HCI-660: Health Data Analytics.

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This HCI-660: Health Data Analytics course introduces techniques for extracting data and creating knowledge from health care data sets. Learners examine methods for describing, summarizing, and presenting data. There is a specific focus on understanding the needs of information users, identifying organizational objectives, and ensuring that the analytical methodology chosen meets those needs.

What Is Healthcare Data Analytics?

Healthcare data analytics is the process of analyzing current and historical industry data to predict trends, improve outreach, and even better manage the spread of diseases. Thus, it is mainly used to reveal paths to improvement in patient care quality, clinical data, diagnosis, and business management. Most importantly, a combination of business intelligence, data visualization tools, and health care data analytics can be used to assist managers to operate better. This can occur by providing real-time information that can support decisions and deliver actionable insights.

HCI-660: Health Data Analytics

The positive impact of healthcare data analytics.

Business intelligence (BI) and reporting solutions are very significant in the business industry. The healthcare industry is no exception, these tools are useful since they increase operational efficiency, reduce costs, and streamline processes via measuring and leveraging KPIs to spot opportunities and inform decision-making. The analysis of medical data is beneficial to patients, medical providers, payers as well as suppliers. Therefore, healthcare analytics is a field that has a huge positive impact on the healthcare industry.

Advantages of healthcare analytics for medical providers.

  • Healthcare analytics helps medical providers to improve performance by delivering data-based quality care.
  • Healthcare analytics also assists medical providers to lessen patient wait times by measuring and leveraging scheduling and staffing procedures.
  • Medical providers are able to improve patient satisfaction and quality of care by streamlining tedious processes related to making appointments, processing insurance, and providing referrals.
  • Medical providers use healthcare analytics to assist them in providing the patients with more personalized treatment and improve the overall patient experience.
  • Healthcare analytics helps medical providers to reduce readmission rates by leveraging population health data against personal patient data to predict at-risk patients.
  • Healthcare analytics helps to monitor patients seeking emergency services/complex ailments. In addition to monitoring patients, it helps in offering customized care solutions that would otherwise be impossible without sufficient data.
  • Health analytics helps to improve patient satisfaction and engagement which is a major concern for many healthcare services.
  • Human error such as a physician prescribing the wrong medication or the wrong dosage not only increases the risk to patients but also increases the insurance and claims costs healthcare facilities absorb. Fortunately, by using health analytics medical providers can lessen these errors.

Advantages of healthcare analytics to payers.

  • Healthcare analytics helps payers to identify and target prospective members by analyzing profiles and demographics.
  • It helps payers to assess hospital claims and prescription fulfillment data to create targeted campaigns for specific health conditions.
  • Helps to leverage pricing data against quality metrics to identify the highest value, lowest cost providers for certain procedures and services.
  •  It is easy to adjust to any regulatory changes through embedding an analytics solution that inherits the existing security model.
  • Healthcare analytics helps to identify the potential for fraud by using predictive analytics to determine and notify at-risk claims.

Advantages of healthcare analytics to the population.

  • Healthcare analytics helps to close care gaps by measuring patient-provider ratios based on specific conditions.
  • By using predictive analytics to identify high-risk patients, managers are able to optimize staff allocation and funding.
  • It helps to carefully track and measure patient intake and conditions to predict and intervene in possible epidemics.
  • It helps to measure patient health outcomes to accurately determine the success of certain programs and treatments.
  • Most importantly, healthcare analytics enables us to track and analyze provider performance, patient satisfaction, and other key metrics. These help us to inform everything from resource allocation to funding initiatives.

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