Preventive medicine
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Preventive medicine · Oct 2022
US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic.
The COVID-19 pandemic has led to unemployment, school closures, movement restrictions, and social isolation, all of which are child abuse risk factors. Our objective was to estimate the effect of COVID-19 shelter in place (SIP) policies on child abuse as captured by Google searches. We applied a differences-in-differences design to estimate the effect of SIP on child abuse search volume. ⋯ We did not find strong evidence for an effect of SIP on child abuse searches. However, an increase in total search volume during the pandemic that may be differential between states with and without SIP policies could have biased these findings. Future work should examine the effect of SIP at the individual and population level using other data sources.
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Preventive medicine · Oct 2022
What explains racial/ethnic inequities in the uptake of differentiated influenza vaccines?
We investigated the role of individual, community and vaccinator characteristics in mediating racial/ethnic disparities in the uptake of differentiated influenza vaccines (DIVs; including high-dose, adjuvanted, recombinant and cell-based vaccines). We included privately-insured (commercial and Medicare Advantage) ≥65 years-old community-dwelling health plan beneficiaries in the US with >1 year of continuous coverage and who received ≥1 influenza vaccine during the study period (July 2014-June 2018). Of 2.8 million distinct vaccination claims, 60% were for DIVs; lower if received in physician offices (49%) compared to pharmacies/facilities (74%). ⋯ These disparities disappeared for whites, but not for non-whites, after controlling for community and vaccinator characteristics. We found an alarming level of inequity in DIV vaccine uptake among fully insured older adults that could not be fully explained by differences in sociodemographic, medical, community, and vaccinator characteristics. New strategies are urgently needed to address these inequities.
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Preventive medicine · Oct 2022
Assessing the effect of COVID-19 stay-at -home orders on firearm injury in Maryland.
This study sought to characterize frequency and demographic characteristics of firearm injury and penetrating trauma in Maryland over the first year of the pandemic, by comparing these characteristics to those of the three years prior to stay-at-home order issuance. Patients were identified in the Maryland Health Services Cost Review Commission database using ICD-10 codes for firearm injury by all intents and assaults by penetrating trauma. Cases from July 1, 2017 to March 31, 2020 ("pre-stay-at-home") were compared to those from April 1, 2020 to March 31, 2021 ("post-stay-at-home") using descriptive statistics. ⋯ While increased unintentional firearm injury among adults was the major significant change found in our study, the persistence of firearm injury, particularly in youth, racial and ethnic minority groups, and those in urban environments, should be deeply concerning. Stay-at-home policies did not keep youth safer from firearm injury. With continued high rates of firearm injury and the national debate over how to prevent these incidents, increased education and comprehensive strategies for prevention are needed.
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Preventive medicine · Oct 2022
Rural and urban disparities in potentially preventable hospitalizations among US patients with Alzheimer's Disease and Related Dementias: Evidence of hospital-based telehealth and enabling services.
We examined urban and rural disparities in potentially preventable hospitalizations (PPHs) among US patients with Alzheimer's Disease and Related Dementias (ADRD) and the use of telehealth post-discharge and enabling services as mediators. We merged 2017 100% Medicare Fee-For-Service (FFS) claims with the Medicare Beneficiary Summary File, along with population and hospital-based characteristics. Logistic regression models were employed to examine differences in PPHs by telehealth and enabling services. ⋯ Telehealth post-discharge combined with enabling services significantly decreased the odds of PPHs associated with acute (OR: 0.93, 95% CI: 0.89-0.98, P-value <0.01) and chronic conditions (OR: 0.96, 95% CI: 0.92-1.00, P-value = 0.07). In addition, telehealth post-discharge combined with enabling services significantly decreased the odds of PPHs in patients with ADRD in rural (acute PPHs OR: 0.56, 95% CI: 0.41-0.77, P-value <0.01; chronic PPHs OR: 0.73, 95% CI: 0.55-0.97, P-value = 0.03) and micropolitan (acute PPHs OR: 0.65, 95% CI: 0.57-0.73, P-value <0.01; chronic PPHs OR: 0.83, 95% CI: 0.74-0.93, P-value <0.01) areas. Our results suggest that the combinations of telehealth post-discharge and enabling services are important interventions in helping to reduce preventable hospitalizations among patients with ADRD living in rural and micropolitan areas.
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Preventive medicine · Oct 2022
Using multiple imputation by super learning to assign intent to nonfatal firearm injuries.
The number of nonfatal firearm injuries in the US by intent (e.g., due to assault) is not reliably known: First, although the largest surveillance system for hospital-treated events, the Healthcare Cost and Utilization Project Nationwide Emergency Department Sample (HCUP-NEDS), provides accurate data for the number of nonfatal firearm injuries, injury intent is not coded reliably. Second, the system that reliably codes intent, the CDC's National Electronic Injury Surveillance System - Firearm Injury Surveillance Study (NEISS-FISS), while large enough to produce stable estimates of the distribution of intent, is too small to produce stable estimates of the number of these events. Third, a large proportion of cases in NEISS-FISS, notably in early years of the system, are coded as of "undetermined intent." Trends in the proportion of nonfatal firearm injuries by intent in NEISS-FISS thus depend on whether these cases are treated as a distinct category, or, instead, can be re-classified through imputation. ⋯ Trends in the number of nonfatal firearm injuries by intent, 2006-2016, derived in our two-step process, are relatively flat. Multiple imputation strategies recovered intent distribution trends that differed from trends derived using methods that are not designed to account for the multiple complex relationships of missingness present in NEISS - FISS data. When applied to NEISS - FISS, MISL imputation produces plausible distributional estimates of firearm injury by intent.