Dataset Information

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample.

ABSTRACT: The growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data.In this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010.The two databases have a similar distribution pattern across all data elements, with 24 of 50 data elements being statistically similar between the two data sources. In general, differences that were found are consistent across diagnosis and procedures categories and were specific to the psychiatric-behavioral and obstetrics-gynecology services areas.Large EHR databases have the potential to be a useful addition to health services researchers, although they require different analytic techniques compared to administrative databases; more research is needed to understand the differences.

SUBMITTER: DeShazo JP

PROVIDER: S-EPMC4572624 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample.

DeShazo Jonathan P JP Hoffman Mark A MA

BMC health services research 20150915

<h4>Background</h4>The growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data.<h4>Methods</h4>In this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010.<h4>Results</h4>The two da ...[more]

PMID: 26373538

Similar Datasets

Project description:ImportanceDespite the broad adoption and optimization of electronic health record (EHR) systems across the continuum of care, serious usability and safety problems persist.ObjectiveTo assess whether EHR safety performance is associated with EHR frontline user experience in a national sample of hospitals.Design, setting, and participantsThis cross-sectional study included all US adult hospitals that used the National Quality Forum Leapfrog Health IT Safety Measure and also used the ARCH Collaborative EHR User experience survey from January 1, 2017, to January 1, 2019. Data analysis was performed from September 2020 to November 2022.Main outcomes and measuresThe primary outcomes were hospital performance on the Leapfrog Health IT Safety measure (overall and 10 subcomponents) and the ARCH collaborative frontline user experience scores (overall and 8 subcomponents). Ordinary least squares models with survey responses clustered by hospital were used to assess associations between the overall measures and their subcomponents.ResultsThere were 112 hospitals and 5689 frontline user surveys included in the study. Hospitals scored a mean of 0.673 (range, 0.297-0.973) on the Leapfrog Health IT safety measure; the mean ARCH EHR user experience score was 3.377 (range, 1 [best] to 5 [worst]). The adjusted β coefficient between the overall safety score and overall user experience score was 0.011 (95% CI, 0.006-0.016). The ARCH overall score was also significantly associated with 10 subcategory scores of the Leapfrog Health IT safety score, and the overall Leapfrog score was associated with the 8 subcategory scores of the ARCH user experience score.Conclusions and relevanceThis cross-sectional study found a positive association between frontline user-rated EHR usability and EHR safety performance. This finding suggests that improving EHR usability, which is a current well-known pain point for EHR users, could have direct benefits in terms of improved EHR safety.

Project description:BACKGROUND:Postoperative delirium is a common complication following major surgeries, leading to a variety of adverse effects. However, there is a paucity of literatures studying the incidence and risk factors associated with delirium after primary elective total hip arthroplasty (THA) using a large-scale national database. METHODS:A retrospective database analysis was performed based on Nationwide Inpatient Sample (NIS) from 2009 to 2014. Patients who underwent primary elective THA were included. Patient demographics, preoperative comorbidities, length of hospital stay (LOS), total charges, in-hospital mortality, and major and minor perioperative complications were evaluated. RESULTS:A total of 388,424 primary elective THAs were obtained from the NIS database, and the general incidence of delirium after THA was 0.90%. Patients with delirium after THA presented more preoperative comorbidities, longer LOS, extra hospital charges, and higher in-hospital mortality rate (P?<?0.001). Delirium following THA was associated with major complications during hospitalization including acute renal failure and pneumonia. Preoperative risk factors associated with postoperative delirium included advanced age, alcohol or drug abuse, depression, neurological disorders, psychoses, fluid and electrolyte disorders, diabetes, weight loss, deficiency anemia, coagulopathy, hypertension, congestive heart failure, valvular disease, pulmonary circulation disorders, peripheral vascular disorders, and renal failure. Both female and obesity were detected to be protective factors. CONCLUSIONS:The results of our study identified a relatively low incidence of delirium after primary elective THA, which is as reported in the NIS and not necessarily the surgical population as a whole. Postoperative delirium of THA was associated with increased preoperative comorbidities, LOS, total charges, in-hospital mortality, and major perioperative complications including acute renal failure and pneumonia. It is of benefit to study risk factors associated with postoperative delirium to moderate its consequences.

Dataset Information

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample.

Publications

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets