2020 NHSN Training Webinar – Outpatient Procedure Component (OPC) Case Scenario

>> I’m Henrietta Smith My colleague Scott Decker and I will review the Outpatient Procedure Component using a case scenario As there were no significant updates to the Outpatient Procedure protocols for 2020, the information presented during the 2019 annual training is still accurate and should be used for basic OPC training The 2019 training can be viewed at this link This 2020 training has been created to complement the 2019 training and to expand participants’ knowledge of the OPC criteria through a detailed case scenario All data in this presentation has been created in a test environment and is for training purposes only Information seen on images during this presentation do not represent any actual data submitted to NHSN by participating facilities Just a reminder of the two modules that are included in OPC, the same-day outcome measures and the surgical site infection measure Our goal in the presentation is to integrate surveillance and analysis By the end of this case scenario, the learner will be able to identify how — excuse me — identify when and how to apply the SDOM criteria, perform analysis of SDOM data and generate a bar chart, evaluate an SSI event using the OPC-SSI criteria, perform analysis of SSI data and review the analysis output, and finally, to describe how OPC can assist ASCs with monitoring outcome measures The case scenario is progressive and is weaved throughout the presentation The slides that are associated with the scenario are displayed like this one So let’s start Downtown ASC started performing unicondylar knee arthroscopies — arthroplasties, KPRO procedures, in October of 2019 In an effort to monitor outcomes for the new KPRO procedures, the ASC has decided to perform surveillance using OPC for the following measures: falls post-KPRO, transfers or admissions to hospitals upon discharge from the ASC post-KPRO, and ASCs attributed to KPRO After enrolling, the first place to start is with the monthly reporting plan The monthly reporting plan is to tell us, NHSN, what data we should expect from your facility When a module is included in the monthly reporting plan, this is an indication that the facility is agreeing to follow the protocol in its entirety This is important because this data will be included in national analyses and intra- and inter-facility comparisons It also indicates that the protocols will be followed as they are written This ensures that each facility is collecting and reporting in a standardized way In-plan reporting means a facility has decided that the module that they’re reporting — that they’re including in their monthly reporting plan uses the NHSN criteria as they’re outlined in the protocols, and these data are included in NHSN reports and publications For those non-NHSN procedures, OPC can be used off-plan Reporting off-plan means a facility has decided to track a particular event for internal use The facility makes no commitment to follow the NHSN protocol for off-plan events Any data they choose can be entered into NHSN, and such data are not included in the NHSN reports or publications, but the NHSN analysis capabilities

within the application are available As mentioned, what is included in the monthly reporting plan is in-plan, and for this Downtown ASC, they’re including the same-day outcome measures and KPRO procedures in their monthly reporting plan And to do this, to create this monthly reporting plan, start by selecting reporting plan from the left navigation bar, add, selecting the month to be monitored, selecting the year to be monitored, and selecting SDOM, and selecting the procedure category from the drop-down menu, and finally, saving the monthly reporting plan >> Thanks, Henrietta As a reminder, I’m Scott Decker, one of Henrietta’s counterparts that works on the analysis for the Outpatient Procedure Component, and now that we’ve set up the monthly reporting plan, before we start rolling into NHSN data analysis, we want to make sure that everyone has kind of a lay of the land when it comes to NHSN and where users can enter different data into different sources throughout your experience and surveillance So this first slide here we’re going to look at, there’s really five main areas in which NHSN users are going to enter data into NHSN Obviously, if you’re going to think of patient, event, procedure data, all those individual data records have their own tab in NHSN, and you can add, find, and look for data In addition, we have summary-level data for forms in the same-day outcome measures, which we’ll explain later on in this presentation, and finally we have surveys, which is facility-level data collected once a year for the previous calendar year When you select one of those data options, there’s three choices that you’re given to do with that within each data source The first: You can click add to enter data It’s going to provide you with a screen with this blank — these blank fields shown on the screen here where you’re going to add individual patient procedure or event-level records and details to save into NHSN The second option is find, which is used to look for previously-entered saved data forms Finally, there’s the incomplete The incomplete section lists the forms that have been started, but not all required fields have yet to have been completed As a reminder, the find and incomplete options are very useful for investigating data quality issues, and especially looking for missing required details or missing required data from one specific record On the next slide, we’re going to have a little bit of a visual representation of how NHSN works and how users interact with the application So you can think of NHSN analysis functionality as kind of like a mixing bowl You’re going to be able to add your individual records, whether it’s events, summary-level data, survey, procedures, into NHSN and kind of mix them up So make sure — you have to ensure that the ingredients or the items that you’re putting into NHSN are accurate, complete, and good So in this case, NHSN is then kind of like the oven that’s going to prepare and bake your dish And so what NHSN is going to do: Once you’ve added all your ingredients, it’s going to be able to put it through the application, through this power, and you’re going to be able to have final outputs when it comes to customized reports, whether those are rate reports — you can find reports on your standardized infection ratio and also just custom modified analysis reports that you’re going to be able to produce as the result of putting in your good data with event, summary, and procedure-level Finally, once you’ve added all the necessary data or all the data that you have at your disposal, your final step for data preparation is generating data sets This must be completed before you go into NHSN analysis to look at the newly-entered data If anything has changed in NHSN, generate data set so this change will be reflected in the analysis report This is often one of the first things we recommend when trouble-shooting analysis problems that come to the NHSN mailbox Note if you have any unresolved alerts, that’s going to prevent data from showing up in those SSI — or excuse me — those SIR reports Even if new data sets are generated, so if there’s incomplete data records or if there’s something — if there’s an error in one of your data entry records that are causing you to have alerts, that data will not appear until those alerts are cleared, even if data sets are generated All right Now once your data sets are generated, you can then start going into the analysis reports and looking at the different analytic options that you have at your disposal You simply go to the same tab that we looked at earlier and click on reports

under the analysis tab to see all available report options in NHSN This screenshot here on the left is kind of an — is an example of the options you’re going to see in the Outpatient Procedure Component We’re going to see both measures for SSI and same-day outcome measures, and under each of these folders, we’re going to find different analysis options that include line lists, frequency tables, bar and pie charts, and the SIR report for SSI events The other main tool that you see on this page is the advanced folder The advanced folder includes several reports that can be modified more to analyze specific data for your facility At the beginning of the presentation, I talked about main — the five main areas of data sources that you, the user, are going to be entering data You can then see on this slide there’s five main — there’s more than five, but there’s those five folders under the advanced folder where you can analyze and look at your data even further, whether it’s patient, event, or procedure-level data, or you can even look at summary or plan data Each folder can collapse to provide you with several report options very similar to what we looked at with the SSI and SDOM measures, such as line lists, pie charts, and more By selecting one of those report options, you’re going to be presented with a menu of three different selections that you can choose The first one at the top of the list will be run report This will provide all data output for all available data for this HAI with default variables displayed Modify report will allow you to set specific time frames, select variables, and sort data you’re interested in looking at rather than the default options previously selected for you in run report The final option you have is export data set This allows you to transfer your data sets or your data to several different file types, including Excel, rich text format, or SAS data — SAS file sets, or — excuse me — SAS files The key takeaways we want you to remember before moving to, you know, looking at specific SSI or SDOM measures is complete all required fields for each data record before you proceed to analysis By selecting run report, NHSN will generate a default report with select variables and all entered data from your facility Finally, as a final reminder, generate data sets after you enter new data in NHSN before you begin running analysis >> Now we’ll take a look at the case scenario for SDOM On November 14th, 2019, Mr. Sam Clarke, a 53-year-old triathlete, completes registration at Downtown ASC for right lateral unicondylar knee arthroplasty — KPRO The procedure was performed, and his recovery was without incident As Mr. Clarke was being prepared for discharge, while being transferred to a wheelchair, he became lightheaded and lost his balance Mr. Clarke fell to the floor and bumped his right knee against the bed frame Mr. Clarke was assisted back to the bed and assessed He was found to be hypotensive, with a scant amount of bleeding from the right knee surgical wound The bleeding was controlled with a compression bandage The patient was transported to Metro Health Hospital emergency room for further evaluation and x-rays of the right knee Mr. Clarke’s blood pressure was found to be normal, and his right knee device was intact by x-ray Follow-up instructions were provided, and the patient was discharged to home Now, applying the SDOM criteria, all patient encounters are included in the surveillance, and including SDOM in the monthly reporting plan means all four outcome measures are monitored, and when all of the patient encounters are included in the surveillance, an encounter is being — is defined as — excuse me — as — is defined as any patient visit to an ASC where the patient completes the registration process, and some ASCs may refer to this as an admission Applying the SDOM criteria to the fall that Mr. Clarke experienced, the fall was a sudden, uncontrolled, unintentional downward displacement of his body to the floor and meets the fall criteria and should be reported as a fall SDOM Applying the SDOM criteria to Mr Clarke’s transfer to Metro Health Hospital, the transfer was from the ASC directly to the hospital for evaluation

and meets the hospital transfer admission criteria and also should be reported as an SDOM Keep in mind that the reason for the transfer is not included in the measure Any cause, including medical indications, that are not related to the procedure or the reason for the encounter at the ASC should be included in the monitoring Reporting instructions for entering SDOM: If the patient experiences more than one different measure, each of those different measures should be reported If the patient experiences one or more of the same measure, then only one of those measures should be reported And if no measure — excuse me — if no events occur during an encounter, then nothing should be reported for that patient The steps for entering the SDOM event start by selecting event from the left navigation bar and then selecting add, and just walking through this slide — it’s numbered here — the mandatory data fields are marked with a red asterisk The minimum information in the patient information section is marked here one through three, and it includes patient ID, gender, and the patient’s birth The next — the event type marked here is number four The OP SDOM is selected This is followed by entering the date of the event, which is marked here number five, and that would be November the 11th, 2019 And finally, the appropriate SDOM event is marked, and here we have selected patient fall and hospital transfer And finally, the record is saved, and a little green box appears at the very top of the form that indicates the event has been successfully saved And just a quick note reminding us about the reporting instruction: reporting instruction A, which denotes that if the patient has two different measures, it should be reported on the same form When entering the SDOM summary data, a single measure is actually — a single data point is actually entered, and again, walking through from the left navigation bar, selecting summary data and then add and then, from the drop-down menu, the same-day outcome measure summary data type should be selected And as I mentioned earlier, a single denominator is entered for all SDOM events This is the total number of encounters for the reporting month The record should be saved, and if there are no events to be — that are reported for that surveillance month, then the no same-day outcome measure should be marked As a quality check, the box is grayed out and made unavailable if an event has been entered for that reporting month, which is the case here The SDOM — >> Now that we’ve completed entering our same-day outcome measures summary data, the descriptive analysis options, such as line listing, frequency tables, and bar and pie charts are available for same-day outcome measure events and some monthly summary records Guides on using the NHSN OPC analysis features are available in the analysis resource section found on this link So our first stop that we want to do is I’m going to have you remember back to where we find those analysis reports in NHSN and find your way over to the same-day outcome measure folder, where we can find line listing for same-day outcome measure events For this example, we want to modify the report to only include specific procedure types and time frames to limit the number of event records that we have so we can find Mr. Clarke’s easily

By clicking modify, we’ll be presented with a number of tabs at the top of the screen to help filter and exclude certain variables to set up parameters to find the data quickly The first thing we want to do is set our time period You can see in the highlighted section here event year quarter is highlighted and selected This is going to ensure to enter our time period for the data to be restricted to Since we’re looking for Mr. Clarke’s event, we are only interested in quarter four of 2019 This would include all of the events entered for October, November, December of this calendar year These selections can make your line lists much more manageable and easier to read rather than having a long line list with all available data for same-day outcome measure events listed The next thing we’re going to do is filter our data to get even more specific Because we’re only looking for one patient, we’re going to filter this data by using the patient ID by selecting patient ID in the drop-down menu highlighted here The next step we’re going to do is select our operator to equal This is going to limit variable to only patients with a specific ID number that we set it to Finally, we’re going to enter that patient ID number in the blank field to limit to only one patient This is where we must enter Mr. Clarke’s patient ID exactly as it is recorded in the patient record form Now output that we should expect to see is just one row, indicating that we’re just looking at one patient, Mr. Clarke The first thing we want to look at is just to make sure the correct patient and event details are listed We can see that we have an event date for November 14th, 2019, which fits to our parameters that we set for the time frame to just have Q4 2019 data In addition, we see that the patient ID is that of Mr. Clarke’s The second thing we want to bring our eyes to is the same-day outcome measure for patient fall equal to Y, which is yes This indicates that this patient fell after the procedure Third, we want to look at the same-day outcome measure hospital admission This is also set to Y and indicates that the patient was admitted to the hospital after their procedure The remaining same-day outcome measures that you’re going to find to the right on this table are all set to no, indicating that there are no other same-day outcome measures recorded for Mr. Clarke for this event date Same-day outcome measures event line list can be limiting, and it’s only — really, the only thing that we’re looking at from those analysis options Another thing you may want to do as a user is you potentially use different visualization tools and reports that are found in NHSN A bar chart is a good way to visually show trends over a period of time and could be considered running this for different reports to incorporate visualizations This can help bolster data presentations or reports to hospital staff and other stakeholders In this example, we’re going to set — we’re going to try to create a bar chart looking for this facility’s trends of same-day outcome measures for a full calendar year Very similar to what we did for the patient same-day outcome measure events line listing, we’re going to have to set and filter our data, starting with our time period Again, we’re going to set the date variable equal to YQ, and we’re going to set the beginning month and ending to the year 2019, and last, the thing we’re going to do is select quarter one as the beginning of our data and the ending as quarter four This is going to ensure that all data from the calendar year 2019 is going to be included in our bar chart The next step, what we want to do is look at our display options The first thing we will look at is the chart variable to event date YQ This chart variable selection allows you to set the time period you want to establish for each bar By choosing event date YQ, each bar is going to represent one quarter of 2019 The next selection we want to make is our stratification variable Here we’re going to indicate that the stratification variable is going to be patient fall This will exclude all other same-day outcome measures except patient fall and ensure that patient fall will be summed at the quarter level in each bar for 2019 So another thing we want to ask is: What can we learn from our same-day outcome measure data by using this bar chart looking at a whole year’s worth of data? We can see that we have a bar chart established here, and on top of each bar, we have a number The total number of patients with falls will appear above each bar This would say that for the first bar there, for 2019 quarter one, there were three patient falls that were observed and entered for that quarter The next item is the percentages So within each bar, a percentage of patient falls for the quarter is displayed So, for example, for 2019 quarter one, 23.08 of all patient falls occurred

within this quarter for the 2019 calendar year This bar chart, we can see this part shows that patient falls have occurred at a relatively consistent pace during each quarter of 2019, neither trending upwards or downwards They stayed pretty consistently in the same area Before we move on to SSI events, the key takeaways for the same-day outcome measures is to remind everyone that the means to track and trend adverse events such as fall, burn, wrong events, all-cause hospital transfer admission Each patient encounter is monitored for all of the same-day outcome measure events that occurred during this day in the ASC There was no post-discharge surveillance Modifying reports by using filters and specific time periods can help make same-day outcome measure reports more concise and manageable, and lastly, using data visualizations like we just saw, such as bar charts and pie graphs, can help make your data tell a story >> Now moving the case scenario into SSI The following note dated November the 15th, 2019 was documented in Mr. Clarke’s medical record at the surgeon’s office: Call received from the patient to report increased tightness in his knee Patient did not have any other symptoms Patient is advised to continue to elevate his knee and apply cold packs intermittently This is likely increased swelling secondary to trauma at the operative site due to the post-op fall The patient was instructed to follow up if no improvement Now the question “Should consideration be given to the fall as a reason to exclude an SSI if a subsequent SSI develops?” and the answer to that is no No consideration should be given to the fall If Mr. Clarke experiences a subsequent SSI that meets the SSI criteria, the event should be reported This is outlined in the SSI event reporting instruction number nine On December 3rd, the infection preventionist from Metro Health Hospital contacted Downtown ASC and provided the following information: On November 25th, 2019, Mr Clarke was admitted from the surgeon’s office with severe right knee pain, fever, and blood-tinged drainage from the incision An incision and drainage of the right knee was performed A hematoma was observed in the joint space There was no obvious pus, the prosthesis appeared intact, and the hematoma was evacuated Cultures were taken from both the joint space and the surface of the KPRO device Both cultures subsequently grew Staph aureus The patient was treated with IV antibiotics for three days and eventually discharged to home with orders for home health and IV antibiotics On December 30th, Downtown ASC received the following information from the surgeon’s office: On 11/21/2019, Mr. Clarke was seen for a follow-up appointment with complaints of pain, swelling, and swelling of the right knee There was slight separation of the incision, with a small amount of serous drainage noted After the wound was cleaned, a swab of the incisional drainage was collected and Steri-Strips were applied A prescription for antibiotics were provided and follow-up appointment was scheduled The culture subsequently grew Staph aureus A reminder: The OPC-SSI module includes two sets of SSI criteria, the general SSI criteria and the breast surgery SSI criteria Since the procedures that were — that are being followed are KPROs, the general OPC-SSI criteria should be used to assess the SSI events Another reminder is that KPRO procedures have a 90-day surveillance period which means the procedures should be monitored for 90 days, and day one is the date of the procedure Let’s take a look at the procedure data Again the mandatory fields are marked with a red asterisk here in the patient information sections noted as one, two, and three, and a look at the procedure information section, marked here as number four, we are

— we need to report the NHSN procedure category, which is labeled here as the procedure — NHSN procedure code There is 30 operative procedure categories that are included in OPC, and they’re included in the drop-down menu We’ve selected KPRO Marked here as number five, the CPT code is also required, and it should be entered, followed by the procedure date, marked here as number six The procedure date is November 14th, 2019 When compared to data entry for SDOM, there are many more variables that are required for SSI surveillance, the reason being the risk for an SSI is based on the procedure that is performed So here, marked as number one, are some of the required fields in the procedure details section For the procedure category that is being monitored, all procedures performed should be entered This is considered the denominator for procedure I’d like to highlight here an optional variable, which is the surgeon information This variable can be added to your data collection to assist with creating surgeon-specific reports Surgeon codes can be created using the facility tab on the left navigation bar These codes should be created prior to entering the procedure records And finally, when the data are complete, the record should be saved After the record is saved, again the box that confirms that the data has been added appears at the top of the screen Now we’ll move into looking at the SSI event data Again, the patient information in this section is exactly the same as the — in — for the procedure record The required fields are marked with a red asterisk The SSI event information start with selecting OP SSI as the event type Next, the date of event is entered The date of event is the date when the first element used to meet the OPC-SSI infection criteria occurs for the first time during the SSI surveillance period In our case scenario, the date of event is 11/25 An explanation about the date of event: Here we see that the SSI event met superficial criterion B on 11/21, but there is a reporting instruction number three that says that the SSI event should be reported at the deepest tissue level The infection progressed to a deeper tissue level on 11/25 and is the SSI date of event in our case scenario, which was shown in a previous slide Next, the SSI event should be associated with or linked to a procedure An important reminder is that the procedure records should be entered before the SSI event so that the event can be linked If the patient has had multiple procedures, eligible procedures for that patient are listed, and the correct procedure should be selected and then linked, and in our case, the patient only had one procedure, and so it is linked to this KPRO procedure Now that the procedure is linked, there are procedure data elements that are auto-filled As mentioned earlier, the infection at the deepest tissue level should be reported In this case, it was an organ space SSI Here, reviewing the organ space criteria, criterion B was met with organisms that were identified from a tissue culture So in our scenario, organ space is selected, and criterion B, which is organisms identified, is also selected

A note here: Additional monitoring for the KPRO performed on 11/14/2019 is not required as the infection is documented at the deepest tissue level and only one such infection can be attributed to a procedure Only if the patient returns to the operating room for another NHSN operative procedure, a new surveillance period will start Based on our case scenario, the SSI event details were received from another facility, which was Metro Health Hospital, so passive surveillance is selected, along with report from another facility is marked Downtown ASC also received information from the surgeon’s office that reflected a superficial SSI, but this information is not reported Accuracy and identifying SSI events post-discharge can be challenging, but is critical for attributing the event to the correct facility and operative procedure Inaccuracy hampers understanding SSI risk as well as the ability to develop effective prevention strategies, so we require that facilities use a post-discharge process that is active and patient-based Active surveillance is patient-based — is a patient-based process that is intentional, systematic, and focused, with the aim to identify and detect SSI events The process is structured to foster two-way communication with the patient, the surgeon, and medical staff and other facilities Examples include post-discharge letters or phone calls to patients and inter-facility notification of patient encounters or admissions The process may be unique to each facility, but the goal is to identify SSIs that meet the NHSN OPC-SSI criteria In contrast, passive surveillance is a bit random in nature and unstructured It is dependent on other entities and sources for identifying SSI events Reports of SSI events are incidental and unsolicited This method may not accurately allow SSI attribution and may not allow facilities to monitor their SSI rates accurately An SSI event is attributed to the facility in which the NHSN operative procedure was originally performed Facilities that have identified potential SSI events that are attributable to procedures performed at a different facility should provide details of the potential events to the facility where the procedure was originally performed And finally, the SSI event We add the organism to the report since the organism — the organism that was identified is Staph aureus, so this is selected from the organism list, and it is saved And finally, the box appears at the top that indicates that the record was successfully added to the data >> All right Thank you, Henrietta As many of us already know, SSI surveillance, the procedure carries the risk of infection, meaning that risk factors for each procedure category and each procedure that’s recorded may differ In NHSN analysis reports, they allow you to view these risk factor variables for each procedure to ensure good data quality and help inform infection prevention priorities and practices So we saw Henrietta select several different risk factors or enter several different risk factor information within these records, and so we’re — now we’re going to take an opportunity to take a look at these within our analyses So just a reminder: We’re going to return to the advanced folder for this section as I run through an example for Mr. Clarke and finding his procedure on the line list So we should be familiar with this — finding this analysis report under advanced in the procedure-level folder, under line listing for all procedures, and we’re going to want to modify this report just to highlight procedures like Mr. Clarke’s

So our first step here is we’re going to be greeted with these tabs, and what I want to do, what I want to demonstrate here, is how to modify and also just save a custom — and save a custom report that we can use later on So I want to bring everyone’s attention to all the different details that you can select and look at from this front — this first screen you’re going to see when you modify So the first thing you’re going to see is this show descriptive variable names in the top left of the screen or in the top left of the photo here By selecting show descriptive variable names, you’re going to be using the variable name that we’ve given that’s more clear — for example, procedure ID versus proc ID The proc ID is just an abbreviated code that we’ve created in NHSN to define procedure ID So it’s easier or maybe more clear to use procedure ID So by selecting this checkbox and this checkmark right here, we’re going to be given more clear and easier to read variable names to run through our analysis and set up our filters and sort our variables with The next piece of information we have is the analysis data set, indicating which data set we’re using to pull this data from We’re going to see it says OP procedures, so we’re going to see that all the data that we’ve entered into our procedure-level records are going to be incorporated in this line list it’s limited to, but the next, our type field here or that type category, is going to tell you what kind of output you’re going to expect So in this case, we’ve selected a line listing, and finally, last generated here I want to bring everyone’s attention to this It’s timestamped with when the data set was last generated So this is kind of your final warning and last opportunity to identify, “Hey, have I added new data since this specific date that I want to have incorporated in this line list?” If the answer’s yes, we’re going want to — have to take a couple steps backwards and regenerate data sets If you have all the data, if all the data is up to date to this point in time, we can proceed forward with setting up the rest of our modification to get to our output The next thing I want to do: Like I said, what I’d like to have us do in this time is set up a custom report that we can save and then access later on So by using the title, it’s an opportunity to kind of save a more clear and specific indication of what type of report we have, so this is a good opportunity to consider renaming it So knowing that, knowing that I want to use this report and maybe access it in the future, I’ve titled this “Line Listing of KPRO procedures for November 2019,” so very clear on what this output is going to produce The next thing we see on the screen is the format section So you can choose the format in which the report is displayed and presented to you, such as HTML, Excel, or PDF, and as a reminder, in NHSN, the default format that we use is HTML Now a quick word on some of these formats and the uses for the different types As I said, default setting is HTML, and this is because it’s easy to read and view data quickly However, if you want to, you know, print, save a report, or send it electronically as an attachment, a PDF file type is useful An XLS or your — an Excel file is helpful maybe if you want to filter or do some analysis of your data or manage some of your data in an Excel data sheet, and then finally, we have rich text format So information like this can be opened with this file type in several different programs and software, depending on what you’re using with your computer The next part here — we should be familiar with this, but we’re going to walk through it again — is selecting our time period So again, this allows for the selection of a specific time period for your report The first thing we want to do is select a date variable from the date variable drop-down menu and specify the beginning, ending date for the desired time period If the ending date is left blank, the results will only include — excuse me — will include all data from the beginning time period and forward So whatever you set your beginning time period to, if you have no ending, it’s going to give you all the days of data up until when the data was last generated So here we’re going to see how we set this up For our example, we are looking at November 2019 data, so we set that procedure date year/month as our date variable, and again, we want to select the specific month and year for our data, and in the fields or in the boxes next to that, to the right of the date variable, we have beginning and ending We’ve chose to select November 2019 as 11/2019 as the beginning and 11/2019 as the ending This will ensure that all data for November of 2019 is only listed in our line list

The next step is our filters Filters are set up by groups and rules Each will allow you to specify values to include in your report A group is something that will generate a table in your report with a select number of rules or conditions set Rules are conditions that will restrict what type of data is populated within a group or a table, so simply group is your table and rule are your variables or your factors that are going to be conditioned within that table In our example, we set up only one group and one rule Our one group embodies our rule procedure code Procedure code is selected in the drop-down box on the bottom of the screen here We will then set up our operator to equal This will give us a drop-down to select equal to, and then, finally, in our blank field next to it, we selected or we’ve entered KPRO This is to specify the desired value of the variable that we should include in our line list Since we only want to view KPRO procedures, we enter that code in the blank field, and this is something you have to manually enter that is case-sensitive and must be exact for the variable that you’re trying to isolate and measure for this rule And then finally here, all our selections are made within one group, so everything you see here within that gold border is a group, and that procedure code equal to KPRO is our rule within the group Our next stop is display variables On the left-hand side of the screen, we see all available variables that you can bring into your selected variables box on the right All available variables are able to be brought over and seen in your final output Identify the variables of interest in the available variables and then bring them over to the selected variables by highlighting them, selecting selected, which will then bring them over to the right side of the screen under selected variables and will ensure that they’re included in your final output So in this example, we’re going to look at some of the fields that Henrietta entered in her procedure records in her event records So we have duration, ASA class, and BMI value Those are variables that we were interested in They could have something to do or associate with a risk with our knee procedures, and so we want to take a look at them in our final output so we’ll go over to the right-hand side of the screen Finally, once we’re ready to generate a report, we just simply go to the bottom of our modify screen to select run What we see here is our giant line — or not our giant, but a line list of our KPRO procedures The first thing I want to bring our attention to is to the left-hand side of the screen to look at some of the data that’s presented here or some the information that’s presented here The first thing we see is our OP procedure is listed here This is to indicate that the data set that was used to generate this report was our procedures data set The next level of information we want to look at it our proc date year/month This includes the date fields or the date variables that were used that this data will be found within So, again, we double-check that we’ve selected that only the month of November 2019 is going to be incorporated in this line list As we go through our line list, we could then validate those things by looking at the procedure date column The procedure date column is just as we expected to have — is that all procedures that are listed here are found between November 1st, 2019 and November 30th, 2019 The next thing to look at is our procedure code column All procedures found here are KPRO procedures To the right of that, we have three new variables that we’ve brought in: our duration, ASA class, and BMI values, all with their own individual columns available to view Since we’re looking for Mr Clarke, we knew his procedure, that occurred in November 2019, and it was at KPRO We do find him on this list with his correct patient ID, date of birth, gender, and procedure ID Not only can we find Mr Clarke’s information on this list Line lists such as this can also provide us with opportunities to find potential data quality issues or areas of improvement for our facility, so modified analysis, they can assist with our data quality efforts There’s two pieces of information here that do stick out We find that one procedure duration was four minutes long, which seems short Another area of concern is we have one patient with a BMI value with an extremely low mark of 7.6 This is an opportunity for our facility and for data quality efforts to be informed to validate that these were entered correctly and if so, if they led to any kind of —

if they led to an event in the future There are other options outside of running your report in NHSN that you can choose at the bottom of the screen The second I want to show you today is the save By selecting save, you’re able to save this report for future use Selecting save brings the analysis report title that saves with your name — Scott — the type of report that you have — here, a line listing — and the title you gave it at the beginning of your modification Once you’ve selected and once you’ve titled your report to what you’d like to save it as, it will then be populated at the bottom of the folder in which you found the initial report This report can now be accessed at any time upon logging into NHSN and going to reports It also can be modified any time to change time frames, add or drop variables, or change groups or rules Another option you have is to export a modified report to an Excel sheet, a SAS file, a CSV file, and many more types by selecting export Later on, we’ll show this is only one of two options you have when exporting your data As early on the presentation, when you select a report, you’re given three options: run, modify, or export data By selecting export data in this scenario, you’re going to export the entire data set from which the resulting report is generated, so all the modifications that you may or may not have will not be included in this report It’s just going to give you a raw report of all data that’s been entered for this folder The second option is if you select it here, within the customize or the modified section of your analysis, is to find — is export the output data set that appears at the bottom of the modify screen This is going to present you with two options: one, to export your entire data set, or two, export the analysis data set using the modification, so this will only export data used in generating the report for the specified time period, including selection criteria So to export the data set that we just created and customized, we would select the second option, export analysis data using set modification Finally, moving on to SSI event analysis, after we’ve analyzed the procedures, we may want to look at SSI events, specifically the one that we have for Mr. Clarke’s KPRO event We will go back to the analysis reports folder SSI and find line listing all SSI events and modify the report to find Mr. Clarke’s Similar to the other screen, we’re going to select the time period in which we know Mr. Clarke’s event was recorded Because his event was recorded during quarter four of 2019, we set a date variable, yr/quarter, to 2019 quarter four to begin and end in that same quarter So like I said, we’re interested in Mr. Clarke, so we select 2019 quarter four, and then, like we did in previous examples, we’re going to go to our filters and setup our rules within a group here We know Mr. Clarke’s event that we’re interested in is a KPRO event, so we simply select procedure code to only observe KPRO is equal to KPRO We’ll use a drop-down box to select procedure code, then the operator to equal, and then manually enter KPRO Make sure procedure code matches exactly the code from your reporting plan, as it is case-sensitive All right Our SSI event analysis output We’re given a table here, and highlighted in the table, we see Mr. Clarke’s name In addition to Mr. Clarke’s name, we see that we have five KPRO events for quarter four of 2019 Among them is Mr. Clarke’s event, highlighted in green above, from the procedure date marked November 14th, 2019 What also may be alarming here is that there are five KPRO events in one quarter This is an opportunity to conduct an additional analysis to help identify maybe clinical interventions or additional information that will inform us about these events or procedures We will take a step backwards now and go back to our filters and our display variables to bring in new variables of interest that could provide us more details or more information regarding Mr Clarke’s procedures or other procedures that had five events during this period

So in this situation, we’ve selected ASA class, BMI, and also, we’ve selected surgeon information in our new selections Now remember Henrietta had entered surgeon code information and surgeon’s first and last name when she was entering procedure records earlier in this presentation By entering display options as another option you can have, you can use these data variables Display options allow you to break up data by variable type to create multiple tables, and by bringing in surgeon code, we can now display options by surgeon by surgeon’s last name We will set surgeons last name to our page — to the page by variable to ensure that we now have procedures organized by surgeon’s last name and given a table for each surgeon So our display option, we should expect to see multiple tables, one table for each surgeon that conducted procedures during this time frame, and looking at the SSI event output, that’s exactly what we see We see three new tables now organized by surgeon’s last name We see that there is a surgeon Garrett, Jacobs, and Tyler that performed procedures for KPRO during quarter four of 2019 that had events We also see the new variables that were brought in from the display variables from the previous page for ASA class, BMI, and the surgeon code By adding surgeon code and surgeon’s first and last name, we then can assemble these reports or assemble this information and use them to put together post-discharge surveillance surveys for these surgeons Key takeaways regarding the outpatient SSI module to keep in mind are the module is a means to track and trend ambulatory surgery center events, SSI events, that are associated with the 30 NHSN operative procedure categories All procedures and SSI events of the selected operative procedure categories are to be reported There are two sets of SSI criteria: the general and breast surgery criteria SSI events are identified as superficial incisional, deep incisional, or organ space We also went over that we must monitor all procedures and events of the selected operative procedure category, and finally, post-discharge surveillance is required Key takeaways that are analytic or analysis-focused- our risk factor variables can be analyzed at the procedure level to help identify areas of improvement for the standardized infection ratio, time spent creating custom modified reports will help save time in the future for data analysis and will bolster data quality efforts, and lastly, data can be exported and saved into several different file types using NHSN reports >> So as we come — as we conclude, the question that we ask is, “How can OPC assist Downtown ASC with monitoring its KPRO outcome measures?” Using the SDOM module allows the ASC to monitor falls and hospital transfers or admissions using OPC-SSI — the OPC-SSI module It allows the ASC to perform surveillance for SSI events Both modules provide analysis reports that include options to modify and customize the reports based on the facility’s needs What are some of the benefits of using OPC-SSI? Is that the modules include measures that have been vetted by external ASC quality organizations, and as data are collected, it will allow us to create national benchmarks to be established that will include all payer types The use of NHSN is advantageous to facilities and public health entities because CDC is able to aggregate and analyze the data and provide reports at the facility, state, regional, and national level to monitor quality, process, and outcome measures Within our presentation, we have successfully identified when and how to apply SDOM criteria, demonstrated how to perform analysis of SDOM data and generate a bar chart, shown how to evaluate an SSI event using the OPC-SSI criteria, outlined how to perform analysis of SSI data and review the analysis output,

and described how OPC can assist ASCs with monitoring outcome measures This concludes our presentation Please send your questions to nhsn@cdc.gov and include OPC in the subject line Thank you for viewing