CRM Best Practices

Predictive Modeling

Predictive

Age, family history, diet, exercise, and how a person habitually handles stress — all of these factors can determine someone's level of wellness and the likeliness they’ll need to receive medical attention, compared to other individuals in a defined population. While it’s easy to market to large groups with general messages, targeting consumers with an individualized approach is more efficient. The individualized approach does present its own challenges, but with a proper predictive modeling strategy, hospital marketers can maximize market share, manage costs, and improve overall patient care and satisfaction.

The majority of industry stakeholders agree. According to a survey by Health Catalyst, nearly 80 percent of hospital leaders said predictive analytics can improve the future of healthcare. As of September 2016, however, only 31 percent of surveyed hospitals reported using the technology, although 38 percent said they had plans to adopt predictive modeling strategies in the next three years.

In this installment of our CRM best practices series, we examine the critical role predictive modeling plays in individualizing messaging and how it can help your healthcare marketing team.

What is predictive modeling?

Predictive modeling involves assessing aggregated data to determine the likelihood of certain potential outcomes coming to pass. In healthcare, it is generally used to understand what types of attention or services a person is likely to need in the future, based on the individual’s current state of health, behaviors, and lifestyle factors. Such predictive strategies can also be used to anticipate costs and more effectively manage the health of specific populations.

How can predictive modeling help hospital marketers?

Predictive modeling helps your marketing team better address consumers when they need your help the most, through statistic formulas designed to identify trends shared among variables. It can help hospital marketers achieve a number of goals. For example, you could use predictive modeling to:

  • Identify at-risk populations. Distinguishing common risk factors — such as medical history, age, and lifestyle habits — gives marketers a better idea of whom they need to reach in a certain population.
  • Segment the market with greater accuracy. Predictive modeling can assess risk based on how closely a patient’s current state of health resembles the model, which allows hospital marketers to personalize their communication strategies.
  • Establish message urgency. Certain patient needs generate greater urgency, which allows marketers to send correlating information when patients seem most responsive and approachable.
  • Select the most effective channels to reach the right individuals. With predictive modeling, you can keep track of individuals’ propensity for engaging through certain marketing channels, improving your message’s odds of success by leveraging the recipient’s preferences.

How can predictive modeling be leveraged in a CRM strategy?

By integrating predictive modeling into your CRM strategy, you can better identify market opportunities that best align with your health system’s goals. The insights you gather will improve your CRM marketing’s effectiveness by getting the right message to the right consumers at the right time and through the right channel.

Predictive modeling can give hospitals the information they need to bring in new patients, manage current populations, and increase the loyalty of affiliated parties. By meeting patients where they are, you can demonstrate that your health system is focused on their care needs and on making their experience more convenient and positive overall, which helps to ensure they will keep choosing your brand.

Learn more about Predictive Models.

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Read the next installment of this series: Attribution >>

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