Work we do every day in our courtrooms. One interesting thing that did come from the study that was conducted was the value of proposition 47 for reducing Racial Disparity. I raise it here today, its one of the rare policies we see working on reducing incarceration and gives the greatest benefit to African American men, above anybody else. Thats a pleasant outcome that warrants evaluation and is the type of policy we want to prioritize across criminal justice if were going to look for areas to reduce mass incarceration and we can simultaneously impact the communitys most impacted by the policies. I think we have come to a good policy to be replicated. So this graph shows the impacts we have around prop 47 and dramatic arrests in relation to other population groups. So as i mention, the data systems within San Francisco for the das office, we have a Case Management system called damien. We input the information about the cases were processing, that system does not contain race information. The information we have on race comes from the courts Management System, which unfortunately has very outdated categories that dont even account for ethnicity. Latinos and other asian populations are not even categorized in the court Management System making it difficult to do a Racial Disparity study or anything else related to race and equity. This is hopefully an issue with justice to the resources to help facilitate the court moving over to a new system and other agencies on boarding can be improved. The places we keep race data of our own that we have confidence in, victims around the city and the services we provide to them and to build on a statement from theo earlier, it is an important area of the Public Safety conversation that we often dont incorporate in the conversation. We know very well overrepresentations of individuals accused or suspected of crime but we dont spend a lot of time talking the victims of the crimes and the sense of safety in the community they reside. Okay. Sorry. Can you go back one . So this will just that is very hard to read. Its in the handout, easier to read. It will show you for example African Americans accounting for about 6 of the population in the city but 19 of the victims. And for latinos about 14 of the population and about 30 of the victims of crime. Those may be numbers that the Commission Wants to consider further. This data we review along with all the other crime data in our monthly da stat, please stand by. Third largest proportion of latino prosecutors at 10. 1 . This does not count our support staff or investigative staff within the office, which would certainly take those numbers even higher. And in addition to diversity, we spend a fair amount of time on our Office Working on implicit and explicit virus we also brought in kimberly papion to work with us on exercises and put that out to the office to make sure its front of mind for staff. Because of the importance of the work we do and the implications that we have. That was a whirlwind. I apologize. I dont want to take up anybody elses time but im happy to answer anybodys questions or be here after. Thank you for being here. You, like the speakers we have, its an introduction to what you are doing in your departments or jurisdictions so we can begin our conversation about what we believe our city should be doing and bringing in the city agencies. So well be happy to have you back and look forward to take a deeper dive into the justice with you and the Public Defenders Office. Thank you for your leadership and for the presentation. Since our administration is antimuslims, antidaca, antiimmigration, what are some of the things that you are doing to safeguard data thats being collected. And probably the most concerning area for us is probably around immigrants, in terms of the fear that people have about coming forward and working with us and we have done as much work fair amount of work telling people we have no plan to work with i. C. E. We have a policy where people who are victims of Violent Crime they can apply for a uvisa. And we file more of those than anybody at least in the state the vast majority are not granted, unfortunately, even under prior administrations, but we have a robust policy of making sure that people are aware of that right and facilitating the application the other effort weve taken is training all of our staff on the potential for i. C. E. Showing up in the court houses, as has happened in the country, both texas and pasadena, california, to make sure that were aware what we can and cannot do should i. C. E. Show up looking for victims, witnesses or defendants, to make sure were a good partner in the city family. So weve trained our victim advocates to be that support for anybody that comes to the courthouse, expressing fears or concerns about immigration consequences within the building, but we offer an escort to that individual throughout the Court Process to make sure that theyre protected and our advocates have the hotline information so they can call immediately to get immigration counsel for anybody confronted by i. C. E. In the courthouses. Thank you. Any other comments or questions . Thank you. Thank you. Next, i would like to invite up, dr. Bennett, with the department of public health. Thank you for being here. Im dr. Bennett, director of interdivisional initiatives, which means that i do work that crosses from Environmental Health and Health Education and those things and the San Francisco health network, which has our hospitals and clinics and Behavioral Health come poep component, so i deal with the data on both sides, which is how i get to be here. So the department uses data pretty extensively. We have very little choice about having the data. Most of the time large amounts of data are required almost us for state, federal or grantrelated reporting. And the medical records that are used for clinical care. So we have lots of data. And we also use data for program planning, for billing, for services, but most importantly, we use data to improve Program Quality and Service Delivery and health quality. So we do that by tracking outcomes. We do it for directing programming to populations most at need or patients most at need. And for evaluating and setting policy. So im going to give just a few examples, because i was told to keep it short. Before i even do that, i will direct people most of the data not most, but a large amount of the data the Health Department collects, at least that that is not specific to patients, is publicly available. Probably the easiest and most userfriendly source is sfhip. Com, the collaborative of all the hospitals in San Francisco, which is overseen by the Health Department and gathers data from across the city and we consider things like Educational Attainment and unemployment and Economic Health data. So thats number of strokes and visits and things you think of. So sfhip. Org. So the example of how we track outcomes, i will take from the San Francisco health network, primary care clinics that include castro, mission, and places you are familiar with. So these slides are hard to read. I think its the screen. What we see on the slide is the clinics and this is hypertension control rate for black African American patients in each clinic. Of all the people, they know who has hypertension in the clinic who are africanamerican, which of them have that hypertension under control under that medical standard and have set goals for themselves about what level all the patients should be at and the goal next to that is that there should not be a disparity between groups. The largest disparity is between black africanamerican patients and the average and thats what all the clinics are focused on right now. Some are quite small. So we know our Patient Population is really concentrated. In some clinics, it may be just a few people, which is why that line looks so busy. Month to month, the clinic judges themselves to get an idea of how you patients are. Next slide. For directing programming, i will use our getting to zero program thats care of h. I. V. , and prevention for people at risk for h. I. V. , very heavily focused on in our clinic sites. The main thrust is out of the research and Health Education departments or areas within the Population Health division. Th this slide shows what has happened with h. I. V. Its a national model. If you look at the green line, its dropped dramatically over the last 10 years, as have deaths and new infections. People living with h. I. V. Is a good thing because its mainly because thats where we got that. This is a slide of just women. That blue line that is above everyone else, africanamerican women. So that lets the team know that while they have many reasons to feel good, there is work still to be done and thats allowed them to create new projects around prevention. If i used other slides, i could explain why theyre focused on transwomen and on youth. All of those are groups that are not following that trend that the general population of h. I. V. Positive people or people at risk of h. I. V. Are following. So thats how we use that data to create equity, we look for data that looks positive, you look to see if its positive equally across the population. And setting policy. This is out of the office of inclusion and Work Force Development looks at what the racial and ethnic makeup of our work force is and this compares that to the makeup of our San Francisco population, which is our client base. So white, asian, africanamerican, if you go down, you can see the different groups and thats where the wide gaps are. First, more white or caucasian staff than population in the city. So the red bar versus the blue. We have fewer africanamerican staff than we have people in the city. Its looking at that imbalance and helping to set policy about how we oversee hiring panels, what kind of oversight we do in terms of recruitment, hiring a recruiter to improve the racial diversity of our pools for applicants, all of those things were done in response to looking at that data. Next slide. And then just an overview of what our approach to data is. We use two methodologies. One is lean, coming out of industry that looks at how to improve a process. And when is resultsbased accountability thats out of public government, looking at how to improve services. And it basically says, use the data to define the problem, so collect good data, analyze the cause very deeply of why your data looks the way it is. Make changes. Measure the impact. And then make changes again and repeat and repeat and repeat. So data is meant to be part of an iterative process that says, we looked at the data. We made decisions based on the data and keep going back again and again, so the data is an ongoing endeavor. Not something we do one time it. Has to be something that you can look at in realtime in order to be useful for all of the uses. Questions . Thank you. This is interesting. I know you are giving us snapshots of Different Things going on, different data that you are collecting and analyzing, but tracking outcomes. Do you track them across the board for just about everything or do you choose strategic things to track . There are things about which we have no choice, like hep a outbreak. Other things are mandated but with choice. So we have outcomes around our valuebased payments. So part of the way the system is converting to reward quality work in medicaid and medicare is by paying people based on their outcomes. Which outcomes they pay for is somewhat mandated by the federal government and somewhat up to the institution. We have chosen some like africanameric africanamerican hypertension. We were required to do an equity measure and we chose that one. And others are based on what we see in the population. H. I. V. Is a very salient issue in San Francisco. It might not be something tracked as closely in other jurisdiction, probably to their detriment. And other things are clinicspecific. So every entity within our system is doing a slightly different look at their own data and people have some agency around having their own data and each clinic can look at what they, themselves, are doing and then when have both mandated and centrally decided measures that we use. We do have measures that are used across the department to judge quality of work. Is tracking live births in the city data that you collect . Yes. That is state mandated data that we and every other medical unit in the city send. And mortality data. Hospital admission data. Those things are on sfhip site. Very interesting. Look forward to having you back to go deeper into this. Any questions or comments . Well move open to the next speaker. I will slink away, too, because i have to go parent. Thank you for being here tonight. Next i would like to ask our public defender to join us tonight. Thank you. I think what i heard the District Attorney say is that the system is not racist. I would disagree with that. Everything was explained by other factors. And while i think thats partially true, i think that the data definitely shows that the system is not raceneutral. I dont think there could be any dispute about that. Even though our africanamerican population is 5 , 55 of our clients, public differ ender clients, and folks in the system are africanamerican men and women. If you look at categories of crime starting with traffic tickets, africanamericans are seven times as likely to be stopped for a traffic violation. Why is that, because africanamericans cant drive . More likely to be stopped for a drug offense, even though every study has shown that whites use and abuse and sell drugs more. If you look at the overdose rate, six times the rate for whites than blacks, but the statistic is the opposite when it comes to being arrested for drug offenses. James bell, who spoke earlier, did an amazing, groundbreaking study. It showed clearly that there were disparities. We sought to take that study and work with the university of pennsylvania, which offered to do a twoyear study independently. All we did was provide them with our files. And we opened our files up to them. They came up with a report first slide, please . Second slide. They gave us an economist and a scientist and a law professor for two years, who worked on the study. And we gave them 11,000 cases. When asking the question, what specifically did the disparities result in . They found that africanamericans are held in pretrial custody 62 longer than their white counterparts and on average serve 30 days longer in custody. These are folks that are charged with the same crime, same criminal history and all of the characteristics are exactly the same. So in other words, making an applestoapples comparison. Next slide, please. In terms of cases, the time to resolve a case is 14 longer if you are africanamerican. And on average, it was 90 days to process a case of a black defendant. 77 days to process a case for a white defendant. Same charges. Same criminal history. Same background. Defendants of color are convicted of more serious crimes than their white counterparts. 60 more felony charges and 10 fewer misdemeanor charges. Next slide. Defendants of color receive longer sentences than white defendants. Sentences received by blacks are 28 longer than those received by whites. Probation sentences received by latinos are 55 longer than those received by whites. Next slide. People of color receive more serious charges at the initial booking stage and the reason why this was significant, again, you ask the question, why, why do we get different out comes . For a person of color for the same offense, you will be charged with more serious charges and more charges. And thats when the Police Determine what the charges are. And they found that that disparity starts with the police charging and goes throughout the system. In other words, the District Attorneys, defense attorneys, are responding to the charge. So you might have a black defendant that will be charged with more serious charges than a White Department for this same conduct, given the same criminal history. So it has a Ripple Effect that effects subsequent charges and results in a person of color being convicted of more charges than their white counterparts. So that gives you an overview as to what the study found and we have a link to the study, which is quite comprehensive. The question is, what do we do about it . How do we address this . You will also see that theres a chart at the end of the materials that you have and i have them for the audience as well. Thats a breakdown of exactly what we do in our office. Were able to see for every teryn now how many pleas, trials, misdemeanor pleas, dismissals, diversions. And its allowed us to be able to look at exactly what our lawyers are doing. Were interested in the disparities in the way that our lawyers are representing clients. And we did find disparities we found one attorney that pled clients guilty to 30 felonies in a year. Weve had another that only had 5. So we started to look at those and say, which lawyer would you want . Somebody that fled somebody to 30 felony pleas or somebody that pled 5 . We started to look at the practices and we saw differences in outcomes because of the way that cases were being handled. So we have implicit bias training and mandatory coaches and meetings to ensure that were addressing that within our own office. You also see the stats that we published through our annual report and we have an annual report its against the law in San Francisco to use city