Prehospital Emergency Care
ISSN: 1090-3127 (Print) 1545-0066 (Online) Journal homepage: http://www.tandfonline.com/loi/ipec20
Epidemiology of Emergency Medical Service Responses to Older People Who Have Fallen: A Prospective Cohort Study Paul M. Simpson MScM(ClinEpi), BHSc, BEd, Jason C. Bendall PhD, MBBS, MM(ClinEpi), Anne Tiedemann PhD, BSc, Stephen R. Lord PhD, DSc, MA, BSc & Jacqueline C. T. Close MD, MBBS To cite this article: Paul M. Simpson MScM(ClinEpi), BHSc, BEd, Jason C. Bendall PhD, MBBS, MM(ClinEpi), Anne Tiedemann PhD, BSc, Stephen R. Lord PhD, DSc, MA, BSc & Jacqueline C. T. Close MD, MBBS (2014) Epidemiology of Emergency Medical Service Responses to Older People Who Have Fallen: A Prospective Cohort Study, Prehospital Emergency Care, 18:2, 185-194 To link to this article: http://dx.doi.org/10.3109/10903127.2013.856504
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Published online: 08 Jan 2014.
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Article views: 242
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Citing articles: 2 View citing articles
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ipec20 Download by: [Florida Atlantic University]
Date: 05 November 2015, At: 17:03
EPIDEMIOLOGY OF EMERGENCY MEDICAL SERVICE RESPONSES TO OLDER PEOPLE WHO HAVE FALLEN: A PROSPECTIVE COHORT STUDY Paul M. Simpson, MScM(ClinEpi), BHSc, BEd, Jason C. Bendall, PhD, MBBS, MM(ClinEpi), Anne Tiedemann, PhD, BSc, Stephen R. Lord, PhD, DSc, MA, BSc, Jacqueline C. T. Close, MD, MBBS
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
ABSTRACT
248 (15%) had called within the past month. The most common patient-reported reasons for falling were loss of balance (30%) and “simple trips” (25%). New injury and/or pain was documented for 1,172 (73%) of patients, and 656 (41%) presented with “abnormal” physiology; only 238 (15%) presented with no new injury/pain and normal physiology. The nontransport rate was 28%. Conclusion. In this population, ambulance services appear to provide timely responses to older people who have fallen, and “long-lies” are relatively uncommon. More than one-quarter of patients were not transported to an emergency department, and repeat use of ambulance resources appears to be common. Opportunities exist to explore alternate pathways and models of care that maximize outcomes for nontransport patients as well as improving operational efficiency of the ambulance service. Key words: ambulance; emergencies; aged; accidental falls; emergency medical services
Objectives. To describe the characteristics of older people who fall and call an emergency ambulance, and the operational and clinical impact of the ambulance responses they receive. Methods. A prospective cohort study of people aged ≥65 who had fallen and called for an ambulance was conducted between October 1, 2010 and June 30, 2011. Fall-related data were collected using a project-specific data collection tool. These data were then linked to routinely collected ambulance service clinical records and dispatch data, providing a sequential description of fall-related cases from time of ambulance dispatch through to the end of the prehospital episode of care. Results. There were 1,610 cases eligible for analysis. The median response time was 15 minutes (IQR 10–24) and “long-lies” (>60 minutes on the ground) occurred in 13% of cases. Patients were predominantly female (61%) and community dwelling (82%). Forty-four percent had never previously called an ambulance for a fall, whereas
PREHOSPITAL EMERGENCY CARE 2014;18:185–194
INTRODUCTION Falls experienced by the elderly are among the most common events to which emergency medical services are dispatched, comprising between 5 and 10% of annual emergency workload.1,2 Faced with an increasingly aging population, falls experienced by the elderly are likely to consume an increasing proportion of ambulance resources over the coming decade.3 This population of patients presents substantial operational and clinical challenges for ambulance services. While the traditional function of ambulance paramedics has been to transport patients to an emergency department (ED) for medical assessment, there is no clear evidence that doing so improves health outcomes or reduces risk of further falls for older people who have fallen.4–6 On the other hand, older fallers not transported to an ED appear to be a vulnerable population at risk of future falls, suboptimal health outcomes, and ambulance reattendance.7–9 Consequently, there is a real need to develop clinical strategies and innovative models of care aimed at optimizing the prehospital management of older fallers by paramedics. However, the current evidence to inform such development is lacking in proportion to the level of demand and complexity associated with these incidents, partially due to the inability of routinely collected ambulance data to capture detailed fall-specific information.10
Received April 2013 from University of Western Sydney, Sydney, Australia, and the Ambulance Service of New South Wales, Sydney, Australia (PMS), School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia (PMS, SRL), Sydney Medical School, The University of Sydney, Sydney, Australia and University of Sydney, Sydney, Australia (AT), Neuroscience Research Australia, Sydney, Australia (SRL, JCTC), and Prince of Wales Clinical School, University of New South Wales, Sydney, Australia (JCTC). Revision received September 6, 2013; accepted for publication September 9, 2013. This project was commissioned by the NSW Clinical Excellence Commission following a funding allocation from the Centre for Health Advancement in the NSW Ministry of Health, Australia. The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper. The authors would like to acknowledge Peter Kennedy, Lorraine Lovitt, and Rebecca Mitchell of the NSW Clinical Excellence Commission (CEC) Ambulance Falls Advisory Committee, and the paramedics from Ambulance Service of New South Wales for their important contributions to the study and commitment to out-ofhospital research. This study was presented as a poster presentation at the 2012 National Association of EMS Physicians Scientific Assembly, January 9–12, 2012, Tucson, AZ, USA. Address correspondence to Mr. Paul Simpson, University of Western Sydney, Locked Bag 1797, Penrith NSW 2751, Australia. e-mail: [email protected] doi: 10.3109/10903127.2013.856504
185
186
PREHOSPITAL EMERGENCY CARE
With this context in mind, the aim of this prospective descriptive study was to describe 1) the characteristics of older people who fall and call an ambulance, and 2) the characteristics of the falls and the ambulance response they receive.
METHODS Study Design
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
This study was a prospective, observational cohort study in which fall-specific information collected using a tailored data-collection tool was combined with ambulance clinical records (ACR) and computer-aided dispatch (CAD) data.
Study Setting The study was conducted in New South Wales (NSW), Australia. The Ambulance Service of New South Wales (ASNSW) is a statewide government ambulance service that responds to approximately 1,120,000 incidents annually, of which 825,280 are emergency cases.11 The ambulance service provides coverage across a geographic area of approximately 802,000 km2 encompassing both metropolitan and rural/remote regions, and has a frontline clinical workforce of almost 3,000 operational paramedics. The paramedic workforce consists of four clinical levels: paramedic trainee (PT) (first year of training), paramedic intern (PI) (second/third year of training), qualified paramedics (QP) (completed 3 years of core training to advanced life support level), and paramedic specialist (specialist training as an intensive care paramedic (ICP) or extended care paramedic (ECP)). Paramedics operate under a protocol-based system with a high level of autonomy and with little on-scene medical consultation. Paramedic management of cases involving falls experienced by older people is guided by a “falls in the elderly” protocol (Supplement 1, available online), which provides a decision-assistance algorithm that supports paramedics in deciding how best to manage an older faller. Paramedics can recommend nontransport where strictly defined criteria are met following detailed history taking and patient assessment, although any patient requesting transport following discussion must be transported to an ED. Dispatch of ambulance resources is managed by a computer-aided dispatch (CAD) system, in which incoming calls are categorised and prioritized using the Medical Priority Dispatch System (MPDS) and ProQA software (version 11.3) (Priority Dispatch, Salt Lake City, Utah, USA). Incidents are allocated a response priority of 1–9, with priority 1 and 2 calls constituting “emergency” responses. Priority 1 cases involve urgent, “lights and sirens” responses, while priority 2 cases receive nonurgent responses within locally defined time frames.
APRIL/JUNE 2014
VOLUME 18 / NUMBER 2
Study Population The study population comprised people aged 65 years and older who received an emergency response and were confirmed to have fallen by paramedics at the scene. A fall was defined as “an event which results in a person coming to rest inadvertently on the ground, floor or lower level with or without loss of consciousness and other than as a consequence of sudden onset of paralysis, epileptic seizure or overwhelming external force.”12 An emergency ambulance response was defined as any response initiated through the emergency call system that was allocated a response priority of 1 (urgent) or 2 (nonurgent). Incidents allocated a response priority of 3–9 (cases that do not originate via the emergency call system including routine transports, operational standbys, medical appointments, and interhospital transfers) were excluded.
Data Sources A fall-specific data collection tool was designed prior to the commencement of the study by an advisory group consisting of experts in the field of falls and balance, geriatrics, and prehospital care, using a consensus approach. This was necessary due to the fact that the routinely completed ambulance clinical record does not systematically capture fall-specific data at a detailed level. The paper-based form collected fallspecific information across 24 variables of interest detailing patient demographics, including co-morbidity and medication history, environment, previous falls and ambulance usage, fall circumstances, paramedicdiagnosed injury, and prehospital outcomes. In order to ensure its suitability for use in the field, the tool was piloted for one month prior to the commencement of data collection, with results assessed by the research team, and modifications made where required to promote consistency among data collectors. Data from this tool were merged with routinely collected clinical and dispatch information from the PCR and CAD databases.
Data Collection Data were collected between October 1, 2010 and June 30, 2011. As participation in research is noncompulsory in the Ambulance Service of NSW, a statewide network of paramedics was established to collect data. An expression of interest was released to all paramedics in ASNSW during the 3 months preceding the data collection phase inviting them to participate in the study. By the commencement of the data collection period, 384 paramedics had agreed to participate, representing 13% of frontline operational paramedics. Paramedics received education with regard to the broad objectives and rationale of the study, but the specific research
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
P. M. Simpson et al.
187
EMS RESPONSES TO OLDER FALLERS
questions upon which analyses would be based were withheld so as to reduce the potential of paramedics changing their clinical practice during the study period. Education was also provided detailing how to use the tool and the data collection requirements, including definitions of variables to increase consistency in completion. Identification of eligible patients was determined by paramedics on scene, not during the dispatch process. After arriving on scene and determining the patient met the eligibility criteria, paramedics provided the standard level of acute care according to normal clinical practice and then obtained the additional information required for the purposes of the study. The completed fall-specific data form was then sent to the research team where it was scanned and entered into an electronic database using automated data entry software (Cardiff Teleform, Vista, CA).
Data Analysis The fall-specific data were deterministically matched to the routinely collected clinical record and dispatch data using a unique clinical record number. Analysis was undertaken using SAS 9.2 (SAS Institute, Cary, NC, USA). Descriptive statistics were generated, using mean and standard deviation (SD) and median with interquartile range (IQR) for normal and non-normally distributed data, respectively. Differences in normally distributed independent continuous variables were assessed using Student’s t-tests, and in non-normally distributed independent continuous variables using the Wilcoxon rank sum tests. Differences in proportions for dichotomous nominal variables were analyzed using chi-squared (χ 2 ) statistics. For independent ordinal group variables such as age group, the Mantel-Haenszel test for trend was used to compare more than two independent proportions. Differences for all analyses were considered statistically significant at p < 0.05. To enable categorical analyses of continuous variables, time of day was categorized into day (0700–1859) and night (1900–0659); response priority into urgent and nonurgent; and age into 3 groups (65–74; 75–84; 85+). Physiological status, based on vital signs, was categorized using established physiological parameters within this health system,13 creating “normal” and “abnormal” categories Table 1). Time spent on the floor (“long-lies”) was estimated by the patient or a witness if present.
Ethical Approval and Consent A waiver of consent was granted by the Human Research Ethics Committee (HREC). Ethical approval was granted by the Sydney South West Area Health Service HREC (Protocol No. X10-0152 & HREC/10/RPAH/282).
TABLE 1. Criteria for classification of physiological status (“normal” versus “abnormal”)a Vital sign
Heart rate (beats/min) Respiratory rate (breaths/min) Systolic blood pressure (mmHg) SpO2 (%) Level of consciousness (AVPU)
Normal
Abnormal
>50 and 10 and
ISSN: 1090-3127 (Print) 1545-0066 (Online) Journal homepage: http://www.tandfonline.com/loi/ipec20
Epidemiology of Emergency Medical Service Responses to Older People Who Have Fallen: A Prospective Cohort Study Paul M. Simpson MScM(ClinEpi), BHSc, BEd, Jason C. Bendall PhD, MBBS, MM(ClinEpi), Anne Tiedemann PhD, BSc, Stephen R. Lord PhD, DSc, MA, BSc & Jacqueline C. T. Close MD, MBBS To cite this article: Paul M. Simpson MScM(ClinEpi), BHSc, BEd, Jason C. Bendall PhD, MBBS, MM(ClinEpi), Anne Tiedemann PhD, BSc, Stephen R. Lord PhD, DSc, MA, BSc & Jacqueline C. T. Close MD, MBBS (2014) Epidemiology of Emergency Medical Service Responses to Older People Who Have Fallen: A Prospective Cohort Study, Prehospital Emergency Care, 18:2, 185-194 To link to this article: http://dx.doi.org/10.3109/10903127.2013.856504
View supplementary material
Published online: 08 Jan 2014.
Submit your article to this journal
Article views: 242
View related articles
View Crossmark data
Citing articles: 2 View citing articles
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ipec20 Download by: [Florida Atlantic University]
Date: 05 November 2015, At: 17:03
EPIDEMIOLOGY OF EMERGENCY MEDICAL SERVICE RESPONSES TO OLDER PEOPLE WHO HAVE FALLEN: A PROSPECTIVE COHORT STUDY Paul M. Simpson, MScM(ClinEpi), BHSc, BEd, Jason C. Bendall, PhD, MBBS, MM(ClinEpi), Anne Tiedemann, PhD, BSc, Stephen R. Lord, PhD, DSc, MA, BSc, Jacqueline C. T. Close, MD, MBBS
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
ABSTRACT
248 (15%) had called within the past month. The most common patient-reported reasons for falling were loss of balance (30%) and “simple trips” (25%). New injury and/or pain was documented for 1,172 (73%) of patients, and 656 (41%) presented with “abnormal” physiology; only 238 (15%) presented with no new injury/pain and normal physiology. The nontransport rate was 28%. Conclusion. In this population, ambulance services appear to provide timely responses to older people who have fallen, and “long-lies” are relatively uncommon. More than one-quarter of patients were not transported to an emergency department, and repeat use of ambulance resources appears to be common. Opportunities exist to explore alternate pathways and models of care that maximize outcomes for nontransport patients as well as improving operational efficiency of the ambulance service. Key words: ambulance; emergencies; aged; accidental falls; emergency medical services
Objectives. To describe the characteristics of older people who fall and call an emergency ambulance, and the operational and clinical impact of the ambulance responses they receive. Methods. A prospective cohort study of people aged ≥65 who had fallen and called for an ambulance was conducted between October 1, 2010 and June 30, 2011. Fall-related data were collected using a project-specific data collection tool. These data were then linked to routinely collected ambulance service clinical records and dispatch data, providing a sequential description of fall-related cases from time of ambulance dispatch through to the end of the prehospital episode of care. Results. There were 1,610 cases eligible for analysis. The median response time was 15 minutes (IQR 10–24) and “long-lies” (>60 minutes on the ground) occurred in 13% of cases. Patients were predominantly female (61%) and community dwelling (82%). Forty-four percent had never previously called an ambulance for a fall, whereas
PREHOSPITAL EMERGENCY CARE 2014;18:185–194
INTRODUCTION Falls experienced by the elderly are among the most common events to which emergency medical services are dispatched, comprising between 5 and 10% of annual emergency workload.1,2 Faced with an increasingly aging population, falls experienced by the elderly are likely to consume an increasing proportion of ambulance resources over the coming decade.3 This population of patients presents substantial operational and clinical challenges for ambulance services. While the traditional function of ambulance paramedics has been to transport patients to an emergency department (ED) for medical assessment, there is no clear evidence that doing so improves health outcomes or reduces risk of further falls for older people who have fallen.4–6 On the other hand, older fallers not transported to an ED appear to be a vulnerable population at risk of future falls, suboptimal health outcomes, and ambulance reattendance.7–9 Consequently, there is a real need to develop clinical strategies and innovative models of care aimed at optimizing the prehospital management of older fallers by paramedics. However, the current evidence to inform such development is lacking in proportion to the level of demand and complexity associated with these incidents, partially due to the inability of routinely collected ambulance data to capture detailed fall-specific information.10
Received April 2013 from University of Western Sydney, Sydney, Australia, and the Ambulance Service of New South Wales, Sydney, Australia (PMS), School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia (PMS, SRL), Sydney Medical School, The University of Sydney, Sydney, Australia and University of Sydney, Sydney, Australia (AT), Neuroscience Research Australia, Sydney, Australia (SRL, JCTC), and Prince of Wales Clinical School, University of New South Wales, Sydney, Australia (JCTC). Revision received September 6, 2013; accepted for publication September 9, 2013. This project was commissioned by the NSW Clinical Excellence Commission following a funding allocation from the Centre for Health Advancement in the NSW Ministry of Health, Australia. The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper. The authors would like to acknowledge Peter Kennedy, Lorraine Lovitt, and Rebecca Mitchell of the NSW Clinical Excellence Commission (CEC) Ambulance Falls Advisory Committee, and the paramedics from Ambulance Service of New South Wales for their important contributions to the study and commitment to out-ofhospital research. This study was presented as a poster presentation at the 2012 National Association of EMS Physicians Scientific Assembly, January 9–12, 2012, Tucson, AZ, USA. Address correspondence to Mr. Paul Simpson, University of Western Sydney, Locked Bag 1797, Penrith NSW 2751, Australia. e-mail: [email protected] doi: 10.3109/10903127.2013.856504
185
186
PREHOSPITAL EMERGENCY CARE
With this context in mind, the aim of this prospective descriptive study was to describe 1) the characteristics of older people who fall and call an ambulance, and 2) the characteristics of the falls and the ambulance response they receive.
METHODS Study Design
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
This study was a prospective, observational cohort study in which fall-specific information collected using a tailored data-collection tool was combined with ambulance clinical records (ACR) and computer-aided dispatch (CAD) data.
Study Setting The study was conducted in New South Wales (NSW), Australia. The Ambulance Service of New South Wales (ASNSW) is a statewide government ambulance service that responds to approximately 1,120,000 incidents annually, of which 825,280 are emergency cases.11 The ambulance service provides coverage across a geographic area of approximately 802,000 km2 encompassing both metropolitan and rural/remote regions, and has a frontline clinical workforce of almost 3,000 operational paramedics. The paramedic workforce consists of four clinical levels: paramedic trainee (PT) (first year of training), paramedic intern (PI) (second/third year of training), qualified paramedics (QP) (completed 3 years of core training to advanced life support level), and paramedic specialist (specialist training as an intensive care paramedic (ICP) or extended care paramedic (ECP)). Paramedics operate under a protocol-based system with a high level of autonomy and with little on-scene medical consultation. Paramedic management of cases involving falls experienced by older people is guided by a “falls in the elderly” protocol (Supplement 1, available online), which provides a decision-assistance algorithm that supports paramedics in deciding how best to manage an older faller. Paramedics can recommend nontransport where strictly defined criteria are met following detailed history taking and patient assessment, although any patient requesting transport following discussion must be transported to an ED. Dispatch of ambulance resources is managed by a computer-aided dispatch (CAD) system, in which incoming calls are categorised and prioritized using the Medical Priority Dispatch System (MPDS) and ProQA software (version 11.3) (Priority Dispatch, Salt Lake City, Utah, USA). Incidents are allocated a response priority of 1–9, with priority 1 and 2 calls constituting “emergency” responses. Priority 1 cases involve urgent, “lights and sirens” responses, while priority 2 cases receive nonurgent responses within locally defined time frames.
APRIL/JUNE 2014
VOLUME 18 / NUMBER 2
Study Population The study population comprised people aged 65 years and older who received an emergency response and were confirmed to have fallen by paramedics at the scene. A fall was defined as “an event which results in a person coming to rest inadvertently on the ground, floor or lower level with or without loss of consciousness and other than as a consequence of sudden onset of paralysis, epileptic seizure or overwhelming external force.”12 An emergency ambulance response was defined as any response initiated through the emergency call system that was allocated a response priority of 1 (urgent) or 2 (nonurgent). Incidents allocated a response priority of 3–9 (cases that do not originate via the emergency call system including routine transports, operational standbys, medical appointments, and interhospital transfers) were excluded.
Data Sources A fall-specific data collection tool was designed prior to the commencement of the study by an advisory group consisting of experts in the field of falls and balance, geriatrics, and prehospital care, using a consensus approach. This was necessary due to the fact that the routinely completed ambulance clinical record does not systematically capture fall-specific data at a detailed level. The paper-based form collected fallspecific information across 24 variables of interest detailing patient demographics, including co-morbidity and medication history, environment, previous falls and ambulance usage, fall circumstances, paramedicdiagnosed injury, and prehospital outcomes. In order to ensure its suitability for use in the field, the tool was piloted for one month prior to the commencement of data collection, with results assessed by the research team, and modifications made where required to promote consistency among data collectors. Data from this tool were merged with routinely collected clinical and dispatch information from the PCR and CAD databases.
Data Collection Data were collected between October 1, 2010 and June 30, 2011. As participation in research is noncompulsory in the Ambulance Service of NSW, a statewide network of paramedics was established to collect data. An expression of interest was released to all paramedics in ASNSW during the 3 months preceding the data collection phase inviting them to participate in the study. By the commencement of the data collection period, 384 paramedics had agreed to participate, representing 13% of frontline operational paramedics. Paramedics received education with regard to the broad objectives and rationale of the study, but the specific research
Downloaded by [Florida Atlantic University] at 17:03 05 November 2015
P. M. Simpson et al.
187
EMS RESPONSES TO OLDER FALLERS
questions upon which analyses would be based were withheld so as to reduce the potential of paramedics changing their clinical practice during the study period. Education was also provided detailing how to use the tool and the data collection requirements, including definitions of variables to increase consistency in completion. Identification of eligible patients was determined by paramedics on scene, not during the dispatch process. After arriving on scene and determining the patient met the eligibility criteria, paramedics provided the standard level of acute care according to normal clinical practice and then obtained the additional information required for the purposes of the study. The completed fall-specific data form was then sent to the research team where it was scanned and entered into an electronic database using automated data entry software (Cardiff Teleform, Vista, CA).
Data Analysis The fall-specific data were deterministically matched to the routinely collected clinical record and dispatch data using a unique clinical record number. Analysis was undertaken using SAS 9.2 (SAS Institute, Cary, NC, USA). Descriptive statistics were generated, using mean and standard deviation (SD) and median with interquartile range (IQR) for normal and non-normally distributed data, respectively. Differences in normally distributed independent continuous variables were assessed using Student’s t-tests, and in non-normally distributed independent continuous variables using the Wilcoxon rank sum tests. Differences in proportions for dichotomous nominal variables were analyzed using chi-squared (χ 2 ) statistics. For independent ordinal group variables such as age group, the Mantel-Haenszel test for trend was used to compare more than two independent proportions. Differences for all analyses were considered statistically significant at p < 0.05. To enable categorical analyses of continuous variables, time of day was categorized into day (0700–1859) and night (1900–0659); response priority into urgent and nonurgent; and age into 3 groups (65–74; 75–84; 85+). Physiological status, based on vital signs, was categorized using established physiological parameters within this health system,13 creating “normal” and “abnormal” categories Table 1). Time spent on the floor (“long-lies”) was estimated by the patient or a witness if present.
Ethical Approval and Consent A waiver of consent was granted by the Human Research Ethics Committee (HREC). Ethical approval was granted by the Sydney South West Area Health Service HREC (Protocol No. X10-0152 & HREC/10/RPAH/282).
TABLE 1. Criteria for classification of physiological status (“normal” versus “abnormal”)a Vital sign
Heart rate (beats/min) Respiratory rate (breaths/min) Systolic blood pressure (mmHg) SpO2 (%) Level of consciousness (AVPU)
Normal
Abnormal
>50 and 10 and
