Journal of Medical Systems

, 44:54 | Cite as

Web-Based Dashboard for the Interactive Visualization and Analysis of National Risk-Standardized Mortality Rates of Sepsis in the US

  • Meng-Tse Lee
  • Fong-Ci Lin
  • Szu-Ta Chen
  • Wan-Ting Hsu
  • Samuel Lin
  • Tzer-Shyong Chen
  • Feipei Lai
  • Chien-Chang LeeEmail author
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement


Sepsis mortality is heavily influenced by the quality of care in hospitals. Comparing risk-standardized mortality rate (RSMR) of sepsis patients in different states in the United States has potentially important clinical and policy implications. In the current study, we aimed to compare national sepsis RSMR using an interactive web-based dashboard. We analyzed sepsis mortality using the National Inpatient Sample Database of the US. The RSMR was calculated by the hierarchical logistic regression model. We wrote the interactive web-based dashboard using the Shiny framework, an R package that integrates R-based statistics computation and graphics generation. Visual summarizations (e.g., heat map, and time series chart), and interactive tools (e.g., year selection, automatic year play, map zoom, copy or print data, ranking data by name or value, and data search) were implemented to enhance user experience. The web-based dashboard ( is cross-platform and publicly available to anyone with interest in sepsis outcomes, health inequality, and administration of state/federal healthcare. After extrapolation to the national level, approximately 35 million hospitalizations were analyzed for sepsis mortality each year. Eight years of sepsis mortality data were summarized into four easy to understand dimensions: Sepsis Identification Criteria; Sepsis Mortality Predictors; RSMR Map; RSMR Trend. Substantial variation in RSMR was observed for different states in the US. This web-based dashboard allows anyone to visualize the substantial variation in RSMR across the whole US. Our work has the potential to support healthcare transparency, information diffusion, health decision-making, and the formulation of new public policies.


Dashboard Sepsis Risk standardized mortality rate And visualization 



Agency for Healthcare Research and Quality


Acute Myocardial Infarction


Clinical Classification Software codes


Centers for Medicare & Medicaid Services


Heart Failure


Hierarchical linear modeling


Health and Human Services


International Classification of Diseases, Ninth Revision, Clinical Modification


National Inpatient Sample


National Quality Forum


Risk Standardized Mortality Rates

United States




We thank the staff of the Core Labs, the Department of Medical Research, and National Taiwan University Hospital for technical support. Medical wisdom consulting group for technical assistance in statistical analysis.

Funding Information

This study is supported by the Taiwan National Science Foundation Grant NSC 102–2314-B-002 -131 -MY3; Taiwan National Ministry of Science and Technology Grants MOST 104–2314-B-002 -039 -MY3, and MOST 105–2811-B-002-031. No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Compliance with Ethical Standards

Financial Disclosure and Conflict of Interest

None declared.

Conflict of Interest

No Conflicts.

Supplementary material

10916_2019_1509_MOESM1_ESM.docx (176 kb)
ESM 1 (DOCX 175 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  • Meng-Tse Lee
    • 1
  • Fong-Ci Lin
    • 2
  • Szu-Ta Chen
    • 3
    • 4
    • 5
    • 6
  • Wan-Ting Hsu
    • 3
  • Samuel Lin
    • 7
  • Tzer-Shyong Chen
    • 8
  • Feipei Lai
    • 1
    • 9
    • 10
  • Chien-Chang Lee
    • 2
    • 11
    Email author
  1. 1.Department of Emergency MedicineNational Taiwan University HospitalTaipeiTaiwan
  2. 2.Graduate Institute of Biomedical Electronics and BioinformaticsNational Taiwan UniversityTaipeiTaiwan
  3. 3.Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonUSA
  4. 4.Department of PediatricsNational Taiwan University Hospital Yun-Lin BranchYunlin CountyTaiwan
  5. 5.Department of PediatricsNational Taiwan University and College of MedicineTaipeiTaiwan
  6. 6.Graduate Institute of ToxicologyCollege of Medicine, National Taiwan UniversityTaipeiTaiwan
  7. 7.Department of Data SciencesUniversity of CaliforniaBerkeleyUSA
  8. 8.Department of Information ManagementTunghai UniversityTaichungTaiwan
  9. 9.Department of Computer Science & Information EngineeringNational Taiwan UniversityTaipeiTaiwan
  10. 10.Department of Electrical EngineeringNational Taiwan UniversityTaipeiTaiwan
  11. 11.Health Economic Outcomes Research Group and Department of Emergency MedicineNational Taiwan University HospitalTaipeiTaiwan

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