Impacts of Technological Change: OSH Systems
welcome to the third installment of the 2022 expanding research Partnerships webinar series today's webinar topic is promoting Partnerships to explore the impacts of technological change on work and well-being with a focus on OSH systems before we get started a little information about our continuing education credits for continuing education credits are available with this presentation through the cdc's training and continuing education online system we are pleased to be able to offer continuing education for a variety of professional groups as seen at the top of the slide detailed instructions on accessing the training and continuing education office site are available for download at the website shown on the screen that website is tceols.cdc.gov please note that the live activity number listed on screen is only valid for those watching today's live webinar you will need the course access code to receive credit the archived activity number shown on the screen is to be used only by those who view the webinar recording later or attempt to access CEUs after October 14 2022. we are recording today's webinar and we plan to post the webinar recording on the CDC YouTube channel worker safety and health playlist within a month for those who cannot join us today now it is my pleasure to introduce Dr Jessica stright niosh's deputy director for research integration thank you Nicole on behalf of niosh I would like to welcome everyone to our September expanding research Partnerships webinar exploring different perspectives on the impact of technological change on work and well-being today we are pleased to bring together Partners from the occupational health and safety Community to consider the impacts of technological change on work and well-being with a focus on occupational safety and health systems it is my pleasure to introduce today's distinguished speakers I will briefly introduce them both now so we can move smoothly and quickly between presentations for those who are interested full bios are available on the niosh expanding research Partnerships webpage our first Speaker today is Dr Emily Haas Emily is a research health scientist in the niosh National personal protective technology laboratory or npptl where she serves as principal investigator for several projects seeking to identify personal organizational and environmental risk factors in workplace settings her work emphasizes the application of Occupational Safety and Health Management System elements including Employee Engagement and culture enhancement to improve the integration and safe adoption of new Occupational Safety and Health Technologies for her excellent work in this area Emily has received several prestigious Awards today's second speaker is Dr Zeke McKinney as an occupational and environmental medicine practitioner Zeke is one of few clinicians in Minnesota who evaluates work and Community related environmental toxicologic exposures Zeke is also the program director of an occupational and environmental Medicine Residency program an affiliate assistant professor at the University of Minnesota School of Public Health and a clinical investigator for the Health Partners Institute he focuses on ensuring that Health Care Systems address the social determinants of Health including Health Care Access housing employment environmental hazards and nutrition Zeke is passionate about Justice for All and ensuring that Health Care outcomes and preventable hazards are equitably distributed across populations rather than disproportionately affecting some more than others and now we are ready to begin our webinar approximately 70 minutes of presentation from our speakers will be followed by a question and answer session with the audience please enter your questions for our speakers in the Q a box on your screen at any time during the webinar without further delay I'd like to introduce an invite Dr Emily Haas to our virtual Podium as today's first Speaker Emily welcome and thank you for joining us today great thank you so much Jessica for the introduction and for the invitation to present at this niosh expanding research Partnerships webinar so the presentation that I am giving today is titled using health and safety Management Systems to facilitate the integration of new technologies and I'm really looking forward to sharing some of the things that niosh's Center for director reading and sensor Technologies has been up to the last year or so so with that I will go ahead and get started so throughout throughout my time today I have a few objectives so first of all I will discuss occupational health and safety Management systems and complementary Management Systems thinking related to director reading and sensor Technologies and then after providing this Foundation I will introduce and discuss the results of an online survey LED out of niosh's Center for direct reading and sensor Technologies and then using feedback from the survey I highlight some potential implications for leveraging core elements of health and safety management system to facilitate technology integration in the workplace with worker well-being in mind thank you so before I progress through these goals today I wanted to spend a couple of slides just on semantics and definitions so we're all on the same page and I do want to start by acknowledging that there are a variety of specific Technologies and processes that have been developed with respect to Industry 4.0 that could Monitor and provide alerts in the field for workers for the purposes of this presentation I will likely use the broad term of Technologies just for brevity although if I do use that term I am specifically referring to the application and use of direct reading and sensor Technologies or drst drsts can monitor and alert workers exposure to contaminant health hazards and physical safety hazards in the field you see some examples of drsts on this slide including direct reading methodologies or instruments real-time monitors and wearable monitors that may collect different types of data points so again throughout my discussion today I'll either use drsts or Technologies interchangeably and then moving on to the definition of health and safety Management Systems there are also many variations available here in this presentation I pull from a couple so first I reference the International Organization for standardization or iso's language which indicates that an hsms provides a framework for managing health and safety risks and finding opportunities to prevent injuries and illnesses as well as provide strategic and operational decisions for an organization a combination of multiple health and safety management system elements and practices are necessary to achieve these results there are also several hsms Frameworks that are available available that companies usually consult and tailor as needed to fit the size of their organization or resources that they have and these Frameworks are often based on a continuous improvement process to help control risks to an acceptable level and these all advocate for some form of that plan do a study check act processed and you can see that continuous cycle on this slide you can also see in the middle of that slide specific elements around leadership communication and engagement which I'll talk about a little bit more on the next slide so the ISO definition provides a nice universal view of an hsms but for this presentation I do specifically focus and pull from the occupational safety and health administration or OSHA's published guidelines for recommended hsms practices that contain seven inter-related elements that you can see on this slide these seven elements are also consistent with those discussed in ISO standards and the ANSI aiha Z10 programs as well as I just said on the last slide there has been some emphasis in updated guidelines on some of these elements specifically management leadership and employee participation have been discussed as fundamentally connected activities that weave through the other system elements and according to the national Safety Council possessing a certified hsms with strong leadership and employee engagement really shows an organization's commitment to ensuring good working conditions worker Health well-being and Equity practices on the job additionally successful health and safety management is reliant on effective communication not only from you know the top down or the down up but really across organizations and employees as well so given their increasingly important Focus I refer to these elements as kind of the core hsms elements and I'll get into the practices of these elements throughout the presentation as well so although many Technologies inherently managed worker safety and health and hazardous workplaces research around the intersection of these two areas is a little bit more limited and within our Center we wanted to bring these two bodies of knowledge together to study how the intentional use of core health and safety management system elements could be leveraged to facilitate new technology adoption among both employees and Employers in a way that keeps the well-being of the worker at the Forefront so using data collected from OSH professionals we compared individual and organizational concerns around integrating drsts in the workplace to understand differences in perceptions between individual workers and their employers when it comes to new technology integration so in 2021 niosh's Center for direct reading sensor Technologies engaged in formative research using an online survey to understand how various technologies have been used in the workplace as well as strategies benefits and barriers to adoption among participating employees and their employers so the survey was announced and made available at the end of several virtual conferences and had open and close-ended questions with a variety of response options this presentation only highlights a small snippet of the results provided by the 88 convenience responses that were received so here are some brief um kind of information and background about their respondents you can see that respondents affiliated with manufacturing Mining and oil and gas the most with the remaining sample identifying with other sectors or multiple sectors and using the American industrial hygiene association's definition of tier-based competencies half of our sample reported being Advanced users of drsts with half also having more than 21 years of OSH experience this presentation uses results from questions around perceived concerns to implementing drsts rather than specific uses and case examples of drsts that were already in practice but we are highlighting some of these more specific results on our website and additional blogs and presentations in the future so specifically in our survey we asked individuals to check all that applied to them regarding a specific drst concern that they had in the workplace as well as those perceived concerns of their organization or organizational management and the table that you see on this slide shows the percentage of respondents who noted a specific concern related to these new technologies in their workplace as you can see in the first row reliability and validity of data received was the top concern noted by individual respondents whereas they felt the organization's top concern that they worked for was the additional cost investment of these new technologies in the workplace standardization of data was a high concern in both groups while individual respondents perceived issues around user acceptability ease of use and integration with other non-drst Technologies to be barriers to widespread implementation and use I can probably spend a whole presentation just on this slide but we don't have time for that so the main thing that I want to note here is that the perceptual differences between these two groups already shows that potential disconnect between some of the organizational processes and priorities that may be in place for implementing and procuring new drsts and then by the workers who use this technology and this disconnect can already start to Foster that Stress and Anxiety among end users and is something that we can definitely and should further explore to really promote worker well-being as we're integrating these new technologies and overall these responses did help frame the qualitative analysis of our open-ended comments which I discussed next so interestingly the inductive qualitative analysis from our open-ended questions revealed several themes that are not well documented in the literature and can be used to glean some potential barriers to future grst use regarding the impacts on worker well-being so specifically results provide an opening to use some health and safety management system elements and practices to advance the integration initiatives and priorities again keeping that worker well-being in mind these themes include acceptability and Trust in technology ease of use and support and guidelines and I'm going to briefly highlight these three themes on the next few slides so first the open-ended feedback commonly referenced concerns around trust in these new technologies from several angles a lack of trust in the data produced by Technologies was a trend as noted in a quote on this slide which also mirrors the survey responses where 58 of respondents noted that this was a personal concern for them respondents also noted individual concerns around data privacy as well as ensuring that the data was reliable respondents also noted that some employees think that drsts listen or record their productivity or what they say on the job which causes some additional stress and anxiety and that came out in our open-ended feedback as well from an organizational perspective respondents felt that their employers also didn't fully understand the health and safety benefits of drsts and that this lack of awareness or buy-in of those benefits was perceived as a primary inhibitor for their employers purchasing and using drst so again some disconnects that need to be mitigated in the planning stages another theme was the challenge of using either one or many Technologies in the workplace and examples included training and retraining employees on not only how to use these new drsts but also how to interpret alarms and alerts and then how to respond to the alarms and alerts as they are triggered for example one respondent noted that the variety of instruments needed for all types of exposures creates problems for workers trying to remember which buttons to push which can become a safety concern over time other respondents took this concept further and noting the challenge of getting non-ih employees to not only use and understand these Technologies but to do so with little oversight and feedback and then from an organizational perspective respondents felt that their employers can be easily disappointed because not all of these drst processes are the same and if benefits aren't realized really quickly um many people noted that programs can be shelved before they can even take off and so along these lines individuals often felt that integrating drsts and making sense of the data to communicate implications to upper management was a challenge and often stressful for them and then last there was an abundance of feedback that really referenced the lack of guidelines and best practices available to support the use of these new Smart Technologies in the workplace for example one respondent noted that getting regulatory bodies to accept data was the biggest barrier for them while another said without external support from governing bodies to use drst in the workplace for certain monitoring that really this just becomes one more thing that people have to do and becomes an additional stressor on the job and instead of a health and safety Aid so without some sort of best practice it can be hard to share and interpret the data across organizations so after going through all of these results you might be wondering you know what does this have to do with an occupational health and safety management system well a lot um research has argued that the future adoption of Technologies is really dependent on the ability of occupational safety and health professionals to address identified barriers to acceptance and fortunately these results identified several barriers that we can help control by using elements of an hsms to help develop a consistent narrative and implementation strategy for these Technologies to not only promote adoption but support worker well-being while we're doing that so when organizations integrate drsts they're likely to consult and use technical practices that are already outlined in their hsms such as engineering controls and auditing and training to ensure that certain regulatory criteria you are met however I'm bringing us back to this consideration of those core hsms elements that are shown again on this slide in a little bit different format that may not always be considered so this oversight um is it's kind of been notable because we see that in our results with the lack of trust management support and inconsistent guidelines and communication these were all common barriers that emerged in our survey and common barriers to integrating and using drsts so if organizations can execute these health and safety practices outlined in our system Frameworks it can help send a powerful message to employees that the organization does care for its workers so in how are you thinking how we do this I have just a couple of slides left that provide some adopted health and safety practices as recommended in hsms Frameworks and OSHA guidelines based on our results so I provide some of these practices in the realm of that plan do checked study act process that I highlighted earlier to really show the application of an hsms as a continuous process in the workplace when you are introducing and monitoring anything so first the results show that managers commitment to integrating Technologies is increasingly important for employees to visibly see to increase their trust in these new technologies and we argue that managers can visually show their commitments to these new technologies by allocating resources such as training and additional support and then being visible during the planning stages to answer question and then being visible during that implementation phase to answer questions so as drsts are implemented in the workplace showing a plan to discuss the purpose of the technology and providing resources to ensure success can really support worker perceptions and buy-in and then looking at this last example we have some practices on this slide that are relative to worker engagement and communication within a management system there were a lot of messages provided by respondents about the role and positive outcome of employee involvement so one respondent stated employees can be great participants in exposure monitoring efforts if they're approached in an honest manner responsible Manner and they're provided with results at the end of the monitoring period so to this end involvement in these processes during planning and implementation can again improve employee buy-in of new technologies and help employees understand why certain procedures are important to follow additionally employee involvement can create a non-threatening environment where employees feel comfortable approaching management to discuss safety concerns and then finally considering how to best utilize worker engagement within a management system extends Beyond only involving the end users and the process so organizations should also consider how to holistically extend beyond just those end users to involve relevant departments such as it which was one example brought up within our open-ended comments that some of these instruments are complicated in terms of downloading and then interpreting the data it could be a little bit unpredictable with how that process might work and that it can be a valuable partner to connect devices and show how data can be used So within throughout this slide we provide kind of practices through making that open door policy available for workers to again kind of share their concerns and be involved in this process from all the way from procuring that technology to using it to evaluating its on health and safety so in summary Technologies with the within the industry 4.0 should not be developed in isolation and an organization's health and safety management system really should be considered and it is embedded within an organization safety culture which make things even more important when we're keeping the worker at the Forefront the implications from our Center's results do show that the inclusion and use of core hsms elements such as communication leadership and worker engagement could be a missing link to continually ensure that workers are considered while we are selecting and integrating new technologies in the workplace and moving forward we may need to update our health and safety Management systems and practices to be a bit more flexible As We are continuing to update new technologies introducing them into the workplace and we want to make sure that employee well-being is considered during this process as the future of work continues to evolve and I just closed by thanking Emmanuel Kata who is the coordinator and director for the center and with that I will pass it back over to Jessica thank you Emily so much for that insightful discussion of the role of health and safety Management Systems to improve the integration of new and advancing Technologies including Those sensors and wearables into both work and workplaces I would now like to invite Dr Zeke McKinney to the virtual Podium Zeke welcome and thank you for being with us today yeah thank you so much for having me you know uh as I can occupational position we really value uh all you folks out there at niosh and everything everyone's doing occupational health and safety broadly so uh just as a heads up you know I'm gonna go for about 45 or 50 minutes um I'll just warn you guys I go kind of fast and so the hope is that you can get these slides from niosh and review things in more detail if you'd like and so we're going to talk about uh opportunities limitations and consequent disparities in occupational data collection because I think we still have a lot of room to go there so this is kind of an informatics talk but we'll get there oops sorry oh there it is uh so just to talk about some epidemiology of Occupational Health disparities this is a study from Stanberry and Rosemont from 2014 where they looked at all the workers in Michigan which is about 4.2 million
people in 2011. and really just making the point that in black and brown populations you see more essential workers more uh work that's going to be potentially hazardous versus white on to some degree Asian populations that are going to be a more white collar or more high order occupations where they're going to be potentially less hazards similarly we see that distributed this is the same study again across populations where you see you know for example in the Hispanic population more proportions of heavy tractor truck trailer drivers and food servers or in the black population you know more laborers and again more drivers so again just that same distribution of uh jobs and this is stuff you guys already probably know but I'm just kind of laying out the basics of where we're going to get to and so then when you look at rates of injuries and this is the same study yet again they were looking at silicosis fatal injuries pesticides Burns and occupational asthma and you know they saw these rate ratios of like 5.5 Times Higher rates of silicosis in the black population more than a quarter Times Higher in uh for burns 1.9 Times Higher
for asthma and then the Hispanic population fatal injuries one and a half wow that's pretty high and pesticides you know four so I mean those are you know pretty good demonstrations of what I'm talking about in terms of these hazards on different populations and so Sears and folks looked in 2015 and about 90 000 people over a six year period in five states Arizona California Florida New Jersey and New York and again just making the point that you see in your Latino Hispanic population higher rates of all occupational injuries up to about the 2.29 range at the most New Jersey there falls again about almost two times higher in the Latina Hispanic population though weirdly uh less prevalent in the black population we could argue about why that is Machinery hazards up to you know more than five times higher which is really high uh motor vehicle crashes a little bit higher in both the black and brown population and then strangely assaults and homicides and maybe somebody knows why this is but we can talk about that later too up to three times higher in the black population so again pretty significant and to answer Jane Terry on the questions over there yes these will be shared or at least I've given these and I ask them they're welcome to share them with you at their convenience uh stages in 2014 looked at U.S private sector workers about 1.7 million people
where you had 220 non-fatal injuries and illnesses 220 000 that is and 27 000 deaths and again just making the point that gee look uh you know Hispanic black native uh populations are more likely to get injured multiple races a little bit more higher uh High to get injured of course how do we measure multiple races that's what we're gonna talk about later you know having lower education of course portends a greater likelihood of injury being born outside the United States definitely and being born even outside the continental United States uh definitely and no surprise lower wage workers have higher rates of injury again no surprise there and so why does this happen in these different you know essential jobs or jobs with uh you know lower wage jobs greater hazards you know there's precarious work people don't have contracts people are undocumented people are putting together multiple jobs to make one job people may not have health insurance or they may not have be covered under work conference a number of weird reasons uh they may not be able to afford care or co-pay when they go in you know people aren't getting adequate safety trainings whether it's not offered at all not offered in their language not offered at a level of their own uh health or Cultural Literacy maybe they're not giving personal protective equipment and I know that might sound crazy but think about even early in the pandemic Physicians like me couldn't get n95 so you know how bad do you think it is for other people and even if they do have PB it might not fit right and they're not trained to use it and by the way these same issues exist across various underrepresented disenfranchised groups but I'm just being pretty broad about it to make the point that we know there are differences in outcomes and so we saw this with covid again just to make a point here so on the left this uh these are chloropleth repeat Maps as people might call them colloquially on the left we're looking at incidents on the right we're looking at mortality where uh in particular B is black C is Latino Latina he is uh Native and again you saw higher rates of incidents and higher rates of mortality and that was represented across occupations too with races and ethnicities uh distributed in the same way and so interestingly looking at covert in particular and I'm not going to read a lot of quotes but I'm going to read a couple and this is one of the ones I really like as with all diseases for which workplace environment is a root cause the most marginalized workers with the least power and resources for example people are undocumented incarcerated people color women lesbian gay bisexual transgender are queer are the least likely to have access to testing for infectious diseases and the most likely to be missed in cohort numeration wait wait wait wait wait wait wait wait so you're telling me the people who are the most at risk are the ones who we're not you know testing and we're not picking them up when we're trying to look at this stuff too yeah that's scary and it is scary so why does race matter well structural racism is probably a second of two quotes something to read and this is actually really important is the totality of ways in which societies Foster racial discrimination through here's the only takeaway point from this whole conversation if you really want to know what I'm going to talk about is mutually reinforcing systems of housing education employment earnings benefit credit media Healthcare and criminal justice wait a second that sounds like social determinants of Health it is social terms of health and so you know when you look at Social determinants of health and those are defined by healthy people uh I mentioned 2020 on here of course 2030 is coming up soon really it's across those domains of economic stability neighborhood and built environment health and Healthcare education and social Community context you know this web of causation on the right isn't really a specific example other than you look at the outcome of increased maternal and infant mortality in the center there and see that that's impacted by income and education and safety and access to care and that goes all the way back to things like Jim Crow and slavery and redlining which is affecting housing policies but people would argue correctly that racism is its own social determinant of health and that's true and I would say that's probably part of Social and Community context foreign so we see this reflected in life expectancy from birth this is data all the way back from 1970 up to about 2010 where again white females do the best or white women better than black women now black women are just a shade better than white men whereas the worst of all black males hi welcome to my world which kind of sucks because I'm going to die earlier this is how it is and even though life expectancy is improved across all these groups you don't really see that Gap narrowing unfortunately and similarly you know it shows up you know black people in general I'm speaking to the black population this is what I know as a black man uh in general die at higher rates of all causes this was shown again in Jama in 2021 in January where they said you know basically all cause mortality if you're black is like one there has a relative risk of like 1.27 so that's pretty scary but here we are and so we know that in fact it turns out that social determinants actually have a greater impact on people's outcomes than our ability to deliver care this graphs this diagram suggests it's 80 social German it's a 20 clinical care but you know it ranges anywhere from probably 50 to 90 social determinants and the minority is clinical care so that means even if I'm doing the best job I can prescribing the best medications being the best doctor in the world I'm only affecting a minority of people's Health outcomes and everything actually is really more dependent on what's going outside of Clinic including race and ethnicity and including work as a social determinant if you think about it that way so this diagram is just to make the point about Mutual reinforcement of these risks looking at environmental lung disease burden again is affected at the individual level or in the intrinsic level by your genetics and your age and stress but outside of you it could be physical activity and sleep and you know your insurance and your occupation smart uh but also you know what's going on in the community what what's the availability of food what's your Access to Health Care what's your built environment like what's you know culturally happening or even globally you know what's going on uh with the employment rate or with the economy or racial bias or law enforcement which intersects with racial bias quite a bit as we know anyway the point being these things don't exist on Islands so you know being black is a risk being poor is a risk being poor and black is more of a risk and so we see mistrust uh when we're trying to engage people in occupational health and safety because of all these peripheral traumas you know historically in communities of color there are things like the Tuskegee syphilis study if you don't know about you to read about it or you know Marion Sims who's considered the father of modern OB GYN because he experimented on slaves and developed really cool new surgical techniques you know we've seen infectious disease stigmatization with AIDS way back uh in well not even that way back but back in the AIDS epidemic in the 80s and 90s and now with covid-19 you know people call it the China virus or even more now with monkey pox uh and you know men who have sex with men being considered you know stigmatized for this disease in clinical settings we know patients aren't believed they're called drug seeking they're called malingering people talk about quote difficult patients we shouldn't use that language and then socially like I said things about like law enforcement violence redlining which is what you see in the white box here not allowing people of certain races or ethnicities to buy houses in certain areas cultural appropriation that's why I showed the Redskins logo thankfully that's gone now or even know people being stigmatized for being undocumented Etc and those are all very real things and so in Occupational Health we see this manifest as like you know employers actually denying risk when you know people get injured or people talking about OG Zeke or other Ahmed docs you're a company doctor you know I'm working on the company's behalf or gee well you guys didn't train me on safety stuff or you didn't give me PPE or no you know this guy's just faking it and gaming the system and he doesn't want to actually work or people you know being classified as contractors so you know we don't have to cover them in terms of injuries or we know that people are discriminated against and get you know more harassment and more bullying because of race ethnicity identify gender and things like that and then individually people you know have these issues of language and culture that may be a barrier for them I don't know who's moving the mouse around on my slides but please stop doing that anyway and then also a fear of reprisal and blame and job loss uh you know that happens because people like well I don't want to report this under because I'm gonna get blamed for it and then there's this concept of John henryism you know oh well I already know people think black people are lazy so I better work work that much harder and I don't I'll just take the hardest jobs there are and you know that way nobody's going to think I'm trying to shirk out of anything and based on all this are we really surprised that people are scared to report injuries uh and the answer is I'm not surprised so we know that systemic racism impacts mental health which again also is going to impact physical health and it's just going to manifest a number of ways about how people engage care how people are seeking help how people are interacting with doctors or health and safety professionals Etc and so the stigma and shame that exists in so many other ways also very much exists around behavioral health conditions and we know as in terms of workplace discrimination this has a huge impact on mental health and people you know more psychological stress more anxiety and depression more negative emotions and really experience of more emotional trauma in general you know anybody who's black or brown has experienced a lot of these microaggressions in the workplace there's a lot less overt racism hey we don't like you n-word but rather hey maybe you're not going to get a promotion or you're not going to get a job and wait a second did that happen because I did a bad job or because I'm a bad guy or just because people don't like how I look you never know and that's where this anxiety comes from so in reality we actually see this manifest in uh greater structural issues associated with racism like work-related disability and so this paper is like one of my favorite interesting papers and so they were looking at on the left here graphs of uh predicted lung function and the top is for black people bottom is for white people and what they were saying is based on Corrections for race and lung function by spirometry if you know we got rid of those race Corrections you'd actually see black people get more expected dotted line here work related disability for lung function because of Occupational lung disease versus right now where they're actually not getting as much as they should because they're presumed to have better lung function than maybe they do based on race correction uh interestingly this paper said and I don't know this is true but this is what they reported I haven't gone back all the way to the private Village on this that apparently black people have better hearing at Baseline than white people and so we actually have the opposite effect where you have more white people getting work related disability around noise-induced hearing loss or example than black people because of Correction and they're they were arguing this paper that we should actually have race correction for hearing go in the other direction I don't know if that's true or false but it's interesting there we go so we've seen evidences mistrust reported in lots of study here here's one that looks at concordance between people reporting injuries and whether or not their job reports the same occupational injury and uh so you know the top most light and the bottom most dark bars are you know so the bottom dark bars nobody report they didn't report it and the job didn't report it at the top is both the job and the personal report of it and in between is either the person themselves in the job didn't or the job did and the person didn't and again you see these greater discrepancies in the Hispanic and the non-hispanic black populations again no surprise and this was statistically significant but kind of demonstrating that point that there is going to be some discordance there because people are afraid and rightfully so so I'm going to flip it over to thinking about informatics now this is like one of my all-time favorite informatics slides the dikw framework data information knowledge wisdom uh and just showing you that in these domains of data where you're collecting information or information where you're organizing and interpreting that data and proceeding onto knowledge where you then integrate that and understand that and proceeding onto wisdom where you can actually apply that in real settings and importantly the clinical care applying with compassion so you know informatics isn't just computers and robots but you know as we go along these domains you get increasing degrees of complexity and increasing degrees of inner relationships between this information now I'm going to make this more uh relevant than this abstract thing so why does it matter well anytime you're implementing processes or for example Occupational Health Systems you have to think about how you're hitting each of these layers and so again you might just need to start with collecting data if we don't even have the Baseline data to get where we're going and that's kind of the point I'm trying to make and will make throughout the course of this talk because without the data we can't even proceed to to getting information and getting knowledge and actually making changes based on the wisdom of what we are seeing happening in the world and so in Occupational Health we have a lot of different data sources we have employer Collective health information we have clinical and research-based data in Health Systems we have personal health data that people are collecting via fitbits and things like that you have population Health Data being collected by you know Public Health Systems and then you have health plan data collected by insurers and all of those are different and all of those are relatively segregate and so the question is how do we use those together in a happy way to actually do good Occupational Health surveillance well that's what I'm going to try to talk about and so we see uh basically you know there are these various clinical data sources but we also have various payers of healthcare services and so who quote owns the data or can access it actually is quite different this is also bolstered by legal limitations whether it's HIPAA or Gina or even workers compensation law that precludes people sharing data in a variety of different ways and so the problem is people get care in multiple different Health Care Systems that may or may not be able to share data between each other it's getting better over time but it's still not great and certainly not perfect but similarly even if people are staying in the same Health Care System they might be getting care paid by multiple sources their personal insurance there were cop insurance or their employer you know paying for them getting a pre-employment exam done and so often you know at a high level people talk about clinical versus claims data where claims data is very rich and detailed but it's only limited to what you can get within that Health System whereas claims data tends to be quite broad but again you're not going to get as much of those details but it'll span across all the health systems because one payer is paying for everything at least in that context and so the problem is then you can look at stuff like electronic health records which by the way were not designed for clinical care historically but we're really designed for billing or Pharmacy or practice management like scheduling purposes and some of these have variable degrees of customization which is balanced with how much administrative Management's put on there and these have really complicated workflows because a lot of information traveling around medicine and a lot of weird data storage and places to access things because there's lots of different Specialties and everybody wants things done their own way a gas or denial enterologist needs it one way but me as occupational medicine doctor needs in another way and even though we have this stuff stored digitally like I said not all these systems can share with each other um the EHR with the biggest market share epic can sometimes share other systems data but not generally and they don't have an impetus to to do it because it doesn't help their business and by the way none of these systems or very few of them collect occupational uh Health Data very well and specifically non-occupational ehrs where they were talking about epic or something else don't really collect detailed employer data so we're going to go into that now Public Health Data sources on the other hand may do some of this better but they're usually identified and there are certainly even more legal limitations in some ways around those especially here in the state where I'm in Minnesota we have huge data limitations in law about what public health data can be shared or rather what can be shared with a public health entity and so often you have very specific narrow purposes like you know immunization information surveillance systems we have a really good one in Minnesota or mortality data and things like that and so then you have employer-based health system Health Data Systems which you know often are maintained within the employer or sometimes actually at a clinic like mine but it's separate from your employee record so this is not an HR record uh It ultimately it's limited degrees of somebody's had a full medical history but it's going to be specific stuff whereas insurer-based data sources are going to be claimed data and again it will span across Healthcare systems but it's really only the data paid by that insurer so it may not have other visits they had if they just change Insurance last year for example and this is always privately held so they may or may not care that somebody like me some research or whatever locally clinician on the street wants to see that stuff I wish and then you have personal health data which again this is really uncontrolled you know people have their Fitbit on or their heart rate monitors or their active grass and sleep monitors or whatever and this stuff is stored in the cloud and again people are collecting this data for money mostly uh and sometimes you can aggregate personal health records but people aren't really using those uh and sometimes you can integrate with clinical data systems but that hasn't happened a lot yet so we're going to get there so here's some examples all right so somebody gets a shoulder injury right there's a new work related shoulder injury and they're getting care within a large Health System let's say where I work whatever and other clinicians in my health system can see that I saw this person or somebody saw this person was getting treated and you know the word cop insurer can see it too well does this matter well maybe uh the problem is you know depending on who's trying to access this they may not be able to see other parts of this person's medical history like let's say it was getting they were getting care somewhere else or you know more specifically clinicians may not have access to the person's job description that's really common or industrial hygiene data that's even more common I wish but you know sometimes I just don't have that stuff and so how can I tell that for example maybe six seven twenty different people at that job are all getting shoulder underaries well without an integrated Occupational Health Data System I probably can't and so this is just to make that point that like there are limitations on data so that such that even if there were patterns in what was happening to people it may not be obvious to us or there may be very few people who have ability to look at that so somebody comes in for a pre-employment exam this is an employee going to work at a delivery company they say yep I don't have any medical history and I don't you know we don't have any access to their medical records or they don't want us to access it and so I say yeah this guy looks fine and I totally claim for Duty well then the person comes back whatever four months later and they have a new uh low back injury and then they're treated at the same Clinic they did the Supreme Court examine maybe they're even seeing me again and it's kind of found out through talking to the person and getting their history like wait a second you had all this low back injury stuff in the past and surgery and a bunch of stuff and so fine well now I'm treating this person for an acute exacerbation of that injury but the company ultimately fires that person because they misrepresented their medical history on a pre-employment exam and again how could we do a better job of seeing this stuff in advance to avoid the worker getting actually injured because they got into a job that maybe they weren't prepared to have and now this employer sort of bought that injury on work cop even though the whole intent was for them not to do that in the first place and not that I'm necessarily trying to protect employers interests I mean sometimes I am but really the point is these things need to line up okay so now let's here's another one somebody comes in for a chemical exposure this is stuff I really do all the time princesses yep otherwise I'm healthy and hey by the way you know like several other people at my job are having the same symptoms and you know I don't have anything to do with wherever these people are getting their medical surveillance For Occupational Health so it's not available to me and the employer is not giving me industrial hygiene data because they're just ignoring my emails to them and so these employees with a similar exposure in reality may be seen in different places uh Minnesota where compets uh choose your own state which I like but it is what it is so people can go wherever they want and the employer doesn't have any requirement to provide me any any industrial hygiene data I wish and clinicians outside of Occupational Medicine may or may not even know to ask about stuff like that and non-occupational clinicians also don't know anything about the job or the exposures and so the employee even if they go get seen about this illness they might not even know to tell somebody like this might be related to my job and that happens all the time and so even though we can maybe look at diseases in clinical systems like I want to look at all the people who have contact dermatitis and that's maybe a very specific one let me assure you these can be much more nebulous than that but what about trying to look at exposures how do I search for everybody who has exposure to toluene and that doesn't exist I I wish again I wish a lot of things in this talk so we also see data gaps and demographics whether you're talking about occupational health or just regular old health care and so historically this has gotten a little bit better race and ethnicity was one choice you could pick white black Asian native other multiple nowadays you can actually pick more than one but even a few years ago you couldn't and ethnicity was divided into Hispanic and non-hispanic but you know race is a social construct so what about nationality and so when it comes to nationality a lot of things ask about country of origin maybe a better question would be country of birth because country origin especially here in Minnesota gets really wonky we have the greatest here in Minneapolis we have the largest Somali population outside of Mogadishu so you can have some guys from Somalia originally moves here becomes U.S citizen and he comes to the clinic you say well where are you from and he's I'm from here you know I'm from here in Minneapolis you're like no no but where are you from you know people ask me that all the time because I'm Brown and nobody can tell that I'm black and whatever but anyway and the question you're really trying to ask somebody is like what's your ethnicity or what is your birth country or whatever and both of those are different social determinants so we should ask them but the question is we have to ask these things in a clear way and by the way documentation status like whether somebody's undocumented or not certainly isn't really in the EHR and I wish it was now gender is a big deal and again we're not doing a great job I think in healthcare overall collecting you know identify gender a lot of times for medical care biological sex May really matter but there's plenty of times I identify gender matters too and so being able to parse out these different data elements are really really important to us doing good Occupational Health surveillance or good clinical care in general and so here's a practical example of this so this was actually a study done in our Residency program a few years ago where basically somebody looked at two years of our occupational injuries and looked across race and ethnicity to see were there higher rates of injury and turned out that the our Hispanic population had three times higher rates of low back injury and about two times higher rates of upper extremity injury now the problem was this we didn't know industry and occupation we were collecting you know employer name and job title but those don't certainly don't map well to actual industry and occupation and what does Hispanic really mean are we talking about somebody who's from Mexico somebody from Spain somebody from South America somebody's Spanish-speaking some we don't I don't know what that means and so the problem was this is pretty limited and so given that it's so limited then how do we really take this finding and do something useful with it we saw these same data gaps for collecting race and ethnicity exist in other studies you know the top the one on the left is from the VA in 2009 the one of the rights from 2015. uh and these build relatively small sample sizes in the hundreds but again just showing that there's a discordance between if you ask a person themselves what is your racial ethnicity and look what's actually in the electronic health record they may not be the same they'd say wait a second how is that possible well think about it patients or employees aren't aren't entering this data into the health record so it's being put in by someone that someone may look at somebody who walks and says oh this guy looks whiter this guy looks black and so they just put it in without asking the person even though the person may identify something completely different so there's like a lot of gaps like that that might exist and again the point is we tend to see that this type of data has high specificity but not always a great sensitivity and I'll show you even a worse example of this so we just published something in the American Journal of industrial medicine earlier this year this is about n of 800 so bigger than those other two studies and again showed really high specificity in really low sensitivity for using the self-reported form as a gold standard compared to what's in the electronic health record system now you'd say wait a second what is sensitivity and specificity mean in this context what that means is if the electronic health record says you're black you probably are black if it doesn't say you're black I don't know maybe so anyway moving on but the point is uh it's not really perfectly concordant uh oh I had to slide in there twice my bad so one other issue we have in terms of data gaps is that work relatedness is not always discreetly identified so in our Clinic we try to use this ICD-10 code y99.0 which essentially means work related entry so that one day maybe if we go back and try to capture all these we can do a good job about it but how else do you identify it well some people say well you could look by the payer was it a work comp insurer okay that's one way to do it but the problem is we're comptonize a lot of stuff and so that's not going to always work uh and so it gets hard to know and you say well what if we just look at a reducing and occasional medicine again High specificity low sensitivity a majority of workers compensation care is provided outside of Occupational Medicine because docs like near rare and nobody knows we exist but that's another issue and so like I said when you know we're taking employer name and job title as part of somebody's you know history how well is that actually correspond to True industry and occupation or if you want to code them under for example nakes and sock could you when the answer is not easily or not always and then we still don't even know what happened with the injury again necessarily into discrete fashion usually people do a good job already things down a free text but you know using ICD-10 our coding system is pretty limited for mechanism and an atom uh sometimes it's good for anatomy not great for mechanisms sometimes you have it I actually like bls's system awakes which does this a lot more systematically and so I'm going to show you what that looks like uh to propose maybe we do a better job of the future capturing data like that so let's think about like occupational asthma from an epidemiological perspective so in a perfect world the work Carpenter uh has you know gets claims of Occupational asthma and the medical record is from different clinicians are all available and by the way we have all the IH and safety data and so we can look at who has asthma how bad is it and what's possibly causing it in what context great yeah well in the worst case and this is probably closer to reality a person gets asthma-like symptoms they don't know whether it may or may not be related to the workplace they might not even think of that they uh may be seen by their primary care clinician or an urgent care or an ER and nobody thinks about the work is associated with it and even if they are seen by an occupational physician like myself I may not have that industrial hygiene data or no information about their job or about all the other people who may have been injured [Music] so how do we find these things well we have ehrs in the United States and they're pretty much ubiquitous at this point and they're somewhat searchable though it's limited a little bit but again this terminology issue is a big one because clinicians use a lot of the different words to describe the same exact thing some Specialties are I would say worse about that than others are different about it uh you know if you talk to a regular on the street clinician like me you know Radiologists use like a completely different language when they describe their reports and that's partially why they're they paid the big bucks but the point is it's sometimes hard to know that oh chondrial Malaysia they
2022-09-30 16:52
