Are investments in hospital data management eligible with patient expenses?

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In conversation with Antonio De Castro, Senior Industry Consultant, Global Health and Life Sciences Practice at SAS Health (Singapore)

A healthcare analysis system balances users, equipment and consumables. Crucial data such as proportion of medical devices and actual number of devices used, responsibility of trained personnel with health device handling capabilities, parking of medical personnel and devices, consumables deployed and needed, all can be managed effectively by installing advanced predictive analytics to accelerate healthcare success. Modern health services can be accelerated by making appropriate use of the analytical capacities of health care. Accurately locating and calibrating resource availability is key to accelerating healthcare services for efficient deployment of medical devices, patient data, clinical advancements and more. Antonio De Castro, Senior Industry Consultant, Global Health and Life Sciences Practice at SAS Health (Singapore) shares a comprehensive overview of health data analysis.

How do you define the evolution of merits and risks in predictive healthcare analytics? Are investments in big data management eligible with APAC health spending without being a burden for patients?

In terms of merit, allowing a health system to implement a change that flattens the cost curve while allowing access to an equitable health system that is both safe and provides high level care. quality is the key to success. .

Creating a health care system where staff feel capable of working in a productive and rewarding environment that improves health care delivery is also a key merit.

The development of an infrastructure that supports continued clinical trials to enable better development and delivery of drugs is also essential. When done correctly and the results are used to drive a data-driven solution for change, the expense is never a patient expense. Using data to reduce waste, eliminate unnecessary processes, and support a healthier population saves far more money than investing in analytics.

In terms of risk (which is always present in any strategy), the first is that there is an expense in a solution that does not keep its promises or that is not used to make the changes it was put to. implemented. It will then become a financial burden for patients if the investment is used to build a data management solution that has no impact.

Another risk is the possibility of excluding patients. Poor quality testing can create and reinforce bias in the healthcare system, which also leads to negative outcomes for patients and hospital staff. Data used to exclude, deprioritize or deny patient coverage is considered a risk, especially when it is also related to privacy concerns.

Overall, there are significant gains to be made in terms of patient outcomes and overall health care delivery from an analytical approach and this should not be viewed as a cost that harms the patient. Being aware of risks and their mitigation will enable APAC health care systems to become higher quality, accessible and cost effective in responding to health care needs.

How do you see the prospects and progress of APAC in the area of ​​analytics-based value-for-money?

The Covid-19 crisis shed light on health systems that did not understand the resources they had or how to grow to meet sudden demand. APAC hospitals and health systems should now consider this lesson learned to drive a strategy for optimizing medical resources to enable better crisis response in the future.

In any crisis, there are 3 stages in which analytics can play a role. These are Respond, retrieve so what Reinvent. These steps are vital in any crisis and have often not been the subject of a preparedness strategy.

Using the recent experience of a crisis to conduct situation analyzes and modernize resource allocation is likely to be driven by government incentives to improve.

The need to fight the pandemic leaves room for progress in the harmonization of health data. This will ultimately allow progress in terms of technical skills and culture around data analysis.

An example of this would be a visual analytics dashboard that was created for the Southern Philippines Medical Center (SPMC) to provide support during the pandemic. The dashboard provided an overview of COVID cases as well as available medical supplies and equipment critical to the COVID response. This prompted the Center to investigate, track and visualize their data in ways that better serve their operations.

It also sparked discussions with other healthcare providers to compare information and results. The real crisis would be if the healthcare sector did not continue the progress accelerated by the pandemic by adopting data-driven approaches to optimize healthcare processes, improve patient experience and improve health outcomes.

Hihaishi C Bhaskar

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