Predictive Analytics in Health Care

The health care sector has seen significant service delivery, quantity, and quality changes. The COVID-19 pandemic and rapid artificial intelligence (AI) system growth largely prompted these changes. After years of traditional methods, or the familiar “we have always done it this way” mentality, more human service organizations are embracing technological advancements. Learn how health care professionals use AI instruments for data collection and analysis to improve person-centered health care outcomes — including mental health well-being — for the future. 

Applications of Predictive Analytics in Health Care

Many AI tools and systems are available for storing, analyzing, and sharing health data. Health professionals consistently gather this data through various means. Using technology provides transference of valuable information in the current time, allows for tracking or trending a specific focus or pattern, and may identify potential areas needing clarification or errors in data documentation. These tools of technology include: 

  • Electronic health records (EHRs). 
  • Personal health records (PHRs).
  • Electronic prescription services (E-prescribing).
  • Client website portals.
  • Master patient indexes (MPI).
  • Health-related smartphone apps. 

Implementing health care predictive analytics strategies enables and strengthens a collaborative team approach to propose individualized care interventions that promote better health outcomes for individuals. The benefits of predictive health care analysis can provide ways to reduce medical costs without diminishing levels of care, including treatment for mental health disorders. Mental health well-being is receiving more media attention as a growing need for treatment strategies becomes apparent in societies worldwide. The U.S. Substance Abuse and Mental Health Services Administration (SAMHSA), in its 2019 Survey on Drug Use and Mental Health, found that one in five adults has a mental health concern.

Examples of Visual Analytic Platforms 

Various AI companies offer services to individuals and companies. Coordination of care across several platforms can be complicated using combinations of strategy, design, and engineering customized solutions to provide a holistic client care approach. Artificial Intelligence can transmit up-to-the-minute information which may help save lives or prevent further issues.

Deeper Insights

Deeper Insights enables clients to use data search, extraction, structuring, and visualization to improve efficiency and enhance care decision-making. Through the Deeper Insights AI, health professionals can become inspired to explore the incredible AI potential that can transform lives. Consulting team experts are on hand to provide assistance and use proven successful business strategies in various industries, including health care.

The Alan Turing Institute 

The Alan Turing Institute offers early-detection, cost-effective AI systems for diagnoses of mental health concerns. The approach uniquely combines interdisciplinary know-how from machine learning, neuroscience, clinical practice, and industry experience. Solutions tackle the challenge of early detection and prediction of personalized trajectories for mental health concerns.

Methods of Predictive Health Care Analysis Systems

Learn more about the methodology involved in predictive health care analysis systems:

Clinical Decision Support Systems

These tools can be a quick reference guide for various health conditions, supporting clinical care decision-making and providing interventions from evidence-based research data. Establishing a best practices clinical resource tool can guide health care professionals about symptom evaluations, ordering tests, and appropriate treatment choices for individuals.

Fraud Detection

An AI security system can help deter fraudulent practices such as forging paperwork to extend a disability claim, billing for services not received, and bogus overcharging fees.

Population Health Management

This newer approach assesses a person’s health care needs and how these needs will change over time. Reviewing current data analysis from community-based resources builds more proactive, successful care models tailored to individual needs, goals, and treatment. These approaches reveal links between physical and mental health issues and the need for integrated care interventions for overall well-being.

Predictive Modeling

Historical data and known past events can provide insight to anticipate or predict future outcomes. Selecting the correct predictive modeling technique to begin a task is paramount to saving time and reviewing accurate information. It also plays a valuable part in promoting more efficient health care financial systems, which allow for cost reductions and waste reductions to provide enhanced resources to serve the needs of communities. 

Challenges of Predictive Analytics in Health Care

Using health care AI systems will involve encountering technological barriers that pose threats, such as potential delays in care, errors or misunderstandings, and attempted security attacks. Trust is vital in the relationships with health care providers and their data systems. It is essential to minimize risks to appreciate the enormous benefits of artificial intelligence health care involvement and embrace it as part of the multidisciplinary team.

All health care providers must adhere to transmitting data securely and should receive data protection training. AI systems can detect cyber attacks and may include the use of firewall settings, encrypting sensitive data, and antiviral software updates to protect stored information.  

Challenges or barriers to health care predictive analysis may include the following:


  • No one takes responsibility for mistakes. 
  • Too many error incidents occur. 

Possible resolutions: Addressing mistakes promptly, identifying the root cause of the problem, and providing additional staff training.

Availability of Specialized Personnel 

  • A serious or specific system breakdown beyond staff capabilities may require a specialist maintenance visit.
  • Specialists may be in short supply or in high demand for their expertise which can cause delays in resolving artificial intelligence issues.
  • Specialized personnel can experience other delay factors such as inclement weather disrupting travel to a facility.

Possible resolutions: Training a member of the facility staff to investigate initial problems for possible solutions, implementing a strategy in the event of a mass system breakdown, and having a good working relationship with external AI personnel for timely responses to issues.

Ethical and Legal Obligations

  • Biased or judgmental documentation occurs.
  • Staff do not understand legal obligations for confidentiality and reporting.

Possible resolutions: Training staff on current regulations, including the statutory definition of AI, with ethics training to prevent biased reporting.

Human Errors 

  • Information enters the wrong part of the system or incorrect inputting of information occurs.
  • Information does not get added at all to the system. 

Possible resolutions: Training staff on the importance of their roles and ensuring data is free from error.

Resistance to Change

  • Staff are familiar with older methods and nervous about a new system.
  • Staff raise concerns regarding technology taking their jobs.

Possible resolutions: Providing adequate training for staff, allowing staff time for questions, and explaining how AI systems assist staff, not replace them.

System Breakdowns

  • Computer crashes or loss of functional abilities occur for undetermined periods.
  • Slower than normal functioning takes place.

Possible resolutions: Contacting a professional for advice, conducting regular system updates, and storing relevant information only.

System Costs and Maintenance

  • Too many system breakdowns occur.
  • The system is expensive to repair and maintain.

Possible resolutions: Investing in a modern, cost-effective system to save money in the long term, conducting regular system checks, and training staff to detect basic problems with a method of reporting issues.

The Benefits of Visualizing Your Data

Visualizing your health data offers the following advantages:

  1. Reduction in medical care expenses, wastage, and errors: Omitting unnecessary expenditure through using technology equipment is a continuous process to save money, time, and the environment.
  2. Abilities to store additional data within easy reach and with quick reference points access: A system needs to have the capacity space to store relevant data and promote easy accessibility.
  3. Increased employee work productivity, staff retention, job satisfaction, and business growth: People with the tools to do their jobs effectively and work in a positive environment will be more productive.
  4. Quicker decision-making processes based on outputs from cognitive technologies: Efficiently accessing data may contribute to better choices for health care.
  5. Fewer opportunities for errors with a correctly set up and maintained AI system: Reducing errors and consequences saves time and ensures individuals receive the appropriate care they need.
  6. Allowance for expertise growth through enabling data analysis and offering intelligence support: An effective system will have a user-friendly navigation guide with assistance services.
  7. Systems provide insight into client preferences, goals, and needs for person-centered care approaches: It is essential to recognize every individual as unique to provide accurate care services.

Moving away from outdated, impractical, and low-functioning operating systems means shifting the focus to more modern, practicable, and higher-functioning methods to deliver appropriate care standards. Businesses and organizations must be prepared for growing populations as people have longer life expectancies and are more likely to have multiple diagnoses requiring integrated treatment plans. AI systems designed to use predictive analytics can assist health care professionals in detecting individual client health concerns, providing preventive care strategies, and promoting overall better health outcomes for individuals.

With the right human services software for your organization, you can gather the data you need and maximize the ability of predictive analytics to help people. Are you looking for an analytics program specifically for the human services field? Discover what Foothold Technology offers. Our human services software can assist your agency with treatment planning, client tracking, case management, and more. Contact us to find out whether our program is right for your organization.