At-Home Versus In-Clinic INR Monitoring: A Cost-Utility Analysis from The Home INR Study (THINRS).

BACKGROUND: Effective management of patients using warfarin is resource-intensive, requiring frequent in-clinic testing of the international normalized ratio (INR). Patient self-testing (PST) using portable at-home INR monitoring devices has emerged as a convenient alternative. As revealed by The Home INR Study (THINRS), event rates for PST were not significantly different from those for in-clinic high-quality anticoagulation management (HQACM), and a cumulative gain in quality of life was observed for patients undergoing PST. OBJECTIVE: To perform a cost-utility analysis of weekly PST versus monthly HQACM and to examine the sensitivity of these results to testing frequency. PATIENTS/INTERVENTIONS: In this study, 2922 patients taking warfarin for atrial fibrillation or mechanical heart valve, and who demonstrated PST competence, were randomized to either weekly PST (n = 1465) or monthly in-clinic testing (n = 1457). In a sub-study, 234 additional patients were randomized to PST once every 4 weeks (n = 116) or PST twice weekly (n = 118). The endpoints were quality of life (measured by the Health Utilities Index), health care utilization, and costs over 2 years of follow-up. RESULTS: PST and HQACM participants were similar with regard to gender, age, and CHADS2 score. The total cost per patient over 2 years of follow-up was $32,484 for HQACM and $33,460 for weekly PST, representing a difference of $976. The incremental cost per quality-adjusted life year gained with PST once weekly was $5566 (95 % CI, -$11,490 to $25,142). The incremental cost-effectiveness ratio (ICER) was sensitive to testing frequency: weekly PST dominated PST twice weekly and once every 4 weeks. Compared to HQACM, weekly PST was associated with statistically significant and clinically meaningful improvements in quality of life. The ICER for weekly PST versus HQACM was well within accepted standards for cost-effectiveness, and was preferred over more or less frequent PST. These results were robust to sensitivity analyses of key assumptions. CONCLUSION: Weekly PST is a cost-effective alternative to monthly HQACM and a preferred testing frequency compared to twice weekly or monthly PST.

Implications of long-term care capacity response policies for an aging population: a simulation analysis.

INTRODUCTION: The demand for long-term care (LTC) services is likely to increase as a population ages. Keeping pace with rising demand for LTC poses a key challenge for health systems and policymakers, who may be slow to scale up capacity. Given that Singapore is likely to face increasing demand for both acute and LTC services, this paper examines the dynamic impact of different LTC capacity response policies, which differ in the amount of time over which LTC capacity is increased, on acute care utilization and the demand for LTC and acute care professionals. METHODS: The modeling methodology of System Dynamics (SD) was applied to create a simplified, aggregate, computer simulation model for policy exploration. This model stimulates the interaction between persons with LTC needs (i.e., elderly individuals aged 65 years and older who have functional limitations that require human assistance) and the capacity of the healthcare system (i.e., acute and LTC services, including community-based and institutional care) to provide care. Because the model is intended for policy exploration, stylized numbers were used as model inputs. To discern policy effects, the model was initialized in a steady state. The steady state was disturbed by doubling the number of people needing LTC over the 30-year simulation time. Under this demand change scenario, the effects of various LTC capacity response policies were studied and sensitivity analyses were performed. RESULTS: Compared to proactive and quick adjustment LTC capacity response policies, slower adjustment LTC capacity response policies (i.e., those for which the time to change LTC capacity is longer) tend to shift care demands to the acute care sector and increase total care needs. CONCLUSIONS: Greater attention to demand in the acute care sector relative to demand for LTC may result in over-building acute care facilities and filling them with individuals whose needs are better suited for LTC. Policymakers must be equally proactive in expanding LTC capacity, lest unsustainable acute care utilization and significant deficits in the number of healthcare professionals arise. Delaying LTC expansion could, for example, lead to increased healthcare expenditure and longer wait lists for LTC and acute care patients.

Simulating the impact of long-term care policy on family eldercare hours.

OBJECTIVE: To understand the effect of current and future long-term care (LTC) policies on family eldercare hours for older adults (60 years of age and older) in Singapore. DATA SOURCES: The Social Isolation Health and Lifestyles Survey, the Survey on Informal Caregiving, and the Singapore Government's Ministry of Health and Department of Statistics. STUDY DESIGN: An LTC Model was created using system dynamics methodology and parameterized using available reports and data as well as informal consultation with LTC experts. PRINCIPAL FINDINGS: In the absence of policy change, among the elderly living at home with limitations in their activities of daily living (ADLs), the proportion of those with greater ADL limitations will increase. In addition, by 2030, average family eldercare hours per week are projected to increase by 41 percent from 29 to 41 hours. All policy levers considered would moderate or significantly reduce family eldercare hours. CONCLUSION: System dynamics modeling was useful in providing policy makers with an overview of the levers available to them and in demonstrating the interdependence of policies and system components.

Expert estimates of caregiver hours for older Singaporeans with dementia.

AIM: To obtain experts' estimates of the number of non-medical care hours required by older Singaporeans at different stages of ageing-related dementia, with low or high behavioural features. METHODS: Experts on dementia in Singapore attended one of two meetings where they provided estimates of the number of care hours required for individuals at mild, moderate and severe levels of dementia with either low or high behavioural features. The experts were shown the collated responses, given an opportunity to discuss as a group, and then polled again. RESULTS: The estimated mean care hours varied by dementia severity and the level of behavioural features. There was no interaction between dementia severity and behavioural features. CONCLUSION: Estimated care hours needed by individuals with dementia is independently influenced by severity of dementia and behavioural features. These estimates may be useful for policy-makers in projecting the impact of caregiving.