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Slides + notes Healthcare Analytics and Optimization

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All slides of the course Health Analytics and Optimization of the master Health Sciences. Also includes personal notes + further explanations.

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  • 13 januari 2025
  • 108
  • 2024/2025
  • College aantekeningen
  • Erwin hans
  • Alle colleges
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Healthcare Analytics and Optimization
Lecture 1 Optimizing Healthcare Processes (11/11 & 18/11)
Roughly two types of studies within OM:
1. Modeling related studies: These studies focus on developing mathematical, computational, or
simulation models to analyze and optimize operational processes (focus of this course)
2. Empirical studies: These studies collect and analyze real-world data to investigate operational
phenomena and validate theories or models (main focus within rest of the program)

Learning Objectives
• describe the basic principles of OM
• explain the steps in a problem-solving methodology
• describe the impact of variability
• compare productivity within/between various healthcare organizations
• recognize the use of queuing, simulation and mathematical programming models in a
healthcare setting
• classify planning functions in the framework for planning and control
• evaluate projects using project management techniques
• develop and analyze quality monitoring and control charts
• determine which OM-tools to use for analyzing and optimizing processes in a specific
healthcare situation
• apply the tools provided in settings discussed in the lectures, and in new settings
• draw conclusions from the analyses done
• implement the tools in Excel

Operations management (OM)
= the activity of managing the resources which are devoted to the production and delivery of
products and services.
= an area of business that is concerned with the production of good quality goods and services, and
involves the responsibility of ensuring that business operations are efficient and effective. It is the
management of resources, the distribution of goods and services to customers.

What is important for performance of organizations:
 Efficiency
 Effectiveness
 Quality of care (QALYs)
 Quality of service (patient experience)
 Quality of labor (work pressure)
 Sustainability (“Effectiveness”: serving the purpose)
o Economical sustainability = does the organization still exists in ten years?
o Societal sustainability = personal shortage, if we don’t change than we need more
personal in the future  infeasible
o Ecological sustainability = impact on the planet

In healthcare, not many performance measures are measured. Focusing on one thing, limits the
other.
 In hospitals, money is leading the process.
 Matching demand & supply
o Supply = capacity, demand = patients


1

,OM  the challenge is organizing multi morbid care for specialties in healthcare
 No single electronic healthcare system among hospitals or GP’s: impossible to share
information about patients, no communication.

Operations management in healthcare
The need for OM in healthcare
 Advance of new technologies
 Rising costs: In healthcare there is annual growth in health expenditure.
 Poor quality
 Aging populations in developed countries
 Empowered healthcare consumer
 Medical and life sciences knowledge explosion

Applying OM to healthcare is not easy, why?
 Objective function is a mystery  challenging to define a clear and measurable objective,
such as balancing cost, quality, and patient outcomes.
 Lack of interest, support, and knowledge on the part of health care managers  managers
often prioritize immediate clinical needs over operational improvements.
 Not related to direct clinical care and disease research  operational issues are seen as
secondary compared to patient care and medical advancements.
 State of health care information system and data  many systems are outdated, fragmented,
or lack the necessary data integration for analysis
 Financial model does not reward efficiency
 Healthcare is different than industry  the unpredictable and patient-centered nature of
healthcare makes standard industrial approaches less applicable.

Differences between manufacturers and service organizations
 Services:  Manufacturers:
o Intangible product o Tangible product
o Product cannot be inventoried o Product can be inventoried
o High customer contact o Low customer contact
o Short response time o Longer response time
o Labor intensive o Capital intensive

Similarities service and manufacturers
 All use technology
 Both have quality, productivity, & response issues
 All must forecast demand
 Each will have capacity, layout, and location issues
 All have customers and suppliers
 All have scheduling and staffing issues

Healthcare: a business unlike all others
 Financial model does not reward efficiency
 Patients are customer and product at the same time
 Patients cannot be refused
 Interventions cannot be preempted
 More variability than in any other industry
 Many different types of care providers
 Different types of hospitals, different strategies
 Academic hospitals do almost everything


2

,  Specialized clinics
 Multiple decision makers (doctors  managers)
 Stakeholders often have conflicting goals

“Het kan écht: betere zorg voor minder geld”
Logistical improvements go hand-in-hand with quality improvements: patients that have to visit the
hospital less often, have shorter waiting times, and may count on more attention from nurses and
physicians.
Logistical quality improvements will yield some 3 to 3.5 billion EUR: almost a quarter of the entire
hospital budget…
In other words: improved care for less money!

Ongoing changes in the Netherlands
 Hiring OM experts from industry
 OM education of healthcare managers
 Introduction of regulated market mechanisms
 Process reorganization (clinical pathways: to standardize care, improve outcomes and reduce
cost)
 Copying logistical paradigms from industry

Approaches for organizational improvement
 Top down  system design
 Bottom up  continuous improvement

Bottom-up improvement paradigms
Continuous improvement
 Example: Toyota

ConWip (Constant Work-In-Process)
Strive to a constant “optimal” workload
 reduces lead-time, improves quality
Advantages:
• Simple principles
• Simple control
• Process-wide orientation
Disadvantages:
• Unsuitable when there is much variability in the process ( waiting times)

Push vs. Pull vs. ConWip




3

, Clinical Pathways
Standardisation of work processes with protocols
 efficient, improved quality
 First focus on major patient categories
 Is often succeeded with dedicating capacity
Advantages:
 “Repetition” can lead to efficiency
 Rapid access for patients
Disadvantage:
 Blockage other patients

Benchmarking
Learning from your peers by comparison of performance
• In reality often “naming, shaming & blaming”
• Uniform definitions essential
• Routinely measuring performance allows you to
compare yourself with yourself in the past
• What is “performance”?
 The best practice in practice is not the best possible practice

TOC (= Theory of Constraints)
 Focus on the bottleneck improves the entire process
 Focus on non-bottleneck is wasted time
 Note:
• is about efficiency, not quality
• there is always a bottleneck
• position of bottleneck regularly changes
• focus is on one demarcated process

Total access
Planning is a weakness, do todays work today, strive for flexibility
• Organise on a walk-in basis, where possible
Advantages:
• Simple control
• No access time
Disadvantages:
• Possibly much waiting time
Can often not be realized cost-effectively

4

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