Probability Of Visit Research Articles

Patient visit behaviour shapes the virus infection dynamics in hosts

Chronic HBV infection is a dynamic process of rapid viral replication and clearance, with large amounts of virus being produced and lost in the body daily. The patient's visit behaviour is closely related to viral load in the body, while the data-driven mathematical model still lacking. Therefore, we first include 28,912 patients to investigate the relationships between the visit behaviour and the HBV-DNA virus load. Then, we propose an HBV virus infection dynamics model that considers the patient's visit behaviour. The system is chaotic once the behaviour of patients during visits depends on the virus load. Our results may help us understand the process of viral transmission, and increasing the visit probability to the clinic can lead to stabilising HBV-DNA viral loads and further help healthcare professionals develop targeted clinical intervention strategies.

Socioeconomic inequity in the utilization of healthcare among people with eating disorders in Australia.

Little is known about socioeconomic equity in access to healthcare among people with eating disorders in Australia. This study aims to measure the extent of inequity in eating disorder-related healthcare utilization, analyze trends, and explore the sources of inequalities using New South Wales (NSW) administrative linked health data for 2005 to 2020. Socioeconomic inequities were measured using concentration index approach, and decomposition analysis was conducted to explain the factors accounting for inequality. Healthcare utilization included: public inpatient admissions, private inpatient admissions, visits to public mental health outpatient clinics and emergency department visits, with three different measures (probability of visit, total and conditional number of visits) for each outcome. Private hospital admissions due to eating disorders were concentrated among individuals from higher socioeconomic status (SES) from 2005 to 2020. There was no significant inequity in the probability of public hospital admissions for the same period. Public outpatient visits were utilized more by people from lower SES from 2008 to 2020. Emergency department visits were equitable, but more utilized by those from lower SES in 2020. Public hospital and emergency department services were equitably used by people with eating disorders in NSW, but individuals from high SES were more likely to be admitted to private hospitals for eating disorder care. Use of public hospital outpatient services was higher for those from lower SES. These findings can assist policymakers in understanding the equity of the healthcare system and developing programs to improve fairness in eating disorder-related healthcare in NSW.

Core Mental Health Clinician Capacity and Use Rates in the US Military

Active duty service members have higher mental health stress and cannot choose where to live. It is imperative to understand how geographic access may be associated with their ability to obtain mental health treatment and how the COVID-19 pandemic was associated with these patterns. To identify changes in the prevalence and intensity of mental health care use when service members experienced changes in core mental health clinician (defined to include psychiatrists, psychiatric nurse practitioners, clinical psychologists and social workers, and marriage and family therapists) capacity in their communities and whether patterns changed from before to after the onset of the COVID-19 pandemic. This retrospective cohort study of the active duty population between January 1, 2016, and December 31, 2022, was conducted using individual fixed-effects models to estimate changes in the probability of mental health care visits and visit volume when a person moved across communities with adequate core mental health clinician capacity (≥1 clinician/6000 beneficiaries), shortage areas (<1 clinician/6000 beneficiaries), and areas with 0 clinicians within a 30-minute drive time. All US active duty service members stationed in the continental US, Hawaii, and Alaska were included. Data were analyzed from January through July 2024. The first set of outcomes captured the probability of making at least 1 mental health care visit in a given quarter; the second set of outcomes captured the intensity of visits (ie, the number of visits log transformed). This study included 33 039 840 quarterly observations representing 2 461 911 unique active duty service members from the Army, Navy, Marines, and Air Force (1 959 110 observations among Asian or Pacific Islander [5.9%], 5 309 276 observations among Black [16.1%], 5 287 168 observations among Hispanic [16.0%], and 18 739 827 observations among White [56.7%] individuals; 27 473 563 observations among males [83.2%]; mean [SD] age, 28.20 [7.78] years). When an active duty service member moved from a community with adequate capacity at military treatment facilities to one with 0 clinicians within a 30-minute drive, the probability of a mental health visit to any clinician decreased by 1.13 percentage points (95% CI, -1.21 to -1.05 percentage points; equivalent to a 11.6% relative decrease) and the intensity of total visits was reduced by 7.7% (95% CI, -9.0% to -6.5%). The gap increased from before to after the onset of the COVID-19 pandemic, from 8.5% (equivalent to -0.82 percentage points [95% CI, -0.92 to -0.73 percentage points]) to 16.2% (equivalent to -1.58 percentage points [95% CI, -1.70 to -1.46 percentage points]) in the probability of visiting any clinician type for mental health. In this study, active duty personnel assigned to locations without core military mental health clinicians within a 30-minute drive time were less likely to obtain mental health care and had fewer mental health care visits than those in communities with adequate military mental health capacity even if there was adequate coverage from the civilian sector. The care disparity increased after the onset of the COVID-19 pandemic.

On-Demand Meal Delivery: A Markov Model for Circulating Couriers

On-demand meal delivery has become a feature of most cities around the world as a result of platforms and apps that facilitate it as well as the pandemic, which for a period, closed restaurants. Meals are delivered by couriers, typically on bikes, e-bikes, or scooters, who circulate collecting meals from kitchens and delivering them to customers, who usually order online. A Markov model for circulating couriers with n + 1 parameters, where [Formula: see text] is the number of kitchens plus customers, is derived by entropy maximization. There is one parameter for each kitchen and customer representing the demand for a courier, and there is one parameter representing the urgency of delivery. It is shown how the mean and variance of delivery time can be calculated once the parameters are known. The Markov model is irreducible. Two procedures are presented for calibrating model parameters on a data set of orders. Both procedures match known order frequencies with fitted visit probabilities; the first inputs an urgency parameter value and outputs mean delivery time, whereas the second inputs mean delivery time and outputs the corresponding urgency parameter value. Model calibration is demonstrated on a publicly available data set of meal orders from Grubhub. Grubhub data are also used to validate the calibrated model using a likelihood ratio. By changing the location of one kitchen, it is shown how the calibrated model can estimate the resulting change in demand for its meals and the corresponding mean delivery time. The Markov model could also be used for the assignment of courier trips to a street network. History: This paper has been accepted for the Transportation Science Special Issue on ISTTT Conference.

MCI모형을 이용한 중국 옌타이시 대형소매점 매출예측 및 상권영향분석

Recent research on GIS analysis, spatial interaction models, and site selection for large retail stores is actively underway in China both domestically and internationally. However, most studies tend to rely on secondary data provided by government agencies, neglecting research based on actual consumer survey data. Therefore, this study aimed to improve methods for analyzing commercial areas of large-scale retail stores in China by proposing the use of consumer data to enhance existing spatial interaction models. Specifically, by conducting surveys among consumers who actually visit large-scale retail stores, basic data such as store visit rates and visitor travel distances were collected to construct the MCI model. Through this approach, the study estimated the visit probability and market share of large-scale retail stores, and analyzed the impact of market environmental changes on commercial areas. Firstly, based on address data from 279 Chinese consumers, the study area was divided into 44 regions. These regions were combined with information on consumer shopping patterns and store details to construct a matrix of interactions between regions and large-scale retail stores. Secondly, important parameters in the MCI model, such as store attractiveness index and distance sensitivity, were estimated through OLS regression analysis. Findings revealed that the store type (regional large-scale retail, urban large-scale retail) did not significantly impact on consumers’ store preferences. Instead, customer visits exhibited an inverse relationship with distance and a direct relationship with store size. These estimated results were consistent with the theoretical perspectives of spatial interaction models. Thirdly, to examine how changes in the retail environment may affect retail businesses within commercial areas, the study focused on changes in sales and market share of surrounding retail businesses when a specific store expanded its area or entered a new region. The results showed that both expanding store area and entering new regions had negative impacts on other existing stores.

The impact of medical insurance and old-age security on the utilization of medical services by the older population with disabilities

ObjectiveIn this study, the impact of medical insurance and old-age security on the use of medical services by the older population with disabilities is analyzed. A reference for decision makers is provided to improve medical and old-age security policies and enhance the use of medical services by the older population.MethodsData were drawn from 3,737 older people with disabilities aged 65 years or above from the 2018 China Longitudinal Healthy Longevity Survey. A two-part model based on social ecological theory was used for both analysis and group prediction.ResultsIn terms of the use of outpatient medical services, old-age pension significantly increased the probability of outpatient visits for this population group (P < 0.05). Urban employee/resident medical insurance, the new rural cooperative medical insurance, and retirement pension significantly affected medical expenses. In terms of the use of inpatient medical services, the new rural cooperative medical insurance and retirement pension significantly influenced the choice of inpatient medical services; retirement pension increased inpatient medical expenditure (p < 0.01). The expected average probability of hospitalization, unconditional expected cost, and conditional expected cost for the older population with disabilities were 49.5%, RMB 6629.31, and RMB 3281.51, respectively. Both conditional and unconditional expected costs were significantly higher for older people with disabilities with the following attributes: male, married, no less than three chronic conditions, and unassisted daily care; costs were lower for older people with disabilities who are female, not married, had less than three chronic conditions, and had a spouse, child, or other caregiver.ConclusionMedical insurance and old-age security can significantly promote the utilization of medical services by the older population with disabilities. It is therefore recommended to focus on strengthening the support and health management of these people who are unattended to improve the effective use of health services and better meet their needs.

Hospital admissions in the last month of life for patients with advanced cancer residing in nursing homes

IntroductionOvertreatment and frequent hospital admissions in patients at end-of-life has been shown in several studies, including in the nursing home (NH) setting. However, overtreatment in NH residents with advanced cancer has not been studied before. Our objective was to compare emergency room (ER) visits and hospital admissions in the last month of life and place of death among NH residents with or without advanced cancer. Materials and MethodsThis retrospective study is based on Region Stockholm's administrative database from 2015 to 2019. Demographic data, ER visits, and Hospital Frailty Risk Score (HFRS) were extracted for each subject. Univariable and multivariable analyses were performed, and odds ratios (OR) calculated. ResultsIn total, 30,324 NH residents were identified, of which 1807 had advanced cancer. Advanced cancer was associated with more ER visits in the last month of life in the univariable analysis but not when adjusted for age, sex, and risk of frailty with an adjusted aOR of 1.07 (95 %CI 0.97–1.19). Having a cancer diagnosis was significantly associated with acute hospital admissions, although the association was rather weak with an aOR 1.13 (95 %CI 1.02–1.26). NH residents with advanced cancer were less likely to die in hospital than non-cancer residents: aOR 0.63 (95 %CI 0.54–0.73). DiscussionNH residents with advanced cancer have a slightly higher risk of hospital admissions in the last month of life compared to non-cancer residents but are less likely to die in hospital. The probability of ER visits during the last month of life was similar between NH residents with and without cancer.

Visit probability and accessibility within space–time prism of activity program

Space–time prism (STP) is widely applied to measure individuals’ ability to reach opportunities given the resource limitations. The majority of STP models treat prism-based accessibility as binary measures, wherein all locations within a prism are assumed equally accessible while others are deemed inaccessible. Although a few STP models examined heterogeneous interiors by modeling visit probabilities within the STPs, they primarily focused on trip-level analysis and did not explore the application for accessibility measurement. This study proposes a model framework based on multi-state supernetworks for constructing and estimating the probabilistic STPs of daily activity programs. The estimation is implemented with latent class models to account for individual heterogeneities in travel and activity participation. Based on the probabilistic STPs, we suggest a space–time accessibility measurement incorporating visit probabilities. We validate the model framework using mobility trajectory data collected in the Netherlands and demonstrate that the visit probability model can effectively capture the probabilistic STP interiors and the proposed accessibility measurement can provide a comprehensive evaluation of accessibility in the presence of activity chains.

Does supplemental private health insurance impact health care utilization and seeking behavior of residents covered by social health insurance? Evidence from China National Health Services Survey

BackgroundSupplemental private health insurance (PHI) plays a crucial role in complementing China’s social health insurance (SHI). However, the effectiveness of incorporating PHI as supplementary coverage lacks conclusive evidence regarding its impact on healthcare utilization and seeking behavior among SHI-covered individuals. Therefore, investigating the effects of supplementary PHI on health care utilization and seeking behavior of residents covered by social health insurance is essential to provide empirical evidence for informed decision-making within the Chinese healthcare system.MethodsData from the 2018 China National Health Services Survey were analyzed to compare outpatient and inpatient healthcare utilization and choices between PHI purchasers and non-purchasers across three SHI schemes: urban employee-based basic medical insurance (UEBMI), urban resident-based basic medical insurance (URBMI), and the new rural cooperative medical scheme (NRCMS). Using the Andersen Healthcare Services Utilization Behavior Model as the theoretical framework,binary logistic regression and multinomial logistic regression (MNL) models were employed to assess the impact of PHI on healthcare utilization and provider preferences.ResultsAmong UEBMI, URBMI, and NRCMS participants with PHI, outpatient visit rates were 17.9, 19.8, and 21.7%, and inpatient admission rates were 12.4, 9.9, and 12.9%, respectively. Participants without PHI exhibited higher rates for outpatient visits (23.6, 24.3, and 25.6%) and inpatient admissions (15.2, 12.8, and 14.5%). Binomial logistic regression analyses revealed a higher probability of outpatient visits and inpatient admissions among UEBMI participants with PHI (p < 0.05). NRCMS participants with PHI showed a lower probability of outpatient visits but a higher probability of inpatient admissions (p < 0.05). Multinomial logistic regression indicated that NRCMS participants with PHI were more likely to choose higher-level hospitals, with a 17% increase for county hospitals and 27% for provincial or higher-level hospitals compared to primary care facilities.ConclusionThe findings indicate that the possession of PHI correlated with increased utilization of outpatient and inpatient healthcare services among participants covered by UEBMI. Moreover, for participants under the NRCMS, the presence of PHI is linked to a proclivity for seeking outpatient care at higher-level hospitals and heightened utilization of inpatient services. These results underscore the nuanced influence of supplementary PHI on healthcare-seeking behavior, emphasizing variations across individuals covered by distinct SHI schemes.

Associations of Homelessness With Primary Care and Acute Care Utilization Among Medicaid-Enrolled Youth.

Youth comprise one-third of the US homeless population. However, little is known about how homelessness affects health care utilization. Examine associations of homelessness with hospitalization, primary care, and ED visits, varying by race/ethnicity, among Medicaid-enrolled youth. A cross-sectional analysis was conducted using California Medicaid claims data on youth beneficiaries with complex needs. We examined the number of hospitalizations, preventable and nonpreventable ED, and primary care visits using a multivariate regression. We further explored the differential associations by race/ethnicity. Approximately 17% of our sampled youth experienced homelessness in 2018 (N=90,202). Compared with their housed counterparts, youth experiencing homelessness had a 1.9 percentage point (pp) higher likelihood of frequent ED visits (95% CI: 1.7-2.2) but a 2.9 pp lower probability of any primary care visits (95% CI: -3.9 to -1.9). Homelessness was associated with 221 more ED visits (95% CI: 182-260), 100 more preventable ED visits (95% CI: 84-116), 19.9 more hospitalizations (95% CI: 12-27), but 56 fewer primary care visits (95% CI: -104 to -7), per 1000 youth. The associations of homelessness with total ED visits, preventable ED visits, and needed and nonpreventable ED visits were all higher among Whites and, particularly, Blacks than for Hispanics and Asians. Medicaid-enrolled youth who experienced homelessness had more overall ED, preventable ED, and hospital visits, but fewer primary care visits than their housed peers. Our results suggest promoting primary care use should be considered among strategies to improve health and reduce costs.

Association of Patient-Reported Social Needs with Emergency Department Visits and Hospitalizations Among Federally Qualified Health Center Patients.

Health care systems are increasingly screening for unmet social needs. The association between patient-reported social needs and health care utilization is not well understood. To investigate the association between patient-reported social needs, measured by the Protocol for Responding to and Assessing Patients' Assets, Risks, and Experiences (PRAPARE), and inpatient and emergency department (ED) utilization. This cohort study analyzed merged 2017-2019 electronic health record (EHR) data across multiple health systems. Adult patients from a federally qualified health center (FQHC) in central North Carolina who completed PRAPARE as part of a primary care visit with behavioral health services. The count of up to 12 unmet social needs, aggregated as 0, 1, 2, or 3 + . Outcomes include the probability of an ED visit and hospitalization 12months after PRAPARE assessment, modeled by logistic regressions controlling for age, sex, race, ethnicity, comorbidity burden, being uninsured, and prior utilization in the past 12months. The study population consisted of 1924 adults (38.7% male, 50.1% Black, 36.3% Hispanic, 55.9% unemployed, 68.2% of patients reported 1 + needs). Those with more needs were younger, more likely to be unemployed, and experienced greater comorbidity burden. 35.3% of patients had ED visit(s) and 36.3% had hospitalization(s) 1year after PRAPARE assessment. In adjusted analysis, having 3 + needs was associated with a percentage point increase in the predicted probability of hospitalization (average marginal effect 0.06, SE 0.03, p < 0.05) compared with having 0 needs. Similarly, having 2 needs (0.07, SE 0.03, p < 0.05) or 3 + needs (0.06, SE 0.03, p < 0.05) was associated with increased probability of ED visits compared to 0 needs. Patient-reported social needs were common and associated with health care utilization patterns. Future research should identify interventions to address unmet social needs to improve health and avoid potentially preventable escalating medical intervention.

Analysis of the Potential of Commercial Corridor Based on Consumer Movement Interactions in Central Jakarta

In the evolving landscape of modern commercial development, the potential of Jakarta’s shopping center corridors has emerged as a key area of interest. Consumer lifestyle behavior shifts, technological advancements, and design innovations have shaped new trends in the retail industry. The development of modern shopping centers has brought significant changes in consumer movement patterns in various metropolitan cities, including Central Jakarta. Utilizing empirical data from bustling shopping centers, the research employs the Huff and Gravity models to analyze consumer movement patterns. These models offer a nuanced understanding of how factors like accessibility, population density, and urban design influence consumer choices. The results show that ITC Roxy has the highest probability of consumer visits, while H. M. Saleh Ishak Street, Sutan Syahrir Street, Dr GSSJ Ratulangi Street, Menteng Raya Street, Kramat Kwitang Street, and Pasar Senen Street have the highest interaction volumes due to their proximity to arterial roads and collectors. The results reveal a significant shift in consumer movement behavior, driven by urban development and demographic changes, underscoring the urgency for adaptive commercial planning.

Incentivizing dental services in healthy behaviour Medicaid waivers.

In the United States, adult dental benefits are optional in the state-managed, public insurance program, Medicaid. States also have the option to adapt their Medicaid program via waivers which pair healthy behaviour incentives (HBI) with cost-sharing. These waivers have proven ineffective, but the empirical evidence has ignored differences between states. This study aims to evaluate the impact of four state's HBI Medicaid waiver on dental visits among low-income adult population subject to incentives and cost-sharing requirements by the HBI waiver. Analysing biannual data from the Behavioural Risk Factor Surveillance System's Oral Health module (2008-2018) with a Difference-in-Differences design, this study estimated the effect of a Healthy Behaviour Incentive waiver on the probability of visiting the dentist in the past year. The three states that implemented an HBI Waiver (Indiana, Michigan and Wisconsin) were analysed separately. Secondary outcomes included being uninsured and having all teeth extracted. Matrix Completion methods accounted for dynamic treatment and tested for non-common trends. Inference was based on randomization inference tests. Only in Michigan was an HBI waiver consistently associated with a significant increase in the probability of a dental visit (Est. = 5.6%-points, p = .01). There was little convincing evidence that HBI waivers were associated with being uninsured or having all teeth extracted. Between 2010 and 2019, many states have implemented an HBI waiver, each with a different approach to incentivizing dental visits. These implementation differences may explain the heterogeneous effects by state. More work is needed to evaluate how Medicaid waivers impact health outcomes in low-income populations.

Elective Joint Replacement Among Medicaid Beneficiaries: Utilization and Postoperative Adverse Events by Racial and Ethnic Groups.

Hip and knee replacement have been marked by racial and ethnic disparities in both utilization and postoperative adverse events among Medicare beneficiaries, but limited knowledge exists regarding racial and ethnic differences in joint replacement care among Medicaid beneficiaries. To close this gap, this study used Medicaid claims in 2018 and described racial and ethnic differences in the utilization and postoperative adverse events of elective joint replacements among Medicaid beneficiaries. Among the 2,260,272 Medicaid beneficiaries, 5987 had an elective joint replacement in 2018. Asian (0.05%, 95% confidence interval [CI]: 0.03%-0.07%) and Hispanic beneficiaries (0.12%, 95% CI: 0.07%-0.18%) received joint replacements less frequently than American Indian and Alaska Native (0.41%, 95% CI: 0.27%-0.55%), Black (0.33%, 95% CI: 0.19%-0.48%), and White (0.37%, 95% CI: 0.25%-0.50%) beneficiaries. Black patients demonstrated the highest probability of 90-day emergency department visits (34.8%, 95% CI: 32.7%-37.0%) among all racial and ethnic groups and a higher probability of 90-day readmission (8.0%, 95% CI: 6.9%-9.0%) than Asian (3.4%, 95% CI: 0.7%-6.0%) and Hispanic patients (4.4%, 95% CI: 3.4%-5.3%). These findings indicate evident disparities in postoperative adverse events across racial and ethnic groups, with Black patients demonstrating the highest probability of 90-day emergency department visits. This study represents an initial exploration of the racial and ethnic differences in joint replacement care among Medicaid beneficiaries and lay the groundwork for further investigation into contributing factors of the observed disparities.

A Study of Hospital Competition in Yogyakarta City with Huff’s Gravity Model and Valuation Methods

This analysis was conducted to identify the level of hospital competition in Yogyakarta City. The object of this study is 12 hospitals in Yogyakarta City. The analytical tools in this study consist of two methods. The ?irst method is the Huff’s Gravity Model used to estimate the probability of visits to each hospital so that the competition between hospitals can be known. The second method is the valuation method using the income approach to calculate the potential value of the hospital. The results of this study show that the largest visit probability and potential value are owned by RS PKU Muhammadiyah Yogyakarta with a probability value of 19.91% and a potential value of IDR 8,493,747,933,578 for an optimistic estimate, IDR 3,370,534,894,277 for a moderate estimate, and IDR 1,400,068,340,700 pessimistic estimate. The contribution of this research can be considered in making investment decisions, especially in planning the establishment of a new hospital or expanding the capacity of an existing hospital. For investors who will invest in the hospital industry, they should look for locations that are easily accessible and avoid building hospitals with lower types near hospitals with high types; this will affect the level of probability of visits to the hospital itself. If the level of visit opportunity is low, then the potential value that will be obtained will also be low.

Wild bumblebees use both absolute and relative evaluation when foraging

Abstract Foraging theory assumes that animals assess value based on objective payoffs; however, animals often evaluate rewards comparatively, forming expectations based on recent experience. This form of evaluation may be particularly relevant for nectar foragers such as bumblebees, where individuals can visit thousands of flowers daily that vary in nectar quality. While many animals, including bees, demonstrate reference-based evaluation in experimental contexts, it is unclear whether this occurs in the wild. Here, we asked how daily experience with wildflower nectar influenced wild bumblebees’ reward evaluation. We measured the daily nectar concentration of bee-visited wildflowers (Penstemon spp.), before presenting foragers with conspecific flowers filled with a range of artificial nectar concentrations. We recorded bees’ acceptance of artificial nectar, the probability of subsequent visits to flowers on the same plant, and residence time. While bees had a minimum threshold of nectar acceptability that was unaffected by experience, when there was higher-concentration environmental nectar, they were less likely to accept lower-quality rewards on manipulated plants. Bees also visited more flowers and stayed longer on plants with higher-concentration nectar. This study shows evidence for both absolute and reference-based evaluation in wild bees and points towards differences between bees’ behavior in lab- and wild-foraging contexts.

Attributing practice variation by its sources: the case of varicose veins treatments in the Netherlands

BackgroundUnwarranted practice variation refers to regional differences in treatments that are not driven by patients’ medical needs or preferences. Although it is the subject of numerous studies, most research focuses on variation at the end stage of treatment, i.e. the stage of the treating specialist, disregarding variation stemming from other sources (e.g. patient preferences, general practitioner referral patterns). In the present paper, we introduce a method that allows us to measure regional variation at different stages of the patient journey leading up to treatment.MethodsA series of logit regressions estimating the probability of (1) initial visit with the physician and (2) treatment correcting for patient needs and patient preferences. Calculating the coefficient of variation (CVU) at each stage of the patient journey.ResultsOur findings show large regional variations in the probability of receiving an initial visit, The CVU, or the measure of dispersion, in the regional probability of an initial visit with a specialist was significantly larger (0.87–0.96) than at the point of treatment both conditional (0.14–0.25) and unconditional on an initial visit (0.65–0.74), suggesting that practice variation was present before the patient reached the specialist.ConclusionsWe present a new approach to attribute practice variation to different stages in the patient journey. We demonstrate our method using the clinically-relevant segment of varicose veins treatments. Our findings demonstrate that irrespective of the gatekeeping role of general practitioners (GPs), a large share of practice variation in the treatment of varicose veins is attributable to regional variation in primary care referrals. Contrary to expectation, specialists’ decisions meaningfully diminish rather than increase the amount of regional variation.

Abstract 16083: How Will the Use of New Heart Failure Treatments Impact US Health System Reimbursement Under Alternative Payment Models: Measuring the Impact of Sotagliflozin Use Among Patients Hospitalized for Heart Failure

Background: In the SOLOIST-WHF clinical trial, sotagliflozin lowered rates of readmission and emergency department (ED) visits among patients hospitalized for worsening heart failure (HF), but its impact on health systems’ finances is unclear. Research Question: What is the economic impact of the adoption of sotagliflozin on health systems after incorporating reimbursement bonuses within alternative payment models (APM)? Goal: To quantify the financial impact on health systems of adopting sotagliflozin relative to standard of care (SoC) for treating patients with HF as in SOLOIST-WHF. Methods: This study created a decision tree model and estimated the clinical impact of sotagliflozin use relative to SoC from the SOLOIST-WHF trial. The model first assessed the impact of sotagliflozin on re-hospitalization, ED visit rates and mortality. Next, these clinical outcomes were translated into impacts on a health system’s finances relative to SoC within a one-year time frame under traditional fee-for-services (FFS) and three APMs: hospital readmissions reduction program (HRRP), Bundled Payments for Care Improvement (BPCI), and Accountable Care Organization (ACO). Results: An average community hospital (6,109 admissions annually) would have 83 patients per year with an index HF hospitalization. Sotagliflozin reduced the probability of re-hospitalization, ED visits, and deaths by 29.3%, 38.5%, and 17.8%, respectively vs. SoC. For hospitals not experiencing capacity constraint, sotagliflozin adoption increased financial returns by $9,365 per person (pp) ($781,340 per health system) under HRRP, $1,200 pp. ($100,106 per health system) for BPCI, and $1,078 pp. ($89,910 per health system) for ACO. (Figure 1) Conclusion: Sotagliflozin adoption decreased hospitalizations, ED visits, and deaths, which—under various APMs—led to a net positive financial impact on health systems after accounting for APM bonus payments. Sponsorship: Lexicon Pharmaceuticals, Inc.

Propensity of US Military Personnel to Seek Mental Health Care When Community Psychiatric Capacity Changes

Understanding how the active duty military population's mental health care use is associated with local military and civilian psychiatrist capacity is critical in designing the optimal allocation of mental health resources from both sectors to improve the mental health of military personnel. To evaluate whether the probability of mental health care visits by military personnel changes when psychiatrist capacity changes in their communities, when capacity is measured separately for military treatment facilities and civilian sectors. This cohort study of active duty US military service members between January 1, 2016, and September 30, 2020, combines data from the Defense Health Agency, the National Plan and Provider Enumeration System, and the US Census. Data were collected and analyzed from June 2022 to July 2023. The main outcome was the probability of making at least 1 mental health care visit in a given quarter at military treatment facilities and in civilian settings. Linear probability models with 2-dimensional fixed effects at individual and community levels were implemented to estimate changes in individual outcomes when community psychiatrist capacity changed. This study includes 1 958 421 US service members (83% men; mean [SD] age at baseline, 28.4 [8.0] years). Thirteen percent of service members did not have military treatment facility psychiatrists available within a 30-minute driving time, and 66% lived in communities with a psychiatrist shortage (<1 psychiatrist per 20 000 relevant population), while 9% lived in communities with high (>3 psychiatrists per 20 000 relevant population) military treatment facility psychiatrist capacity. Five percent of service members lived in communities with no civilian psychiatrists within a 30-minute driving time, while 66% lived in communities with high civilian psychiatrist capacity. The mean quarterly mental health care visit rates to military treatment facilities and civilian settings were 7% and 2%, respectively. The probability of a mental health care visit to a military treatment facility increased by 0.95 percentage points (95% CI, 0.79-1.10 percentage points; equivalent to 14%) when the individual experienced a change in military treatment facility capacity from no psychiatrist to high capacity. The probability of a mental health care visit to a civilian setting increased by 0.57 percentage points (95% CI, 0.38-0.76 percentage points; equivalent to 32%) when civilian capacity changed from no psychiatrist to high capacity. The magnitude of responses to military treatment facility capacity changes remained similar in communities that already had high civilian capacity. This cohort study of the US military population suggests that active duty military personnel rely largely on military treatment facilities for their mental health care and that there are meaningful responses to military treatment facility psychiatrist capacity changes even in communities with high civilian psychiatric capacity. Realigning military treatment facility psychiatrists across communities with shortages and high-capacity military treatment facilities, as well as addressing nongeographical barriers in the civilian sector, remain critical to achieve the optimal balance between military and civilian care provision.

Continuity of primary care and emergency department visits following knee and hip replacement surgery: a retrospective cohort study.

Continuity of primary care (CPC) improves patient well-being, but the association between CPC and surgical outcomes has not been well studied. The numbers of joint replacement procedures are expected to rise considerably in the coming years, so it is crucial to identify factors related to successful outcomes. The purpose of this study was to examine the association between CPC and emergency department (ED) visits after knee and hip replacement surgery. Physician claims and hospital data from 2005 to 2020 in Nova Scotia were used in this retrospective study. To measure CPC, we used the Modified Modified Continuity Index (MMCI), which is the number of primary care providers adjusted for the total number of visits. The outcome was ED visits within 90 days of discharge. Logistic regression was used to test for associations between MMCI and the probability of an ED visit. There were 28 574 knee and 16 767 hip procedures in the data set; 13.9% (95% confidence interval [CI] 13.5%-14.3%) and 13.5% (95% CI 13.0%-14.0%) of the patients, respectively, had an ED visit within 90 days. For patients who underwent knee procedures, the mean MMCI was 0.868 (95% CI 0.867-0.870); 10.7% (95% CI 10.4 %-11.1 %) had perfect continuity of care. For patients who underwent hip procedures, the corresponding measures were 0.864 (95% CI 0.862-0.866) and 13.5% (95% CI 13.0%-14.0%). There was a statistically significant negative association between greater continuity of care and the probability of an ED visit after controlling for confounders. Having multiple primary care providers before surgery increased the likelihood of negative outcomes following knee or hip replacement surgery compared with having a single provider. Presurgical conversations should include primary care history to improve postsurgical outcomes.