Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014
| dc.contributor.advisor | Bruijns, Stevan Raynier | en_ZA |
| dc.contributor.author | Cohen, Kirsten Lesley | en_ZA |
| dc.date.accessioned | 2018-02-07T09:06:28Z | |
| dc.date.available | 2018-02-07T09:06:28Z | |
| dc.date.issued | 2017 | en_ZA |
| dc.description.abstract | Background: Much emphasis has been placed on Quality Measurements or Key Performance Indicators in Emergency Medicine. Internationally, KPI's are used to measure and improve quality of care, with a major emphasis on waiting times, measured as time-based KPI's. These times are related to the various stages of a patient journey through the Emergency Center. In South Africa this has not been routinely done. The Western Cape has conducted audits in recent years to measure these. This study aims to provide a snapshot of waiting times (specifically time to triage, time to doctor, time to disposition decision and time to departure from the EC) within Cape Town public sector Emergency Centres. Methods: This is a retrospective descriptive study of waiting times for all patients presenting to Emergency Centres in the Western Cape in 2013-2014, as per six monthly waiting times audits conducted by the Western Cape Department of Health. A wide variety of emergency centers were audited, from 24 hour clinics to larger acute hospital based ECs. Results: The proportional acuity difference between hospitals and CHC for the first random 100 folders were statistically no different. Arrival to triage times were universally longer than internationally accepted as safe. The mean time for all-comers across all facilities was just under an hour, the higher acuity patients were triaged significantly faster (half an hour) than the lower acuity patients (hour or more). This difference was significant for hospitals, with a non-significant trend for CHCs. At hospital ECs, green patients were triaged significantly faster than yellow patients; this was not the case at CHCs. The mean time from triage to clinician consultation for all-comers across all facilities (over two hours) was significantly longer at hospitals as compared to clinics. Time from triage to clinician consultation, per triage category, were longer than the SATS guide times, although higher acuity cases were seen faster than lower acuity cases in a stepwise fashion. Red patients waited nearly an hour on average, with no significant difference between hospitals and CHCs. Orange patients had to wait one to two hours; this was significantly longer at hospitals. The mean time from assessment and management to a disposal decision for all-comers was significantly longer at hospitals as compared to CHCs across all priorities. Green patients took a lot longer at hospital compared to CHCs. A similar pattern was seen for the disposition decision to leaving time. The mean total time was significantly longer at hospitals as compared to clinics. Orange and yellow cases stayed significantly longer at hospitals as compared to CHCs; red and green cases also stayed longer at hospitals as compared to CHCs, though this was not significant. Red cases appeared to stay the longest at CHCs. Conclusions: Patients attending CHCs and hospitals are of similar illness acuity, despite policies dictating that sicker patients should be seen at hospitals not CHC level. CHCs have limited packages of care (decision making investigations, management options and expertise), and can only manage patients to a defined level. Thus, it takes longer for patients who are moderately or very ill to be seen and sorted in a CHC than a hospital, as at a CHC they are generally referred onwards to a hospital. Their journey through the EC will then begin again, so that for sicker patients the time spent in ECs in this study is underestimated. Models need to be explored so that patients receive care at point of contact as far as possible. Since CHC-based ECs see as many patients who are as ill as those in hospitals, these should have similar resources to hospitals, so that only those requiring definite admission need to be referred onwards. Point of care testing, bedside ultrasound, appropriate medications and EM skills should all be available at facilities closest to the patients with emergency conditions. Green patients, the lowest acuity, also take longer to be seen and sorted at hospitals versus CHCs, because investigations are available that are then done as an emergency versus outpatient basis. Efficient and timely outpatient appointments would help mitigate this. | en_ZA |
| dc.identifier.apacitation | Cohen, K. L. (2017). <i>Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014</i>. (Thesis). University of Cape Town ,Faculty of Health Sciences ,Division of Emergency Medicine. Retrieved from http://hdl.handle.net/11427/27366 | en_ZA |
| dc.identifier.chicagocitation | Cohen, Kirsten Lesley. <i>"Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014."</i> Thesis., University of Cape Town ,Faculty of Health Sciences ,Division of Emergency Medicine, 2017. http://hdl.handle.net/11427/27366 | en_ZA |
| dc.identifier.citation | Cohen, K. 2017. Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Cohen, Kirsten Lesley AB - Background: Much emphasis has been placed on Quality Measurements or Key Performance Indicators in Emergency Medicine. Internationally, KPI's are used to measure and improve quality of care, with a major emphasis on waiting times, measured as time-based KPI's. These times are related to the various stages of a patient journey through the Emergency Center. In South Africa this has not been routinely done. The Western Cape has conducted audits in recent years to measure these. This study aims to provide a snapshot of waiting times (specifically time to triage, time to doctor, time to disposition decision and time to departure from the EC) within Cape Town public sector Emergency Centres. Methods: This is a retrospective descriptive study of waiting times for all patients presenting to Emergency Centres in the Western Cape in 2013-2014, as per six monthly waiting times audits conducted by the Western Cape Department of Health. A wide variety of emergency centers were audited, from 24 hour clinics to larger acute hospital based ECs. Results: The proportional acuity difference between hospitals and CHC for the first random 100 folders were statistically no different. Arrival to triage times were universally longer than internationally accepted as safe. The mean time for all-comers across all facilities was just under an hour, the higher acuity patients were triaged significantly faster (half an hour) than the lower acuity patients (hour or more). This difference was significant for hospitals, with a non-significant trend for CHCs. At hospital ECs, green patients were triaged significantly faster than yellow patients; this was not the case at CHCs. The mean time from triage to clinician consultation for all-comers across all facilities (over two hours) was significantly longer at hospitals as compared to clinics. Time from triage to clinician consultation, per triage category, were longer than the SATS guide times, although higher acuity cases were seen faster than lower acuity cases in a stepwise fashion. Red patients waited nearly an hour on average, with no significant difference between hospitals and CHCs. Orange patients had to wait one to two hours; this was significantly longer at hospitals. The mean time from assessment and management to a disposal decision for all-comers was significantly longer at hospitals as compared to CHCs across all priorities. Green patients took a lot longer at hospital compared to CHCs. A similar pattern was seen for the disposition decision to leaving time. The mean total time was significantly longer at hospitals as compared to clinics. Orange and yellow cases stayed significantly longer at hospitals as compared to CHCs; red and green cases also stayed longer at hospitals as compared to CHCs, though this was not significant. Red cases appeared to stay the longest at CHCs. Conclusions: Patients attending CHCs and hospitals are of similar illness acuity, despite policies dictating that sicker patients should be seen at hospitals not CHC level. CHCs have limited packages of care (decision making investigations, management options and expertise), and can only manage patients to a defined level. Thus, it takes longer for patients who are moderately or very ill to be seen and sorted in a CHC than a hospital, as at a CHC they are generally referred onwards to a hospital. Their journey through the EC will then begin again, so that for sicker patients the time spent in ECs in this study is underestimated. Models need to be explored so that patients receive care at point of contact as far as possible. Since CHC-based ECs see as many patients who are as ill as those in hospitals, these should have similar resources to hospitals, so that only those requiring definite admission need to be referred onwards. Point of care testing, bedside ultrasound, appropriate medications and EM skills should all be available at facilities closest to the patients with emergency conditions. Green patients, the lowest acuity, also take longer to be seen and sorted at hospitals versus CHCs, because investigations are available that are then done as an emergency versus outpatient basis. Efficient and timely outpatient appointments would help mitigate this. DA - 2017 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2017 T1 - Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014 TI - Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014 UR - http://hdl.handle.net/11427/27366 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/27366 | |
| dc.identifier.vancouvercitation | Cohen KL. Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014. [Thesis]. University of Cape Town ,Faculty of Health Sciences ,Division of Emergency Medicine, 2017 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/27366 | en_ZA |
| dc.language.iso | eng | en_ZA |
| dc.publisher.department | Division of Emergency Medicine | en_ZA |
| dc.publisher.faculty | Faculty of Health Sciences | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Emergency Medicine | en_ZA |
| dc.subject.other | Patient Safety | en_ZA |
| dc.title | Patient waiting times within public Emergency Centres in the Western Cape: describing key performance indicators with respect to waiting times within Western Cape Emergency Centres in 2013-2014 | en_ZA |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MPhil | en_ZA |
| uct.type.filetype | Text | |
| uct.type.filetype | Image | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Thesis | en_ZA |
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