Transitional Care in the Emergency Department

1. Transitional Care in the Emergency Department Michael A. LaMantia, MD, MPH Center for Aging and Health Institute on Aging University of North Carolina

2. Disclosures • Work supported by: • NIA Grant # 2T32AG000272-06A2 • UNC John A. Hartford Foundation Center of Excellence in Geriatric Medicine and Training

3. Outline • Challenges of Care of the Elderly in the ED • UNC’s Efforts to Improve Care of Elderly: • Understanding our patients/understanding outcomes of their care • Coordinating Care with other Providers • Areas for Future Research

4. Transitional Care • Definition: “A set of actions designed to ensure the coordination and continuity of healthcare as patients transfer between different locations or different levels of care within the same institution.” –American Geriatrics Society (2003)

5. Transitional Care • During transitions, patients are at risk for: • Medical errors • Service duplication • Inappropriate care • Critical elements of care plan “falling though the cracks” -AGS (2003)

6. Aging: Impact on Emergency Departments Elderly patients: Are more ill at presentation Arrive by ambulance more frequently Receive more tests than younger patients Suffer from more chronic medical comorbidities Are admitted to the hospital at higher rates Experienced longer ED stays Incurred higher medical bills Return frequently to the ED after having been seen there 3/11/2014 6

7. Background • Elderly patients receive a high volume of resource intensive care in EDs1,2 • EDs are seeing more patients than ever and are frequently overcrowded • According to NHAMCS and AHA: ED utilization increased 26% between 1993-2003 and majority of EDs were at/over capacity at least 50% of time in 2003 3 • Concern exists that the aging of the baby boom generation will overtax EDs in the future • Identification of patients at risk for hospital admission or return to the ED might facilitate interventions to improve care of elderly patients and reduce overcrowding • McCusker J, Cardin S, Bellavance F, Belzile E. Return to the emergency department among elders: Patterns and predictors. Acad Emerg Med. 2000;7:249-259. • McCusker J, Verdon J. Do geriatric interventions reduce emergency department visits? A systematic review. Journals of Gerontology Series A: Biological and Medical Sciences. 2006;61:53-62. • Hunt KA, Weber EJ, Showstack JA, Colby DC, Callaham ML. Characteristics of frequent users of emergency departments. Ann Emerg Med. 2006;48:1-8.

8. Investments for the Future GrantUNC School of Medicine Improving the Health of North Carolina’s Underserved Elders Jan Busby-Whitehead, MD J. Stephen Kizer, MD Carol Giuliani, PhD, PT

9. Specific Aims • To establish and maintain a community-UNC-HCS partnership to improve care of vulnerable elders in Orange County and provide a platform for research and teaching • To improve the access to, navigation through, and transitions to and from the UNC-HCS for community-living frail elders including those in long term care facilities • To expand community-based preventive services for vulnerable elders in Orange County, through the development of a prevention clinic and balance program

10. Transitional Care of the Elderly in the Emergency Department Aims • Create a profile of elders who use the ED • Develop an understanding of reasons that: • elders seek care in the ED • are admitted to the hospital from the ED • return to the ED • Build and test interventions to streamline and improve the care of elderly patients as they transition into/out of ED

11. Predicting Admission to the Hospital or Return to the Emergency Department • Hypothesis: A set of variables can be identified among elderly ED patients that could predict admission or return to the ED • Methods: Retrospective chart review with training and validation data sets • Reviewed all charts (n=4,873) during 2007 at a single, academic ED serving a large elderly community • Chief complaint, triage score, Charlson comorbidity score, vital signs, and demographic data were collected

12. Methods (continued) • Logistic regression models were developed from the 2007 data for: • Patient admission • Patient return to the ED • These models were then applied in a blinded manner to the 2008 data to predict these two outcomes. • These predictions were then compared to the actual outcomes for these two endpoints. • Receiver Operating Characteristic (ROC) curves were developed and Area Under the Curve (AUC) calculated

13. Results • Five variables were present in final model for patient admission: • Age • Triage Score • Heart Rate • Diastolic BP • Chief complaint

14. Chief Complaint • Some chief complaints increase likelihood of admission: General Weakness: OR 2.00 (95% CI 1.4-2.8) Shortness of Breath: OR 3.27 (95% CI 2.4-4.5) Hip Injury: OR 4.70 (95% CI 2.4-9.1)

15. Chief Complaint • Some chief complaints increase likelihood of admission: General Weakness: OR 2.00 (95% CI 1.4-2.8) Shortness of Breath: OR 3.27 (95% CI 2.4-4.5) Hip Injury: OR 4.70 (95% CI 2.4-9.1) • Some chief complaints decrease likelihood of admission: Blood in urine: OR 0.47 (95% CI 0.3-0.9) Painful urination: OR 0.09 (95% CI 0.01-0.8) Head/neck laceration: OR 0.28 (95% CI 0.1-0.7)

16. ROC Curve for Admission Prediction

17. ROC Curve for Return Prediction

18. Conclusions from Initial Work in Emergency Department • Our models can provide a reasonably accurate prediction of the probability of admission of elderly patients • This might lead to use of an admission prediction tool which would enable an expedited admission process for elderly patients • We are unable to produce models that predict return to the ED for elderly patients

19. Communications Initiative • Partnership between UNC and local NH’s • Goal: To develop a bidirectional communication link between NH and ED providers • Format: • Web-based referral document for NH patients sent to ED that is incorporated into medical record • Faxing of ED notes/instructions back to facility on discharge

20. Communications Initiative • Challenges: • Nursing Home: • Staff turnover • Staff training • Computer access • Buy-in from staff and facility • “Another form” to fill out • Emergency Department: • Residents from various departments • Demands for time • “Another form” to fill out

21. Next Steps: ED Transitional Care Research • RCT of ability of admission prediction tool to affect ED length of stay • Validation of Tool elsewhere • Refinement Communications Initiative • Evaluation of Triage of Elderly Patients • Telephone Follow-up of Discharged Elderly

22. Acknowledgements • UNC Futures Group Team: • Drs. Jan Busby-Whitehead, J. Stephen Kizer, Charles Cairns, Timothy Platts-Mills, Kevin Biese, Laura Patel, Christine Khandelwal, Debbie Travers, Ellen Roberts • Cory Forbach, Brenda McCall, and Sergio Rabinovich • UNC Center for Aging and Health: • Dr. Laura Hanson • Amy Rix • UNC Institute on Aging: • Drs. Victor Marshall and Daniel Lee

23. Thank You! • Questions/Comments? • My contact information: Michael LaMantia, MD, MPH Center for Aging and Health CB 7550 Chapel Hill, NC 27599-7550 mlamanti@unch.unc.edu 919-966-5945 x 263