Top

Published in:

Open Access 01-12-2007 | Original Article

Applying Systems Engineering Principles in Improving Health Care Delivery

Authors: Renata Kopach-Konrad, MSc, Mark Lawley, PhD, Mike Criswell, MSN, RN, CCNS, Imran Hasan, MSc, Santanu Chakraborty, MSc, Joseph Pekny, PhD, Bradley N. Doebbeling, MD, MSc

Published in: Journal of General Internal Medicine | Special Issue 3/2007

Abstract

Background

In a highly publicized joint report, the National Academy of Engineering and the Institute of Medicine recently recommended the systematic application of systems engineering approaches for reforming our health care delivery system. For this to happen, medical professionals and managers need to understand and appreciate the power that systems engineering concepts and tools can bring to redesigning and improving health care environments and practices.

Objective

To present and discuss fundamental concepts and tools of systems engineering and important parallels between systems engineering, health services, and implementation research as it pertains to the care of complex patients.

Design

An exploratory, qualitative review of systems engineering concepts and overview of ongoing applications of these concepts in the areas of hemodialysis, radiation therapy, and patient flow modeling.

Results

In this paper, we describe systems engineering as the process of identifying the system of interest, choosing appropriate performance measures, selecting the best modeling tool, studying model properties and behavior under a variety of scenarios, and making design and operational decisions for implementation.

Conclusions

We discuss challenges and opportunities for bringing people with systems engineering skills into health care.

Starfield B. Deficiencies in US medical care. JAMA. 2000;284(17):2184–5.PubMedCrossRef

McGlynn E, Asch S, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348(26):2635–45.PubMedCrossRef

American College of Physicians. The Advanced Medical Home: a Patient-centered, Physician-guided Model of Health Care. United States: American College of Physicians Monograph; 2005.

Kohn L, Corrigan J, Donaldson M. To Err is Human Building a Safer Health System Committee on Quality of Health Care in America. Washington DC: Institute of Medicine National Academy Press; 1999.

Murphy J, Chang H, Montgomery J, Rogers W, Safran D. The quality of physician–patient relationships: patients experiences, 1996–1999. J Fam Pract. 2001;50:123–9.PubMed

Wu S, Green A. A Projection of Chronic Illness Prevalence and Cost Inflation. Santa Monica, Calif: RAND Health; 2000.

Proctor P, Compton WD, Grossman J, Fanjiang G. Building a Better Delivery System: a New Engineering/Health Care Partnership, Committee on Engineering and the Health Care System. Washington DC: National Academy of Engineering and Institute of Medicine, National Academy Press; 2005.

Kossiakoff A, Sweet W. Systems Engineering Principles and Practice. New York: Wiley; 2003.

Kerzner H. Project Management: A Systems Approach to Planning, Scheduling, and Controlling, 8th edn. New Jersey: Wiley; 2003.

10.

Endress A, Aydeniz B, Wallwiener D, Kurek R. The critical path method to analyze and modify OR-workflow: integration of an image documentation system. Minim Invasive Ther Allied Technol. 2006;15(3):177–86PubMedCrossRef

11.

Park C. Fundamentals of Engineering Economics. New Jersey: Prentice-Hall; 2003.

12.

Neftci S. Principles of Financial Engineering. New York: Academic Press; 2004.

13.

Steenstra I, Anema J, van Tulder M, Bongers P, de Vet H, van Mechelen W. Economic evaluation of a multi-stage return to work program for workers on sick-leave due to low back pain. J Occup Rehabil. 2006;16(4):557–78.PubMedCrossRef

14.

Ross S. Introductory Statistics, 2nd edn. New York: Academic Press; 2005.

15.

Montgomery D. Design and Analysis of Experiments, 6th edn. New Jersey: Wiley; 2004.

16.

Montgomery D, Peck E, Vining G. Introduction to Linear Regression Analysis, 3rd edn. New Jersey: Wiley-Interscience; 2001.

17.

Parachoor S, Rosow E, Enderle A. Knowledge management system for benchmarking performance indicators using statistical process control (SPC) and virtual instrumentation (VI). Biomed Sci Instrum. 2003;39:175–8.PubMed

18.

Durrett R. Essentials of Stochastic Processes. New York: Springer; 2001.

19.

Hauskrecht M, Fraser H. Planning treatment of ischemic heart disease with partially observable Markov decision processes. Artif Intell Med. 2000;18(3):221–44. MarPubMedCrossRef

20.

Rardin R. Optimization in Operations Research. New Jersey: Prentice-Hall; 1997.

21.

Brennan P, Ferris M, Robinson S, Wright S, Marquard J. Modeling participation in the NHII: operations research approach. AMIA Annu Symp Proc. 2005;76–80.

22.

Lehto M, Buck J, Buck M. Introduction to Human Factors and Ergonomics for Engineers. Hillsdale, NJ: Lawrence Erlbaum Associates; 2007.

23.

Koubek R, Benysh D, Buck M, Harvey C, Reynolds M. The development of a theoretic framework and design tool for process usability assessment. Ergonomics 2003;46(1–3):220–41.PubMedCrossRef

24.

vanderAalst W, vanHee K. Workflow Management: Models, Methods, and Systems. Cambridge, Mass: The MIT Press; 2004.

25.

Gupta D, Natarajan M, Gafni A, Wang L, Shilton D, Holder D, Yusuf S. Capacity planning for cardiac catheterization: a case study. Health Policy. 2007;82(1):1–11.PubMedCrossRef

26.

Law A, Kelton D. Simulation Modeling and Analysis, 3rd edn. London: McGraw-Hill; 1999.

27.

Kelton D, Sadowski R, Sturrock D. Simulation with Arena, 4th edn. London: McGraw-Hill; 2007.

28.

Hung G, Whitehouse S, O’Neill C, Gray A, Kissoon N. Computer modeling of patient flow in a pediatric emergency department using discrete event simulation. Pediatr Emerg Care 2007;23(1):5–10.PubMedCrossRef

29.

Brandeau M, Sainfort F, Pierskalla W, eds. Handbook of Operations Research/Management Science Applications in Health Care. Dordrecht: Kluwer Academic Publishers; 2004.

30.

Sullivan KL, Besarab A, Bonn J, Shapiro MJ, Gardiner GA, Moritz MJ.Hemodynamics of Failing Dialysis Grafts. J Radiol. 1993;186(3):867–72.

31.

Kaye M, Baird C, McCloskey B, Oscar G, D’Avirro M. Two years sequential hemodynamic data on polytetrafluoroethylene (PTFE) grafts used for hemodialysis. Proc Eur Dial Transplant Assoc. 1979;16:266–71PubMed

32.

Alagoz O, Maillart L, Schaefer A, Roberts, M. Determining the acceptance of cadaveric livers using an implicit model of the waiting list. Oper Res. 2007;55(1):24–36.CrossRef

33.

Alagoz O, Maillart L, Schaefer A, Roberts M. The optimal timing of living-donor liver transplantation. Manage Sci. 2004;50(10):1420–30.CrossRef

34.

Schaefer A, Bailey M, Shechter S, Roberts M. Medical decisions using Markov decision processes. In: Sainfort F, Brandeau M, Pierskalla W, eds. Handbook of Operations Research/Management Science Applications in Health Care. Dordrecht: Kluwer Academic Publishers, 2004;597–616.

35.

Shepard D, Ferris C, Olivera G, Mackie T. Optimizing the delivery of radiation therapy to cancer patients. SIAM Rev. 1999;41(4):721–44.CrossRef

36.

Rardin R, Preciado-Walters F, Langer F, Thai V. Column generation for IMRT cancer therapy optimization with implementable segments. Ann Oper Res. 2006;148(1):65–79.CrossRef

37.

Rardin R, Preciado-Walters F, Langer F, Thai V. A coupled column generation, mixed-integer approach to optimal planning of intensity modulated radiation therapy for cancer. Math Program. 2004;101:319–38.

38.

Su X, Zenios S. Patient choice in kidney allocation: a sequential stochastic assignment model. Oper Res. 2005;53(3):443–55.CrossRef

39.

Jeffrey A, Xia X, Craig I. When to initiate HIV therapy: a control theoretic approach. IEEE Trans Biomed Eng. 2003;50(11):1213–20.PubMedCrossRef

40.

Pardalos P, Chaovalitwongse W, Iasemidis L, et al. Seizure warning algorithm based on optimization and nonlinear dynamics. Math Program Ser B. 2004;101:365–85.CrossRef

41.

Wu J, Wein L, Perelson A. Optimization of influenza vaccine selection. Oper Res. 2005;53(3):456–76.CrossRef

42.

Peterson J. Petri Net Theory and the Modeling of Systems. New Jersey: Prentice-Hall; 1981.

43.

Haas P. Stochastic Petri Nets Modeling, Stability, Simulation. New York: Springer; 2002.

44.

American National Standards Institute. HL7 Version 3 Normative Edition, Health Level Seven. United States: American National Standards Institute; 2006.

45.

Cooperrider D, Whitney D. Appreciative Inquiry. San Francisco, CA: Berrett-Koehler Communications; 1999.

46.

Goldstein M, Coleman R, Tu S, et al.Translating research into practice: sociotechnical integration of automated decision support for hypertension in three medical centers. J Am Med Inform Assoc. 2004;11(5):368–76.PubMedCrossRef

Title: Applying Systems Engineering Principles in Improving Health Care Delivery
Authors: Renata Kopach-Konrad, MSc
Mark Lawley, PhD
Mike Criswell, MSN, RN, CCNS
Imran Hasan, MSc
Santanu Chakraborty, MSc
Joseph Pekny, PhD
Bradley N. Doebbeling, MD, MSc
Publication date: 01-12-2007
Publisher: Springer-Verlag
Published in: Journal of General Internal Medicine / Issue Special Issue 3/2007
Print ISSN: 0884-8734
Electronic ISSN: 1525-1497
DOI: https://doi.org/10.1007/s11606-007-0292-3

ACC 2024 Congress Coverage

Heart Failure Video

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Applying Systems Engineering Principles in Improving Health Care Delivery

Abstract

Background

Objective

Design

Results

Conclusions

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Objective

Design

Results

Conclusions

Please log in to get access to this content

Other articles of this Special Issue 3/2007

Managing Patient and System Complexities to Improve the Quality and Outcomes of Chronic Care

The Challenges of Multimorbidity from the Patient Perspective

Studying Complexity is Complex

Patient Complexity: More Than Comorbidity. The Vector Model of Complexity

Patients with Complex Chronic Diseases: Perspectives on Supporting Self-Management

What is the Business Case for Improving Care for Patients with Complex Conditions?

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page