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Vol 24, No. 02, February 2020   |   Issue PDF view/purchase
SPOTLIGHTS
Analytics priorities for the Healthcare Professional
The increasing demand for the digitization of healthcare information from the use of electronic medical records and medical devices, calls for healthcare systems to focus on the importance of analytics platforms for healthcare data. To illuminate on analytics platforms in the healthcare industry in providing valuable insights that can positively drive clinical and business decisions is Celine Siow, Regional Vice-President for Asia and Japan at Alteryx.

  1. What are the top five analytics priorities for healthcare professionals?

    Trends such as an aging population and rise in Non-Communicable Diseases are driving demand for healthcare services, leading to the upward spiral of medical costs. According to a new study by a global health research organization, an average Singaporean can expect to live 85.4 years in 2040, up from the average of 83.3 years in 2016.1 To grapple with the economic implications of today’s healthcare challenges, many governments are looking to new models of care, in particular, value-based care. This model aims to improve patient outcomes by helping patients live healthier and prioritizes prevention over treatment.

    But to be truly successful in making the shift to a value-based approach, the investment in data and health informatics is going to be a key enabler, according to the World Economic Forum.2

    The good news is, there is potential for providers in the entire healthcare ecosystem to leverage data analytics to make better clinical and business decisions. With the digitization of healthcare information, increased adoption of electronic medical records and medical devices, the top analytic priorities are as follows:

    1. Enable the delivery of more cost-effective care
    2. Better identify patients at risk of adverse health events
    3. Reduce hospital readmission rates
    4. Minimize issues with reimbursement and payment
    5. Optimize revenue cycle management
    6. To achieve these priorities, there is a pressing need to enable access to the data required and to empower providers in the entire healthcare ecosystem to perform analyses.

  2. Where are providers experiencing the most analytics successes and challenges?

    Many healthcare providers built their analytics systems on legacy data warehouses in order to create reports and dashboards that summarize descriptive information. However, there is a lack of predictive and prescription analysis. Electronic medical records (EMR) were not set up consistently, so they can be difficult to extract data from due to a lack of standardization, making complex analytics a challenge.

    Meaningful analysis also requires approximately six data sources, but a small percentage of healthcare organizations have access to that number. Part of the problem is that data is not sufficiently democratized across organizations, making it difficult for departments to access up-to-date data.

    By democratizing data, healthcare providers can enable everyone in the ecosystem to generate meaningful insights. Data can even be drawn in from other models and third-party sources. Democratization empowers every provider to collaborate and generate actionable insights that can make a true impact on clinical and business decisions. It also facilitates scalability and governance as well.

  3. Why is enabling healthcare providers and analysts to perform forward-looking, predictive analytics critical?

    The Singaporean market has strongly embraced analytics. According to the 2019 Data and Digitization Report3 commissioned by Alteryx, the top three perceived benefits of data analytics were increased productivity (62%), more value to deliver deeper insights (48%) and the ability to uncover savings and efficiencies (48%).

    However, the report also shed light on the need for organizations to address technological and cultural challenges to be successful in building an effective data pipeline. Today, only 15 percent of Singaporean organizations in either the public or healthcare sector are at the advanced stages of their analytics journey. While healthcare providers are aware of the value in implementing data analytics to inform a wide variety of decisions, the difficulty lies in implementation, due to a lack of data democratization.

    Data analytics can inform a wide variety of decisions, ranging from those that affect the hospital floor to those that can bring change to the back office. Healthcare providers understand that this data can contribute valuable information on how they approach their work and patient care. They want to be able to leverage information to make meaningful and actionable decisions, especially when it comes to providing patient care and cutting costs. Moreover, data analytics can help HR departments obtain crucial information for procuring and maintaining hospital staff.

  4. How is the automated routine processing achieved? (I.e. in a drag and drop, click and run, code-free and code friendly environment.)

    Healthcare providers can use Alteryx Designer to prepare and blend data from all relevant data sources. Using an easy-to-use drag-and-drop workflow interface, users can leverage built-in tools to quickly cleanse, prep and blend data without having to write code.

    Alteryx takes a different approach by offering data prep and data blending capabilities through an intuitive user interface that is more efficient than traditional approaches. This approach makes predictive analytics accessible to every provider. With repeatable workflows that deliver the self-service data analytics capabilities required for predictive analytics, healthcare providers can create models with drag-and-drop tools.

    This workflow approach extends to the next step of performing analysis. Healthcare providers can leverage statistical, predictive or spatial analysis by dragging and dropping tools and then configuring them. There are more than 60 built-in tools for spatial and R-based predictive analytics within Alteryx that are as varied as drive times, regression or clustering.

  5. In what ways will patient data be stored and processed to achieve predictive analytics for healthcare?

    Like many, the healthcare industry is in the midst of a digital transformation. Take the example of the increasing adoption of health-related wearables that track physical activity and even sleep patterns, for instance. There is a myriad of insights that can be gleamed from such personalized health data. Just looking at data from physical activity over a period of time, we are able to predict mortality risk and even identify segments of a population at-risk of obesity, a precursor of leading chronic diseases. Such data, if properly integrated into the National Electronic Health Record System, can inform interventions that are at the core of value-based healthcare.

    At the heart of any analytic priorities is a structured and transparent journey for employees to find, share and collaborate on data. To achieve that, organizations need to involve IT to build a sustainable and scalable analytics strategy that meets the needs of both business and IT, without jeopardizing data quality. By allowing transparency in data usage, processing and model deployment, Alteryx is able to help everyone across the organizations explain their analytics process.

References

  1. IHME, (2018, October 16), How healthy will we be in 2040? Retrieved from: http://www.healthdata.org/news-release/how-healthy-will-we-be-2040
  2. World Economic Forum, (2018, January), Value in Healthcare Mobilizing cooperation for health system transformation. Retrieved from: http://www3.weforum.org/docs/WEF_Value_Healthcare_report_2018.pdf
  3. Alteryx, (n.d.), The 2019 Data + Digitization Report, Retrieved from: https://www.alteryx.com/apac-data-savvy-workforce-is-business-critical-and-key-to-driving-businesses-forward

About the interviewee

Celine Siow, Regional Vice-President, Asia and Japan, Alteryx

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