Health Services Research and Managerial Epidemiology最新文献

Introduction: The federal government legislated supplemental funding to support community health centers (CHCs) in response to the COVID-19 pandemic. Supplemental funding included standard base payments and adjustments for the number of total and uninsured patients served before the pandemic. However, not all CHCs share similar patient population characteristics and health risks.

Objective: To use machine learning to identify the most important factors for predicting whether CHCs had a high burden of patients diagnosed with COVID-19 during the first year of the pandemic.

Methods: Our analytic sample included data from 1342 CHCs across the 50 states and D.C. in 2020. We trained a random forest (RF) classifier model, incorporating 5-fold cross-validation to validate the RF model while optimizing the model's hyperparameters. Final performance metrics were calculated following the application of the model that had the best fit to the held-out test set.

Results: CHCs with a high burden of COVID-19 had an average of 65.3 patients diagnosed with COVID-19 per 1000 patients in 2020. Our RF model had 80.9% accuracy, 80.1% precision, 25.0% sensitivity, and 98.1% specificity. The percentage of Hispanic patients served in 2020 was the most important feature for predicting whether CHCs had high COVID-19 burden.

Conclusions: Findings from our RF model suggest patient population race and ethnicity characteristics were most important for predicting whether CHCs had a high burden of patients diagnosed with COVID-19 in 2020, though sensitivity was low. Enhanced support for CHCs serving large Hispanic patient populations may have an impact on addressing future COVID-19 waves.

Background: Being born with low birthweight is a major determinant of perinatal, neonatal, and infant survival. Even though low birthweight-related neonatal mortality is high, there is an information gap regarding the survival status of low birthweight neonates and their predictors of mortality in Ethiopia.

Objective: This study was conducted to assess the survival status and predictors of mortality among low birthweight neonates admitted to Amhara region referral hospitals in Ethiopia.

Methods and materials: A retrospective follow-up study was conducted on randomly selected low birthweight neonates admitted to the Amhara region referral hospital between January 01-2017 and December 30-2018. Data were entered into Epi-data 4.4.2.1 and exported to Stata 14 for cleaning and analysis. A cox regression model was used to analyze the data. Tables, charts, and text were used to report the results.

Results: This study revealed that 35.2% of participants died with incidence rates of 37.86 per 1000 person-day observations (95%CI: 31.79-45.10). Sepsis (AHR:1.72(95% CI: 1.05-2.81), respiratory distress (AHR: 2.03 (95% CI:1.36-3.03), necrotizing enterocolitis (AHR: 2.47 (95% CI: 1.17-5.20), congenital anomalies (AHR:2.37 (95% CI: 1.36-4.13), extreme low birth weight (AHR:2.62 (95% CI:1.54-4.44) and prematurity (AHR: 2.55 (95% CI:1.10-5.92) were independent predictors of mortality.

Conclusion: Sepsis, respiratory distress, necrotizing enterocolitis, congenital anomalies, extremely low birth weight, and premature birth were the independent predictors of mortality. Therefore, it is better for all stakeholders to focus more on the early diagnosis and management of low birth weight neonates with the factors associated with mortality.

Background: Low dietary diversity is the main public health issue in developing countries. Despite its burden, there is a paucity of information on the dietary diversity of households and related factors in rural residents of southern Ethiopia. Therefore, this study assessed household dietary diversity and associated factors among rural residents of Gomole district.

Methods: A community-based cross-sectional study design was conducted from November 1 to December 30, 2020, among 554 randomly selected rural households. Data were collected by using pretested structured face-to-face interviews about dietary intake by any household members within the past 24 h. The data were coded and entered into Epi data 3.1 and analyzed using Statistical Package for Social Sciences version 23. Both descriptive and analytic statistics were employed. Adjusted odds ratios (AORs) together with 95% confidence intervals and p values of less than 0.05 were used to declare statistical significance.

Results: Out of the total, 19% (95%; CI = 15.7-22.2) of households had adequate dietary diversity scores. The mean (±SD) dietary diversity score was 5.12 (±1.6). The most consumed food groups in the study area were cereals/grains (96.4%), condiments (salt and beverages (tea)) (84.3%) and milk and milk products (80%). The sex of the household head (AOR = 2.31, 95% CI: 1.04-5.13), bank account ownership (AOR = 2.18, 95% CI: 1.04-4.59), and livestock ownership (AOR = 4.75, 95% CI: 1.35-16.73) were positively associated with dietary diversity. However, distance to the marketplace (AOR = 0.11, 95% CI: 0.02-0.56) was negatively associated with adequate dietary diversity.

Conclusion: There is low dietary diversity among households of study area. Improving livestock rearing and bank accounts should be strengthened through strong intersectional collaboration to alleviate the problem.

Introduction/objectives: We examined an initial step towards co-generation of clinic notes by inviting patients to complete a pre-visit questionnaire that could be inserted into clinic notes by providers and describe the experience in a safety-net and non-safety-net clinic.

Methods: We sent an electronic pre-visit questionnaire on visit goals and interim history to patients at a safety-net clinic and a non-safety-net clinic before clinic visits. We compared questionnaire utilization between clinics during a one-year period and performed a chart review of a sample of patients to examine demographics, content and usage of patient responses to the questionnaire.

Results: While use was low in both clinics, it was lower in the safety-net clinic (3%) compared to the non-safety-net clinic (10%). We reviewed a sample of respondents and found they were more likely to be White compared to the overall clinic populations (p < 0.05). There were no statistically significant differences in patient-typed notes (word count and number of visit goals) between the safety-net and non-safety-net samples however, patients at the safety-net clinic were less likely to have all of their goals addressed within the PCP documentation, compared to the non-safety-net clinic.

Conclusions: Given potential benefits of this questionnaire as a communication tool, addressing barriers to use of technology among vulnerable patients is needed, including access to devices and internet, and support from caregivers or culturally concordant peer navigators.

Background: Cardiovascular diseases are a group of disorders of the heart and blood vessels. Globally an estimated 17.9 million people died from cardiovascular diseases, which covers 31% of all global deaths, and the three quarters taking place in developing countries. Hypertension is the major cause of cardiovascular diseases. Its influence is high with other risk factors. This study aimed to determine the major risk factors of cardiovascular disease among hypertensive patients at Jimma University Medical Center.

Methods: Using December to January 2017 hypertension-related report of Jimma University Medical Center (JUMC), a retrospective cohort study type was conducted on purposively selected 343 patients. Three nurses from JUMC participated in the data collection, and the data were fitted using the Cox-Proportional Hazard (Cox-PH) model.

Results: About 138 (40.23%) patients were experienced cardiovascular disease at 28 months median time. From the Cox-PH model, the hazard ratio and 95% CI of age (HR = 1.0495, 95% CI: 1.0250-1.0747), urban (HR = 2.1225, 95% CI: 1.3813-3.2613), diabetes mellitus (HR = 1.702, 95% CI: 1.0082-2.8731), proteinuria (HR = 1.8749, 95% CI: 1.2675-2.7734), two drug users (HR = 0.2533, 95% CI: 0.1376-0.4662), systolic blood pressure (HR = 1.0343, 95% CI: 1.0147-1.0542) and pulse rate (HR = 1.0111, 95% CI: 0.9933-1.0293).

Conclusion: The presence of proteinuria, diabetes mellitus, and being an urban resident had a great impact on the cardiovascular diseases of hypertensive patients.

Background: The number of pre-anesthetic medical evaluations (PAMEs) being conducted in primary care is increasing. Due to the COVID-19 pandemic, the use of telemedicine has surged, providing a feasible way to conduct some of these visits. This study aimed to identify patient-related factors where a face to face (FTF) evaluation is indicated, measured by the need for pre-operative testing.

Methods: A retrospective chart review was conducted on patients age ≥ 18 years who had a PAME between January 2019-June 2020 at a rural primary care clinic in Southeast Minnesota. Data collected included age, gender, Charlson Comorbidity Index Score, medications, revised cardiac risk index (RCRI), smoking status, exercise capacity, body mass index, and pre-operative testing. Logistical regression modeling for odds ratios of outcomes was performed.

Results: 254 patients were included, with an average age of 64.1 years; 43.7% were female. Most were obese (mean BMI 31.6), non-smoking (93.7%) with excellent functional capacity (87.8% ≥ 5 METs). 76.8% of the planned surgeries were intermediate or high risk. 35.0% (n = 89) of visits resulted in medication adjustments and 76.7% (n = 195) in pre-operative testing. Age ≥ 65 years, ≥7 current medications, and diabetes all significantly increased the odds of requiring pre-operative testing (P < .05).

Conclusions: This study was able to identify patient-related factors that increased the likelihood of requiring pre-operative testing. Patients who are age ≥ 65 years, ≥7 current medications, and those with diabetes could be scheduled for a FTF evaluation. Others could be scheduled for a telemedicine visit to minimize health-care exposures.