Benefits Of Health Care Interventions Research Articles

Application of the EQ-5D in the Middle East: A Systematic Review Focusing on Patients Living in the Kingdom of Saudi Arabia.

Patients’ quality of life (QoL) and reported outcomes are critical indicators of the burden of a disease and the benefits of healthcare intervention. This systematic review explores publications that have adapted the EQ-5D for use with a population living in Saudi Arabia. The review of the following databases: MEDLINE, EMBASE, Wiley’s Database, EBSCO, and ClinicalTrials.gov was conducted on December 1, 2020. The search strategy was adapted from the SPIDER search tool, and the included articles were classified by author, year of publication, region, disease of interest, sample size, type of EQ-5D, and format. Level of EQ-5D was classified as either 3L or 5L. Thirteen articles met the search inclusion criteria. The earliest publication was conducted in 2015 and the latest in 2020. These studies were conducted in four Saudi administrative regions, and multiple conditions or treatments were studied, the most studied condition being diabetes mellitus, followed by musculoskeletal disorders, back pain, and injuries. This systematic review article finds that the EQ-5D has been well adapted in the KSA. However, continued work is needed to investigate the quality of life for major conditions such as cardiovascular disease and cancer. Moreover, QoL research is lacking in certain regions, such as southern and northern Saudi Arabia. Despite the successful application and validation of the EQ-5D, a local QoL tool is needed to capture the unique context of patients within the healthcare system in the Middle East.

Lifetime Costs of Hospitalised Cardiovascular Disease in Australia: An Incidence-Based Estimate

To estimate the incidence-based, lifetime costs of health care and productivity losses associated with cardiovascular disease (CVD) using hospital admission data from Queensland, Australia. Retrospective analysis of data on CVD health care use sourced from Queensland Hospital Admitted Patient Data Collection (QHAPDC), Emergency Department Data Collection (EDDC), Medicare Benefits Schedule (MBS) and the Pharmaceutical Benefits Scheme (PBS). Costs were estimated from the societal perspective. Study participants included patients who were first admitted to any Queensland hospital in 2010 for a CVD-related treatment. Subsequent admissions of these patients were followed until December 2015. The present value of incidence-based lifetime costs per patient were used to estimate the total costs for Australia. All costs were presented in Australian dollars at 2019 prices. The estimated lifetime health care cost of CVD was AUD$65,700 per person. Productivity loss cost was higher at AUD$75,200 per person, and total indirect lifetime costs were $140,900 per person. Scaling these costs up for the Australian population, the estimated incidence-based lifetime CVD costs for Australia were $60.5 billion ($28.2 billion in direct costs and $32.3 billion in indirect costs). Incidence-based lifetime indirect costs of CVD were higher than the direct costs. The life-time cost structure suggests that economic benefits of health care interventions for cardiovascular diseases from a societal perspective should be at least twice as large than that from a health service perspective.

Health-Related Resource-Use Measurement Instruments for Intersectoral Costs and Benefits in the Education and Criminal Justice Sectors.

BackgroundIntersectoral costs and benefits (ICBs), i.e. costs and benefits of healthcare interventions outside the healthcare sector, can be a crucial component in economic evaluations from the societal perspective. Pivotal to their estimation is the existence of sound resource-use measurement (RUM) instruments; however, RUM instruments for ICBs in the education or criminal justice sectors have not yet been systematically collated or their psychometric quality assessed. This review aims to fill this gap.MethodsTo identify relevant instruments, the Database of Instruments for Resource Use Measurement (DIRUM) was searched. Additionally, a systematic literature review was conducted in seven electronic databases to detect instruments containing ICB items used in economic evaluations. Finally, studies evaluating the psychometric quality of these instruments were searched.ResultsTwenty-six unique instruments were included. Most frequently, ICB items measured school absenteeism, tutoring, classroom assistance or contacts with legal representatives, police custody/prison detainment and court appearances, with the highest number of items listed in the Client Service Receipt Inventory/Client Sociodemographic and Service Receipt Inventory/Client Service Receipt Inventory–Children’s Version (CSRI/CSSRI/CSRI-C), Studying the Scope of Parental Expenditures (SCOPE) and Self-Harm Intervention, Family Therapy (SHIFT) instruments. ICBs in the education sector were especially relevant for age-related developmental disorders and chronic diseases, while criminal justice resource use seems more important in mental health, including alcohol-related disorders or substance abuse. Evidence on the validity or reliability of ICB items was published for two instruments only.ConclusionWith a heterogeneous variety of ICBs found to be relevant for several disease areas but many ICB instruments applied in one study only (21/26 instruments), setting-up an international task force to, for example, develop an internationally adaptable instrument is recommended.Electronic supplementary materialThe online version of this article (doi:10.1007/s40273-017-0522-4) contains supplementary material, which is available to authorized users.

To enable shared decision making we must understand healthcare statistics

This article was migrated. The article was not marked as recommended. The concept of a society in which patients are properly informed about the risks and benefits of healthcare interventions and participate in a culture of shared decision making with their doctors is now more than 30 years old. For shared decision making to work in practice, doctors must have an adequate working knowledge of healthcare statistics so that they can provide patients with the accurate and up-to-date information they require to make informed decisions regarding their care.The first part of this paper argues that at present doctors lack this knowledge; it provides evidence for this in the form of previous studies conducted, which have specifically tested doctor's statistical literacy. Simple techniques that doctors can employ to improve their statistical literacy and reduce their susceptibility to inherent bias in the way data is presented are then described and evidenced.Patients too require a basic knowledge of healthcare statistics if they expect to make informed decisions, however, as outlined in this paper they too are easily confused by misleading risk communication practices, especially in relation to screening. To combat this, healthcare authorities and doctors have a responsibility to provide evidence in the most transparent way possible. Tools known as 'decision aids' have been developed to help in this regard, by assisting doctors in communicating healthcare statistics to patients at the consultation level. The second part of this paper critiques the evidence supporting the use of one such decision aid known as an Option Grid.™

Utility Scores In Patients With Oxygen-Dependent COPD: A Case-Control Study

Background: Utility measures that summarize the health-related quality of life of an individual using a single number usually between 0 (death) and 1 (full health) are useful to quantify the benefits of health care interventions in terms of quality-adjusted life years (QALYs) and to help prioritizing limited health resources from cost-effectiveness analyses among patients with different health conditions. Objective: To determine utility scores in patients with oxygen-dependent chronic obstructive pulmonary disease (COPD). Methods: Patients with oxygen-dependent COPD (the cases) were matched, on a 1:2 basis, to COPD controls according to gender, age (± 5 years) and FEV1 (±5% predicted). Utility scores were obtained from the SF-6D, a measure derived from the SF-36. Results: From a cohort of 102 patients with oxygen-dependent COPD, 68 (42 men; mean age: 71 years; mean FEV1: 35% predicted) were successfully matched with 136 controls. We found clinically and statistically significant differences in mean utility scores between cases (0.588 ± 0.071) and controls (0.627 ± 0.085; p = 0.001). The same differences were observed in men and women. Conclusion: Oxygen-dependence adds to the burden of disease in terms of quality of life. These utility scores may be useful in cost-utility analyses involving patients with oxygen-dependent COPD.

Effective Risk Management Tools

Risk management proactively assesses the potential risks and benefits of health care interventions, including both drugs and medical devices. Risk management systematically identifies safety indications and establishes a risk management strategy for potential adverse events. Professionals trained in risk management have unique expertise in assessing the balance between risk and benefit. They play an important role in clinical study oversight (pre- and postmarketing) and in measuring outcomes of health care interventions. Assessing the risks and benefits of any therapy requires consideration of the complex interactions of multiple variables of the population to treat, including disease state, proposed treatment, and potential risks. Several key factors contribute to the effectiveness and acceptability of any treatment. For example, physician compliance with prescribing guidelines and a patient’s ability to tolerate a drug and to understand how to administer medications accurately will affect risk management assessments. Concurrent treatments (drug interactions) and diseases are also important considerations. Other variables include drug treatment ratios (placebo/active) and, increasingly, the use of screening tools to identify pharmacogenetic markers in particular patient populations that correlate with drug metabolism, efficacy, and other outcomes.

Economics of Atypical Antipsychotics in Bipolar Disorder

Economic evaluations are increasingly being used by policy makers to evaluate the relative costs and benefits of healthcare interventions. These analyses provide economic and clinical evidence to decision makers seeking to make recommendations on treatment alternatives for patients. This article describes the economic evidence on the atypical antipsychotics currently approved for the treatment of bipolar disorder. This area remains under-researched. A literature search identified only six relevant studies of atypical antipsychotics in bipolar disorder: two retrospective database analyses, three economic analyses alongside clinical trials and one cost-effectiveness analysis. Based on the limited available studies, there appears to be no significant difference in healthcare resource use between olanzapine, quetiapine, risperidone and valproate semisodium (divalproex sodium; an antiepileptic drug and a standard treatment for mania associated with bipolar disorder). While a cost-effectiveness study for the UK found haloperidol (a conventional antipsychotic) to be more cost effective than atypical antipsychotics, these results must be considered with caution because of the non-inclusion of adverse effects in the model. No economic data are available for aripiprazole, clozapine or ziprasidone in bipolar disorder. Until more economic evidence becomes available, the economic implications of atypical antipsychotic treatment in patients with bipolar disorder are unlikely to significantly impact on prescribing and treatment patterns. Future economic studies evaluating atypical antipsychotics in bipolar disorder should address the issue of long-term costs and effectiveness to reflect the chronic nature of the disease, the variety of health states that patients may experience and the range of treatments they may receive. A better understanding of the complex interplay between effectiveness, safety, quality of life, adherence and resource use should ultimately contribute to improving the treatment of bipolar disorder.

Preference-based approaches to measuring the benefits of perinatal care.

Studies that measure benefits of health care interventions in natural or physical units cannot incorporate the several health changes that might occur within a single measure, and they overlook individuals' preferences for those health changes. This paper discusses and critically appraises the application of preference-based approaches to the measurement of the benefits of perinatal care that have developed out of economic theory. These include quality adjusted life year (QALY)-based approaches, monetary-based approaches, and discrete choice experiments. QALY-based approaches use scaling techniques, such as the rating scale, standard gamble approach, and time trade-off approach, or multi-attribute utility measures, to measure the health-related quality of life weights of health states. Monetary-based approaches include the revealed preference approach, which involves observing decisions that individuals actually make concerning health risks, and the willingness-to-pay approach, which provides a framework for investigating individuals' willingness to pay for benefits of health care interventions. Discrete choice experiments describe health care interventions in terms of their attributes, and elicit preferences for scenarios that combine different levels of those attributes. Empirical examples are used to illustrate each preference-based approach to benefit measurement, and several methodological issues raised by the application of these approaches to the perinatal context are discussed. Particular attention is given to identifying the relevant attributes to incorporate into the measurement instrument, appropriate respondents for the measurement exercise, potential sources of bias in description and valuation processes, and the practicality, reliability, and validity of alternative measurement approaches. The paper's conclusion is that researchers should be explicit and rigorous in their application of preference-based approaches to benefit measurement in the context of perinatal care.

Should Clinical Trials With Concurrent Economic Analyses Be Blinded?

ECONOMIC ANALYSES are increasingly conducted alongside clinical trials, as the funders of research recognize that they require estimates of both the costs and benefits of health care interventions. In fact, many commissioning organizations will fund clinical trials only if they are designed to provide estimates of cost-effectiveness, and economic analyses are already being used to inform decisions on the reimbursement of pharmaceuticals in some health care systems. 1 The addition of economic data collection and analysis to clinical trials raises a number of important methodological issues, 2 including whether those clinical trials incorporating an economic analysis should be blinded. Rationale for Blinding in Clinical Trials Blinding physicians and patients to treatment allocation in clinical trials aims to reduce bias in estimates of treatment effect, since outcomes are often open to interpretation, and knowledge of the treatment regimen may affect patient or physician behavior. The impact of blinding on estimates of