Advice for isolated statisticians collaborating in academic healthcare centre settings

Mehta, C. Christina; Stedman, M.; Rao, Sowmya R.; Podolsky, Robert H.

doi:10.1002/sta4.492

Cited by 6 publications

(7 citation statements)

References 32 publications

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“…Historically, it has been common practice for clinical departments to hire or engage a single quantitative staff, often a statistician, to support their research needs (Mehta et al, 2022; Welty et al, 2013). While it may seem desirable for clinical leadership to have short‐term control of workflows and the staff's effort, there are numerous drawbacks to the growth and longevity of these types of arrangements.…”

Section: Organizational Infrastructure and Managementmentioning

confidence: 99%

“…With a sole embedded staff and a higher propensity for turnover, historical knowledge is not retained when that individual is not available (e.g., resigns or goes on leave). Instead, it is ideal to establish a centralized resource that fosters connections and leverages diverse expertise among quantitatively trained peers (Khalatbari et al, 2020; Mehta et al, 2022; Welty et al, 2013). AHCs should support the development of quantitative units that can properly hire, manage, and retain staff.…”

Section: Organizational Infrastructure and Managementmentioning

confidence: 99%

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Methods for building a staff workforce of quantitative scientists in academic health care

Peskoe,

Slade,

Rende

et al. 2024

Stat

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Collaborative quantitative scientists, including biostatisticians, epidemiologists, bioinformaticists, and data‐related professionals, play vital roles in research, from study design to data analysis and dissemination. It is imperative that academic health care centers (AHCs) establish an environment that provides opportunities for the quantitative scientists who are hired as staff to develop and advance their careers. With the rapid growth of clinical and translational research, AHCs are charged with establishing organizational methods, training tools, best practices, and guidelines to accelerate and support hiring, training, and retaining this staff workforce. This paper describes three essential elements for building and maintaining a successful unit of collaborative staff quantitative scientists in academic health care centers: (1) organizational infrastructure and management, (2) recruitment, and (3) career development and retention. Specific strategies are provided as examples of how AHCs can excel in these areas.

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Section: Organizational Infrastructure and Managementmentioning

confidence: 99%

Section: Organizational Infrastructure and Managementmentioning

confidence: 99%

Methods for building a staff workforce of quantitative scientists in academic health care

Peskoe,

Slade,

Rende

et al. 2024

Stat

View full text Add to dashboard Cite

show abstract

“…This early and in‐depth involvement in projects can improve rigour, reproducibility and data integrity. Furthermore, embedded statisticians gain in‐depth knowledge of their domain‐specific field and can bridge gaps between clinical and statistical perspectives (Mehta et al, 2022). Greater content knowledge then allows embedded statisticians to not only construct more informed statistical models but also interpret results and better communicate findings to clinical audiences.…”

Section: Critical Role Of Collaborative Statisticians and Benefits An...mentioning

confidence: 99%

“…Within the group of collaborative statisticians, there exist isolated statisticians (Figure 1), those outside structured statistics‐related departments or statistical consulting hubs. Isolated statisticians face many challenges in terms of professional support and networking, mentorship and clear role expectations (Mehta et al, 2022). It is worthwhile to note that “isolated” is a relative term.…”

Section: Introductionmentioning

confidence: 99%

Documenting and communicating the contributions of embedded statisticians: Show me the value!

Vasilopoulos,

Crisp,

Garvan

et al. 2024

Stat

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Academic research productivity relies upon the contribution of statisticians, who are typically clustered in statistics and biostatistics departments, isolated from clinical researchers. Most academic health centres have created consultation hubs or research incubators to make statisticians available for individual collaboration to support the clinical research enterprise. Additionally, some clinical departments within academic health centres have recognized the value in colocating statisticians within their clinical departments to improve availability for collaboration with physicians/researchers. Embedded statisticians encounter the same challenges of isolated statisticians regarding professional support and networking, mentorship and clear role expectations. While for all collaborative statisticians, it is important to effectively communicate value to both collaborators and supervisors, this may be especially problematic for embedded statisticians in clinical departments where their supervisors may not have backgrounds in research or statistics. Previous papers have reported valuable metrics for statisticians, particularly those associated with Biostatistics, Epidemiology and Research Design Cores. There is a knowledge gap regarding metrics tailored to meet the needs of the embedded statistician and clinical supervisors. This paper is a first step towards addressing this important need.In this paper, we explore (1) the critical role of collaborative statisticians and the benefits and challenges of the embedded statistician model, (2) the need for additional metrics specific to embedded statisticians which measure value and (3) how to design a value report. We offer a framework for evaluation of the contributions of the embedded statistician with the following domains: (1) collaboration, (2) research output/productivity, (3) mentoring and (4) education. Metrics that are particularly specific to embedded statisticians and that are not routinely captured include time from project initiation to completion/outcome, time from initial statistical consultation to statistical outcome completion and summary of level of contribution for manuscripts and presentations in addition to author order. We conclude with thoughts on future directions for development of metrics and reporting systems for statisticians embedded in clinical departments.

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“…First, these schools may encounter difficulty recruiting biostatistics faculty and staff due to the absence of a local talent pool. Second, any biostatisticians who are recruited are at risk of isolation, which could lead to lower productivity, career dissatisfaction, and departure from the institution (Mehta et al, 2022). Third, schools in biostatistics deserts would be unable to draw upon support from biostatistics trainees (e.g., biostatistics student interns and student‐led consulting services) (Kaseda et al, 2022; Pomann et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Biostatistics deserts and scholarly productivity among US medical schools

Vasilopoulos,

Tumin

2024

Stat

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The teaching and practice of biostatistics are essential to medical education, but access to biostatistical expertise is limited at many medical schools. Medical schools in rural and historically underserved areas may be doubly disadvantaged in accessing biostatistics expertise by their lack of financial resources and a lack of local programmes training future generations of biostatisticians. Using public data on US medical schools and biostatistics PhD programmes, we identified medical schools operating in ‘biostatistics deserts’ (institutions without an affiliated or colocated PhD programme in biostatistics) and correlated each medical school's location in a biostatistics desert with scholarly productivity, operationalized as the annual number of scholarly publications. Among 126 MD‐granting medical schools in our analysis, 46% were located in a biostatistics desert and had a median of 590 publications/year, compared to 993 for medical schools with a colocated PhD programme and 1,369 with an affiliated programme. On multivariable analysis, the presence of a Biostatistics, Epidemiology, and Research Design (BERD) programme, but not affiliation or colocation with a biostatistics PhD program, was associated with higher scholarly productivity. Structured biostatistics services, such as BERD programmes, may represent the best opportunity for medical schools to leverage the local biostatistics workforce to support scholarly publication.

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Advice for isolated statisticians collaborating in academic healthcare centre settings

Cited by 6 publications

References 32 publications

Methods for building a staff workforce of quantitative scientists in academic health care

Methods for building a staff workforce of quantitative scientists in academic health care

Documenting and communicating the contributions of embedded statisticians: Show me the value!

Biostatistics deserts and scholarly productivity among US medical schools

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