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          2 min read

          Goldilocks State of Healthcare Analytics: Overcoming Surgical Backlog

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          Speak to any healthcare leader in Canada and you quickly realize healthcare analytics is a paradox. There is too much in terms of the sheer volume of data – too many silos, locales, standards, and redundancies – but also too little in terms of usable, real-time, reliable details to drive wiser business decisions and stronger security protocols. Logibec’s customers' success with surgical analytics indicates there is a goldilocks zone, where data can translate to insights and improve access and care. This article highlights how our customers found the goldilocks zone by - optimizing the three axes of technology, people, and process with us - to overcome the burden of surgical backlog.

          The increasing volume of healthcare data has exceeded the ability of health organizations to process it for improving clinical and financial efficiencies and quality of care. Pre-pandemic our experience of working with providers across Canada is reflective of the literature on healthcare analytics maturity models. Organizations are at various stages of healthcare analytics maturity. According to survey research by Scottsdale and Cerner, only 45 percent of healthcare organization in their sample was at level 4 and 5, where they are ready to deploy analytics for strategic impact.

          article-goldilocks-apmm(Source: Scottsdale Institute and Cerner, 2022)

          The pandemic exasperated and exposed chronic problems across healthcare, especially ones like a surgical backlog. Just in Quebec, there are over 160,000 patients waiting for surgical care and 20,000 of these patients have been waiting for more than 12 months. The problem is similarly dire in the neighbouring province of Ontario, where over one million surgical procedures are on backlog. There is strong political motivation to fund and overcome this backlog quickly. Christian Dubé, the Minister of Health, for Quebec, intends to catch up within "two to three years". The question of how to deploy this capital effectively to deliver on the political will is a question that is best answered with good (surgical) analytics, as the province of British Columbia has done.

          According to the health minister of B.C., Adrian Dix, the performance of B.C. in tackling the problem of surgical backlog during the last two years of the pandemic is anything but “stunning”. The B.C. Ministry of Health said in the first week of May 2022 they completed 337,560 scheduled and unscheduled surgeries since March 2021. Moreover, B.C was able to shrink the surgical backlog by 6% fewer than the number waiting before the pandemic in 2019/2020.

          B.C. was able to deploy its resources effectively - to open new and unused operating rooms, add hours on weekdays and weekends, and hired the right staff including surgeons, nurses, and anesthesiologists to tackle bottlenecks - and quickly bounce back. The foundation of this success is attributable to the goldilocks state of analytic capabilities - people, process, and technology - at health authorities in B.C. enabled by Logibec’s LightHouse solution. We have seen that careful and attentive use of data analytics in healthcare, specifically in surgery, can transform data into knowledge that can improve patient access, outcomes, and operational efficiency.

          To overcome the paradox of healthcare analytics we mentioned earlier, successful customers have first focused their analytical efforts on a key business challenge. In this case, it was to reduce the surgical backlog. Second, customers have facilitated a collaborative culture of data-driven decision-making. This dealt more with people and processes. And lastly, the third is the deployment of technology that is best-of-breed and in line with their strategic goals.

          Article-goldilocks

          Typically, we notice our customers achieve the goldilocks state of healthcare analytics in three phases. During phase one, we co-create a comprehensive view with interactive dashboards into their surgery operations within the first 45-days. We do this by pulling data from disparate EMRs and other clinical systems into a normalized data repository with configurable data visualization. In the next 60-days, we facilitate a culture of data-driven collaboration by bringing seasoned subject matter data and domain experts to help our customers. This is phase 2, where customers start to notice an increased level of communication across the perioperative and administrative teams using dashboards/reports and shared interpretation of insights. In the third and last phase, we help our customers start to move into advanced analytics - scenario planning and predictive optimization - meaningful to meet the strategic goals, in this case, to increase access and efficiency of care.

           

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