1. Professor, Department of Anesthesiology
From “Solution Shop” to “Focused Factory ” in Cardiothoracic Surgery
David J. Cook, M.D.
Professor, Department of Anesthesiology
Mayo Clinic College of Medicine Center for the Science of Healthcare Delivery
Has no relevant financial relationships to disclose.
Will not be discussing off-label/investigative use(s) of commercial devices.

2. Case Study: The Medicare Gap in CVS
Reduce cost per case by 20%
Operational analysis:
Stakeholder analysis 2

3. CV Surgical Care Model:
“Who’s patient is this?”

4. CV Surgical Care Model:
“Who’s patient is this?”

5. Unwarranted variation (total variable costs):
Daily matching
demand and capacity
ICU length of stay (routine)
Surgical Hours
Duration UCI

6. Christensen HBS: Typology of Business Models:
example
Payment model
Solution Shop
Unstructured problems, undifferentiated complexity, expertise and intuition
Consulting, architecture, law, medicine
Fee for service
Value-adding Process (VAP) (via Focused Factory)
Process application increases value,
manage product (output)
Refining,
Manufacturing,
Healthcare (surgicenter, imaging, lab facilities)
Pay for outcome FFS
Facilitated network
Manages exchanges: services, data or information
Cable services, insurance, banking
Membership, subscription, transaction fees

7. Solution Shop Model: Unstructured problem:
Decision making by ‘expert” Unique knowledge, training
Experience and intuition

8. Value-Adding Process Model:
Solution Shop Model:
Value-Adding Process Model:
Create a standardized, protocol-based pathway across care geographies (Focused Factory)
Support delivery via communication, information-systems, geography
Empower bedside providers and shift decision-making

9. Product and Process Specifications
Informed/empowered bedside provider
UCO
Ambulation
Chest tubes out
Pacer wires out
Anesthetic management Hemodynamic Drips
Blood Component Therapy
Antibiotics
Wean mechanical ventilation Fluid management
Wean hemodynamic support
Remove “lines”

11. Process: Urinary Catheter Out (UCO)
Cook, Thompson et al., Am Journal of Medical Quality Aug, 2013

12. Resource Utilization: ICU Length of Stay
Vertical histograms showing distribution for duration of ICU length of stay control (2008-upper panel) and intervention (2012- lower panel) groups (n = 769 for each group). Median and mean values as well as 95% confidence intervals are shown below respective panels.
Cook, Pulido et al. Annals of Surgery Dec. 2014

13. UHC: Total Variance from Predicted LOS (DRG’s 216 – 221)
2008
2012

15. In-Hospital Safety: Variable§ Pre (2008) (N=769) Post (2012) P-value*
Initial ventilation duration (h) †
Re-intubated
Initial ICU length of stay (h)
Readmission to the ICU
9.3 (6.2, 14.5)
5 (1%)
26.3 (23.6, 44.3)
19 (3%)
6.3 (4.7, 9.2)
1 (0%)
22.5 (20.0, 25.8)
18 (2%)
<.001
0.22
1.0
* P-values are from rank-sum tests for continuous variables and Fisher’s exact tests for categorical variables.
†There were 14 missing values for initial ventilation duration.
§ Values are n (%) for categorical variables and median (q1, q2) for continuous variables.
Cook, Pulido et al. Ann Surg December 2014

16. * * * * 14-15% reduction In cost
Cook, et al. Health Affairs: May2014 * *
14-15% reduction
In cost * *
Distribution of costs pre- and post-implementation of focus factory model is shown. The red line of in each box indicates the median cost; the lower and upper border of the boxes show the 25th and 75th percentiles of the cost distribution, while the stars (*) indicates the outliers. (n=769 per group).

17. Process metrics → Outcome Metrics
Cook, et al. Health Affairs: May2014
Process metrics → Outcome Metrics

18. Cook, et al. Health Affairs: May2014
COST
2012 data

19. Observations/Conclusions:
Health care delivery provides a product as a result of a process (business model)
Complexity and unwarranted variation drive poorer outcomes and higher cost
Specifications can be established for both process and product → Predictability

20. Cost/Complexity Distribution in Populations:
Very different practice (business) models
Implications for: decision model (expert or algorithm) work model practice improvement normative data on process, outcome and cost

21. Learning Objectives:
By the end of this session, participants should be able to:
Understand the origins of unwarranted variations in surgical care
Understand means to reduce unwarranted variations
Understand the implications of the distribution of cost and care complexity for populations of surgical patients