Public sector health analytics capacity before and after Covid-19: A case study of manager perspectives in New Brunswick, Canada.

James Ayles, Maria do Carmo Correia de Lima, Neeru Gupta
Author Information
  1. James Ayles: Government of New Brunswick, Fredericton E3B 6G3, Canada.
  2. Maria do Carmo Correia de Lima: Consortium on Analytics for Data-Driven Decision-Making, McGill University, Montreal H3A 0G4, Canada.
  3. Neeru Gupta: New Brunswick Department of Health, Fredericton E3B 6G3, Canada.

Abstract

Background: Demand for health data and analytics to support research, policy, and practice continues to rise, accelerated by the Covid-19 pandemic. Despite the importance of the government analytics workforce in driving academic-based data sharing and linkage platforms, little is known about how public sector managers assess capacity in health analytics. This case study describes findings from consultations among middle managers of analytics services in a Canadian provincial health ministry.
Methods: Data collection involved a mixed-questions survey to gauge the functional perspective of managers on organisational and human resource analytics capacity within the New Brunswick Department of Health. The repeated cross-sectional survey was implemented in two rounds, with a baseline collected before the Covid-19 global outbreak (in 2016) and a follow-up after the pandemic emergency response (in 2022).
Results: The post-pandemic period was associated with perceptions of a growing role for public service personnel in handling analytics. Recruitment and retention of skilled analytics professionals emerged as the top priority for capacity building, including needs-based planning, competitive compensation packages to address skills shortages, professional development and promotion opportunities, and tracking key performance indicators for employee satisfaction.
Conclusions: Government health analytics professionals play a critical role in advancing administrative data use and re-use. Enhanced knowledge sharing is needed on best practices in supply-demand monitoring for analytics professionals and planning for human resources surge capacity in the public service, lest significant innovation potential for health system improvement be left untapped.

Keywords

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MeSH Term

Humans
COVID-19
New Brunswick
Cross-Sectional Studies
Public Sector
Capacity Building
Pandemics
SARS-CoV-2

Word Cloud

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