Barriers and facilitators of CT scan reduction in the workup of pediatric appendicitis: A pediatric surgical quality collaborative qualitative study

INTRODUCTION

Despite ongoing efforts to decrease ionizing radiation exposure from computed tomography (CT) use in pediatric appendicitis, high CT utilization rates are still observed across many hospitals. This study aims to identify factors influencing CT use and facilitators and barriers to quality improvement efforts.

METHODS

The Pediatric Surgery Quality Collaborative is a voluntary consortium of 42 children's hospitals participating in the National Surgical Quality Improvement Project - Pediatric. Hospitals were compared based on CT utilization from January 1, 2019, to December 31, 2019. Semi-structured interviews were conducted with surgeons, radiologists, emergency medicine physicians, and clinical data abstractors from 7 hospitals with low CT use rates (high performers) and 6 hospitals with high CT use rates (low performers). A mixed deductive and inductive coding approach for analysis of the interview transcripts was used to develop a codebook based on the Theoretical Domains Framework and subsequently identify prominent barriers and facilitators to CT reduction.

RESULTS

Thematic saturation was achieved after 13 interviews. We identified four factors that distinguish high-performing from low-performing hospitals: (1) consistent availability of resources such as ultrasound technicians, pediatric radiologists, and magnetic resonance imaging (MRI); (2) presence of and adherence to protocols guiding imaging modality decision making and imaging execution; (3) culture of inter-departmental collaboration; and (4) presence of a radiation reduction champion.

CONCLUSIONS

Significant barriers to reducing the use of CT in pediatric appendicitis exist. Our findings highlight that future quality improvement efforts should target resource availability, protocol adherence, collaborative culture, and radiation reduction champions.

LEVELS OF EVIDENCE

Level III.

Novel Quality Improvement Targets to Address Healthcare Encounters After Pediatric Appendectomy

INTRODUCTION

Pediatric appendicitis clinical practice guidelines (CPGs) do not typically address postdischarge healthcare encounters. This study aims to examine common indications for returns to the health system to identify novel quality improvement targets.

METHODS

This retrospective cohort study analyzed patients aged 3 to 18 y undergoing appendectomy at a single institution from July 1, 2019, to July 31, 2020. The primary outcome was physical postdischarge encounters comprising emergency department (ED) visits and hospital readmissions. Indications for each encounter were categorized and stratified by appendicitis type (i.e., simple, gangrenous, or perforated). Multivariable logistic regression models were used to estimate association between appendicitis category and postdischarge encounters.

RESULTS

Of 434 patients, 240 (55.3%) had simple appendicitis, 77 (17.7%) gangrenous, and 117 (29.9%) perforated appendicitis. Overall, 48 patients had at least one instance of an unplanned postdischarge encounter with a total of 56 unplanned ED presentations and 24 readmissions. Perforated patients were significantly more likely to experience postdischarge ED (odds ratio 2.55; 95% confidence interval 1.29-5.02) and readmission encounters (odds ratio 6.63; 95% confidence interval 2.28-19.28). Common indications for ED encounters included abdominal pain (n = 20) with 25.0% readmitted, abdominal pain and gastrointestinal symptoms (e.g., diarrhea, vomiting, distention) (n = 16) with 87.5% readmitted, and incision concerns (n = 6) with 16.7% readmitted. Common indications for readmissions included intraabdominal abscesses (n = 8) and small bowel obstruction (n = 4).

CONCLUSIONS

Assessing indications for postdischarge healthcare encounters enables identification of novel quality improvement targets, including proactively addressing incision concerns and abdominal pain.

Latin America and the Caribbean SARS-CoV-2 Surveillance: Longitudinal Trend Analysis

Background

The COVID-19 pandemic has placed unprecedented stress on economies, food systems, and health care resources in Latin America and the Caribbean (LAC). Existing surveillance provides a proxy of the COVID-19 caseload and mortalities; however, these measures make it difficult to identify the dynamics of the pandemic and places where outbreaks are likely to occur. Moreover, existing surveillance techniques have failed to measure the dynamics of the pandemic.

Objective

This study aimed to provide additional surveillance metrics for COVID-19 transmission to track changes in the speed, acceleration, jerk, and persistence in the transmission of the pandemic more accurately than existing metrics.

Methods

Through a longitudinal trend analysis, we extracted COVID-19 data over 45 days from public health registries. We used an empirical difference equation to monitor the daily number of cases in the LAC as a function of the prior number of cases, the level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano–Bond estimator in R. COVID-19 transmission rates were tracked for the LAC between September 30 and October 6, 2020, and between October 7 and 13, 2020.

Results

The LAC saw a reduction in the speed, acceleration, and jerk for the week of October 13, 2020, compared to the week of October 6, 2020, accompanied by reductions in new cases and the 7-day moving average. For the week of October 6, 2020, Belize reported the highest acceleration and jerk, at 1.7 and 1.8, respectively, which is particularly concerning, given its high mortality rate. The Bahamas also had a high acceleration at 1.5. In total, 11 countries had a positive acceleration during the week of October 6, 2020, whereas only 6 countries had a positive acceleration for the week of October 13, 2020. The TAC displayed an overall positive trend, with a speed of 10.40, acceleration of 0.27, and jerk of –0.31, all of which decreased in the subsequent week to 9.04, –0.81, and –0.03, respectively.

Conclusions

Metrics such as new cases, cumulative cases, deaths, and 7-day moving averages provide a static view of the pandemic but fail to identify where and the speed at which SARS-CoV-2 infects new individuals, the rate of acceleration or deceleration of the pandemic, and weekly comparison of the rate of acceleration of the pandemic indicate impending explosive growth or control of the pandemic. Enhanced surveillance will inform policymakers and leaders in the LAC about COVID-19 outbreaks.

Surveillance Metrics of SARS-CoV-2 Transmission in Central Asia: Longitudinal Trend Analysis

BACKGROUND

SARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19.

OBJECTIVE

The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully.

METHODS

Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19-related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.

RESULTS

COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight.

CONCLUSIONS

The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.