Testing of Coding Algorithms for Inflammatory Bowel Disease Identification, as Indication for Use of Biological Drugs, Using a Claims Database from Southern Italy

Figures & data

Table 1 Coding Algorithms Developed to Identify Patients with CD or UC from the Claims Database of Caserta LHU During the Years 2015–2018

Algorithms	Crohn’s Disease	Comment of the Local Expert
1	ICD-9-CM: 555x (primary) OR Exemptions from healthcare service co-payment: 009.555 OR 555	CD algorithm was adapted from the study conducted by Di Domenicantonio et al;^Citation20 indeed, in that study, ICD9-CM diagnosis code of 555.xx as the primary or secondary diagnosis or the activation of co-payment exemption for CD (code 009.555) was used as a case definition criteria. In our algorithm, we decided to consider only ICD9-CM diagnosis code of 555.xx as primary cause of hospitalization to be sure that the hospital admission was related to CD
2	ICD-9-CM: 555x (primary) OR Exemptions from healthcare service co-payment: 009.555 OR 555 OR ((Exemptions from healthcare service co-payment: 009) AND (Methotrexate: 039153x, 044252x, 044253x, 043416x, 044257x, 044149x, 044224x))	CD algorithm was performed from “Algorithm 1”, adding methotrexate dispensing (considering only NDC codes approved for the treatment of CD and other IMIDs in Italy).^Citation41 The combination of both methotrexate dispensing AND the exemption from healthcare service co-payment code, identifying unspecified IBD (009), could ensure the identification of CD (rather than other IMIDs)
3	ICD-9-CM: 555x (primary) OR Exemptions from healthcare service co-payment: 009.555 OR 555 OR ((Exemptions from healthcare service co-payment: 009) AND (Methotrexate: 039153x, 044252x, 044253x, 043416x, 044257x, 044149x, 044224x)) OR Budesonide: 034734x, 036507022, 036507034, 036507059, 036507046, 036507010, 044798x	CD algorithm was performed from “Algorithm 2”, adding budesonide dispensing (considering only NDC codes with the only approval for the treatment of CD in Italy).^Citation42 We decided to consider CD-related ICD-9-CM codes OR exemptions from co-payment codes OR non-biological drugs with indication for CD in order to explore all the conditions to identify CD patients from claims databases
4	Exemptions from healthcare service co-payment: 009.555 OR 555 OR ((Exemptions from healthcare service co-payment: 009) AND (Methotrexate: 039153x, 044252x, 044253x, 043416x, 044257x, 044149x, 044224x)) OR (Budesonide: 034734x, 036507022, 036507034, 036507059, 036507046, 036507010, 044798x)	CD algorithm was performed from “Algorithm 3”, excluding CD-related ICD-9-CM codes to explore whether these codes have (or not) an impact for the identification of CD
5	ICD-9-CM: 555x (primary) OR Budesonide: 034734x, 036507022, 036507034, 036507059, 036507046, 036507010, 044798x	CD algorithm was performed from “Algorithm 4”, replacing exemptions from healthcare service co-payment codes and methotrexate dispensing with CD-related ICD-9-CM codes to explore how the performance of the algorithm changed
Algorithms	Ulcerative colitis
1	ICD-9-CM: 556x (primary) OR Exemptions from healthcare service co-payment: 009.556 OR 556	UC algorithm was adapted from the study conducted by Di Domenicantonio et al;^Citation20 indeed, in that study, ICD9-CM diagnosis code of 556.xx (excluding 556.0, 556.1, 556.4, 556.8) as the primary or secondary diagnosis or the activation of co-payment exemption for UC (code 009.556) was used as a case definition criteria. In our algorithm, we decided to consider only ICD9-CM diagnosis code of 556.xx as primary cause of hospitalization to be sure that the hospital admission was related to UC
2	ICD-9-CM: 556x (primary) OR Exemptions from healthcare service co-payment: 009.556 OR 556 OR ((Exemptions from healthcare service co-payment: 009) AND (Golimumab 039541x [excl. 039541091]))	UC algorithm was performed from “Algorithm 1”, adding Golimumab dispensing (considering only NDC codes approved for the treatment of UC and other IMIDs in Italy^Citation43). The combination of both Golimumab dispensing AND the exemption from healthcare service co-payment code, identifying unspecified IBD (009), could ensure the identification of UC (rather than other IMIDs)
3	ICD-9-CM: 556x (primary) OR Exemptions from healthcare service co-payment: 009.556 OR 556 OR ((Exemptions from healthcare service co-payment: 009) AND (Golimumab 039541x [excl. 039541091])) OR (Mesalazine specific AIC (see Supplement Table 2) OR (Balsalazide 033858x) OR (Budesonide: 043461x, 036507061, 036507085, 036507073)	UC algorithm was performed from “Algorithm 2”, adding mesalazine/balsalazide/budesonide dispensing (considering only NDC codes with the only approval for the treatment of CD in Italy).^Citation42,Citation44,Citation45 We decided to consider UC-related ICD-9-CM codes OR exemptions from co-payment codes OR non-biological drugs with indication for CD in order to explore all the conditions to identify UC patients from claims databases
4	Exemptions from healthcare service co-payment: 009.556 OR 556 OR ((Exemptions from healthcare service co-payment: 009) AND (Golimumab 039541x [excl. 039541091])) OR Mesalazine: specific AIC (see Supplement Table 2) OR Balsalazide: 033858x OR Budesonide: 043461x, 036507061, 036507085, 036507073	UC algorithm was performed from “Algorithm 3”, excluding UC-related ICD-9-CM codes to explore whether these codes have (or not) an impact for the identification of UC
5	ICD-9-CM: 556x (primary) OR Mesalazine: specific AIC (see Supplement Table 2) OR Balsalazide: 033858x OR (Budesonide: 043461x, 036507061, 036507085, 036507073)	UC algorithm was performed from “Algorithm 4”, replacing exemptions from healthcare service co-payment codes and golimumab dispensing with UC-related ICD-9-CM codes to explore how the performance of the algorithm changed

Abbreviations: NDC, National drug code; IMID, immune-mediated inflammatory disease.

Figure 1 Flow-chart of patients identified in the gold standard cohort from Caserta LHU database in the period 2015–2018. *Unspecified diagnosis=IBD as indication for use, not specified if CD or UC.

Abbreviations: LHU, Local Health Unit; IBDs, inflammatory bowel diseases; ETP, electronic therapeutic plan; CD, Crohn’s disease; UC, ulcerative colitis.

Table 2 Baseline Characteristics of IBD Biological Drugs Users, Stratified by Indication for Use, as Reported in the First Electronic Therapeutic Plan

	Crohn’s Disease N=83	Ulcerative Colitis N=51	Other Indications for Use N=489	Crohn’s Disease vs Other Indications for Use (Effect Size^#)	Ulcerative Colitis vs other Indications for Use (Effect Size^#)
Sex – N (%)
Male	47 (56.6)	28 (54.9)	231 (47.2)	(0.066)	(0.045)
Female	36 (43.4)	23 (45.1)	258 (52.8)
Age (years) – mean± SD	36.4 (15.4)	43.6 (15.8)	49.5 (14.7)	(0.887)	(0.394)
Age categories – N (%)
<45	61 (73.5)	25 (49.0)	158 (32.3)	(0.301)	(0.107)
45–64	19 (22.9)	21 (41.2)	253 (51.7)
65–79	3 (3.6)	5 (9.8)	72 (14.7)
≥80	0 (0)	0 (0)	6 (1.3)
Follow-up period (months) – median (Q1–Q3)	24.6 (11.6–27.1)	22.9 (9.7–26.5)	25.3 (20.2–27.0)	(0.060)	(0.128)
Index drug – N (%)
Adalimumab	56 (67.5)	14 (27.4)	343 (70.1)	(0.021)	(0.264)
Golimumab	0 (0)	12 (23.5)	85 (17.4)	(0.172)	(0.047)
Infliximab	20 (24.1)	16 (31.4)	32 (6.5)	(0.215)	(0.255)
Vedolizumab	6 (7.2)	9 (17.6)	0 (0)	(0.250)	(0.403)
Ustekinumab	1 (1.2)	0 (0)	0 (0)	(0.102)	(0)
Other	0 (0)	0 (0)	29 (5.9)	(0.095)	(0.077)
Comorbidities – N (%)^a
Hypertension	9 (10.8)	9 (17.6)	89 (18.2)	(0.069)	(0.004)
Diabetes mellitus	3 (3.6)	4 (7.8)	64 (13.1)	(0.104)	(0.046)
Respiratory disease	52 (62.6)	37 (72.5)	327 (66.9)	(0.031)	(0.035)
Renal failure	0 (0)	0 (0)	1 (0.2)	(0.017)	(0.014)
Neoplasms	27 (32.5)	16 (31.4)	109 (22.3)	(0.085)	(0.063)
Cerebrovascular disease	2 (2.4)	0 (0)	24 (4.9)	(0.042)	(0.070)
Other autoimmune diseases
Spondyloarthritis	3 (3.6)	0 (0)	82 (16.8)	(0.130)	(0.137)
Psoriasis	5 (6.0)	5 (9.8)	217 (44.4)	(0.277)	(0.206)
Psoriatic arthritis	2 (2.4)	1 (1.9)	152 (31.1)	(0.228)	(0.189)
Rheumatoid arthritis	2 (2.4)	2 (3.9)	193 (39.5)	(0.275)	(0.216)
Previous use of conventional drugs – N (%)^a
Aminosalicylic acid and similar agents	80 (96.4)	51 (100.00)	150 (30.7)	(0.472)	(0.419)
Immunosuppressants	50 (60.2)	30 (58.8)	366 (74.8)	(0.116)	(0.106)
Glucocorticoids	64 (77.1)	50 (98.0)	348 (71.2)	(0.047)	(0.179)
Corticosteroids acting locally	56 (67.4)	47 (92.1)	36 (7.4)	(0.576)	(0.688)
Concomitant drugs – N (%)^b
Antithrombotic agents	11 (13.2)	3 (5.8)	78 (15.9)	(0.026)	(0.083)
Platelet aggregation inhibitors excl. heparin	3 (3.6)	2 (3.9)	57 (11.6)	(0.092)	(0.073)
Antiarrhythmics	4 (4.8)	5 (9.8)	112 (22.9)	(0.158)	(0.093)
Antibacterials for systemic use	65 (78.3)	37 (72.5)	335 (68.5)	(0.075)	(0.026)
Drugs for peptic ulcer and gastro-esophageal reflux disease (GORD)	34 (40.9)	35 (68.6)	294 (60.1)	(0.136)	(0.051)
Antivirals for systemic use	0 (0)	2 (3.9)	16 (3.3)	(0.070)	(0.011)
NSAIDs	5 (6.0)	11 (21.6)	269 (55.0)	(0.345)	(0.196)
Statins	3 (3.6)	3 (5.9)	71 (14.5)	(0.114)	(0.074)

Notes: ^aEvaluated any time prior to index date (ID), defined as the first date of the biologic dispensing. ^bEvaluated within one year prior to ID. ^#Effect sizes are reported as Cramér’s V for categorical variables and standardized mean difference or “standardized Z-score” from the Mann–Whitney U-test for continuous variables as appropriate. SD, standard deviation; Q1–Q3: first–third quartiles; Antithrombotic agents: vitamin K antagonists, heparin group, direct thrombin inhibitors, direct factor Xa inhibitors, other antithrombotic agents; Aminosalicylic acid and similar agents: sulfasalazine, mesalazine, olsalazine, balsalazide; Corticosteroids acting locally: budesonide; Glucocorticoids: prednisone, hydrocortisone, methylprednisolone; Immunosuppressants: azathioprine, mercaptopurine, methotrexate, cyclosporine.

Table 3 Diagnostic Accuracy of the Coding Algorithms Developed to Identify Patients with Crohn’s Disease in the Cohort of Biological Drug Users from Caserta LHU in the Years 2015–2018

Algorithms	Sensitivity (95% CI)	Specificity (95% CI)	Positive Predictive Value (95% CI)	Negative Predictive Value (95% CI)	F-score	Youden Index	N of Identified CD Cases/Users of Biological Drugs Approved for IBDs (%)
1	91.6 (83.4–96.5)	98.1(96.6–99.1)	88.4(80.4–93.4)	98.7(97.4–99.4)	0.89	0.897	116/1205 (9.6)
2	91.6(83.4–96.5)	97.8(96.1–98.8)	86.4(78.3–91.7)	98.7(97.4–99.3)	0.87	0.894	119/1205 (9.9)
3	98.8(93.5–100.0)	97.2(95.5–98.4)	84.5(76.8–90.1)	99.8(98.7–100.0)	0.87	0.960	132/1205 (10.9)
4	71.1(60.1–80.5)	97.9(96.4–98.9)	84.3(74.6–90.7)	95.7(94.0–96.9)	0.81	0.690	96/1205 (7.9)
5	96.4(89.8–99.2)	97.8(96.1–98.8)	86.9(79.2–92.1)	99.4(98.3–99.8)	0.88	0.942	127/1205 (10.5)

Abbreviations: CD, Crohn’s disease; CI, confidence interval; ETP, electronic therapeutic plan; IBDs, inflammatory bowel diseases.

Table 4 Diagnostic Accuracy of the Coding Algorithms Developed to Identify Patients with Ulcerative Colitis in the Cohort of the Biological Drug Users from Caserta LHU in the Years 2015–2018

Algorithms	Sensitivity (95% CI)	Specificity (95% CI)	Positive Predictive Value (95% CI)	Negative Predictive Value (95% CI)	F-Score	Youden Index	N of Identified UC Cases/Users of Biological Drugs Approved for IBDs (%)
1	90.2(78.6–96.7)	92.1(89.6–94.2)	50.5(43.2–57.8)	99.1(97.9–99.6)	0.55	0.823	133/1205 (11.0)
2	92.2(81.1–97.8)	91.8(89.2–93.9)	50.0(42.9–57.1)	99.2(98.1–99.7)	0.55	0.840	135/1205 (11.2)
3	94.1(83.8–98.8)	91.6(89.1–93.7)	50.0(43.1–56.9)	99.4(98.3–99.8)	0.55	0.857	138/1205 (11.4)
4	64.7(50.1–77.6)	93.9(91.6–95.7)	48.5(39.2–58.0)	96.8(95.4–97.8)	0.51	0.586	89/1205 (7.4)
5	74.5(60.4–85.7)	96.3(94.4–97.7)	64.4(53.6–73.9)	97.7(96.4–98.5)	0.66	0.708	98/1205 (8.1)

Abbreviations: CI, confidence interval; ETP, electronic therapeutic plan; IBDs, inflammatory bowel diseases; UC, ulcerative colitis.

Figure 2 Frequency distribution (Venn diagrams) of the number of biological drug users identified by the coding algorithms developed for Crohn’s disease (a) and ulcerative colitis (b) identification.

Notes: The dark green sets showed the true positive cases for Crohn’s disease (a) and ulcerative colitis (b), identified through electronic therapeutic plans. The other sets showed the Crohn’s disease (a) and ulcerative colitis (b) positive cases identified by the 5 different tested algorithms. Full details about algorithms definition are reported in Table 1.

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