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Application of Statistics in Hospital and Healthcare Organizations


Abinash Adhikari


Statistician, Department of Medical Excellence, Max Healthcare,
Saket, New Delhi-110017, India




Mobile No: 09716255679, 09210261753




Now-a-days healthcare organizations are very much competitive. And they want to lead in all the areas of improvement. But sometimes they have to face big challenges for solutions to analytical problems relating to quality management, business development, cost optimization, risk management, strategic planning, decision making, inventory management, queuing management and resource utilization. There are solutions to these problems and this article will focus the areas of improvements using statistical and mathematical tools.


Introduction and Definition:


Statistics is the science of collection, tabulation, analysis and interpretation of data and drawing valid conclusions. Statistics mainly deals with data. Data can be of any type, both qualitative (not measurable numerically) and quantitative (measurable numerically). And properly collected sample data can give us the true estimate of the population with some tolerance. Hence data management (tabulation of data) is very important before performing any statistical calculations. Improper management of data can give us a wrong picture of the population. In healthcare organizations we should be very much aware about the reliability of the data. The data should be reliable in all respect. Otherwise there will be a mismatch between the real value and the estimated value. There should not be any variations from one person to other regarding pattern of the data. Standardizations are required to collect reliable data. After data collection we have to analyze the data. For analyzing data there are lots of statistical tools. And proper use of statistical tools will make us able to estimate variation, minimize error, analyze demand and supply, optimize resource, and calculate the expected values and many more that are needed. Statistics can be applied for any area from literature to advanced science and engineering technology.


Importance of Statistics:


Statistics is a discipline which is concerned with:


Design of Experiments


Numerical Analysis


Drawing Conclusions from Data

Estimation and Prediction


Decision Making

Operations Management


Statistics is an inevitable tool for research, development and management. Statistics is primarily important in applied research in all disciplines of science. Some application areas are: Education, Social Development, Health Policy and Administration, Space Research, Agricultural Research, Fisheries Management, Psychological Research, Biology, Genetics, Epidemiology, Chemistry, Criminal Justice, Economics, Marketing, Finance, Forecasting, Forestry, Actuarial Science, Insurance, Political Science, Physics, Engineering and Technology, Geography, Climatology and Hydrology, Weather Forecasting, Population Studies, Environmental Science and many other fields.


Advantages of Using Statistics in Healthcare:


Any healthcare’s big challenges are with data management and solutions to analytical problems. The problems may be related to optimize inventory, managing queue, improving quality, minimizing length of stay, measuring patient satisfaction, risk management, decision making, strategic planning, and many more. For these kinds of problems opened eye solutions will give wrong picture many times. And nobody will know that the result is wrong until there is a big problem arising in future which will contradict the solution provided after an opened eye analysis. It’s all because of improper solutions and application of wrong tools and techniques. Proper monitor and evaluation are required for all measurements. And statistics is the inevitable tool for giving the right solution with some acceptable tolerance. There are lots of statistical tools which can be used for the analysis of healthcare data. Below are some of important areas where we can use statistics and find a reasonable solution:


ØModeling Inequalities in Healthcare [1], [2]

ØModeling Healthcare Decision Making [3], Risk Analysis [4]

ØManagement of Inventory [5]

ØManaging Queue, Optimizing Patient Flow [6]

ØMinimizing Length of Stay [7]

ØPatient Bed Management [8]

ØOptimizing Cost [9]

ØForecast Sales, Forecast population (future no of patients) [10]

ØAnalysis of Demand and Supply [11]

ØInterpret Business Problems [12]

ØAnalytical Assessment of Business [13]

ØProper Utilization of Resource [14]

ØHospital Surveys [15]

ØHealthcare Research and Development [16]

ØAnalysis of Data for Quality Control [17]

ØMeasuring Quality [18]

ØMeasuring Expectations of Customers [19]

ØMeasuring Patient Satisfaction [20]

ØPredicting the Important Factors (Both Good and Bad) for hospital’s success [21]

ØMeasuring Success [22]

ØSix Sigma Implementation and Measuring Continuous Quality Improvement [23]

ØAnalysis of Mortality and Morbidity Data [24]

ØInterpret Data related to Drug Testing [25]

ØEffectiveness of New Treatments [25]

ØSample Size Calculation for Clinical Trials [26]

ØMeasuring Changes [27]

ØHealthcare Modeling [28]

ØConstant Data Compilation and Analysis [29]

ØBiomedical and Genetics data analysis [30]

ØStatistical Analysis in Laboratory Medicine [31]

ØStem Cell Research




The proper use of the statistical tools can give the healthcare organizations a lot. Even it can make able to reach a leading position if reliable solutions are found. So all the healthcare organizations can use statistics as an inevitable tool for solutions to their problems. But at the same time we have to remember that improper use of statistics can go to the opposite direction. So should be beware of misuse of statistics and nobody should apply it without proper knowledge, as it may be dangerous then. But proper application of statistics can really open a new door for improvement to the healthcare industries.




1.Andrew M. Jones, Angel López Nicolás. Measurement and explanation of socioeconomic inequality in health with longitudinal data

2.J Y Nazroo, E Falaschetti, M Pierce, P Primatesta. Ethnic inequalities in access to and outcomes of healthcare: analysis of the Health Survey for England


4.Peter C. Albertsen, James A Hanley, Donald F. Gleason, Michael J. Barry. Competing Risk Analysis of Men Aged 55 to 74 Years at Diagnosis Managed Conservatively for Clinically Localized Prostate Cancer

5.William Burke, Case Study – Inventory Management

6.Toros Caglar, A Queueing Theoretic Approach to Gridlock Prediction in Emergency Departments

7.MICHAEL RYAN, Reducing the length of stay in hospital

8.Chris Ham, Nick York, Steve Sutch, Rob Shaw. Hospital bed utilisation in the NHS, Kaiser Permanente, and the US Medicare programme: analysis of routine data


10.Health and Health Care 2010, Health and Health Care Forecast

11.Roel van der Sanden, Hayke Everwijn, Etiënne Rouwette, Jan Gubbels. Balancing supply and demand for dementia care in the Netherlands

12.Susan Keyes-Pearce. Linkage Between Business Plans and Information System Strategies Across Hospital Organizational Networks

13.International Institute of Business Analysis, Guide to the Business Analysis Body of Knowledge

14.Heather K. Sun, David P. Nicolau and Joseph L. Kuti. Resource Utilization of Adults Admitted to a Large Urban Hospital With Community-Acquired Pneumonia Caused by Streptococcus pneumoniae

15.Jack V. Tu, Joan Porter. Stroke Care in Ontario: Hospital Survey Results

16.Jennifer Peat, Craig Mellis, Katrina Williams and Wei Xuan. Health Science Research: A Handbook Quantitative Methods

17.Leo L. Pipino, Yang W. Lee, and Richard Y. Wang. Data Quality Assessment

18.Huw Davies, Measuring and reporting the quality of health care

19.A C Bara, WJA van den Heuvel, JAM Maarse. Discrepancies between Romanian patient expectations and experiences of health care

20.Rosemin Kassam, John B Collins, Jonathan Berkowitz. Developing anchored measures of patient satisfaction with pharmaceutical care delivery: Experiences versus expectations

21.José M Quintana, Nerea González, Amaia Bilbao, Felipe Aizpuru, Antonio Escobar, Cristóbal Esteban, José Antonio San-Sebastián, Emilio de-la-Sierra and Andrew Thompson. Predictors of patient satisfaction with hospital health care

22.Kevin J. Leonard. Critical Success Factors Relating to Healthcare’s Adoption of New Technology: A Guide to Increasing the Likelihood of Successful Implementation

23.Nadica Hrgarek, Kerri-Anne Bowers. Integrating Six Sigma into a Quality Management System in the Medical Device Industry

24.Anjali Tempe, Leena Wadha, Shally Gupta, Siddharth Bansal, Labani Satyanarayana. Prediction of Mortality and Morbidity by Simplified Acute Physiology Score II in Obstetric Intensive Care Unit Admissions

25.Christy Chuang-Stein, Ralph D’Agostino. Statistics in Drug Development

26.Janet Wittes. Sample Size Calculations for Randomized Controlled Trials

27.Martin Gaynor and Deborah Haas-Wilson. Change, Consolidation, and Competition in Health Care Markets

28.A.I. Yashin & E.N. Shigan. Problems of Modeling and Decision Making in Health Care

29.Canadian Institute for Health Information: Experiences With Primary Health Care in Canada (July 2009)

30.Russ Wolfinger, Improved Statistical Analysis of Data from Genetics, Microarrays, and Proteomics

31.Michael F. W. Festing and Douglas G. Altman. Guidelines for the Design and Statistical Analysis of Experiments Using Laboratory Animals


Article By: Abinash Adhikari

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