General Ward Nurses Detection and Response to Clinical Deterioration in Three Hospitals at the Kenyan Coast: A Convergent Parallel Mixed Methods Study

General Ward Nurses Detection and Response to Clinical Deterioration in Three Hospitals at the Kenyan Coast: A Convergent Parallel Mixed Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article General Ward Nurses Detection and Response to Clinical Deterioration in Three Hospitals at the Kenyan Coast: A Convergent Parallel Mixed Methods Study Nickcy Mbuthia, Nancy Kagwanja, Moses Ngari, Mwanamvua Boga This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2633455/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Mar, 2024 Read the published version in BMC Nursing → Version 1 posted 10 You are reading this latest preprint version Abstract Background In low and middle-income countries like Kenya, critical care facilities are limited, which means acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to clinical deterioration. Methods This convergent parallel mixed-methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the patients' vital signs 24 hours before a cardiac arrest (death) occurred was retrieved from patients' medical records. Additionally, in-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards. Results This study reviewed 405 patient records and found that most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 hours prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs, availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers. Conclusion The study showed that nurses did not consistently monitor and record vital signs in the general wards. The nurses worked in suboptimal ward environments characterised by inadequate and malfunctioning monitoring equipment, high workload due to staff shortages, communication and teamwork gaps, and little training on handling patient deterioration at the ward level; factors that negatively impact patient safety and outcomes. The findings provide an opportunity for future research to test interventions to improve nurses' assessment and management of clinical deterioration in general wards. Clinical deterioration vital signs nurse documentation patient safety medical surgical nursing recognising responding Figures Figure 1 Background Failure to rescue is a patient safety and healthcare quality measure, which refers to the delay or failure to detect and respond to clinical deterioration in hospitalised patients, leading to mortality [ 1 , 2 ]. In-hospital mortality is increasingly being recognised as a measure of service provision quality and a key indicator of patient safety [ 3 , 4 ]. Although patients inevitably die in the hospital, clinicians should be able to detect the deterioration in the patient early enough and act promptly to prevent death. Early detection and response to the changes in vital signs and physiological parameters in hospitalised patients are essential in reducing the risk of preventable death and preventing unplanned admission into critical care units [ 5 , 6 ]. Numerous studies have established that there are physiological antecedents before a cardiac arrest occurs in a hospitalised patient, allowing the clinician to identify the deterioration and act promptly [ 7 – 10 ]. Patient monitoring, which involves the assessment of vital signs and physiological changes, allows for early detection of these antecedents of patient deterioration. Subsequently, based on monitoring criteria, the clinician triggers or activates the rapid response team to treat the deteriorating patients before adverse events occur [ 11 ]. The most commonly used monitoring and call criteria for rapid response include abnormalities in physiologic measures such as respiratory rate, heart rate, systolic blood pressure, oxygen saturation, acute change in mental status, and the clinician's significant concern about the patient's condition [ 12 ]. Regularly monitoring these physiologic measures allows the clinician to identify deterioration and thus act hastily to prevent further deterioration by escalating and communicating the information clearly to the individual or team that shall manage the patient and prevent further deterioration. Escalation of care in most institutions is guided by institutional protocols that clearly outline the actions that the clinician can implement until they are satisfied that the correct response has been achieved. These actions include a change in monitoring frequency, possible modifications of care, a review of the patient by a senior medical officer, seeking assistance from an intensive care specialist, or activation of the Emergency Response System [ 13 ]. In addition, a concise, efficient and accurate flow of information about the deteriorating patient is a fundamental component of the escalation of care [ 13 , 14 ]. The different modes to communicate the deterioration of care include face-to-face communication, overhead announcement within the hospital, mobile and landline telephones, and hospital alarms [ 15 ]. Whichever mode is used to communicate deterioration, it is critical to use a common language using a structured communication tool to ensure a timely response. In Kenya, like most low and middle-income countries, patient complexity is increasing because of higher morbidity due to non-communicable diseases, road traffic accidents, and a longer life expectancy. This has led to a higher demand for critical care services as compared to developed countries, yet the availability of these services is limited [ 16 – 19 ]. This has therefore led to acutely ill patients being managed in the general medical and surgical wards. In the critical care units (CCUs), patient's vital signs are continuously and closely monitored with monitoring equipment and technologies, and therefore detection of deterioration and response is timely. Additionally, the CCUs are well equipped with resuscitation equipment and are adequately staffed with staff trained in responding to changes in patient deterioration. However, in the general wards where most acute patient deterioration occurs, patient surveillance is done periodically. Therefore, it depends on the clinicians' ability to recognise and respond to the deterioration. Because of the role that nurses play in early deterioration identification, failure to rescue may be very sensitive to nursing care. According to Mushta et al. (2018) [ 20 ], failure to rescue as a nurse-sensitive indicator includes failure to recognise changes in patient condition, failure to escalate the changes and inadequate decision-making. Patient assessment and monitoring is a fundamental nursing competence; therefore, nurses carry the highest responsibility in detecting and responding to patient deterioration. However, research shows that nurses fail to recognise and respond timely to patients' deterioration [ 21 – 23 ]. Vital signs monitoring is fundamental to nursing, whereby the nurse must assess, document, and interpret vital signs promptly and escalate any abnormal values. However, research shows that monitoring, documentation, and reporting of vital signs are often irregular, incomplete, and not used to make clinical decisions [ 24 – 26 ]. Documented factors that contribute to the failure of a nurse to recognise and respond include the lack of knowledge and skills in the detection of warning signs, poor or absent monitoring of the patient's vital signs, difficulty in prioritising competing demands with increasing workload and fear of reporting the deterioration [ 27 – 31 ]. Notably, most of the literature on the general ward nurses' issues and challenges in detecting and escalating patient deterioration has been generated in high-income country settings, with little literature from developing countries. We did not identify any studies reporting on the Kenyan context. Therefore, this study aimed to examine the general ward nurses' vital signs documentation practices in the deteriorating patient and explore the factors influencing their ability to detect and respond to clinical deterioration in three Kenyan hospitals. Methods Design A convergent parallel mixed-methods design was utilised to achieve the objectives. A retrospective descriptive design was used to retrieve quantitative data from medical records of patients who had suffered a cardiac arrest and died in the previous year in the study hospitals' general medical and surgical wards. Specifically, the study sought to determine the extent to which the nurses monitored and documented the patients' vital signs 24 hours before a cardiac arrest (death) occurred. Additionally, qualitative data was collected by conducting in-depth interviews with nursing staff, including ward managers, to understand better the factors that influence the ability to detect and respond to clinical deterioration. Data from the two methods were analysed separately, and the results were compared and related. Each type of data was used to validate the other during the interpretation, creating solid foundations through which we could better achieve the study objectives [ 32 ]. Setting The study was undertaken in the adult medical and surgical wards of three purposefully selected hospitals in Kenya's coastal region. We identified hospitals with prior contact or linkage with the research team to minimise trust concerns related to our data collection. One hospital in Mombasa County was a Level Five hospital (Hospital A), while the other two were Level Four hospitals (Hospital B and C) in Kilifi County. Level Four and Five hospitals are secondary-level referral hospitals in the Kenyan health system. Level Five hospitals offer a more comprehensive array of specialised curative services than level 4 hospitals [ 33 ]. The three hospitals are relatively homogeneous in their organisational structure, resource availability, and the populations they serve. Sample and Sampling technique Nurses' documentation review The sample comprised the records of patients who suffered a cardiac arrest and died in the adult medical and surgical wards the previous year. We decided to review the records of these patients because it is well documented that patients frequently display physiological changes as much as 24 hours before a cardiac arrest and death occur [ 7 , 9 ]. Therefore, we included all records from male and female patients 18 years and older and those admitted for more than 24hrs between January and December 2019. Key informant interviews The sample for the interviews was purposefully drawn from the registered nurses working in the adult medical wards and the surgical wards in the three hospitals. Therefore, we included in the interviews nurses who had worked in the adult medical and surgical wards in the study hospitals for at least six months. Data collection procedures Documentation Review In hospital B, a list of all the deaths that occurred in the adult medical and surgical wards in 2019 was obtained from an electronic database. A systematic sampling technique was used to obtain the sample. It was possible to obtain the patient's admission number from the database, which was then used to retrieve the patient's file in the medical records department. Hospitals A and C had no databases of the deaths available. Therefore, with the assistance of the medical records personnel, the data collectors retrieved all the files of the patients who had died in the respective hospitals in 2019. Subsequently, they selected the files from the adult medical and surgical wards from which they randomly selected and analysed files for each month in 2019. To examine if, which, where, and how physiological parameters of the patients were documented before patient deterioration, the sampled records were reviewed for the nursing documentation of six vital signs 24 hours before death. The vital signs were respiratory rate in breaths per minute, systolic blood pressure in millimetres of mercury (mmHg), oxygen saturation as a percentage, heart rate in beats per minute, temperature in degrees centigrade, and consciousness level. According to the literature, to detect patient deterioration, these are the minimum physiological parameters that trigger the nurse to call for help, and they should be monitored at least every 4 hours [ 12 , 34 ]. Data were collected using a predesigned tool developed by the researchers based on recommendations from literature and guidelines on documentation of patients' physiological observations. In the data collection tool, the research assistants first identified which document the vital signs were retrieved from, either the vital signs observation chart or the nursing notes (Kardex). According to the literature, acute patients' vital signs should be monitored every four hours unless the patient's condition or specific treatment requires more frequent measurements[ 35 ]. Therefore, the data collection tool also captured the last six vital signs documented by the nurse in the previous 24 hours before death occurred. If none of the vital signs had been recorded in the 24 hours preceding the cardiac arrest, the last recorded vital sign(s) was captured, including the time it was recorded. Key informant interviews We conducted in-depth, semi-structured in-person interviews in each hospital to better understand the factors that influence the ability to detect and escalate clinical deterioration. An interview guide was used to explore the nurses' experiences in caring for the deteriorating patient, the challenges in detecting deterioration, their actions when a patient deteriorates, and the communication practices for escalating the deterioration. In addition, examples of clinical deterioration were used to prompt the recall of similar situations experienced by participants. The scenarios aimed to trigger reflection on personal experiences. We sought informed consent before conducting interviews. The interviews were conducted in offices within the nurses' respective wards, where we anticipated few interruptions. However, because the interviews were conducted during regular shift hours, the nurses' colleagues were informed of the locations in case of any urgent situations. All interview sessions lasted approximately 20–30 min and were recorded using an audio recorder. The interviews took place in an office setting that guaranteed privacy and an acoustically conducive environment. Since data collection occurred during the COVID-19 pandemic, we adopted prevention measures such as wearing masks and social distancing during the interviews. Data analysis Analysis of the documentation All quantitative data were extracted from patient records using a standard tool and entered into the Epidata database. All categorical patient characteristics were reported as frequencies and their respective percentage. Age in years was reported as median and interquartile range (IQR) because it was skewed. Documentation for each vital event was reported as the number of patients with a vital event documented at each time point. Statistical analyses were conducted using Stata (Version 17.0, College Station, Texas, USA). Analysis of the interviews For the qualitative data, all audio recordings and field notes were maintained in a secure location. A professional transcriber transcribed the audio recordings into an MS WORD document. The researchers listened to the recordings and compared them with the transcription to ensure accuracy and enhance familiarisation with the data. We adopted a thematic analysis approach, as described by Braun & Clarke, 2006 [ 36 ], where we sought to identify patterns in the reviewed transcripts. Our analysis was deductive, driven by the research objectives and our focus on nurses' experiences of patient clinical deterioration. The analysis process involved familiarisation with the data, generating initial codes, searching for themes, reviewing themes, defining themes and writing up the report [ 36 , 37 ]. The process, though described step-wise, was iterative. Ethical considerations Ethical review and approval were obtained from the Pwani University Ethics Review Committee (ERC/PU-STAFF/001/2020). A research permit to conduct the study was obtained from the National Commission for Science, Technology & Innovation (NACOSTI/P/20/4890). Upon ethical approval, permission to collect data was granted by the respective hospital boards after assurances to adhere to the COVID-19 preventive measures to protect the study participants and the data collectors. Interview participation was completely voluntary. The participating nurses were provided with written information about the research and their rights to the study. The participants were requested to sign and date the informed consent form upon agreement. Results Quantitative analysis results Patient characteristics A total of 405 records were reviewed, 186 (46%), 135 (33%), and 84 (21%) in Hospital A, Hospital B, and Hospital C, respectively. Their median [IQR] age was 54 [36 to 68] years. Two hundred and forty-two (60%) were male. The most frequent diagnoses identified from the reviewed patient files were cancer 41 (10%), Cerebrovascular accident 30 (7.4%), Heart failure 27 (6.7%), Tuberculosis 25 (6.2%) and Meningitis 24 (5.9%) shown in Table 1 . Table 1 Patient Characteristics A (N = 186) B (N = 135) C (N = 84) Overall (N = 405) Sex Male 120 (65) 78 (58) 44 (52) 242 (60) Female 66 (35) 57 (42) 40 (48) 163 (40) Age in years Median [IQR] 48 [35‒65] 60 [37‒70] 55.5 [42‒70] 54 [36‒68] Leading primary diagnosis Cancer 22 (12) 14 (10) 5 (5.9) 41 (10) Cerebrovascular accident 10 (5.4) 13 (9.6) 7 (8.3) 30 (7.4) Heart failure 10 (5.4) 10 (7.4) 7 (8.3) 27 (6.7) Tuberculosis 14 (7.5) 9 (6.7) 2 (2.4) 25 (6.2) Meningitis 8 (4.3) 13 (9.6) 3 (3.6) 24 (5.9) Chronic Kidney Disease 13 (7.0) 5 (3.7) 6 (7.1) 24 (5.9) Pneumonia 9 (4.8) 9 (6.7) 4 (4.8) 22 (5.4) Sepsis 14 (7.5) 3 (2,2) 4 (4.8) 21 (5.2) Anaemia 6 (3.2) 9 (6.7) 5 (6.0) 20 (4.9) Gastroenteritis 9 (4.8) 3 (2.2) 8 (9.5) 20 (4.9) Head Injury 15 (8.1) 3 (2.2) 1 (1.2) 19 (4.7) Diabetes Mellitus 7 (3.8) 3 (2.2) 7 (8.3) 17 (4.2) Liver disease 5 (2.7) 6 (4.4) 2 (2.4) 13 (3.2) Hypertension 6 (3.2) 4 (2.9) 3 (3.6) 13 (3.2) Acute Kidney Injury 3 (1.6) 7 (5.2) 2 (2.4) 12 (3.0) Others 35 (19) 24 (18) 18 (21) 77 (19) Results are N (%) unless specified, IQR; Interquartile range. Patient deterioration nursing documentation Of the 405 patient records reviewed, the vital signs were documented in the nursing notes (Kardex) and vital signs observation chart among 391 (97%) and 14 (3.5%), respectively. During the 24 hours prior to patient deterioration/death reviewed, 283 (70%) patients had no respiratory rate documented, 77 (19%) had only one documentation of respiratory rate, while only 5/405 (1.2%) had documentation for all the six-time points. There was no heart rate documentation among 45 (11%) patients, while 87 (21%), 107 (26%) and 101 (25%) had one, two and three documentations, respectively. The temperature was not documented among 115 (28%) patients, while it was documented once, twice and thrice among 104 (26%), 92 (23%) and 65 (16%) patient files, respectively. There were 43 (11%) patient files with no blood pressure documentation, and it was documented among 91 (22%), 107 (26%) and 102 (25%) patients once, twice and thrice, respectively. Oxygen saturation was not documented among 116 (29%) patients but was documented once, twice and thrice among 91 (22%), 80 (20%) and 62 (15%) patients, respectively. Almost nine in every ten patients (N = 356, 88%) had no documentation for the level of consciousness but was documented once, twice and thrice among 31 (7.7%), 7 (1.7%) and 3 (0.7%) patients, respectively, as shown in Table 2 . Less than 2% of patients had any vital signs documented for all the six-time points; respiratory rate (N = 5, 1.2%), heart rate (N = 6, 1.5%), temperature (N = 6, 1.5%), blood pressure (N = 6, 1.5%), oxygen saturation (N = 5, 1.2%) and level of consciousness (N = 2, 0.5%) as illustrated in Fig. 1 . Table 2 Patient deterioration nursing documentation review. Vital events Number of final six vital signs documented None 1 2 3 4 5 6 Respiratory rate 283 (70) 77 (19) 26 (6.4) 8 (1.9) 4 (0.9) 2 (0.5) 5 (1.2) Heart rate 45 (11) 87 (21) 107 (26) 101 (25) 45 (11) 14 (3.5) 6 (1.5) Temperature 115 (28) 104 (26) 92 (23) 65 (16) 18 (4.4) 5 (1.2) 6 (1.5) Blood Pressure 43 (11) 91 (22) 107 (26) 102 (25) 43 (11) 13 (3.2) 6 (1.5) Oxygen Saturation 116 (29) 91 (22) 80 (20) 62 (15) 42 (10) 9 (2.2) 5 (1.2) Level of consciousness 356 (88) 31 (7.7) 7 (1.7) 3 (0.7) 2 (0.5) 4 (1.0) 2 (0.5) Results are N (%). Qualitative analysis results Participants characteristics We conducted 24 interviews with respondents across the three study hospitals. Of these 24, there were two senior hospital management nurses and six ward managers. All the nurse ward managers reported carrying out clinical nursing duties and ward administration responsibilities. Table 3 below summarises the participants' characteristics related to their gender and how long they had provided nursing services. Table 3 Interview respondent characteristics Characteristic Hospital A (N = 10) Hospital B (N = 8) Hospital C (N = 6) Overall duration as a nurse (years) 0–5 1 4 2 6–10 2 0 1 11–20 4 3 0 21–30 3 1 1 > 30 0 0 2 No. of years working in current ward* 6months-1year 5 1 1 2-3years 1 4 3 4-5years 2 2 0 > 5years 2 0 1 Gender Male 1 3 2 Female 9 5 4 *Two nurses from Hospitals B and C are not included in the number of nurses working in the wards among the study respondents because they were hospital nurse managers with mainly administrative and managerial responsibilities. Ward Characteristics Table 4 summarises some hospital and ward characteristics that appeared to influence the extent to which nurses could monitor the patients and document their findings. In hospitals B and C, the medical and surgical patients were nursed in the same ward. The wards were distinguished as male and female, with the female wards comprising patients with medical, surgical (general surgical and orthopaedic) and gynaecological conditions. The male wards (hospitals B and C) also admitted medical and surgical patients. Further, some admitted patients had psychiatric conditions in hospital C. Hospital A had separate male and female medical and surgical wards. As a result, hospital A respondents were more in number (Table 3 ) compared to Hospital B and C. Hospital A had an Intensive Care Unit (ICU) with a capacity of 15 beds ( Table 4 ), where patients needing critical care from Hospitals B and C were also referred. This was a challenge, as quoted by one of the participants: "The person who is receiving the call will tell you my ICU is full. What will you do after you hear that? How will you verify if ICU is full? You have very critical patient who really, really needs ICU, needs ventilation…The present condition is going down you end up risking with fluids, with medication, you can put oxygen and that's all. As we wait like 3,4 hours you call again you ask. Patients end up staying for like for 3, 4 days even without going for an ICU. So we lose patients just like that" (B006) Table 4: Ward characteristics in study hospitals Ward Characteristics Hospital A Hospital B Hospital C Type of patients admitted into wards Separate medical and surgical wards for female and male patients Mixed female ward (admitting, medical, surgical and gynaecological patients) Mixed female ward (admitting, medical, surgical and gynaecological patients) ICU or HDU in a hospital ICU present No ICU HDU present No. of nurses working in the study wards Male surgical: 22 Male ward: 10 Male ward: 10 (but two away on study leave) Female surgical: 11 Male medical: 21 Female ward: 11 Female ward: 8 nurses (2 away on leave) Female medical: 20 The bed capacity of the study ward Male surgical: 70 Male ward: 34 patients Male ward: can hold up to 60 patients Female surgical: 40 Male medical: 72 Female ward: 32 patients Female ward: 48 patients Female medical: 80 Abbreviations: ICU-Intensive Care Unit; HDU-High Dependency Unit Factors influencing nurses' ability to detect and respond to clinical deterioration Interview respondents acknowledged that they faced challenges in detecting and responding to clinically deteriorating patients in the ward. Five broad, interrelated themes related to detecting and responding promptly to patient deterioration emerged from the analysis of qualitative interviews. These were insufficient monitoring of vital signs, availability of equipment and supplies , staffing conditions and workload , lack of training and guidelines , communication and teamwork among healthcare workers . These are discussed in turn below. Insufficient monitoring of vital signs The qualitative results were consistent with the findings of the document review related to gaps in vital signs documentation. Across all three study hospitals, interview respondents reported inconsistently taking vital signs for patients admitted to the wards. These inconsistencies, linked to poorly functioning and limited availability of equipment for monitoring patients, also manifested in poor documentation of patients' vital signs, as illustrated in the quote below: "And the biggest challenge is that we don't have the apparatus at hand. For example, if we are depending on one monitor to observe all the patients and then monitor breaks down. Like for now, you go borrowing from another ward, you find that it is being used. This really disturbs the documentation especially when it comes to vitals. So, you can find a patient may be observed maybe twice, thrice maybe a patient who has stayed for like 3 or 4 days which is a quite an ugly picture" (A003) Instances of poorly functioning equipment included the failure of the digital blood pressure machines and thermometers. Respondents reported that this equipment functioned well if their use was limited to a few patients. However, as highlighted in Table 4 above, the wards where the respondents worked frequently had high patient numbers, for whom the nurses only had one digital thermometer and blood pressure machine for patient monitoring. It was also common for other monitoring equipment, such as blood sugar machines, to sometimes lack batteries. There were also instances where monitors had been present in the wards but were not in use because they had not been repaired or replaced. Another type of equipment which was reportedly absent in one of the study hospitals was a pulse oximeter. In this hospital, the respondents reported relying only on observations of respiratory distress to administer oxygen and held the view that they perhaps were giving oxygen too late because they were unaware of the patient's oxygen saturation. "In case a patient starts gasping, that's when we put them on oxygen because we don't have things like oximeter that we can be able to monitor oxygen saturation. I would say it's mostly when the patient is going down, they are gasping or difficulties in breathing then we start them on oxygen…" (B003) Despite these challenges, there were efforts to closely monitor patients judged to be severely ill. Most of these patients were placed in the acute rooms of the different wards to enable the nurses to quickly detect changes in the patient's conditions. In addition, when there were students in the ward, they were utilised to closely monitor the patients as they learnt. However, because students were still in training, they were not always able to quickly detect a deteriorating patient and communicate this to the nurse in good time. Availability of equipment and supplies Regarding the low availability of equipment and supplies, many respondents highlighted that oxygen, commonly used to respond to deteriorating patients, was often not readily available. In Hospitals B and C, some of the beds in the acute bay had oxygen ports for piped oxygen. However, if more than four patients, for example, in the case of Hospital C, needed oxygen, then an oxygen concentrator or oxygen cylinders would have to be used. However, the oxygen concentrator shared between the male and female wards in Hospital C had been broken down for over six months without repair. They, therefore, had to borrow from either the paediatric ward or High Dependency Unit (HDU). In Hospital A, they mainly used oxygen cylinders but reportedly experienced delays in connecting the oxygen as they tried to move the heavy oxygen cylinders: "We don't have concentrators, we don't have oxygen, and there is a patient who needs oxygen, and it's not there. We don't even have a concentrator" (C003) "There is also a challenge there in terms of because these cylinders sometimes we run out of oxygen and you find we go to another ward cylinders are in use, cylinders are heavy these big cylinders. So you find a nurse is not able to move that cylinder" (A001) Other equipment-related factors that hindered prompt response to deteriorating patients included the incomplete nature of the emergency trays in some wards. One respondent reported: "Yes, we had a crash cart but we have never been able to manage the crash cart. Because you see, one, people still have that habit of picking drugs. So today you can refill the crash cart then you find within a minute you are not seeing those drugs maybe by the end of the day no single drugs because people pick, pick and they don't replace, there is a lack of discipline in a way someone can just come dashing because maybe a patient has changed condition in another ward maybe a medical ward looking for a certain drug, picks and go" (A003) Respondents also highlighted that having one bag valve mask (BVM) per ward meant that there was a delay when a patient required resuscitation, especially if the BVM was not functioning well. In such cases, nurses had to borrow from another ward. Another inadequate supply that hindered prompt responses was Personal Protective Equipment (PPE). This was particularly relevant for nurses who were managing COVID-19 patients. Staffing conditions and workload Across all the study hospitals, most respondents felt that the adult medical and surgical wards were grossly understaffed, making monitoring and detecting deteriorating patients difficult. As noted above, an acute bay was supposed to help nurses quickly detect when patients' conditions changed. However, this quick identification was limited in most cases because the nursing shifts were often covered by few nurses, making it challenging to do timely observations of vital signs. For example, one respondent from hospital B observed: "Even though the male and female wards have acute areas. The only benefit of the acute areas is that the nurse is near the patients. However, it is difficult to do close monitoring when the nurse is working alone and the patients are many... because I have said sometimes we have a capacity of 45. So it won't be easy for you to be checking vitals maybe every 2 hours" (B005) In the afternoon and night shifts, nurses commonly worked alone, with the support of students. The morning shifts were reportedly better staffed, as about two to three nurses reported to work. Most respondents felt that it was easier to detect deteriorating patients during the morning shift. During the shifts where a nurse was working alone, it was reportedly not uncommon for nurses to find out from relatives that patients were deteriorating as they did other procedures in the hospital wards. In fact, nurses across all three hospitals considered relatives a resource who could inform them when patients deteriorated. "And sometimes because of the shortage, we are not able to identify as quick as we can. You can imagine when you are alone in the ward, you are giving treatment on the other side. So in the most cases it's the relatives who calls you. They call you, this one has deteriorated and then we notice." (C003) "So you are only getting something you are told by the caretaker this patient has deteriorated. And by the time you are being told that, you realised that it has gone to the extreme end. You don't get to intervene early enough. When you go and see this patient the general condition has already deteriorated to a further extent that the measures you take maybe you are trying to resuscitate this patient anaenda tu hivo [dies]. Nevertheless, you try. (B006) "When the nurse is alone and you are on the other side and you left patient A, you have maybe 30 patients, like now we have 27 and the night nurse is alone, so she left patient A and now she is doing patient 25, and this A changes condition, unless the relatives call you, you will not know. By the time you go there, maybe it will be too late. So I think the nurse/patient ratio plays a big role" (A006) The challenges with staffing also hindered effective response to a deteriorating patient, particularly one who required resuscitation, as described below by one of the respondents: "You are alone, and the patient has changed; the one you have is a student. Some of the students they are very junior, they don't know anything, tell me, whom will you call? And here you know resuscitation is teamwork. Teamwork of around 3, 4 people together working. When you are alone it becomes very difficult to do all those procedures alone. You need someone to record [vital signs], the other one do cardiac massage...If there is no that teamwork, the patient becomes zero because when you are alone, you can't do" (A005) When responding to a deteriorating patient, staffing was not only a nursing issue; it also seemed to cut across to other healthcare professionals who worked in the ward. Doctors especially were commonly few and busy, and the respondents reported delays when they called them. At night, across the three study hospitals, the doctors were not available in the wards and were commonly in casualty admitting patients. In Hospitals B and C, one Medical Officer (MO) intern circulated across the casualty department, theatre, and wards. Lack of training and guidelines Across all the study hospitals, most of the nurses had not been trained in Cardiopulmonary Resuscitation (CPR), Basic Life Support (BLS) or Advanced Cardiac Life Support (ACLS) despite caring for the acutely ill patients in the wards. Instead, most nurses relied on their pre-service training to detect and respond to deteriorating patients. "Very few people have gone through BLS, ACLS. Personally, I haven't done BLS, ACLS because it's time and money… I don't know but 90% of the people who are there have not done the BLS and ACLS." (B006) "I have not done any [BLS or ACLS training]. I did it in college, and that's what I am surviving with…(C004) In addition, there were no existing policies and guidelines that were observed or reported on in relation to processes for detecting and responding to deteriorating patients. The exception was in Hospital A, where there were posters with some guidance on the ward notice boards, but the nurses in these wards reported that no training had preceded the introduction of these posters. Communication and Teamwork among the healthcare workers Experiences of communication varied across the three hospitals. For example, in Hospital A, an alert system that utilised colour codes (e.g. code blue, code red) had been introduced. There were posters at the ward level describing the response process when a patient was noted to be deteriorating. This process required calling through the operator, who would then call the doctors. Unfortunately, few study respondents from Hospital A understood this alert system, and many reported that they had not been trained in its use. As a result, it was hardly utilised. In hospital B, the ward nurse was expected to call the Medical officer (MO) intern to notify them and request their support if there was a deteriorating patient. The intern would then escalate the issue depending on his ability to address the patient's deterioration. In hospital C, there was a long chain of communication in which the ward nurse was required to call the nurse covering the hospital, who would then call the MO intern or the MO to support a response to a deteriorating client. This long chain of communication inevitably slowed down the response to the deteriorating client, as illustrated in the quote below: "Communication is another issue. I have to call the nurse who is covering the one who has the phone, to call the MO. You see that. It's an emergency, I call somebody to call for me the MO. You can imagine the one I am calling she is in the office, maybe for example at night or in the afternoon...I call her, I have a patient who is gasping, let me call the MO intern, MO intern comes, she feels I can't handle this alone, let me call the MO. You see the chain. Is that an emergency? (C003) Notably, the challenges described above were experienced mainly during the night and afternoon shifts and the weekend when there were few staff in the hospital. The respondents noted that during the morning shift, doctors and clinical officers were more available in the ward, and sometimes it was not necessary to make a phone call to reach them to communicate that a patient was deteriorating. Regarding what was communicated when a call was made, while the respondents acknowledged that there were no written-down guidelines that described what should be said, they reported describing the patient's details, the diagnosis, and the most recent vital signs of the patient, including what actions had been taken by the nurse who was calling. Because of the reported staffing challenges, teamwork appeared to be lacking in ensuring timely responses to deteriorating patients. This was illustrated by reports of certain doctors being too focused on their patients that they did not participate when there was a call for resuscitating a patient that they did not admit: "Patient is deteriorating from theatre, now I have called the MO. The MO is referring me to the surgeon. Then the surgeon is not picking the phone and I have called over several times, I called the nurse covering. So went back to the MO, so he insisted call the surgeon, but we insisted, please for the sake of the patient, please come and assist us in resuscitating the patient. So we had to apply our own… so we had to resuscitate the patient on our own." (B002) Discussion This study sought to understand an under-investigated issue in the Kenyan setting. Nurses' identification and response to a deteriorating patient is a critical role that needs to be further illuminated and improved upon to reduce unplanned admission to the few available critical care units as well as to reduce morbidity and mortality. Therefore, this study sought to find out how nurses documented the patients' vital signs 24 hours before a cardiac arrest (death) and to understand better the factors that influenced the ability to detect and respond to clinical deterioration. As a result, we identified five central influencing factors that hinder the nurses' ability to detect and respond to patient deterioration. These were the insufficient monitoring of vital signs, availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork amongst healthcare workers. This study found that vital signs monitoring and documentation by the nurses in the general wards was suboptimal and below the recommended standards of vital signs observations for an acute patient. This finding was consistent both in the document review and from the reports by the interviewees. From the document review, we found that less than 2% of the reviewed patient's files had complete documentation of the six vital signs in the 24hrs prior to death. In addition, 70% of the patients did not have any recording of the respiratory rate 24hrs prior to death despite it being the more accurate predictor of clinical deterioration [38, 39]. Furthermore, the documentation of the vital signs was primarily done in the nursing notes and not in the vital signs observations chart, therefore, limiting who could access the information. It is important to note that this study only considered the vital signs documented in the nursing notes and observation charts. Therefore the vital signs may have been taken but not documented and thus could explain the findings in this study. However, these findings are consistent with reports from studies that show that vital signs monitoring and documentation are often incomplete, with the respiratory rate being the lowest monitored vital sign [40–42]. A cross-cutting challenge that the study participants reported was the unavailability of equipment and supplies to enable them to detect and respond to clinical deterioration. This included the lack of monitoring devices, which were not functioning correctly where available. Additionally, they indicated a lack of resuscitation equipment and supplies and a lack of PPEs in the face of COVID-19. However, the most glaring issue was the lack of oxygen supply in the general wards. Where available, it was available in oxygen cylinders that required the nurse to move the heavy cylinder from one location to another hence delaying the response to deterioration. The unavailability of oxygen in the healthcare facilities in Kenya became a significant focus during the COVID-19 pandemic, with reports of many hospitals lacking reliable oxygen access [16, 43]. A dependable source of oxygen is necessary to administer oxygen therapy, which can be obtained through various means. They include oxygen tanks that are filled at a facility, oxygen concentrators that extract oxygen from the surrounding air, oxygen plants that distribute oxygen via pipes or tanks, and liquid oxygen provided by a specialised gas plant and stored at high pressure on the premises [44]. However, studies show that ensuring a steady and appropriate oxygen supply in the Lower and Middle Countries remains challenging [45–48]. This is not only hampered by factors such as the use of low-quality equipment that is not well-maintained but also by broader systemic issues, such as an unsteady power supply, limited healthcare workforce, and insufficient funding for healthcare [49, 50]. Studies show that vital signs monitoring and documentation takes a considerable amount of nurses' time, which tends to increase depending on whether the observations are being done 6-hourly, 4-hourly or more [51–53]. The documentation burden is further exacerbated by increased nursing workload due to poor staffing, as we found in this study. Poor staffing affected nurses and doctors in all three hospitals and was a common factor influencing the detection and response to patient deterioration. These findings are consistent with those from other studies in Singapore and the United Kingdom, where poor staffing led to increased workloads and therefore was a barrier to early detection and response to the clinical deterioration [26, 54]. The World Health Organization acknowledges the shortage of healthcare workers (HCWs) globally but reports that nurses are the most affected cadre of HCWs. The African region is among the most affected regions, with an estimated shortage of 4.2 million HCWs as of 2013 [55]. In Kenya, several studies have highlighted understaffing problems [56–58]. Our study adds to this literature by illustrating how sub-optimal staffing at the ward level influences the capacity of nurses to identify deteriorating patients and respond timely. Effective communication is crucial for quickly identifying, escalating, and responding to clinical deterioration. Additionally, it is essential that there are laid down processes to enable the clinician to communicate the information clearly, logically and precisely [59, 60]. Furthermore, to guarantee safe and reliable care of the deteriorating patient, effective communication requires clinicians' teamwork based on mutual respect, problem-solving and sharing of ideas [61]. But as reported by the nurses from all three hospitals, they perceived that there was inadequate communication between clinicians, a lack of a process for ensuring timely management when patients deteriorate, and a low level of teamwork and collaboration amongst the different cadres of healthcare workers in agreement with findings from other studies [29, 62–64]. The importance of effective communication and teamwork cannot be understated in a healthcare system that is becoming increasingly complex, fragmented and with many professionals with different specialisations. Therefore, hospitals must implement measures and strategies to ensure structured communication processes among clinicians, clear guidelines and procedures for communicating deteriorations and creating a safety culture promoting teamwork. Study Limitations This study utilised data from medical records reviews and interviews. Our findings, particularly those drawn from in-depth interviews, may have been affected by social desirability bias. However, we attempted to offset this by including a review of documents to triangulate self-reported findings related to documentation practices by the nurses. Further, conducting the study in three hospitals was another form of triangulation. We did not find significant differences across the study hospitals regarding documentation practices and identifying and responding to deteriorating patients. Carrying out the study in two counties limits the generalisability of our findings. However, we have provided an adequate description of the study settings, particularly the study hospitals. We believe these findings can support readers to exercise judgement in determining the transferability of our study findings. Conclusion Nurses have a critical role in recognising and responding to deteriorating patients. However, this study has demonstrated that nurses did not consistently monitor and document vital signs. Further, these nurses worked in sub-optimal ward environments characterised by inadequate and poorly functioning monitoring equipment; high workload because of staff shortages; sub-optimal communication during emergencies; gaps in teamwork and little training on actions to take when patients deteriorate at the ward level. All these features can negatively affect patient safety, quality of care, and patient outcomes at the ward level. Paying closer attention to the context in which nurses provide care can help to support nurses in promptly identifying and responding to deteriorating patients. Some hospital-level actions that could be taken towards this include providing adequate equipment for monitoring patients; simplifying the chain of communication when patients deteriorate and ensuring awareness of how such communication should be done; providing training targeted at nurses and other cadres of healthcare workers at ward level on collaborative practices including specific packages such as BLS and ACLS. This study also highlights a broad health system challenge beyond the influence of nurse managers at the ward and hospital level, that of the health worker shortage. The severe shortages reported in this study could hinder safe patient care. They also illustrate a need for policies and strategies that combine short, medium, and long-term approaches to attracting and retaining ward-level healthcare workers. Important considerations include the skill mix of nurses, provisions for conducting a rational review of staffing norms with the input of nursing managers, and engagement with training institutions to have more nurses in the pipeline. Abbreviations ACLS - Advanced Cardiac Life Support; BLS - Basic Life Support; BP - Blood pressure; BVM - Bag Valve Mask; CCU - Critical Care Unit; CPR - Cardiopulmonary Resuscitation; HCWs - Healthcare Workers; HDU - High Dependency Unit; HR - Heart rate; ICU - Intensive Care Unit; LOC - Level of consciousness; MO - Medical Officer; PPE - Personal Protective Equipment; RR - Respiratory rate; Sp02 - Oxygen saturation; Temp –Temperature. Declarations Ethics approval and consent to participate The study was approved by Pwani University Ethics Review Committee (ERC/PU-STAFF/001/2020). A research permit to conduct the study was obtained from the National Commission for Science, Technology & Innovation (NACOSTI/P/20/4890). Informed consent was obtained from all study participants and the study was carried out in accordance with The Helsinki Declaration and institutional procedures. Consent for publication Not applicable. Availability of data and materials The data that support the findings of this study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was supported by the 2019 Sigma/Alpha Eta Collaborative Research Grant from Sigma Theta Tau International Honor Society of Nursing. Authors' contributions NM, NK, MB: conceived and designed the study. NM, NK, MN were responsible for the data acquisition, collection analysis, and interpretation. NM, NK, MN were involved in the drafting of the manuscript. NK, MN, MB did the critical revision of the manuscript. All the authors read and approved the final manuscript. Acknowledgements The authors wish to thank all the nurses who participated in this study. We also thank all the medical records personnel who assisted in the retrieval of the patient's files in the study hospitals Authors' information Authors and Affiliations NM - Department of Medical-Surgical Nursing and Preclinical Science, School of Health Sciences, Kenyatta University, Nairobi, Kenya. NK - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya. MN - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya. MB - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya. References Hall K, Lim A, Gale B. (2020) Failure To Rescue. In: Hall KK, Shoemaker-Hunt S, Hoffman L, Making Healthcare Safer III: A Critical Analysis of Existing and Emerging Patient Safety Practices. Agency for Healthcare Research and Quality (US), Rockville (MD), pp 2–1 to 2–16 Silber JH, Williams SV, Krakauer H, Schwartz S. Hospital and Patient Characteristics Associated With Death After Surgery: A Study of Adverse Occurrence and Failure to Rescue. Med Care. 1992;30:615–29. Donaldson LJ, Panesar SS, Darzi A. Patient-Safety-Related Hospital Deaths in England: Thematic Analysis of Incidents Reported to a National Database, 2010–2012. PLoS Med. 2014;11:e1001667. English M, Mwaniki P, Julius T, Chepkirui M, Gathara D, Ouma PO, Cherutich P, Okiro EA, Snow RW. Hospital Mortality – a neglected but rich source of information supporting the transition to higher quality health systems in low and middle income countries. BMC Med. 2018;16:32. Gong X-Y, Wang Y-G, Shao H-Y, Lan P, Yan R-S, Pan K-H, Zhou J-C. A rapid response team is associated with reduced overall hospital mortality in a Chinese tertiary hospital: a 9-year cohort study. Ann Transl Med. 2020;8:317–7. Kurita T, Nakada T, Kawaguchi R, Fujitani S, Atagi K, Naito T, Arai M, Arimoto H, Masuyama T, Oda S. Impact of increased calls to rapid response systems on unplanned ICU admission. Am J Emerg Med. 2020;38:1327–31. Andersen LW, Kim WY, Chase M, Berg K->, Mortensen M, Moskowitz SJ, Novack A, Cocchi V, Donnino MN MW. The prevalence and significance of abnormal vital signs prior to in-hospital cardiac arrest. Resuscitation. 2016;98:112–7. Churpek MM, Adhikari R, Edelson DP. The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016;102:1–5. Oh H, Lee K, Seo W. Temporal patterns of change in vital signs and Cardiac Arrest Risk Triage scores over the 48 hours preceding fatal in-hospital cardiac arrest. J Adv Nurs. 2016;72:1122–33. Zografakis-Sfakianakis M, De Bree E, Linardakis M, Messaritaki A, Askitopoulou H, Papaioannou A, Aggouridakis P. The value of the Modified Early Warning Score for unplanned Intensive Care Unit admissions of patients treated in hospital general wards. Int J Nurs Pract. 2018;24:e12632. Jones DA, DeVita MA, Bellomo R. Rapid-Response Teams. N Engl J Med. 2011;365:139–46. Petersen JA. Multiple Parameter Track and Trigger Systems. In: DeVita MA, Hillman K, Bellomo R, Odell M, Jones DA, Winters BD, Lighthall GK, editors. Textbook of Rapid Response Systems. Cham: Springer International Publishing; 2017. pp. 87–94. Australian Commission on Safety and Quality in Health Care. (2012) Essential element 2: escalation of care. https://www.safetyandquality.gov.au/sites/default/files/migrated/Low-res-PDF-Essential-element-2-escalation-of-care.pdf . Accessed 7 Nov 2022 Ozekcin LR, Tuite P, Willner K, Hravnak M. Simulation Education: Early Identification of Patient Physiologic Deterioration by Acute Care Nurses. Clin Nurse Specialist. 2015;29:166–73. Considine J, Rhodes K, Jones D, Currey J. Systems for recognition and response to clinical deterioration in Victorian emergency departments. Australasian Emerg Care. 2018;21:3–7. Barasa EW, Ouma PO, Okiro EA. Assessing the hospital surge capacity of the Kenyan health system in the face of the COVID-19 pandemic. PLoS ONE. 2020;15:e0236308. Murthy S, Adhikari NK. Global Health Care of the Critically Ill in Low-Resource Settings. Annals ATS. 2013;10:509–13. Oketch UK, Chokwe TM, Mung’ayi V. The operational setup of intensive care units in a low income country in East Africa: a cross sectional survey. East Afr Med J. 2015;92:72–80. Waweru-Siika W, Mung’ayi V, Misango D, Mogi A, Kisia A, Ngumi Z. The history of critical care in Kenya. J Crit Care. 2020;55:122–7. Mushta J, Rush L, Andersen K E. Failure to rescue as a nurse-sensitive indicator. Nurs Forum. 2018;53:84–92. Al-Thubaity D, Williamson S, Leavey R, Tume LN. Newly qualified Saudi nurses’ ability to recognize the deteriorating child in hospital. Nurs Crit Care. 2019;24:263–7. Azimirad M, Magnusson C, Wiseman A, Selander T, Parviainen I, Turunen H. Nurses’ ability to timely activate rapid response systems for deteriorating patients: A comparative case scenario study between Finnish and British nurses. Intensive and Critical Care Nursing. 2020;60:102871. Bliss M, Aitken LM. Does simulation enhance nurses’ ability to assess deteriorating patients? Nurse Educ Pract. 2018;28:20–6. Cardona-Morrell M, Prgomet M, Lake R, Nicholson M, Harrison R, Long J, Westbrook J, Braithwaite J, Hillman K. Vital signs monitoring and nurse–patient interaction: A qualitative observational study of hospital practice. Int J Nurs Stud. 2016;56:9–16. Hands C, Reid E, Meredith P, Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Patterns in the recording of vital signs and early warning scores: compliance with a clinical escalation protocol. BMJ Qual Saf. 2013;22:719–26. Redfern OC, Griffiths P, Maruotti A, Recio Saucedo A, Smith GB. The association between nurse staffing levels and the timeliness of vital signs monitoring: a retrospective observational study in the UK. BMJ Open. 2019. https://doi.org/10.1136/bmjopen-2019-032157 . Dalton M, Harrison J, Malin A, Leavey C. Factors that influence nurses’ assessment of patient acuity and response to acute deterioration. Br J Nurs. 2018;27:212–8. Massey D, Chaboyer W, Aitken L. Nurses’ perceptions of accessing a Medical Emergency Team: A qualitative study. Australian Crit Care. 2014;27:133–8. Mohammmed Iddrisu S, Hutchinson AF, Sungkar Y, Considine J. Nurses’ role in recognising and responding to clinical deterioration in surgical patients. J Clin Nurs. 2018;27:1920–30. Mok W, Wang W, Cooper S, Ang ENK, Liaw SY. Attitudes towards vital signs monitoring in the detection of clinical deterioration: scale development and survey of ward nurses. Int J Qual Health Care. 2015;27:207–13. Pantazopoulos I, Tsoni A, Kouskouni E, Papadimitriou L, Johnson EO, Xanthos T. Factors influencing nurses’ decisions to activate medical emergency teams: MET activation. J Clin Nurs. 2012;21:2668–78. Creswell JW. Research design: qualitative, quantitative, and mixed methods approaches. 4th ed. Thousand Oaks: SAGE Publications; 2014. Ministry of Health. Kenya Health Sector Strategic Plan - July 2018–June 2023. Nairobi, Kenya: Government of the Republic of Kenya; 2018. DeVita MA, Smith GB, Adam SK et al. (2010) “Identifying the hospitalised patient in crisis”--a consensus conference on the afferent limb of rapid response systems. Resuscitation 81:375–382 McGhee TL, Weaver P, Solo S, Hobbs M. Vital signs reassessment frequency recommendation. Nurs Manag. 2016;47:11–2. Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3:77–101. Maguire M, Delahunt B. Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. AISHE-J. 2017;9:3351–14. Daw W, Kaur R, Delaney M, Elphick H. Respiratory rate is an early predictor of clinical deterioration in children. Pediatr Pulmonol. 2020;55:2041–9. Mochizuki K, Shintani R, Mori K, Sato T, Sakaguchi O, Takeshige K, Nitta K, Imamura H. Importance of respiratory rate for the prediction of clinical deterioration after emergency department discharge: a single-center, case-control study. Acute Med Surg. 2017;4:172–8. Ogero M, Ayieko P, Makone B, Julius T, Malla L, Oliwa J, Irimu G, English M. An observational study of monitoring of vital signs in children admitted to Kenyan hospitals: an insight into the quality of nursing care? J Global Health. 2018;8:010409. Stevenson JE, Israelsson J, Petersson G, Bath PA. Factors influencing the quality of vital sign data in electronic health records: A qualitative study. J Clin Nurs. 2018;27:1276–86. Ullah E, Albrett J, Khan O, Matthews C, Perry I, GholamHosseini H, Lu J. Workload involved in vital signs-based monitoring & responding to deteriorating patients: A single site experience from a regional New Zealand hospital. Heliyon. 2022;8:e10955. Otiangala D, Agai NO, Olayo B, et al. Oxygen insecurity and mortality in resource-constrained healthcare facilities in rural Kenya. Pediatr Pulmonol. 2020;55:1043–9. World Health Organization, United Nations Children’s Fund (UNICEF). WHO-UNICEF technical specifications and guidance for oxygen therapy devices. Geneva: World Health Organization; 2019. Dauncey JW, Olupot-Olupot P, Maitland K. Healthcare-provider perceptions of barriers to oxygen therapy for paediatric patients in three government-funded eastern Ugandan hospitals; a qualitative study. BMC Health Serv Res. 2019;19:335. Ogot M, Ayah R, Muriuki R, Nyangaya J. Oxygen Access and Affordability in Health Facilities in Kenya. Kenya Policy Briefs. 2021;2:53–4. Rahman AE, Mhajabin S, Dockrell D, Nair H, El Arifeen S, Campbell H. Managing pneumonia through facility-based integrated management of childhood management (IMCI) services: an analysis of the service availability and readiness among public health facilities in Bangladesh. BMC Health Serv Res. 2021;21:667. Tolla HS, Woyessa DB, Balkew RB, Asemere YA, Fekadu ZF, Belete AB, Gartley M, Battu A, Lam F, Desale AY. Decentralizing oxygen availability and use at primary care level for children under-five with severe pneumonia, at 12 Health Centers in Ethiopia: a pre-post non-experimental study. BMC Health Serv Res. 2022;22:676. Calderon R, Morgan MC, Kuiper M, Nambuya H, Wangwe N, Somoskovi A, Lieberman D. Assessment of a storage system to deliver uninterrupted therapeutic oxygen during power outages in resource-limited settings. PLoS ONE. 2019;14:e0211027. Graham HR, Bagayana SM, Bakare AA, Olayo BO, Peterson SS, Duke T, Falade AG. Improving Hospital Oxygen Systems for COVID-19 in Low-Resource Settings: Lessons From the Field. Glob Health Sci Pract. 2020;8:858–62. Collins S, Couture B, Kang MJ, Dykes P, Schnock K, Knaplund C, Chang F, Cato K. Quantifying and Visualizing Nursing Flowsheet Documentation Burden in Acute and Critical Care. AMIA Annu Symp Proc. 2018;2018:348–57. Dall’Ora C, Griffiths P, Hope J, Briggs J, Jeremy J, Gerry S, Redfern OC. How long do nursing staff take to measure and record patients’ vital signs observations in hospital? A time-and-motion study. Int J Nurs Stud. 2021;118:103921. Tasew H, Mariye T, Teklay G. Nursing documentation practice and associated factors among nurses in public hospitals, Tigray, Ethiopia. BMC Res Notes. 2019;12:612. Chua WL, Legido-Quigley H, Ng PY, McKenna L, Hassan NB, Liaw SY. Seeing the whole picture in enrolled and registered nurses’ experiences in recognizing clinical deterioration in general ward patients: A qualitative study. Int J Nurs Stud. 2019;95:56–64. World Health Organization. Global strategy on human resources for health: workforce 2030. Geneva: World Health Organization; 2016. Miseda MH, Were SO, Murianki CA, Mutuku MP, Mutwiwa SN. The implication of the shortage of health workforce specialist on universal health coverage in Kenya. Hum Resour Health. 2017;15:80. Munywoki J, Kagwanja N, Chuma J, Nzinga J, Barasa E, Tsofa B. Tracking health sector priority setting processes and outcomes for human resources for health, five-years after political devolution: a county-level case study in Kenya. Int J Equity Health. 2020;19:165. Nyawira L, Tsofa B, Musiega A, et al. Management of human resources for health: implications for health systems efficiency in Kenya. BMC Health Serv Res. 2022;22:1046. Liu SI, Shikar M, Gante E, Prufeta P, Ho K, Barie PS, Winchell RJ, Lee JI. Improving Communication and Response to Clinical Deterioration to Increase Patient Safety in the Intensive Care Unit. Crit Care Nurse. 2022;42:33–43. Manojlovich M, Krein SL. We don’t talk about communication: why technology alone cannot save clinically deteriorating patients. BMJ Qual Saf. 2022;31:698–700. Fuchshuber P, Greif W. Creating Effective Communication and Teamwork for Patient Safety. In: Romanelli JR, Dort JM, Kowalski RB, Sinha P, editors. The SAGES Manual of Quality, Outcomes and Patient Safety. Cham: Springer International Publishing; 2022. pp. 443–60. Dinius J, Philipp R, Ernstmann N, Heier L, Göritz AS, Pfisterer-Heise S, Hammerschmidt J, Bergelt C, Hammer A, Körner M. Inter-professional teamwork and its association with patient safety in German hospitals—A cross sectional study. PLoS ONE. 2020;15:e0233766. Jones A, Johnstone M-J. Managing gaps in the continuity of nursing care to enhance patient safety. Collegian. 2019;26:151–7. Newman D, Hofstee F, Bowen K, Massey D, Penman O, Aggar C. A qualitative study exploring clinicians’ attitudes toward responding to and escalating care of deteriorating patients. J Interprof Care. 2022. https://doi.org/10.1080/13561820.2022.2104231 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Mar, 2024 Read the published version in BMC Nursing → Version 1 posted Editorial decision: Major revision 08 Aug, 2023 Reviews received at journal 16 Jul, 2023 Reviews received at journal 10 Jul, 2023 Reviewers agreed at journal 29 Jun, 2023 Reviewers agreed at journal 29 Jun, 2023 Reviewers invited by journal 16 Jun, 2023 Editor assigned by journal 15 Jun, 2023 Editor invited by journal 13 Mar, 2023 Submission checks completed at journal 13 Mar, 2023 First submitted to journal 27 Feb, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2633455","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":182916408,"identity":"44ef81a0-0c32-4922-9552-82c1a9f1b4ab","order_by":0,"name":"Nickcy Mbuthia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYDACCQYGZgYDBhDJDCRtDCDCB/BqYWxG0pJGrBYIAGk5TFiL7uwe88cFBXYM5uzMjw1+tp03NjjA/PADwxkbnFrM7pwxbJ5hkMxg2cxmnNjbdtvM4ACbsQTDjTTcWm7kGDbzGABD4DAP82HGtts2BgcYzBgYPhwmpKUepuUcUAv7N6CW/4S0HAZrSWZsOwB0GA/Qlhu4/W9251jhbB6D40BdbMaGPeeSjSUP8xRLJJxJxq3ldvOGzzx/quUMzh9+LPGjzM6w73j7xg8fjtnh1AIDPGCSkY0BEj0JBDXAwR/ilY6CUTAKRsHIAQDoZ1EPwnxT+QAAAABJRU5ErkJggg==","orcid":"","institution":"Kenyatta University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Nickcy","middleName":"","lastName":"Mbuthia","suffix":""},{"id":182916409,"identity":"f159b779-877c-4149-bd2b-9d4689a00d8e","order_by":1,"name":"Nancy Kagwanja","email":"","orcid":"","institution":"KEMRI Centre for Geographic Medicine Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nancy","middleName":"","lastName":"Kagwanja","suffix":""},{"id":182916410,"identity":"09df88dc-c4d1-4e9a-9112-0ded6227ce2b","order_by":2,"name":"Moses Ngari","email":"","orcid":"","institution":"KEMRI Centre for Geographic Medicine Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Moses","middleName":"","lastName":"Ngari","suffix":""},{"id":182916411,"identity":"e8f608c4-5b71-437a-bcf2-9128063ad170","order_by":3,"name":"Mwanamvua Boga","email":"","orcid":"","institution":"KEMRI Centre for Geographic Medicine Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mwanamvua","middleName":"","lastName":"Boga","suffix":""}],"badges":[],"createdAt":"2023-02-27 10:29:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2633455/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2633455/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12912-024-01822-2","type":"published","date":"2024-03-01T15:01:47+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":34315216,"identity":"6cacdc86-5b47-46af-955e-73b39845a310","added_by":"auto","created_at":"2023-03-15 19:19:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53562,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA stack bar chart showing proportions of vital events documented at the six-time points.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2633455/v1/51165e60a94b87afd26b0862.png"},{"id":51958284,"identity":"3246475a-fd9f-4461-9e8f-9be510503f70","added_by":"auto","created_at":"2024-03-04 15:14:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":631225,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2633455/v1/8a1a086d-3f5a-4769-8aaf-88db4f0e6183.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eGeneral Ward Nurses Detection and Response to Clinical Deterioration in Three Hospitals at the Kenyan Coast: A Convergent Parallel Mixed Methods Study\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eFailure to rescue is a patient safety and healthcare quality measure, which refers to the delay or failure to detect and respond to clinical deterioration in hospitalised patients, leading to mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In-hospital mortality is increasingly being recognised as a measure of service provision quality and a key indicator of patient safety [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although patients inevitably die in the hospital, clinicians should be able to detect the deterioration in the patient early enough and act promptly to prevent death. Early detection and response to the changes in vital signs and physiological parameters in hospitalised patients are essential in reducing the risk of preventable death and preventing unplanned admission into critical care units [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Numerous studies have established that there are physiological antecedents before a cardiac arrest occurs in a hospitalised patient, allowing the clinician to identify the deterioration and act promptly [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatient monitoring, which involves the assessment of vital signs and physiological changes, allows for early detection of these antecedents of patient deterioration. Subsequently, based on monitoring criteria, the clinician triggers or activates the rapid response team to treat the deteriorating patients before adverse events occur [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The most commonly used monitoring and call criteria for rapid response include abnormalities in physiologic measures such as respiratory rate, heart rate, systolic blood pressure, oxygen saturation, acute change in mental status, and the clinician's significant concern about the patient's condition [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Regularly monitoring these physiologic measures allows the clinician to identify deterioration and thus act hastily to prevent further deterioration by escalating and communicating the information clearly to the individual or team that shall manage the patient and prevent further deterioration.\u003c/p\u003e \u003cp\u003eEscalation of care in most institutions is guided by institutional protocols that clearly outline the actions that the clinician can implement until they are satisfied that the correct response has been achieved. These actions include a change in monitoring frequency, possible modifications of care, a review of the patient by a senior medical officer, seeking assistance from an intensive care specialist, or activation of the Emergency Response System [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition, a concise, efficient and accurate flow of information about the deteriorating patient is a fundamental component of the escalation of care [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The different modes to communicate the deterioration of care include face-to-face communication, overhead announcement within the hospital, mobile and landline telephones, and hospital alarms [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Whichever mode is used to communicate deterioration, it is critical to use a common language using a structured communication tool to ensure a timely response.\u003c/p\u003e \u003cp\u003eIn Kenya, like most low and middle-income countries, patient complexity is increasing because of higher morbidity due to non-communicable diseases, road traffic accidents, and a longer life expectancy. This has led to a higher demand for critical care services as compared to developed countries, yet the availability of these services is limited [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This has therefore led to acutely ill patients being managed in the general medical and surgical wards. In the critical care units (CCUs), patient's vital signs are continuously and closely monitored with monitoring equipment and technologies, and therefore detection of deterioration and response is timely. Additionally, the CCUs are well equipped with resuscitation equipment and are adequately staffed with staff trained in responding to changes in patient deterioration. However, in the general wards where most acute patient deterioration occurs, patient surveillance is done periodically. Therefore, it depends on the clinicians' ability to recognise and respond to the deterioration.\u003c/p\u003e \u003cp\u003eBecause of the role that nurses play in early deterioration identification, failure to rescue may be very sensitive to nursing care. According to Mushta et al. (2018) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], failure to rescue as a nurse-sensitive indicator includes failure to recognise changes in patient condition, failure to escalate the changes and inadequate decision-making. Patient assessment and monitoring is a fundamental nursing competence; therefore, nurses carry the highest responsibility in detecting and responding to patient deterioration. However, research shows that nurses fail to recognise and respond timely to patients' deterioration [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVital signs monitoring is fundamental to nursing, whereby the nurse must assess, document, and interpret vital signs promptly and escalate any abnormal values. However, research shows that monitoring, documentation, and reporting of vital signs are often irregular, incomplete, and not used to make clinical decisions [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Documented factors that contribute to the failure of a nurse to recognise and respond include the lack of knowledge and skills in the detection of warning signs, poor or absent monitoring of the patient's vital signs, difficulty in prioritising competing demands with increasing workload and fear of reporting the deterioration [\u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Notably, most of the literature on the general ward nurses' issues and challenges in detecting and escalating patient deterioration has been generated in high-income country settings, with little literature from developing countries. We did not identify any studies reporting on the Kenyan context. Therefore, this study aimed to examine the general ward nurses' vital signs documentation practices in the deteriorating patient and explore the factors influencing their ability to detect and respond to clinical deterioration in three Kenyan hospitals.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign\u003c/h2\u003e \u003cp\u003eA convergent parallel mixed-methods design was utilised to achieve the objectives. A retrospective descriptive design was used to retrieve quantitative data from medical records of patients who had suffered a cardiac arrest and died in the previous year in the study hospitals' general medical and surgical wards. Specifically, the study sought to determine the extent to which the nurses monitored and documented the patients' vital signs 24 hours before a cardiac arrest (death) occurred. Additionally, qualitative data was collected by conducting in-depth interviews with nursing staff, including ward managers, to understand better the factors that influence the ability to detect and respond to clinical deterioration. Data from the two methods were analysed separately, and the results were compared and related. Each type of data was used to validate the other during the interpretation, creating solid foundations through which we could better achieve the study objectives [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSetting\u003c/h2\u003e \u003cp\u003eThe study was undertaken in the adult medical and surgical wards of three purposefully selected hospitals in Kenya's coastal region. We identified hospitals with prior contact or linkage with the research team to minimise trust concerns related to our data collection. One hospital in Mombasa County was a Level Five hospital (Hospital A), while the other two were Level Four hospitals (Hospital B and C) in Kilifi County. Level Four and Five hospitals are secondary-level referral hospitals in the Kenyan health system. Level Five hospitals offer a more comprehensive array of specialised curative services than level 4 hospitals [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The three hospitals are relatively homogeneous in their organisational structure, resource availability, and the populations they serve.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSample and Sampling technique\u003c/h2\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eNurses' documentation review\u003c/h2\u003e \u003cp\u003eThe sample comprised the records of patients who suffered a cardiac arrest and died in the adult medical and surgical wards the previous year. We decided to review the records of these patients because it is well documented that patients frequently display physiological changes as much as 24 hours before a cardiac arrest and death occur [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, we included all records from male and female patients 18 years and older and those admitted for more than 24hrs between January and December 2019.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eKey informant interviews\u003c/h2\u003e \u003cp\u003eThe sample for the interviews was purposefully drawn from the registered nurses working in the adult medical wards and the surgical wards in the three hospitals. Therefore, we included in the interviews nurses who had worked in the adult medical and surgical wards in the study hospitals for at least six months.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData collection procedures\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eDocumentation Review\u003c/h2\u003e \u003cp\u003eIn hospital B, a list of all the deaths that occurred in the adult medical and surgical wards in 2019 was obtained from an electronic database. A systematic sampling technique was used to obtain the sample. It was possible to obtain the patient's admission number from the database, which was then used to retrieve the patient's file in the medical records department. Hospitals A and C had no databases of the deaths available. Therefore, with the assistance of the medical records personnel, the data collectors retrieved all the files of the patients who had died in the respective hospitals in 2019. Subsequently, they selected the files from the adult medical and surgical wards from which they randomly selected and analysed files for each month in 2019.\u003c/p\u003e \u003cp\u003eTo examine if, which, where, and how physiological parameters of the patients were documented before patient deterioration, the sampled records were reviewed for the nursing documentation of six vital signs 24 hours before death. The vital signs were respiratory rate in breaths per minute, systolic blood pressure in millimetres of mercury (mmHg), oxygen saturation as a percentage, heart rate in beats per minute, temperature in degrees centigrade, and consciousness level. According to the literature, to detect patient deterioration, these are the minimum physiological parameters that trigger the nurse to call for help, and they should be monitored at least every 4 hours [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Data were collected using a predesigned tool developed by the researchers based on recommendations from literature and guidelines on documentation of patients' physiological observations. In the data collection tool, the research assistants first identified which document the vital signs were retrieved from, either the vital signs observation chart or the nursing notes (Kardex). According to the literature, acute patients' vital signs should be monitored every four hours unless the patient's condition or specific treatment requires more frequent measurements[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, the data collection tool also captured the last six vital signs documented by the nurse in the previous 24 hours before death occurred. If none of the vital signs had been recorded in the 24 hours preceding the cardiac arrest, the last recorded vital sign(s) was captured, including the time it was recorded.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eKey informant interviews\u003c/h2\u003e \u003cp\u003eWe conducted in-depth, semi-structured in-person interviews in each hospital to better understand the factors that influence the ability to detect and escalate clinical deterioration. An interview guide was used to explore the nurses' experiences in caring for the deteriorating patient, the challenges in detecting deterioration, their actions when a patient deteriorates, and the communication practices for escalating the deterioration. In addition, examples of clinical deterioration were used to prompt the recall of similar situations experienced by participants. The scenarios aimed to trigger reflection on personal experiences.\u003c/p\u003e \u003cp\u003e We sought informed consent before conducting interviews. The interviews were conducted in offices within the nurses' respective wards, where we anticipated few interruptions. However, because the interviews were conducted during regular shift hours, the nurses' colleagues were informed of the locations in case of any urgent situations.\u003c/p\u003e \u003cp\u003eAll interview sessions lasted approximately 20\u0026ndash;30 min and were recorded using an audio recorder. The interviews took place in an office setting that guaranteed privacy and an acoustically conducive environment. Since data collection occurred during the COVID-19 pandemic, we adopted prevention measures such as wearing masks and social distancing during the interviews.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eAnalysis of the documentation\u003c/h2\u003e \u003cp\u003eAll quantitative data were extracted from patient records using a standard tool and entered into the Epidata database. All categorical patient characteristics were reported as frequencies and their respective percentage. Age in years was reported as median and interquartile range (IQR) because it was skewed. Documentation for each vital event was reported as the number of patients with a vital event documented at each time point. Statistical analyses were conducted using Stata (Version 17.0, College Station, Texas, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eAnalysis of the interviews\u003c/h2\u003e \u003cp\u003eFor the qualitative data, all audio recordings and field notes were maintained in a secure location. A professional transcriber transcribed the audio recordings into an MS WORD document. The researchers listened to the recordings and compared them with the transcription to ensure accuracy and enhance familiarisation with the data. We adopted a thematic analysis approach, as described by Braun \u0026amp; Clarke, 2006 [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], where we sought to identify patterns in the reviewed transcripts. Our analysis was deductive, driven by the research objectives and our focus on nurses' experiences of patient clinical deterioration. The analysis process involved familiarisation with the data, generating initial codes, searching for themes, reviewing themes, defining themes and writing up the report [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The process, though described step-wise, was iterative.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e Ethical review and approval were obtained from the Pwani University Ethics Review Committee (ERC/PU-STAFF/001/2020). A research permit to conduct the study was obtained from the National Commission for Science, Technology \u0026amp; Innovation (NACOSTI/P/20/4890). Upon ethical approval, permission to collect data was granted by the respective hospital boards after assurances to adhere to the COVID-19 preventive measures to protect the study participants and the data collectors. Interview participation was completely voluntary. The participating nurses were provided with written information about the research and their rights to the study. The participants were requested to sign and date the informed consent form upon agreement.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative analysis results\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eA total of 405 records were reviewed, 186 (46%), 135 (33%), and 84 (21%) in Hospital A, Hospital B, and Hospital C, respectively. Their median [IQR] age was 54 [36 to 68] years. Two hundred and forty-two (60%) were male. The most frequent diagnoses identified from the reviewed patient files were cancer 41 (10%), Cerebrovascular accident 30 (7.4%), Heart failure 27 (6.7%), Tuberculosis 25 (6.2%) and Meningitis 24 (5.9%) shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA (N\u0026thinsp;=\u0026thinsp;186)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB (N\u0026thinsp;=\u0026thinsp;135)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC (N\u0026thinsp;=\u0026thinsp;84)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;405)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e242 (60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e163 (40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian [IQR]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 [35‒65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 [37‒70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.5 [42‒70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54 [36‒68]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeading primary diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41 (10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular accident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (7.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (6.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeningitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (5.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (5.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2,2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (5.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastroenteritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (9.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 (4.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (3.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (4.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (3.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 (19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResults are N (%) unless specified, IQR; Interquartile range.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003ePatient deterioration nursing documentation\u003c/h2\u003e \u003cp\u003eOf the 405 patient records reviewed, the vital signs were documented in the nursing notes (Kardex) and vital signs observation chart among 391 (97%) and 14 (3.5%), respectively. During the 24 hours prior to patient deterioration/death reviewed, 283 (70%) patients had no respiratory rate documented, 77 (19%) had only one documentation of respiratory rate, while only 5/405 (1.2%) had documentation for all the six-time points. There was no heart rate documentation among 45 (11%) patients, while 87 (21%), 107 (26%) and 101 (25%) had one, two and three documentations, respectively. The temperature was not documented among 115 (28%) patients, while it was documented once, twice and thrice among 104 (26%), 92 (23%) and 65 (16%) patient files, respectively. There were 43 (11%) patient files with no blood pressure documentation, and it was documented among 91 (22%), 107 (26%) and 102 (25%) patients once, twice and thrice, respectively. Oxygen saturation was not documented among 116 (29%) patients but was documented once, twice and thrice among 91 (22%), 80 (20%) and 62 (15%) patients, respectively. Almost nine in every ten patients (N\u0026thinsp;=\u0026thinsp;356, 88%) had no documentation for the level of consciousness but was documented once, twice and thrice among 31 (7.7%), 7 (1.7%) and 3 (0.7%) patients, respectively, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Less than 2% of patients had any vital signs documented for all the six-time points; respiratory rate (N\u0026thinsp;=\u0026thinsp;5, 1.2%), heart rate (N\u0026thinsp;=\u0026thinsp;6, 1.5%), temperature (N\u0026thinsp;=\u0026thinsp;6, 1.5%), blood pressure (N\u0026thinsp;=\u0026thinsp;6, 1.5%), oxygen saturation (N\u0026thinsp;=\u0026thinsp;5, 1.2%) and level of consciousness (N\u0026thinsp;=\u0026thinsp;2, 0.5%) as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient deterioration nursing documentation review.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVital events\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003eNumber of final six vital signs documented\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e283 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (6.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e101 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14 (3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e102 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43 (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6 (1.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxygen Saturation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of consciousness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e356 (88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eResults are N (%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eQualitative analysis results\u003c/h2\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003eParticipants characteristics\u003c/h2\u003e \u003cp\u003eWe conducted 24 interviews with respondents across the three study hospitals. Of these 24, there were two senior hospital management nurses and six ward managers. All the nurse ward managers reported carrying out clinical nursing duties and ward administration responsibilities. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below summarises the participants' characteristics related to their gender and how long they had provided nursing services.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInterview respondent characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHospital A (N\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHospital B (N\u0026thinsp;=\u0026thinsp;8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHospital C (N\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall duration as a nurse (years)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u0026ndash;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo. of years working in current ward*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6months-1year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2-3years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4-5years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Two nurses from Hospitals B and C are not included in the number of nurses working in the wards among the study respondents because they were hospital nurse managers with mainly administrative and managerial responsibilities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eWard Characteristics\u003c/h2\u003e \u003cp\u003e\u003cb\u003eTable\u0026nbsp;4\u003c/b\u003e summarises some hospital and ward characteristics that appeared to influence the extent to which nurses could monitor the patients and document their findings. In hospitals B and C, the medical and surgical patients were nursed in the same ward. The wards were distinguished as male and female, with the female wards comprising patients with medical, surgical (general surgical and orthopaedic) and gynaecological conditions. The male wards (hospitals B and C) also admitted medical and surgical patients. Further, some admitted patients had psychiatric conditions in hospital C. Hospital A had separate male and female medical and surgical wards. As a result, hospital A respondents were more in number (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) compared to Hospital B and C. Hospital A had an Intensive Care Unit (ICU) with a capacity of 15 beds (\u003cb\u003eTable\u0026nbsp;4\u003c/b\u003e), where patients needing critical care from Hospitals B and C were also referred. This was a challenge, as quoted by one of the participants:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e\u003cem\u003e\"The person who is receiving the call will tell you my ICU is full. What will you do after you hear that? How will you verify if ICU is full? You have very critical patient who really, really needs ICU, needs ventilation\u0026hellip;The present condition is going down you end up risking with fluids, with medication, you can put oxygen and that's all. As we wait like 3,4 hours you call again you ask. Patients end up staying for like for 3, 4 days even without going for an ICU. So we lose patients just like that\" (B006)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cp\u003e\u003cstrong\u003eTable 4: Ward characteristics in study hospitals\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWard Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.750830564784053%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital A\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital C\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eType of patients admitted into wards\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.750830564784053%\"\u003e\n \u003cp\u003eSeparate medical and surgical wards for female and male patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMixed female ward (admitting, medical, surgical and gynaecological patients)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMixed female ward (admitting, medical, surgical and gynaecological patients)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eICU or HDU in a hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.750830564784053%\"\u003e\n \u003cp\u003eICU present\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eNo ICU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eHDU present\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eNo. of nurses working in the study wards\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.750830564784053%\"\u003e\n \u003cp\u003eMale surgical: 22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMale ward: 10\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMale ward: 10 (but two away on study leave)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003eFemale surgical: 11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.03769401330377%\"\u003e\n \u003cp\u003eMale medical: 21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"33.48115299334812%\"\u003e\n \u003cp\u003eFemale ward: 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"33.48115299334812%\"\u003e\n \u003cp\u003eFemale ward: 8 nurses (2 away on leave)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003eFemale medical: 20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eThe bed capacity of the study ward\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"24.750830564784053%\"\u003e\n \u003cp\u003eMale surgical: 70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMale ward: 34 patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"25.083056478405314%\"\u003e\n \u003cp\u003eMale ward: can hold up to 60 patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003eFemale surgical: 40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"33.03769401330377%\"\u003e\n \u003cp\u003eMale medical: 72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"33.48115299334812%\"\u003e\n \u003cp\u003eFemale ward: 32 patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"33.48115299334812%\"\u003e\n \u003cp\u003eFemale ward: 48 patients\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003eFemale medical: 80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: ICU-Intensive Care Unit; HDU-High Dependency Unit\u003c/p\u003e\n\u003ch3\u003eFactors influencing nurses\u0026apos; ability to detect and respond to clinical deterioration\u003c/h3\u003e\n\u003cp\u003eInterview respondents acknowledged that they faced challenges in detecting and responding to clinically deteriorating patients in the ward. Five broad, interrelated themes related to detecting and responding promptly to patient deterioration emerged from the analysis of qualitative interviews. These were \u003cem\u003einsufficient monitoring of vital signs,\u003c/em\u003e \u003cem\u003eavailability of equipment and supplies\u003c/em\u003e, \u003cem\u003estaffing conditions and workload\u003c/em\u003e, \u003cem\u003elack of training and guidelines\u003c/em\u003e, \u003cem\u003ecommunication and teamwork\u003c/em\u003e \u003cem\u003eamong healthcare workers\u003c/em\u003e. These are discussed in turn below.\u003c/p\u003e\n\u003ch4\u003eInsufficient monitoring of vital signs\u0026nbsp;\u003c/h4\u003e\n\u003cp\u003eThe qualitative results were consistent with the findings of the document review related to gaps in vital signs documentation. Across all three study hospitals, interview respondents reported inconsistently taking vital signs for patients admitted to the wards. These inconsistencies, linked to poorly functioning and limited availability of equipment for monitoring patients, also manifested in poor documentation of patients\u0026apos; vital signs, as illustrated in the quote below:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;And the biggest challenge is that we don\u0026apos;t have the apparatus at hand. For example, if we are depending on one monitor to observe all the patients and then monitor breaks down. Like for now, you go borrowing from another ward, you find that it is being used. This really disturbs the documentation especially when it comes to vitals. So, you can find a patient may be observed maybe twice, thrice maybe a patient who has stayed for like 3 or 4 days which is a quite an ugly picture\u0026quot; (A003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInstances of poorly functioning equipment included the failure of the digital blood pressure machines and thermometers. Respondents reported that this equipment functioned well if their use was limited to a few patients. However, as highlighted in Table 4 above, the wards where the respondents worked frequently had high patient numbers, for whom the nurses only had one digital thermometer and blood pressure machine for patient monitoring. It was also common for other monitoring equipment, such as blood sugar machines, to sometimes lack batteries. There were also instances where monitors had been present in the wards but were not in use because they had not been repaired or replaced. Another type of equipment which was reportedly absent in one of the study hospitals was a pulse oximeter. In this hospital, the respondents reported relying only on observations of respiratory distress to administer oxygen and held the view that they perhaps were giving oxygen too late because they were unaware of the patient\u0026apos;s oxygen saturation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;In case a patient starts gasping, that\u0026apos;s when we put them on oxygen because we don\u0026apos;t have things like oximeter that we can be able to monitor oxygen saturation. I would say it\u0026apos;s mostly when the patient is going down, they are gasping or difficulties in breathing then we start them on oxygen\u0026hellip;\u0026quot; (B003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDespite these challenges, there were efforts to closely monitor patients judged to be severely ill. Most of these patients were placed in the acute rooms of the different wards to enable the nurses to quickly detect changes in the patient\u0026apos;s conditions. In addition, when there were students in the ward, they were utilised to closely monitor the patients as they learnt. However, because students were still in training, they were not always able to quickly detect a deteriorating patient and communicate this to the nurse in good time.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eAvailability of equipment and supplies\u003c/h4\u003e\n\u003cp\u003eRegarding the low availability of equipment and supplies, many respondents highlighted that oxygen, commonly used to respond to deteriorating patients, was often not readily available. In Hospitals B and C, some of the beds in the acute bay had oxygen ports for piped oxygen. However, if more than four patients, for example, in the case of Hospital C, needed oxygen, then an oxygen concentrator or oxygen cylinders would have to be used. However, the oxygen concentrator shared between the male and female wards in Hospital C had been broken down for over six months without repair. They, therefore, had to borrow from either the paediatric ward or High Dependency Unit (HDU). In Hospital A, they mainly used oxygen cylinders but reportedly experienced delays in connecting the oxygen as they tried to move the heavy oxygen cylinders:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;We don\u0026apos;t have concentrators, we don\u0026apos;t have oxygen, and there is a patient who needs oxygen, and it\u0026apos;s not there. We don\u0026apos;t even have a concentrator\u0026quot; (C003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;There is also a challenge there in terms of because these cylinders sometimes we run out of oxygen and you find we go to another ward cylinders are in use, cylinders are heavy these big cylinders. So you find a nurse is not able to move that cylinder\u0026quot; (A001)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOther equipment-related factors that hindered prompt response to deteriorating patients included the incomplete nature of the emergency trays in some wards. One respondent reported:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;Yes, we had a crash cart but we have never been able to manage the crash cart. Because you see, one, people still have that habit of picking drugs. So today you can refill the crash cart then you find within a minute you are not seeing those drugs maybe by the end of the day no single drugs because people pick, pick and they don\u0026apos;t replace, there is a lack of discipline in a way someone can just come dashing because maybe a patient has changed condition in another ward maybe a medical ward looking for a certain drug, picks and go\u0026quot; (A003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRespondents also highlighted that having one bag valve mask (BVM) per ward meant that there was a delay when a patient required resuscitation, especially if the BVM was not functioning well. In such cases, nurses had to borrow from another ward. Another inadequate supply that hindered prompt responses was Personal Protective Equipment (PPE). This was particularly relevant for nurses who were managing COVID-19 patients.\u003c/p\u003e\n\u003ch4\u003eStaffing conditions and workload\u003c/h4\u003e\n\u003cp\u003eAcross all the study hospitals, most respondents felt that the adult medical and surgical wards were grossly understaffed, making monitoring and detecting deteriorating patients difficult. As noted above, an acute bay was supposed to help nurses quickly detect when patients\u0026apos; conditions changed. However, this quick identification was limited in most cases because the nursing shifts were often covered by few nurses, making it challenging to do timely observations of vital signs. For example, one respondent from hospital B observed:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;Even though the male and female wards have acute areas. The only benefit of the acute areas is that the nurse is near the patients. However, it is difficult to do close monitoring when the nurse is working alone and the patients are many...\u003c/em\u003e \u003cem\u003ebecause I have said sometimes we have a capacity of 45. So it won\u0026apos;t be easy for you to be checking vitals maybe every 2 hours\u0026quot; (B005)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn the afternoon and night shifts, nurses commonly worked alone, with the support of students. The morning shifts were reportedly better staffed, as about two to three nurses reported to work. Most respondents felt that it was easier to detect deteriorating patients during the morning shift. During the shifts where a nurse was working alone, it was reportedly not uncommon for nurses to find out from relatives that patients were deteriorating as they did other procedures in the hospital wards. In fact, nurses across all three hospitals considered relatives a resource who could inform them when patients deteriorated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;And sometimes because of the shortage, we are not able to identify as quick as we can. You can imagine when you are alone in the ward, you are giving treatment on the other side. So in the most cases it\u0026apos;s the relatives who calls you. They call you, this one has deteriorated and then we notice.\u0026quot; (C003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;So you are only getting something you are told by the caretaker this patient has deteriorated. And by the time you are being told that, you realised that it has gone to the extreme end. You don\u0026apos;t get to intervene early enough. When you go and see this patient the general condition has already deteriorated to a further extent that the measures you take maybe you are trying to resuscitate this patient anaenda tu hivo [dies]. Nevertheless, you try. (B006)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;When the nurse is alone and you are on the other side and you left patient A, you have maybe 30 patients, like now we have 27 and the night nurse is alone, so she left patient A and now she is doing patient 25, and this A changes condition, unless the relatives call you, you will not know. By the time you go there, maybe it will be too late. So I think the nurse/patient ratio plays a big role\u0026quot; (A006)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe challenges with staffing also hindered effective response to a deteriorating patient, particularly one who required resuscitation, as described below by one of the respondents:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;You are alone, and the patient has changed; the one you have is a student. Some of the students they are very junior, they don\u0026apos;t know anything, tell me, whom will you call? And here you know resuscitation is teamwork. Teamwork of around 3, 4 people together working. When you are alone it becomes very difficult to do all those procedures alone. You need someone to record [vital signs], the other one do cardiac massage...If there is no that teamwork, the patient becomes zero because when you are alone, you can\u0026apos;t do\u0026quot; (A005)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWhen responding to a deteriorating patient, staffing was not only a nursing issue; it also seemed to cut across to other healthcare professionals who worked in the ward. Doctors especially were commonly few and busy, and the respondents reported delays when they called them. At night, across the three study hospitals, the doctors were not available in the wards and were commonly in casualty admitting patients. In Hospitals B and C, one Medical Officer (MO) intern circulated across the casualty department, theatre, and wards.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eLack of training and guidelines\u003c/h4\u003e\n\u003cp\u003eAcross all the study hospitals, most of the nurses had not been trained in Cardiopulmonary Resuscitation (CPR), Basic Life Support (BLS) or Advanced Cardiac Life Support (ACLS) despite caring for the acutely ill patients in the wards. Instead, most nurses relied on their pre-service training to detect and respond to deteriorating patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;Very few people have gone through BLS, ACLS. Personally, I haven\u0026apos;t done BLS, ACLS because it\u0026apos;s time and money\u0026hellip; I don\u0026apos;t know but 90% of the people who are there have not done the BLS and ACLS.\u0026quot; (B006)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;I have not done any [BLS or ACLS training]. I did it in college, and that\u0026apos;s what I am surviving with\u0026hellip;(C004)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIn addition, there were no existing policies and guidelines that were observed or reported on in relation to processes for detecting and responding to deteriorating patients. The exception was in Hospital A, where there were posters with some guidance on the ward notice boards, but the nurses in these wards reported that no training had preceded the introduction of these posters.\u0026nbsp;\u003c/p\u003e\n\u003ch4\u003eCommunication and Teamwork among the healthcare workers\u003c/h4\u003e\n\u003cp\u003eExperiences of communication varied across the three hospitals. For example, in Hospital A, an alert system that utilised colour codes (e.g. code blue, code red) had been introduced. There were posters at the ward level describing the response process when a patient was noted to be deteriorating. This process required calling through the operator, who would then call the doctors. Unfortunately, few study respondents from Hospital A understood this alert system, and many reported that they had not been trained in its use. As a result, it was hardly utilised. In hospital B, the ward nurse was expected to call the Medical officer (MO) intern to notify them and request their support if there was a deteriorating patient. The intern would then escalate the issue depending on his ability to address the patient\u0026apos;s deterioration. In hospital C, there was a long chain of communication in which the ward nurse was required to call the nurse covering the hospital, who would then call the MO intern or the MO to support a response to a deteriorating client. This long chain of communication inevitably slowed down the response to the deteriorating client, as illustrated in the quote below:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;Communication is another issue. I have to call the nurse who is covering the one who has the phone, to call the MO. You see that. It\u0026apos;s an emergency, I call somebody to call for me the MO.\u003c/em\u003e \u003cem\u003eYou can imagine the one I am calling she is in the office, maybe for example at night or in the afternoon...I call her, I have a patient who is gasping, let me call the MO intern, MO intern comes, she feels I can\u0026apos;t handle this alone, let me call the MO. You see the chain. Is that an emergency? (C003)\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNotably, the challenges described above were experienced mainly during the night and afternoon shifts and the weekend when there were few staff in the hospital. The respondents noted that during the morning shift, doctors and clinical officers were more available in the ward, and sometimes it was not necessary to make a phone call to reach them to communicate that a patient was deteriorating. Regarding what was communicated when a call was made, while the respondents acknowledged that there were no written-down guidelines that described what should be said, they reported describing the patient\u0026apos;s details, the diagnosis, and the most recent vital signs of the patient, including what actions had been taken by the nurse who was calling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBecause of the reported staffing challenges, teamwork appeared to be lacking in ensuring timely responses to deteriorating patients. This was illustrated by reports of certain doctors being too focused on their patients that they did not participate when there was a call for resuscitating a patient that they did not admit:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;Patient is deteriorating from theatre, now I have called the MO. The MO is referring me to the surgeon. Then the surgeon is not picking the phone and I have called over several times, I called the nurse covering. So went back to the MO, so he insisted call the surgeon, but we insisted, please for the sake of the patient, please come and assist us in resuscitating the patient. So we had to apply our own\u0026hellip; so we had to resuscitate the patient on our own.\u0026quot; (B002)\u003c/em\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study sought to understand an under-investigated issue in the Kenyan setting. Nurses\u0026apos; identification and response to a deteriorating patient is a critical role that needs to be further illuminated and improved upon to reduce unplanned admission to the few available critical care units as well as to reduce morbidity and mortality. Therefore, this study sought to find out how nurses documented the patients\u0026apos; vital signs 24 hours before a cardiac arrest (death) and to understand better the factors that influenced the ability to detect and respond to clinical deterioration.\u0026nbsp;As a result, we identified five central influencing factors that hinder the nurses\u0026apos; ability to detect and respond to patient deterioration. These were the insufficient monitoring of vital signs, availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork amongst healthcare workers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study found that vital signs monitoring and documentation by the nurses in the general wards was suboptimal and below the recommended standards of vital signs observations for an acute patient. This finding was consistent both in the document review and from the reports by the interviewees. From the document review, we found that less than 2% of the reviewed patient\u0026apos;s files had complete documentation of the six vital signs in the 24hrs prior to death. In addition, 70% of the patients did not have any recording of the respiratory rate 24hrs prior to death despite it being the more accurate predictor of clinical deterioration\u0026nbsp;[38, 39]. Furthermore, the documentation of the vital signs was primarily done in the nursing notes and not in the vital signs observations chart, therefore, limiting who could access the information. It is important to note that this study only considered the vital signs documented in the nursing notes and observation charts. Therefore the vital signs may have been taken but not documented and thus could explain the findings in this study. However, these findings are consistent with reports from studies that show that vital signs monitoring and documentation are often incomplete, with the respiratory rate being the lowest monitored vital sign\u0026nbsp;[40\u0026ndash;42].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA cross-cutting challenge that the study participants reported was the unavailability of equipment and supplies to enable them to detect and respond to clinical deterioration. This included the lack of monitoring devices, which were not functioning correctly where available. Additionally, they indicated a lack of resuscitation equipment and supplies and a lack of PPEs in the face of COVID-19. However, the most glaring issue was the lack of oxygen supply in the general wards. Where available, it was available in oxygen cylinders that required the nurse to move the heavy cylinder from one location to another hence delaying the response to deterioration. The unavailability of oxygen in the healthcare facilities in Kenya became a significant focus during the COVID-19 pandemic, with reports of many hospitals lacking reliable oxygen access\u0026nbsp;[16, 43]. A dependable source of oxygen is necessary to administer oxygen therapy, which can be obtained through various means. They include oxygen tanks that are filled at a facility, oxygen concentrators that extract oxygen from the surrounding air, oxygen plants that distribute oxygen via pipes or tanks, and liquid oxygen provided by a specialised gas plant and stored at high pressure on the premises\u0026nbsp;[44]. However, studies show that ensuring a steady and appropriate oxygen supply in the Lower and Middle Countries remains challenging\u0026nbsp;[45\u0026ndash;48]. This is not only hampered by factors such as the use of low-quality equipment that is not well-maintained but also by broader systemic issues, such as an unsteady power supply, limited healthcare workforce, and insufficient funding for healthcare\u0026nbsp;[49, 50].\u003c/p\u003e\n\u003cp\u003eStudies show that vital signs monitoring and documentation takes a considerable amount of nurses\u0026apos; time, which tends to increase depending on whether the observations are being done 6-hourly, 4-hourly or more\u0026nbsp;[51\u0026ndash;53]. The documentation burden is further exacerbated by increased nursing workload due to poor staffing, as we found in this study. Poor staffing affected nurses and doctors in all three hospitals and was a common factor influencing the detection and response to patient deterioration. These findings are consistent with those from other studies in Singapore and the United Kingdom, where poor staffing led to increased workloads and therefore was a barrier to early detection and response to the clinical deterioration\u0026nbsp;[26, 54]. The World Health Organization acknowledges the shortage of healthcare workers (HCWs) globally but reports that nurses are the most affected cadre of HCWs. The African region is among the most affected regions, with an estimated shortage of 4.2 million HCWs as of 2013\u0026nbsp;[55]. In Kenya, several studies have highlighted understaffing problems\u0026nbsp;[56\u0026ndash;58]. Our study adds to this literature by illustrating how sub-optimal staffing at the ward level influences the capacity of nurses to identify deteriorating patients and respond timely. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEffective communication is crucial for quickly identifying, escalating, and responding to clinical deterioration. Additionally, it is essential that there are laid down processes to enable the clinician to communicate the information clearly, logically and precisely\u0026nbsp;[59, 60]. Furthermore, to guarantee safe and reliable care of the deteriorating patient, effective communication requires clinicians\u0026apos; teamwork based on mutual respect, problem-solving and sharing of ideas\u0026nbsp;[61]. But as reported by the nurses from all three hospitals, they perceived that there was inadequate communication between clinicians, a lack of a process for ensuring timely management when patients deteriorate, and a low level of teamwork and collaboration amongst the different cadres of healthcare workers in agreement with findings from other studies\u0026nbsp;[29, 62\u0026ndash;64]. The importance of effective communication and teamwork cannot be understated in a healthcare system that is becoming increasingly complex, fragmented and with many professionals with different specialisations. Therefore, hospitals must implement measures and strategies to ensure structured communication processes among clinicians, clear guidelines and procedures for communicating deteriorations and creating a safety culture promoting teamwork.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eStudy Limitations\u003c/h3\u003e\n\u003cp\u003eThis study utilised data from medical records reviews and interviews. Our findings, particularly those drawn from in-depth interviews, may have been affected by social desirability bias. However, we attempted to offset this by including a review of documents to triangulate self-reported findings related to documentation practices by the nurses. Further, conducting the study in three hospitals was another form of triangulation. We did not find significant differences across the study hospitals regarding documentation practices and identifying and responding to deteriorating patients. Carrying out the study in two counties limits the generalisability of our findings. However, we have provided an adequate description of the study settings, particularly the study hospitals. We believe these findings can support readers to exercise judgement in determining the transferability of our study findings.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNurses have a critical role in recognising and responding to deteriorating patients. However, this study has demonstrated that nurses did not consistently monitor and document vital signs. Further, these nurses worked in sub-optimal ward environments characterised by inadequate and poorly functioning monitoring equipment; high workload because of staff shortages; sub-optimal communication during emergencies; gaps in teamwork and little training on actions to take when patients deteriorate at the ward level. All these features can negatively affect patient safety, quality of care, and patient outcomes at the ward level. Paying closer attention to the context in which nurses provide care can help to support nurses in promptly identifying and responding to deteriorating patients. Some hospital-level actions that could be taken towards this include providing adequate equipment for monitoring patients; simplifying the chain of communication when patients deteriorate and ensuring awareness of how such communication should be done; providing training targeted at nurses and other cadres of healthcare workers at ward level on collaborative practices including specific packages such as BLS and ACLS.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study also highlights a broad health system challenge beyond the influence of nurse managers at the ward and hospital level, that of the health worker shortage. The severe shortages reported in this study could hinder safe patient care. They also illustrate a need for policies and strategies that combine short, medium, and long-term approaches to attracting and retaining ward-level healthcare workers. Important considerations include the skill mix of nurses, provisions for conducting a rational review of staffing norms with the input of nursing managers, and engagement with training institutions to have more nurses in the pipeline.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACLS - Advanced Cardiac Life Support; BLS - Basic Life Support; BP - Blood pressure; BVM - Bag Valve Mask; CCU - Critical Care Unit; CPR - Cardiopulmonary Resuscitation; HCWs - Healthcare Workers; HDU - High Dependency Unit; HR - Heart rate; ICU - \u0026nbsp; Intensive Care Unit; LOC - Level of consciousness; MO - Medical Officer; PPE - Personal Protective Equipment; RR - Respiratory rate; Sp02 - Oxygen saturation; Temp \u0026ndash;Temperature.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eThe study was approved by Pwani University Ethics Review Committee (ERC/PU-STAFF/001/2020). A research permit to conduct the study was obtained from the National Commission for Science, Technology \u0026amp; Innovation (NACOSTI/P/20/4890). Informed consent was obtained from all study participants and the study was carried out in accordance with The Helsinki Declaration and institutional procedures.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis research was supported by the 2019 Sigma/Alpha Eta Collaborative Research Grant from Sigma Theta Tau International Honor Society of Nursing.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; contributions\u003c/h3\u003e\n\u003cp\u003eNM, NK, MB: conceived and designed the study. NM, NK, MN were responsible for the data acquisition, collection analysis, and interpretation. NM, NK, MN were involved in the drafting of the manuscript. NK, MN, MB did the critical revision of the manuscript. All the authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eAcknowledgements\u003c/h3\u003e\n\u003cp\u003eThe authors wish to thank all the nurses who participated in this study. We also thank all the medical records personnel who assisted in the retrieval of the patient\u0026apos;s files in the study hospitals\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; information\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eAuthors and Affiliations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNM - Department of Medical-Surgical Nursing and Preclinical Science, School of Health Sciences, Kenyatta University, Nairobi, Kenya.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNK - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMN - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya.\u003c/p\u003e\n\u003cp\u003eMB - KEMRI Wellcome Trust Research Programme, KEMRI Centre for Geographic Medicine Research Coast, Kilifi, Kenya.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHall K, Lim A, Gale B. (2020) Failure To Rescue. In: Hall KK, Shoemaker-Hunt S, Hoffman L, Making Healthcare Safer III: A Critical Analysis of Existing and Emerging Patient Safety Practices. Agency for Healthcare Research and Quality (US), Rockville (MD), pp\u0026nbsp;2\u0026ndash;1 to 2\u0026ndash;16\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilber JH, Williams SV, Krakauer H, Schwartz S. Hospital and Patient Characteristics Associated With Death After Surgery: A Study of Adverse Occurrence and Failure to Rescue. Med Care. 1992;30:615\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDonaldson LJ, Panesar SS, Darzi A. Patient-Safety-Related Hospital Deaths in England: Thematic Analysis of Incidents Reported to a National Database, 2010\u0026ndash;2012. PLoS Med. 2014;11:e1001667.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnglish M, Mwaniki P, Julius T, Chepkirui M, Gathara D, Ouma PO, Cherutich P, Okiro EA, Snow RW. Hospital Mortality \u0026ndash; a neglected but rich source of information supporting the transition to higher quality health systems in low and middle income countries. BMC Med. 2018;16:32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGong X-Y, Wang Y-G, Shao H-Y, Lan P, Yan R-S, Pan K-H, Zhou J-C. A rapid response team is associated with reduced overall hospital mortality in a Chinese tertiary hospital: a 9-year cohort study. Ann Transl Med. 2020;8:317\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKurita T, Nakada T, Kawaguchi R, Fujitani S, Atagi K, Naito T, Arai M, Arimoto H, Masuyama T, Oda S. Impact of increased calls to rapid response systems on unplanned ICU admission. Am J Emerg Med. 2020;38:1327\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersen LW, Kim WY, Chase M, Berg K-\u0026gt;, Mortensen M, Moskowitz SJ, Novack A, Cocchi V, Donnino MN MW. The prevalence and significance of abnormal vital signs prior to in-hospital cardiac arrest. Resuscitation. 2016;98:112\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChurpek MM, Adhikari R, Edelson DP. The value of vital sign trends for detecting clinical deterioration on the wards. Resuscitation. 2016;102:1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOh H, Lee K, Seo W. Temporal patterns of change in vital signs and Cardiac Arrest Risk Triage scores over the 48 hours preceding fatal in-hospital cardiac arrest. J Adv Nurs. 2016;72:1122\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZografakis-Sfakianakis M, De Bree E, Linardakis M, Messaritaki A, Askitopoulou H, Papaioannou A, Aggouridakis P. The value of the Modified Early Warning Score for unplanned Intensive Care Unit admissions of patients treated in hospital general wards. Int J Nurs Pract. 2018;24:e12632.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones DA, DeVita MA, Bellomo R. Rapid-Response Teams. N Engl J Med. 2011;365:139\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetersen JA. Multiple Parameter Track and Trigger Systems. In: DeVita MA, Hillman K, Bellomo R, Odell M, Jones DA, Winters BD, Lighthall GK, editors. Textbook of Rapid Response Systems. Cham: Springer International Publishing; 2017. pp. 87\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAustralian Commission on Safety and Quality in Health Care. (2012) Essential element 2: escalation of care. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.safetyandquality.gov.au/sites/default/files/migrated/Low-res-PDF-Essential-element-2-escalation-of-care.pdf\u003c/span\u003e\u003cspan address=\"https://www.safetyandquality.gov.au/sites/default/files/migrated/Low-res-PDF-Essential-element-2-escalation-of-care.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 7 Nov 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOzekcin LR, Tuite P, Willner K, Hravnak M. Simulation Education: Early Identification of Patient Physiologic Deterioration by Acute Care Nurses. Clin Nurse Specialist. 2015;29:166\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConsidine J, Rhodes K, Jones D, Currey J. Systems for recognition and response to clinical deterioration in Victorian emergency departments. Australasian Emerg Care. 2018;21:3\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarasa EW, Ouma PO, Okiro EA. Assessing the hospital surge capacity of the Kenyan health system in the face of the COVID-19 pandemic. PLoS ONE. 2020;15:e0236308.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurthy S, Adhikari NK. Global Health Care of the Critically Ill in Low-Resource Settings. Annals ATS. 2013;10:509\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOketch UK, Chokwe TM, Mung\u0026rsquo;ayi V. The operational setup of intensive care units in a low income country in East Africa: a cross sectional survey. East Afr Med J. 2015;92:72\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaweru-Siika W, Mung\u0026rsquo;ayi V, Misango D, Mogi A, Kisia A, Ngumi Z. The history of critical care in Kenya. J Crit Care. 2020;55:122\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMushta J, Rush L, Andersen K E. Failure to rescue as a nurse-sensitive indicator. Nurs Forum. 2018;53:84\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Thubaity D, Williamson S, Leavey R, Tume LN. Newly qualified Saudi nurses\u0026rsquo; ability to recognize the deteriorating child in hospital. Nurs Crit Care. 2019;24:263\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzimirad M, Magnusson C, Wiseman A, Selander T, Parviainen I, Turunen H. Nurses\u0026rsquo; ability to timely activate rapid response systems for deteriorating patients: A comparative case scenario study between Finnish and British nurses. Intensive and Critical Care Nursing. 2020;60:102871.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBliss M, Aitken LM. Does simulation enhance nurses\u0026rsquo; ability to assess deteriorating patients? Nurse Educ Pract. 2018;28:20\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCardona-Morrell M, Prgomet M, Lake R, Nicholson M, Harrison R, Long J, Westbrook J, Braithwaite J, Hillman K. Vital signs monitoring and nurse\u0026ndash;patient interaction: A qualitative observational study of hospital practice. Int J Nurs Stud. 2016;56:9\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHands C, Reid E, Meredith P, Smith GB, Prytherch DR, Schmidt PE, Featherstone PI. Patterns in the recording of vital signs and early warning scores: compliance with a clinical escalation protocol. BMJ Qual Saf. 2013;22:719\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRedfern OC, Griffiths P, Maruotti A, Recio Saucedo A, Smith GB. The association between nurse staffing levels and the timeliness of vital signs monitoring: a retrospective observational study in the UK. BMJ Open. 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2019-032157\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2019-032157\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDalton M, Harrison J, Malin A, Leavey C. Factors that influence nurses\u0026rsquo; assessment of patient acuity and response to acute deterioration. Br J Nurs. 2018;27:212\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMassey D, Chaboyer W, Aitken L. Nurses\u0026rsquo; perceptions of accessing a Medical Emergency Team: A qualitative study. Australian Crit Care. 2014;27:133\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohammmed Iddrisu S, Hutchinson AF, Sungkar Y, Considine J. Nurses\u0026rsquo; role in recognising and responding to clinical deterioration in surgical patients. J Clin Nurs. 2018;27:1920\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMok W, Wang W, Cooper S, Ang ENK, Liaw SY. Attitudes towards vital signs monitoring in the detection of clinical deterioration: scale development and survey of ward nurses. Int J Qual Health Care. 2015;27:207\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePantazopoulos I, Tsoni A, Kouskouni E, Papadimitriou L, Johnson EO, Xanthos T. Factors influencing nurses\u0026rsquo; decisions to activate medical emergency teams: MET activation. J Clin Nurs. 2012;21:2668\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCreswell JW. Research design: qualitative, quantitative, and mixed methods approaches. 4th ed. Thousand Oaks: SAGE Publications; 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health. Kenya Health Sector Strategic Plan - July 2018\u0026ndash;June 2023. Nairobi, Kenya: Government of the Republic of Kenya; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeVita MA, Smith GB, Adam SK et al. (2010) \u0026ldquo;Identifying the hospitalised patient in crisis\u0026rdquo;--a consensus conference on the afferent limb of rapid response systems. Resuscitation 81:375\u0026ndash;382\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGhee TL, Weaver P, Solo S, Hobbs M. Vital signs reassessment frequency recommendation. Nurs Manag. 2016;47:11\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBraun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3:77\u0026ndash;101.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaguire M, Delahunt B. Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. AISHE-J. 2017;9:3351\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaw W, Kaur R, Delaney M, Elphick H. Respiratory rate is an early predictor of clinical deterioration in children. Pediatr Pulmonol. 2020;55:2041\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMochizuki K, Shintani R, Mori K, Sato T, Sakaguchi O, Takeshige K, Nitta K, Imamura H. Importance of respiratory rate for the prediction of clinical deterioration after emergency department discharge: a single-center, case-control study. Acute Med Surg. 2017;4:172\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgero M, Ayieko P, Makone B, Julius T, Malla L, Oliwa J, Irimu G, English M. An observational study of monitoring of vital signs in children admitted to Kenyan hospitals: an insight into the quality of nursing care? J Global Health. 2018;8:010409.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStevenson JE, Israelsson J, Petersson G, Bath PA. Factors influencing the quality of vital sign data in electronic health records: A qualitative study. J Clin Nurs. 2018;27:1276\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUllah E, Albrett J, Khan O, Matthews C, Perry I, GholamHosseini H, Lu J. Workload involved in vital signs-based monitoring \u0026amp; responding to deteriorating patients: A single site experience from a regional New Zealand hospital. Heliyon. 2022;8:e10955.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOtiangala D, Agai NO, Olayo B, et al. Oxygen insecurity and mortality in resource-constrained healthcare facilities in rural Kenya. Pediatr Pulmonol. 2020;55:1043\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization, United Nations Children\u0026rsquo;s Fund (UNICEF). WHO-UNICEF technical specifications and guidance for oxygen therapy devices. Geneva: World Health Organization; 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDauncey JW, Olupot-Olupot P, Maitland K. Healthcare-provider perceptions of barriers to oxygen therapy for paediatric patients in three government-funded eastern Ugandan hospitals; a qualitative study. BMC Health Serv Res. 2019;19:335.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgot M, Ayah R, Muriuki R, Nyangaya J. Oxygen Access and Affordability in Health Facilities in Kenya. Kenya Policy Briefs. 2021;2:53\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRahman AE, Mhajabin S, Dockrell D, Nair H, El Arifeen S, Campbell H. Managing pneumonia through facility-based integrated management of childhood management (IMCI) services: an analysis of the service availability and readiness among public health facilities in Bangladesh. BMC Health Serv Res. 2021;21:667.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolla HS, Woyessa DB, Balkew RB, Asemere YA, Fekadu ZF, Belete AB, Gartley M, Battu A, Lam F, Desale AY. Decentralizing oxygen availability and use at primary care level for children under-five with severe pneumonia, at 12 Health Centers in Ethiopia: a pre-post non-experimental study. BMC Health Serv Res. 2022;22:676.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalderon R, Morgan MC, Kuiper M, Nambuya H, Wangwe N, Somoskovi A, Lieberman D. Assessment of a storage system to deliver uninterrupted therapeutic oxygen during power outages in resource-limited settings. PLoS ONE. 2019;14:e0211027.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham HR, Bagayana SM, Bakare AA, Olayo BO, Peterson SS, Duke T, Falade AG. Improving Hospital Oxygen Systems for COVID-19 in Low-Resource Settings: Lessons From the Field. Glob Health Sci Pract. 2020;8:858\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins S, Couture B, Kang MJ, Dykes P, Schnock K, Knaplund C, Chang F, Cato K. Quantifying and Visualizing Nursing Flowsheet Documentation Burden in Acute and Critical Care. AMIA Annu Symp Proc. 2018;2018:348\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDall\u0026rsquo;Ora C, Griffiths P, Hope J, Briggs J, Jeremy J, Gerry S, Redfern OC. How long do nursing staff take to measure and record patients\u0026rsquo; vital signs observations in hospital? A time-and-motion study. Int J Nurs Stud. 2021;118:103921.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTasew H, Mariye T, Teklay G. Nursing documentation practice and associated factors among nurses in public hospitals, Tigray, Ethiopia. BMC Res Notes. 2019;12:612.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChua WL, Legido-Quigley H, Ng PY, McKenna L, Hassan NB, Liaw SY. Seeing the whole picture in enrolled and registered nurses\u0026rsquo; experiences in recognizing clinical deterioration in general ward patients: A qualitative study. Int J Nurs Stud. 2019;95:56\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global strategy on human resources for health: workforce 2030. Geneva: World Health Organization; 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiseda MH, Were SO, Murianki CA, Mutuku MP, Mutwiwa SN. The implication of the shortage of health workforce specialist on universal health coverage in Kenya. Hum Resour Health. 2017;15:80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunywoki J, Kagwanja N, Chuma J, Nzinga J, Barasa E, Tsofa B. Tracking health sector priority setting processes and outcomes for human resources for health, five-years after political devolution: a county-level case study in Kenya. Int J Equity Health. 2020;19:165.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNyawira L, Tsofa B, Musiega A, et al. Management of human resources for health: implications for health systems efficiency in Kenya. BMC Health Serv Res. 2022;22:1046.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu SI, Shikar M, Gante E, Prufeta P, Ho K, Barie PS, Winchell RJ, Lee JI. Improving Communication and Response to Clinical Deterioration to Increase Patient Safety in the Intensive Care Unit. Crit Care Nurse. 2022;42:33\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManojlovich M, Krein SL. We don\u0026rsquo;t talk about communication: why technology alone cannot save clinically deteriorating patients. BMJ Qual Saf. 2022;31:698\u0026ndash;700.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFuchshuber P, Greif W. Creating Effective Communication and Teamwork for Patient Safety. In: Romanelli JR, Dort JM, Kowalski RB, Sinha P, editors. The SAGES Manual of Quality, Outcomes and Patient Safety. Cham: Springer International Publishing; 2022. pp. 443\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDinius J, Philipp R, Ernstmann N, Heier L, G\u0026ouml;ritz AS, Pfisterer-Heise S, Hammerschmidt J, Bergelt C, Hammer A, K\u0026ouml;rner M. Inter-professional teamwork and its association with patient safety in German hospitals\u0026mdash;A cross sectional study. PLoS ONE. 2020;15:e0233766.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones A, Johnstone M-J. Managing gaps in the continuity of nursing care to enhance patient safety. Collegian. 2019;26:151\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewman D, Hofstee F, Bowen K, Massey D, Penman O, Aggar C. A qualitative study exploring clinicians\u0026rsquo; attitudes toward responding to and escalating care of deteriorating patients. J Interprof Care. 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13561820.2022.2104231\u003c/span\u003e\u003cspan address=\"10.1080/13561820.2022.2104231\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Clinical deterioration, vital signs, nurse documentation, patient safety, medical surgical nursing, recognising, responding","lastPublishedDoi":"10.21203/rs.3.rs-2633455/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2633455/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIn low and middle-income countries like Kenya, critical care facilities are limited, which means acutely ill patients are managed in the general wards. Nurses in these wards are expected to detect and respond to patient deterioration to prevent cardiac arrest or death. This study examined nurses' vital signs documentation practices during clinical deterioration and explored factors influencing their ability to detect and respond to clinical deterioration.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis convergent parallel mixed-methods study was conducted in the general medical and surgical wards of three hospitals in Kenya's coastal region. Quantitative data on the extent to which the nurses monitored and documented the patients' vital signs 24 hours before a cardiac arrest (death) occurred was retrieved from patients' medical records. Additionally, in-depth, semi-structured interviews were conducted with twenty-four purposefully drawn registered nurses working in the three hospitals' adult medical and surgical wards.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThis study reviewed 405 patient records and found that most of the documentation of the vital signs was done in the nursing notes and not the vital signs observation chart. During the 24 hours prior to death, respiratory rate was documented the least in only 1.2% of the records. Only a very small percentage of patients had any vital event documented for all six-time points. Thematic analysis of the interview data identified five broad themes related to detecting and responding promptly to deterioration. These were insufficient monitoring of vital signs, availability of equipment and supplies, staffing conditions and workload, lack of training and guidelines, and communication and teamwork constraints among healthcare workers.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study showed that nurses did not consistently monitor and record vital signs in the general wards. The nurses worked in suboptimal ward environments characterised by inadequate and malfunctioning monitoring equipment, high workload due to staff shortages, communication and teamwork gaps, and little training on handling patient deterioration at the ward level; factors that negatively impact patient safety and outcomes. The findings provide an opportunity for future research to test interventions to improve nurses' assessment and management of clinical deterioration in general wards.\u003c/p\u003e","manuscriptTitle":"General Ward Nurses Detection and Response to Clinical Deterioration in Three Hospitals at the Kenyan Coast: A Convergent Parallel Mixed Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-03-15 19:19:10","doi":"10.21203/rs.3.rs-2633455/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-08-08T09:05:05+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-07-16T13:16:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-07-10T11:38:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"512147f2-a69e-43cf-a5f0-b4d87833e20b","date":"2023-06-29T06:47:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321e7ec2-74f7-45aa-82c6-168802499e98","date":"2023-06-29T06:02:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-06-16T09:56:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-06-15T09:54:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2023-03-13T05:37:30+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-03-13T05:27:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2023-02-27T10:24:26+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb0c178e-b0e0-43be-af19-d5d0808f5ab5","owner":[],"postedDate":"March 15th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-04T15:08:18+00:00","versionOfRecord":{"articleIdentity":"rs-2633455","link":"https://doi.org/10.1186/s12912-024-01822-2","journal":{"identity":"bmc-nursing","isVorOnly":false,"title":"BMC Nursing"},"publishedOn":"2024-03-01 15:01:47","publishedOnDateReadable":"March 1st, 2024"},"versionCreatedAt":"2023-03-15 19:19:10","video":"","vorDoi":"10.1186/s12912-024-01822-2","vorDoiUrl":"https://doi.org/10.1186/s12912-024-01822-2","workflowStages":[]},"version":"v1","identity":"rs-2633455","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2633455","identity":"rs-2633455","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}