Assessment of the Quality of Chest Compressions Performed by Health-Care Workers Under Simulated Conditions

Aim of the study: to investigate chest compression parameters by city hospital staff under simulated conditions with and without the use of a sensor device for quality control of chest compressions.

Materials and Methods. The study was conducted in Moscow's multidisciplinary hospitals. The study included 359 medical staff members. The participants were divided into 4 groups: physicians (n=97) and nurses (n=82) from intensive care units (ICU) and physicians (n=92) and nurses (n=88) from specialized departments. Participants performed 2 minutes of chest compressions without a chest compressions quality control (CCQC) sensor, followed by 2 minutes of chest compressions using a defibrillator sensor with audiovisual prompts from the device turned on. The percentage of target compressions, rate and depth of compressions were analyzed.

Results. Compression parameters in the group of ICU doctors were outside the reference range (% target compression — 0.5 (0.0; 14.5)%, rate 124.1±17.8 per minute, depth 5.6±1.1 cm), in the group of ICU nurses, the percentage of target compressions was 0.0 (0.0; 3.5)%, rate — 123.6±23.7 per minute, depth — 5.3±1.2 cm, in the group of specialist doctors the percentage of target compressions was 0.0 (0.0; 1.2) %, rate — 123.8±23.2 per minute, depth — 5.8±1.2 cm, in specialized nurses group the percentage of target compressions was 0.0 (0.0; 6.1)%, rate — 119.7±29.5 per minute, depth — 5.6±1.2 cm. There was a significant improvement in compression performance in all groups when the sensor device was used: in ICU physicians the percentage of target compressions was 81.6 (64.80; 87.90)%, rate — 124.1±17.8 per minute, depth — 5.5±0.2 cm; in ICU nurses the percentage of target compressions was 69.1 (47.4; 80.6), rate — 123.6±23.7 per minute, depth — 5.3±0.3 cm, in specialist doctors the percentage of target compressions was 69.30 (50.50; 78.70), rate — 123.8±23.2 per minute, depth — 5.4±0.3 cm, in specialized nurses the percentage of target compressions reached 63.70 (42.90; 75.80), rate — 119.7±29.5 per minute, depth — 5.4±0.3 cm. There were no differences in analysed compression parameters between staff in different departments or positions.

Conclusion. Compression parameters (percentage of target compressions, rate, depth) were not influenced by the department where the staff member worked and the position held (doctor or nurse). The use of a compression quality sensor device has improved compression parameters by reducing rate and normalizing depth. The use of the sensor does not increase the percentage of target compressions to the maximum values, indicating the need for training by an instructor.

1. Andersen L.W., Holmberg M.J., Berg K.M., Donnino M.W., Granfeldt A. In-Hospital Cardiac Arrest: A Review. JAMA. 2019; 321 (12): 1200–1210. DOI: 10.1001/jama.2019.1696

2. Nassar B.S., Kerber R. Improving CPR Performance. Chest. 2017; 152 (5): 1061-1069. DOI: 10.1016/j.chest.2017.04.178

3. Rohlin O., Taeri T., Netzereab S., Ullemark E., Djärv T. Duration of CPR and impact on 30-day survival after ROSC for in-hospital cardiac arrest-A Swedish cohort study. Resuscitation. 2018; 132: 1–5. DOI: 10.1016/j.resuscitation.2018.08.017

4. Pessach I.M., Paret G. Pediatric In-Hospital Cardiac Arrest-Can We Do Better? Pediatr Crit Care Med. 2019; 20 (3): 293–294. DOI: 10.1097/PCC.0000000000001856

5. Panchal A.R., Berg K.M., Hirsch K.G., Kudenchuk P.J., Del Rios M., Cabañas J.G., Link M.S., Kurz M.C., Chan P.S., Morley P.T., Hazinski M.F., Donnino M.W. 2019 American Heart Association Focused Update on Advanced Cardiovascular Life Support: Use of Advanced Airways, Vasopressors, and Extracorporeal Cardiopulmonary Resuscitation During Cardiac Arrest: An Update to the American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2019; 140 (24): 881–894. DOI: 10.1161/CIR.0000000000000732

6. Myat A., Song K.J., Rea T. Out-of-hospital cardiac arrest: current concepts. Lancet. 2018; 391 (10124): 970–979. DOI: 10.1016/S0140-6736(18)30472-0

7. Duval S, Pepe P.E., Aufderheide T.P., Goodloe J.M., Debaty G., Labarère J., Sugiyama A., Yannopoulos D. Optimal Combination of Compression Rate and Depth During Cardiopulmonary Resuscitation for Functionally Favorable Survival. JAMA Cardiol. 2019; 4 (9): 900–908. DOI: 10.1001/jamacardio.2019.2717

8. Yannopoulos D., McKnite S., Aufderheide T.P., Sigurdsson G., Pirrallo R.G., Benditt D., Lurie K.G. Effects of incomplete chest wall decompression during cardiopulmonary resuscitation on coronary and cerebral perfusion pressures in a porcine model of cardiac arrest. Resuscitation. 2005; 64 (3): 363–372. DOI: 10.1016/j.resuscitation.2004.10.009

9. Oermann M.H., Krusmark M.A., Kardong-Edgren S., Jastrzembski T.S., Gluck K.A. Training interval in cardiopulmonary resuscitation. PLoS One. 2020; 15 (1): e0226786. DOI: 10.1371/journal.pone.0226786

10. Riggs M., Franklin R., Saylany L. Associations between cardiopulmonary resuscitation (CPR) knowledge, self-efficacy, training history and willingness to perform CPR and CPR psychomotor skills: A systematic review. Resuscitation. 2019; 138: 259–272. DOI: 10.1016/j.resuscitation.2019.03.019

11. Brown L.L., Lin Y., Tofil N.M., Overly F., Duff J.P., Bhanji F., Nadkarni V.M., Hunt E.A., Bragg A., Kessler D., Bank I., Cheng A. International Network for Simulation-based Pediatric Innovation, Research, Education CPR Investigators (INSPIRE). Impact of a CPR feedback device on healthcare provider workload during simulated cardiac arrest. Resuscitation. 2018; 130: 111–117. DOI: 10.1016/j.resuscitation.2018.06.035

12. Monsieurs K.G., Nolan J.P., Bossaert L.L., Greif R., Maconochie I.K., Nikolaou N.I., Perkins G.D., Soar J., Truhlář A., Wyllie J., Zideman D.A. ERC Guidelines 2015 Writing Group. European Resuscitation Council Guidelines for Resuscitation 2015: Section 1. Executive summary. Resuscitation. 2015; 95: 1-80. DOI: 10.1016/j.resuscitation.2015.07.038

13. Kuzovlev A.N., Abdusalamov S.N., Linchak R.M. Resuscitation measures in a hospital — a quality problem. Meditsinskiy alfavit. 2017; 2, 17 (314): 35–39 [In Russ.].

14. Castillo J., Gallart A., Rodríguez E., Castillo J., Gomar C. Basic life support and external defibrillation competences after instruction and at 6 months comparing face-to-face and blended training. Randomised trial. Nurse Educ Today. 2018; 65: 232–238. DOI: 10.1016/j.nedt.2018.03.008

15. Lin Y., Cheng A., Grant V.J., Currie G.R., Hecker K.G. Improving CPR quality with distributed practice and real-time feedback in pediatric healthcare providers — A randomized controlled trial. Resuscitation. 2018; 130: 6–12. DOI: 10.1016/j.resuscitation.2018.06.025

16. Liu Y., Huang Z., Li H., Zheng G., Ling Q., Tang W., Yang Z. CPR feedback/prompt device improves the quality of hands-only CPR performed in manikin by laypersons following the 2015 AHA guidelines. Am J Emerg Med. 2018; 36 (11): 1980–1985. DOI: 10.1016/j.ajem.2018.02.034

17. Wagner M., Bibl K., Hrdliczka E., Steinbauer P., Stiller M., Gröpel P., Goeral K., Salzer-Muhar U., Berger A., Schmölzer G.M., Olischar M. Effects of Feedback on Chest Compression Quality: A Randomized Simulation Study. Pediatrics. 2019; 143 (2): e20182441. DOI: 10.1542/peds.2018-2441

18. Pritchard J., Roberge J., Bacani J., Welsford M., Mondoux S. Implementation of Chest Compression Feedback Technology to Improve the Quality of Cardiopulmonary Resuscitation in the Emergency Department: A Quality Initiative Test-of-change Study. Cureus. 2019 29; 11 (8): e5523. DOI: 10.7759/cureus.5523