Dataset Information

Unexpected discrepancies in hospital administrative databases can impact the accuracy of monitoring thyroid surgery outcomes in France.

ABSTRACT:

Objective

To determine the validity of hospital administrative databases compared to prospective collection of medical data assessing thyroid surgery complications.

Background

Administrative data are increasingly used to track surgical outcomes.

Methods

All patients undergoing thyroid surgery at three French university hospitals between April 2008 and April 2009 were prospectively included. Using diagnosis and procedural codes from hospital administrative database, we designed three indicators for measuring complications of thyroid surgery: recurrent laryngeal nerve palsy, postoperative hypoparathyroidism, and postoperative hemorrhage. Gold standard was obtained from a prospective collection of medical data after systematically screening each patient for the above-mentioned complications. Their ability to monitor surgical outcomes over time within individual hospitals was estimated using control charts. Spatial comparison between hospitals was performed by funnel plots.

Results

A total of 1909 patients were included. Complication rates extracted from administrative data were significantly lower compared to medical data (nerve palsy 2.4% vs. 6.7%, hypoparathyroidism 10.6% vs. 22.3%, p<0.0001). Indicator sensitivity was 30.4% for nerve palsy, 45.4% for hypoparathyroidism and 71.4% for postoperative hemorrhage. Corresponding positive predictive values were 84.4%, 95.1% and 68.2%. In two of the three hospitals, administrative data were not able to track temporal variations in complications rates. Regarding inter-hospital comparisons, 2 out of 3 hospitals were considered outliers according to administrative data despite having an average performance based on medical data.

Conclusions

The ability of indicators extracted from administrative databases to measure thyroid surgery outcomes depends on the quality of underlying data coding. Validation in every center should be a prerequisite before implementing such metrics for tracking performance.

SUBMITTER: Mercier F

PROVIDER: S-EPMC6283582 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Unexpected discrepancies in hospital administrative databases can impact the accuracy of monitoring thyroid surgery outcomes in France.

Mercier Frederic F Laplace Nathalie N Mitmaker Elliot J EJ Colin Cyrille C Kraimps Jean-Louis JL Sebag Frederic F Bourdy Stephanie S Duclos Antoine A Lifante Jean-Christophe JC

PloS one 20181206 12

<h4>Objective</h4>To determine the validity of hospital administrative databases compared to prospective collection of medical data assessing thyroid surgery complications.<h4>Background</h4>Administrative data are increasingly used to track surgical outcomes.<h4>Methods</h4>All patients undergoing thyroid surgery at three French university hospitals between April 2008 and April 2009 were prospectively included. Using diagnosis and procedural codes from hospital administrative database, we desig ...[more]

PMID: 30521574

Similar Datasets

Project description:ContextMany of the publicly available health quality report cards are based on administrative data. ICD-9-CM codes in administrative data are not date stamped to distinguish between medical conditions present at the time of hospital admission and complications, which occur after hospital admission. Treating complications as preexisting conditions gives poor-performing hospitals "credit" for their complications and may cause some hospitals that are delivering low-quality care to be misclassified as average- or high-performing hospitals.ObjectiveTo determine whether hospital quality assessment based on administrative data is impacted by the inclusion of condition present at admission (CPAA) modifiers in administrative data as a date stamp indicator.Design, setting, and patientsRetrospective cohort study based on 648,866 inpatient admissions between 1998 and 2000 for coronary artery bypass graft (CABG) surgery, coronary angioplasty (PTCA), carotid endarterectomy (CEA), abdominal aortic aneurysm (AAA) repair, total hip replacement (THR), acute MI (AMI), and stroke using the California State Inpatient Database which includes CPAA modifiers. Hierarchical logistic regression was used to create separate condition-specific risk adjustment models. For each study population, one model was constructed using only secondary diagnoses present at admission based on the CPAA modifier: "date stamp" model. The second model was constructed using all secondary diagnoses, ignoring the information present in the CPAA modifier: the "no date stamp model." Hospital quality was assessed separately using the "date stamp" and the "no date stamp" risk-adjustment models.ResultsForty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 40 percent of the THR hospitals, and 33 percent of the AMI hospitals identified as low-performance hospitals by the "date stamp" models were not classified as low-performance hospitals by the "no date stamp" models. Fifty percent of the CABG hospitals, 33 percent of the PTCA hospitals, 50 percent of the CEA hospitals, and 36 percent of the AMI hospitals identified as low-performance hospitals by the "no date stamp" models were not identified as low-performance hospitals by the "date stamp" models. The inclusion of the CPAA modifier had a minor impact on hospital quality assessment for AAA repair, stroke, and CEA.ConclusionThis study supports the hypothesis that the use of routine administrative data without date stamp information to construct hospital quality report cards may result in the mis-identification of hospital quality outliers. However, the CPAA modifier will need to be further validated before date stamped administrative data can be used as the basis for health quality report cards.

Project description:Diagnostic data routinely collected for hospital admitted patients and used for case-mix adjustment in care provider comparisons and reimbursement are prone to biases. We aim to measure discrepancies, variations and associated factors in recorded chronic morbidities for hospital admitted patients in New South Wales (NSW), Australia. Of all admissions between July 2010 and June 2014 in all NSW public and private acute hospitals, admissions with over 24 hours stay and one or more of the chronic conditions of diabetes, smoking, hepatitis, HIV, and hypertension were included. The incidence of a non-recorded chronic condition in an admission occurring after the first admission with a recorded chronic condition (index admission) was considered as a discrepancy. Poisson models were employed to (i) derive adjusted discrepancy incidence rates (IR) and rate ratios (IRR) accounting for patient, admission, comorbidity and hospital characteristics and (ii) quantify variation in rates among hospitals. The discrepancy incidence rate was highest for hypertension (51% of 262,664 admissions), followed by hepatitis (37% of 12,107), smoking (33% of 548,965), HIV (27% of 1500) and diabetes (19% of 228,687). Adjusted rates for all conditions declined over the four-year period; with the sharpest drop of over 80% for diabetes (47.7% in 2010 vs. 7.3% in 2014), and 20% to 55% for the other conditions. Discrepancies were more common in private hospitals and smaller public hospitals. Inter-hospital differences were responsible for 1% (HIV) to 9.4% (smoking) of variation in adjusted discrepancy incidences, with an increasing trend for diabetes and HIV. Chronic conditions are recorded inconsistently in hospital administrative datasets, and hospitals contribute to the discrepancies. Adjustment for patterns and stratification in risk adjustments; and furthermore longitudinal accumulation of clinical data at patient level, refinement of clinical coding systems and standardisation of comorbidity recording across hospitals would enhance accuracy of datasets and validity of case-mix adjustment.

Project description:BackgroundVenous thromboembolism (VTE) events are tracked in trauma registries and by administrative data sets. Both databases are used to assess outcomes, despite having varying processes for data capture.Study designThis study was performed at an urban, university-based, Level I trauma center from 2004 to 2014. Retrospective review of the trauma registry and the hospital's administrative database was performed querying for all VTEs. Each VTE was then validated through manual chart review. Confirmed events were those with radiographic evidence of VTE by ultrasound, CT, and/or ventilation-perfusion scan. Sensitivity, specificity, and predictive values were calculated and compared between databases.ResultsThere were 19,353 trauma patients admitted during the study period; 656 VTEs were identified in the registry and 890 were identified via administrative data; 527 potential events were identified by both databases; 129 events were only in registry; and 363 were only found in the administrative database. We confirmed 636 of 656 events in registry (positive predictive value, 97%; 95% CI, 95.6% to 98.3%) vs 815 of 890 events in administrative data (positive predictive value, 91.6%; 95% CI, 89.75% to 93.4%; p < 0.001). Sensitivity was higher for administrative (87.2% vs 68.0%; p < 0.001), as 299 confirmed VTE events were not in the registry. Differences between the 2 databases were diminished when the analysis excluded untreated events and those present on admission. Twenty-three percent of validated deep vein thrombosis events in the registry were upper extremity events.ConclusionsThe trauma registry showed higher specificity and lower sensitivity compared with administrative data. The low false-positive rate of the trauma registry supports its validity in VTE outcomes research. Additional investigation is needed to evaluate the relevance of the variable sensitivity, likely due to definitional differences. Supplementation of trauma registry data with administrative data can strengthen its completeness.

Project description:BACKGROUND:Claims databases are generally considered inadequate for obesity research due to suboptimal capture of body mass index (BMI) measurements. This might not be true for bariatric surgery because of reimbursement requirements and changes in coding systems. We assessed the availability and validity of claims-based weight-related diagnosis codes among bariatric surgery patients. METHODS:We identified three nested retrospective cohorts of adult bariatric surgery patients who underwent adjusted gastric banding, Roux-en-Y gastric bypass, or sleeve gastrectomy between January 1, 2011 and June 30, 2018 using different components of OptumLabs® Data Warehouse, which contains linked de-identified claims and electronic health records (EHRs). We measured the availability of claims-based weight-related diagnosis codes in the 6-month preoperative and 1-year postoperative periods in the main cohort identified in the claims data. We created two claims-based algorithms to classify the presence of severe obesity (a commonly used cohort selection criterion) and categorize BMI (a commonly used baseline confounder or postoperative outcome). We evaluated their performance by estimating sensitivity, specificity, positive predictive value, negative predictive value, and weighted kappa in two sub-cohorts using EHR-based BMI measurements as the reference. RESULTS:Among the 29,357 eligible patients identified using claims only, 28,828 (98.2%) had preoperative weight-related diagnosis codes, either granular indicating BMI ranges or nonspecific denoting obesity status. Among the 27,407 patients with granular preoperative codes, 12,346 (45.0%) had granular codes and 9355 (34.1%) had nonspecific codes in the 1-year postoperative period. Among the 3045 patients with both preoperative claims-based diagnosis codes and EHR-based BMI measurements, the severe obesity classification algorithm had a sensitivity 100%, specificity 71%, positive predictive value 100%, and negative predictive value 78%. The BMI categorization algorithm had good validity categorizing the last available preoperative or postoperative BMI measurements (weighted kappa [95% confidence interval]: preoperative 0.78, [0.76, 0.79]; postoperative 0.84, [0.80, 0.87]). CONCLUSIONS:Claims-based weight-related diagnosis codes had excellent validity before and after bariatric surgical operation but suboptimal availability after operation. Claims databases can be used for bariatric surgery studies of non-weight-related effectiveness and safety outcomes that are well-captured.

Dataset Information

Unexpected discrepancies in hospital administrative databases can impact the accuracy of monitoring thyroid surgery outcomes in France.

Objective

Background

Methods

Results

Conclusions

Publications

Unexpected discrepancies in hospital administrative databases can impact the accuracy of monitoring thyroid surgery outcomes in France.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets