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Abstract

Information technology (IT) can act as a catalyst to sustain and ameliorate any healthcare services and delivery. This study aims to systematically review the impact of IT on hospitals’ performance and identify factors contributing towards hospital efficiency and healthcare services and input and output indicators. The search databases included PubMed, Google Scholar, Scopus and Science Direct. The time period included was from 1st January 2010 to 31st December 2020. A total of 21 articles were included. Among these, 12 were from Asia, five from North America and four from Europe. This review showed that six of 21 studies discussed the direct impact of IT on hospital performance and suggested boosting Hospital Information Technology (HIT) to increase hospital productivity and improve the work environment. The review findings included 18 input indicators and 25 output indicators for assessing hospital efficiency. Our results indicated that hospitals in Asian countries could increase their output by up to 23.70% while maintaining the current level of inputs for adequate performance. There is a strong need for governments and policymakers to formulate national strategies for implementing HIT for performance enhancement, error reduction and fast healthcare services in less-developed countries like India. In addition, regular training, educational opportunities on data management, HIT for healthcare and non-healthcare staff, appropriate use of available resources and critical monitoring are vital.

Keywords

Input indicators output indicators data envelopment analysis hospital performance information technology systematic review

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References

Alolayyan

M. N.

, Alyahya

M. S.

, Alalawin

A. H.

, Shoukat

, & Nusairat

F. T.

(2020). Health information technology and hospital performance the role of health information quality in teaching hospitals. Heliyon , 6(10). https://doi.org/10.1016/j.heliyon.2020.e05040

Annapoorni

, & Prakash

(2017). Measuring the performance efficiency of hospitals: PCA–DEA combined model approach. Indian Journal of Science and Technology , 9(S1). https://doi.org/10.17485/ijst/2016/v9is1/93159

Caballer-Tarazona

, Moya-Clemente

, Vivas-Consuelo

, & Barrachina-Martínez

(2010). A model to measure the efficiency of hospital performance. Mathematical and Computer Modelling , 52(7–8), 1095–1102. https://doi.org/10.1016/j.mcm.2010.03.006

Chitnis

, & Mishra

D. K.

(2019). Performance efficiency of Indian private hospitals using data envelopment analysis and super-efficiency DEA. Journal of Health Management , 21(2), 279–293. https://doi.org/10.1177/0972063419835120

Davey

, Raghav

S. K.

, Singh

J. V.

, Davey

, & Singh

(2015). A comparative evaluation of public health centers with private health training centers on primary healthcare parameters in India: A study by data envelopment analysis technique. Indian Journal of Community Medicine , 40(4), 252–257. https://doi.org/10.4103/0970-0218.164394

Hafner

J. M.

, Williams

S. C.

, Koss

R. G.

, Tschurtz

B. A.

, Schmaltz

S. P.

, & Loeb

J. M.

(2011). The perceived impact of public reporting hospital performance data: Interviews with hospital staff. International Journal for Quality in Health Care , 23(6), 697–704. https://doi.org/10.1093/intqhc/mzr056

Jat

T. R.

, & Sebastian

M. S.

(2013). Technical efficiency of public district hospitals in Madhya Pradesh, India: A data envelopment analysis. Global Health Action, 6(1). https://doi.org/10.3402/gha.v6i0.21742

Khalifa

, & Alswailem

(2015). Hospital information systems (HIS) acceptance and satisfaction: A case study of a tertiary care hospital. Procedia Computer Science , 63, 198–204. https://doi.org/10.1016/j.procs.2015.08.334

Kumar

(2011). Impact of health information systems on organizational health communication and behavior. The Internet Journal of Allied Health Sciences and Practice , 9(2). https://doi.org/10.46743/1540-580X/2011.1350

10.

Labib

N. A.

, Ghobashi

M. M.

, El-Shafei

, Al-Fadhli

A. N.

, & Dashti

M. H.

(2016). Assessment of Ibn-Sina specialized surgical tertiary care hospital performance and defining opportunities for improvement. Medical Journal of Cairo University , 84(2), 347–352.

11.

McCullough

J. S.

, Casey

, Moscovice

, & Prasad

(2010). The effect of health information technology on quality in U.S. hospitals. Health Affairs , 29(4), 647–654. https://doi.org/10.1377/hlthaff.2010.0155

12.

Mehrtak

, Yusefzadeh

, & Jaafaripooyan

(2014). Pabon Lasso and data envelopment analysis: A complementary approach to hospital performance measurement. Global Journal of Health Science , 6(4), 107–116. https://doi.org/10.5539/gjhs.v6n4p107

13.

Melis

A. K.

, & Ertugrul

E. K.

(2014). Imprecise DEA framework for evaluating the efficiency of state hospitals in Istanbul . World Congress on Engineering, July 2–4, London, UK.

14.

Mogha

, Yadav

, & Singh

(2012). Performance evaluation of Indian private hospitals using DEA approach with sensitivity analysis. International Journal of Advances in Management and Economics , 1(2), 1–12. https://doi.org/10.31270/ijame/01/02/2012/01

15.

Page

M. J.

, McKenzie

J. E.

, Bossuyt

P. M.

, Boutron

, Hoffmann

T. C.

, Mulrow

C. D.

, & Moher

(2021). Updating guidance for reporting systematic reviews: Development of the PRISMA 2020 statement. Journal of Clinical Epidemiology , 134, 103–112. https://doi.org/10.1016/j.jclinepi.2021.02.003

16.

Pavithra

(2019). Do we have enough doctors in the country? Factly . https://factly.in/do-we-have-enough-doctors-in-the-country/

17.

Polyzos

(2012). A three-year performance evaluation of the NHS hospitals in Greece. Hippokratia , 16(4), 350–355.

18.

Pourmohammadi

, Hatam

, Shojaei

, & Bastani

(2018). A comprehensive map of the evidence on the performance evaluation indicators of public hospitals: A scoping study and best fit framework synthesis. Cost Effectiveness and Resource Allocation , 16(1). https://doi.org/10.1186/s12962-018-0166-z

19.

Rabar

(2013). Evaluation of Croatia’s regional hospital efficiency: An application of data envelopment analysis. Interdisciplinary Management Research , 9, 649–659. https://www.researchgate.net/publication/303630703

20.

Sharma

, Chandrasekaran

, Boyer

K. K.

, & McDermott

C. M.

(2016). The impact of Health Information Technology bundles on hospital performance: An econometric study. Journal of Operations Management , 41, 25–41. https://doi.org/10.1016/j.jom.2015.10.001

21.

Sun

, Zhang

, Yang

, Zhang

, Luo

, & Han

(2016). Data envelopment analysis on evaluating the efficiency of public hospitals in Tianjin, China. Transactions of Tianjin University , 22(2), 182–188. https://doi.org/10.1007/s12209-016-2725-8

22.

Tripathi

C. B.

, Kumar

, Sharma

R. C.

, & Agarwal

(2016). Assessment of performance of services in a tertiary care neuropsychiatric institute using Pabon Lasso model. Asian Journal of Medical Sciences , 7(6), 69–74. https://doi.org/10.3126/ajms.v7i6.15408

23.

Wang

, Luo

, Qin

, Feng

, Gao

, & Feng

(2016). Evaluation of performance and impacts of maternal and child health hospital services using data envelopment analysis in Guangxi Zhuang Autonomous Region, China: A comparison study among poverty and non-poverty county level hospitals. International Journal for Equity in Health , 15(1). https://doi.org/10.1186/s12939-016-0420-y

24.

Williams

, Asi

, Raffenaud

, Bagwell

, & Zeini

(2016). The effect of information technology on hospital performance. Health Care Management Science , 19(4), 338–346. https://doi.org/10.1007/s10729-015-9329-z

Impact of Information Technology on the Performance of Tertiary Care Hospitals: A Systematic Review

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