Obtaining insurance authorization for applied behavior analysis (ABA) services has become a routine job expectation for many board certified behavior analysts (BCBAs). Navigating insurance authorizations can be daunting for BCBAs because it requires them to write goals that align with medical necessity and each funder’s unique requirements. Failure to write goals in this manor can lead to partial or full denials for authorization for services, resulting in less access to care for clients. This presentation will focus on understanding funder-specific requirements for ABA services, tying the core deficits of autism to those requirements, and writing treatment goals that are individualized to the client and that are likely to be authorized by funders. Participants will be guided through case examples and practice describing medical necessity, writing treatment goals, and requesting authorization for services from funders.
In the current ABA and landscape we have seen a steady increase in the need for ABA services throughout the United States. This demand has subsequently driven the need for BCBAs to provide that care. Current information says that ~50% of all BCBAs have had their certificate for less then 3 years. This indicates that a majority of the workforce is new to the field. As a BCBA you are asked to be competent in dozens of various skills in areas you may not have been adequately trained for or trained at all. On top the daily speedbumbs that may arise to make your day-to-day clinical life challenging we are also faced with technology and administrative burdens. During this session, Dr. Rodriguez will discuss how these challenges can be addressed and mitigated by using OMB applications to support clinical teams, and ensure higher quality care for the families we care for.
Learning Objectives:
1. Identify OBM Applications to support common concerns in ABA Clinics.
2. Identify OBM solutions that may help your performance improvement needs.
3. Identify OBM solutions to help new BCBAs thrive in an oversight role.
Data-driven decision-making is at the core of Applied Behavior Analysis (ABA). Technology advancements continue to shape how behavior analysts and other ABA professionals approach client care. Traditional pen-and-paper documentation is steadily giving way to innovative digital solutions. Using technology for data collection improves accuracy and efficiency and allows behavior analysts to more rapidly make data-driven decisions to improve client outcomes.
Importance of Data Collection for Children with Autism
The vast majority of ABA clinicians, over 70%, work within the autism population (BACB). Each child is unique and requires individualized, data-driven care. As such, ABA clinicians know the importance of accurate and efficient data collection for driving the best possible outcomes. Data enables behavior analysts to develop tailored interventions based on a client’s needs, track progress, analyze trends, and make data-informed modifications about their progress on an ongoing basis. Data is crucial for assessing the effectiveness of interventions and ensuring clients progress toward their long-term goals.
How to Improve Data Collection with Technology
While many options exist for collecting ABA data, technology-based methods have emerged during the current digital age. Utilizing technology for data collection comes with many advantages. By using a data collection software that is tailored to the unique needs of ABA professionals, organizations can improve client and staff outcomes, resulting in improved quality of life for clients and higher job satisfaction for staff.
ABA organizations can improve their data collection methods by adopting digital-based data solutions. Some of the benefits of transitioning to a technology-based data collection method include:
Reduced chances of human error– Improved accuracy is one of the primary benefits of digital data. When using paper data, technicians may be unable to immediately enter data, resulting in data entry several minutes after the observation, reducing accuracy. Digital data collection allows staff to seamlessly enter data in real-time, which reduces the chances of staff forgetting the correct information and thus entering inaccurate data. Entering data only once, rather than transferring paper data to another system, also reduces the likelihood of human error.
Increased efficiency– Digital data platforms allow technicians to enter data immediately upon observation, saving time and allowing technicians to focus more of their attention directly on their clients rather than being bogged down with paperwork. Digital data also makes session note writing effortless, allowing technicians to end each session with a well-written, concise note.
Streamlined data analysis– With real-time data submitted electronically, behavior analysts can readily analyze data, allowing them to make well-informed, data-driven treatment decisions. This all leads to more effective and individualized interventions.
Enhanced security and privacy– Digital ABA data also enhances the security and privacy of client data when using a HIPAA-compliant platform. All client data and session notes are housed in one secure location rather than on numerous data sheets that can be lost or misplaced.
Ease of use– In a fast-paced therapy session, carrying around a clunky clipboard or binder and scrambling through data sheets can be a challenge. Using a phone, tablet, or other compatible device, a technician can efficiently move about the session and seamlessly enter data as the session progresses without missing anything. Whether chasing clients around their homes or working out in the community, digital data makes this much more manageable.
Increased compliance– Maintaining records in one secure location increases compliance with laws, funding requirements, and regulatory bodies.
Why Are Some ABA Professionals Still Using Paper?
Despite the countless benefits of technology-driven data collection, some ABA clinicians still cling to paper-based and other disintegrated methods. This reluctance to transition to digital data collection often stems from a pre-existing comfort with using one’s current system. While paper data collection is less efficient and comes with other challenges, such as increased proneness to error and risk of non-compliance, change can be difficult to accept. Some behavior analysts may continue to use paper data because they feel it has worked well enough for them thus far. Likely, many are simply unaware of the available ABA data collection solutions and their benefits.
Other reasons ABA professionals may avoid adapting to digital data collection may be concerns regarding technology complexity, a lack of time to learn new methods, and the costs associated with digital platforms.
At Raven Health, we recognize the concerns many ABA clinicians have with transitioning to digital data collection. As such, we are committed to making the switch as seamless as possible.
Raven Health’s Mission to Equip the ABA Industry
Raven Health enables behavior analysts to harness the power of data collection effectively. With innovative software tailored for ABA, clinicians can improve client outcomes while improving staff satisfaction.
Schedule a demo today to see our platform in action and learn more about how we’re improving care through technology.
ReferencesCooper, J. O., Heron, T. E., & Heward, W. L. (2019). Applied Behavior Analysis (3rd Edition). Hoboken, NJ: Pearson Education.
Applied behavior analysis (ABA) is a data-driven science. Data collection and analysis are at the heart of what ABA practitioners do. Each learner has unique behaviors and environmental variables that can impact data collection needs. There is no one-size-fits-all approach in ABA. In this blog, we will dive into the intricacies of the various ABA data methods.
What is Data Collection in ABA?
ABA data collection is a systematic process of gathering information about a learner’s behavior, their environment, and the circumstances surrounding their behavior. This data is crucial for behavior analysts to understand the learner’s behaviors and current skills, inform interventions that best meet the learner’s unique needs, and monitor progress to ensure ongoing success.
Types of ABA Data Collection Methods
There are several different ABA data collection methods. Each method has its’ own benefits depending on the goal, learner needs, environmental factors and barriers, and the resources available to the behavior analyst.
Methods for collecting quantifiable behavior data are divided into two categories: continuous and discontinuous. Continuous data consists of measures like latency, count, rate, interesponse time, and duration. These methods involve tracking each occurrence of the target behavior. Conversely, discontinuous data consists of measures such as whole and partial interval recording and time sampling. Discontinuous data involves recording some, but not all, occurrences of a target behavior. Continuous measurement is more accurate and concise. However, discontinuous measurement is often better when time constraints and other environmental barriers are at play.
Overview of the Most Common ABA Data Collection Methods
1. Latency Recording
Latency is a measurement of the time between the presentation of a stimulus (e.g., a demand) and the onset of the behavior. For example, if you instruct your student to go get their backpack and they get up two minutes later to get it, the latency is two minutes. Latency recording is beneficial for monitoring delayed responses.
2. Event Recording (Count and Rate)
Event recording is one of the most common data collection methods in ABA for tracking target behaviors and skills. Event recording measures the number of times a particular behavior occurs. The count is an overall tally of the behavior. For example, recording your client manded (requested) 12 times. The rate measures the number of times the behavior occurs across a specified period of time. For example, if your client mands 12 times in a 2-hour session, the rate would be 6x/hour.
3. Duration Recording
Duration recording is your best option when you’re interested in knowing how long a particular behavior lasts. Duration involves recording the total time from the start of a behavior until the behavior ceases. Recording duration is best for behaviors that have a discrete beginning and ending.
4. Interresponse Time
Interresponse time consists of recording the amount of time from the end of one response to the beginning of the next. For example, if your client spits, then 14 minutes later, they spit again, then the interresponse time between the two occurrences of spitting was 14 minutes.
5. Whole Interval Recording
Whole interval recording is a discontinuous measurement procedure. In this method, the observation period is divided into intervals of time. During each interval, if the client engages in the target behavior for the full duration, the interval is marked with a +, ✓, or yes. If the client does not engage in the target behavior for the entire interval, it is marked as a -, X, or no.
6. Partial Interval Recording
Partial interval recording is another discontinuous measurement procedure. Again, start by breaking the observation into intervals. Record a +, ✓, or yes for each interval that the client engaged in the target behavior at all during the interval.
7. Time Sampling
Another discontinuous measurement procedure is time sampling or momentary time sampling. In this method, the session is divided into intervals. At the end of each interval, the observer records whether or not the behavior is occurring at that time. Partial and whole interval recording and time sampling are often used in schools and other situations when continuously observing and recording each occurrence of a target behavior is not feasible.
8. Trial-By-Trial/Per Opportunity Recording
Trial-by-trial or per-opportunity recording is commonly used for skill acquisition data. This method consists of recording the total number of times the learner engaged in the target behavior or demonstrated the target skill out of the total number of opportunities. For example, imagine you’re teaching your client to respond to the question, “What’s your name?” You ask them this question five times throughout the session. Two of the times you target this skill, they answer correctly. Thus, the per opportunity data would be 2/5 or 40% accuracy.
9. Rating Scale Data
Rating scales are used to assess and monitor behavior on a continuum. This type of data measurement is more subjective than the others. However, they can be beneficial in certain circumstances. Rating scales can be used when teaching a learner to self-monitor and evaluate their own behavior. Rating scales can also be used to assess the magnitude or intensity of a behavior, such as the intensity of aggression or the magnitude of a learner’s voice volume.
10. Antecedent-Behavior-Consequence (ABC) Data
ABC data comprises recording the antecedent (the event that occurred directly before the behavior), the target behavior, and the consequence (the event that occurred directly after the behavior). ABC data is crucial for behavior analysts to better understand the variables surrounding their learner’s behavior. By analyzing ABC data, behavior analysts can identify the potential function(s) of the behavior by looking at trends in the antecedents and consequences.
11. Scatterplot Analysis
A scatterplot analysis is another method for analyzing target behaviors. Scatterplot data helps behavior analysts visualize the relationship between different variables, such as the time of day and the target behavior. This is beneficial for identifying patterns in the learner’s behavior.
Raven Health’s ABA software makes data collection seamless for behavior technicians and behavior analysts. With a user-friendly interface, ABA professionals can utilize a wide range of data collection methods that address the unique needs of the learner. Book a demo to learn more about the data tracking and analysis tools available with Raven Health.
Choosing the Best ABA Data Collection Method
The method of ABA data collection you use depends on many factors. Consider the following questions when determining the best method to use.
Are you tracking behaviors targeted for reduction or skill acquisition?
Are you seeking to identify variables related to the target behavior or quantifiable data, such as how often the behavior occurs?
Can you count the number of times the behavior occurs or how long the behavior occurs?
What resources are available?
Are there barriers or time constraints to data recording?
Which data method would best support the learner in meeting their individualized goals?
Which method allows the ABA professional to maximize time spent with the learner?
Raven Health’s Mission to Equip the ABA Industry
Raven Health enables behavior analysts to harness the power of data collection effectively. With innovative software tailored for ABA, clinicians can improve client outcomes while improving staff satisfaction.
Schedule a demo today to see our platform in action and learn more about how we’re improving care through technology.
ReferencesCooper, J. O., Heron, T. E., & Heward, W. L. (2019). Applied Behavior Analysis (3rd Edition). Hoboken, NJ: Pearson Education.
In the current ABA landscape, we have seen a steady increase in the need for ABA services throughout the United States. This demand has subsequently driven the need for BCBAs to provide that care. Current information says that ~50% of all BCBAs have had their certificate for less than 3 years. This indicates that a majority of the workforce is new to the field. As a BCBA you are asked to be competent in dozens of various skill in areas you may not have been adequately trained for, or trained at all. Often times the process of learning how to approach family guidance is ignored during a BCBA’s training process. Subsequently, they are not prepared to conduct effective and meaningful family guidance. In this session, we will explore strategies for BCBAs to use in their programming to better connect with caregivers, provide more effective family guidance, as well as how to ensure BCBAs can stay consistent in their delivery thus better empowering families to transition care away from daily ABA programming.
Learning Objectives
1. Explore the current system that generates BCBAs and the shortcomings in that process and the issues it can create.
2. Develop strategies to build rapport with family.
3. Discuss why strong caregiver relationships are essential to effect care.
