Using the Trauma Quality Improvement Program (TQIP) Metrics Data to Change Clinical Practice Abigail R. Blackmore, MSN, RN Pamela W. Bourg, PhD, RN, TCRN, FAEN
Learning Objectives Explain the importance of creating, gathering and distributing metrics data to evaluate trends and implement practice change. Identify a problem in clinical outcomes and assess for areas where practice can be improved. Identify resources to help change clinical practice and understand how to validate the change through analysis of quality metrics data.
Disclosure Statement Presenters disclose no conflict of interest relative to this educational activity.
Successful Completion To successfully complete this course, participants must attend the entire event and complete/submit the evaluation at the end of the session. Society of Trauma Nurses is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center's Commission on Accreditation.
Introduction Since 2008, the Trauma Quality Improvement Program (TQIP) has been working to improve the quality of care for trauma patients Collect data from trauma centers Provide feedback to each center on performance using risk adjusted benchmarking to national comparisons
TQIP Data Report Provides a scientific basis in which you can change and improve your clinical practice Guides you in understanding your population and who you are impacting (Population Management) Helps you understand your institution s overall problem areas, so that you can create individualized solutions If successful, you may increase quality of care and decrease costs at your hospital The report also helps you understand the areas you excel in
But How Do I Use my Report?
Purpose Provide a step-by step tutorial that enables you to: 1. Describe the data provided by TQIP 2. Identify trends or outliers in the data 3. Create individualized solutions / corrective action plans 4. Reevaluate your data and the impact of your corrective action plan Review this process using 3 examples from our institution
TQIP Data Reports Blunt multisystem injuries Penetrating injuries Shock patients Severe traumatic brain injuries Elderly patients *Cohorts per the Fall 2017 Benchmark Report Elderly blunt multisystem injuries Elderly patients with isolated hip fracture Orthopedic fractures Hemorrhagic shock Splenic injuries Statistical models are used to create risk adjusted estimates for outcomes/complications at your hospital in comparison to TQIP as a whole Adjust for relevant patient and injury characteristics
TQIP Data Reports Odds Ratio (OR) measure of association between an exposure and an outcome Look to see where your OR falls on the box plot OR >1 = odds of an outcome are greater than average OR < 1 = odds of an outcome are less than average If the confidence intervals are both above or both below the median line, your hospital is considered a high or low outlier, respectively. (ACS TQIP Benchmark Report)
Identify Outliers
Identify Trends How are we performing over time?
Trends and Outliers Once problem areas are identified, consider: Is this a quality issue? Is this a data coding issue? Is it a process of care issue? SAH EXAMPLE: In our first report, we had a high percentage of DVTs. 1. Was it because we do baseline screening for DVTs? (process of care?) 2. Was it because we are not following our DVT prophylaxis protocol? (quality) 3. No, it was a coding issue. We went back and recoded DVTs, according to the specific definition provided by TQIP, and then our DVT complication aligned with the other facilities.
DRILL DOWN on your data!!! Use the drill down feature to obtain patient level data, such as demographics, clinical characteristics, and outcomes. REMEMBER the NTDB data center? (OLD WAY)
ACS Quintiles.(NEW driller)
Create individualized solutions Share results with trauma program staff, multidisciplinary committee, and hospital administration Form a committee with interested parties to create a corrective action plan. Include tasks such as: Create or revise clinical care guidelines if necessary Review definitions of specific complications with team Provide education for inter-rater reliability purposes Double check software data mapping if necessary
Reevaluate the Data
Examples SAH used TQIP data to analyze problem areas in TQIP benchmark reports. They included the following concerns: Unplanned return to ICU in Isolated Hip Fractures Pneumonia in Severe TBI Increase CAUTI rates as complication
Example 1 Isolated Hip Fractures in the Elderly TQIP data demonstrated an increase in major complications among isolated hip fracture (IHF) patients 65 years at our trauma center in comparison to other like facilities. Our objective was to further investigate the IHF patients with major complications in order to identify trends and create specific corrective action plans that will improve care.
IHF Methods October 2014-August 2015 IHF Patients 65 years (n=116) No Major Complications (n=101) Major Complication (n=15)
IHF Methods 15 patients had 19 major complications: Unplanned return to the ICU (n=11) Deep Vein Thrombosis (n=2) Myocardial Infarction (n=2) Stroke/Cerebrovascular Accident (n=2) Urinary Tract Infection (n=1) Catheter Related Blood Stream Infection (n=1) Since 11/15 (73%) patients had an unplanned return to the ICU, this was our focal group in which to identify trends and create an improvement plan.
IHF Methods Data Analysis: Retrospective case analysis of patient management Compared demographics, clinical characteristics, & outcomes between IHF patients with an unplanned return to the ICU and those without major complications Fisher s Exact and Wilcoxon two-sample tests
IHF Demographics & Clinical Characteristics No Major Complications (n=101) Unplanned Return to ICU (n=11) P-value Age, years 84 (66-99) 83 (70-92) 0.70 Female 67 (66.3%) 6 (54.6%) 0.51 Smoker 4 (4.0%) 1 (9.1%) 0.41 Hypertension with medication 59 (58.4%) 7 (63.6%) 1.0 Diabetes 11 (10.9%) 2 (18.2%) 0.61 Bleeding Disorder 13 (12.9%) 4 (36.4%) 0.06 2 Comorbidities 38 (37.6%) 6 (54.6%) 0.34 Injury Severity Score 9 (9-10) 9 (9-10) 0.61 Arrival to OR (hours) 23.8 (2.7-127.6) 39.6 (12.6-73.9) 0.01 *Data presented are n (%) or median (range)
IHF Outcomes No Major Complications (n=101) Unplanned Return to ICU (n=11) P-value Deep Vein Thrombosis 1 (1.0%) 1 (9.1%) 0.19 Myocardial Infarction 0 (0%) 1 (9.1%) 0.10 Unplanned Intubation 1 (1.0%) 0 (0%) 1.0 Urinary Tract Infection 3 (3.0%) 1 (9.1%) 0.34 Hospital Length of Stay 5 (2-13) 8 (5-14) <0.001 Discharge Disposition Home Rehabilitation Skilled Nursing Facility Died Other 20 (19.8%) 7 )6.9%) 71 (70.3%) 2 (2.0%) 1 (1.0%) *Data presented are n (%) or median (range) 2 (18.2%) 1 (9.1%) 7 (63.6%) 1 (9.1%) 0 (0%) 0.46
Deeper Dive into the 11 Patients with an Unplanned Return to the ICU Case analysis, documenting: Time to surgery and the reason for the delay If the patient was initially admitted to floor and had an unplanned ICU stay or if they were discharged from the ICU but had an unplanned return Reason for unplanned ICU stay
Conclusion: IHF patients with an unplanned return to the ICU experienced a longer time from arrival at the hospital until operative fixation of their hip fracture, thus reinforcing the importance of timely (<48 hours) surgical intervention for geriatric hip fractures.
Plan of Action: Provide education to the consulting services regarding our geriatric IHFs and resultant complications Develop geriatric clinical care guideline that focus on areas identified in the drilldown, such as decreasing the time from arrival to operative fixation Evaluate the effects of the performance improvement process via further review of TQIP benchmark reports
Example 2 Pneumonia in Traumatic Brain Injury Patients Fall 2016 TQIP report High outlier complications Pneumonia in severe TBI
Spring 2016 33
All patients were reviewed in the EMR for exact organism associated with pneumonia.
Spring 2017 35
Example 3 Catheter Associated Urinary Tract Infections Nursing leaders at our institution recognized a high number of catheter associated urinary tract infections (CAUTIs) when reviewing fiscal year 2014 CAUTI data. As a result, the HOUDINI protocol, an evidence-based, nurse driven urinary catheter removal algorithm was approved for use at our institution in 2014. TQIP data for CAUTIs demonstrated our institution was a high outlier (10th decile, Odds ratio = 4.89) in comparison to other like facilities during the July 2015-June 2016 reporting period.
CAUTI Objective To examine the impact of implementing the HOUDINI protocol and the characteristics of patients with CAUTI at our institution.
CAUTI Methods Implementation of the HOUDINI protocol began in 2015. All nurses had to complete online learning modules by June 30, 2015. Instead of waiting for orders to remove the catheter, the nurse performs daily, morning assessments for continued catheter use. The nurse removes the indwelling catheter unless HOUDINI criteria are met: Hematuria Obstruction Urologic, gynecologic, or perineal surgery patients Decubitis ulcers open sacral or perineal wound in an incontinent patient I&O, strict for critical patients on comfort or hospice care Immobility
CAUTI Data Analysis Retrospective study of trauma patients at a Level 1, Community Based Hospital Examined one year of data after the required nursing education on the HOUDINI protocol was complete (7/2015 6/2016) Reported the frequency of CAUTIs by month. Compared the proportion of CAUTIs in the first half of the year (7/2015-12/2015) to the second half of the year (1/2016-6/2016). Assessed demographics, clinical characteristics, & outcomes between patients with CAUTI to those without CAUTI using chi-square and Wilcoxon two-sample tests
CAUTI Results There were 1154 patients in our TQIP database between 7/1/2015 and 6/30/2016. 32 (2.8%) patients developed a CAUTI The number of CAUTIs decreased from 27 (84%) in the last 6 months of 2015 to 5 (16%) during the first 6 months of 2016 (p<0.001) 9 8 7 6 5 4 3 2 1 0 Frequency of CAUTI by Month 2015 2016
CAUTI Results Patients with CAUTI were significantly: Older Female Higher injury severity score More likely to use alcohol and steroids. Patients with CAUTI had more complications including: VAP Increased ventilator days More days in the ICU Longer hospital lengths of stay
CAUTI Organisms Organism n (%) E. Coli 13 (37%) Klebsiella 8 (23%) Staphylococcus Aureus 3 (8%) Proteus Mirabilis 3 (8%) Pseudomonas Aeruginosa 2 (6%) Candida Albicans 2 (6%) Proteus Vulgaris 1 (3%) Streptococcus Pneumoniae 1 (3%) Lactobicillus 1 (3%) K. Oxytoca / r ornithinolytica 1 (3%)
Conclusion The data suggest that implementing the HOUDINI protocol has led to fewer CAUTIs at our Level I Trauma Center. Based upon the reported CAUTI organisms, good handwashing is not only essential for providers, but for the patients too.
Plan of Action Provide education on the prevention of CAUTIs and the HOUDINI protocol through an online learning portal. Communicate the risk factors that place patients at risk for CAUTI to the staff to ensure increased awareness, use of the HOUDINI protocol, and good handwashing. A committee at our institution has a debriefing on every CAUTI event. Use the electronic health record to monitor indwelling catheters by pulling a daily report of every patient with a catheter for longer than 48 hours so that the patient can be assessed more efficiently for continued use of the Foley.
Challenges Metrics in the TQIP report change Familiarity with the Quintiles new drilling feature Tedious and labor intensive to drill into the patients. Requires time and resources. Remember to go back and clean your data if there were data errors. VAP, AKI, Unplanned Return to ICU, DVT
Conclusions ACS TQIP provides trauma centers with the ability to benchmark the quality of their care. It is important to investigate your data and drill down for trends that can be improved through evidence-based practice change. A robust quality monitoring program provides real-time and retrospective data that can be used to evaluate patient risk profiles. Evaluating the impacts of corrective action plans is vital to sustainment of clinical practice change. You can follow these same steps outlined to identify the areas in which you are exceling.
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