Modeling Patient Flow In The Emergency Department
In collaboration with Dr. Scott Zeger, Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, we developed statistical models to characterize the different stages of emergency care. We applied a Poisson log-linear regression model to predict hourly arrivals to the emergency department (ED) based on temporal, weather and hospital characteristics. This model can be used to optimize ED resources (particularly staffing) as well as to predict demand for hospital services (i.e. inpatient beds, emergency surgeries, laboratory tests). We used a discrete-time survival analysis model to illustrate the negative impact of crowding (time variant) on ED length of stay. We used quantile regression models to characterize service completion times in the emergency department. Quantile regression models can be used to identify barriers to patient flow, begin the process of reengineering the system to reduce variability, and improve the timeliness of care provided in the emergency department.
- McCarthy ML, Zeger SL, Ding R, Aronsky D, Hoot N, Kelen GD. The Challenge of Predicting Demand for Emergency Department Services. Academic Emergency Medicine 15(4): 337-346, 2008. Schweigler LM, Desmond JS, McCarthy ML, Bukowski KJ, Ionides EL, Younger JG. Forecasting Models of Emergency Department Crowding. AEM 16(4): 301-308, 2009.
- McCarthy ML, Zeger SD, Ding R, Levin SR, Desmond JS, Lee J, Aronsky D. Crowding Delays Treatment and Lengthens Emergency Department Length of Stay, Even Among High Acuity Patients. Annals of Emergency Medicine 54(4):492-503, 2009.
- Ding R, McCarthy ML, Desmond JS, Lee JS, Aronsky D, Zeger SL. Characterizing Waiting Room Time, Treatment Time and Boarding Time in the Emergency Department Using Quantile Regression. AEM 17(8):813-823,2010.
Evaluating The Quality Of Emergency Care
Patient safety is an important dimension of quality of care. Patients who leave the emergency department before treatment is completed (either leave without being seen or leave against medical advice) are a potential safety hazard. For example, patients who leave against medical advice are more likely to return to the emergency department within 30 days of their initial visit and require hospitalization compared to patients who complete their care.
- Ding R, McCarthy ML, Li G, Kirsch TD, Jung JJ, Kelen GD. Patients Who Leave Without Being Seen: Their Characteristics and Past History of Emergency Department Use. Annals of Emergency Medicine 48 (6): 686-693, 2006.
- Ding R, Jung JJ, Kirsch TD, Levy F, McCarthy ML. Recidivism of Those Who Leave the Emergency Department Against Medical Advice. AEM 14(10): 870-876, 2007.
- Pham JC, Ho GK, Hill PM, McCarthy ML, Pronovost PJ. National Study of Patient, Visit and Hospital Characteristics Associated with Leaving an Emergency Department Without Being Seen: Predicting LWBS. AEM 16(10): 949-955, 2009.
Detecting patient safety issues in the emergency department can be challenging. One source that typically involves more serious patient injuries is malpractice claims. Malpractice claims show that diagnostic and procedural errors are the most common types in the emergency department.
- Brown T, McCarthy ML, Kelen GD, Frederick F. An Epidemiological Study of Closed Emergency Department Malpractice Claims in a National Database of Physician Malpractice Insurers. AEM 17 (5): 553-560, 2010.
- Howard J, Levy F, Patch M, Mareiniss DP, Craven CK, McCarthy ML, Epstein-Peterson ZD, Wong V, Pronovost PJ. New Legal Protections For Reporting Patient Errors Under the Patient Safety Quality Improvement Act: a Review of the Medical Literature and Analysis. Journal of Patient Safety 6(3): 147-152, 2010.
Estimating the Impact of Different Risk Factors on the Quality of Emergency Care
Crowding has a negative impact on all dimensions of the quality of emergency care. We proposed and validated a simple and feasible measure of emergency department crowding, the Occupancy Rate. We also compared different methods of measuring crowding to illustrate the advantages and disadvantages of various approaches. Daily measures of crowding will mask much of the variation in crowding that occurs within a 24-hour period. ED census at arrival demonstrated similar variation in crowding exposure as time-varying ED census. Discrete time survival analysis is a more appropriate approach for estimating the effect of crowding on an outcome.
- McCarthy ML, Aronsky D, Jones IA, Miner JR, Band RA, Baren JM, Desmond JS, Baumlin KM, Ding R, Shesser R. The Emergency Department Occupancy Rate: A Simple Measure of Emergency Department Crowding? Annals of Emergency Medicine 51(1): 15-24, 2008.
- Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, McCarthy ML, et al. The Effect of Emergency Department Crowding on Clinically-Oriented Outcomes. AEM 16(1): 1-10, 2009.
- Hwang U, McCarthy ML, Aronsky D, Asplin B, Craven C, Crane P, Epstein S, Fee C, Handel D, Pines JM, Rathlev N, Schafermeyer R, Zwemer F, Bernstein SL. Measures of Crowding in the Emergency Department: A Systematic Review. Academic Emergency Medicine 18(5):527-38, 2011.
- McCarthy ML. Ding R, Pines JM, Zeger SL. Comparison of Methods of Measuring Crowding and its Impact on Emergency Department Length of Stay. Academic Emergency Medicine 18(12): 1269-1277, 2011.
The quality of emergency care can also vary among emergency department providers. In a prospective cohort study that used ultrasound to screen for abdominal aortic aneurysms among high risk patients, we found that experienced providers were more likely to accurately visualize the entire abdominal aorta compared to less experienced ones. In a multi-center study of emergency departments receiving treatment in the fast track area, substantial variation in patient treatment times existed across the providers. At all 3 sites, provider and clinical factors explained more variation in fast track treatment time than patient, ED demand, or temporal factors.
- Hoffmann B, Bessman ES, Um P, Ding R, McCarthy ML. Successful Sonographic Visualization of the Abdominal Aorta Differs Significantly Among a Diverse Group of Credentialed Emergency Department Providers. Emergency Medicine Journal 28(6):472-6, 2011.
- McCarthy ML, Ding R, Pines JM, Terwiesch C, Sattarian M, Hilton J, Lee J, Zeger SL. Provider Variation in Fast Track Treatment Time. Medical Care 50(1):43-49,2012.
Evaluating Interventions To Improve The Quality Of Emergency Care
We have implemented and evaluated different interventions aimed at improving the quality of care and/or outcomes of emergency department patients using quasi-experimental and experimental research designs. The interventions we have assessed include: (1) evaluating the utility of diagnostic tests/treatments not routinely provided in an emergency department (e.g. ultrasound screening for abdominal aortic aneurysm or rapid C urea breath test for detecting H Pylori infection); (2) evaluating interventions aimed at improving the safety (computerized screening for intimate partner violence or ultrasound guided peripheral intravenous access) or timeliness (triage standing orders) of care delivered; and (3) improving patient outcomes such as satisfaction or medication adherence.
- McCarthy ML, Hirshon JM, Ruggles R, Docimo A, Welinsky M, Bessman E. Referral of Medically Uninsured, Emergency Department Patients to Primary Care. Academic Emergency Medicine 9(6): 639-642, 2002
- Trautman D, McCarthy ML, Miller N, Campbell J, Kelen GD. Intimate Partner Violence and Emergency Department Screening: Computerized Screening Versus Usual Care. Annals of Emergency Medicine 49(4): 526-534, 2007.
- Hoffmann B, Um P, Bessman ES, Ding R, Kelen GD, McCarthy ML. Routine screening for asymptomatic abdominal aortic aneurysm in high-risk patients is not recommended in emergency departments that are frequently crowded. AEM 16(11): 1242-1250, 2009.
- Retezar R, Bessman ES, Ding R, Zeger SL, McCarthy ML. The Effect of Diagnostic Triage Standing Orders on Emergency Department Treatment Time. Annals of Emergency Medicine 57(2), 89-99, 2011.
- McCarthy ML. Ding R, Zeger SL, Agada NO, Bessman SC, Chiang W, Kelen GD, Scheulen JJ, Bessman ES. A Randomized Controlled Trial of the Impact of Service Delivery Information on Patient Satisfaction in an ED Fast Track. Academic Emergency Medicine 18(7): 674-685, 2011.
- Pines JM, McCarthy ML. Executive Summary: Interventions to Improve Quality in the Crowded Emergency Department. Academic Emergency Medicine 18(12): 1229-1233, 2011.
- Shokoohi H. Boniface KS, McCarthy M, et al. Ultrasound-Guided Peripheral Intravenous Access Program is Associated With Marked Reduction in Central Venous Catheter Use in Noncritically Ill Emergency Department Patients. Annals of Emergency Medicine 61(2): 198-203, 2013.
- Meltzer AC, Pierce R, Cummings DA, Pines JM, May L, Smith MA, Marcotte J, McCarthy ML. Rapid C Urea Breath Test to Identify Helicobacter Pylori Infection in Emergency Department Patients with Upper Abdominal Pain. Western Journal of Emergency Medicine 14(3): 278-282, 2013.
- McCarthy ML, Ding R, Roderer NK, Steinwachs DM, Ortmann MJ et al. Does Providing Prescription Information And/Or Services Improve Medication Adherence Among Patients Discharged From The Emergency Department? A Randomized Controlled Trial. Annals of Emergency Medicine 62(3): 212-223, 2013.
- Lee J, Ding R, Zeger SL, McDermott A, Habteh-Yimer G, Chin M, Balder RS, McCarthy ML. Impact of Subsidized Health Insurance Coverage on Emergency Department Utilization by Low-Income Adults in Massachusetts. Medical Care 53(1):38-44, 2015.
- McCarthy ML, Shokoohi H, Boniface KS, Eggelton R, Lowey A, Lim K, Shesser R, Li X, Zeger SL. Ultrasonography Versus Landmark for Peripheral Intravenous Cannulation: A Randomized Controlled Trial. Annals of Emergency Medicine, Oct 13, 2015, epub ahead of print.
Measuring The Impact Of Injuries On Patient Outcomes
Impairment, functional limitations and poorer health-related quality of life are common after severe lower limb injuries. It is essential to have valid instruments, such as the Guides to the Evaluation of Permanent Impairment, the Functional Capacity Index, the Brief Symptom Inventory, and others to measure the impact of these injuries on people’s lives.
- McCarthy ML, McAndrew M, MacKenzie EJ, et al. Correlation between the Measures of Impairment According to the Modified System of the American Medical Association, and Function. Journal of Bone and Joint Surgery 80-A (7): 1034-1042, 1998.
- McCarthy ML and MacKenzie EJ. Predicting ambulatory function following lower extremity trauma using the Functional Capacity Index. Accident Analysis and Prevention 33:821 - 831, 2001.
- Bosse MJ, MacKenzie EJ, Kellam JF, Burgess AR, Webb LX, Swiontkowski MF, Sanders RW, Jones AL, McAndrew MP, Patterson BM, McCarthy ML, Travison TG, Castillo RC. An Analysis of Two-Year Outcomes of Reconstruction or Amputation of Leg-Threatening Injuries in Level I Trauma Centers. New England Journal of Medicine 347 (24): 1924-1931, 2002.
- McCarthy ML, MacKenzie EJ, Edwin E, Bosse MJ, Castillo R, Starr A, Kellam JF, Burgess AR, Webb LX, Swiontkowski MF, Sanders RW, Jones AL, McAndrew MP, Patterson BM. Psychological Distress Associated with Severe Lower Limb Injury. Journal of Bone and Joint Surgery 85-A(9): 1689 - 1697, 2003.
Many researchers have documented the neurobehavioral consequences associated with traumatic brain injury in children, but few have examined the impact of traumatic brain injury on a child’s function, role performance and emotional well-being. The Pediatric Quality of Life Inventory is a reliable and valid instrument for measuring children’s general health following traumatic brain injury.
- McCarthy ML, MacKenzie EJ, Durbin D. Children’s Health Status Instruments: Their Potential Application in the Emergency Department. Ambulatory Pediatrics 2(4): 337-344, 2002.
- Selassie AB, McCarthy ML, Ferguson PL, Tian J, Langlois JA. Risk of Death After Hospital Discharge Among a Population-Based Sample of Cases with Traumatic Brain Injury. Journal of Head Trauma and Rehabilitation 20(3): 257-269, 2005.
- McCarthy ML, MacKenzie EJ, Durbin DR, Aitken ME, Jaffe KM, Paidas CN, Slomine BS, Dorsch AM, Berk RA, Christensen JR, Ding R and the CHAT Study Group. The Pediatric Quality of Life Inventory: An Evaluation of its Reliability and Validity For Children With Traumatic Brain Injury. Archives of Physical Medicine and Rehabilitation 86(10): 1901-1909, 2005.
- McCarthy ML, MacKenzie EJ, Durbin DR, Aitken ME, Jaffe KM, Paidas CN, Slomine BS, Dorsch AM, Christensen JR, Ding R and the CHAT Study Group. Health-Related Quality of Life During The First Year After Traumatic Brain Injury. Archives of Pediatrics and Adolescent Medicine 160 (3): 252-260, 2006. Slomine BS, McCarthy ML, Ding R, MacKenzie EJ, Jaffe KM, Aitken ME, Durbin DR, Christensen JR, Dorsch AM, Paidas CN and the CHAT Study Group. Healthcare Utilization and Needs Following Traumatic Brain Injury. Pediatrics 2006, 117 (4): e663-74.
- McCarthy ML, Dikmen SS, Langlois JA, Selassie AW, Gu JK, Horner MD. Self-Reported Psychosocial Health Among Adults With Traumatic Brain Injury. Archives of Physical Medicine and Rehabilitation 87 (7): 953-961, 2006.
- McCarthy ML. Measuring Children’s Health-Related Quality of Life Following Trauma. Journal of Trauma 63 (Suppl 6): S122-129, 2007.
- Sesma HW, Slomine BS, Ding R, McCarthy ML and the CHAT Study Group. Executive Functioning in the First Year After Pediatric Traumatic Brain Injury. Pediatrics 121(6): 1686-95, 2008.
- Aitken ME, McCarthy ML, Slomine B, et al. Family Burden Following Traumatic Brain Injury in Children. Pediatrics 123(1): 199-206, 2009.