WHAT WE DO:  

EVIDENCE GENERATIONObservational research studies can help identify and quantify the value of health care interventions. Collection and analysis of subject-level data can provide insight in the epidemiology, patient and economic burden, and treatment patterns of health conditions. Furthermore, data collected with observational studies can be used to evaluate real-world treatment effectiveness, safety and economic value of healthcare interventions and policies. In particular valuation of policies in context is essential to understanding both what drives value and effectiveness across different health systems and locations. Design and implementation of observational studies With retrospective observational studies, such as chart reviews, pre-recorded, patient-level data are used to answer the research questions of interest. The information obtained from these studies can also be helpful in guiding subsequent prospective observational studies to collect health economics and outcomes data not available in existing data sources. Our epidemiologists and health economists have the expertise to design and implement such studies. Furthermore, we can perform cross-sectional surveys to elicit information on patient outcomes and medical resource use associated with health states. Secondary data analysis Analysis of existing subject-level data from health survey data, clinical records and a wide array of global data sources of disease prevelance and healthcare spend.  can provide an efficient alternative to bespoke observational studies to characterize disease burden or understand the value of treatments in a real-world context. Our experts have performed studies based on a variety of databases from Latin America, Asia and sub-Saharan Africa Preference and utility studies Preference studies, such as discrete choice experiments, can provide valuable insight in the burden of disease and the relevance of achieving targeted health outcomes from the perspective of patients or physicians.  Utility studies to obtain preference estimates by means of standard gamble and time trade-off exercises provide information frequently needed to support willingness-to-pay studies that form the social value placed on achieving particular health states. 

EVIDENCE SYNTHESISEvidence synthesis involves powerful research techniques to combine multiple sources of clinical evidence. Evidence synthesis helps inform decision-making by establishing the comparative effectiveness of medical interventions for different subgroups of patients. Evidence synthesis is also used to support drug development, inform future study design, and evaluate the relationship between outcome measures.  Systematic literature reviews A good systematic literature review to identify, select, and extract data from relevant studies is the foundation of a solid evidence synthesis, whether the research questions concern efficacy and safety of interventions, or the relationship between endpoints. Meta-analysis Meta-analysis of randomized controlled trials, single arm studies, observational studies, multiple designs, multiple outcomes, and multiple treatments.  Network meta-analysis (indirect and mixed treatment comparisons) Synthesis of networks of trials involving treatments compared directly, indirectly, or both by means of network meta-analysis. We have the expertise to perform advanced network meta-analysis, including analysis of survival curves, repeated measures analysis, and combination of patient level with study level data. Econometric analysis Precision Global Health partners with its sister company Precision Health Economics to undertake a wide array of in depth econometric analyses to better understand the wider and longer term social value of investment in health care both at the macro or system level, but also at the micro or disease, treatment or policy level.  Examples of such studies show the impact of reducing the burden of a disease on productivity, poverty, household financial risk, economic growth and overall well-being. 

EVIDENCE INTEGRATIONClinical, health policy, and access decisions often involve trading off competing objectives in the presence of uncertainty about the benefits, harms and costs of medical interventions and health policies. Decision-analytic models integrate the available evidence around the effectiveness and cost of interventions in a transparent manner to evaluate their risk-benefit, economic value, and public health impact. Decision-analytic models are very powerful tools to evaluate the economic viability of new untested health policies or interventions prior to the costly process of scale-up.  Decision & economic modeling Evidence-based decision-analytic models to assess risk-benefit, economic value, and the public health impact of medical interventions or health policies developed according to the latest methodological guidelines and the requirements of funders and health service delivery organizations.  Infectious disease modeling Dynamic modeling approaches to evaluate the public health impact and cost-effectiveness of infectious disease control interventions and programs. 

EVIDENCE COMMUNICATIONThe value of a medical intervention is only recognized by health care decision-makers when it is supported by relevant evidence. Effective communication of evidence to inform clinical and access decisions requires a good understanding of the evidence needs and requirements of the decision-maker. Scientific publications Publication of a scientific study, such as an evidence synthesis or economic evaluation, in a peer-reviewed journal is still the primary way to communicate the findings to physicians and other health care decision-makers.  Engaging key opinion leaders Internationally recognized clinical experts are often involved with preparation of treatment guidelines. Engaging key opinion leaders in evidence synthesis and evidence integration studies is key to acceptance and successful dissemination of the findings. Health economics apps Precision Global Health is one of the few companies who have health economists with direct experience working on digital products, bridging the gap between science and visualization. We take standard economic models and turn them into visually engaging iPad apps that can be tailored to specific payer interactions at the touch of a button.