The Impacts of Long-Term Care Insurance on Health Care Utilization and Expenditure: Evidence From China

Long-term care insurance (LTCI) is one of the important institutional responses to the growing care needs of the ageing population. Although previous studies have evaluated the impacts of LTCI on health care utilization and expenditure in developed countries, whether such impacts exist in developing countries is unknown. The Chinese government has initiated policy experimentation on LTCI to cope with the growing and unmet need for aged care. Employing a quasi-experiment design, this study aims to examine the policy treatment effect of LTCI on health care utilization and out-of-pocket health expenditure in China. The Propensity Score Matching with Difference-in-difference approach was used to analyse the data obtained from four waves of China Health and Retirement Longitudinal Study (CHARLS). Our findings indicated that, in the aspect of health care utilization, the introduction of LTCI significantly reduced the number of outpatient visits by 0.322 times (p<0.05), the number of hospitalizations by 0.158 times (p<0.01), and the length of inpatient stay during last year by 1.441 days (p<0.01). In the aspect of out-of-pocket health expenditure, we found that LTCI significantly reduced the inpatient out-of-pocket health expenditure during last year by 533.47 yuan (p<0.01), but it did not exhibit an impact on the outpatient out-of-pocket health expenditure during last year. LTCI also had a significantly negative impact on the total out-of-pocket health expenditure by 512.56 yuan. These results are stable in the robustness tests. Considering the evident policy treatment effect of LTCI on health care utilization and out-of-pocket health expenditure, the expansion of LTCI could help reduce the needs for health care services and contain the increases in out-of-pocket health care expenditure in China.

Healthcare utilization and costs among high-need and frail Mexican American Medicare beneficiaries

Objectives To examine Medicare health care spending and health services utilization among high-need population segments in older Mexican Americans, and to examine the association of frailty on health care spending and utilization. Methods Retrospective cohort study of the innovative linkage of Medicare data with the Hispanic Established Populations for the Epidemiologic Study of the Elderly (H-EPESE) were used. There were 863 participants, which contributed 1,629 person years of information. Frailty, cognition, and social risk factors were identified from the H-EPESE, and chronic conditions were identified from the Medicare file. The Cost and Use file was used to calculate four categories of Medicare spending on: hospital services, physician services, post-acute care services, and other services. Generalized estimating equations (GEE) with a log link gamma distribution and first order autoregressive, correlation matrix was used to estimate cost ratios (CR) of population segments, and GEE with a logit link binomial distribution was applied to estimate odds ratios (OR) of healthcare use. Results Participants in the major complex chronic illness segment who were also pre-frail or frail had higher total costs and utilization compared to the healthy segment. The CR for total Medicare spending was 3.05 (95% CI, 2.48–3.75). Similarly, this group had higher odds of being classified in the high-cost category 5.86 (95% CI, 3.35–10.25), nursing home care utilization 11.32 (95% CI, 3.88–33.02), hospitalizations 4.12 (95% CI, 2.88–5.90) and emergency room admissions 4.24 (95% CI, 3.04–5.91). Discussion Our findings highlight that frailty assessment is an important consideration when identifying high-need and high-cost patients.

Home Health Care Utilization in Children With Medicaid

BACKGROUND: Although many children with medical complexity (CMC) use home health care (HHC), little is known about all pediatric HHC utilizers. Our objective was to assess characteristics of pediatric HHC recipients, providers, and payments. METHODS: We conducted a retrospective analysis of 5 209 525 children age 0-to-17 years enrolled Medicaid in the 2016 IBM Watson MarketScan Medicaid Database. HHC utilizers had ≥ 1 HHC claim. Healthcare Common Procedure Coding System (HCPCS) and Current Procedural Terminology (CPT) codes were reviewed to codify provider types when possible: registered nurse (RN), licensed practical nurse (LPN), home health aide (HHA), certified nursing assistant (CNA), or companion/personal attendant. Enrollee clinical characteristics, HHC provider type, and payments were assessed. Chronic conditions were evaluated with Agency for Healthcare Research and Quality’s Chronic Condition Indicators and Feudtner’s Complex Chronic Conditions. RESULTS: Of the 0.8% of children who used HHC, 43.8% were age <1 year, 25% had no chronic condition, 38.6% had a noncomplex chronic condition, 21.5% had a complex chronic condition without technology assistance, and 15.5% had technology assistance (eg, tracheostomy). HHC for children with technology assistance accounted for 72.6% of all HHC spending. Forty-five percent of HHC utilizers received RN/LPN-level care, 7.9% companion/personal attendant care, 5.9% HHA/CNA-level care, and 36% received care from an unspecified provider. For children with technology assistance, the majority (77.2%) received RN/LPN care, 17.5% companion/personal assistant care, and 13.8% HHA/CNA care. CONCLUSIONS: Children using HHC are a heterogeneous population who receive it from a variety of providers. Future investigations should explore the role of nonnurse caregivers, particularly with CMC.

Age, gender, and residence differences in prevalence and patterns of multimorbidity among older Chinese: Evidence from Chinese Longitudinal Healthy Longevity Survey

Background With the dramatic acceleration of ageing in China, multimorbidity among the older adults has become increasingly common，which are associated with more functional decline and higher health care utilization and mortality. Understanding demographic differences of patterns of multimorbidity is in favor of making targeted intervention strategies. The purpose of this study was to reveal age- specific, gender- specific, and residence- specific prevalence and patterns of multimorbidity among older adults in China. Methods The present analysis is based on the 2018 wave of Chinese Longitudinal Health Longevity Survey (CLHLS). We selected 13 chronic diseases from the CLHLS survey, and information was collected based on self-report. Multimorbidity was defined as the coexistence of two or more chronic diseases from 13 chronic diseases in the same individual. Descriptive statistical analysis was used to examine multimorbidity according to age, sex, and residence. Patterns and trends of chronic disease pairs and multimorbidity were explored using association rule mining. Results 9,660 individuals aged 65-117 years in the CLHLS were analyzed in this study. Overall, 74.4% of all participants had one or more morbidities, and 42.4% were multimorbid. The prevalence of individual chronic diseases ranged from 1.5% for cancer to 41.8% for hypertension, and each disease was often accompanied by one or more other chronic diseases. The prevalence of multimorbidity does not always increase with age. The subgroups with the highest prevalence of multimorbidity was 80-89 years old (48.2%), female (45.0%) and urban (47.2%) group. Prevalence of the hypertension- diabetes pattern decreases with age and is higher in women than in men. The prevalence of hypertension- depression pattern was at the highest among the 90-117 years and rural older adults, while the other groups were hypertension-heart disease. Moreover, it was noteworthy that the multimorbidity rate of dyslipidemia is the highest at 95.5% among the 13 chronic diseases. Conclusions The prevalence of multimorbidity among older Chinese was substantial, and patterns of multimorbidity differed in age, sex, and residence. Future efforts are needed to identify possible prevention strategies and guidelines targeted demographic differences of multimorbid patients to promote health in older adults.

Approaches to Evaluations of Virtual Care in Primary Care

A literature search informed this Environmental Scan and identified 11 evaluations of virtual care in primary care health settings and 7 publications alluding to methods, standards, and guidelines (referred to as evaluation guidance documents in this report) being used in various countries to evaluate virtual care in primary care health settings. The majority of included literature was from Australia, the US, and the UK, with 2 evaluation guidance documents published by the Heart and Stroke Foundation of Canada. Evaluation guidance documents recommended using measurements that assess the effectiveness and quality of clinical care including safety outcomes, time and travel, financial and operational impact, participation, health care utilization, technology experience including feasibility, user satisfaction, and barriers and facilitators or measures of health equity. Evaluation guidance documents specified that the following key decisions and considerations should be integrated into the planning of a virtual care evaluation: refining the scope of virtual care services; selecting an appropriate meaningful comparator; and identifying opportune timing and duration for the evaluation to ensure the evaluation is reflective of real-world practice, allows for adequate measurement of outcomes, and is comprehensive, timely, feasible, non-complex, and non–resource-intensive. Evaluation guidance documents highlighted that evaluations should be systematic, performed regularly, and reflect the stage of virtual care implementation to encompass the specific considerations associated with each stage. Additionally, evaluations should assess individual virtual care sessions and the virtual care program as a whole. Regarding economic components of virtual care evaluations, the evaluation guidance documents noted that costs or savings are not limited to monetary or financial measures but can also be represented with time. Cost analyses such as cost-benefit and cost-utility estimates should be performed with a specific emphasis on selecting an appropriate perspective (e.g., patient or provider), as that influences the benefits, effects, and how the outcome is interpreted. Two identified evaluations assessed economic outcomes through cost analyses in the perspective of the patient and provider. Evidence suggests that, in some circumstances, virtual care may be more cost-effective and reduces the cost per episode and patient expenses (e.g., travel and parking costs) compared to in-person care. However, virtual care may increase the number of individuals treated, which would increase overall health care spending. Four identified evaluations assessed health care utilization. The evidence suggests that virtual care reduces the duration of appointments and may be more time-efficient compared to in-person care. However, it is unclear if virtual care reduces the use of medical resources and the need for follow-up appointments, hospital admissions, and emergency department visits compared to in-person care. Five identified evaluations assessed participation outcomes. Evidence was variable, with some evidence reporting that virtual care reduced attendance (e.g., reduced attendance rates) and other evidence noting improved attendance (e.g., increased completion rate and decreased cancellations and no-show rates) compared to in-person care. Three identified evaluations assessed clinical outcomes in various health contexts. Some evidence suggested that virtual care improves clinical outcomes (e.g., in primary care with integrated mental health services, symptom severity decreased) or has a similar effect on clinical outcomes compared to in-person care (e.g., use of virtual care in depression elicited similar results with in-person care). Three identified evaluations assessed the appropriateness of prescribing. Some studies suggested that virtual care improves appropriateness by increasing guideline-based or guideline-concordant antibiotic management, or elicits no difference with in-person care.

Health care utilization following “digi-physical” assessment compared to physical assessment for infectious symptoms in primary care

Background The use of chat-based digital visits (eVisits) to assess infectious symptoms in primary care is rapidly increasing. The “digi-physical” model of care uses eVisits as the first line of assessment while assuming a certain proportion of patients will inevitably need to be further assessed through urgent physical examination within 48 h. It is unclear to what extent this approach can mitigate physical visits compared to assessing patients directly using office visits. Methods This pre-COVID-19-pandemic observational study followed up “digi-physical” eVisit patients (n = 1188) compared to office visit patients (n = 599) with respiratory or urinary symptoms. Index visits occurred between March 30th 2016 and March 29th 2019. The primary outcome was subsequent physical visits to physicians within two weeks using registry data from Skåne county, Sweden (Region Skånes Vårddatabas, RSVD). Results No significant differences in subsequent physical visits within two weeks (excluding the first 48 h) were noted following “digi-physical” care compared to office visits (179 (18.0%) vs. 102 (17.6%), P = .854). As part of the “digital-physical” concept, a significantly larger proportion of eVisit patients had a physical visit within 48 h compared to corresponding office visit patients (191 (16.1%) vs. 19 (3.2%), P < .001), with 150 (78.5%) of these eVisit patients recommended some form of follow-up by the eVisit physician. Conclusions Most eVisit patients (68.9%) with respiratory and urinary symptoms have no subsequent physical visits. Beyond an unavoidable portion of patients requiring urgent physical examination within 48 h, “digi-physical” management of respiratory and urinary symptoms results in comparable subsequent health care utilization compared to office visits. eVisit providers may need to optimize use of resources to minimize the proportion of patients being assessed both digitally and physically within 48 h as part of the “digi-physical” concept. Trial registration Clinicaltrials.gov identifier: NCT03474887.

Prevalence and Predictors of Palliative Care Utilization among Hospitalized Patients with Diffuse Large B-Cell Lymphoma

Objective: Research has shown that palliative care improves the quality of life of cancer patients; however, there is no literature on specific factors that predict its use in diffuse large b-cell lymphoma (DLBCL) patients. Therefore, the prevalence of palliative care utilization and predictors of palliative care utilization among patients with DLBCL were examined. Methods: Data from the National Inpatient Sample (NIS) collected between 2016 to 2018 were used for all analyses. Multivariable logistic regression models were used to examine the predictors of palliative care utilization among hospitalized patients with DLBCL. Descriptive analyses were used to explore the overall prevalence of palliative care receipt in this population. Results: Of the 41,789 hospitalizations, 7.1% of patients used palliative care during hospitalization, while 4.8% utilized palliative care and were discharged alive. DLBCL patients aged 70 and older had 1.3 times (95% CI: 1.14-1.41) higher odds of utilizing palliative care compared to those less than 70 years. Relative to Medicare/Medicaid patients, those with other types of insurance were 1.7 times (95% CI: 1.34-2.05) more likely to receive palliative care. Those who were either transferred to a facility/discharged with home health (AOR: 6.23; 95% CI: 5.21-7.44) or died during hospitalization (AOR: 45.17; 95% CI: 36.98-55.17) had higher odds of receiving palliative care when relative to those with a routine hospital discharge. Other associated factors were type of admission, length of stay, chemotherapy receipt, and number of comorbidities. Conclusions: The prevalence of palliative care utilization was low and factors predicting utilization in our population were identified. Our findings highlight the need to increase awareness among medical oncologists on the need to involve the palliative care team early in the management of hospitalized patients with DLBCL.