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": "ðŸĪ• Trauma-related disorders", "emoji": "🚑", "spending": 198.6, "treatment": "Counseling and physical therapy", "savings": "$500"}, {"condition": "ðŸĶ€ Cancer", "emoji": "🎗ïļ", "spending": 171.0, "treatment": "Early detection and treatment", "savings": "$2000"}, {"condition": "🧠 Mental disorders", "emoji": "🧘", "spending": 150.8, "treatment": "Therapy and medication", "savings": "$1500"}, {"condition": "ðŸĶī Osteoarthritis and joint disorders", "emoji": "ðŸĨ", "spending": 142.4, "treatment": "Low-impact exercise and physical therapy", "savings": "$800"}, {"condition": "💉 Diabetes", "emoji": "ðŸĐļ", "spending": 107.4, "treatment": "Regular checkups and medication", "savings": "$1200"}, {"condition": "ðŸ˜Ū‍ðŸ’Ļ Chronic obstructive pulmonary disease and asthma", "emoji": "ðŸ˜Ū‍ðŸ’Ļ", "spending": 91.0, "treatment": "Inhalers and breathing exercises", "savings": "$600"}, {"condition": "ðŸĐš 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": "ðŸĶī 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": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as regular HbA1c testing, eye exams, and nephropathy screening." }, { "name": "Cardiovascular Disease", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, lipid profile screening, and blood pressure control." }, { "name": "Asthma", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, asthma action plans, and follow-up care after hospitalization." }, { "name": "Behavioral Health", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care after hospitalization." }, { "name": "Cancer Screening", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate cancer screening tests." }, { "name": "Immunizations", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate immunizations." }, { "name": "Maternity Care", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate prenatal care, postpartum care, and screenings." }, { "name": "Osteoporosis", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, bone density testing, and follow-up care." }, { "name": "Chronic Kidney Disease", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, monitoring, and follow-up care." }, { "name": "Depression", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ Providing timely and appropriate interventions, such as medication therapy, counseling, and follow-up care." }, { "name": "Attention Deficit Hyperactivity Disorder (ADHD)", "patient_population": "ðŸ‘Ĩ 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": "🛠ïļ 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 ðŸĐšðŸŽ€ | Clinical Code: CPT 77067 3. Colorectal Cancer Screening: % of adults screened for colorectal cancer ðŸĐšðŸ’Đ | Clinical Code: CPT 82274 4. Comprehensive Diabetes Care: % of diabetic patients who had all recommended tests ðŸĐšðŸĐđ | Clinical Code: LOINC 4548-4 5. Controlling High Blood Pressure: % of patients with controlled blood pressure ðŸĐšðŸ’Š | Clinical Code: ICD10 I10 6. Medication Management for Asthma: % of asthma patients with proper meds 💊🌎ïļ | Clinical Code: SNOMED 195967001 7. Follow-up After Mental Illness Hospitalization: % of patients with follow-up care ðŸĐšðŸĨ | Clinical Code: HCPCS G0181 8. Prenatal & Postpartum Care: % of pregnant women with proper care ðŸĪ°ðŸĐš | Clinical Code: ICD10 Z34 9. Comprehensive Eye Exam: % of diabetic patients with eye exam ðŸĐšðŸ‘€ | 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 ðŸĐšðŸ‘Đ | Clinical Code: CPT 87491 12. Avoidance of Antibiotic Treatment for Acute Bronchitis: % of patients without antibiotics ðŸĐšðŸ’Š | Clinical Code: ICD10 J20.9 13. Osteoporosis Management in Women: % of women with bone density test ðŸĐšðŸ’Š | Clinical Code: CPT 77080 14. Use of High-Risk Medications in the Elderly: % of elderly with safe meds 💊ðŸ‘īðŸ‘ĩ | Clinical Code: HCPCS G9612 15. Diabetes Screening for Schizophrenia or Bipolar Disorder: % of patients with mental illness screened 🧠ðŸĐš | Clinical Code: SNOMED 169609005 16. All-Cause Readmissions: % of patients readmitted within 30 days ðŸĐšðŸĨ | Clinical Code: ICD10 Z51.5 17. Antidepressant Medication Management: % of depressed patients with proper meds & follow-up ðŸĐšðŸ§  | Clinical Code: CPT 96127 18. Follow-up Care for Children Prescribed ADHD Medication: % of children with follow-up care ðŸĐšðŸ§’ | Clinical Code: ICD10 F90 19. Imaging Studies for Low Back Pain: % of patients without imaging studies ðŸĐšðŸ“Š | Clinical Code: ICD10 M54.5 20. Spirometry Testing for COPD: % of COPD patients with spirometry testing ðŸĐšðŸŦ | 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 ðŸ―ïļ E: Endocrine, nutritional, and metabolic diseases 🧠 F: Mental, behavioral, and neurodevelopmental disorders 🧠 G: Diseases of the nervous system 👁ïļ H0-H5: Eye and adnexa (accessory organs) diseases 👂 H6-H9: Ear and mastoid process diseases âĪïļ I: Circulatory system diseases ðŸ’Ļ J: Respiratory system diseases ðŸ―ïļ K: Digestive system diseases ðŸĶĩ L: Skin and subcutaneous tissue diseases 💊 M: Musculoskeletal and connective tissue diseases 🍆 N: Genitourinary system diseases ðŸ‘ķ O: Pregnancy, childbirth, and the puerperium (postpartum) issues ðŸ‘ķ P: Perinatal (before and after birth) conditions ðŸ‘ķ Q: Congenital (present at birth) malformations and deformations ðŸĪ’ R: Symptoms, signs, and abnormal clinical and laboratory findings ðŸĪ• S, T: Injury, poisoning, and other consequences of external causes ðŸĨ U: Special-purpose codes 🔍 V, W, Y: External causes of morbidity and mortality 🧎 Z: Factors influencing health status and contact with health services """)