Helping Identify & Reduce Institutionalized Bias
P-CIS provides three standard dashboards to assist staff and providers to make decisions about care options for a person and for a program. Using our revolutionary Success Focused Artificial Intelligence (SF-AI), P-CIS provides interpretable results designed to help care workers use their own expertise and knowledge, supplemented by their history of success, to make the best and most appropriate decisions for care. Railing against institutional bias, P-CIS returns examples of successful outcomes on which to base future successful decisions. Traditional AI bases future predictions on past decisions, institutionalizing poor decisions. In contrast, SF-AI provides users with information on all of the options which have resulted in successful outcomes for people with similar circumstances, helping care providers to make decisions which are more likely to result in success again and again. Rather than regressing to the mean, P-CIS helps providers regress to the best. Somewhere, at some time, a person with those circumstances avoided falling through the cracks. P-CIS capitalizes on those examples of success to identify how we can do better. Over time, as SF-AI continues to support good decision after good decision, considering the full combination of circumstances that a person faces. By regressing an organization toward decisions for optimal well-being, P-CIS promises to help reduce institutionalized bias.
Excitingly, P-CIS securely and directly connects an agency’s data directly to powerful analysis engines of R and Python, allowing agency analysts to develop their own intelligent statistical models, such as regression, latent class analysis, random forest and even neural networks right in P-CIS. There is no longer any need to export data from an EHR into a CSV file and import it into another statistical processing application for higher level insights as P-CIS automates analysis directly from assessment data, right after assessments are captured. Providing boundless options for visualization, P-CIS supports filtering and drilling-down for real-time discovery. Dynamic visualizations with deep learning statistical models are directly available and distributable to an unlimited number of users. Say goodbye to expensive visualization tools that perform only descriptive statistics and do not connect directly to your production data while charging extra fees for distribution of static reports to a broad audience of users. P-CIS has the ability to support and even automate your wildest dreams for insights into your data.
What do you think you will learn? How many lives could you improve if you asked your data to tell you how? How much more efficient could your staff, programs or agency be if they regressed toward the best? Find out with P-CIS. You will never know if you don’t try.