Primary Self Care Algorithms
What is Primary Self Care?
Primary self care (PSC) exists at the intersection of primary health care and self-care. With an emphasis on self-management, self-testing, and self-awareness, PSC enables individuals to understand and optimize their health status through self-care interventions. While some PSC methods invite collaboration with clinical providers and others are entirely independent of healthcare systems, all can be applied to improve health outcomes at various stages of life1.
Why Primary Self Care?
According to The World Health Organization, there will be a shortage of 18 million physicians by 2030. Primary self care has the potential to fill this gap and reduce the burden on healthcare systems through better screening and prevention of diseases, all while providing more education on self-management of conditions. PSC empowers individuals to understand their health data and offers ways to effectively act on it. This leads to more engagement when patients interact with the healthcare system. Primary self care is also a way for individuals to personalize their care according to their needs and claim more decision making power in their health.
What is a Primary Self Care algorithm?
Primary self care algorithms are decision support tools for individuals to better understand their health and the steps needed to optimize their health status. PSC algorithms include clinical decision support (CDS) tools, patient decision aids, health assessments, and screening and testing services.
Why does the PSC Algorithms Project matter?
Despite being at the core of self care interventions, primary self care has been inconsistently defined. In light of the growing number of at-home healthcare technologies and services, there is a "pressing need for a clearer conceptualization of self care" as well as what self-care is not1. A publicly-available knowledge base of PSC algorithms can serve as an instrumental resource for patients, policy makers, and healthcare workers. This project will also reveal the current gaps in research and implementation of PSC models.
Top 10 Primary Self Care Algorithms
1. Vaccine Decision Aids
The global response to the COVID-19 pandemic highlighted just how critical vaccination efforts are in mitigating the spread and severity of infectious diseases. In 2020, COVID-19 rose to the third leading cause of death in the US and caused 6.26 million deaths globally2. In the decade, vaccine-preventable diseases like measles and pertussis have begun to rise as vaccine hesitancy spreads3. Despite the safety and efficacy of vaccines, getting people vaccinated has proven challenging due to a combination of mistrust in the scientific community, lack of education, and insufficient access.
Models
- COVID-19: Vaccine Options (Original source no longer available)5
- Copyright © 2022 EBSCO Publishing, Inc.
- Immunization Calculation Engine (ICE)39
- LGPLv3, open source
- Patient decision aid in vaccination: a systematic review of the literature4
- License not found, likely closed
2. Blood Pressure Monitoring
Heart disease is the leading cause of death in the United States with more than 659,000 lives lost each year. Coronary heart disease, heart attacks, and other related heart conditions make up one in every four deaths, which amounts to spending $363 billion a year on healthcare services and medication10. The key risk factors of heart disease are behavior based: poor nutrition, physical inactivity, and high alcohol or drug consumption; early detection and promotion of healthy behaviors can prevent 34% of deaths due to heart disease11.
Models
- The USPSTF provides an A grade recommendation for screening for hypertension in adults 18 years or older without hypertension12
- Copyright Notice. U.S. Preventative Task Force. September 2017
- Self monitoring blood pressure in conjunction with clinical support in patients with hypertension yields significant BP reductions13
- Copyright © 2017 Tucker et al.
- Creative Commons Attribution License, open source
3. At-Home Urinalysis
Kidney disease affects more than 15% of the US population, or 1 in 7 people. However, 90% of affected individuals are unaware of their condition as symptoms typically don't appear until the late stages14. Key risk factors for kidney disease are comorbidities such as diabetes, hypertension, and obesity. Minority groups are at highest risk of developing severe kidney disease and kidney failure due to a higher prevalence of associated comorbidities and disparities in primary care access; as a result, these groups are less likely to receive pre-dialysis care and must wait longer for kidney transplants. Early detection of kidney disease is essential to ensuring that individuals can take preventative care measures or receive pre-dialysis treatment options.
Models
- Healthy.io home-based urinalysis test kit and smartphone app15
- 10 parameter urinalysis dipstick test16
- Lab Tests Online®
- Copyright © 2022 Regenstrief Institute, Inc
- Toilet mountable at-home urinalysis17
4. Mental Health Assessments
In the United States, 1 in 5 individuals live with a mental illness, with a higher prevalence among minorities and young adults; in 2020, only half of the 52.9 million affected people received any sort of treatment or counseling6. The stigmatization and poor education surrounding mental illness make it difficult for those seeking diagnosis and treatment. Suicide was the twelfth leading cause of death in the US in 2020 and most common in middle-aged white men7. Since three-fourths of mental illnesses begin before the age of 24, early identification and treatment are essential to lowering suicide and suicide attempt rates.
Models
- Computer Assisted Self Assessment (CART) in persons with severe mental illness (SMI)8
- License not found, likely closed
- Ecological momentary assessment (EMA) to assess and support self-management in serious mental illness9
- Copyright © 2006 CMA Media Inc.
5. Vision Tests
Vision impairment and blindness impact 2.2 billion people around the world, and more than half of these have not yet been diagnosed21. The most common vision loss diseases and leading causes of blindness are age-related macular degeneration, diabetic retinopathy, and glaucoma. Vision loss is also highly correlated to comorbidities like hearing impairment, kidney disease, stroke, arthritis, and heart disease22. Early screening and diagnosis of vision loss are key to correcting vision acuity before disease progression, and self-management of comorbidities can prevent further vision loss.
Models
6. Blood Glucose Monitoring
One of the most prevalent chronic conditions in the US, diabetes is the seventh leading cause of death. There are 37.3 million people currently living with diabetes in the country, and 38% of the adult population lives with pre-diabetes, which often goes undiagnosed until it progresses to Type 2 diabetes25. Early diagnosis and lifestyle changes can be effective in preventing diabetes progression, particularly for individuals with pre-diabetes. Comorbidities of diabetes include hypertension, chronic kidney disease, and cardiovascular disease, which means that early diagnosis, treatment, and lifestyle interventions are crucial.
Models
7. Breast Self-Exam
Breast cancer is the most prevalent cancer in the US and the second leading cause of cancer death in women. One in eight women (13%) are at risk of developing breast cancer during their lifetime. Black women in particular have the highest risk of developing breast cancer earlier than white women and experience a higher mortality rate than any other group. The incidence of breast cancer has been trending up in the past years, though deaths have been slowly decreasing, likely due to improved screening and early detection18.
Models
- Breast Self-Exam (BSE)19
- Copyright © 2022. BreastCancer.org
- Breast Cancer Risk Assessment Tool20
- BrCa RAM License Agreement, Open source
8. Birth Control Decision Aid
Globally, more than 200 million women face an unmet need for family planning options and contraceptives, and 1.4 million unplanned pregnancies occur each year28. Inadequate access to contraception is directly related to higher rates of unintended pregnancies and births, higher rates of STDs, and poorer educational and economic outcomes. There are lower rates of contraception usage among racial and ethnic minorities, a reflection of inequities in healthcare access and insufficient education around reproductive health. Contraceptive access and education are effective in reducing unintended pregnancies and in turn increasing high school graduation rates29. Women who want to avoid pregnancy often cite lack of access as a reason for not using contraception, but concerns about side effects and lack of knowledge are also barriers to access30.
Models
- A Decision Aid to Help Women Choose and Use a Method of Birth Control, PCORI31
- Copyright 2019. University of California San Francisco
- Your Birth Control Choices32
- Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, Open source
9. Air Quality Monitor
Chronic respiratory diseases are the third leading cause of death in the US and account for 7.5 million deaths worldwide each year33. These respiratory illnesses include chronic obstructive pulmonary disease (COPD), asthma, bronchitis, and other lung diseases. These conditions often start early in life and are exacerbated by environmental pollutants, poor nutrition, obesity, and lack of physical activity. Onset of these diseases can be determined by environmental factors such as irritants or allergens like smoke as well as lifestyle habits formed in adolescence, making it especially crucial that CRD risk factors are addressed early on.
Models
- Indoor air quality monitoring systems for public health34
- Creative Commons Attribution 4.0 International License, Open source
10. Pulse Oximetry
A pulse oximeter is an electronic device that clips onto a patient's fingertip or ear to measure the saturation of oxygen in their blood. The reading is noninvasive and painless, and results take less than a minute35. Pulse oximetry is often considered the "fifth vital sign" as it is used for routine screenings of pulmonary health, diabetes, and sleep disorders.
Models
Application of Primary Self Care Across Life
| Self-care topic | 0-5 years old | 6-12 | 13-20 | 21-30 | 31-40 | 41-50 | 51-60 | 61-70 | 71-80 | 81-90 | 90+ |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Vaccinations |  | | | | | | | | | | |
| Blood Pressure | | | | | | | | | |||
| Urinalysis | | | | | | ||||||
| Mental Health | | | | | | | | | | ||
| Vision Test | | | | | | | | | | | |
| Glucose Monitoring | | | | | | | |||||
| Breast Self-Exam | | | | | | | |||||
| Air Quality Monitor | | | | | | | | | | | |
| Pulse Oximetry | | | | | |
Database of Primary Self Care Algorithms
The AirTable below contains a database of Primary Self Care algorithms organized by the impacted bodily health system, the relevant social determinants of health, and the type of test or assessment. Relevant resources and information about each model are provided as well as the most prevalent health condition addressed.
Methods
Decision Matrix
The ranking of the 10 top Primary Self Care algorithms were determined by rating each algorithm against the following decision matrix adapted from methods of evaluating clinical decision support38.
| Criteria | Weight (1-4) | 1 | 0 | -1 |
|---|---|---|---|---|
| Audience How many patients & clinicians do/or can utilize this algorithm? | 2 | can be utilized by the majority of people, regardless of health status | utilized for common or highly prevalent conditions | utilized for only rare conditions |
| Effectiveness How much of a difference can the algorithm make on someone's health status regardless of condition progression? | 4 | high impact at many stages in disease progression | moderate impact at some stages in disease progression | low or no impact at many stages of disease progression |
| Validity & Reliability Has this algorithm been rigorously tested and have results been replicated? | 4 | validated and replicated by many credible institutions | validated by some credible sources, limited replication studies | not validated or replicated by credible sources |
| Complexity How easy is it to learn to use and understand results from an algorithm? | 2 | almost no learning curve, easy to implement and learn from results | moderate learning curve and results are mostly manageable to interpret | high learning curve to use and results are difficult to interpret |
| Cost How expensive are any necessary tools/services? | 3 | $ low cost or free | $$ | $$$ |
| Availability How readily available and accessible is this tool? | 1 | over the counter or diy | some barrier to access (clinical treatment or prescription, specially ordered, etc.) | still in development, not openly available |
| Support How much clinical support or guidance is required? | 2 | completely independent | minimal community or clinical involvement | requires clinical support or intervention |
| Licensing Is the algorithm open or closed source? | 2 | open | unknown licensing | closed |
Ranking of Top 10 Algorithms
| Criteria | Weight (1-4) | Vaccinations | Blood Pressure | Urinalysis | Mental Health | Vision Test | Glucose Monitoring | Breast Self-Exam | Birth Control | Air Quality Monitor | Pulse Oximetry |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Audience | 2 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 0 |
| Effectiveness | 4 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | -1 |
| Validity/Reliability | 4 | 1 | 1 | 1 | 1 | 0 | 1 | -1 | 1 | 0 | 0 |
| Complexity | 3 | 1 | 1 | -1 | 1 | 1 | 0 | 1 | -1 | 0 | 0 |
| Cost | 3 | 1 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
| Availability | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Support | 2 | -1 | 0 | 1 | 1 | 1 | 0 | 1 | -1 | 1 | 1 |
| Licensing | 2 | 1 | 1 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 0 |
| Weighted Totals | 17 | 16 | 15 | 15 | 11 | 11 | 9 | 8 | 7 | -1 |
Next Steps
Future iterations of the PSC Algorithms Project will include an even more comprehensive database and an updated ranking of the top algorithms. The decision matrix will also be expanded to include the applicability in global settings, compliance, error rates, and variability in implementation; there will be a more in-depth look at licensing information as well. Additionally, this project will inform the editing of Wikipedia's self-care page, which does not currently distinguish between primary self care and self-care.
The ultimate purpose of the Primary Self Care Algorithms Project is to support:
- Healthcare UX Designers creating intentional, patient-first tools and services.
- Providers tailoring medical care to patient needs.
- Patients seeking intuitive, value-adding tools as they take ownership over their health.
Authors
Arpna Ghanshani, GoInvo
Chloe Ma, GoInvo
Juhan Sonin, GoInvo
Contributors
Samantha Wuu
Huahua Zhu
Eric Benoit
Craig McGinley
References
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