Operations Research in Healthcare Industry

8/11/2019 Operations Research in Healthcare Industry

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Operations Research in Healthcare industry


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Introduction

Operational Research is the scientific study of operations for the purpose of

making better decisions.

It is a discipline that deals with application of advanced analytical methods to

facilitate better decisions.

It represents the study of optimal resource allocation.

In simple terms, it is described as the science of better

Now a days the principles and techniques of Operational Research are being

applied in every field of human research and development


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HISTORY

Operational Research has been existed as a science since 1930s.

But as a formal discipline Operational Research originated by the efforts of

military planner during World War II

The analytical study of military problems was undertaken to provide scientific

basis for decisions to improve military operations.

In the decade after World War-II the techniques began to be applied more

widely in problems of business, industries and societies

Since the time Operational Research has expanded into a field widely used in

industries ranging from petro- chemical to airlines, finances, logistics and

government.

Now it has become an area of active academic and industrial research

The techniques of Operational Research have been applied and proven in many

industries under different names. For instance :- - Lean in manufacturing. -

Supply Chain in logistics and - Yield Management in airlines.


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OBJECTIVES OFOPERATIONAL RESEARCH

Decision making and improve its quality.

Identify optimum solution.

Integrating the systems. Improve the objectivity of analysis.

Minimize the cost and maximize the profit.

Improve the productivity.

Success in competition and market leadership.


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Introduction of Operation Research in Hospitals

Ancillary services such as those provided by logistics seem simple and straight

forward, yet their role is often overlooked by hospitals.

Recent studies indicate that logistics-related activities impact significantly on

the quality of health care as well as on hospital costs.

Hospital logistics contributes to the provision of care to patients by ensuring

that all required services and resources are delivered at the right time.

Operations Research provides methodologies to support the logistical

operations of hospitals and assist in process optimization.

Operations Research (OR) provides a wide range of methodologies that can

help hospitals and other health care systems to significantly improve their

operations.

At the same time, many of the complex problems presented by the health care

sector also foster the development of new OR methodologies.


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What are Operations Research Technologies?

There are many ways in which management science and Operations Research

can use information to study and improve business processes. Foremost

amongst a range of techniques that we use are those of discrete-eventsimulation and systems optimization.

Discrete-event simulation

Discrete-event simulation is particular suited to the representation of hospital

services, because of its ability to reflect the non-steady stat behaviors that typify

clinical demand. As its name suggests, discrete-event simulation treats each

arrival, usually that of a patient, into a model of a hospital system as a specific

individual and records the experiences of that particular individual as he or she

passes through the processes within the model. In this way, the queues and

associated delays that occur at times of peak demand are clearly revealed, in

precise statistical terms. An accurate picture emerges of the extremes of system

performance in a way that does not occur with more commonly used modeling

techniques that use averaging methods. Discrete-event simulation is the best

way to understand the effects of the peaks and troughs of clinical demand.

Systems optimization

Computer based optimization techniques enhance the value of outputs from a

discrete-event simulation model. They allow you to define a performance target

and then perform an automated sequence of simulation experiments that, with

each successive iteration, through a methodical adjustment of the key dependent

variables, converge upon the optimal settings for the system. The newly

optimized set of operating parameters may now be implemented in real life.


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Applications of Operations Research in Health Care:

The field of health care has traditionally provided a broad range of applications

suitable for analysis using Operations Research (OR) techniques. Most of the

historical applications were either motivated or were a consequence of theburdens new medical technologies pose on complex health care delivery

systems. However, as medical technology progresses further, the spectrum of

possible OR applications is only going to become broader and more exciting. In

fact, the recent explosion of technological innovations in health care, which has

been fuelled by new knowledge and information, has been matched by renewed

interest among OR scholars.

Some Operations Research application areas in health care are:

-Personalization of therapies based on advanced medical information.

-Optimization of new or existing medical technologies to meet either a specific

clinical goal or a specific system goal.

-Management and optimization of health care operations.

-Resource allocation problems in health care.

The decision technologies, tools and theories of Operations Research and

Management Sciences have long been applied to a wide range of issues and

problems within health care.

Broad Areas of Operations Research Application:

Health Care Operations Improvement:

-Scheduling and workforce planning

-Inventory management

-Supply chain management

-Logistics planning and modeling

-Equipment planning,


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-Planning

-Facility location and layout

-Workforce & workload models

-Decision support systems

-Performance measurement & modeling

-Queuing models

-Quality management

Economic Analysis:

-Equipment evaluation & selection models

-Optimal pricing and costing models

-Demand forecasting and planning models

-Impact of policies on health care demand

-Technology assessment.

Public Policy:-Regional planning and network models

-Access and availability population models

-Technology diffusion models

-Disease prevention

-Health care coverage

-Vaccine modeling

-Organ allocation models

-Disease screening

-Resource allocation


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-Drug policies

-Blood supply management policies

Clinical Applications:

-Risk assessment and analysis

-Clinical diagnosis and decision making


-Disease modeling (individual level)

-Treatment design and planning

-Drug selection models

-Optimal dosing models

-Vaccine models

-Clinical qualities

In the context of material and patient flows, hospital logistics and OM provide a

broad range of applications suitable for analysis using OR techniques

An area that has received considerable attention among operations researchers

is workforce scheduling, and in particular, nurse roistering.

The problem of constructing work timetables for nurses to cover fluctuatingdemand requirements is extremely difficult.

The rosters must satisfy work regulations, distinguish between permanent and

casual staff, assign suitably qualified nurses, distribute night and weekend shifts

equitably among nurses, allow for leave and days, and accommodate a range of

employee preferences.Despite the vast body of literature on production planning and inventory

control, the translation of well-known practices into the hospital environment is

not as widespread as might be hoped. Purchasing, distribution, and inventory

management of medical supplies could greatly benefit from OR


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Need of Operation research in Health care industry

Global health challenges

We now look at some key generic challenges that arise in global health and

consider how operational research and management science can contribute toeach.

Global health challenges for operational research and management science

Identifying problemsOperational research methods are useful for the systematic identification of

problems and the search for potential solutions. Structured approaches toidentifying options, such as the strategic choice approach23or systematic

creativity approaches. New approaches are important for global health because

strategies and programmes must be designed to deal with both current and future

challengesfrom the global spread of disease to the impact of climate change.This can sometimes take us beyond traditional forecasting methodologies to the

use of scenario analysis and other futures thinking methods.

Choosing interventions

Choosing appropriate interventions is clearly a crucial step. Effectiveness,safety, cost and equity should all be considered and researchers will be familiar

with standard text-book methods for assessing these. But, in reality, assessmentsare rarely straightforward. It is often more effective and efficient to combine

interventions, or to treat more than one disease at a time. For example, the
http://www.who.int/bulletin/volumes/89/9/11-086066/en/#R23http://www.who.int/bulletin/volumes/89/9/11-086066/en/#R23http://www.who.int/bulletin/volumes/89/9/11-086066/en/#R23


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integration of treatments for different diseases into cost-saving combined

packages.Finding the best combinations and delivery methods is a majorresearch exercise in its own right. Modelling different intervention strategies

before roll-out is now ubiquitous in many industries but is less common in

health care. Combining this approach with the necessary field and pilot studiesshould speed up and focus efforts. Modelling work has been done on ways to

reduce maternal mortality and in cervical cancer screening in low-resourcesettings.

Introducing new interventions

Innovation is a key issue in global health. For instance telemedicine isincreasingly being used in high-income countries, and beginning to be applied in

middle- and low-income countries, enabled by the rapid global spread of mobilephone networks. However, many such applications in developing countries arenot evaluated so there is a clear role for operational research to assess them and

to improve their design and deliveryThe contribution that operational researchand management science can make to design and delivery is not restricted to

high technology. Oral rehydration therapy is a low-techlow-costhigh-

impact innovation in which operational research was used to explore ways it

could be administered at low cost using readily available ingredients by laypeople, with an escalation pathway to treatment by health-care professionals

when necessary.

Scaling-up

Small-scale projects generally need considerable modifications to work on a

larger scale. For example, we need to understand better what happens when

whole countries are treated with drugs or vaccines. Such upscaling includes a

need to forecast future demand, to decide the location and size of facilities andto set staffing levels. Classic operational research techniques such as simulation

modelling can be used in locating services, managing the pharmaceutical supply

chain and developing the health care workforce.


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Improving patient flows through Operations Research

Hospitals are complicated places. Every day they must face the problem of howbest to meet complex, often rapidly changing clinical demands with the finite

resources that are actually available to them. Unlike many manufacturing and

service industries, few hospitals can draw upon the proven capabilities ofOperations Research based technologies to guide them with capacity planning andwith their daily operations.

At Hospital Navigator we study the logistics of hospital services. We use

management science and Operations Research techniques to enable hospitals totreat patients better, to meet performance targets and yet contain costs.


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Opportunities for Operations Research

OR has a long history of successful application of advanced analytical methods

to help make better decisions in many industrial sectors

Although health care OR is not a new field the number and impact of ORapplications lag behind other service industries.

Often, decision-makers claim that health care systems, and in particular

hospitals, pose rather complex and dynamic problems compared to those facedby other service industries, thereby hindering the successful application of OR

tools.

However, complex processes also arise in industrial settings and many OM

concepts and OR methodologies have been successfully developed to tackle

them.

Naturally, it is necessary to identify their applicability to meet the specificconditions encountered in hospitals.


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Conclusion

Hospitals are under increasing pressure to reduce unnecessary costs while

improving the quality of the care they provide to patients.

There is much room for OR to improve resource management and thus makingsupply meet demand for care adequately.

A fundamental requirement for the successful application of OR techniques is a

basic understanding of the core hospital processes and the way in which theyuse resources.

There are many protocol-based care pathways for patients with a given clinicalprofile that define the expected steps to be followed by such patients.

However, these protocols are often clinically focused and ignore theinteractions between processes and the use of resources.

Operational Research needs to be integrated as an essential part of monitoringand evaluation efforts in Public Health.

Thus concept of MORE could become a new paradigm for enhancing the

practice of integrated monitoring and evaluation dimensions as one commoncomponent into program management system.


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Introduction










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HISTORY










government.






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operations.




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-Planning





-Queuing models

-Quality management

Economic Analysis:









-Disease prevention


-Vaccine modeling


-Disease screening



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-Drug policies










-Vaccine models

-Clinical qualities














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when necessary.

Scaling-up








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tools.



them.



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Conclusion












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Introduction










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HISTORY










government.






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operations.




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-Planning





-Queuing models

-Quality management

Economic Analysis:









-Disease prevention


-Vaccine modeling


-Disease screening



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-Drug policies










-Vaccine models

-Clinical qualities














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when necessary.

Scaling-up








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tools.



them.



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Conclusion












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Introduction










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HISTORY










government.






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operations.




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-Planning





-Queuing models

-Quality management

Economic Analysis:









-Disease prevention


-Vaccine modeling


-Disease screening



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-Drug policies










-Vaccine models

-Clinical qualities














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when necessary.

Scaling-up








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tools.



them.



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Conclusion












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Operations Research in Healthcare Industry

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