Does Digital Inclusive Finance Promote Commercial Insurance Participation? -- An Empirical Study Based on the Digital Inclusive Finance Index and China Family Panel Studies Data

<p>This paper matches the "Peking University Digital Inclusive Finance Index" published by Peking University Digital Finance Research Center with the 2018 China Family Panel Studies (CFPS) database, and uses Probit and Logit models to empirically investigate the impact of digital inclusive finance on impact of household commercial insurance participation. The findings show that, first, the development of digital inclusive finance significantly increases commercial insurance participation, and this effect remains significant after adding control variables or changing models; second, the impact of digital inclusive finance on commercial insurance participation shows structural differences by urban-rural, regional, and risk preferences. At the urban-rural level, the impact of digital inclusive finance on commercial insurance participation is significantly higher in rural than in urban areas; at the regional level, the impact of digital inclusive finance is greater in western regions than in eastern and central regions; at the risk preference level, the impact of digital inclusive finance on commercial insurance participation is higher in risk-averse groups than in risk-averse groups. Based on the above findings, this paper proposes to accelerate the development of digital inclusive finance, especially focusing on the construction of digital inclusive finance in less developed regions; improve the financial market system, strengthen the supervision of insurance products; and increase the popularization of financial knowledge.</p>

Does Digital Inclusive Finance Promote Commercial Insurance Participation? -- An Empirical Study Based on the Digital Inclusive Finance Index and China Family Panel Studies Data

<p>This paper matches the "Peking University Digital Inclusive Finance Index" published by Peking University Digital Finance Research Center with the 2018 China Family Panel Studies (CFPS) database, and uses Probit and Logit models to empirically investigate the impact of digital inclusive finance on impact of household commercial insurance participation. The findings show that, first, the development of digital inclusive finance significantly increases commercial insurance participation, and this effect remains significant after adding control variables or changing models; second, the impact of digital inclusive finance on commercial insurance participation shows structural differences by urban-rural, regional, and risk preferences. At the urban-rural level, the impact of digital inclusive finance on commercial insurance participation is significantly higher in rural than in urban areas; at the regional level, the impact of digital inclusive finance is greater in western regions than in eastern and central regions; at the risk preference level, the impact of digital inclusive finance on commercial insurance participation is higher in risk-averse groups than in risk-averse groups. Based on the above findings, this paper proposes to accelerate the development of digital inclusive finance, especially focusing on the construction of digital inclusive finance in less developed regions; improve the financial market system, strengthen the supervision of insurance products; and increase the popularization of financial knowledge.</p>

Public and Commercial Medical Insurance Enrollment Rates of Rural-to-Urban Migrants in China

Objectives: Large-scale rural-to-urban migration of China has provoked heated discussion about the health of migrants and whether they have equal access to the health resources. This article aimed to compare the public and commercial medical insurance enrollment rates between temporary, permanent migrants and urban natives.Methods: Average marginal effects (AME) of the weighted logistic regression models using 2017 China General Social Survey from 2,068 urban natives, 1,285 temporary migrants, and 1,295 permanent migrants.Results: After controlling for the demographic and socio-economic characteristics, our results show that while the temporary and permanent migrants have a similar public insurance enrollment rate compared with the urban natives, both temporary and permanent migrants have significantly lower commercial insurance enrollment rates (7.5 and 5.3%, respectively) compared with the urban natives.Conclusions: The results highlight significant institutional barriers preventing the temporary migrants from gaining access to public medical insurance and the adverse impact of disadvantaged socio-economic backgrounds on the access of temporary migrants to both public and commercial insurance.

Hospitalization for Chemotherapy Toxicities (Chemotoxicities) during Treatment of Pediatric Hematologic Malignancies

Background: The projected 5y survival rates for pediatric hematologic malignancies exceed 85% (SEER statistics, 2017), in large part due to risk-stratified intensive multi-agent therapeutic approaches. However, these regimens result in chemotoxicity, often requiring hospitalization. However, the burden of chemotoxicity-related hospitalizations in children with hematologic malignancies remains understudied. Methods: Using an administrative claims database (Truven Marketscan ®), we describe chemotoxicity-related hospitalizations within the first 12 mo from first claim of chemotherapy in children with hematologic malignancies who were &lt;21y at diagnosis. Eligibility included (i) incident acute lymphoblastic leukemia (ALL; ICD-10-CM code: C91), acute myeloid leukemia (AML; C92), Hodgkin lymphoma (HL; C81) or non-Hodgkin lymphoma (NHL; C83.0, C83.3, C83.5, C83.7, C84.4, C85) diagnosed between 2011 and 2018; and (ii) continued insurance coverage 30d prior to and 365d after cancer diagnosis. Chemotoxicities (identified using ICD-9 and -10 codes) were grouped into organ systems (hematologic, infectious, gastrointestinal, renal, allergic, pulmonary, central nervous system, cardiovascular and miscellaneous). A hospitalization was considered chemotoxicity-related if a toxicity diagnosis was the primary reason for admission (i.e., first billing code) or occurred in the second billing position only if the cancer diagnosis was in the primary billing position. Hospitalizations for chemotherapy administration for primary or relapsed cancer were excluded. Logistic regression was used to examine the following factors for their association with chemotoxicity-related hospitalization: age at cancer diagnosis, sex, year of diagnosis (2011-2014; 2015-2018), insurance (commercial, Medicaid) and primary cancer diagnosis. Results: We identified 897 eligible patients (ALL: n=461, AML: n=79, HL: n=202, NHL: n=155). Median age at diagnosis was 15y (range, 0-21), 52.7% were male, 54.2% were diagnosed between 2011 and 2014, and 70.2% had commercial insurance. Medicaid patients were younger than those with commercial insurance (median age at diagnosis: 12y [range, 0.9-21] vs. 17y [0-21y]), and were less likely to carry a diagnosis of ALL (46% vs. 54%, P&lt;0.001) but more likely to have AML (15% vs. 6%, P&lt;0.001). Over the 4,736 person-months of follow-up, 360 patients (40.1%) had 636 chemotoxicity-related hospitalizations (ALL: 56.9%, AML: 8.9%, HL: 20.9%, NHL: 13.2%); 164 (18.3%) patients had ≥1 chemotoxicity-related hospitalization. Median time to first chemotoxicity-related hospitalization from start of therapy was 37d (interquartile range, 12-78). Chemotoxicity claims included hematologic toxicities (63.6%), infections (22.7%) and gastrointestinal toxicities (6.1%); the figure shows the distribution of claims during these hospitalizations by hematologic malignancy. The average length of stay (LOS) for chemotoxicity-related hospitalization was 6.8±8.7d [5.8±7.8d (HL) to 8.6±12.6d (AML)]. Multivariable logistic regression analysis identified Medicaid insurance (vs. commercial) to be associated with lower odds of chemotoxicity-related hospitalization (odds ratio=0.68, 95% confidence interval 0.56-0.84, P&lt;0.001). Conclusions: Over 40% of children with hematologic malignancies require chemotoxicity-related hospitalizations during the first year of treatment. These data could be used to provide guidance to patients and their families and inform healthcare policy decisions. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.