Big Data Analytics and Visualization for Hospital Recommendation using HCAHPS Standardized Patient Survey

Full Text (PDF, 945KB), PP.1-9

Views: 0 Downloads: 0


Ajinkya Kunjir 1,* Jugal Shah 1 Navdeep Singh 1 Tejas Wadiwala 1

1. Lakehead University, Department of Computer Science, Thunder Bay, Ontario, Canada

* Corresponding author.


Received: 30 Dec. 2018 / Revised: 11 Jan. 2019 / Accepted: 20 Jan. 2019 / Published: 8 Mar. 2019

Index Terms

HCAHPS, Predictive Analysis, Classification, Survey, Recommendation, Patient Satisfaction


In Healthcare and Medical diagnosis, Patient Satisfaction surveys are a valuable information resource and if studied adequately can contribute significantly to recognize the performance of the hospitals and recommend it. The analysis of measurements concerning patient satisfaction can act as a valid indicator for giving recommendations to the patient about a specific hospital, as well as can provide insights to improve the services for healthcare organizations. The primary objective of the proposed research is to carry out an in-depth investigation of all the measurements in HCAHPS survey dataset and distinguish those that contribute considerably to the hospital suggestions. This work performs predictive analysis by building multiple classification models, each of which examined and evaluated to determine the efficiency in predicting the target variable, i.e., whether the hospital is recommended or not, based on specific set of measurements that contribute to it. All the models built as a part of research specified the same list of measure id is that help in deriving the target. It provides an insight into how caregiver interaction, emphasizes on the services rendered by the caregiver and overall patient experience makes a hospital highly valued and preferred. An in depth-analysis is conducted to derive the implementation results and have been stated in the later part of the paper.

Cite This Paper

Ajinkya Kunjir, Jugal Shah, Navdeep Singh, Tejas Wadiwala, "Big Data Analytics and Visualization for Hospital Recommendation using HCAHPS Standardized Patient Survey", International Journal of Information Technology and Computer Science(IJITCS), Vol.11, No.3, pp.1-9, 2019. DOI:10.5815/ijitcs.2019.03.01


[1]Young GJ, Meterko M, Desai KR, “Patient Satisfaction with hospital care: Effects of demographic and institutional characteristics”, Med Care 2000;38: 325-334.

[2]Jackson JI, Kroenke K, “Patient Satisfaction and Quality of Care,” Mil Med 1997;162:273-277.

[3]Burroughs TE, Davies AR, Cira JC, Dungan WC, “Understanding patient willingness to recommend and return: A strategy for prioritizing improvement opportunities, 1999.

[4]"HCAHPS Hospital Survey," [Online]. Available:

[5]E. Sezgin, S. Ozkan,, "A systematic literature review on Health Recommender Systems," in E-Health and Bioengineering Conference (EHB), Iasi, 2013.

[6]T.G. Morrell, L. Kerschberg, "Personal Health Explorer: A Semantic Health Recommendation System," in Data Engineering Workshops (ICDEW), 2012 IEEE 28th International Conference, Arlington, 2012.

[7]L. Fernandez-Luque, R. Karlsen, L. K. Vognild, "Challenges moreover, opportunities of using recommender systems for personalized health education," MID, pp. 903-907, August 2009.

[8]G. Adomavicius, A. A. Tuzhilin, "Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions," IEEE Trans. on Knowl. and Data Eng., vol. 17, no. 6, pp. 734-749, 2005.

[9]Tannaz Sattari Tabrizi, Mohammad Reza Khoie, Elham Sahebkar, Shahram Rahimi, Nina Marhamati,” Towards a Patient Satisfaction Based Hospital Recommendation System”, IEEE 2016.

[10]Shou-Hsia Cheng, Ming-Chin Yang, Tung-Liang Chiang,” Patient Satisfaction with the recommendation of a hospital: effects of interpersonal and technical aspects of hospital care”, International Journal for Quality in Health Care 2003; Volume 15, Number 4: pp. 345±355.

[11]Hanqing Chao, Yuan Cao, Junping Zhang, Fen Xia, Ye Zhou, and Hongming Shan,” Population Density-based Hospital Recommendation with Mobile LBS Big Data”, arXiv, 2017.

[12]Kyle Kemp, Brandi McCormack,” Semantics-enhanced Recommendation System for Social Healthcare”, 2015.

[13]Minerva, Sanjog,”Big Data in Health care : A Mobile based solution”, ICBDAC, IEEE2017.

[14]Xiao Li, “Patient record level integration of de-identified healthcare big databases”, IEEE 2016.

[15]John W. Huppertz, Jay P. Carlson, “Consumers Use of HCAHPS Ratings and Word‐of‐Mouth in Hospital Choice”, November 2010.

[16]Thomas Isaac, Alan M. Zaslavsky, Paul D. Cleary, Bruce E. Landon, “The Relationship between Patients’ Perception of Care and Measures of Hospital Quality and Safety”, July 2010.

[17]Kyle A. Kemp,Nancy Chan, Brandi McCormack, Kathleen Douglas, “Drivers of Inpatient Hospital Experience Using the HCAHPS Survey in a Canadian Setting”, December 2014.

[18]Rupinder K. Mann, Zishan Siddiqui, Nargiza Kurbanova, Rehan Qayyum, “Effect of HCAHPS reporting on patient satisfaction with physician communication”, September 2015.


[20]Parul Pandey, “A Guide to Machine Learning for Beginners: Logistic Regression”, August 2018.