Rishi Manchanda: [00:03] Hi everybody. I'm Dr Rishi Manchanda. I'm CEO at Health Begins. Welcome to this module titled, CPT Evaluation and Management Guidelines, Implications for Patient Social Risk Data and Health Equity. This is an introductory module from Health Begins, the Gravity Project and the American Medical Association. I am pleased beyond belief to be joined today by Dr Sarah DeSilvey, Director of Terminology at the Gravity Project and pediatric faculty at Larner College of Medicine at the University of Vermont. Hi Sarah and welcome.
Sarah DeSilvey: Hi Rishi.
Manchanda: Together, Sarah and I are going to be, going through quite a bit of content. In the first half of this introductory training module, we'll provide an overview of the 2021 E/M office or other outpatient services coding guidelines and review how these guidelines can help practices represent time and or complexity of medical decision making associated with social risk. In the second half of the module, we'll then review opportunities to document social risk data and also review associated benefits and risks of documentation of social risk. And we'll also outline ways in which clinicians and care teams can use this social risk data to adjust and improve the quality of care and support population, health management and community level approaches to address the social drivers of health equity. Before we begin, a reminder that this module is eligible for continuing education, continuing medical education credits. Please be sure to review the information on this webpage to learn more.
I'll recap some of our learning objectives for today. We hope that by the end of this module you'll be able to better first understand the 2021 E/M office or other outpatient services coding guidelines. Second, demonstrate how these guidelines can help practices represent increased time or complexity of medical decision making that may be associated with social risk. Third, we hope that you'll be able to describe opportunities for social risk data documentation and associated benefits and risks. And lastly, we want you to be able to list ways in which clinicians and care teams can use social risk data to improve quality of care and support population and community level approaches to advance health equity. To help learners understand the new coding guidelines and their implications for social risk and equity. Sarah and I thought we'd start by sharing a case scenario. This is Clinic X.
Clinic X is an outpatient primary care clinic serving a racially, ethnically, and economically diverse population. Their payer mix includes commercial insurance plans, Medicare and Medicaid. The vast majority of their revenue comes through fee service arrangements. During the pandemic, like many of you, clinicians at this clinic saw an increase in the number of patients, including patients with poorly controlled disease who reported having a hard time making ends meet some of their patients reported food insecurity, feeling uncertain or being unable to acquire enough healthy food to meet the needs of their families. Clinicians noted that patients unmet social needs impacted often impacted that the amount of time that they would spend with patients and also impacted the complexity of their medical decision making. In this clinic, clinicians as well as clinic managers are wondering how they can reflect this time and this complexity of medical decision making using the new E/M coding guidelines and as they see payers focus more on closing care gaps and focusing increasingly on identifying and eliminating health inequities, clinicians in this clinic are wondering how collecting and documenting social risk data might also fit within their overall health equity efforts.
Manchanda: [03:55] So to help our colleagues at Clinic X this clinic, in our case scenario, let's review some of the key questions that they're trying to navigate. First, what are the new office or other outpatient services, E/M coding guidelines? Second, how can these guidelines help us better capture the time or complexity of medical decision making associated with social risk? Third, what opportunities do we have to document the social factors that impact our patients? And what are the potential benefits and risks associated with documenting social risk? And then lastly, how can clinicians and care teams use social risk data to improve quality of care and support population and community approaches to advance health equity? So Sarah, as we reflect on this scenario, let's review this first set of key questions facing outpatient clinicians and administrators. What are the 2021 E/M office or other outpatient services coding guidelines and what do they mean for clinicians caring for patients with social risk?
DeSilvey: [05:02] The new office or other outpatient services guidelines went into effect in January 1st, 2021. They reflect the most significant change in E/M coding undertaken since 1997. The goals of the new office or other outpatient services, E/M coding guidelines are to decrease documentation burden and note bloat, make co level selection more intuitive, to decrease the need for audits through addition and expansion of key definitions. A key takeaway is that code level should be based on clinician work and managing the patient problem or problems with a focus on decision making, not just simply volume of test and treatments. One changes that the build level of service be based either on total time spent or the complexity of the clinician's medical decision making, otherwise known as MDM during the office visit. Medical decision making includes establishing diagnoses, assessing the status of a patient's condition or conditions and/or selecting management options.
[06:10] More specifically, MDM is defined by three elements, and these are really important. So we're going to take them one by one. The number and complexity of the problem or problems addressed the amount and or complexity of the data to be reviewed and analyzed. For example, medical records test or use of independent historian and the risk of complications and or morbidity or mortality of patient management decisions at the visit associated with the patient problems, diagnostic procedures or treatments. The changes in medical decision making criteria lead to a far more subtle but potentially more important change in the updated guidelines for the very first time assessment of the complexity of medical decision making can explicitly take a patient socioeconomic risk into account.
So the next step is why is this important? Before these updates to the E/M coding guidelines, the build level of service for a patient living in poverty, with diabetes, for instance, typically could not reflect the complexity or time of adjusting insulin doses based on access, accessibility of food, availability of transportation, or the patient's medication costs. So while all of us, all clinicians working with patients in poverty or facing other socioeconomic barriers sometimes make adjustments based on social conditions, these adjustments generally were not able to be reflected in the CPT coding of the visit. For example, a randomized study in 2019 revealed the level of service assessments did not vary regardless of whether documented visits reflected patients socioeconomic barriers. The new guidelines create an opportunity for clinicians and practices to reflect the additional complexity of and risk of assessing and addressing social risks as part of either medical decision making or increased time in the CPT coding of the visit. This matters because many clinicians are already doing the work to take their patient's social risk factors into account. When delivering care and making treatment plans, the updated guidelines explicitly allow for this effort to be taken into account.
Manchanda: [08:26] Sarah, thank you so much for reviewing those, um, updated E/M office or other outpatient services coding guidelines and also why they're so important for clinicians caring for patients with social risk. This leads to another question. How should clinicians go about representing the time and or complexity of medical decision making associated with caring for patients with social risk?
DeSilvey: [08:50] That's a great question. Under the updated E/M office or other services coding guidelines, there are two ways to represent the time and or complexity of medical decision making associated with caring for patients with social risk. Documenting by time or documenting by medical decision making. Let's recap how this works. Documenting by time under the updated coding guidelines, a clinician can always document based on the time it took to integrate social risks into the plan of care. For example, let's think of our case scenario. Imagine a patient shows up for return office visit to follow up on poorly controlled diabetes. The clinician reviews the patient's social risks, including food insecurity. Taking this social risk into account, the clinician takes time to change the form of insulin for cost reasons. Counsels the patient on the new medication and personally educates the patient about local food resources.
She's effectively coordinating a diabetes plan of care that's sensitive to her patients identified food insecurity. The time it takes for these efforts can all be included in the way that it is coded under the new updated E/M Coding guidelines. When documenting by time, one important thing is it is important to keep in consideration, especially in team-based cares. Important to note that the 2021 E/M coding guidelines do not permit clinicians to count the time of other staff like financial assistance counselor or community health workers who may have been involved in addressing the patient's social risks during their visit to your practice. The other option available to the clinician and practice is documenting by medical decision making. Social risk information can be useful to determining management risk, one of the elements of MDM. As I mentioned earlier, when determining the level of complexity of MDM, clinicians and coders can consider problems the number and complexity of problems and addressed in the encounter, data, the amount and or complexity of data reviewed and analyzed and management risk, risk of complications or morbidity, mortality of patient management.
Understanding and documenting social risk data can be important here. The question is, is the diagnosis or treatment complicated by identified social risk as in our patient story. To demonstrate how to represent the complexity of MDM with social risk. Let's again consider the scenario a patient shows up for return office visit to follow up un poorly controlled diabetes, the clinician reviews the patient's social risk, including food insecurity, and significantly address their treatment plan taking them into account. First, it's always important to remember that discussing social risk with patients is the first step to helping address, let alone documenting it. Second, the clinician in this case may decide that the patient's social risk complicated their diagnosis or treatment and increased their management risks.
[11:51] Third, we always have to remember that management risk is just one component of MDM. And remember that in order to select a level of E/M service, two of the three elements of MDM must be met or exceeded. As a reminder, the core elements of medical decision making are all detailed on the AMA elements of medical decision making table demonstrated here. So going back to our example, the clinician may decide that the patient's social risk complicates diagnosis or treatment and increase their management risk, even if the impact of a patient's social risk factors on the care provided contributed to a moderate level of management risk. By prompting a medication adjustment for instance, it does not ensure that the visit may be coded as a moderate MDM. It has to require two of those three elements. Number and complexity of problems addressed data and risk of management to meet a moderate level E/M service. So other information about the number and complexity of problems addressed during the visit and the amount of complexity of data reviewed and analyzed during the visit would have to be considered before determining the appropriate CPT code.
Manchanda: [13:05] Thanks so much, Sarah. At this point in the conversation we've reviewed, Sarah has really done a wonderful job reviewing the updated E/M office or other outpatient services coding guidelines. And Sarah, also you discussed how these guidelines can help practices represent the time and or complexity of medical decision making associated with caring for patients with social risk. Let's now transition at this halfway mark to the latter half of this module, and let's talk more now about social risk data. When we think about social risk data, one key set of questions is what opportunities do clinicians have to document the social risk factors that impact their patients? So let's go back to our patient in the scenario that we shared earlier. During a visit in the clinic, a medical assistant may screen the patient for social risk factors using a standardized screening tool like the PRAPARE tool or the accountable health communities screening tool. Among other social risk factors that she may be experiencing, the patient decides to disclose and prioritize food insecurity as a social need during this screening process. During the visit, her clinician discusses food insecurity with her patient and assesses that it's negatively impacting her ability to manage her diabetes, which is not well controlled. She then decides to adjust her patient's insulin dosing to minimize health risks associated with food insecurity and asks her care manager colleague to refer the patient to a local nonprofit that provides food or nutrition support. So Sarah, with this patient scenario in mind, what are some opportunities for clinicians to better document social risk data?
DeSilvey: [14:48] Thanks, Rishi I want to review the two main opportunities the clinicians can use to document social risk data. The first is using text. [pause] Clinicians can simply describe a patient's social needs in their visit. Note, when the patient's electronic health record chart, for example, the clinician, in this scenario can write food insecurity or not enough food at the end of the month, they can also document the impact of the social need on their health or treatment. For example, increased risk of hypoglycemia due to identified food insecurity. And finally, they can describe their plan or actions based on the social risk data. For example, adjust insulin due to lower risk of hypoglycemia aided by natural language processing software clinicians, clinical informaticists researchers and coders have opportunities to help document this social risk data that exist in the unstructured clinical text. There's a key takeaway to remember here to be coded for MDM.
DeSilvey: [15:54] Under the updated E/M coding guidelines, clinicians must describe how it affected the risk of treatment. For instance, just writing food insecurity is not enough. Clinically it may suffice but not for the MDM level. Another opportunity clinicians and practices have to document social risk social risk data is using terminology, and this is my favorite. When documenting social risk Clinicians and practices should move beyond using free text and add the appropriate supplemental SNOMEDCT problem list and ICD-10-CM codes that identify patients social needs. Utilizing these codes will allow providers and payers to collect data and identify solutions to address patient needs.
[16:41] Z-codes ranging from Z-55 to Z-65 are the ICD-10-CM encounter reason codes you to just use to document social risk data factors such as housing instability, food insecurity, and transportation. There are also SNOMED CT codes, which represent coded terms may be used within electronic health records, which to capture record and share clinical data for use in health careorganizations and provision of related services. Improving social risk documentation through the use of ICD-10-CM Z-codes, for example, can be used to support the choice of the appropriate level of time or complexity of MDM associated with this patient visit under the 2021 E/M office or other outpatient services coding guidelines when a patient's social risk has added to the complexity of medical decision making or to the total time of the encounter.
[17:37] Let's review some important facts about Z codes. According to the 2022 IC-10-CM official guidelines for coding and reporting Z-codes, social risk should be assigned when this information's documented in the medical record. Since this information represents social information rather than medical diagnoses, coding professionals can utilize documentation of social information from social workers, community health workers, case managers, or nurses if their documentations is included in the official medical record. Patient's self-reported documentation may also be used to assign codes for social needs as long as the patient's self-reported information is signed off by and incorporated into the medical record by either a clinician or provider.
[18:28] Z-codes describing social risk should be assigned when this information is documented in the medical record. Remember, any clinician or care team member can document a patient's social need during any encounter. This includes clinicians, social workers, community health workers, case managers, and patient navigators. This data can be collected at intake through health risk assessments, screening tools, patient clinician interaction, and individual self-reporting. It's worth noting that while any team member can document a social need, only those items that are addressed during the encounter by the reporting clinician are eligible for consideration of assigning the appropriate CPT code. If a social need is documented but not addressed during that encounter, it cannot be considered in assigning the appropriate CPT.
[19:20] Many clinicians and hospitals still don't routinely use Z-codes to code social needs. This means there's a lot of opportunity to improve the way we document and address the social risks that impact the health of patients and that drive health inequities. To improve your practices capacity to use text and terminology to better document social risk data. There's a lot of really great resources. CMS produced a helpful infographic describing steps to improve use of Z codes. Clinicians and practice administrators can also leverage the updated E/M office or other outpatient services coding guidelines as an opportunity to meet with coders and clinical informatics to review opportunities to improve social risk documentation. For clinics that use PRAPARE screening tool, use the PRAPARE toolkit to help improve documentation of social risk data. The PRAPARE data documentation crosswalk concludes coding specifications and instructions for all PRAPARE measures and maps PRAPARE data to existing codes such as ICD-10, LOINC, and SNOMED codes. It also includes recommendations for ways to document social intervention responses based on identified social needs.
Manchanda: [20:32] So Sarah, you've really outlined and discussed opportunities to improve documentation of social risk data. Uh, it it's been so helpful to kind of review all that with you. I wonder if we can step back and consider why does this matter? Why, what are the potential benefits and also the potential risks associated with documenting social risk data.
DeSilvey: [20:53] I'm going to start by reviewing some potential benefits of collecting and documenting social risk data, the first addressing the injustice of data and invisibility. As we've seen through the COVID-19 pandemic, real harms and injustices can result when data for certain populations or regions doesn't exist. For example, the lack of granularity of racial, ethnic and linguistic data meant that Indigenous, Black, Latinx and other people who've disproportionately suffered from COVID-19 were effectively invisible in the data. The second is to support clinicians and care teams to better adjust care plans and improve quality of care. For example, at Clinic X, documenting social risk data might help clinicians and care managers proactively flag patients whose insulin doses might need to be adjusted based on the problems of accessing healthy food. The next is to help clinicians, payers, and researchers better identify patterns of health inequities, including racial health inequities that are exacerbated by the unjust and unequal distribution of social risk across groups of people.
[22:06] We can also use data to inform population health management approaches to address social drivers of health inequities. For example, more clinics or not only screening for social risk factors like food insecurity. They're also using software and technology platforms to refer at risk patients to social resources in order to address their social needs and importantly improve outcomes. This is known as social prescribing. Another facet is to prepare for and improve capacity to perform in value-based payment models that ask for social risk data and encourage health and social care integration. As more payers move to value-based payment models, more clinics that have traditionally relied on fee-for-service payments are trying to adjust and build their capacity to deliver care.
[22:57] The last one is helping clinicians, administrators, payers, and local policy makers strengthen and target resources available for patients of populations. For example, more accurate documentation of social risk factors like food insecurity might spur Clinic X to work with a Medicaid managed care plan and local self-insured employers to help fund local anti-hunger community-based nonprofits. These potential benefits are encouraging and it's part of the reason more health systems are screening for and documenting social risks. But it's also why it's important to consider and try to mitigate the risks of documenting and collecting social risk data as well. Here are a couple potential risks.
[23:43] The first importantly is risk of stigma, discrimination, and harm. When sensitive data is visible, we're careful to recognize from a point of data justice and medical ethics that although social risk data can address gaps in care, it can also place a person at risk of bias. For example, documenting sensitive data, including data and social risk, may expose patients to negative implicit bias or discrimination by providers. In addition, if adequate equity centered policy safeguards and protections are not in place sensitive social risk data may be used in ways that harm groups of patients and clients. This is not unique to social risk data. Think about the way weaponized against BIPOC communities for decades to reinforce oppressive systems that result in divestment and often inappropriate and harmful policies. Or think of gender identity, sexual orientation, or even pregnancy status and the ways some policy makers have or plan to have a plan to discriminate against patients based on these identifying characteristics.
[24:50] This is why it's not just about screening for and documenting social risk data, it's also about countering oppressive data practices that make it easier to weaponize this data. Another key risk is risk for uninsured and underinsured patients. Increasing the complexity of a visit for social risk and fee for service settings means an uninsured or underinsured individual may be liable for increased cost of care. By definition, visits that are coded at a higher level have the potential to be billed at a higher cost. These costs may be passed on to uninsured or underinsured patients, which can exacerbate economic inequity. It can also increase the copay for the insured patient. Patients with high deductible health plans, for example, may be liable for that higher cost.
Manchanda: [25:44] So Sarah, as you've said, it's so important to understand these potential benefits and risks and it leads to this next question. How do we maximize the benefits and decrease the risks from an equity lens? To start, we can ensure we're asking about and collecting social risk appropriately and effectively. So first, for example, we can build staff comfort and skill when it comes to social risk data using empathic inquiry and other methods. Empathic inquiry was created by combining motivational interviewing and trauma informed care approaches along with inputs from patients and other stakeholders. The Oregon Primary Care Association, for example, has used this approach to facilitate collaboration and provide emotional support for both patients and health center staff through the social needs screening process. And it also has been used to evoke patient priorities relating to social determinants of health and social needs for integration into subsequent care planning and delivery.
[26:43] Another way to be able to help build comfort and maximize the benefits and minimize the risks of social risk data collection is to help ensure your practice is asking about documenting and using social risk data appropriately and effectively by engaging patients and community members, including those who self-identify with and belong to historically marginalized communities. As your practice considers engaging patients and community members for this purpose, you can gather your colleagues together to ask and answer a couple of key questions together. First, how is your practice involving patients and other members who belong to historically marginalized communities in your own existing health equity efforts? Second, what patterns of inequity do patients and community members perceive when it comes to health careaccess, quality, or outcomes? Next, what are the social and structural drivers that patients and community members identify as the potential root causes for these inequities? Next, what are their recommendations for ensuring that staff in your own practice are more appropriately asking for and documenting patient's social risk? And last but not least, how is your practice compensating patients and community members for their insights and their contributions to this work?
Manchanda: [28:08] This brings us to the last set of questions for this module today um, for clinicians and practices to consider. What are some ways clinicians and care teams can use social risk data to improve quality of care and support population health management and broader community level approaches to advancing health equity? As we've discussed, improving social risk documentation through the use of ICD-10-CM Z-codes, for example, can be used to support the choice of the appropriate level of time or complexity of medical decision making associated with a patient visit under these new outpatient services coding guidelines when social risk has been added to the complexity of MDM or to the total time of the encounter. But improving documentation of social risk data can also help clinicians and practices in other ways. Sarah has touched on some of these potential benefits. Let's recap them. First, social risk documentation can help increase your capacity to participate in value-based payment or alternative payment models that prioritize health equity.
[29:09] As you consider this ask, are there commercial and health insurance plans, Medicare advantage plans or Medicaid managed care plans that have approached your practice about value-based payment or alternative payment models? Do they provide incentives for collecting, documenting, and acting on social risk data? For example, considering our scenario with Clinic X, let's imagine that they recently started an APM contract alternative payment model contract with a managed care plan to help care for defined set of complex patients. If that clinic meets specific quality of care benchmarks including social risk screening and referral benchmarks, it can under this new contract receive savings from the managed care plan. Administrators realize that documenting social risk using Z codes and demonstrating their capacity to improve the quality of health and social care based on this social risk information will be key to meeting these quality benchmarks. The clinic also goes so far as to ask for and receive upfront payments from the payer from the plan and also, uh, uses projected revenue from shared savings to invest in expanding and sustaining partnerships with community nonprofits, which can provide housing, food, and other social care services for their patients.
[30:27] This revenue also can help offset the costs of more complex care management and costs associated with integrating health and social care for other patients, including asthmatic children, for example, or food insecure diabetic adults like the patient in our story. Another important opportunity and benefit here is to document social risk in order to help clinicians and practices improve their capacity to analyze patient data, including social risk data in order to help identify inequities in healthcare. For example, let's imagine clinicians in our scenario are at Clinic X are concerned about the impact of housing conditions on the health of their asthmatic patients. Working with a local public health department and place-based health collaboratives in their community, the clinic identifies four zip codes with the highest rates of asthma diagnosis and associated utilization of the emergency department among children and teens. With support for partners like a local academic institution. Clinic X identifies inequities in health status, no show rates, and also emergency department utilization between Black and Latinx children with asthma compared to white counterparts who live in the same ZIP codes.
Manchanda: [31:36] Together, the practice administrators, clinicians and the coders agreed that in order to help support better analysis, better insights into these inequities, they agreed to improve documentation of housing instability and substandard housing conditions, especially for those for asthmatic patients who live in these communities in order to support clinic community efforts to close racial inequities and asthma outcomes. Third, documenting social risk data can also help clinicians and health systems partner with others and support efforts to not just analyze, but to address health inequities, including the social and structural drivers of health inequities impacting their own patients and their communities. For example, practice administrators and clinicians, um, who are improving the documentation of, um, housing and stability and substandard housing conditions can then use this along with equity focused data use agreements and health information exchange to securely share, de-identified and disaggregated patient data, including social risk data and housing stability with a public health agency.
[32:40] The public health department might then be able to better identify the housing problems that Clinic X has helped document and see that they're associated with racial inequities in asthma outcomes among local residents. Based on this data, this analysis, these insights, Clinic X helps to enable the local health department as well as the local community nonprofit and legal aid organization to increase enforcement of housing codes with landlords who own buildings where many of clinic access patients were impacted reside. So Sarah, I've covered a lot in this last section here. What really stands out to you? I mean, when it comes to applying an equity lens to the way we can use social risk data for population health management or community level approaches to advancing health equity, are there a couple of key recommendations that you'd really like to elevate here?
DeSilvey: [33:28] Thanks, Rishi. I'd really like outpatient clinicians and practice managers to remember a couple key things. I think the first key takeaway would be to ensure throughout adding in all uses of data, that the goal is to address the needs identified by the patients and communities whose data rightfully is. The second would be to ensure that throughout all uses, one is preventing and addressing any potential harm.
Manchanda: [33:52] Well, that brings us to the end of this introductory module on the new E/M office or other outpatient services, coding guidelines and also their implications for social risk data and health equity. At this point, we hope you feel more equipped to be able to address these learning objectives on the screen. I want to end by giving my thanks to the entire team at Health Begins the Gravity Project and the AMA Health Solutions team for their support in developing this module. And last but not least, my special thanks to my colleague Sarah DeSilvey for joining us today.
DeSilvey: [34:22] Thank you, Rishi.
Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships.
If applicable, all relevant financial relationships have been mitigated.