Introduction

The National Health and Medical Research Council (NHMRC) of Australia spends over $800 million per year on medical and public health research, most of which is dependent on accurate data analysis and interpretation. We suggest that unless considerable attention is made to strengthening the essential scientific discipline of Bio Statistical Programming Services, the value of our health research investment, in terms of better health and lives saved, is endangered. This danger is exacerbated by the development of research opportunities provided by the significant data age, which quickly increases the availability and scale of new data, needing a better grasp of statistical concerns and computational tools. Concerns about Australia’s biostatistical underpinnings were expressed in a statement released by the International Society of Biostatistics.

The problem

In the presence of unpredictability and uncertainty, statistical reasoning offers the theoretical foundation for extracting information from data. Most experimental research in public health and clinical care relies on biostatistical input on everything from study design to data analysis and reporting, with the best studies combining biostatistical information on everything from study design to data analysis and recording. Clinical biostatistics programming service approaches are at the foundation of essential public health research disciplines, including epidemiology and health services research, a function that reflects the discipline’s basic character. On the other hand, bioinformatics and computational biology are vital emerging areas in data-intensive biomedical research that are anchored by statistical principles and methodologies and components highly informed by other basic disciplines like computer science and mathematics. “These issues [of poor study design, conduct, and analysis] are often related to misuse of statistical methods, which is exacerbated by inadequate training in methods,” according to a recent review of the scale of waste and ineffectiveness in health research, echoing similar observations made more than two decades earlier.

Importantly, biostatistics, as a subdiscipline of clinical case report statistical service (perhaps the first “data science “5), is a recognized scientific discipline in its own right, rather than a collection of procedures that must be applied appropriately. Not only does good biostatistical work include an understanding of mathematics, probability, and causes of bias, which underpin statistical theory and methodologies, but it also necessitates (and increasingly) substantial technological capabilities, such as computers. To develop these abilities and the understanding required to conceptualize issues and traverse the difficult seas between real-world health challenges and complicated methodologies, in-depth training is essential. According to a recent analysis, most physicians struggle to complete such training. A superficial comprehension of statistics can readily lead to improper behaviour and be criticized.

Necessary steps

• Recognition of biostatistics as an academic field, essential to the intellectual architecture of the larger research enterprise, is required for the development of biostatistics as a core subject within educational health and medical research. This necessitates systems that support biostatistical work at all levels, from nonspecialists like physicians through master’s level biostatistics graduates and doctorate students, postdoctoral researchers, and research leaders in biostatistical methods.
• The requirement for academic effort across this spectrum is common in other fields of science, but it is sometimes overlooked in biostatistics due to a propensity to treat the subject as merely a toolset of procedures rather than a growing scientific discipline.
• Medical Biostatistical Programming Service comprises a long process that includes mathematical derivations and conceptualizations, simulation studies, thorough case studies, and the translation of newly created methodologies for use by other researchers. The development of marginal structural models, which enabled the appropriate handling of time-dependent confounding in treatment decisions based on CD4 cell count levels that are themselves affected by treatment, was critical in the wave of research into antiretrovirals for the treatment of human immunodeficiency virus infection. The training of future biostatistical leaders must also include experience in methodological research.

The international situation and Australia’s position

Other countries have recognized the critical role of biostatistics in health and medical research. Many major universities in the United States have biostatistics departments established in the 1970s thanks to financing from the National Institutes of Health for biostatistical research training programmes, with a call for a renewed effort to expand biostatistical training programmes in 2006. In a similar vein, the Medical Research Council in the United Kingdom has long supported a national centre in biostatistical methodology — the Medical Research Council’s Biostatistics Unit — and many methodology hubs whose core research agenda is the statistical methodology, which has been funded since 2009. Similar to Europe and the United States, Australia has never invested systematically in developing biostatistics, either in universities or industry.

Potential solutions

Inappropriately, there is no simple fix for the issues raised, but we feel the following initiatives are necessary to enhance and promote the biostatistics field in Australia:

• Universities and research institutes must foster the development of organizational structures with a critical mass of academic biostatisticians working in methodology and collaborating with health researchers, as well as training opportunities and career development for biostatisticians;
• Biostatistics Clinical trial Research Services and advanced training must keep pace with the dramatic changes in the data science landscape to ensure that graduates have the necessary breadth of knowledge.

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References

1. Lee, Katherine J., et al. “Biostatistics: a fundamental discipline at the core of modern health data science.” The Medical Journal of Australia 211.10 (2019): 444.
2. National Health and Medical Research Council. Outcomes of funding rounds [website]. NHMRC, 2019. https://www. nhmrc.gov.au/funding/data-research/ outcomes-funding-rounds (viewed Sept 2019).
3. Ioannidis JP, Greenland S, Hlatky MA, et al. Increasing value and reducing waste in research design, conduct, and analysis. Lancet 2014; 383: 166–17