Process Improvement Plan – Part 1 – Implementing Wearable Technology to ImproveStroke and Heart Disease Outcomes Among Elderly Patients

2. Introduction

Technological innovations and advancements continue to become pervasively ingrained
into today’s everyday life and people are starting to increasingly integrate consumer grade
hardware and software devices to control and track their health. Smart wearable technology are
consumer-grade electronic devices that people can wear on their bodies as accessories or
embedded into their clothing. They include fitness trackers, smartwatches, smart fabric or
clothing, smart glasses, smart earbuds, or heard-mounted glasses. All these devices contain
numerous sophisticated sensors with a high processing power capable of gleaning new health
insights. It is estimated that at least 20 percent of the current US adult population presently own a
smart wearable sensor or device and the international market is projected to grow by 25 percent
annually, hitting about $70 billion by 2025 (Bayoumy et al., 2021).
Unlike other technologies that have become an integral part of the healthcare system,
such as telehealth and electronic health records (EHRs), the adoption of wearable technology in
clinical settings has been slow and, honestly, has never considered a prerequisite in improving
healthcare outcomes. One of the reasons wearable devices have not been widely implemented in
clinical settings is lack of regulatory approval. Most wearable technology has been taken as
“fads” without proper regulation or standardization. This lack of regulation means non-clinical
companies have taken advantage of the craze among consumers for health-related products to
manufacture “devices” and falsely label them as health sensors without proper approval. There is
also little evidence to support the effectiveness of these devices in supporting diagnosis,
treatment, and health promotion in clinical settings.
Despite these concerns about wearable technology, empirical evidence has consistently
shown the possibility of wearable sensors and other devices improving patient monitoring and

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healthcare outcomes (Prieto-Avalos et al., 2022). One area that researchers believe the
technology can yield profound impacts is in managing cardiovascular diseases, the globe’s most
widespread and deadliest chronic disorder mostly affecting seniors aged 60 and older (CDC,
2022).
This process improvement proposes implementing wearable technology like
smartwatches, fitness trackers, and fabric sensors to monitor stroke and heart disease biomarkers
and symptoms, including blood pressure, heart rate, and other vital signs. In particular, the
technology would be implemented in critical care units (CCUs) specifically designated for
elderly patients (60+ years) with stroke and heart disease, two of the leading causes of death
globally. This process improvement project would provide key insights into the key practice and
process changes required for the meaningful implementation of wearable technology.

3. Problem Statement

Cardiovascular diseases (CVDs) are the leading causes of mortality in the US and
globally; the US and global death tolls are 868,662 and 17.9 million annually (American Heart
Association, 2021; World Health Organization, n.d.). Cardiovascular diseases are a group of
illnesses affecting the blood and vessels and the heart and include stroke, coronary heart disease,
rheumatic heart disease, cerebrovascular disease, heart failure, arrhythmias, valvular heart
disease, and congenital heart disease, among others. The risk factors associated with CVDs
include family history of heart disease, lack of exercise, obesity, diabetes, smoking, high
cholesterol, high blood pressure, and poor dietary intake. The problem is that the risk of CVDs,
especially stroke and heart disease, is disproportionately high among older people 65+,
predisposing them to poor quality of life (QoL), stress and other psychological effects,
debilitating physical impacts like pain, high cost of treatment, and mortalities. In critical care

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units (CCUs), evidence has also shown that 60-year-plus-olds diagnosed with heart disease and
stroke have the highest disease prevalence, morbidity, and mortality rates than any other age
group (Sidney et al., 2022). Therefore, there is a need to find a long-lasting, effective, and
cheaper way of diagnosing, monitoring, and preventing older patients diagnosed with heart
disease and stroke to reduce the burden.

4. Background of the Problem

Cardiovascular diseases (CVDs) are presently the leading cause of death in the US and
globally. The American Heart Association estimates that 121.5 million adults in the United
States, or about 48% of the adult population, have some form of cardiovascular disease.
Globally, the World Health Organization (n.d.) estimates that 17.9 million people die due to
CVDs annually. Cardiovascular diseases include a range of illnesses that affect the heart and
blood vessels, such as coronary artery disease, heart failure, and stroke. Risk factors for these
diseases include high blood pressure, high cholesterol, smoking, diabetes, and obesity, among
others.
In particular, stroke and heart disease are shown to cause the highest prevalence,
morbidity, and mortality rates, compared to other CVDs. About 18.6 million adults in the U.S.
have coronary artery disease, which is the most common type of heart disease. Additionally,
about 6.2 million adults in the U.S. have heart failure, and about 795,000 people have a new or
recurrent stroke each year. The CDC estimates roughly 655,000 American die from heart disease
each year, which accounts for roughly one in every four mortalities. Additionally, stroke was
listed as the underlying cause of death for approximately 148,000 people in the U.S. in 2020.
This means that stroke was responsible for about 1 in every 19 deaths in the country.

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Additionally, the cost of treating heart disease and stroke is substantial, both in terms of
direct medical costs and indirect costs due to lost productivity and disability. The American
Heart Association estimates that treating heart disease and stroke costs the US economy roughly
$351.2 billion. Of this, roughly $219 billion is linked to direct medical costs, including
hospitalizations, readmissions, drugs, and outpatient care. The other $132.2 billion is linked to
indirect costs, particularly lost productivity because of disability or premature death.
In terms of lost work hours, heart disease and stroke were directly responsible for about
18.2 million lost workdays in 2019 alone. This figure includes work missed due to illness or
disability and days of reduced productivity as a result of these illnesses. In terms of disability, the
two disorders accounted for nearly 21% of all disability-adjusted life years lost. “Disability-
adjusted life years” measures the effect of disease on overall health and well-being of citizens,
taking into account both premature death and years lived with disability.
There is also sufficient empirical evidence to support the argument that heart disease and
stroke negatively impact the health, well-being, quality of life, cost, and overall satisfaction rates
of older patients admitted to critical care units with these conditions. Like other cardiovascular
diseases, older patients admitted to critical care units have been found to have significantly
elevated levels of high blood pressure, C-reactive protein (CRP), homocysteine, lipoprotein a,
fibrinogen, and troponin. CRP is a biomarker of inflammation and increased amounts can
augment the risk of heart disease and stroke. Homocysteine, an amino acid, and lipoprotein, a
type of cholesterol, have also been shown to increase the risk of heart disease and stroke.
Troponin is a protein released into blood following damage or injury heart muscle cells, while
fibrinogen is a primary protein involved in blood clotting. Elevated levels of both markers
increase the risk of heart disease and stroke (Xu et al., 2020). Increased weight, body mass index

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(BMI), waist-circumference ratio, respiration rate (shortness of breath), and pulse rate
(tachycardia) can also be used to diagnose and assess heart disease and stroke – although these
metrics are not specific biomarkers for stroke and heart disease.

5. Evidence-Based Solution/ Tests of Change

1 1/2 -2 pages)
This is where students stumble. You are required to identify THREE evidence-based change tests
aimed at improving 2-3 related poor outcomes. You should review these with Dr Gannon or Dr
Bradley before getting too far into your paper. Use the evidence (RCTs, systematic reviews,
meta-analyses, or guidelines) to justify your choice of interventions. No lower evidence is
acceptable

6. Aim Statement

This process improvement proposes implementing wearable technology like
smartwatches, fitness trackers, and fabric sensors to improve the monitoring of stroke and heart
disease biomarkers and symptoms, including blood pressure, heart rate, and other vital signs,
among, and the ultimate treatment of these orders among older patients 60+ admitted in critical
care units (CCUs) with these cardiovascular diseases. The secondary aim is to identify key
organizational and process insights necessary for the meaningful implementation of wearable
technology in healthcare organizations.

7. PDSA Process Improvement Framework

(1/2 page) PDSA is the preferred choice.

8. Stakeholders

8.1. Stakeholders and Their Roles/Interests in This Evaluation

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8.2. The Plan to Engage Them

9. Inputs (Resources)

What resources are available/needed to support the improvement process (e.g., staff, money,
space, time, partnerships, technology, etc.)?

10. Outputs
    (products, units of service delivered): (1/4 page
    What products (e.g., materials such as documents, units of services delivered, education
    materials, forms, policies, etc) are produced by your staff as a result of the activities performed?
11. Evaluation Design
    11.1. The Design for the Quality Improvement Project
    (e.g., quasi-experimental, pre-post with comparison group, time-series, case study, post-test only,
    etc etc 1 pg
    11.2. Intended Outcome Objectives
    11.2.1. Process objectives
    Ex. “To measure the number of participants….”
    “To measure the utility of the new protocol…”
    11.2.2. Outcome objectives
    Ex. “To measure the IMPACT of (intervention X) on (an outcome of interest, like participant
    satisfaction, cost, quality measures, errors, etc
12. Conclusion

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References

American Heart Association. (2021). 2021 heart disease and stroke statistics update fact sheet.
https://www.heart.org/-/media/phd-files-2/science-news/2/2021-heart-and-stroke-stat-
update/2021_heart_disease_and_stroke_statistics_update_fact_sheet_at_a_glance.pdf
Bayoumy, K., et al. (2021). Smart wearable devices in cardiovascular care: where we are and
how to move forward. Nature Reviews Cardiology, 18, 581-599.
https://doi.org/10.1038/s41569-021-00522-7
CDC. (2022). Heart disease and stroke.
https://www.cdc.gov/chronicdisease//publications/factsheets/heart-disease-stroke.htm
Prieto-Avalos, G., et al. (2022). Wearable devices for physical monitoring of heart: A review.
Biosensors, 12(5), 292. doi: 10.3390/bios12050292
Sidney, S., et al. (2022). Age-adjusted mortality rates and age and risk–associated contributions
to change in heart disease and stroke mortality, 2011-2019 and 2019-2020. JAMA
Network Open, 5(3). doi:10.1001/jamanetworkopen.2022.3872
Xu, C., et al. (2020). Brain–heart axis and biomarkers of cardiac damage and dysfunction after
stroke: A systematic review and meta-analysis. International Journal of Molecular
Sciences, 21(7). doi: 10.3390/ijms21072347
World Health Organization. (n.d.). Cardiovascular diseases. https://www.who.int/health-
topics/cardiovascular-diseases#tab=tab_1