If you opt to include a prescreening process in your SBIRT protocol (that is, asking a single question such as whether the patient binge drinks), then you will have this sector of data for every SBIRT patient. Prescreening data should be separated by type (i.e., alcohol, drugs, tobacco, depression, etc…). In many cases, these data will be binary (1,0 or T,F) because they will either present as ‘Positive’ or ‘Negative.’ These data can provide you and your stakeholders with a broad picture of the level of a given morbidity in a population (i.e., “XX% of your patients prescreening positive for problematic alcohol use” is a quick and easy way to conceptualize the burden of use in your patient population). If the number pre-screening positive is too low, you may suspect a problem in the prescreening process or the patients’ understanding of the question.
Depending on the screening tool that you choose to use, these data also can be used to check for discrepancies in application. For example, prescreening and screening data can be checked for logical impossibilities to find errors in the patient flow within a clinic (for example, most alcohol prescreening questions preclude the possibility of that patient scoring a “0” on the AUDIT. If such an instance occurs, then there is a problem with the system).
If you use a prescreening process, then you will have screening data only for patients who prescreen positive or who are assigned to complete a screening by a physician or other concerned medical party. If you use a screening-only process, then you will have screening data for all patients. These data will cluster across a range of values which are dependent on the screening tool. For example, the AUDIT is scored from 0 to 40. Within that range, there are four zones of use, each of which suggests the need for a different SBIRT process regarding the patient’s alcohol use. These data can be very useful to stakeholders.
For example, if your organization uses a prescreening process, then the screening data will exist only for patients who are likely to exhibit problematic, risky, or dependent use. It is possible to both provide a sense of the severity of a given morbidity in the patient population (i.e., “of the XX% of patients who prescreened positive for alcohol use, the mean AUDIT score was XX, indicating…”) and to separate patients by zone (providing frequency data by zone… “XX% of patients fell into Zone 1, XX% fell into Zone II, etc…”). This illustrates both the prevalence (breadth) and the severity (depth) of a screenable condition within a patient population.
You will likely keep track of the services provided to patients.
Depending on the type of SBIRT project you implement, these may include brief intervention (BI), brief treatment (BT; a less common modality), and referral to treatment (RT). Most validated screening tools provide recommended levels of services based on screening scores. Not only can this data inform stakeholders of the work being completed as part of your SBIRT project, you can also match these data to screening scores in order to determine whether appropriate actions are being taken by caregivers (if not, why not?). Be alert to the very common problem of patients being given appointments for followup but not keeping the appointment: thus, tracking appointments made and kept are both useful to assessing your program.