Armenia has an upward trend in cesarean sections (CS); the CS rate increased from 7.2% in 2000 to 31.0% in 2017. The purpose of this study was to investigate potential factors contributing to the rapidly increasing rates of CS in Armenia and identify the actual costs of CS and vaginal birth (VB), which are different from the reimbursement rates by the Obstetric Care State Certificate Program of the Ministry of Health. This was a partially mixed concurrent quantitative-qualitative equal status study. The research team collected qualitative data via in-depth interviews (IDI) with obstetrician-gynecologists (OBGYN) and policymakers and focus group discussions (FGD) with women. The quantitative phase of the study utilized the bottom-up cost accounting (considering only direct variable costs) from the perspective of providers, and it included self-administered provider surveys and retrospective review of mother and child hospital records. The survey questionnaire was developed based on IDIs with providers of different medical services. The mean estimated direct variable cost per case was 35,219 AMD (94.72 USD) for VB and 80,385 AMD (216.19 USD) for CS. The ratio of mean direct variable costs for CS vs. VB was 2.28, which is higher than the government’s reimbursement ratio of 1.64. The amount of bonus payments to OBGYNs was 11 fold higher for CS than for VB indicating that OBGYNs may have significant financial motivation to perform CS without a medical necessity. The qualitative study analysis revealed that financial incentives, maternal request and lack of regulations could be contributing to increasing the CS rates. While OBGYNs did not report that higher reimbursement for CS could lead to increasing CS rates, the policymakers suggested a relationship between the high CS rate and the reimbursement mechanism. The quantitative phase of the study confirmed the policymakers’ concern. The study suggested an important relationship between the increasing CS rates and the current health care reimbursement system.

Background: The COVID-19 pandemic forced many health systems to proactively reduce care delivery to prepare for an expected surge in hospitalizations. There have been concerns that care deferral may have negative health effects, but it is hoped that telemedicine can provide a viable alternative. Objective: This study aimed to understand what type of health care services were being deferred during the COVID-19 pandemic lockdown, the role played by telemedicine to fill in care gaps, and changes in attitudes toward telemedicine. Methods: We conducted a cross-sectional analysis of survey responses from 1694 primary care patients in a mid-sized northeastern city. Our main outcomes were use of telemedicine and reports of care deferral during the shutdown. Results: Deferred care was widespread—48% (n=812) of respondents deferred care—but it was largely for preventive services, particularly dental and primary care, and did not cause concerns about negative health effects. In total, 30.2% (n=242) of those who delayed care were concerned about health effects, with needs centered around orthopedics and surgery. Telemedicine was viewed more positively than prior to the pandemic; it was seen as a viable option to deliver deferred care, particularly by respondents who were over 65 years of age, female, and college educated. Mental health services stood out for having high levels of deferred care. Conclusions: Temporary health system shutdowns will give rise to deferred care. However, much of the deferrals will be for preventive services. The effect of this on patient health can be moderated by prioritizing surgical and orthopedic services and delivering other services through telemedicine. Having telemedicine as an option is particularly crucial for mental health services.

The cost-effectiveness of community health worker (CHW)-based cardiovascular disease (CVD) risk-reduction interventions is not well established. Colorado Heart Healthy Solutions is a CHW-based intervention designed to reduce modifiable CVD risk factors. This program has previously demonstrated success, but the cost-effectiveness is unknown. CHW-based interventions are potentially attractive complements to healthcare delivery because laypersons implement the intervention at a lower cost relative to medical care and may be attractive in rural settings with limited clinical resources. CHWs performed screenings and provided ongoing participant support within predominantly rural communities. A point-of-service software tool was used to generate 10-year Framingham CVD risk scores and assist CHWs to make medical referrals and provide ongoing individualized support for lifestyle changes. A sample of program participants returned for reassessment of risk factors. We calculated quality-adjusted life years (QALYs) gained and program costs using a Markov model. Transition probabilities were calculated using Framingham risk equations or derived from the literature using the observed mean reduction in 10-year CVD risk score over of 37- months follow-up. Program cost-effectiveness was calculated for both at-risk (abnormal baseline CVD risk factors) and overall program populations. The base-case scenario evaluating a 52-year-old male participant revealed an incremental cost savings of $3576 and a gain of 0.16 QALYs associated with the intervention. Cost savings were greater in at-risk populations. The economic dominance of the model was robust in multiple sensitivity analyses. A community-based CVD intervention demonstrated to reduce CVD risk is cost-effective. This suggests that population-based public health programs may have the potential to complement primary care preventative services to improve health and reduce the burden of traditional medical care.

This study aims to identify sentiments that consumers have about health insurance by analyzing what they discuss on Twitter. The objective was to use sentiment analysis to identify attitudes consumers express towards health insurance and health care providers. We used an Application Programming Interface to gather tweets from Twitter with the words “health insurance” or “health plan” during health insurance enrollment season in the United States in 2016‒2017. Word association was used to find words associated with “premium,” “access,” “network,” and “switch.” Sentiment analysis established which specific emotions were associated with insurance and medical providers, using the NRC Emotion Lexicon, identifying emotions. We identified that provider networks, prescription drug benefits, political preferences, and norms of other consumers matter. Consumers trust medical providers but they fear unexpected health events. The results suggest that there is a need for different algorithms to help consumers find the plans they want and need. Consumers buying health insurance in the Affordable Care Act marketplaces in the United States choose lower-cost plans with limited benefits, but at the same time express fear about unexpected health events and unanticipated costs. If we better understand the origin of the sentiments that drive consumers, we may be able to help them better navigate insurance plan options and insurers can better respond to their needs.

Background: Many studies have focused on the characteristics of symptomatic patients with COVID-19 and clinical risk factors. This study reports the prevalence of COVID-19 in an asymptomatic population of a hospital service area (HSA) and identifies factors that affect exposure to the virus. Objective: The aim of this study is to measure the prevalence of COVID-19 in an HSA, identify factors that may increase or decrease the risk of infection, and analyze factors that increase the number of daily contacts. Methods: This study surveyed 1694 patients between April 30 and May 13, 2020, about their work and living situations, income, behavior, sociodemographic characteristics, and prepandemic health characteristics. This data was linked to testing data for 454 of these patients, including polymerase chain reaction test results and two different serologic assays. Positivity rate was used to calculate approximate prevalence, hospitalization rate, and infection fatality rate (IFR). Survey data was used to analyze risk factors, including the number of contacts reported by study participants. The data was also used to identify factors increasing the number of daily contacts, such as mask wearing and living environment. Results: We found a positivity rate of 2.2%, a hospitalization rate of 1.2%, and an adjusted IFR of 0.55%. A higher number of daily contacts with adults and older adults increases the probability of becoming infected. Occupation, living in an apartment versus a house, and wearing a face mask outside work increased the number of daily contacts. Conclusions: Studying prevalence in an asymptomatic population revealed estimates of unreported COVID-19 cases. Occupational, living situation, and behavioral data about COVID-19–protective behaviors such as wearing a mask may aid in the identification of nonclinical factors affecting the number of daily contacts, which may increase SARS-CoV-2 exposure.