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closes yubin-park#66. adds full_partial_nondual, lti and graft_duration arguments to HCCEngine.riskprofile() necessary for the ESRDv24 model. Adds _E2423T1M for ESRDv24 interactions and _E2423T1P for ESRDv24 risk coefficient lookups.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,67 @@ | ||
| from collections import Counter | ||
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| def create_interactions(cc_lst, DISABL, age): | ||
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| x = Counter(cc_lst) | ||
| z = Counter() | ||
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| # payable HCC's count interaction | ||
| hcccnt = len([k for k in x.keys() if "HCC" in k]) | ||
| if hcccnt > 9: | ||
| x["D10P"] = 1 | ||
| elif hcccnt > 0: | ||
| x["D{}".format(hcccnt)] = 1 | ||
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| # diagnostic categories | ||
| z["CANCER"] = max(x["HCC8"], x["HCC9"], x["HCC10"], | ||
| x["HCC11"], x["HCC12"]) | ||
| z["DIABETES"] = max(x["HCC17"], x["HCC18"], x["HCC19"]) | ||
| #z["IMMUNE"] = x["HCC47"] | ||
| z["CARD_RESP_FAIL"] = max(x["HCC82"], x["HCC83"], x["HCC84"]) | ||
| z["CHF"] = x["HCC85"] | ||
| z["gCopdCF"] = max(x["HCC110"], x["HCC111"], x["HCC112"]) | ||
| z["RENAL_V24"] = max(x["HCC134"], x["HCC135"], x["HCC136"], | ||
| x["HCC137"], x["HCC138"]) | ||
| #z["COMPL"] = x["HCC176"] | ||
| z["SEPSIS"] = x["HCC2"] | ||
| z["gSubstanceUseDisorder_V24"] = max(x["HCC54"], x["HCC55"], x["HCC56"]) | ||
| z["gPsychiatric_V24"] = max(x["HCC57"], x["HCC58"], x["HCC59"], x["HCC60"]) | ||
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| # community model interactions | ||
| x["HCC47_gCancer"] = x["HCC47"] * z["CANCER"] | ||
| x["DIABETES_CHF"] = z["DIABETES"] * z["CHF"] | ||
| x["CHF_gCopdCF"] = z["CHF"] * z["gCopdCF"] | ||
| x["HCC85_gRenal_V24"] =x["HCC85"] * z["RENAL_V24"] | ||
| x["gCopdCF_CARD_RESP_FAIL"] = z["gCopdCF"] * z["CARD_RESP_FAIL"] | ||
| x["HCC85_HCC96"] = x["HCC85"] * x["HCC96"] | ||
| x["gSubUseDs_gPsych_V24"] = z["gSubstanceUseDisorder_V24"] * z["gPsychiatric_V24"] | ||
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| x["NONAGED_gSubUseDs_gPsych"] = DISABL * x["gSubUseDs_gPsych_V24"] | ||
| x["NONAGED_HCC6"] = DISABL * x["HCC6"] | ||
| x["NONAGED_HCC34"] = DISABL * x["HCC34"] | ||
| x["NONAGED_HCC46"] = DISABL * x["HCC46"] | ||
| x["NONAGED_HCC110"] = DISABL * x["HCC110"] | ||
| x["NONAGED_HCC176"] = DISABL * x["HCC176"] | ||
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| # institutional model interactions | ||
| x["PRESSURE_ULCER"] = max(x["HCC157"], x["HCC158"], | ||
| x["HCC159"]) | ||
| x["SEPSIS_PRESSURE_ULCER_V24"] = z["SEPSIS"] * x["PRESSURE_ULCER"] | ||
| x["SEPSIS_ARTIF_OPENINGS"] = z["SEPSIS"] * x["HCC188"] | ||
| x["ART_OPENINGS_PRESSURE_ULCER_V24"] = x["HCC188"] * x["PRESSURE_ULCER"] | ||
| x["gCopdCF_ASP_SPEC_B_PNEUM"] = z["gCopdCF"] * x["HCC114"] | ||
| x["ASP_SPEC_B_PNEUM_PRES_ULC_V24"] = x["HCC114"] * x["PRESSURE_ULCER"] | ||
| x["SEPSIS_ASP_SPEC_BACT_PNEUM"] = z["SEPSIS"] * x["HCC114"] | ||
| x["SCHIZOPHRENIA_gCopdCF"] = x["HCC57"] * z["gCopdCF"] | ||
| x["SCHIZOPHRENIA_CHF"] = x["HCC57"] * z["CHF"] | ||
| x["SCHIZOPHRENIA_SEIZURES"] = x["HCC57"] * x["HCC79"] | ||
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| x["NONAGED_HCC85"] = DISABL * x["HCC85"] | ||
| x["NONAGED_PRESSURE_ULCER_V24"] = DISABL * x["PRESSURE_ULCER"] | ||
| x["NONAGED_HCC161"] = DISABL * x["HCC161"] | ||
| x["NONAGED_HCC39"] = DISABL * x["HCC39"] | ||
| x["NONAGED_HCC77"] = DISABL * x["HCC77"] | ||
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| cc_lst = [k for k, v in x.items() if v > 0] | ||
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| return cc_lst |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,169 @@ | ||
| def get_risk_dct(coefn, hcc_lst, age, sex, elig, origds, origesrd, full_partial_nondual, disabled, lti, graft_duration): | ||
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| risk_dct = {} | ||
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| # build demographic bracket strings and add to risk_dct | ||
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| if elig in {"DI", "GI",}: | ||
| elig_sex = elig + "_" + sex | ||
| elif elig in {'GF','GNP'}: | ||
| # broken out by aged and non aged | ||
| aged = 'N' if disabled else 'A' | ||
| elig += aged | ||
| elig_sex = elig + "_" + sex | ||
| elif elig in {'DNE', 'GNE'}: | ||
| # new enrolle | ||
| elig_sex = "NE" + sex | ||
| elif elig in {"TRANSPLANT_KIDNEY_ONLY_1M", | ||
| "TRANSPLANT_KIDNEY_ONLY_2M", | ||
| "TRANSPLANT_KIDNEY_ONLY_3M"}: | ||
| elig_sex = elig | ||
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| # build age bracket strings and add to risk_dct | ||
| # ESRD new enrolee age variables do not follow samme structure | ||
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| if elig == 'GNE' and 65 <= age <= 69: | ||
| age_match = elig_sex + str(age) | ||
| elif elig in {"TRANSPLANT_KIDNEY_ONLY_1M", | ||
| "TRANSPLANT_KIDNEY_ONLY_2M", | ||
| "TRANSPLANT_KIDNEY_ONLY_3M"}: | ||
| age_match = elig_sex | ||
| else: | ||
| age_ranges = [x for x in coefn.keys() if elig_sex in x and elig in x and '_' in x[-5:]] | ||
| if not age_ranges: | ||
| print('\t',elig) | ||
| print('\t',disabled) | ||
| print('\t',elig_sex) | ||
| print('\t',age_ranges) | ||
| age_match = "" | ||
| for age_range in age_ranges: | ||
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| age_tokens = age_range[-5:].replace(sex, "").split("_") | ||
| lb, ub = 0, 999 | ||
| if len(age_tokens) == 1: | ||
| lb = int(age_tokens[0]) | ||
| ub = lb + 1 | ||
| elif age_tokens[1] == "GT": | ||
| lb = int(age_tokens[0]) | ||
| else: | ||
| lb = int(age_tokens[0]) | ||
| ub = int(age_tokens[1]) + 1 | ||
| if lb <= age < ub: | ||
| if elig in {'DNE', 'GNE'}: | ||
| age_match = elig_sex + age_range.split(elig_sex)[1] | ||
| else: | ||
| age_match = age_range | ||
| break | ||
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| # Dual status interactions with Age and Sex used in dialysis CE model; | ||
| elig_fbpb = '' | ||
| if elig == "DI" and full_partial_nondual != 'N': | ||
| if full_partial_nondual == 'F': | ||
| elig_fbpb = elig + '_FBDual' | ||
| else: | ||
| elig_fbpb = elig + '_PBDual' | ||
| if sex == 'M': | ||
| elig_fbpb += '_Male' | ||
| else: | ||
| elig_fbpb += '_Female' | ||
| if disabled: | ||
| elig_fbpb += '_NonAged' | ||
| else: | ||
| elig_fbpb += '_Aged' | ||
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| # Originally Disabled Interactions with Sex used in dialysis CE model and functioning graft community aged models; | ||
| elig_origds = '' | ||
| if origds > 0: | ||
| elig_origds = elig + "_OriginallyDisabled_" | ||
| if sex == "M": | ||
| elig_origds += "Male" | ||
| else: | ||
| elig_origds += "Female" | ||
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| # Originally ESRD interactions with Sex used in dialysis CE model; | ||
| elig_origesrd = '' | ||
| if elig == 'DI' and origesrd > 0: | ||
| elig_origesrd = elig + "_Originally_ESRD_" | ||
| if sex == "M": | ||
| elig_origesrd += "Male" | ||
| else: | ||
| elig_origesrd += "Female" | ||
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| # LTI interactions with Aged used in dialysis CE model; | ||
| elig_ltia = '' | ||
| if elig == "DI" and lti > 0: | ||
| elig_ltia = elig + '_LTI_' | ||
| if disabled: | ||
| elig_ltia += 'NonAged' | ||
| else: | ||
| elig_ltia += 'Aged' | ||
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| # dualstatus (ND_PBD / FBD), origds (NORIGDIS / ORIGDIS), modelcode ('', G), sex_age_band (== age_match) | ||
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| base_demo_variable = '' | ||
| if elig in {'DNE', 'GNE'}: | ||
| base_demo_variable = '_'.join([ | ||
| elig, | ||
| 'FBD' if full_partial_nondual == 'F' else 'ND_PBD', | ||
| 'ORIGDIS' if origds > 0 else 'NORIGDIS', | ||
| age_match if elig == 'DNE' else 'G_' + age_match | ||
| ]) | ||
| else: | ||
| base_demo_variable = age_match | ||
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| fgf_variable = '' # functioning graft factor transplant bump-up factors | ||
| pbd_factor_variable = '' # partial benefit dual status bump up factors | ||
| actadj_variable = '' | ||
| if 'G' in elig: | ||
| if graft_duration: | ||
| fgf_variable = '_'.join([ | ||
| 'FGI' if lti > 0 else 'FGC', | ||
| 'LT65' if disabled > 0 else 'GE65', | ||
| graft_duration, | ||
| 'FBD' if full_partial_nondual == 'F' else 'ND_PBD', | ||
| ]) | ||
| if full_partial_nondual == 'P' and not 'NE' in elig: | ||
| pbd_factor_variable = '_'.join([ | ||
| 'FGI' if lti > 0 else 'FGC', | ||
| 'PBD', | ||
| 'LT65' if disabled > 0 else 'GE65', | ||
| 'flag' | ||
| ]) | ||
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| # Actuarial adjustment factor for new enrollees functioning graft model transplant bumps | ||
| if elig == 'GNE' and graft_duration: | ||
| actadj_variable = 'ActAdj_' | ||
| actadj_variable += graft_duration | ||
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| actadj_factor = coefn.get(actadj_variable, 1.0) | ||
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| if base_demo_variable: | ||
| risk_dct[base_demo_variable] = coefn.get(base_demo_variable, 0.0) | ||
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| if elig_fbpb: | ||
| risk_dct[elig_fbpb] = coefn.get(elig_fbpb, 0.0) | ||
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| if elig_origds: | ||
| risk_dct[elig_origds] = coefn.get(elig_origds, 0.0) | ||
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| if elig_origds: | ||
| risk_dct[elig_origds] = coefn.get(elig_origds, 0.0) | ||
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| if elig_ltia: | ||
| risk_dct[elig_ltia] = coefn.get(elig_ltia, 0.0) | ||
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| if fgf_variable: | ||
| risk_dct[fgf_variable] = coefn.get(fgf_variable, 0.0) | ||
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| if pbd_factor_variable: | ||
| risk_dct[pbd_factor_variable] = coefn.get(pbd_factor_variable, 0.0) | ||
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| # # build hcc factor strings and add to risk_dict | ||
| for hcc in hcc_lst: | ||
| elig_hcc = elig + '_' + hcc | ||
| risk_dct[elig_hcc] = coefn.get(elig_hcc, 0.0) | ||
|
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| return risk_dct, actadj_factor |
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