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Quality improvement initiative: improving obstetric triaging practices in a rural maternal hospital in central India
  1. Mihir Ranade1,
  2. Shuchi Jain2,
  3. Poonam Varma Shivkumar2,
  4. Subodh Gupta3,
  5. Manish Jain4
  1. 1Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra, India
  2. 2Obstetrics and Gynecology, Mahatma Gandhi Institute of Medical Sciences, Sevagram, India
  3. 3Community Medicine, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra, India
  4. 4Pediatrics, MGIMS, Wardha, Maharashtra, India
  1. Correspondence to Dr Shuchi Jain; shuchijain{at}


Triaging of obstetric patients by emergency care providers is paramount. It helps provide appropriate and timely management to prevent further injury and complications. Standardised trauma acuity scales have limited applicability in obstetric triage. Specific obstetric triage index tools improve maternal and neonatal outcomes but remain underused. The aim was to introduce a validity-tested obstetric triage tool to improve the percentage of correctly triaged patients (correctly colour-coded in accordance with triage index tool and attended to within the stipulated time interval mandated by the tool) from the baseline of 49% to more than 90% through a quality improvement (QI) process.

A team of nurses, obstetricians and postgraduates did a root cause analysis to identify the possible reasons for incorrect triaging of obstetric patients using process flow mapping and fish bone analysis. Various change ideas were tested through sequential Plan-Do-Study-Act (PDSA) cycles to address issues identified.

The interventions included introduction and application of an obstetric triage index tool, training of triage nurses and residents. We implemented these interventions in eight PDSA cycles and observed outcomes by using run charts. A set of process, output and outcome indicators were used to track if changes made were leading to improvement.

Proportion of correctly triaged women increased from the baseline of 49% to more than 95% over a period of 8 months from February to September 2020, and the results have been sustained in the last PDSA cycle, and the triage system is still sustained with similar results. The median triage waiting time reduced from the baseline of 40 min to less than 10 min. There was reduction in complications attributable to improper triaging such as preterm delivery, prolonged intensive care unit stay and overall morbidity. It can be thus concluded that a QI approach improved obstetric triaging in a rural maternity hospital in India.

  • Control charts/Run charts
  • Healthcare quality improvement
  • Maternal Health Services
  • PDSA

Data availability statement

Data are available upon reasonable request.

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  • Until 2010, labour and delivery units triaged pregnant women based on standardised emergency acuity scales, but studies have shown their limited applicability in obstetric triage. Since 2010, many obstetric triaging scales have been introduced and validated with respect to their content, reliability, consistency and responsiveness.


  • In our study, we introduced the Obstetric Triage Acuity Scale as an obstetric triage tool for a more efficient triaging of obstetric patients. We improved on this application through quality improvement methodology and have sustained this improvement amidst and beyond the COVID pandemic.


  • The concept of obstetric triage is upcoming and is being considered as one of the most crucial factors for high-risk obstetric care but remains underused in India. We recommend that other institutions adopt our strategy and emulate triaging or other safe care tools.


Problem description

This quality improvement (QI) project was implemented in the labour room of a mother and child health wing of a rural tertiary care medical college in Wardha district in central India over a period of 8 months. Earlier, the triage nurses had been using a trauma triaging scale for the triaging of obstetric patients. However, studies have shown the limited applicability of these scales in obstetric triage, as obstetric triage is beyond just a concise estimate and entails a thorough assessment of the mother and fetus, and the acuity determinants do not reflect the variation of pregnancy manifestations or the specialised needs of obstetric patients.1 We analysed the existing triaging system for a period of 2 weeks by reassessing the patients and retrospectively applying the Obstetric Triage Acuity Scale (OTAS) to them. We found that the baseline rate for correctly triaged patients (correctly colour-coded in accordance with triage index tool and attended to within the stipulated time interval mandated by the tool) was just 49%, with a median triage waiting time of 40 min. We found an above average incidence of preterm deliveries, neonatal intensive care unit (NICU) admissions and prolonged hospital stays for both the baby and the mother, most of which could have been avoided had the woman been triaged in time and given the necessary interventions. We also encountered a few cases of mismanaged and incompletely worked up patients due to poor triaging, and some potential windows for complications like cord prolapse, prolonged labour and obstructed labour which should not have occurred in the first place. Thus, there was a need to introduce an obstetric triage-specific tool.

Ours is an 800-bedded rural tertiary medical college and hospital in Wardha district of Maharashtra in central India, primarily catering to the low and lower middle socioeconomic populations from the surrounding area. A 200-bedded maternal and child health wing is run by the obstetrics and paediatrics departments of the medical college. The hospital caters to approximately 5000–6000 deliveries annually, that is, 400–500 deliveries per month translating to 12–15 deliveries every day. There are two resident doctors and three staff nurses on duty in each 12-hour shift in the labour room, while the obstetric triage is staffed with one triage nurse and one point-of-contact resident doctor every day on rotation. It is a tertiary care institute and provides round-the-clock essential and emergency obstetric and newborn care services. Being a tertiary care centre, the hospital also gets referrals from primary health centres, rural hospitals, as well as district hospitals, many of which are high-risk referrals requiring intensive care.

A QI team was assembled, comprising the head of the emergency department (triage), the labour room sister in charge, the residents posting in charge and the researcher. The team identified a QI project to improve the percentage of correctly triaged patients from the baseline of 49% to more than 90% in the obstetric department of maternal and child health wing of a rural tertiary care hospital over a period of 8 months from February 2020 to September 2020. This project was conducted by applying the principles of Plan-Do-Study-Act (PDSA) cycles of the QI methodology. These goals were achieved at the end of the project, the improvement sustained and this triage structure is now ingrained in our institution as an important tool.


Obstetrical emergencies are life-threatening medical problems that develop during pregnancy, labour or delivery. Both the mother and the child’s health may be jeopardised. An effective obstetric unit must care for patients in a variety of emergency scenarios, ranging from minor problems to life-threatening serious conditions. Triage is the practice of prioritising patients based on the severity of their problems so that they can receive the best care possible in the shortest amount of time.2 When triaged accurately, patients receive care in an appropriate and timely manner by emergency care providers.3 During the last decade, obstetric triage is one of the latest services to emerge. A successful contemporary obstetric triage paradigm is one that addresses the questions of ‘sick or not sick’ and ‘labour or no labour’ for every obstetric patient that presents for care.4 Triage algorithms for obstetric acuity are effective in assessing and prioritising obstetric patients.5 6 Triage acuity scales such as the Canadian Triage and Acuity Scale (CTAS), the Emergency Severity Index and the Manchester Triage System have only a limited number of obstetric determinants and hence are unsuitable to be used as an obstetric triage tool. Hence, the London Health Sciences Centre developed the OTAS based on the five-category CTAS tool.7 OTAS consists of five levels: critical, emergency, urgent, semiurgent and non-urgent. The scale is based on disease severity and acuity and is colour-coded into blue, red, yellow, green and grey according to severity. It includes a comprehensive set of obstetrical presenting complaints organised by categories of signs and symptoms, along with assessment of maternal vital signs, fetal status and the suggested response time. OTAS enables standardised assessments of acuity within and across institutions. Further, it facilitates assessment of patient care and flow based on acuity. OTAS has been shown to have higher reliability than other obstetric triage index tools, and hence we decided to adopt it as our triage index tool.8 ,9 Application of such obstetric triage scales has been shown to improve maternal and fetal outcomes, reduce patient waiting times in hospitals and prioritise care based on acuity.10 ,11

The advantages of implementing QI principles in clinical practice have been widely reported, with significant improvements in patient care aspects such as care coordination, safety, operational efficiency and access to care, in order to provide the best care and value to the patient.12 Puri et al concluded that QI methods have the potential to develop effective strategies to improve triaging.13 Kumar et al reported that QI methodology was practical and effective in reducing waiting time to triage in the emergency department of a large hospital in India.14 Joshi et al succeeded in establishing a paediatric emergency triage system and culture in a small hospital in India through QI methodology using successive PDSA cycles and improving the triage rate from the baseline of 16–20% to 68% and sustaining it.15 Goodman et al showed that a QI-based implementation of an obstetric triage system designed for a high-volume, high-risk referral hospital in Ghana resulted in a significant and locally sustained reduction in waiting time. By the end of this study, they were able to correctly triage 99% of the patients from the baseline of 45%, and reduced median triage waiting time from 40 min to 5 min.16 Terri et al showed that the QI-based application of an obstetric triage scale in Georgia resulted in reduction in waiting time and total visiting time of patients and prioritised care based on acuity.


We started off the study by doing a baseline analysis of the existing triage system, which included using a trauma triaging scale for the triaging of obstetric patients, for 1 month to know the preintervention correct triaging rate and median triage waiting time. The criteria for patients included all pregnant women reporting to the obstetric triage in emergency. Patients admitted from outpatient department (OPD), or those sent to the labour room for elective induction or elective caesarean section, were excluded from the study. The QI team tracked the maternal and fetal outcomes of all such patients. The OTAS was retrospectively applied to all the patients. The data suggested that out of total eligible women in whom triaging was done, only 49% of them were triaged correctly, that is, correctly colour-coded by the triage nurse in accordance with the OTAS and attended to within the stipulated time interval mandated by the OTAS by an obstetrician. In order to improve this triaging rate, training of the triage nurses to implement the OTAS for triaging of all patients reporting to the emergency department was planned.

The process indicator was the proportion of women correctly triaged. The numerator was the number of women who were colour-coded and attended to within the stipulated time period as directed by their severity by OTAS, while the denominator was the total number of women reporting in emergency to the obstetric triage unit.


The study was carried out in the following steps:

  1. Forming a QI team that included the head of the emergency department (triage), the labour room sister in charge, the residents posting in charge and the researcher.

  2. Measuring the proportion of women correctly triaged in the obstetric triage department over 2 weeks to collect baseline data.

  3. The triage nurse maintained a triage register where data of all patients presenting to the triage in emergency were entered.

  4. The labour room resident collected the data and the researcher presented it to the head of the triage every week.

  5. Analysing possible reasons for poor triaging using root cause analysis.

  6. Conducting multiple PDSA cycles to test change ideas identified by the team on small scale initially and then expanding to larger scale. It was planned that the whole QI team would meet at the end of every PDSA cycle to analyse the data and discuss further course of action.

  7. Descriptive statistics were used to describe baseline variables. Run charts were used to display and interpret the serial measurement of indicators and to study the impact of changes.

The team conducted a brainstorming session. The various challenges identified by fish bone analysis (figure 1) and process flow chart were:

  1. There was no obstetric-specific triaging index tool in place. The residents had been using a three-level trauma triaging scale for the triaging of obstetric patients, which did not account for the wide range of pregnancy symptoms or the unique demands of obstetric patients.

  2. Triage nurses and resident doctors needed to be trained in the correct application of the planned implementation of OTAS.

  3. The triage nurses were merely acting as informers and not responders.

  4. There was no written policy regarding the waiting time of a patient, lest the obstetrician on duty be occupied elsewhere.

Figure 1

Fish bone analysis of problem. LR, labour room; JR, junior resident.

Figure 2

New triage protocol. ANC, ante natal care; Anti-D, anti rhesus-D immunoglobulin; BP, blood pressure, DBP, diastolic blood pressure, FHR, fetal heart rate; HR, heart rate; ICU, intensive care unit; MSAF, meconium stained amniotic fluid; NST, non stress test; OT, operation theatre; PV, per vagina; RR, respiratory rate; SBP, systolic blood pressure; Td, tetanus and diphtheria toxoid vaccine.


After analysing the challenges with the help of fish bone analysis and process flow chart, the QI team planned PDSA cycles to implement different change ideas. With this premise, a QI process was planned involving a series of PDSA cycles to improve the percentage of women correctly triaged. Data collection and analysis were done as follows:

  • The triage nurse maintained a register with details of patient name, hospital registration number, diagnosis, date and time of entry into the triage, time of being seen by the obstetrician and OTAS colour code given.

  • The researcher, aided by the respective unit residents, followed up the outcome of all these patients in the register with respect to whether there was discharge/delivery/death, intensive care unit (ICU) stay, any interventions done, neonatal Apgar score, NICU admission and whether there was any maternal or neonatal mortality.

  • These data were collected by the labour room resident, compiled and presented to the head of the emergency department (triage) by the researcher, who then discussed and analysed it every Sunday.

  • The researcher presented these findings to the whole team at team meetings conducted every 2 weeks, or at the end of every PDSA cycle, where the problems were discussed, solutions offered, good changes (like dividing the resident duty hours, extra training sessions of triage nurses) were adopted, some changes were adapted (like only employing interns for vitals recording), while bad changes were abandoned (like posting a resident exclusively in triage, using interns as first responders).

PDSA cycles undertaken:

The team met for an interim review and identified potential barriers in improper triaging as: (1) on-call residents being scrubbed in emergency OT (operation theatre) leads to longer waiting times for women in triage, (2) in case the on-call residents were in the OT, the labour room resident would look after triage, but if they were conducting delivery at that time, it would lead to delays.

PDSA cycle 6: Conducting multiple training sessions and drills for triage nurses for the application of OTAS. Data collection by the researcher also included checking whether the colour code given by a triage nurse to a patient is correct. There still was some discrepancy in the colour coding by the triage nurses in accordance with the OTAS. To address this issue, training sessions were conducted every Sunday for a period of 4 weeks (3 May to 31 May 2020). These included mock drills, demonstrations and scenarios (for instance, a patient who is convulsing will always be code blue). A large chart showing the OTAS was displayed in the triage area for quick referencing. By the end of the sessions, the nurses became more efficient and confident in assigning the correct colour code to every patient in triage, eliminating the error from their side, and the process indicator had risen to 82%.

The obstetric triage system was modified over and over and streamlined in this way to increase efficiency. (Figure 2)It was seen that OTAS was a valuable addition to our triage, and it aided in providing better quality of care. But before we could test the long-term validity of the scale, the COVID-19 pandemic hit, and with the imposition of lockdown, the main challenge in front of us was how we could triage COVID and non-COVID patients separately.

PDSA cycle 7: Triaging in COVID pandemic. A new ‘isolation area’ was set up within the triage area itself for examination of women coming from outside the district, as COVID suspects. Patients were allowed to enter the ‘clean’ labour room only after checking their proof of address and travel history, a job entrusted to the triage nurse. The obstetrician would see all COVID suspects in this isolation area, wearing personal protective equipment (PPE) kit, and reverse transcriptase-PCR test was sent for all such women. Colour coding continued as per the OTAS. It was observed that this system ensured containment of suspected cases as well as limited exposure of working staff through quarantine. This cycle was conducted for a period of 2 weeks (1 June to 14 June 2020). No COVID-positive patients were encountered, but it was safe to assume that the situation would arise sooner than later. COVID brought with it its own specific set of problems like PPE kit-related issues, the prolonged quarantine periods for exposed residents and the hostile behaviour of patients, leading to a drop in the proportion of correctly triaged women down to 68.5%.

PDSA cycle 8: Management of full-blown COVID-19 pandemic. With the first COVID-19-positive woman near labour, it was mandatory to create segregated wards for three sets of patients: COVID positive, COVID negative and COVID report awaited. It was observed that creation of these isolation wards was an extremely important step in managing patient flow in the COVID pandemic. At the same time, strict adherence to these protocols was just as vital. Despite so many hurdles, the team was now efficient in OTAS application; in fact, OTAS ensured that exposure to COVID-positive or suspected patients was not prolonged. At the end of 4 weeks (15 June to 12 July 2020), it was found that the proportion of correctly triaged women had risen to 86%. Thus, by implementing the principles of QI methodology through multiple PDSA cycles, we were able to create a triaging system which seemed to work, despite the numerous hurdles in the way.

Sustenance: Testing the long-term validity of the OTAS. A sustenance cycle was planned and conducted for a period of 8 weeks (13 July to 7 September 2020) to test the long-term efficiency and effectiveness of the triaging process through OTAS. This was basically an extension of PDSA cycle 8 for a longer duration to see whether the results could be reciprocated. With the whole COVID background, triaging continued as per the OTAS, data variables recorded and results noted. Over 95% of women were now correctly triaged, rising from the baseline of 49%. The COVID-specific problems in the last few cycles were tackled in the same way of PDSA in accordance with QI methodology. It was found that OTAS became integrated into the triaging practice at our hospital, independent of COVID or non-COVID and worked well in improving maternal and fetal outcomes in terms of reducing the waiting time for women in triage, reduced incidence of maternal and fetal-preventable adverse outcomes and an overall improvement in the quality of healthcare.


In the baseline survey, 49% of all the women reporting to emergency were correctly triaged. By the end of eight PDSA cycles, this proportion had increased to 86%. The result was sustained, in fact even improved on to 95%, in the last ‘sustenance’ cycle without any additional resources(figure 3) (figure 3A). Median triage waiting time (calculated from the time printed on the patient’s OPD paper to the time recorded by the triage nurse when the patient was seen by an obstetrician) was reduced from baseline of 40 min to 10 min in the last cycle, and has been sustained beyond the study as well, which is recommended as per international standards (figure 3A). There was reduced incidence of adverse maternal outcomes (figure 3B) in terms of instrumental delivery, caesarean delivery, cervical tears and their repair, transfusion of blood or blood products, need for prolonged ICU stay, requirement of ventilatory support and overall maternal morbidity and mortality; and neonatal outcomes (figure 3B) in terms of preterm birth, low birth weight, neonatal sepsis, respiratory distress, prolonged NICU stay, requirement of ventilatory support and overall neonatal morbidity and mortality . There was no maternal or fetal or neonatal mortality in the study.

Figure 3

(A) Time series graph of outcome variables: percentage of women correctly triaged and median triage waiting time. (B, C) Tables for maternal and neonatal outcome indicators. (B) Maternal complications before and after quality improvement (QI). (C) Neonatal complications before and after QI. ICU, intensive care unit; NICU, neonatal intensive care unit; PDSA, Plan-Do-Study-Act.

Lessons and limitations

Obstetric triage index scales are exceedingly being used for labour evaluation as well as for pregnancy complications and obstetrical emergencies. It is possible to systematically improve patient care as well as patient outcome through the principles of QI. Introducing any new change or design is never a one-step process. It is a series of steps each focusing on betterment of current scenario to finally achieve the desired outcome. This is basically the process of QI through the use of PDSA cycles.17 The study was successful in establishing a triage system for all pregnant women reporting to the emergency department of rural tertiary care hospital and referral centre in a low and middle-income country. The triage system in discussion is one that has been developed, used and validated across countries over time and considered to be the ideal triaging system for obstetric patients. A number of hurdles were encountered during this process, but with the help of QI methodology, we were able to overcome them and introduce a number of changes to modify the system and later adopt, adapt or abandon said changes, the larger objective being in mind the desired outcome.

Many lessons were learnt during our journey. The first lesson was that just telling people to try something new even if they appreciate it (ie, use a new tool) does not work. It is pertinent to study the local work environment and team dynamics before introducing a change. We learnt to create a team which included representatives from the group being affected by the change, and to explain to the team relevant information, sharing of results, especially positive ones, creating enthusiasm by word of mouth, and being focused on making changes that will have a positive impact, rather than on finding problems and mistakes. Second, creating local autonomy: the triage nurse was initially functioning as a messenger, but with the introduction of the role of the triage nurse as the first responder and first point of contact with the patient, she was also given the responsibility to make her own decisions to an acceptable extent. In a setting with shortage of manpower and workforce, this role of triage nurse was sure a step in the right direction. Third, we learnt the importance of consistency. Even with the COVID era, the triaging using the OTAS continued, and while the COVID protocols kept on changing, triaging protocols were the same and hence there was no change or drop in efficiency, rather, we felt we were able to deal with pandemic better as we had a formal triage structure in place. Another thing we observed was the large safety margin of the OTAS application, which borders on overtriaging, but ensures a good maternal and neonatal outcome. Through this study, we were able to introduce the OTAS for obstetric triaging in a rural maternity hospital in central India, improve the proportion of accurately triaged women, reduce triage waiting times and obtain an overall better maternal and neonatal outcome through QI process. Such was the consistency of the implementation, that even in the midst of COVID pandemic, we were able to sustain improvement and were able to deal with the pandemic in a better way due to a formal triage structure in place.

We also encountered certain limitations to our study. First, the study was not able to define terms overtriage and undertriage. We were unable to determine whether we were wasting resources by overtriaging a patient. While on the other hand, large safety margin could only attribute to some extent of undertriaging. We were also unable to identify and measure the false negatives, that is, women having adverse outcomes in spite of correct triaging, owing to the vast range of obstetrical complications beyond the scope of triaging alone. In addition, we could not explore patient feedbacks to assess patient-centric improvements. Lastly, sustaining the development was a challenge especially due to shortage of manpower. As new recruits learn to adjust to the demands of their new workplace, compliance with the tool’s proper application plummets. While local leadership serves as a dedicated and trusted guiding presence during these periods, regular trainings and interactive feedback are also essential to keep the team engaged, putting pressure on the system. We are still looking for new ideas and feedback from new members to help us figure out how to overcome these constraints.


In this study, we improved quality of care for emergency obstetric patients at our institute by introducing OTAS as an obstetric triage tool with excellent and promising results. We have improved on this application through QI methodology and have sustained this improvement. We recommend that other institutions adopt our strategy and emulate triaging or other safe care tools. While the instrument or change idea chosen may differ, the approach of embedding the change ideas stays consistent.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication


We acknowledge the London Health Sciences Centre (LHSC) for their comprehensive five category obstetric triage tool OTAS (Obstetric Triage Acuity Scale). We also acknowledge the labour room staff nurses and resident doctors for supporting this initiative. We thank the administrators of the institute for providing us infrastructure and technical support.



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  • Contributors SJ, MR and SG contributed to conception and study design. MR, SJ, MJ and SG contributed to reviewing of the database, conducting the project, collection of data and writing the article. SJ, SG and PVS critically reviewed the manuscript for accuracy and intellectual content. All authors approved the final version of the article. SJ is the guarantor.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.