Modelling the size, cost and health impacts of universal basic income: What can be done in advance of a trial?
AbstractOpposition to Universal Basic Income (UBI) is encapsulated by Martinelli ’s claim that ‘an affordable basic income would be inadequate, and an adequate basic income would be unaffordable’. In this article, we present a model of health impact that transforms that assumption. We argue that UBI can affect higher level social determinants of health down to individual d eterminants of health and on to improvements in public health that lead to a number of economic returns on investment. Given that no trial has been designed and deployed with that impact in mind, we present a methodological framework fo...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

The ADI-3: a revised neighborhood risk index of the social determinants of health over time and place
AbstractSince its development, Singh ’s 2003 Area Deprivation Index (ADI) has been routinely used by researchers to measure a global construct of neighborhood socioeconomic deprivation and to investigate how living in neighborhoods of different levels of socioeconomic deprivation affects individuals’ health. We empirically tested t he ADI’s dimensionality, using 2013–2017 American Community Survey tract-level estimates (N = 73,056), and the stability of its performance across time and place. Factor analysis findings illuminated three distinct dimensions, the ADI-3, consisting of neighb...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Which patients benefit most from completing health risk assessments: comparing methods to identify heterogeneity of treatment effects
AbstractMethods for identifying heterogeneity of treatment effects in randomized trials have seen recent advances, yet applying these methods to health services intervention trials has not been well investigated. Our objective was to compare two approaches —predictive risk modeling and model-based recursive partitioning—for identifying subgroups of trial participants with potentially differential response to an intervention involving health risk assessment completion alone (n = 192) versus health risk assessment completion plus telephone-deliv ered health coaching (n = 173). Notably,...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Authentic assessments: a method to detect anomalies in assessment response patterns via neural network
In this study, we propose a hybrid unsupervised-supervised approach to identify inauthentic assessments via anomalous response patterns. The study utilized 60-question behavioral assessment from a clinical population served by a county-operated public children ’s behavioral health services (n = 42,945). A novel hybrid unsupervised-supervised approach was developed to identify inauthentic assessment records from highly dimensional assessment data without the need for a priori record labels, which would otherwise require countless hours of record revi ew by highly trained clinical staff. A neural network ...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Distinguishing frontloading: an examination of medicare home health claims
This study examines visit characteristics of post-acute home health episodes for heart failure patients in the Medicare fee-for-service population and explores whether alternative definitions can empirically distinguish frontloaded episodes. Using 100% Medicare claims and enrollment data for 2016 and 2017, we descriptively examine the first post-acute home health episodes occurring after discharge for patients with heart failure as a primary diagnosis. We use the number and timing of visits during 60-day episodes highlight two definitions of frontloading related to the existing empirical literature. Among heart failure hom...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Using a spatiotemporal model to estimate the impact of suicide prevention in small areas
We describe a novel application of a spatiotemporal model developed for disease mapping to assess the impact of suicide prevention in small areas. As an example, we use small counties exposed to the Garrett Lee Smith (GLS) program. Specifically, the impact of suicide prevention programming on suicide-related hospital use among youth between 2008 and 2018 was explored with this novel method in a sample of rural counties across 10 states. While, on average, suicide-related hospital use was close to what would be expected in the absence of the program, there was considerable variation across counties. For example, among a gro...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Heterogeneous treatment effects and bias in the analysis of the stepped wedge design
AbstractThe effect of an intervention in a stepped wedge design can vary across clusters or with time since exposure to treatment, but consequences of such heterogeneous treatment effects for the analysis of stepped wedge designs are not well recognized. In this article, we advance the idea that the stepped wedge design can be framed as a special case of a difference-in-differences design with staggered treatment exposure. Using this perspective, we show that the standard difference-in-differences regression approach estimates the average treatment effect of the treatment period with bias when treatment effects vary by clu...
Source: Health Services and Outcomes Research Methodology - November 22, 2021 Category: Statistics Source Type: research

Estimating heterogeneous policy impacts using causal machine learning: a case study of health insurance reform in Indonesia
AbstractPolicymakers seeking to target health policies efficiently towards specific population groups need to know which individuals stand to benefit the most from each of these policies. While traditional approaches for subgroup analyses are constrained to only consider a small number of pre-defined subgroups, recently proposed causal machine learning (CML) approaches help explore treatment-effect heterogeneity in a more flexible yet principled way. Causal forests use a generalisation of the random forest algorithm to estimate heterogenous treatment effects both at the individual and the subgroup level. Our paper aims to ...
Source: Health Services and Outcomes Research Methodology - November 9, 2021 Category: Statistics Source Type: research

Incidence rate and financial burden of medical errors and policy interventions to address them: a multi-method study protocol
AbstractMedical error is one of the most critical challenges facing medical services. They pose a substantial threat to patient safety, and their costs draw attention from policymakers, health care planners and researchers. We aim to make a realistic estimation of medical error incidence and related costs and identify factors influencing this incidence in Iranian hospitals. In the first phase of this multi-method study, through two reviews of systematic reviews and a meta-analysis, we will estimate the incidence of medical errors and the strategies to reduce them. We will extract available data among 41 hospitals supervise...
Source: Health Services and Outcomes Research Methodology - November 5, 2021 Category: Statistics Source Type: research

Advanced models for improved prediction of opioid-related overdose and suicide events among Veterans using administrative healthcare data
In this study we propose changes to the original STORM model and propose alternative models that improve risk prediction performance. The best of these proposed models uses a multivariate generalized linear mixed modeling (mGLMM) approach to produce separate predictions for overdose and suicide-related events (SRE) rather than a single prediction for combined outcomes. Further improvements include incorporation of additional data sources and new predictor variables in a longitudinal setting. Compared to a modified version of the STORM model with the same outcome, predictor and interaction terms, our proposed model has a si...
Source: Health Services and Outcomes Research Methodology - November 2, 2021 Category: Statistics Source Type: research

Is Medicaid misreporting stable over time? Self-reported health insurance coverage of Medicaid recipients in Louisiana, 2007 –2017
This study investigates individual-level misreporting among Medicaid recipients in Louisiana from 2007 to 2017. It explores whether the type of individual who misreports varies over time, including following a major policy shift (the implementation of the Affordable Care Act). Results are based on a series of biennial Medicaid Bias Studies from 2007 to 2017 in which Medicaid recipients are asked about their health care coverage, allowing us to identify individuals who misreport their status. Study participants are (1) randomly selected from state Medicaid files or (2) matched participants from a statewide health insurance ...
Source: Health Services and Outcomes Research Methodology - October 22, 2021 Category: Statistics Source Type: research

Initial validation of the global assessment of severity of illness
This study assessed the validity of the Global Assessment of Severity of Illness (GASI), a single-item scale designed for quick and simple assessment of illness severity in children with various chronic physical conditions. Study objectives were to examine validity, reliability, and responsiveness of the GASI. Clinicians assessed the severity of asthma, food allergy, epilepsy, diabetes, and juvenile arthritis in 55 children, and parents reported on children ’s health-related quality of life. Area under the curve (AUC) computed by logistic regression and Kendall’s Tau-c (τc) assessed the strength of associat...
Source: Health Services and Outcomes Research Methodology - October 15, 2021 Category: Statistics Source Type: research

Using synthetic data to replace linkage derived elements: a case study
AbstractWhile record linkage can expand analyses performable from survey microdata, it also incurs greater risk of privacy-encroaching disclosure. One way to mitigate this risk is to replace some of the information added through linkage with synthetic data elements. This paper describes a case study using the National Hospital Care Survey (NHCS), which collects patient records under a pledge of protecting patient privacy from a sample of U.S. hospitals for statistical analysis purposes. The NHCS data were linked to the National Death Index (NDI) to enhance the survey with mortality information. The added information from N...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Standard electronic health record (EHR) framework for Indian healthcare system
AbstractDigitization of health records in public health facility and its instant availability in the form of electronic records anywhere any time health service is yet to be implemented in developing nations like India and other countries. In India, patient care is mainly delivered through 3 levels namely Primary/Community Healthcare Centre (PHC/CHC), Secondary healthcare centre (District Hospital), and Tertiary Healthcare Centre (National level). The healthcare facilities face many challenges in collecting, processing, and storing these data and managing it without compromising security and privacy. Presently, some of the...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Characterizing bias due to differential exposure ascertainment in electronic health record data
The objective of this paper was to explore the bias a nd efficiency of these three analytic approaches across a broad range of scenarios motivated by a study of the association between chronic hyperglycemia and 5-year mortality in an EHR-derived cohort of colon cancer survivors. We found that the best available approach tended to mitigate inefficiency and selection bias resulting from exclusion while suffering from less information bias than the common data approach. However, bias in all three approaches can be severe, particularly when both selection bias and information bias are present. When risk of either of these bias...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Chronic Diseases and Multimorbidity in Iran: A Study Protocol for the Use of Iranian Health Insurance Organization ’s Claims Database to Understand Epidemiology, Health Service Utilization, and Patient Costs
AbstractThe burden of chronic diseases and multimorbidity is continue to increase, especially in developing countries, but little comprehensive population-based data exist related to their epidemiology and associated healthcare utilization and costs. Our aim is to estimate incidence rate, prevalence, and trend of common chronic diseases and clusters of multimorbidity among East Azerbaijan ’s Health Insurance Organization (EAHIO) enrollees applying adopted and updated pharmacoepidemiological approach and to analyze outpatient health service utilization patterns and associated costs among this population using outpatie...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Evaluating efficiency of counties in providing diabetes preventive care using data envelopment analysis
AbstractFor patients with diabetes, annual preventive care is essential to reduce the risk of complications. Local healthcare resources affect the utilization of diabetes preventive care. Our objectives were to evaluate the relative efficiency of counties in providing diabetes preventive care and explore potential to improve efficiencies. The study setting is public and private healthcare providers in US counties with available data. County-level demographics were extracted from the Area Health Resources File using data from 2010 to 2013, and individual-level information of diabetes preventive service use was obtained from...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Improving risk adjustment with machine learning: accounting for service-level propensity scores to reduce service-level selection
In this study, we propose an alternative model using machine learning (ML) techniques to reduce service-level selection by accounting for demographic and diagnostic characteristics as well as service-level propensity scores (SPS) that capture each individual ’s need for each service (the HCC + SPS model). Using the 2013–2014 Truven MarketScan database, we compare the performance of the HCC model (the HCC-only model) and the HCC + SPS model. We first fit both models with ordinary least squares (OLS) because traditional risk adjustment models rely on OLS. We also fit these models with ...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Estimation of causal effects of multiple treatments in healthcare database studies with rare outcomes
AbstractThe preponderance of large-scale healthcare databases provide abundant opportunities for comparative effectiveness research. Evidence necessary to making informed treatment decisions often relies on comparing effectiveness of multiple treatment options on outcomes of interest observed in a small number of individuals. Causal inference with multiple treatments and rare outcomes is a subject that has been treated sparingly in the literature. This paper designs three sets of simulations, representative of the structure of our healthcare database study, and propose causal analysis strategies for such settings. We inves...
Source: Health Services and Outcomes Research Methodology - August 24, 2021 Category: Statistics Source Type: research

Application of pooled testing in estimating the prevalence of COVID-19
AbstractTesting at a mass scale has been widely accepted as an effective way to contain the spread of the SARS-CoV-2 Virus. In the initial stages, the shortage of test kits severely restricted mass-scale testing. Pooled testing was offered as a partial solution to this problem. However, it is a relatively lesser-known fact that pooled testing can also result in significant gains, both in terms of cost savings as well as measurement accuracy, in prevalence estimation surveys. We review here the statistical theory of pooled testing for screening as well as for prevalence estimation. We study the impact of the diagnostic erro...
Source: Health Services and Outcomes Research Methodology - August 7, 2021 Category: Statistics Source Type: research

Applying random forest in a health administrative data context: a conceptual guide
We describe in detail how RF can be useful in health services research, provide guidance on data set up, modeling decisions and demonstrate how to interpret results. We al so highlight specific considerations for applying RF to health administrative data. In a working example, we compare RF with logistic regression, Ridge regression and LASSO in their ability to predict whether a person has a regular medical doctor. We use survey responses to “do you have a regular medical doctor” from three cycles of the Canadian Community Health Survey (2007, 2009, 2011). Responses are linked with physician claims’ data...
Source: Health Services and Outcomes Research Methodology - July 17, 2021 Category: Statistics Source Type: research

Assessing consistency among indices to measure socioeconomic barriers to health care access
AbstractMany places within rural America lack ready access to health care facilities. Barriers to access can be both spatial and non-spatial. Measurements of spatial access, such as the Enhanced Floating 2-Step Catchment Area and other floating catchment area measures, produce similar patterns of access. However, the extent to which different measurements of socioeconomic barriers to access correspond with each other has not been examined. Using West Virginia as a case study, we compute indices based upon the literature and measure the correlations among them. We find that all indices positively correlate with each other, ...
Source: Health Services and Outcomes Research Methodology - July 17, 2021 Category: Statistics Source Type: research

Applying random forest in a health administrative data context: a conceptual guide
We describe in detail how RF can be useful in health services research, provide guidance on data set up, modeling decisions and demonstrate how to interpret results. We al so highlight specific considerations for applying RF to health administrative data. In a working example, we compare RF with logistic regression, Ridge regression and LASSO in their ability to predict whether a person has a regular medical doctor. We use survey responses to “do you have a regular medical doctor” from three cycles of the Canadian Community Health Survey (2007, 2009, 2011). Responses are linked with physician claims’ data...
Source: Health Services and Outcomes Research Methodology - July 17, 2021 Category: Statistics Source Type: research

Assessing consistency among indices to measure socioeconomic barriers to health care access
AbstractMany places within rural America lack ready access to health care facilities. Barriers to access can be both spatial and non-spatial. Measurements of spatial access, such as the Enhanced Floating 2-Step Catchment Area and other floating catchment area measures, produce similar patterns of access. However, the extent to which different measurements of socioeconomic barriers to access correspond with each other has not been examined. Using West Virginia as a case study, we compute indices based upon the literature and measure the correlations among them. We find that all indices positively correlate with each other, ...
Source: Health Services and Outcomes Research Methodology - July 17, 2021 Category: Statistics Source Type: research

Causal mediation analysis decomposition of between-hospital variance
AbstractCausal variance decompositions for a given disease-specific quality indicator can be used to quantify differences in performance between hospitals or health care providers. While variance decompositions can demonstrate variation in quality of care, causal mediation analysis can be used to study care pathways leading to the differences in performance between the institutions. This raises the question of whether the two approaches can be combined to decompose between-hospital variation in an outcome type indicator to that mediated through a given process (indirect effect) and remaining variation due to all other path...
Source: Health Services and Outcomes Research Methodology - July 10, 2021 Category: Statistics Source Type: research

Detecting bad actors in value-based payment models
We describe our approach, demonstrate how it can be applied with hypothetical data, and simulate how efficiently it detects participants who are truly bad actors. In our hypothetical case study, the approach correctly identifies a bad actor in the first period in 86% of simulations and by the second period in 96% of simulations. The trade-off is that 9% of honest participants are mistakenly identified as bad actors by the second period. We suggest several ways for researchers to mitigate the rate or consequences of these false positives. Researchers and policymakers can customize and use our approach to appropriately guard...
Source: Health Services and Outcomes Research Methodology - June 28, 2021 Category: Statistics Source Type: research

Measuring spatial access to emergency general surgery services: does the method matter?
AbstractEmergency general surgery (EGS) is a critical component of emergency care in the United States. Due to the time sensitiveness of EGS conditions, ensuring adequate spatial access to EGS services is paramount for reducing patient morbidity and mortality. Past studies have used travel time to measure spatial access to EGS services, which has its limitations. The major purpose of this paper is to evaluate the utility of a gravity-based spatial access model in measuring spatial access to EGS services in California. Our data sources include the American Hospital Association 2015 Annual Survey, the American Community Surv...
Source: Health Services and Outcomes Research Methodology - June 16, 2021 Category: Statistics Source Type: research

Racial treatment disparities after machine learning surgical risk-adjustment
AbstractBlack patients are less likely to receive certain surgical interventions. To test whether a health risk disparity and thus differential appropriateness for surgery explains a treatment disparity, researchers must adjust observed rates for patient-level health differences using valid contextual regression controls to increase patient comparability. As an alternative to the standard health adjustment with predetermined diagnosis groups, I propose a machine learning-based method that better captures clinical practices to adjust for the important predictors of invasive surgery applied to the context of acute myocardial...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

Comparison of definitions for identifying urgent care centers in health insurance claims
The objective of this study is to describe and validate two claims-based UCC definitions. We used FAIR Health insurance claims from 444,263 organization National Provider Identifiers (NPIs) with at least 10 claims, January 2016 –March 2019 and merged this data with National Plan and Provider Enumeration System data. The first definition required (1) a UCC place of service code (POS), (2) ≥ 10% Current Procedure Terminology (CPT) codes specific to UCCs, or (3) a UCC taxonomy code in the primary field. The second def inition relaxed these criteria. A random sample of 5% of NPIs identified as UCCs were ...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

Identifying cohabiting couples in administrative data: evidence from Medicare address data
AbstractMarital status is recognized as an important social determinant of health, income, and social support, but is rarely available in administrative data. We assessed the feasibility of using exact address data and zip code history to identify cohabiting couples using the 2018 Medicare Vital Status file and ZIP codes in the 2011 –2014 Master Beneficiary Summary Files. Medicare beneficiaries meeting our algorithm displayed characteristics consistent with assortative mating and resembled known married couples in the Health and Retirement Study linked to Medicare claims. Address information represents a promising st...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

The use of segmented regression for evaluation of an interrupted time series study involving complex intervention: the CaPSAI project experience
AbstractAn interrupted time series with a parallel control group (ITS-CG) design is a powerful quasi-experimental design commonly used to evaluate the effectiveness of an intervention, on accelerating uptake of useful public health products, and can be used in the presence of regularly collected data. This paper illustrates how a segmented Poisson model that utilizes general estimating equations (GEE) can be used for the ITS-CG study design to evaluate the effectiveness of a complex social accountability intervention on the level and rate of uptake of modern contraception. The intervention was gradually rolled-out over tim...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

Bias reduction methods for propensity scores estimated from error-prone EHR-derived covariates
AbstractAs the use of electronic health records (EHR) to estimate treatment effects has become widespread, concern about bias introduced by error in EHR-derived covariates has also grown. While methods exist to address measurement error in individual covariates, little prior research has investigated the implications of using propensity scores for confounder control when the propensity scores are constructed from a combination of accurate and error-prone covariates. We reviewed approaches to account for error in propensity scores and used simulation studies to compare their performance. These comparisons were conducted acr...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

Veridical causal inference using propensity score methods for comparative effectiveness research with medical claims
AbstractMedical insurance claims are becoming increasingly common data sources to answer a variety of questions in biomedical research. Although comprehensive in terms of longitudinal characterization of disease development and progression for a potentially large number of patients, population-based inference using these datasets require thoughtful modifications to sample selection and analytic strategies relative to other types of studies. Along with complex selection bias and missing data issues, claims-based studies are purely observational, which limits effective understanding and characterization of the treatment diff...
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

Editorial
(Source: Health Services and Outcomes Research Methodology)
Source: Health Services and Outcomes Research Methodology - June 1, 2021 Category: Statistics Source Type: research

A comparison of approaches to identify live births using the medicaid analytic extract
The objective of this study is to describe and validate five approaches to identifying births using Medicaid Analytic eXtract (MAX) from 45 states (2006 –2014). We calculated total number of MAX births by state-year using five definitions: (1) any claim within 30 days of birth date listed in personal summary (PS) file, (2) any claim within 7 days of PS birth date, (3) live birth ICD-9 in inpatient or other therapies file, (4) live birth ICD-9 co de in inpatient file, (5) live birth ICD-9 in inpatient file with matching PS birth date. We then compared the number of MAX births by state and year to expected co...
Source: Health Services and Outcomes Research Methodology - May 26, 2021 Category: Statistics Source Type: research

Hospital quality-review spending and patient safety: a longitudinal analysis using instrumental variables
AbstractSince the landmark Institute of Medicine ’s (IOM’s) 2000 report first focused attention to the problem of the safety of inpatient care, it has been a priority of hospital staffs, administrators, and policymakers. Despite remarkable progress in the 20 years since the IOM report, there is still much unknown about how these improvements i n safety have been achieved. Using a 12-year (2004–2015) panel of Florida acute-care general hospitals, we estimate the relationship between hospital expenditure on peer (or quality) review and patient-safety outcomes, using a composite measure of patient safety (PS...
Source: Health Services and Outcomes Research Methodology - May 17, 2021 Category: Statistics Source Type: research

Editorial
(Source: Health Services and Outcomes Research Methodology)
Source: Health Services and Outcomes Research Methodology - May 7, 2021 Category: Statistics Source Type: research

Inferring patient transfer networks between healthcare facilities
AbstractConstructing accurate patient transfer networks between hospitals is critical for understanding the spread of healthcare associated infections through statistical and mathematical modeling, and for determining optimal screening and treatment strategies. The Healthcare Cost& Utilization Project (HCUP) State Inpatient Databases (SID) provide valuable information on patient transfers from publicly obtainable claims databases, yet often give an incomplete picture due to missingness of patient tracking identifiers. We designed a novel imputation algorithm that enabled us to estimate the true number of patient transf...
Source: Health Services and Outcomes Research Methodology - May 7, 2021 Category: Statistics Source Type: research

The ADI-3: a revised neighborhood risk index of the social determinants of health over time and place
AbstractSince its development, Singh ’s 2003 Area Deprivation Index (ADI) has been routinely used by researchers to measure a global construct of neighborhood socioeconomic deprivation and to investigate how living in neighborhoods of different levels of socioeconomic deprivation affects individuals’ health. We empirically tested t he ADI’s dimensionality, using 2013–2017 American Community Survey tract-level estimates (N = 73,056), and the stability of its performance across time and place. Factor analysis findings illuminated three distinct dimensions, the ADI-3, consisting of neighb...
Source: Health Services and Outcomes Research Methodology - April 19, 2021 Category: Statistics Source Type: research

Distinguishing frontloading: an examination of medicare home health claims
This study examines visit characteristics of post-acute home health episodes for heart failure patients in the Medicare fee-for-service population and explores whether alternative definitions can empirically distinguish frontloaded episodes. Using 100% Medicare claims and enrollment data for 2016 and 2017, we descriptively examine the first post-acute home health episodes occurring after discharge for patients with heart failure as a primary diagnosis. We use the number and timing of visits during 60-day episodes highlight two definitions of frontloading related to the existing empirical literature. Among heart failure hom...
Source: Health Services and Outcomes Research Methodology - April 18, 2021 Category: Statistics Source Type: research

Modelling the size, cost and health impacts of universal basic income: What can be done in advance of a trial?
AbstractOpposition to Universal Basic Income (UBI) is encapsulated by Martinelli ’s claim that ‘an affordable basic income would be inadequate, and an adequate basic income would be unaffordable’. In this article, we present a model of health impact that transforms that assumption. We argue that UBI can affect higher level social determinants of health down to individual d eterminants of health and on to improvements in public health that lead to a number of economic returns on investment. Given that no trial has been designed and deployed with that impact in mind, we present a methodological framework fo...
Source: Health Services and Outcomes Research Methodology - April 11, 2021 Category: Statistics Source Type: research