sling. Two patients lost >/=20 degrees of elbow or shoulder motion. CONCLUSIONS: For extra-articular distal-third diaphyseal humeral fractures, operative treatment achieves more predictable alignment and potentially quicker return of function but risks iatrogenic nerve injury and infection and the need for reoperation. Functional bracing can be associated with skin problems and varying degrees of angular deformity, but function and range of motion are usually excellent.

Noninvasive measurement of compartment syndrome.

This study compared the effectiveness of a commercially available invasive intracompartmental pressure measuring device with an investigational noninvasive hardness measuring device in 75 patients undergoing examination for possible compartment syndrome. Legs, forearms, thighs, and arms were tested. Pressure values and hardness ratios were compared to one another as continuous variables and to the clinical diagnosis of compartment syndrome as discrete variables. The compartment with the highest pressure reading within a limb diagnosed with compartment syndrome was compared to limbs without compartment syndrome. Due to the low specificity of the noninvasive measurement of hardness compared to the invasive pressure measurement (0.82 versus 0.96), this study does not support the use of the hardness monitor in the diagnosis of compartment syndrome.