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IIR 12-358 – HSR&D Study

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IIR 12-358
Improving Surgical Quality: Risks and Impact of Readmission
Melanie S Morris MD
Birmingham VA Medical Center, Birmingham, AL
Birmingham, AL
Funding Period: December 2014 - March 2018

BACKGROUND/RATIONALE:
Hospital readmissions have been targeted as a hospital quality measure. Readmissions can increase both costs and resource utilization and are associated with poorer patient outcomes. While much research on readmissions has been done in the medical patient population, there has been little study of reasons for readmission in the surgical patient population. It will be important to identify which patients are at high risk for readmission after surgery and to understand whether a readmission is potentially preventable, represents a quality of care issue, or indicates failure of the care transition plan. By incorporating the contributions of patient comorbidity, self-efficacy, caregiver status, procedure complexity, and system factors on readmissions we can develop a risk prediction tool to identify those patients at highest risk.

OBJECTIVE(S):
1. Evaluate the contribution of patient, procedure, post-operative complication and system factors on readmission within 30 days of hospital discharge following surgery, and use these data to develop and validate a readmission risk prediction tool that can be used real-time, develop a classification of readmission reasons, and explore processes of care linked with readmission.
2. Assess potential patient factors not currently collected by VASQIP at discharge and determine their association with readmission.
3. Rank reasons for readmission categories developed from Aims 1 and 2 as potentially preventable and appropriateness as a measure of surgical quality.

METHODS:
A detailed analysis of surgical readmissions using VA Surgical Quality Improvement Program (VASQIP) data linked with clinical and administrative data containing information on index admission vital signs, pain scores and laboratory data will be used to develop a readmission risk prediction tool. Concurrent with these analyses, we will perform prospective data collection on patient health literacy and caregiver status along with prospective evaluation of the readmission risk prediction tool. This will allow us to characterize clinical and social determinants of readmission to further refine our risk prediction tool. Using a Delphi process, we will develop a readmission classification system that categorizes readmission reasons as potentially preventable and whether they reflect quality of surgical care.

FINDINGS/RESULTS:
Final analyses addressing Aim 1 have been completed with results published in Annals of Surgery.[1] The analytic study sample included 237,441 surgeries: 43% orthopedic, 39% general and 18% vascular. Overall 30-day unplanned readmission rate was 11.4%, differing by surgical specialty (vascular 15.4%, general 12.9%, and orthopedic 7.6%, p<0.001). The most common readmission reasons were wound complications (30.7%), GI (16.1%), bleeding (4.9%), and fluid/electrolyte (7.5%) complications. Models using information available at the time of discharge explained 10.3% of the variability in readmissions. Of these, preoperative patient-level factors contributed the most to predictive models (R² 7.0% [c-statistic 0.67]); prediction was improved by inclusion of intraoperative (R² 9.0%, c-statistic 0.69) and postoperative variables (R² 10.3%, c-statistic 0.71). Including post-discharge complications improved predictive ability, explaining 19.6% of the variation (R² 19.6%, c-statistic 0.76).

Secondary analyses examining specific contributors to readmission have been published and are currently ongoing.[2-5] In summary, within the same hospital, readmission rates for three surgical specialties were not correlated and there was little correlation between procedures within specialties. Little of the variation in readmissions was attributable to hospital or specialty level factors. These findings suggest that postoperative readmissions are mostly related to patient-level factors as opposed to hospital or specialty effects.[2] In addition, postoperative pain trajectories identify populations at risk for 30-day readmissions and emergency department visits. This relationship does not appear to be mediated by post-discharge complications. Addressing pain control expectations prior to discharge may help reduce surgical readmissions in high pain categories.[3] In secondary analyses addressing frailty, the modified Frailty Index was associated with poor surgical outcomes primarily due to impaired functional status. Efforts to further characterize and optimize potentially modifiable aspects of frailty preoperatively, specifically improving functional status, may improve perioperative outcomes including unplanned readmission.[4] Lastly, early postoperative hyperglycemia was associated with increased readmission but elevated preoperative HbA1c is not. Higher preoperative HbA1c was associated with increased postoperative glucose checks and insulin use, suggesting that heightened postoperative vigilance and a lower threshold to treat hyperglycemia may explain this finding.[5] In addition, our study team completed and published a methods paper detailing the study design in BMC Health Services Research.[6]

A Delphi panel was convened to address Aim 3. The 14 panelists rated readmission reasons over three rounds and 12 participated in the phone call. Wound-related infections, sepsis, urinary tract infections, pneumonia, hemorrhage or hematoma, anemia, ostomy complications, catheter-related bloodstream infection, acute renal failure and other fluid and electrolyte disorders and postoperative venous thromboembolism were all considered related to surgical quality by our panel of experts. Heart problems, gastrointestinal complaints, seizures, stroke, pain, injuries, and mental health were considered unrelated despite their relatively high prevalence among surgical readmissions (40%).

Data collection and follow-up in the prospective arm of the study (Aim 2) concluded in July 30, 2017 with 749 patients enrolled and an overall readmission rate of 17.0% across all sites. Data cleaning and initial reporting is complete. Preliminary analysis shows surgical readmissions are difficult to predict, but health literacy and post-acute care utilization may influence it. Many factors in the retrospective model stayed consistent with the prospective cohort. Prospectively collected data showed lower health literacy is associated with higher readmission rates and being discharged to an inpatient rehabilitation center or skilled nursing facility is associated with lower readmission rates.



IMPACT:
The products of this study will have a direct impact on patient care by informing the specifications of a real-time risk prediction tool. In developing standardized predictors and metrics of readmission rates, we will be better positioned to assess the quality of surgical care in VA and improve our tracking and reporting of surgical outcomes. In interpreting our results, we described the implications for interventions with patients and caregivers to reduce postoperative readmissions, as well as informed development of discrete readmission tracking variables for VASQIP.


PUBLICATIONS:

Journal Articles

  1. Graham LA, Mull HJ, Wagner TH, Morris MS, Rosen AK, Richman JS, Whittle J, Burns E, Copeland LA, Itani KMF, Hawn MT. Comparison of a Potential Hospital Quality Metric With Existing Metrics for Surgical Quality-Associated Readmission. JAMA Network Open. 2019 Apr 5; 2(4):e191313.
  2. Zarzour JG, Morgan DE, Callaway JP, Hawn MT, Canon CL, Koehler RE. Anti-reflux procedures: complications, radiologic findings, and surgical and gastroenterologic perspectives. Abdominal radiology (New York). 2018 Jun 1; 43(6):1308-1318.
  3. Staudenmayer KL, Hawn MT. The Hospital Readmission Reduction Program for Surgical Conditions: Impactful or Harmful?. Annals of surgery. 2018 Apr 1; 267(4):606-607.
  4. Mull HJ, Rosen AK, O'Brien WJ, McIntosh N, Legler A, Hawn MT, Itani KMF, Pizer SD. Factors Associated with Hospital Admission after Outpatient Surgery in the Veterans Health Administration. Health services research. 2018 Oct 1; 53(5):3855-3880.
  5. Jones CE, Graham LA, Morris MS, Richman JS, Hollis RH, Wahl TS, Copeland LA, Burns EA, Itani KMF, Hawn MT. Association Between Preoperative Hemoglobin A1c Levels, Postoperative Hyperglycemia, and Readmissions Following Gastrointestinal Surgery. JAMA surgery. 2017 Nov 1; 152(11):1031-1038.
  6. Triadafilopoulos G, Clarke J, Hawn M. Whole greater than the parts: integrated esophageal centers (IEC) and advanced training in esophageal diseases. Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus. 2017 Oct 1; 30(10):1-9.
  7. Bakaeen FG, Shroyer AL, Zenati MA, Badhwar V, Thourani VH, Gammie JS, Suri RM, Sabik JF, Gillinov AM, Chu D, Omer S, Hawn MT, Almassi GH, Cornwell LD, Grover FL, Rosengart TK, Graham L. Mitral valve surgery in the US Veterans Administration health system: 10-year outcomes and trends. The Journal of Thoracic and Cardiovascular Surgery. 2018 Jan 1; 155(1):105-117.e5.
  8. Wahl TS, Graham LA, Hawn MT, Richman J, Hollis RH, Jones CE, Copeland LA, Burns EA, Itani KM, Morris MS. Association of the Modified Frailty Index With 30-Day Surgical Readmission. JAMA surgery. 2017 Aug 1; 152(8):749-757.
  9. Tipirneni KE, Warram JM, Moore LS, Prince AC, de Boer E, Jani AH, Wapnir IL, Liao JC, Bouvet M, Behnke NK, Hawn MT, Poultsides GA, Vahrmeijer AL, Carroll WR, Zinn KR, Rosenthal E. Oncologic Procedures Amenable to Fluorescence-guided Surgery. Annals of surgery. 2017 Jul 1; 266(1):36-47.
  10. Wahl TS, Hawn MT. How Do We Prevent Readmissions After Major Surgery?. Advances in surgery. 2017 Sep 1; 51(1):89-100.
  11. Copeland LA, Graham LA, Richman JS, Rosen AK, Mull HJ, Burns EA, Whittle J, Itani KM, Hawn MT. A study to reduce readmissions after surgery in the Veterans Health Administration: design and methodology. BMC health services research. 2017 Mar 14; 17(1):198.
  12. Armstrong EJ, Graham L, Waldo SW, Valle JA, Maddox TM, Hawn MT. Patient and lesion-specific characteristics predict risk of major adverse cardiovascular events among patients with previous percutaneous coronary intervention undergoing noncardiac surgery. Catheterization and Cardiovascular Interventions : Official Journal of The Society For Cardiac Angiography & Interventions. 2017 Mar 1; 89(4):617-627.
  13. Armstrong EJ, Graham LA, Waldo SW, Valle JA, Maddox TM, Hawn MT. Incomplete Revascularization Is Associated With an Increased Risk for Major Adverse Cardiovascular Events Among Patients Undergoing Noncardiac Surgery. JACC. Cardiovascular interventions. 2017 Feb 27; 10(4):329-338.
  14. Mull HJ, Rivard PE, Legler A, Pizer SD, Hawn MT, Itani KMF, Rosen AK. Comparing definitions of outpatient surgery: Implications for quality measurement. American journal of surgery. 2017 Aug 1; 214(2):186-192.
  15. Valle JA, Graham L, DeRussy A, Itani K, Hawn MT, Maddox TM. Triple Antithrombotic Therapy and Outcomes in Post-PCI Patients Undergoing Non-cardiac Surgery. World Journal of Surgery. 2017 Feb 1; 41(2):423-432.
  16. Hollis RH, Graham LA, Richman JS, Morris MS, Mull HJ, Wahl TS, Burns E, Copeland LA, Telford GL, Rosen AK, Itani KF, Whittle J, Wagner TH, Hawn MT. Hospital Readmissions after Surgery: How Important Are Hospital and Specialty Factors? Journal of the American College of Surgeons. 2017 Apr 1; 224(4):515-523.
  17. Hollis RH, Holcomb CN, Valle JA, Smith BP, DeRussy AJ, Graham LA, Richman JS, Itani KM, Maddox TM, Hawn MT. Coronary angiography and failure to rescue after postoperative myocardial infarction in patients with coronary stents undergoing noncardiac surgery. American journal of surgery. 2016 Nov 1; 212(5):814-822.e1.
  18. Levine MS, Carucci LR, DiSantis DJ, Einstein DM, Hawn MT, Martin-Harris B, Katzka DA, Morgan DE, Rubesin SE, Scholz FJ, Turner MA, Wolf EL, Canon CL. Consensus Statement of Society of Abdominal Radiology Disease-Focused Panel on Barium Esophagography in Gastroesophageal Reflux Disease. AJR. American Journal of Roentgenology. 2016 Nov 1; 207(5):1009-1015.


DRA: Health Systems
DRE: Technology Development and Assessment
Keywords: none
MeSH Terms: none

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