The Reliability of Instrumental Variables in Health Care Effectiveness Research: Less Is More.
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ABSTRACT:
SUBMITTER: Soumerai SB
PROVIDER: S-EPMC5264014 | biostudies-literature | 2017 Feb
REPOSITORIES: biostudies-literature
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The Reliability of Instrumental Variables in Health Care Effectiveness Research: Less Is More.
Soumerai Stephen B SB Koppel Ross R
Health services research 20160721 1
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Project description:ObjectivesTo demonstrate how falsification tests can be used to evaluate instrumental variables methods applicable to a wide variety of comparative effectiveness research questions.Study designBrief conceptual review of instrumental variables and falsification testing principles and techniques accompanied by an empirical application. Sample STATA code related to the empirical application is provided in the Appendix.Empirical applicationComparative long-term risks of sulfonylureas and thiazolidinediones for management of type 2 diabetes. Outcomes include mortality and hospitalization for an ambulatory care-sensitive condition. Prescribing pattern variations are used as instrumental variables.ConclusionsFalsification testing is an easily computed and powerful way to evaluate the validity of the key assumption underlying instrumental variables analysis. If falsification tests are used, instrumental variables techniques can help answer a multitude of important clinical questions.
| S-EPMC4799892 | biostudies-literature
Project description: Not available
| S-EPMC6505571 | biostudies-literature
Project description:ObjectiveTo investigate potential bias in the use of the conventional linear instrumental variables (IV) method for the estimation of causal effects in inherently nonlinear regression settings.Data sourcesSmoking Supplement to the 1979 National Health Interview Survey, National Longitudinal Alcohol Epidemiologic Survey, and simulated data.Study designPotential bias from the use of the linear IV method in nonlinear models is assessed via simulation studies and real world data analyses in two commonly encountered regression setting: (1) models with a nonnegative outcome (e.g., a count) and a continuous endogenous regressor; and (2) models with a binary outcome and a binary endogenous regressor.Principal findingsThe simulation analyses show that substantial bias in the estimation of causal effects can result from applying the conventional IV method in inherently nonlinear regression settings. Moreover, the bias is not attenuated as the sample size increases. This point is further illustrated in the survey data analyses in which IV-based estimates of the relevant causal effects diverge substantially from those obtained with appropriate nonlinear estimation methods.ConclusionsWe offer this research as a cautionary note to those who would opt for the use of linear specifications in inherently nonlinear settings involving endogeneity.
| S-EPMC2442231 | biostudies-literature
Project description:The use of genetic markers as instrumental variables (IV) is receiving increasing attention from economists, statisticians, epidemiologists and social scientists. Although IV is commonly used in economics, the appropriate conditions for the use of genetic variants as instruments have not been well defined. The increasing availability of biomedical data, however, makes understanding of these conditions crucial to the successful use of genotypes as instruments. We combine the econometric IV literature with that from genetic epidemiology, and discuss the biological conditions and IV assumptions within the statistical potential outcomes framework. We review this in the context of two illustrative applications.
| S-EPMC4770870 | biostudies-literature
Project description:OBJECTIVE:To compare the quality of care following admission to a nursing home (NH) with and without a dementia special care unit (SCU) for residents with dementia. DATA SOURCES/STUDY SETTING:National resident-level minimum dataset assessments (MDS) 2005-2010 merged with Medicare claims and provider-level data from the Online Survey, Certification, and Reporting database. STUDY DESIGN:We employ an instrumental variable approach to address the endogeneity of selection into an SCU facility controlling for a range of individual-level covariates. We use "differential distance" to a nursing home with and without an SCU as our instrument. DATA COLLECTION/EXTRACTION METHODS:Minimum dataset assessments performed at NH admission and every quarter thereafter. PRINCIPAL FINDINGS:Admission to a facility with an SCU led to a reduction in inappropriate antipsychotics (-9.7 percent), physical restraints (-9.6 percent), pressure ulcers (-3.3 percent), feeding tubes (-8.3 percent), and hospitalizations (-14.7 percent). We found no impact on the use of indwelling urinary catheters. Results held in sensitivity analyses that accounted for the share of SCU beds and the facilities' overall quality. CONCLUSIONS:Facilities with an SCU provide better quality of care as measured by several validated quality indicators. Given the aging population, policies to promote the expansion and use of dementia SCUs may be warranted.
| S-EPMC6153167 | biostudies-literature
Project description:BackgroundIn this paper, we argue for Gender as a Sociocultural Variable (GASV) as a complement to Sex as a Biological Variable (SABV). Sex (biology) and gender (sociocultural behaviors and attitudes) interact to influence health and disease processes across the lifespan-which is currently playing out in the COVID-19 pandemic. This study develops a gender assessment tool-the Stanford Gender-Related Variables for Health Research-for use in clinical and population research, including large-scale health surveys involving diverse Western populations. While analyzing sex as a biological variable is widely mandated, gender as a sociocultural variable is not, largely because the field lacks quantitative tools for analyzing the influence of gender on health outcomes.MethodsWe conducted a comprehensive review of English-language measures of gender from 1975 to 2015 to identify variables across three domains: gender norms, gender-related traits, and gender relations. This yielded 11 variables tested with 44 items in three US cross-sectional survey populations: two internet-based (N = 2051; N = 2135) and a patient-research registry (N = 489), conducted between May 2017 and January 2018.ResultsExploratory and confirmatory factor analyses reduced 11 constructs to 7 gender-related variables: caregiver strain, work strain, independence, risk-taking, emotional intelligence, social support, and discrimination. Regression analyses, adjusted for age, ethnicity, income, education, sex assigned at birth, and self-reported gender identity, identified associations between these gender-related variables and self-rated general health, physical and mental health, and health-risk behaviors.ConclusionOur new instrument represents an important step toward developing more comprehensive and precise survey-based measures of gender in relation to health. Our questionnaire is designed to shed light on how specific gender-related behaviors and attitudes contribute to health and disease processes, irrespective of-or in addition to-biological sex and self-reported gender identity. Use of these gender-related variables in experimental studies, such as clinical trials, may also help us understand if gender factors play an important role as treatment-effect modifiers and would thus need to be further considered in treatment decision-making.
| S-EPMC7898259 | biostudies-literature
Project description:In skin and wound research the instrumental measurement of skin function is established. Despite the widespread use, empirical evidence about measurement errors is widely lacking. The aim of this study was to measure reliability and agreement of skin temperature, transepidermal water loss, epidermal hydration, and erythema at the heel and sacral skin. Four experienced researchers performed skin measurements in 15 subjects. Lowest reliability was observed for transepidermal water loss at the sacral skin (ICC (1) 0.46 (95% CI 0.00-0.78)) and highest for skin temperature at the heel skin (ICC (1) 0.99 (95% CI 0.99-1.00)). Lowest Standard Errors of Measurement were calculated for skin temperature measurements at the heels (0.11°C) and highest for erythema measurements at the sacral skin (26.7 arbitrary units). There was a clear association between variability of estimates and reliability coefficients. Single measurements of skin temperature, stratum corneum, and epidermal hydration at the sacral and heel skin areas can be used in clinical research and practice. Means of at least two measurements should be used for estimating transepidermal water loss and erythema. Evidence is needed to inform researchers about relative and absolute measurement errors of commonly applied instruments and measurements in skin and wound research.
| S-EPMC8450794 | biostudies-literature
Project description:BackgroundThis article demonstrates a means of assessing long-term intervention cost-effectiveness in the absence of data from randomized controlled trials and without recourse to Markov simulation or similar types of cohort simulation.MethodsUsing a Mendelian randomization study design, we developed causal estimates of the genetically predicted effect of bladder, breast, colorectal, lung, multiple myeloma, ovarian, prostate, and thyroid cancers on health care costs and quality-adjusted life-years (QALYs) using outcome data drawn from the UK Biobank cohort. We then used these estimates in a simulation model to estimate the cost-effectiveness of a hypothetical population-wide preventative intervention based on a repurposed class of antidiabetic drugs known as sodium-glucose cotransporter-2 (SGLT2) inhibitors very recently shown to reduce the odds of incident prostate cancer.ResultsGenetic liability to prostate cancer and breast cancer had material causal impacts on either or both health care costs and QALYs. Mendelian randomization results for the less common cancers were associated with considerable uncertainty. SGLT2 inhibition was unlikely to be a cost-effective preventative intervention for prostate cancer, although this conclusion depended on the price at which these drugs would be offered for a novel anticancer indication.ImplicationsOur new causal estimates of cancer exposures on health economic outcomes may be used as inputs into decision-analytic models of cancer interventions such as screening programs or simulations of longer-term outcomes associated with therapies investigated in randomized controlled trials with short follow-ups. Our method allowed us to rapidly and efficiently estimate the cost-effectiveness of a hypothetical population-scale anticancer intervention to inform and complement other means of assessing long-term intervention value.HighlightsThe article demonstrates a novel method of assessing long-term intervention cost-effectiveness without relying on randomized controlled trials or cohort simulations.Mendelian randomization was used to estimate the causal effects of certain cancers on health care costs and quality-adjusted life-years (QALYs) using data from the UK Biobank cohort.Given causal data on the association of different cancer exposures on costs and QALYs, it was possible to simulate the cost-effectiveness of an anticancer intervention.Genetic liability to prostate cancer and breast cancer significantly affected health care costs and QALYs, but the hypothetical intervention using SGLT2 inhibitors for prostate cancer may not be cost-effective, depending on the drug's price for the new anticancer indication. The methods we propose and implement can be used to efficiently estimate intervention cost-effectiveness and to inform decision making in all manner of preventative and therapeutic contexts.
| S-EPMC10988994 | biostudies-literature
Project description:PurposeNursing home residents are of particular interest for comparative effectiveness research given their susceptibility to adverse treatment effects and systematic exclusion from trials. However, the risk of residual confounding because of unmeasured markers of declining health using conventional analytic methods is high. We evaluated the validity of instrumental variable (IV) methods based on nursing home prescribing preference to mitigate such confounding, using psychotropic medications to manage behavioral problems in dementia as a case study.MethodsA cohort using linked data from Medicaid, Medicare, Minimum Data Set, and Online Survey, Certification and Reporting for 2001-2004 was established. Dual-eligible patients ≥65 years who initiated psychotropic medication use after admission were selected. Nursing home prescribing preference was characterized using mixed-effects logistic regression models. The plausibility of IV assumptions was explored, and the association between psychotropic medication class and 180-day mortality was estimated.ResultsHigh-prescribing and low-prescribing nursing homes differed by a factor of 2. Each preference-based IV measure described a substantial proportion of variation in psychotropic medication choice (β(IV → treatment): 0.22-0.36). Measured patient characteristics were well balanced across patient groups based on instrument status (52% average reduction in Mahalanobis distance). There was no evidence that instrument status was associated with markers of nursing home quality of care.ConclusionFindings indicate that IV analyses using nursing home prescribing preference may be a useful approach in comparative effectiveness studies, and should extend naturally to analyses including untreated comparison groups, which are of great scientific interest but subject to even stronger confounding.
| S-EPMC4116440 | biostudies-literature
Project description:BackgroundPatients with venous thromboembolism (VTE) require access to comprehensive physician and pharmacy benefits to prevent recurrence and hemorrhage. Before 2006, Massachusetts provided these benefits through a program restricted to safety net hospitals called Free Care. Providing portable health insurance through Massachusetts health reform could improve outcomes for uninsured with VTE but its cost-effectiveness is unknown.Methods and resultsWe constructed a Markov decision analysis model comparing our conceptualization of the Massachusetts health reform (health reform strategy) to no health reform strategy for a patient beginning warfarin for new episode of VTE. In the model, a patient may develop recurrent VTE or develop hemorrhage or stop warfarin after 6 months if no event occurs. To measure effectiveness, we analyzed laboratory data from Boston Medical Center, the largest safety net hospital in Massachusetts. Specifically, we measured the probability of having a subtherapeutic warfarin level for patients newly insured compared with those on Free Care prereform adjusting for secular trends. To calculate inpatient costs, we used the Health Care Utilization Project. We then calculated the incremental cost-effectiveness ratio for the health reform strategy adjusted to 2014 USD per quality-adjusted life-year (QALY) and performed sensitivity analyses. The health reform strategy cost less and gained more QALYs than the no health reform strategy. Our result was most sensitive to the odds that Health Reform protected against a subtherapeutic warfarin level, the cost of Health Reform, and the percentage of total health care costs attributable to VTE in Massachusetts.ConclusionThe health reform strategy cost less and was more effective than the no health reform strategy for patients with VTE.
| S-EPMC4833580 | biostudies-literature