Probabilistic Linkage of Computerized Ambulance and Inpatient Hospital Discharge Records: A Potential Tool for Evaluation of Emergency Medical Services

J.Michael Dean; Donald D. Vernon; Larry Cook; Patricia Nechodom; James Reading; Anthony Suruda

doi:10.1067/mem.2001.115214

Pediatric Submersions: Prehospital Predictors of Outcome

PEDIATRICS ◽

10.1542/peds.90.6.909 ◽

1992 ◽

Vol 90 (6) ◽

pp. 909-913

Author(s):

Linda Quan ◽

Dennis Kinder

Keyword(s):

Cardiac Arrest ◽

Emergency Medical Services ◽

Hospital Discharge ◽

Life Support ◽

Medical Services ◽

Outcome Predictors ◽

King County ◽

Good Outcome ◽

Neurologic Impairment ◽

Emergency Medical

This retrospective cohort study was conducted to test prehospital prognostic indicators in pediatric submersion victims. The authors studied all less than 20 years old victims submerged in the non-icy waters of King County, WA who were treated by Seattle or King County Emergency Medical Services between 1985 and 1989 and were hospitalized or died. Seventy-seven victims were identified from emergency medical services incident logs, hospital discharge records, and medical examiner's registries. Outcome predictors were correlated with the victim's condition at hospital discharge. Of 29 victims in cardiac arrest, 13 had return of spontaneous circulation following field resuscitation. Of these, 6 (21%) survived, with mild (n = 2) and severe (n = 4) neurologic impairment at hospital discharge. The best outcome predictors were obtained in the field. These were, for death or severe neurologic impairment, submersion durations >10 minutes (6/6) and resuscitation durations >25 minutes (17/17), and for good outcome, sinus rhythm (37/37), reactive pupils (43/43), and neurologic responsiveness (40/40) at the scene. Field-determined factors were reproducibly good outcome predictors. Aggressive emergency medical services may save the lives of pediatric victims in cardiac arrest following short submersion durations. The data support pronouncing dead in the field those pediatric victims of non-icy submersions who do not respond to advanced life support within 25 minutes.

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124 Probabilistic Linkage of Statewide Emergency Medical Services Data to Hospital Outcomes Data in Out-of-Hospital Cardiac Arrest

Annals of Emergency Medicine ◽

10.1016/j.annemergmed.2012.06.101 ◽

2012 ◽

Vol 60 (4) ◽

pp. S45

Author(s):

B.E. Mumma ◽

D.B. Diercks ◽

B. Danilesen ◽

J.F. Holmes

Keyword(s):

Cardiac Arrest ◽

Emergency Medical Services ◽

Medical Services ◽

Hospital Outcomes ◽

Emergency Medical ◽

Probabilistic Linkage ◽

Hospital Cardiac Arrest

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Abstract 291: Cardiopulmonary Resuscitation Prior to Arrival of Emergency Medical Services in Arizona Extended Care Facilities

Circulation ◽

10.1161/circ.140.suppl_2.291 ◽

2019 ◽

Vol 140 (Suppl_2) ◽

Author(s):

Steven A Maher ◽

Amber D Rice ◽

Joshua B Gaither ◽

Chengcheng Hu ◽

Margaret Mullins ◽

...

Keyword(s):

Cardiopulmonary Resuscitation ◽

Emergency Medical Services ◽

Hospital Discharge ◽

Neurologic Outcome ◽

Medical Services ◽

Emergency Medical ◽

Extended Care ◽

Significant Difference ◽

Care Facilities ◽

Bystander Cpr

Background: Extended care facilities (ECFs) house unique patient populations with increased risk of out of hospital cardiac arrest (OHCA) and with unique, generally medically trained first responders initiating care prior to arrival of emergency medical services (EMS). However, little is known about bystander cardiopulmonary resuscitation (CPR) and resuscitation outcomes in this population. Our aim is to assess rate of CPR delivery prior to EMS arrival in cases of OHCA among residents ECFs across the state of Arizona. Methods: Cases of OHCA between 2016-2018, cared for by participating Arizona EMS agencies, were included if OHCA occurred at an ECF, age 18+, and was of presumed cardiac etiology. Association between survival status at discharge and bystander CPR was examined first by Chi-squared test then by logistic regression, which adjusted for important risk factors and potential confounders including: age, gender, witnessed arrest, shockable initial rhythm, and return of spontaneous circulation (ROSC) in EMS care. Results: There were 1,046 cases included in this study after excluding 32 cases with DNR and 11 with unknown bystander CPR status. Median patient age was 74 (interquartile range 64, 83). The overall rate of CPR prior to EMS arrival was 78.4% (95% CI, 75.8%, 80.9%). Survival to hospital discharge and survival with favorable neurologic outcome were not different between nursing home patients who received CPR prior to EMS arrival and those who did not [6.2% vs. 4.4% (p = 0.34) and 3.1% vs. 1.8% (p = 0.29)]. There was no statistically significant difference in the adjusted analysis. Conclusions: In this study population CPR was commonly delivered prior to EMS arrival. However, delivery of CPR prior to EMS arrival was not associated with survival to hospital discharge or favorable neurologic outcome. The lack of positive association between CPR prior to arrival and survival to hospital discharge may be related to comorbid factors present in ECF patients or differences in the time between collapse and initiation of CPR. Further study is needed to identify factors that might improve survival in this unique population.

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Abstract 2721: Probabilistic Matching of Computerized Emergency Medical Services (EMS) records and Emergency Department and Patient Discharge Data: a Novel Approach to Evaluation of Prehospital Stroke Care

Stroke ◽

10.1161/str.43.suppl_1.a2721 ◽

2012 ◽

Vol 43 (suppl_1) ◽

Author(s):

Prasanthi Govindarajan ◽

Larry Cook ◽

David Ghilarducci ◽

S C Johnston

Keyword(s):

Emergency Department ◽

Emergency Medical Services ◽

Patient Discharge ◽

Stroke Care ◽

Medical Services ◽

Matched Pairs ◽

Match Probability ◽

Discharge Data ◽

Emergency Medical ◽

Probabilistic Linkage

Background and Purpose: Emergency Medical Services is an important element of acute stroke care. However, evaluation of prehospital stroke care is limited by lack of exchange of patient outcome data between hospitals and emergency medical services (EMS) agencies. In this study, we describe and demonstrate the feasibility of linking county wide patient level ambulance data with emergency department (EDD) and patient discharge data (PDD) using a probabilistic matching algorithm. Methods: Probabilistic linkage was used to match county-wide ambulance data from 2005-2007 to hospital (EDD and PDD) records with a final ICD -9 diagnosis of stroke (430-436). The linkage model was based on the patient’s transport/admission date, date of birth, race, sex, county of residence, and destination hospital. Probabilistic linkage was performed using LinkSolv version 8.29746 which calculates the probability that a pair of records is a true match based on agreement/disagreement patterns of the linkage variables. Pairs of records with a match probability of 0.8 or higher were considered true matches. All other pairs were false matches and rejected. Results: During 2005 - 2007 there were 310,731 patients transported to a facility in county and 34,785 hospital records with a diagnosis of stroke. Using the linkage algorithm we identified 11,473 (33%) matches with EMS records. Linkage rates increased each year with 30%, 34%, and 36% of hospital patients matching EMS record for 2005, 2006, and 2007 respectively. The median match probability was 0.993 and the IQR was 0.974 to 0.9996. By taking the compliment of the match probability we estimate our linked sample to include 255 (2%) false matches. Date of treatment/admission and the patient’s sex were observed to be the most reliable, disagreeing on less than one percent (1%) of all matched pairs. Patient’s zip code was the least reliable, disagreeing on one third of matched pairs. Conclusions: Our study demonstrates that probabilistic matching can be used to create a comprehensive patient care record which in turn can provide opportunities for researchers to study different phases of stroke care.

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Abstract 89: Accuracy and Clinical Implications of Cincinnati Pre-hospital Stroke Scale and Los Angeles Pre-hospital Stroke Scale use by Emergency Medical Services

Stroke ◽

10.1161/str.46.suppl_1.89 ◽

2015 ◽

Vol 46 (suppl_1) ◽

Author(s):

Tushar Trivedi ◽

Khosrow Heidari ◽

Anwar Merchant ◽

Ed Jauch ◽

Swamy Venkatesh ◽

...

Keyword(s):

Ischemic Stroke ◽

Los Angeles ◽

Emergency Medical Services ◽

Hospital Discharge ◽

Predictive Value ◽

False Negative ◽

True Positive ◽

Emergency Medical ◽

Hospital Discharge Records ◽

Iv Tpa

Background: Cincinnati Pre-hospital Stroke Scale (CPSS) and Los Angeles Pre-hospital Stroke Scale (LAPSS) are widely used by emergency medical services (EMS) to screen potential ischemic stroke patients. We performed a population based state-wide study to evaluate the accuracy of CPSS and LAPSS in identifying stroke cases and investigate their impact on ischemic stroke treatment. Methods: A statewide EMS database was created by linking South Carolina’s statewide Emergency Department (ED) and hospital discharge records for the calendar years 2010-2012. The EMS data were obtained from the Division of EMS and Trauma at Department of Health Environmental Control and linked to hospitalization records at Office of Research and Statistics. Results from the EMS use of CPSS and LAPSS were compared with hospital discharge diagnoses for stroke. For both scales, we calculated Sensitivity, Specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV). Additionally we evaluated the impact of identification of stroke during EMS transportation by CPSS/LAPSS on treatment of ischemic stroke with intravenous tissue plasminogen activator (IV-tPA). Results: Of all the EMS transported cases between January 2010 and December 2012, use of CPSS or LAPSS was recorded for 101,442 cases. Among the cases where the use of CPSS/LAPSS stroke scale was recorded, 6,757 cases had a diagnosis of ischemic stroke on hospital discharge records. CPSS demonstrated sensitivity of 59%, and specificity of 96%. Sensitivity and specificity for LAPSS were 26% and 84%, respectively. PPV and NPV for CPSS were 45% and 98%, and for LAPSS were 27% and 83%, respectively. Rates of IV-tPA administration were approximately five times higher for those correctly identified by CPSS (18.3% for true positive vs. 3.5% for false negative, P<0.01), and about two higher for those correctly identified by LAPSS (33.3% for true positive vs. 14.9% for false negative, P<0.01). Conclusion: Early identification of potential stroke cases using CPSS/LAPSS can have a significant impact on treatment of ischemic stroke with IV-tPA. We report a modest accuracy of CPSS and LAPSS in correctly identifying stroke cases in the field, with CPSS leading to a better rate of IV-tPA use compared with LAPSS.

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