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import streamlit as st
import pandas as pd
import random
import plotly.graph_objects as go
import plotly.express as px
def health_game():
# Define the states and conditions of interest
states = ["Minnesota", "Florida", "California"]
top_n = 10
# Define the list dictionary of top 10 health conditions descending by cost, with emojis, treatment recommendation and potential savings
health_conditions = [
{"condition": "๐ Heart disease", "emoji": "๐", "spending": 214.3, "treatment": "Regular checkups with a cardiologist", "savings": "$1000"},
{"condition": "๐ค Trauma-related disorders", "emoji": "๐", "spending": 198.6, "treatment": "Counseling and physical therapy", "savings": "$500"},
{"condition": "๐ฆ Cancer", "emoji": "๐๏ธ", "spending": 171.0, "treatment": "Early detection and treatment", "savings": "$2000"},
{"condition": "๐ง Mental disorders", "emoji": "๐ง", "spending": 150.8, "treatment": "Therapy and medication", "savings": "$1500"},
{"condition": "๐ฆด Osteoarthritis and joint disorders", "emoji": "๐ฅ", "spending": 142.4, "treatment": "Low-impact exercise and physical therapy", "savings": "$800"},
{"condition": "๐ Diabetes", "emoji": "๐ฉธ", "spending": 107.4, "treatment": "Regular checkups and medication", "savings": "$1200"},
{"condition": "๐ฎโ๐จ Chronic obstructive pulmonary disease and asthma", "emoji": "๐ฎโ๐จ", "spending": 91.0, "treatment": "Inhalers and breathing exercises", "savings": "$600"},
{"condition": "๐ฉบ Hypertension", "emoji": "๐", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$900"},
{"condition": "๐ฌ Hyperlipidemia", "emoji": "๐ฌ", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$700"},
{"condition": "๐ฆด Back problems", "emoji": "๐ง", "spending": 67.0, "treatment": "Physical therapy and exercise", "savings": "$400"}
]
# Create a DataFrame from the list dictionary
df_top_conditions = pd.DataFrame(health_conditions)
# Calculate the total spending
total_spending = round(df_top_conditions["spending"].sum(), 1)
# Define the roll function
def roll():
rolls = [random.randint(1, 10) for _ in range(1000)]
frequencies = [rolls.count(i) for i in range(1, 11)]
return frequencies
# Define the sunburst chart
fig_sunburst = go.Figure(go.Sunburst(
labels=df_top_conditions["emoji"] + " " + df_top_conditions["condition"],
parents=[""] * top_n,
values=df_top_conditions["spending"],
maxdepth=2
))
# Customize the layout of the sunburst chart
#fig_sunburst.update_layout(title=f"Top {top_n} Health Conditions in {', '.join(states)} by Spending (Total: ${total_spending}B)")
fig_sunburst.update_layout(title=f"Top {top_n} Health Conditions by Spending (Total: ${total_spending}B)")
# Display the sunburst chart and variants per condition in the Streamlit app
st.plotly_chart(fig_sunburst)
condition_idx = st.selectbox("Select your current health condition", df_top_conditions.index)
row = df_top_conditions.loc[condition_idx]
st.write(f"Based on the severity of your {row['condition']}, we recommend {row['treatment']} for early treatment. This could save you up to {row['savings']} in healthcare costs.")
frequencies = roll()
fig_bar = px.bar(x=[f"Variant {i}" for i in range(1, 11)], y=frequencies[:10], labels={'x': 'Variant', 'y': 'Frequency'})
fig_bar.update_layout(title=f"Variants of {row['condition']} ({row['emoji']})")
st.plotly_chart(fig_bar)
health_game()
import streamlit as st
health_conditions = [
{
"name": "Diabetes",
"patient_population": "๐ฅ Patients with diabetes",
"icd10_code_range": "๐ E08 - E13",
"gap_identification": "๐ Identifying patients with HbA1c levels > 9%, patients who have not received eye exams, and patients who have not received nephropathy screening.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as regular HbA1c testing, eye exams, and nephropathy screening."
},
{
"name": "Cardiovascular Disease",
"patient_population": "๐ฅ Patients with cardiovascular disease",
"icd10_code_range": "๐ I20 - I25",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received lipid profile screening, and patients who have not received blood pressure control.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, lipid profile screening, and blood pressure control."
},
{
"name": "Asthma",
"patient_population": "๐ฅ Patients with asthma",
"icd10_code_range": "๐ J45",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received asthma action plans, and patients who have not received follow-up care after hospitalization.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, asthma action plans, and follow-up care after hospitalization."
},
{
"name": "Behavioral Health",
"patient_population": "๐ฅ Patients with behavioral health conditions",
"icd10_code_range": "๐ F00 - F99",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received appropriate counseling, and patients who have not received follow-up care after hospitalization.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care after hospitalization."
},
{
"name": "Cancer Screening",
"patient_population": "๐ฅ Patients eligible for cancer screening",
"icd10_code_range": "๐ C00 - D48",
"gap_identification": "๐ Identifying patients who have not received appropriate cancer screening tests, such as mammograms, colonoscopies, and cervical cancer screening.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate cancer screening tests."
},
{
"name": "Immunizations",
"patient_population": "๐ฅ Patients eligible for immunizations",
"icd10_code_range": "๐ Z23",
"gap_identification": "๐ Identifying patients who have not received appropriate immunizations, such as flu shots, pneumococcal vaccines, and HPV vaccines.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate immunizations."
},
{
"name": "Maternity Care",
"patient_population": "๐ฅ Pregnant patients",
"icd10_code_range": "๐ O00 - O99",
"gap_identification": "๐ Identifying patients who have not received appropriate prenatal care, patients who have not received postpartum care, and patients who have not received appropriate screenings.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate prenatal care, postpartum care, and screenings."
},
{
"name": "Osteoporosis",
"patient_population": "๐ฅ Patients with osteoporosis",
"icd10_code_range": "๐ M80 - M82",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received bone density testing, and patients who have not received appropriate follow-up care.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, bone density testing, and follow-up care."
},
{
"name": "Chronic Kidney Disease",
"patient_population": "๐ฅ Patients with chronic kidney disease",
"icd10_code_range": "๐ N18",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received appropriate monitoring, and patients who have not received appropriate follow-up care.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, monitoring, and follow-up care."
},
{
"name": "Depression",
"patient_population": "๐ฅ Patients with depression",
"icd10_code_range": "๐ F32 - F33",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received appropriate counseling, and patients who have not received appropriate follow-up care.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care."
},
{
"name": "Attention Deficit Hyperactivity Disorder (ADHD)",
"patient_population": "๐ฅ Patients with ADHD",
"icd10_code_range": "๐ F90",
"gap_identification": "๐ Identifying patients who have not received appropriate medication therapy, patients who have not received appropriate counseling, and patients who have not received appropriate follow-up care.",
"gap_closure_process": "๐ ๏ธ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care."
}
]
st.title("HEDIS Gap Closure Process for Top 10 Health Conditions")
for condition in health_conditions:
st.header(f"{condition['name']}")
st.markdown(f"{condition['patient_population']}")
st.markdown(f"{condition['icd10_code_range']}")
st.markdown(f"{condition['gap_identification']}")
st.markdown(f"{condition['gap_closure_process']}")
st.markdown("""
# References on gap closure and reporting for value-based care:
These resources provide information and guidance on how to close gaps in care, improve quality scores, and report on quality measures to receive compensation in value-based care. They also discuss the use of health information technology and pay for performance programs to improve quality reporting and outcomes.
1. "Closing Gaps in Care: How to Improve Quality Scores and Boost Reimbursement" by Becker's Hospital Review - https://www.beckershospitalreview.com/close-care-documentation-gaps-expert-tips-for-better-quality-reporting.html
2. "Closing Gaps in Care with Advanced Interoperability Capabilities" by HealthPayerIntelligence - https://healthpayerintelligence.com/news/closing-gaps-in-care-with-advanced-interoperability-capabilities
3. https://www.healthit.gov/topic/federal-incentive-programs/MACRA/MIPS/quality-measures-reporting
4. https://www.ama-assn.org/practice-management/medicare-medicaid/quality-payment-program-qpp-specifics#:~:text=The%20QPP%20was%20created%20by,Incentive%20Payment%20System%20(MIPS).
5. https://qpp.cms.gov/about/qpp-overview
""")
st.markdown("""
# Top 20 HEDIS Gap Closure Evidence
Below is a list of the top 20 HEDIS gap closure evidence, along with the corresponding clinical codes that best represent the evidence submitted to show the gap is closed.
1. Childhood Immunization: % of children immunized by age two ๐ง๐ | Clinical Code: ICD10 Z28.2
2. Breast Cancer Screening: % of women with mammogram in past 2 yrs ๐ฉบ๐ | Clinical Code: CPT 77067
3. Colorectal Cancer Screening: % of adults screened for colorectal cancer ๐ฉบ๐ฉ | Clinical Code: CPT 82274
4. Comprehensive Diabetes Care: % of diabetic patients who had all recommended tests ๐ฉบ๐ฉน | Clinical Code: LOINC 4548-4
5. Controlling High Blood Pressure: % of patients with controlled blood pressure ๐ฉบ๐ | Clinical Code: ICD10 I10
6. Medication Management for Asthma: % of asthma patients with proper meds ๐๐ฌ๏ธ | Clinical Code: SNOMED 195967001
7. Follow-up After Mental Illness Hospitalization: % of patients with follow-up care ๐ฉบ๐ฅ | Clinical Code: HCPCS G0181
8. Prenatal & Postpartum Care: % of pregnant women with proper care ๐คฐ๐ฉบ | Clinical Code: ICD10 Z34
9. Comprehensive Eye Exam: % of diabetic patients with eye exam ๐ฉบ๐ | Clinical Code: CPT 92014
10. Childhood Weight Assessment: % of children with BMI assessment ๐ง๐ | Clinical Code: ICD10 Z00.121
11. Chlamydia Screening in Women: % of sexually active women screened ๐ฉบ๐ฉ | Clinical Code: CPT 87491
12. Avoidance of Antibiotic Treatment for Acute Bronchitis: % of patients without antibiotics ๐ฉบ๐ | Clinical Code: ICD10 J20.9
13. Osteoporosis Management in Women: % of women with bone density test ๐ฉบ๐ช | Clinical Code: CPT 77080
14. Use of High-Risk Medications in the Elderly: % of elderly with safe meds ๐๐ด๐ต | Clinical Code: HCPCS G9612
15. Diabetes Screening for Schizophrenia or Bipolar Disorder: % of patients with mental illness screened ๐ง ๐ฉบ | Clinical Code: SNOMED 169609005
16. All-Cause Readmissions: % of patients readmitted within 30 days ๐ฉบ๐ฅ | Clinical Code: ICD10 Z51.5
17. Antidepressant Medication Management: % of depressed patients with proper meds & follow-up ๐ฉบ๐ง | Clinical Code: CPT 96127
18. Follow-up Care for Children Prescribed ADHD Medication: % of children with follow-up care ๐ฉบ๐ง | Clinical Code: ICD10 F90
19. Imaging Studies for Low Back Pain: % of patients without imaging studies ๐ฉบ๐ | Clinical Code: ICD10 M54.5
20. Spirometry Testing for COPD: % of COPD patients with spirometry testing ๐ฉบ๐ซ | Clinical Code: CPT 94010
""")
st.markdown("""
ICD10 Code Categories for ICD10 Diagnosis used in ADT, Health Service Cases, and Claims :
๐ A, B: Infectious and parasitic diseases
๐งฌ C, D0-D4: Neoplasms (tumors)
๐ D5-D9: Blood disorders and immune system diseases
๐ฝ๏ธ E: Endocrine, nutritional, and metabolic diseases
๐ง F: Mental, behavioral, and neurodevelopmental disorders
๐ง G: Diseases of the nervous system
๐๏ธ H0-H5: Eye and adnexa (accessory organs) diseases
๐ H6-H9: Ear and mastoid process diseases
โค๏ธ I: Circulatory system diseases
๐จ J: Respiratory system diseases
๐ฝ๏ธ K: Digestive system diseases
๐ฆต L: Skin and subcutaneous tissue diseases
๐ช M: Musculoskeletal and connective tissue diseases
๐ N: Genitourinary system diseases
๐ถ O: Pregnancy, childbirth, and the puerperium (postpartum) issues
๐ถ P: Perinatal (before and after birth) conditions
๐ถ Q: Congenital (present at birth) malformations and deformations
๐ค R: Symptoms, signs, and abnormal clinical and laboratory findings
๐ค S, T: Injury, poisoning, and other consequences of external causes
๐ฅ U: Special-purpose codes
๐ V, W, Y: External causes of morbidity and mortality
๐งฌ Z: Factors influencing health status and contact with health services
""") |