Adverse Event and Near-Miss Analysis

ADVERSE EVENT OR NEAR-MISS ANALYSIS 1

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Adverse Event or Near-Miss Analysis

Learner’s Name

Capella University

Quality Improvement for Interprofessional Care

Month, Year

Comment [JS1]: This submission is very well crafted according to the

rubric. It is written in a scholarly voice and free of APA and

grammatical errors.

ADVERSE EVENT OR NEAR-MISS ANALYSIS 2

Adverse Event or Near-Miss Analysis

Preventable adverse events are among the top causes of death in the United States.

Estimates reveal that 210,000 to 400,000 fatal adverse events occur every year (Allen, 2013).

Examples of preventable adverse events are hospital-acquired diseases, medication errors, and

patient falls. The focus of this adverse-event analysis is medication errors, also known as adverse

drug events (ADEs), such as medication overdoses or administration of wrong medicines. The

analysis will recommend strategies to mitigate ADEs based on a case of medication overdose

observed in the emergency department (ED) at TrueWill General Hospital (TGH), a

multispecialty hospital in the United States.

A 40-year-old woman was brought to the ED after suffering a seizure. Before she was

discharged, she suffered a second seizure and the ED doctor prescribed 800 mg of phenytoin, an

anti-seizure medication, to be given intravenously (IV). The ED nurse misread the prescribed

dosage in the electronic medical record (EMR) and administered 8000 mg, which was 10 times

greater than the prescribed dosage. The patient died soon after the lethal infusion (Manias, 2012).

The incident shows that the nurse made a series of cognitive errors in medication

management and missed key steps (Manias, 2012), which will be explained in the analysis

report. Additionally, the analysis will examine the implications of adverse events on multiple

stakeholders. Relevant evidence and metrics will be incorporated when making suggestions for

improvement of patient safety at TrueWill General Hospital.

Analysis of Missed Steps Related to the Adverse Event

Emergency departments are susceptible to adverse events because of the unscheduled

nature of patient presentation, urgency, and severity of cases. In such high-pressure situations,

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ADVERSE EVENT OR NEAR-MISS ANALYSIS 3

clinicians must be more careful when treating a patient (Manias, 2012). Retracing the steps taken

by the nurse revealed several missed steps in the delivery of care.

To begin with, the drug dispensing machines in the ED were stocked with phenytoin in

250 mg vials; the correct dose required only 3.2 vials. As the nurse had misread the dose, she

needed 32 vials of the drug. She took the vials from three different drug dispensers and

administered the dose using two IV bags as well as a piggyback line (Manias, 2012). The nurse

did not question the difficulty in procuring and administering the drugs, nor did she ask anyone

to validate her calculations. Furthermore, she was not asked why she was removing so many

vials from the drug dispensers in the ED unit.

The scenario also shows that the nurse was unaware of the toxic nature of phenytoin

when administered in large quantities; she was unable to recognize the warning signs.

Additionally, the fact that the nurse could remove 32 vials is evidence of the technical drawbacks

of the automated drug-dispensing machines. The machines were not programmed to send out

alerts when large quantities of medications, especially high-alert medications like phenytoin,

were dispensed (Manias, 2012). They were also not synced to the patient’s medical record.

Therefore, the machines contained no information on drug preparation or correct dosages and did

not display any warning signs.

Various systems factors such as communication, leadership, education, training, and

innovation of health care technology influenced the ED nurse’s clinical performance. The factors

originate from the adaptation of systems theory into health care (Huber, 2017). There are,

however, areas of uncertainty regarding the factors becoming problematic in TGH’s scenario.

For example, the nurse’s hesitation to consult her team could have been caused by staff

management problems such as conflict, overwork, or shortage of ED staff. Similarly, her lack of

awareness of

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ADVERSE EVENT OR NEAR-MISS ANALYSIS 4

dosages and safety measures indicates gaps in education and training. Such problems are a result

of a breakdown of systems factors. Further evaluation is essential to understand the root causes

of adverse events and systems problems. Ignoring root causes can result in similar adverse

events in the future and negatively impact the stakeholders.

Implications of the Adverse Event on Stakeholders

Since medicine is a profession that depends on interpersonal relationships, adverse events

have emotional, psychological, and professional consequences on all stakeholders. Patients and

their families are the first victims of adverse events, while health care professionals and the

organization become the second and third victims, respectively (Mira et al., 2015). A similar

inference can be made about the adverse event at TGH; the inference is supported by certain

assumptions about the health care environment. General assumptions about health care are as

follows: (a) quality health care is a result of positive relationships among all stakeholders

(Huber, 2017); (b) stakeholders are part of a high-risk environment where errors in clinical

practice are common; (c) health care professionals are not always responsible for errors, as errors

are often caused by a breakdown in systems factors (Manias, 2012); and (d) errors diminish the

morale and job satisfaction of health care professionals and lead to more adverse events (Huber,

2017).

The analysis of implications for stakeholders begins with identifying how each category

of victims is impacted. The first victims expect hospital stays and procedures to be safe and

beneficial. When a patient suffers an injury or dies because of medical negligence, the family

may feel aggrieved and may require counseling and support. They may feel unnerved and scared

by health care professionals (Bernhard, 2013) and hesitate to seek medical treatment in the

future. The study reported that health care professionals were traumatized after committing a

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5 ADVERSE EVENT OR NEAR-MISS ANALYSIS

preventable error or witnessing an adverse event. They may lose confidence, abandon their

careers (Bernhard, 2013), and experience anxiety or depression (Mira et al., 2015). Adverse

events are damaging to careers, and nursing professionals may face difficulty in finding another

job (Bernhard, 2013).

Adverse events also affect the organization—the third victim—by damaging its

reputation. Adverse events can discourage people from seeking treatment at a particular hospital

(Mira et al., 2015). Moreover, as most preventable errors are not covered by Medicaid and

Medicare services, the hospital may lose a significant amount of reimbursement money.

It is important that health care organizations such as TGH find ways to minimize the

impact of adverse events on stakeholders. The current trend in quality improvement

(QI) is focused on reducing human errors through automation of health care technologies. In the

case of TGH, the existing level of automation of patient records and drug dispensers is

insufficient and must be replaced. The next section recommends and discusses the benefits of a

popular QI technology—patient care dashboards.

Evaluation of Quality Improvement Technologies

Performance measurement and reporting by health care professionals are the crux of QI

because transmitting, organizing, analyzing, and displaying performance data help in identifying

areas that need improvement (Ghazisaeidi, 2015). A recent development in QI technologies is the

introduction of visual dashboards. Dashboards are interactive performance management tools

that use graphic and easy-to-use formats to present specific metrics or key performance

indicators (KPIs) on a single computer screen (Ghazisaeidi, 2015). Implementing a dashboard

can help TGH improve quality of care and patient safety.

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ADVERSE EVENT OR NEAR-MISS ANALYSIS 6

Studies show that the use of data-driven dashboards improves patient safety and

accelerates cost-reduction efforts. A dashboard reduces human errors in processes and minimizes

the cognitive effort needed to make decisions, thereby saving time and increasing efficiency and

accuracy. The KPIs aggregate data collected from various sources. For example, clinical data

incorporated into a dashboard include patient information gathered from physician or nurse

charts. A dashboard can also consolidate metrics about market dynamics, innovation for long-

term sustainability, and availability of financial and human resources for managers to analyze

(Weiner, Balijepally, & Tanniru, 2015).

To help TGH efficiently customize the dashboard to its specific clinical context, the tool

should be tested and evaluated using certain criteria. The categories for each criterion are as

follows: (a) easy customization; (b) knowledge discovery; (c) security; (d) information delivery;

(e) visual design; (f) alerts; and (g) system connectivity and integration (Karami, 2014). These

criteria can be used for all types of dashboards and health care settings.

While the design features are important, the dashboard is only useful if the KPIs provide

valuable data. Hence, the selection and development of KPIs are critical steps in QI at TGH

without which the organization risks ignoring areas that require corrective action

(Ghazisaeidi, 2015).

Relevant Metrics of Quality Improvement for TrueWill General Hospital

The KPIs are the most valuable content in a dashboard. They measure performance

across the organization using a combination of administrative and clinical data sets. To prevent

overloading the electronic dashboard, only a limited number of KPIs concerning high-priority

areas is selected. These KPIs are based on evidence-based academic literature. Data for each KPI

is sourced from different source systems in the organization such as the accounting system,

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7 ADVERSE EVENT OR NEAR-MISS ANALYSIS

human resources system, and clinical system (Ghazisaeidi, 2015). For example, clinical data are

sourced from reports on whether clinicians treated the correct patient, addressed the equipment

or supplies needed, prescribed the correct medication or anesthesia at the appropriate time, and

detected patient allergies (Hagland, 2012). For the adverse event analysis report, the relevant

KPIs will focus on clinical and patient-centric metrics.

Health care agencies such as the Agency for Healthcare Research and Quality (AHRQ)

have developed their own metrics that address various aspects of quality: patient safety,

prevention quality, inpatient quality, and pediatric quality. TGH can customize its clinical and

patient-centric KPIs for the dashboard from these aspects. Examples of relevant AHRQ metrics

that are applicable to the ED adverse event include (a) death rate in low-mortality-diagnosis-

related groups; (b) accidental puncture or laceration rate; (c) heart failure mortality rate; and (d)

dehydration admission rate (AHRQ, 2015a, 2015b, 2015c).

The ED department at THG can include other relevant KPIs in the dashboard such as (a)

monthly averages for patient length of stay (inpatient and outpatient); (b) patients in the ED who

left without being seen (monthly); (c) radiology test (CT scan and x-ray), start to final dictation

turnaround time (Weiner, Balijepally, & Tanniru, 2015); (d) speed of onset of pain relief; (e)

cost-reduction percentage per patient; and (f) risk of drug interactions (Dolan, Veazie, & Russ,

2013).

The evidence base for the selected KPIs consists of peer-reviewed studies. Hagland

(2012) proved the success of the dashboard for patient safety optimization at the Saint Luke’s

Mid America Heart Institute, Missouri. The dashboard increased communication within medical

teams, reduced safety errors, and improved coordination between the teams. Dolan, Veazie, and

Russ (2013) studied the effectiveness of the electronic dashboard as a decision-making tool. The

results showed that the dashboard had potential to foster informed decision making and patient-

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ADVERSE EVENT OR NEAR-MISS ANALYSIS 8

centered care. Weiner, Balijepally, and Tanniru (2015) studied the integration of data-driven

dashboards at the St. Joseph Mercy Oakland Hospital in Michigan. The study reported tangible

benefits such as KPIs reporting reduced adverse event rates and intangible benefits such as

increased accountability across the organization, self-improvement among nurses, and improved

unit performance.

The dashboard is just the technological component of quality improvement. TGH

requires a broader QI framework that incorporates organizational strategies to overcome

problems in the ED that resulted in the death of the patient. A suitable framework will be selected

after evaluating different perspectives and data about quality improvement.

Outline for a Quality Improvement Initiative for TrueWill General Hospital

The health care industry has adopted many QI and measurement models over the years.

Two popular models in quality improvement are the Six Sigma and LEAN models. Both models

have similar goals: eliminate operational waste and defects to improve quality and efficiency of a

system. The main difference between Six Sigma and LEAN is in the approaches to identifying

causes of defects and errors. According to Six Sigma, variations in processes cause errors, while

LEAN thinking highlights unnecessary steps as the cause of operational waste and errors

(AHRQ, 2017).

As both process variations and unnecessary steps can cause errors, the combination of the

LEAN and Six Sigma models can be implemented at TGH as its quality improvement outline.

The hospital can follow the LEAN Six Sigma model’s DMAIC approach. DMAIC is a five-step

approach to process improvement: (a) define—identify key business issues; (b) measure—

understand current levels of performance; (c) analyze—identify root causes of process errors; (d)

improve—introduce strategies and tools to improve quality of process; and (e) control—maintain

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9 ADVERSE EVENT OR NEAR-MISS ANALYSIS

new levels of performance across the organization (Huber, 2017). Implementing the LEAN Six

Sigma into all units and departments—not just the ED—at TGH will help streamline processes

proactively. By improving the whole system, the hospital can prevent communication gaps or

errors, disorganization, and breakdown of faulty systems. DMAIC steps will allow TGH to

enhance QI process using tools and strategies such as the dashboard.

The Institute of Health Improvement’s Plan-Do-Study-Act (PDSA) model and the

Baldrige criteria were other quality improvement perspectives that were considered (Huber,

2017). However, the PDSA insufficiently addressed specific types of errors caused by variations

or unnecessary steps, unlike the LEAN Six Sigma model. The Baldrige criteria too were

insufficient because their usage was more suitable for enabling educational excellence.

Additionally, there is extensive evidence supporting the LEAN and Six Sigma models in quality

improvement.

While the LEAN Six Sigma model and dashboards have a high success rate,

implementing the QI initiative depends on coordinated and collaborative efforts by multiple

stakeholders. Teamwork enables TGH’s health care professionals to optimize systems factors

and the quality of processes and prevent future adverse events.

Conclusion

The process of QI and ensuring patient safety is challenging because health care

organizations must simultaneously provide the highest quality of services and introduce cost-

reduction strategies. Quality improvement initiatives such as implementing dashboards must

focus on finding and fixing the root causes of errors or process inefficiencies. To identify the

root causes of errors, the organization should train health care professionals, update health care

technologies, and open lines of communication to meet the expectations of patients for safe,

timely, affordable, and quality care.

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ADVERSE EVENT OR NEAR-MISS ANALYSIS

References

Agency for Healthcare Research and Quality. (2015a). Prevention quality indicators. Retrieved

from https://qualityindicators.ahrq.gov/Downloads/Modules/PQI/V50/PQI_Brochure.pdf

Agency for Healthcare Research and Quality. (2015b). Patient safety indicators. Retrieved from

https://qualityindicators.ahrq.gov/Downloads/Modules/PSI/V50/PSI_Brochure.pdf

Agency for Healthcare Research and Quality. (2015c). Inpatient quality indicators. Retrieved

from https://qualityindicators.ahrq.gov/Downloads/Modules/IQI/V50/IQI_Brochure.pdf

Agency for Healthcare Research and Quality. (2017). Section 4: Ways to approach the quality

improvement process. In The CAHPS ambulatory care improvement guide: Practical

strategies for improving patient experience. Retrieved from

https://ahrq.gov/cahps/quality-improvement/improvement-guide/4-approach-qi-

process/sect4part2.html#4c

Allen, M. (2013, September 19). How many die from medical mistakes in U.S. hospitals?

[Ongoing investigative report]. ProPublica. Retrieved from

https://propublica.org/article/how-many-die-from-medical-mistakes-in-us-hospitals

Bernhard, B. (2013, May 5). Medical errors leave devastating impact on families, professionals.

St. Louis Post-Dispatch. Retrieved from http://stltoday.com/lifestyles/health-med-

fit/health/medical-errors-leave-devastating-impact-on-families-

professionals/article_0cb6f031-fbc6-5b8f-bed9-610163dbf2f8.html

Dolan, J. G., Veazie, P. J., & Russ, A. J. (2013). Development and initial evaluation of a

treatment decision dashboard. BMC Medical Informatics and Decision Making, 13(1), 51.

Retrieved from https://search-proquest-com.library.capella.edu/docview/1347649264?pq-

origsite=summon

ADVERSE EVENT OR NEAR-MISS ANALYSIS 11

Copyright ©2017 Capella University. Copy and distribution of this document are prohibited.

Hagland, M. (2012). A dashboard for OR patient safety optimization. Healthcare

Informatics, 29(8), 29–31. Retrieved from https://search-proquest-

com.library.capella.edu/docview/1038458450?pq-

origsite=summon&http://library.capella.edu/login%3furl=accountid=27965

Huber, D. L. (2017). Leadership and nursing care management (6th ed.) Philadelphia: W.B.

Saunders. http://dx.doi.org/10.7748/nm.21.6.13.s14

Ghazisaeidi, M., Safdari, R., Torabi, M., Mirzaee, M., Farzi, J., & Goodini, A. (2015).

Development of performance dashboards in healthcare sector: Key practical issues. Acta

Informatica Medica, 23(5), 317–321. Retrieved from https://search-proquest-

com.library.capella.edu/docview/1727377974?pq-origsite=summon

Karami, M. (2014). A design protocol to develop radiology dashboards. Acta Informatica

Medica, 22(5), 341–346. http://dx.doi.org/10.5455/aim.2014.22.341-346

Manias, E. (2012). Looking for meds in all the wrong places [Case study commentary].

Retrieved from https://psnet.ahrq.gov/webmm/case/282/looking-for-meds-in-all-the-

wrong-places?q=Looking+for+meds+in+all+the+wrong+place

Mira, J. J., Lorenzo, S., Carrillo, I., Ferrús, L., Pérez-Pérez, P., Iglesias, F.,… Astier, P. (2015).

Interventions in health organisations to reduce the impact of adverse events in second and

third victims. BMC Health Services Research, 15(1), 341–350. Retrieved from

https://search-proquest-com.library.capella.edu/docview/1780186926?pq-

origsite=summon&http://library.capella.edu/login%3furl=accountid=27965

Weiner, J., Balijepally, V., & Tanniru, M. (2015). Integrating strategic and operational decision

making using data-driven dashboards: The case of St. Joseph Mercy Oakland

Hospital. Journal of Healthcare Management, 60(5), 319–331. Retrieved from

Comment [JS2]: I would suggest locating a more current reference.

This reference is on the cusp of being

outdated according to health care

research standards of being less than

five years. With this topic, I am sure there are more updated references that

could be used instead.

Comment [JS3]: This is another reference that should be updated for

the above reasons.

ADVERSE EVENT OR NEAR-MISS ANALYSIS 12

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https://search-proquest-

com.library.capella.edu/docview/1733617419?OpenUrlRefId=info:xri/sid:summon&acco

untid=27965

1

Adverse Event or Near-Miss Analysis

Capella University

FPX6016: Quality Improvement Interprofessional Care

Dr. Michelle Dykes

June 16, 2021

2

Adverse Event or Near-Miss Analysis

Delivery of quality healthcare builds a critical assessment of specific approaches that

build change and help influence change and improve individual needs. According to Saluja and

Bryant (2021), approximately 67% of pregnancy-related deaths in the United States are

preventable. The quality of care and recognizing essential maternal warning signs are essential

in saving the lives of women (Saluja & Bryant, 2021). Since because black women are three

times more likely than Caucasian women to die, a detailed review of the underlying inequities

in healthcare delivery is required. Globally, maternal mortality has dropped by roughly 2.9

percent. However, in the United States, the tendency has been the polar opposite, with an

estimated 42 maternal fatalities per 100,000 (Amankwaa et al., 2018). Understanding this

pattern emphasizes the need for more favorable policies and regulations to aid in developing a

stronger forum for advancement by focusing on black women.

Pregnancy-related deaths are five times as common in black women over 30 than in

white women. In states with a low pregnancy-related mortality ratio, the mortality rate was

similarly high (PRMR) (Collier & Molina, 2019). These findings show that the existing

disparity in pregnancy-related fatality rates among black and white women is a sensitive and

complex national issue. Because these are avoidable diseases, delivering high-quality maternity

care will greatly reduce the mortality rate linked with them (Chinn et al., 2020).

Case scenario

A 30 years old was brought into the emergency department at Safe Care Health Clinic

with heavy bleeding, severe back pain, fever that had lasted for more than 24 hours and foul-

smelling vaginal discharge. Upon further clinical examination, it was found that she had an

unsafe abortion, and some of the fetus parts had remained in the body, which was contributing

to severe discomfort. However, no scan was performed to ascertain the extent of the problem.

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Further, the doctor did not inquire about the period taken since the unsafe abortion was

conducted. The patient was given intravenous fluid for volume replacement and antibiotics and

discharged the following day after the pain had reduced immensely. There was no vacuum

aspiration indicated despite the realization that the woman had attempted to procure an

abortion. However, after three weeks, she came back with more intense pain and was diagnosed

with endometriosis. The solution was to perform a hysterectomy, which would have been easily

prevented had the correct decisions been made in the initial incidence considering the urgency

and the likelihood of adverse outcomes.

The incident, as observed, shows a series of medical errors made by admitting

physicians, and they could have been easily prevented had the management protocol been

followed efficiently. Building a broader basis for change and improved consideration of the

patient’s healthcare needs should inform the decision to management approach adopted

(Macdorman & Declercq, 2018). Thus, the analysis will provide a detailed evaluation of all the

errors that would have been avoided to ensure that the patient received total quality care. The

assessment will also incorporate the implication of the adverse event on the stakeholders

involved in the whole process.

Analysis of the missed steps to the adverse event

Management of care within a hospital context is evaluated based on the severity of the

patient and the underlying risks that are likely to arise based on given standard operating

procedures. All healthcare providers are expected to adhere to standard operating procedures in

managing patients to ensure that there are no errors within the healthcare environment. The

patient who came to the facility had major signs indicating that she had complications from

unsafe abortion (Miller & Leffert, 2020). The doctor would have known the severity of the

situation and opted to conduct a detailed physical assessment to protect the patient’s healthcare

4

needs. It is imperative to fully review the patient’s situation before determining the type of

management approach.

One of the symptoms that the patient exhibited included foul-smelling vaginal

discharge. This is a key indication that there are some retained parts resulting from unsafe

abortion that was conducted. However, the doctor bypassed this important sign and opted to

prescribe medication to treat other symptoms that the patient was having. Despite knowledge of

the unsafe abortion, the doctor also failed to investigate the length until the symptoms began to

show. The period in this context would have been essential in determining the extent of internal

damage and determine whether it was prudent to conduct vacuum aspiration to clean the uterus.

These challenges can stem from varied sources, including a lack of communication and

delivery of healthcare as a multidisciplinary practice. It is essential to focus on building a

broader change approach that defines an improved basis for change and an improved level of

focus. Building a higher level of engagement within a given context illustrate the need and

ability to improve efficiency and change development strategy (Purohit, 2021). A

multidisciplinary approach to care means an interactive process where all healthcare providers

deliver quality care jointly.

The implication of the adverse event on the stakeholders

The underlying concern based on the whole situation is lack of communication and the

basis of ideology sharing. It would be significant to build change and promote a broader basis

for change development. The adverse event laid a claim on the ability to provide quality care

by the hospital. The patient is the victim of the adverse event, which can be treated as

negligence by the healthcare provider. Healthcare providers are required to provide quality and

ethical care where the patient’s needs and well-being serve as the priority of the care approach

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considered. The actions of the doctor should focus on promoting the general good rather than

harm the patient.

As a key stakeholder in this context, the hospital suffers immensely from low ratings

and claims of incompetency from patients aggrieved by the manner they were treated.

Credibility in a healthcare context is integral to the success of any approaches that are being

integrated within a given care environment. Building a strong change platform defines an

improved change approach where it is possible to understand change strategies and different

measures that build a broader basis of development.

Quality improvement technologies

Improving the quality of care in this context presents a broader basis within which it is

possible to achieve a greater level of change within a hospital setting. Thus, a quality

improvement measure that would be significant in this context is introducing imaging

technologies as standard procedures for patients with severe symptoms to have a better visual

knowledge of the source of discomfort and change development strategy (Mehta et al., 2016).

Health information systems would also be integral in improving the quality of care since the

system would send prompts to questions regarding patient history that have not been asked to

ensure that it is filled and inform on the care development process. Health information

management systems have been integral in building a strong and medical error-free practice

(Willcox et al., 2020).

Relevant Metrics of Quality Improvement for Safe Care Health Clinic

Assessing metrics in the care environment provides a basis for identifying whether the

quality of care delivered is sufficient. The efficiency of these projects presents a broader

context for change and the adoption of better measures that build change and adopt an

improved performance level. The key metrics that are assessed in this context involve checking

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and documenting patient vital signs. The care providers should be competent and can build a

broader basis for change and the adoption of changing processes that improve efficiency and

change development (Macdorman & Declercq, 2018). Thus, assessment of their knowledge

levels and abilities is crucial in shaping change and the adoption of better systems that seek to

promote change and empower quality performance within a healthcare context. Patient

feedback is an essential metric that provides knowledge on how patients perceive the facility’s

quality of care.

Outline for quality improvement initiative at Safe care Health Clinic

Improving healthcare quality presents a highly imperative basis within which it is

possible to achieve high-quality care. Building a strong change approach defines a broader

basis for change while also improving the quality of care. Therefore, Safe Care Health clinic

needs to integrate better approaches to help build change development strategy within the

healthcare environment (Dukhanin et al., 2018).

A Lean quality of care model is efficient in this context, considering that it presents a

strong basis for change and overall focus on quality rather than quantity. Healthcare providers

within the healthcare facility must be well trained and exhibit high-performance strategies. The

lean quality model aims at identifying the source of the problem and allows the development of

strategies and processes that can help control the quality of care (Amran et al., 2020). Thus,

these concepts should form the basis for the delivery of improved care and commitment to

change.

7

Conclusion

Integration of technology in the care context presents a strong basis for change where it

would be possible to influence change and help attain a high quality of care. The presence of

preventable adverse events within a care setting shows a lack of commitment to patient needs

hence negatively influence the quality of care approach. Quality improvement technologies that

could be employed in managing the patient situation to overcome an adverse outcome have

also been effectively investigated and present a broader basis for a higher level of change in

terms of quality of care delivery.

8

References

Amankwaa, L. C., Records, K., Kenner, C., Roux, G., Stone, S. E., & Walker, D. S. (2018).

African-American mothers’ persistent excessive maternal death rates. Nursing Outlook,

66(3), 316–318. https://doi.org/10.1016/j.outlook.2018.03.006

Amran, M. D. M., Januddi, F., Nuraina, S., Ikbar, A. W. M., & Khairanum, S. (2020). The

barriers in lean healthcare implementation. Test Engineering and Management.

Chinn, J. J., Eisenberg, E., Artis Dickerson, S., King, R. B., Chakhtoura, N., Lim, I. A. L.,

Grantz, K. L., Lamar, C., & Bianchi, D. W. (2020). Maternal mortality in the United

States: research gaps, opportunities, and priorities. American Journal of Obstetrics and

Gynecology. https://doi.org/10.1016/j.ajog.2020.07.021

Collier, A. R. Y., & Molina, R. L. (2019). Maternal mortality in the united states: Updates on

trends, causes, and solutions. NeoReviews. https://doi.org/10.1542/neo.20-10-e561

Dukhanin, V., Topazian, R., & Decamp, M. (2018). Metrics and evaluation tools for patient

engagement in healthcare organization-and system-level decision-making: A systematic

review. In International Journal of Health Policy and Management.

https://doi.org/10.15171/ijhpm.2018.43

Macdorman, M. F., & Declercq, E. (2018). The Failure of United States Maternal Mortality

Reporting and Its Impact on Women’s Lives. In Obstetrical and Gynecological Survey.

https://doi.org/10.1097/OGX.0000000000000617

Mehta, R., Bhatt, N., & Ganatra, A. (2016). A Survey on Data Mining Technologies for

Decision Support System of Maternal Care Domain. International Journal of Computer

Applications. https://doi.org/10.5120/ijca2016908965

Miller, E. C., & Leffert, L. (2020). Stroke in Pregnancy: A Focused Update. Anesthesia and

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Analgesia. https://doi.org/10.1213/ANE.0000000000004203

Purohit, N. (2021). Utilization of delivery and postnatal health services by indigenous women

of a hilly, remote district in India: a struggle for safe motherhood. International Journal

Of Community Medicine And Public Health. https://doi.org/10.18203/2394-

6040.ijcmph20210223

Saluja, B., & Bryant, Z. (2021). How Implicit Bias Contributes to Racial Disparities in

Maternal Morbidity and Mortality in the United States. Journal of Women’s Health.

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