Category: Statistics

Inflamm Bowel Dis. 2023 Aug 24:izad167. doi: 10.1093/ibd/izad167. Online ahead of print.

ABSTRACT

BACKGROUND: Exclusive enteral nutrition (EEN) is the recommended first-line induction treatment in pediatric patients with active luminal Crohn’s disease (CD). We aimed to provide a nationwide overview of evolving EEN practices during an era of increasing biologic use.

METHODS: We analyzed a prospectively identified nationwide cohort of newly diagnosed pediatric patients with CD in Scotland between January 1, 2015, and June 30, 2022. Patients who received EEN for any indication were divided into 6-monthly epochs and examined over time. Differences during the COVID-19 pandemic (March 16, 2020, to July 19, 2021) were examined. Data were retrospectively collected from electronic medical records: demographics, anthropometrics, concomitant treatments, aspects of EEN administration, and remission/response rates. Descriptive statistics and linear regression were used for analyses.

RESULTS: A total of 649 patients with CD were identified (63% male; median age 12.6 [interquartile range, 10.8-14.8] years); 497 (77%) of 649 received EEN as postdiagnosis induction therapy with a median course length of 7.7 (interquartile range, 5.9-8.0) weeks. Including repeat courses, 547 EEN courses were examined. An increasing incidence of CD was observed over time with no significant changes in EEN usage, remission or response rates, nasogastric tube usage, or course completion (all P > .05). Increasing use of EEN combined with biologics (combination induction) as first-line induction was observed over time (P < .001). Considering COVID-19, lower rates of EEN usage were observed (P = .008) with no differences in remission, oral administration, and course completion rates (all P > .05).

CONCLUSIONS: Over the past 7.5 years, except during the COVID-19 pandemic, EEN usage rates have not changed despite an increase in biologic use, although combination induction is an emerging trend.

PMID:37619221 | DOI:10.1093/ibd/izad167

Chic Med J Exam. 1878 Jun;36(6):613-618.

NO ABSTRACT

PMID:37617384 | PMC:PMC9839178

Chic Med J Exam. 1877 Oct;35(4):356-362.

NO ABSTRACT

PMID:37617112 | PMC:PMC9833746

Chic Med J Exam. 1875 Nov;32(11):878-879.

NO ABSTRACT

PMID:37616943 | PMC:PMC9829352

Environ Health Perspect. 2023 Aug;131(8):87018. doi: 10.1289/EHP11344. Epub 2023 Aug 24.

ABSTRACT

BACKGROUND: Concentrated animal feeding operations (CAFOs) emit pollutants that can cause negative impacts on human health. The concentration of hog production in North Carolina raises concerns regarding the disproportionate exposure of vulnerable communities to air pollution from CAFOs.

OBJECTIVES: We investigated whether exposure to gaseous ammonia (${\text{NH}}_3$) and hydrogen sulfide ($H_{2}S$) (in 2019) differs between subpopulations by examining demographics, including race/ethnicity, age, educational attainment, language proficiency, and socioeconomic status.

METHODS: We used an Air Monitoring Station (AMS)/Environmental Protection Agency (EPA) Regulatory Model (AERMOD)-based Human Exposure Model (version 3) to estimate ambient concentrations of ${\text{NH}}_3$ and $H_{2}S$ from hog farms in Duplin County and its surrounding counties in North Carolina and estimate subsequent exposures of communities within $50\mathrm{km}$ of Duplin County, North Carolina, or the Duplin County Region. We combined estimated exposures with 2016 American Community Summary Census data, at the block group level, using spatial analysis to investigate whether exposures to these pollutants differ by race and ethnicity, age, income, education, and language proficiency. Based on these estimations, we assessed associated exposure risks to the impacted communities and used multivariable regression modeling to evaluate the relationship between average ammonia exposures from Duplin regional hog farms and the presence of vulnerable populations.

RESULTS: The average [$\pm \text{standard deviation}\left(\text{SD}\right)$] annual estimated concentration of ${\text{NH}}_3$ and $H_{2}S$ in the Duplin County Region is $1.75\pm 2.81{\mu g/m}^3$ and $0.0087\pm 0.014{\mu g/m}^3$, respectively. The maximum average annual ambient concentrations are estimated at $54.27\pm 4.12{\mu g/m}^3$ and $0.54\pm 0.041{\mu g/m}^3$ for ${\text{NH}}_3$ and $H_{2}S$, respectively. Our descriptive analysis reveals that people of low income, people of color, people with low educational attainment, and the linguistically isolated in the Duplin Region are disproportionately exposed to higher levels of pollutants than the average exposure for residents. Alternatively, our statistical results suggests that after adjusting for covariates, communities of color are associated with 1.70% (95% CI: $–3.79$, 0.44) lower ${\text{NH}}_3$ concentrations per 1-SD increase. One-standard deviation increases in the adults with low educational attainment and children $<19$ years of age is associated with 1.26% (95% CI: $–0.77$, 3.33) and 1.20% (95% CI: $–0.62$, 3.05) higher ${\text{NH}}_3$ exposure per 1-SD increase, respectively.

DISCUSSION: Exposures to ${\text{NH}}_3$ and $H_{2}S$ differed by race and ethnicity, educational attainment, language proficiency, and socioeconomic status. The observed associations between exposure to CAFO-generated pollutants and sociodemographic indicators differed among demographics. The disproportionate distribution of hog facilities and resulting pollutant exposures among communities may have adverse environmental and human health impacts, raising environmental justice concerns. https://doi.org/10.1289/EHP11344.

PMID:37616159 | DOI:10.1289/EHP11344

Am J Manag Care. 2023 Aug 1;29(8):e229-e234. doi: 10.37765/ajmc.2023.89409.

ABSTRACT

OBJECTIVES: Readmission is common and costly for hospitalized Medicaid patients with diabetes. We aimed to develop a model predicting risk of 30-day readmission in Medicaid patients with diabetes hospitalized for any cause.

STUDY DESIGN: Using 2016-2019 Medicaid claims from 7 US states, we identified patients who (1) had a diagnosis of diabetes or were prescribed any diabetes drug, (2) were hospitalized for any cause, and (3) were discharged to home or to a nonhospice facility. For each encounter, we assessed whether the patient was readmitted within 30 days of discharge.

METHODS: Applying least absolute shrinkage and selection operator variable selection, we included demographic data and claims history in a logistic regression model to predict 30-day readmission. We evaluated model fit graphically and measured predictive accuracy by the area under the receiver operating characteristic curve (AUROC).

RESULTS: Among 69,640 eligible patients, there were 129,170 hospitalizations, of which 29,410 (22.8%) were 30-day readmissions. The final model included age, sex, age-sex interaction, past diagnoses, US state of admission, number of admissions in the preceding year, index admission type, index admission diagnosis, discharge status, length of stay, and length of stay-sex interaction. The observed vs predicted plot showed good fit. The estimated AUROC of 0.761 was robust in analyses that assessed sensitivity to a range of model assumptions.

CONCLUSIONS: Our model has moderate power for identifying hospitalized Medicaid patients with diabetes who are at high risk of readmission. It is a template for identifying patients at risk of readmission and for adjusting comparisons of 30-day readmission rates among sites or over time.

PMID:37616150 | DOI:10.37765/ajmc.2023.89409

Am J Manag Care. 2023 Aug;29(8):417-422. doi: 10.37765/ajmc.2023.89407.

ABSTRACT

OBJECTIVES: In 2015, CMS implemented reimbursement for non-face-to-face chronic care management (NFFCCM) for beneficiaries with multiple chronic conditions, including diabetes. This analysis estimated the association between NFFCCM and utilization of inpatient, outpatient, and emergency services.

STUDY DESIGN: We implemented a doubly robust estimator using propensity score matching in a regression context to compare eligible patients who used NFFCCM (n = 282) with eligible patients who did not use NFFCCM (n = 26,759).

METHODS: We tested 4 definitions of treatment: having any NFFCCM encounters and having 1 NFFCCM encounter per month, per 2 months, and per 3 months. Two-tailed statistical inference testing was conducted at the 5% level. We examined the utilization differences among patients with diabetes 65 years and older using merged electronic health records for 4 health systems in Louisiana from the Research Action for Health Network database in 2013 through 2018.

RESULTS: We found NFFCCM was associated with increased utilization of care in the outpatient setting by 0.056 visits per month (95% CI, 0.027-0.086) and with lower utilization in the inpatient setting (-0.024 visits per month; 95% CI, -0.038 to -0.010) and in the emergency department setting (-0.017 visits per month; 95% CI, -0.031 to -0.003). Alternative specifications of treatment showed similar associations.

CONCLUSIONS: CMS implementation of reimbursement codes for NFFCCM, and subsequent utilization of that reimbursement by health systems, was associated with a shift in patient utilization from high-cost settings (inpatient and emergency department) to a lower-cost setting (outpatient office).

PMID:37616148 | DOI:10.37765/ajmc.2023.89407

Am J Manag Care. 2023 Aug;29(8):395-401. doi: 10.37765/ajmc.2023.89405.

ABSTRACT

OBJECTIVES: Colorectal cancer (CRC) screening rates continue to be low among safety-net populations. We sought to elucidate the impact of social determinants of health (SDOH) on the noncompletion of fecal immunochemical tests (FITs) and colonoscopies at the Providence Community Health Centers (PCHC).

STUDY DESIGN: This was a retrospective cohort review of PCHC patients with associated SDOH profiles between December 1, 2018, and December 1, 2019.

METHODS: We analyzed fulfilled and unfulfilled CRC screening orders (FITs and colonoscopies) and examined associations and odds ratios between order noncompletion and the presence of SDOH variables. The study sample consisted of a total of 517 orders (fulfilled and unfulfilled; FIT, n = 348; colonoscopy, n = 169).

RESULTS: FITs were completed more often than colonoscopies (81.3% vs 65.7%, respectively; P < .001). Colonoscopy noncompletion was associated with patient-reported social determinants of “housing insecurity/homelessness” (P = .0083) and “living conditions” (P = .048) and staff-reported “behavioral health problem” (P = .048). The presence of housing insecurity/homelessness increased the likelihood of an unfulfilled colonoscopy order (odds ratio, 7.5; 95% CI, 1.3-75.0). Patients who reported any SDOH need had a statistically significant increase in colonoscopy noncompletion (P = .0022), whereas FIT noncompletion was not associated with the presence of SDOH needs (P = .81).

CONCLUSIONS: Providers should consider FITs as a strategic real-world modality for patients with SDOH needs.

PMID:37616146 | DOI:10.37765/ajmc.2023.89405

Euro Surveill. 2023 Aug;28(34). doi: 10.2807/1560-7917.ES.2023.28.34.2300442.

NO ABSTRACT

PMID:37616117 | DOI:10.2807/1560-7917.ES.2023.28.34.2300442

J Healthc Risk Manag. 2023 Aug 24. doi: 10.1002/jhrm.21555. Online ahead of print.

ABSTRACT

Creating adequate safeguards for physical and online locations (e.g., desktop computers, network servers) where protected health information (PHI) may be breached is critical for management within entities compliant with the Health Information Portability and Accountability Act (HIPAA). With the increasing complexity of cyber breaches and budgetary issues, prioritizing which locations require the most immediate attention by top management through a data-driven model is more important than ever. Using CORAS threat modeling and five methods for multi-criteria decision-making, these locations were ranked from greatest to least risk of data breaches. Statistical methods were subsequently used for consistency and robustness checks. The findings illustrate that each type of covered entity under HIPAA must prioritize a different set of locations to safeguard first: health care providers must focus on the security of network servers, other portable electronic devices, and category of others (i.e., miscellaneous locations); health plans must focus on the security of paper and films, network servers, and others; and business associates must focus on the security of category of others, network servers, and other portable electronic devices. Combined with data on the source of the breaches (external vs. internal) and type of threats (e.g., hacking, theft), these findings provide recommendations for risk identification for privacy officers across health care.

PMID:37616038 | DOI:10.1002/jhrm.21555