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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": "💔 Heart disease", "emoji": "💗", "spending": 214.3, "treatment": "Regular checkups with a cardiologist", "savings": "$1000"}, | |
| {"condition": "🤕 Trauma-related disorders", "emoji": "🚑", "spending": 198.6, "treatment": "Counseling and physical therapy", "savings": "$500"}, | |
| {"condition": "🦀 Cancer", "emoji": "🎗️", "spending": 171.0, "treatment": "Early detection and treatment", "savings": "$2000"}, | |
| {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": 150.8, "treatment": "Therapy and medication", "savings": "$1500"}, | |
| {"condition": "🦴 Osteoarthritis and joint disorders", "emoji": "🏥", "spending": 142.4, "treatment": "Low-impact exercise and physical therapy", "savings": "$800"}, | |
| {"condition": "💉 Diabetes", "emoji": "🩸", "spending": 107.4, "treatment": "Regular checkups and medication", "savings": "$1200"}, | |
| {"condition": "😮💨 Chronic obstructive pulmonary disease and asthma", "emoji": "😮💨", "spending": 91.0, "treatment": "Inhalers and breathing exercises", "savings": "$600"}, | |
| {"condition": "🩺 Hypertension", "emoji": "💉", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$900"}, | |
| {"condition": "🔬 Hyperlipidemia", "emoji": "🔬", "spending": 83.9, "treatment": "Lifestyle changes and medication", "savings": "$700"}, | |
| {"condition": "🦴 Back problems", "emoji": "🧍", "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": "👥 Patients with diabetes", | |
| "icd10_code_range": "📈 E08 - E13", | |
| "gap_identification": "🔍 Identifying patients with HbA1c levels > 9%, patients who have not received eye exams, and patients who have not received nephropathy screening.", | |
| "gap_closure_process": "🛠️ Providing timely and appropriate interventions, such as regular HbA1c testing, eye exams, and nephropathy screening." | |
| }, | |
| { | |
| "name": "Cardiovascular Disease", | |
| "patient_population": "👥 Patients with cardiovascular disease", | |
| "icd10_code_range": "📈 I20 - I25", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, lipid profile screening, and blood pressure control." | |
| }, | |
| { | |
| "name": "Asthma", | |
| "patient_population": "👥 Patients with asthma", | |
| "icd10_code_range": "📈 J45", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, asthma action plans, and follow-up care after hospitalization." | |
| }, | |
| { | |
| "name": "Behavioral Health", | |
| "patient_population": "👥 Patients with behavioral health conditions", | |
| "icd10_code_range": "📈 F00 - F99", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care after hospitalization." | |
| }, | |
| { | |
| "name": "Cancer Screening", | |
| "patient_population": "👥 Patients eligible for cancer screening", | |
| "icd10_code_range": "📈 C00 - D48", | |
| "gap_identification": "🔍 Identifying patients who have not received appropriate cancer screening tests, such as mammograms, colonoscopies, and cervical cancer screening.", | |
| "gap_closure_process": "🛠️ Providing timely and appropriate cancer screening tests." | |
| }, | |
| { | |
| "name": "Immunizations", | |
| "patient_population": "👥 Patients eligible for immunizations", | |
| "icd10_code_range": "📈 Z23", | |
| "gap_identification": "🔍 Identifying patients who have not received appropriate immunizations, such as flu shots, pneumococcal vaccines, and HPV vaccines.", | |
| "gap_closure_process": "🛠️ Providing timely and appropriate immunizations." | |
| }, | |
| { | |
| "name": "Maternity Care", | |
| "patient_population": "👥 Pregnant patients", | |
| "icd10_code_range": "📈 O00 - O99", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate prenatal care, postpartum care, and screenings." | |
| }, | |
| { | |
| "name": "Osteoporosis", | |
| "patient_population": "👥 Patients with osteoporosis", | |
| "icd10_code_range": "📈 M80 - M82", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, bone density testing, and follow-up care." | |
| }, | |
| { | |
| "name": "Chronic Kidney Disease", | |
| "patient_population": "👥 Patients with chronic kidney disease", | |
| "icd10_code_range": "📈 N18", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, monitoring, and follow-up care." | |
| }, | |
| { | |
| "name": "Depression", | |
| "patient_population": "👥 Patients with depression", | |
| "icd10_code_range": "📈 F32 - F33", | |
| "gap_identification": "🔍 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": "🛠️ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care." | |
| }, | |
| { | |
| "name": "Attention Deficit Hyperactivity Disorder (ADHD)", | |
| "patient_population": "👥 Patients with ADHD", | |
| "icd10_code_range": "📈 F90", | |
| "gap_identification": "🔍 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": "🛠️ 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 🧒💉 | Clinical Code: ICD10 Z28.2 | |
| 2. Breast Cancer Screening: % of women with mammogram in past 2 yrs 🩺🎀 | Clinical Code: CPT 77067 | |
| 3. Colorectal Cancer Screening: % of adults screened for colorectal cancer 🩺💩 | Clinical Code: CPT 82274 | |
| 4. Comprehensive Diabetes Care: % of diabetic patients who had all recommended tests 🩺🩹 | Clinical Code: LOINC 4548-4 | |
| 5. Controlling High Blood Pressure: % of patients with controlled blood pressure 🩺💊 | Clinical Code: ICD10 I10 | |
| 6. Medication Management for Asthma: % of asthma patients with proper meds 💊🌬️ | Clinical Code: SNOMED 195967001 | |
| 7. Follow-up After Mental Illness Hospitalization: % of patients with follow-up care 🩺🏥 | Clinical Code: HCPCS G0181 | |
| 8. Prenatal & Postpartum Care: % of pregnant women with proper care 🤰🩺 | Clinical Code: ICD10 Z34 | |
| 9. Comprehensive Eye Exam: % of diabetic patients with eye exam 🩺👀 | Clinical Code: CPT 92014 | |
| 10. Childhood Weight Assessment: % of children with BMI assessment 🧒📏 | Clinical Code: ICD10 Z00.121 | |
| 11. Chlamydia Screening in Women: % of sexually active women screened 🩺👩 | Clinical Code: CPT 87491 | |
| 12. Avoidance of Antibiotic Treatment for Acute Bronchitis: % of patients without antibiotics 🩺💊 | Clinical Code: ICD10 J20.9 | |
| 13. Osteoporosis Management in Women: % of women with bone density test 🩺💪 | Clinical Code: CPT 77080 | |
| 14. Use of High-Risk Medications in the Elderly: % of elderly with safe meds 💊👴👵 | Clinical Code: HCPCS G9612 | |
| 15. Diabetes Screening for Schizophrenia or Bipolar Disorder: % of patients with mental illness screened 🧠🩺 | Clinical Code: SNOMED 169609005 | |
| 16. All-Cause Readmissions: % of patients readmitted within 30 days 🩺🏥 | Clinical Code: ICD10 Z51.5 | |
| 17. Antidepressant Medication Management: % of depressed patients with proper meds & follow-up 🩺🧠 | Clinical Code: CPT 96127 | |
| 18. Follow-up Care for Children Prescribed ADHD Medication: % of children with follow-up care 🩺🧒 | Clinical Code: ICD10 F90 | |
| 19. Imaging Studies for Low Back Pain: % of patients without imaging studies 🩺📊 | Clinical Code: ICD10 M54.5 | |
| 20. Spirometry Testing for COPD: % of COPD patients with spirometry testing 🩺🫁 | Clinical Code: CPT 94010 | |
| """) | |
| st.markdown(""" | |
| ICD10 Code Categories for ICD10 Diagnosis used in ADT, Health Service Cases, and Claims : | |
| 💉 A, B: Infectious and parasitic diseases | |
| 🧬 C, D0-D4: Neoplasms (tumors) | |
| 💉 D5-D9: Blood disorders and immune system diseases | |
| 🍽️ E: Endocrine, nutritional, and metabolic diseases | |
| 🧠 F: Mental, behavioral, and neurodevelopmental disorders | |
| 🧠 G: Diseases of the nervous system | |
| 👁️ H0-H5: Eye and adnexa (accessory organs) diseases | |
| 👂 H6-H9: Ear and mastoid process diseases | |
| ❤️ I: Circulatory system diseases | |
| 💨 J: Respiratory system diseases | |
| 🍽️ K: Digestive system diseases | |
| 🦵 L: Skin and subcutaneous tissue diseases | |
| 💪 M: Musculoskeletal and connective tissue diseases | |
| 🍆 N: Genitourinary system diseases | |
| 👶 O: Pregnancy, childbirth, and the puerperium (postpartum) issues | |
| 👶 P: Perinatal (before and after birth) conditions | |
| 👶 Q: Congenital (present at birth) malformations and deformations | |
| 🤒 R: Symptoms, signs, and abnormal clinical and laboratory findings | |
| 🤕 S, T: Injury, poisoning, and other consequences of external causes | |
| 🏥 U: Special-purpose codes | |
| 🔍 V, W, Y: External causes of morbidity and mortality | |
| 🧬 Z: Factors influencing health status and contact with health services | |
| """) |