This study developed an interactive dashboard to compare hospitals using data from the HCAHPS survey. Statistical analyses found that hospital type and ownership had significant associations with overall hospital ratings. The dashboard contains three main components: a hospital map displaying location, type and score, bar graphs comparing HCAHPS metrics, and filters to select hospitals. It allows users to dynamically explore and compare hospitals. The dashboard demonstrates how data visualization can provide insight from large datasets and identifies opportunities to further evaluate and improve such interfaces.

1. The School of Biomedical Informatics |The University of Texas Health Science Center at Houston
HI 5351: Research Design and Evaluation in Health Informatics - Fall, 2016
Han Chen, Ram Dixit, Hannah Joy Plamthottathil, Digant Shah
Supporting Hospital Comparison Using Data Visualization
Results
Introduction
• The source and presentation of publicly reported data on
hospital performance can influence consumers’ decision-
making1.
• As such, reports on performance data should be easy to
use and clearly interpretable to accurately evaluate the
effectiveness of healthcare services2.
• One such data source is the HCAHPS survey
administered by the CMS. The aims of this study are to:
1. Analyze hospital factors that are statistically related to
HCAHPS overall hospital rating.
2. Create a proof-of-concept interactive data visualization
of these factors to support exploration and comparison
of hospital scores.
• Our study is novel in its use of visualization principles to
provide functionality to effectively compare hospitals and
statistical analysis to highlight relevant data.
• Previous efforts have visualized HCAHPS hospital data,
but did not present the data in a meaningful way3,4.
• The visualizations described here can be used to
analyze a single facility or compare across numerous
facilities based on the reported measures.
• While useful in perceiving patterns across hospitals, this
visualization does not consider natural variation and
control limits that are necessary to accurately
characterize variations in hospital processes.
• Future work could increase the scope of the dashboard
to include results from previous years to visualize trends
in ratings and account for natural variation.
We thank Dr. Todd Johnson for assisting us with the
visualization, and Dr. James Langabeer and Karima Lalani
for advising us throughout this project.
Please contact the first author via email:
han.chen.1@uth.tmc.edu
Figure 1. Conceptual Framework and Aims of the study.
• HCAHPS data was accessed from HospitalCompare.gov and cleaned in Trifacta Wrangler.
• A descriptive statistical analysis and a one-way ANOVA on ranks was conducted using IBM
SPSS Statistics to determine whether significant differences existed within Hospital Type and
Hospital Ownerships on their Hospital Overall Rating.
• Finally, an interactive dashboard of the HCAHPS data was created using Tableau v10.0.
Table 3. Mean Ranks by Hospital Ownership
Hospital Ownership N Mean Std Dev
Non-Profit – Church 348 2.85 1.20
Non-Profit – Other 462 2.69 1.31
Non-Profit – Private 1934 2.50 1.43
Proprietary 788 2.43 1.31
Government – State 58 2.08 1.40
Physician 63 1.92 2.15
Government – Hospital
District or Authority
552 1.84 1.57
Government – Local 402 1.73 1.54
Government – Federal 174 0.32 0.98
Tribal 7 0.71 1.25
Table 1. Descriptive statistics of hospitals’ overall
HCAHPS ratings
N Mean Median Std Dev Var Skewness Kurtosis
4788 2.30 3.00 1.499 2.247 -0.46 -1.065
Table 2. Mean Ranks by Hospital Type
Hospital Type N Mean Std Dev
Acute Care Hospitals 1171 2.73 1.194
Veterans Administration 129 0 0
Children’s Hospital 22 0 0
Critical Access Hospitals 1272 1.44 1.681
(χ2(3) = 758.33, p < 0.000)
(χ2(9) = 450.29, p < 0.000)
• A novel combination of visualization principles and
statistical analyses was used to create a proof-of-
concept HCAHPS dashboard that allows users to
interact and compare hospitals through a dynamic
interface.
• This demonstration shows the promise of using data
visualization techniques for gaining insight from large
datasets and opens the door for future research
opportunities in evaluating and improving on such
interfaces.
Conclusion
References
1.Victoor A, Delnoij DM, Friele RD, Rademakers JJ. Determinants of
patient choice of healthcare providers: A scoping review. BMC health
services research. 2012;12(1):1.
2.Drevs F. How patients choose hospitals: Using the stereotypic
content model to model trustworthiness, warmth and competence.
Health Serv Manage Res. 2013;26(2-3):95-101.
3.CMS HCAHPS Star Rating – The Advisory Board. (2016, May 9).
Retrieved from:
https://dag.advisory.com/2013_G_DAG_Gmap/Home/MapView?mapn
ame=cms_hcahps_star_rating
4.Hayes B. Map of US hospitals and their patient experience ratings.
http://businessoverbroadway.com/map-of-us-hospitals-and-their-
patient-experience-ratings. Updated 2012. Accessed 10/3, 2016.
Acknowledgements
Figure 2. Prototype of the HCAHPS Dashboard. A) The “Hospital Map” displays hospitals
by their location, type, and average score. B) The “HCAHPS Metrics Comparison” section
shows bar graphs for individual HCAHPS metrics and the national average score. C) The
filters and legends allow users to narrow or change the selection displayed on the map.
Tables 1, 2, and 3. Table 1 shows the descriptive statistics of hospitals’ overall HCAHPS
ratings. Tables 2 and 3 show the mean ranks and ANOVA results (below each table) for
hospitals categorized by Hospital Type and Hospital Ownership respectively.
In this study we developed an interactive dashboard to
support exploration and comparison of hospitals using the
Center for Medicare and Medicaid Services (CMS)
Hospital Consumer Assessment of Healthcare Providers
and Systems (HCAHPS) survey. A one-way ANOVA on
ranks was performed to determine whether significant
differences existed between Hospital Types and Hospital
Ownerships on Hospitals’ Overall Ratings. Based on the
results, an interactive dashboard of HCAHPS data was
created using Tableau v10.0. Hospital Type and Hospital
Ownership had statistically significant associations with
Overall Hospital Ratings, and were incorporated in the
resulting dashboard. The dashboard has three main
components: Hospital Map, HCAHPS Metrics
Comparison, and filters that allow users to interact and
compare hospitals through a dynamic interface.
Methods DiscussionAbstract