A validation of clinical data captured from a novel Cancer Care Quality Program directly integrated with administrative claims data

Background/aims Health plan administrative claims data present a cost-effective complement to traditional trial-specific ascertainment of clinical events typically conducted through patient report or a single health system electronic health record. We aim to demonstrate the value of health plan claims data in improving the capture of endpoints in longitudinal pragmatic clinical trials. Methods This retrospective cohort study paralleled the design of the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) trial designed to compare the effectiveness of two doses of aspirin. We applied the ADAPTABLE identification query in claims data from Anthem, an American health insurance company, and identified health plan members who met the ADAPTABLE trial criteria. Among the ADAPTABLE eligible members, we selected overlapping members with PCORnet Clinical Data Research Networks in the 2 years prior to the index date (1 April 2014). PCORnet Clinical Data Research Networks consist of network partners (or healthcare systems) that store their electronic health record data in the same format to support multi-institutional research. ADAPTABLE outcome events—cardiovascular hospitalizations including admissions for myocardial infarction, stroke, or cardiac procedures; hospitalizations for major bleeding; and in-hospital deaths—were evaluated for a 2-year follow-up period. Events were classified as within or outside PCORnet Clinical Data Research Networks using facility identifiers affiliated with each hospital stay. Patient characteristics were examined with descriptive statistics, and incidence rates were reported for available Clinical Data Research Networks and claims data. Results Among 884,311 ADAPTABLE eligible health plan members, 11,101 patients overlapped with PCORnet Clinical Data Research Networks. Average age was 70 years, 71% were male, and average follow-up was 20.7 months. Patients had 1521 cardiovascular hospitalizations (571 (37.5%) occurred outside PCORnet Clinical Data Research Networks), 710 for major bleeding (296 (41.7%) outside PCORnet Clinical Data Research Networks), and 196 in-hospital deaths (67 (34.2%) outside PCORnet Clinical Data Research Networks). Incidence rates (events per1000 patient-months) differed between available network partners and claims data: cardiovascular hospitalizations, 4.1 (95% confidence interval: 3.9, 4.4) versus 6.6 (95% confidence interval: 6.3, 7.0), major bleeding, 1.8 (95% confidence interval: 1.6, 2.0) versus 3.1 (95% confidence interval: 2.9, 3.3), and in-hospital death, 0.56 (95% confidence interval: 0.47, 0.67) versus 0.85 (95% confidence interval: 0.74, 0.98), respectively. Conclusion This study demonstrated the value of supplementing longitudinal site-based clinical studies with administrative claims data. Our results suggest that claims data together with network partner electronic health record data constitute an effective vehicle to capture patient outcomes since >30% of patients have non-fatal and fatal events outside of enrolling sites.

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Effect of reminder letters after health checkups on the consultation behavior of participants with possible hypertension, hyperglycemia, and dyslipidemia: A retrospective cohort study using administrative claims data in Japan

Journal of Occupational Health ◽

10.1002/1348-9585.12231 ◽

2021 ◽

Vol 63 (1) ◽

Author(s):

Nobuaki Hoshino ◽

Mo Xiuting ◽

Yoshimitsu Takahashi ◽

Takeo Nakayama

Keyword(s):

Cohort Study ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Claims Data ◽

Administrative Claims ◽

Administrative Claims Data ◽

Reminder Letters

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Characterization of bariatric surgery and outcomes using administrative claims data in the research network of a nationwide commercial health plan

BMC Health Services Research ◽

10.1186/s12913-021-06074-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Qinli Ma ◽

Michael Mack ◽

Sonali Shambhu ◽

Kathleen McTigue ◽

Kevin Haynes

Keyword(s):

Bariatric Surgery ◽

Health Systems ◽

Comparative Effectiveness ◽

Claims Data ◽

Research Network ◽

Hospital Death ◽

Administrative Claims ◽

Administrative Claims Data ◽

Abdominal Operations

Abstract Background The supplementation of electronic health records data with administrative claims data may be used to capture outcome events more comprehensively in longitudinal observational studies. This study investigated the utility of administrative claims data to identify outcomes across health systems using a comparative effectiveness study of different types of bariatric surgery as a model. Methods This observational cohort study identified patients who had bariatric surgery between 2007 and 2015 within the HealthCore Anthem Research Network (HCARN) database in the National Patient-Centered Clinical Research Network (PCORnet) common data model. Patients whose procedures were performed in a member facility affiliated with PCORnet Clinical Research Networks (CRNs) were selected. The outcomes included a 30-day composite adverse event (including venous thromboembolism, percutaneous/operative intervention, failure to discharge and death), and all-cause hospitalization, abdominal operation or intervention, and in-hospital death up to 5 years after the procedure. Outcomes were classified as occurring within or outside PCORnet CRN health systems using facility identifiers. Results We identified 4899 patients who had bariatric surgery in one of the PCORnet CRN health systems. For 30-day composite adverse event, the inclusion of HCARN multi-site claims data marginally increased the incidence rate based only on HCARN single-site claims data for PCORnet CRNs from 3.9 to 4.2%. During the 5-year follow-up period, 56.8% of all-cause hospitalizations, 31.2% abdominal operations or interventions, and 32.3% of in-hospital deaths occurred outside PCORnet CRNs. Incidence rates (events per 100 patient-years) were significantly lower when based on claims from a single PCORnet CRN only compared to using claims from all health systems in the HCARN: all-cause hospitalization, 11.0 (95% Confidence Internal [CI]: 10.4, 11.6) to 25.3 (95% CI: 24.4, 26.3); abdominal operations or interventions, 4.2 (95% CI: 3.9, 4.6) to 6.1 (95% CI: 5.7, 6.6); in-hospital death, 0.2 (95% CI: 0.11, 0.27) to 0.3 (95% CI: 0.19, 0.38). Conclusions Short-term inclusion of multi-site claims data only marginally increased the incidence rate computed from single-site claims data alone. Longer-term follow up captured a notable number of events outside of PCORnet CRNs. The findings suggest that supplementing claims data improves the outcome ascertainment in longitudinal observational comparative effectiveness studies.

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Attribution of Adverse Events Following Coronary Stent Placement Identified Using Administrative Claims Data

Journal of the American Heart Association ◽

10.1161/jaha.119.013606 ◽

2020 ◽

Vol 9 (4) ◽

Author(s):

Sanket S. Dhruva ◽

Craig S. Parzynski ◽

Ginger M. Gamble ◽

Jeptha P. Curtis ◽

Nihar R. Desai ◽

...

Keyword(s):

Adverse Events ◽

Stent Placement ◽

Claims Data ◽

Coronary Stent ◽

Administrative Claims ◽

Administrative Claims Data

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Validation of diabetes case definitions using administrative claims data

Diabetic Medicine ◽

10.1111/j.1464-5491.2011.03238.x ◽

2011 ◽

Vol 28 (4) ◽

pp. 424-427 ◽

Cited By ~ 24

Author(s):

S. Amed ◽

S. E. Vanderloo ◽

D. Metzger ◽

J.-P. Collet ◽

K. Reimer ◽

...

Keyword(s):

Claims Data ◽

Administrative Claims ◽

Case Definitions ◽

Administrative Claims Data ◽

Diabetes Case

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PDB35 Trajectory of Glycated Hemoglobin Over Time Among Obese Type 2 Diabetes Patients Prescribed U-100 Basal-only Insulin Regimens: A US Administrative Claims Data Analysis

Value in Health ◽

10.1016/j.jval.2021.04.432 ◽

2021 ◽

Vol 24 ◽

pp. S84

Author(s):

K. Maughn ◽

J. Chen ◽

D.R. Nelson ◽

L. Fan ◽

Y. Liu ◽

...

Keyword(s):

Type 2 Diabetes ◽

Data Analysis ◽

Claims Data ◽

Glycated Hemoglobin ◽

Administrative Claims ◽

Administrative Claims Data ◽

Claims Data Analysis ◽

Over Time ◽

Diabetes Patients

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Abstract 173: A Comparison of Administrative Claims Discharge Diagnosis with Electronic Medical Record Problem List in the Diagnosis of Acute Myocardial Infarction

Circulation Cardiovascular Quality and Outcomes ◽

10.1161/circoutcomes.7.suppl_1.173 ◽

2014 ◽

Vol 7 (suppl_1) ◽

Author(s):

Michael D McCulloch ◽

Tim Sobol ◽

Joy Yuhas ◽

Bill Ahern ◽

Eric D Hixson ◽

...

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Medical Record ◽

Chart Review ◽

Claims Data ◽

Administrative Claims ◽

Problem List ◽

Principal Diagnosis ◽

Administrative Claims Data ◽

Patient Admissions

Background: Administrative claims data are commonly used for measurement of mortality and readmissions in Acute Myocardial Infarction (AMI). With advent of the Electronic Medical Record (EMR), the electronic problem list offers new ways to capture diagnosis data. However, no data comparing the accuracy of administrative claims data and the EMR problem list exists. Methods: Two years of admissions at a single, quaternary medical center were analyzed to compare the presence of AMI diagnosis in administrative claims and EMR problem list data using a 2x2 matrix. To gain insights into this novel method, 25 patient admissions were randomly selected from each group to undergo physician chart review to adjudicate a clinical diagnosis of myocardial infarction based on the universal definition. Results: A total of 105,929 admissions from January 1, 2010 to December 31, 2011 were included. Where EMR problem list and administrative claims data were in agreement for or against AMI diagnosis they were highly accurate. Where administrative claims data, but not EMR problem list, reported AMI the most common explanation was true AMI with missing EMR problem list diagnoses (60%). Less common reasons for discordance in this category include: (1) administrative coding error (20%), (2) computer algorithm error (8%), (3) patient death before EMR problem list created (4%), (4) EMR problem list not used (4%) and (5) AMI diagnosis was removed from EMR problem list (4%). Where EMR problem list, but not administrative claims data, reported AMI the most common explanation was no AMI with historical diagnosis of AMI from a previous admission (60%). Less common reasons for discordance in this category include: (1) AMI present but not the principal diagnosis (32%), (2) administrative coding error (4%) and (3) erroneous EMR problem list entry (4%). Conclusion: Compared to administrative and chart review diagnoses, we found that using the EMR problem list to identify patient admissions with a principal diagnosis of AMI will overlook a subset of patients primarily due to inadequate clinical documentation. Additionally, the EMR problem list does not discriminate the admission principal diagnosis from the secondary diagnoses.

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