Storage and the changing face of health care

By Warren Pasque, SNIA ANZ Contributor and Hitachi Data Systems’ Industry Manager, APAC Healthcare, Industry and Alliance Solutions
Wednesday, 08 January, 2014

Storage and the changing face of health care

Governments in developed economies face some fundamental challenges when they consider their strategies for healthcare delivery today and into the future. Australia is not immune from these challenges and we are starting to see the federal and state governments react with caps on budgets and healthcare provider services.

Australia’s age demographic is changing and causing the Australian government to rethink their strategy. Today, 13% of the Australian population is 65 years of age or older and it is predicted that this will rise to 23% by 2050. People who are 65 years of age or older are three times more likely to use healthcare services and, as 65 is the current retirement age in Australia, they are less likely to be contributing as much tax.

This is one problem, but there are other issues which have the cost of health care on an unsustainable upward trend, which according to the Australian Bureau of Statistics has seen annual health expenditure increase by 45% from 1997 to 2007 to reach $4507 per individual.

Federal and state governments in Australia are looking at how we can possibly reverse the current upward trend of healthcare costs. Increasingly, they are turning to information technology to help streamline access to patient information, bring greater levels of efficiency in hospitals and clinics, and leverage lower-cost technology to improve preventative health and research. We have already seen major IT projects like the Personally Controlled Electronic Healthcare Record (PCEHR) to help boost patient safety, improve healthcare delivery, and cut waste and duplication.

Health care is in transition from its current state of a patient getting sick, diagnosis, prognosis and treatment to a future state of preventative health.

Technology advances like the Next Generation Genome Sequencing can reveal predispositions to conditions and diseases. With the dramatic reduction in cost over recent years (almost less than $1000) of a genome sequence, it becomes more feasible to conduct more of them across the population. Each genome produces multiple gigabytes of raw data.

Next Generation Genome Sequencing, along with other advances in healthcare technologies, is leading to large increases in machine-generated data. Some examples include:

  • Medical imaging - A 64-slice CT can produce up to 200 MBps of scanning.
  • Digital pathology - Using JPEG compression, the average image size will be approximately 250 MB per cm2.
  • Scanned medical records - Scanning of all paper forms associated with a patient that enters the healthcare practice.
  • Patient monitoring solutions - Now producing digital data that can be stored and analysed.

As healthcare technologies continue to advance and produce more information, it will become difficult or even impossible for clinicians to personally analyse all the information produced. It will require various tools to analyse the information and aid clinicians on diagnosis, prognosis and treatment.

The future of health care will be focused on increased productivity, reduction in waste and prevention, ultimately leading to better health outcomes for a lower cost.

The opportunity for data storage practitioners is not only to build architectures that support the most efficient deployment of healthcare applications today to diagnose and treat patients, but enable the future applications which will focus preventative health ie, predicting a patient’s predisposition to a condition and treating it before it becomes an issue.

Three key storage initiatives that should be considered:

  • Capacity optimisation - To make efficient use of storage for today’s growing number of healthcare applications, technologies like single instancing, deduplication and compression reduce consumption and waste.
  • Object storage - To support the long retention requirements of patient records (up to 15 years in some states) as well as protect against the scenario of changing or deprecated applications, archiving infrequently accessed records to an object store not only is the most cost-efficient consumption of storage but it also can enable the search and recovery of information independent of application.
  • Big data - To cope with the ever-increasing volume of machine generated data, big data solutions that support multipetabyte storage and scale out file systems will reduce silos as data grows and ensure the environment stays manageable.

Although storage practitioners are not likely to be driving healthcare workflows, they have the opportunity to be the enabling platform for the healthcare applications today and in the future.

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