methodology for analyzing environmental quality indicators

Methodology for Analyzing Environmental Quality Indicators (EQIs)

in a Dynamic Operating Room Environment

Jennifer Wagner Ph.D., CIC Microbiologist, Infection Preventionist Prism Environmental Health and Safety, Inc. Managing Partner, OnSite-LLC

Damon G. Greeley PE, CEM, HFDP, CBCP, EDAC, CHFM President, Global Health Systems Inc. Managing Partner, OnSite-LLC

Research Team Dr. Troy Markel – Pediatric surgeon/Associate Professor- Indiana University Health Dr. Jennifer Wagner, Ph.D., CIC - Principal- Prism Environmental Damon G. Greeley -PE, CEM, HFDP, CBCP, EDAC, CHFM -Founder & Managing Partner -Global Health System Inc./ Onsite-LLC John Ostojic – Industrial Hygenist -Artec Environmental Monitoring Dr. Tom Gormley, Ph.D - Associate Professor -MTSU

Research Team and OnSite, LLC “Applying research to improve everyday healthcare”

- Independent evaluation of medical products & devices

- Technical and biological acceptance testing utilizing EQI methodologies adapted to the application

- Outbreak investigations - Surrogate services to in-house

hospital infection prevention departments

Research on the Costs and Benefits of Different Ventilation Rates in ORs

• Tested in 3 actual operating rooms

• Simulated surgical procedure

• Followed proper techniques for scrubbing and gowning

• As much like surgery as possible without patient

Energy Costs by Space Type Approximately 44,010 Operating Rooms in the United States. 33,750 are in hospitals and 10,260 are freestanding surgical centers. (Source: CDC 2004, Lodestone & Frost & Sullivan.)

Factors Relating to Patients Acquiring an Infection During Stay or Procedure per NIH

1. Aerosol and droplet transmission dynamics

2. The nature of the dust levels

3. The health and condition of individuals naso-pharyngeal mucosal linings

4. Population density

5. Ventilation rate 6. Air distribution pattern

7. Humidity and temperature

8. Number of susceptibles

9. Length of exposure

10. Number of infected people producing contaminated aerosols

11. Infectious particle settling rate

12. Lipid or non-lipid viral envelope or microorganism cell wall

13. Surrounding organic material 14. UV light or antiviral chemical exposure 15. Vitamin A & D levels 16. Microorganism resistance to antibiotic or

antiviral therapy 17. Type and degree of invasive procedure 18. Spatial considerations 19. Contact with a carrier 20. Persistence of pathogens within hosts 21. Immuno-epidemiology 22. Transmission resistance and role of host

genetic factors

Wide Range in Code and in Practice • 12 ACH allowed in Calif. with 100%

outside air

• 15 ACH prior to 2010 FGI – such as KY

• 20 ACH after 2010 FGI/ASHRAE – such as TN

• 20 - 25 ACH – common practice

• 30 - 40 ACH recommended in certain ORs*

*Source: ASHE

European Approach uses Air Changes Plus Particle and Microbiological Contamination which have Clean Room/ISO Standards NF –French, UNI-Italian, DIN –German and HTM -British

9

Developed Concept of Environmental Quality Indicators –EQIs

• Temperature

• Relative Humidity

• Air velocity at key points

• Particle counts

• Microbial contamination

• Air change or ventilation rates

• Pressure relationships

• Overall measurement of air quality

• Combines US and European healthcare requirements

• Draws from testing standards used for labs and computer chip manufacturing

Hypothesis & Air Change Rates Tested

• 5 ACH – typical setback level to save energy when not in use

• 15 ACH – 2006 Guidelines

• 20 ACH – 2010 Guidelines

• 25 ACH - commonly used in the industry and the current set point for all ORs in this study

Hypothesis: 20 ACH was cleaner than 15 and 25 ACH was cleaner than 20 ACH.

SSI rates in modern countries are similar in spite of different metrics for ventilation rates

• US 1.9%

• Europe 2.2%

• Germany 1.6%

• England 1.4%

• France 1.6 %

• Portugal 2.0%

• Developing Countries 11.8%

2.0

4.5

1.9 2.2 1.6 1.4 1.6

11.8

Portugal China United States Europe Germany England France Developing Countries

SSIs and Our Mock Surgical Procedure • Over 200,000 SSI per year in the US – NIH

• SSI 30+% of all HAI – Duke Study

• JAMA - Johns Hopkins Study 2013 for patients with an SSI compared to patients without

• Daily total charges $7493 vs $7924,

• Mean LOS 10.56 days vs 5.64 days

• 30-day readmission rate 51.94 vs 8.19 readmissions per 100 procedures

Surgical Site Infections

• SSIs are defined as infections occurring up to 30 days after surgery (1 year for implants) and affecting the incision or deep tissues at the operative site

• Owens, et al. J Hosp Inf 2008

• Surgical Site infections are prevalent and account for 14-17% of all hospital acquired infections

• Spagnolo, et al. J Prev Med and Hygiene, 2013

Definition of SSI


• Patients required significantly more outpatient visits, ER visits, radiology and blood tests, readmissions, and home health aide services

• Perencevich et al. Emerging Infectious Diseases, 2003

• In a single hospital system, over a two year period, SSI took up an additional 4694 bed days and accounted for over $3 million in lost revenue

• Jenks PJ, et al. J of Hosp Inf, 2014


• Sources of infection control in the operating room

• Structural features: Room design, surface finishes

• Ventilation

• Water-sterile versus at scrub sink

• Procedural and Behavioral Factors

• Patient and Personnel


• During surgical procedures, dust and microbes from textiles, skin and respiratory aerosols are released into the air

• Bacteria settling on the wound or instruments can result in surgical site infections

• Several studies have shown that fewer infections arise when (orthopedic) surgery is performed in operating rooms with ultra-clean air facilities

• Spagnolo, et al. J Prev Med and Hygiene, 2013

Planning our Mock Procedure

• In order to evaluate particles and microbes we needed several personnel and multiple instruments.

• We felt it would be unethical to expose patients to increased human and instrument traffic during their operations

• We therefore designed a mock procedure to mimic a dynamic operating room environment

• It kept things moving without review by any IRB

Mock Surgical Procedure

• Designed a 1 hour long mock procedure to mimic actual events in an OR

• Surgeons and Nurses utilized

• Sterile Gowning and Gloving

• Sterile instruments prepared by each institutions' standard practices

• Utilized steak to simulate the patient for Bovie electrocautery.

Mock Surgical Procedure

Clip from OR procedure • 2 min clip

OR Ventilation Systems Overview

Site

Concentrated Primary Diffuser Array/Unidirectional/2 low returns

ASHRAE 52.2 Room

Air Filtration, Normal ACH”

Room Temp & Relative Humidity, Pressure

Pressure Control Method Notes

A Yes/Yes/Yes MERV 17 (terminal)

27

Avg. 68.5 deg. F, < 60% RH, Positive Pressure

Automatically (BMS)

Controlled Room Air Flow Offset

15 ACPH, 0.0039 neg. pressure to sterile core

B No/Yes/Yes MERV 17 (terminal)

26

68 deg. F, < 60% RH, Positive Pressure

Direct Pressure Control of Static

Pressure Set point

C No/Yes/Yes MER 14 (central)

24

68 deg. F, < 60% RH, Positive Pressure

Manually Balanced Air Flow to Static Pressure Set

point

OR A OR B

OR C

OR Control Graphic – Site A

29

Surgery AHU Control Graphic – Site A

Testing Diagram – Particle & Microbial Data Points

• 9 particle sampling locations, 4 sizes - 0.3, 0.5, 1.0, and 5.0 micron

• 3 cycles of 9 points @ 2 min per point ~ 60 min

• 6 air sampling (microbial) locations, 3 in sterile field and 3 on the back table

• 8 cycles of 5:55 time per cycle ~ 60 min.

3 samples on surgical table in Sterile zone

Sterile zone

3 samples on back table outside sterile zone

Nurses station

Particle counts A-I

Stationary particle at return

Remains in sterile fieMoves around/in out

Circulating nurse

Back table RN

Surgeon Surgeon’s assistant

Second surgeon

Anesthesiologist

Scrub tech

Air Samplers at Sterile Field Bair Hugger to Simulate Patient’s Body Heat

Testing Diagram – Velocity & Temp Data

• 4 velocity & temperature recording locations, sterile field upper, sterile field lower, back table, and return grille

• Velocity & temp were recorded same as particles, every 2 minutes

• 1 to 2 video cameras

• 1 location for PAO (poly alpha olefin) injection for CFD particle modeling baseline

Velocity & temp #4 – Return Grille

Velocity & temp #2 – Surgical Table Lower

Velocity & temp #1 – Surgical Table

Upper

Velocity & temp #3 – Back Table PAO Aerosol

injection point for CFD particle baseline

Surgical Table

Air Samplers at Back Table Velocity & Temp Testing Device Locations

Particulate and Microbial Testing USP 797 & ISO Standard 14644-1

Count Time Count Time Count Time Count Time Count Time Count TimeISO Class 1 10 70.1 2 353.4ISO Class 2 100 7.1 24 35.3 10 70.1 4 176.7ISO Class 3 1000 1 237 3.5 102 6.9 35 17.7 8 88.4ISO Class 4 10000 1 2370 1 1020 1 362 1.8 83 8.5ISO Class 5 100000 1 23700 1 10200 1 3520 1 832 1 29 24ISO Class 6 1000000 1 237000 1 102000 1 35200 1 8320 1 293 2ISO Class 7 352000 1 83200 1 2930 1ISO Class 8 3520000 1 832000 1 29300 1ISO Class 9 35200000 1 8320000 1 293000 1Time based on a 1cfm (28.3 LPM) sample rate

ClassificationMaximum concentration limits (particles/M3 of air for particles equal to and greater than the considered sizes shown below.

0.1 0.2 uM 0.3 uM 0.5 uM 1.0 uM 5.0 uM

Note: ISO Classifications are a range by factors of 10.

Choosing Statistical Procedures for Numerical Benchmarking

• In most cases, the microbial and particle data did not meet, either the assumption of normality or the homogeneity of variances and therefore, the median and interquartile ranges were used to determine significance. For velocity data, the assumptions were met and means and standard deviations were used.

Two Independent Variables

Interval or Ratio Independent t-test

Dependent t-test

One-Way ANOVA

Repeated Measures ANOVA

Two -Factor ANOVA

Two-Factor ANOVA

Repeated Measures

Ordinal Mann-Whitney U Wilcoxon Kruskal-

Wallis Friedman

Nominal Chi-Square Chi-Square Chi-Square

Multiple Independent

Groups

Multiple Dependent

Groups

Factorial Designs

Independent Groups

Dependent Groups

Measurement Scale of the Dependent

Variable

One Independent VariableTwo Levels More than 2 Levels

Two Independent

Groups

Two Dependent

Groups

Source: University of Tennessee Knoxville

Particulate Data Summary Numerical Benchmarking an OR by ISO 14644-1

• ISO Classification by 0.5 µm particle size

15 ACH 20 ACH 25 ACH

9 Point Cycle 1

9 Point Cycle 2

9 Point Cycle 3

9 Point Cycle 1

9 Point Cycle 2

9 Point Cycle 3

9 Point Cycle 1

9 Point Cycle 2

9 Point Cycle 3

OR A Particles/ m3 **

5.03 21.06 10.57 2.72 25.8 2.62 3.1 21.54 4.14

ISO 8 8 8 7 8 7 7 8 8

OR B Particles/ m3 **

2.997 5.02 1.92 4.56 2.64 1.42 3.91 2.76 0.57

ISO 7 8 7 8 7 7 8 7 7

OR C Particles/ m3 **

9.91 11.90 12.83 8.35 11.52 10.1 12.87 15.32 17.23

ISO 8 8 8 8 8 8 8 8 8

** number x 105

Particulate Data Summary – OR A • Hypothesis; 20 ACH was cleaner than 15 and 25 ACH was cleaner than 20

ACH. Significant at p<0.05

15 ACH 20 ACH 20 ACH 25 ACH

Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)

P value Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)

P value

OR A 9 point grid (0.3mParticles/ m3)

599583.00 (3924632)

158954.00 (1848132)

0.06 158954.00 (1848132)

102394.00 (1683199)

0.60

9 point grid (0.5mParticles/ m3)

221065.00 (1025637)

85097.00 (656816)

0.07 85097.00 (656816)

56832.00 (604788)

0.58


90597.00 (316620)

44576.00 (224004)

0.08 44576.00 (224004)

30452.00 (209974)

0.59


3666.00 (2719)

2639.00 (2553)

0.17 2639.00 (2553)

2359.00 (2393)

0.27

Particulate Data Summary – OR B • Hypothesis; 20 ACH was cleaner than 15 and 25 ACH was cleaner than 20



Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)


*Mean (STD)

Median (IR)/

*Mean (STD)

P value

OR B 9 point grid (0.3mParticles/ m3)

238067.00 (564912)

134366.00 (403319)

0.03 134366.00 (403319)

86918.00 (227790)

0.11


105440.00 (171211)

85325.00 (100494)

0.11 85325.00 (100494)

49534.00 (94949)

0.08


45182.00 (54820)

45002.00 (47289)

0.26 45002.00 (47289)

26993.00 (40990)

0.07


2179.00 (1473)

1840.00 (1080)

0.02 1840.00 (1080)

1293.00 (1047)

0.01

Particulate Data Summary – OR C • Hypothesis; 20 ACH was cleaner than 15 and 25 ACH was cleaner than 20



Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)


*Mean (STD)

Median (IR)/

*Mean (STD)

P value

OR C 9 point grid (0.3mParticles/ m3)

11812313.00 (1054936)

11149499.00 (729238)

<0.001 11149499.00 (729238)

13612763.00 (736236)

<0.001


1084782.00 (292680)

912232.00 (216852)

<0.001 912232.00 (216852)

1419972.00 (270852)

<0.001


100735.00 (85552)

60645.00 (65590)

0.004 60645.00 (65590)

66463.00 (92657)

0.72


2979.00 (2126)

2239.00 (1633)

<0.001 2239.00 (1633)

2093.00 (2000)

0.97

Microbial Data Summary • ISO Classification by mean CFU/m3


Microbial Sterile Field

Microbial Back Table





OR A

Range* 1-18 24-98 1-10 16-51 1-8 10-31

ISO 8 8 8 8 7 8

OR B

Range* 28-104 16-164 14-41 10-24 7-27 7-199

ISO >8 >8 8 8 8 8

OR C

Range* 2-15 5-18 0-13 2-15 3-15 0-20

ISO 8 8 8 8 8 8

Microbial Data Summary 15 ACH 20 ACH 20 ACH 25 ACH

Median (IR)

Median (IR)

P value Median (IR)

Median (IR)

P value

OR A Back Table Microbial (CFU/m3)

39.00 (13)

27.00 (11)

0.004 27.00 (11)

22.00 (15)

0.04

Sterile Field

Microbial (CFU/m3)

7.50 (6)

3.00 (3)

0.006 3.00 (3)

3.00 (3)

0.84

OR B Back Table Microbial (CFU/m3)

34.50 (19)

16.00 (6)

<0.001 16.00 (6)

16.00 (7)

0.86

Sterile Field

Microbial (CFU/m3)

51.00 (24)

22.00 (12)

<0.001 22.00 (12)

16.00 (8)

<0.001

OR C Back Table Microbial (CFU/m3)

7.00 (5)

5.00 (4)

0.001 5.00 (4)

5.00 (5)

0.84

Sterile Field

Microbial (CFU/m3)

8.00 (6)

6.00 (4)

0.03 6.00 (4)

5.50 (5)

0.93

Microbial Data Summary

ISO 8

ISO 8 ISO 7

Sterile Field Microbial Comparison OR A Microbial Load CFU/m3 & P-Value

15 v 20 ACH P Value =

0.006

CFU per m3

Sterile Field Comparison

Site - ACH Range CFU

per m3

Mean CFU

per m3

OR A – 15 ACH 1-18 7.5

OR A – 20 ACH 1-10 3

OR A – 25 ACH 1-8 3

OR B – 15 ACH 28-104 51

OR B – 20 ACH 14-41 22

OR B – 25 ACH 7-27 16

OR C – 15 ACH 2-15 8

OR C – 20 ACH 0-13 6

OR C – 25 ACH 3-15 5.5


0.84

ISO >8

ISO 8 ISO 8


Sterile Field Microbial Comparison OR B Microbial Load CFU/m3 & P-Value


<0.001

20 v 25 ACH P Value = <0.001

ISO 8

ISO 8 ISO 8

Sterile Field Microbial Comparison OR C Microbial Load CFU/m3 & P-Value

15 v 20 ACH P Value = 0.03

20 v 25 ACH P Value = 0.93

Microbial & Velocity Data Summary 15 ACH 20 ACH 25 ACH BT SF BT SF BT SF Median

(IR)/ *Mean (STD)

Median (IR)/

*Mean (STD)

P val Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)

P val Median (IR)/

*Mean (STD)

Median (IR)/

*Mean (STD)

P val

OR A Microbial (CFU/m3)

39.00 (13)

7.50 (6)

<.001 27.00 (11)

3.00 (3)

<.001 22.00 (15)

3.00 (3)

<.001

Velocity (feet/min)

12.00 (7)

28.00 (28)

<.001 13.00 (8)

32.00 (10)

<.001 14.56* (8.336)

40.59* (13.580)

<.001

OR B Microbial (CFU/m3)

34.50 (19)

51.00 (24)

.004 16.00 (6)

22.00 (12)

.002 16.00 (7)

16.00 (8)

.33

Velocity (feet/min)

18.41* (6.755)

27.52* (6.351)

<.001 13.00 (12)

31.00 (6)

<.001 16.41* (11.050)

39.67* (12.746)

<.001

OR C Microbial (CFU/m3)

7.00 (5)

8.00 (6)

.94 5.00 (4)

6.00 (4)

.16 5.00 (5)

5.50 (5)

.41

Velocity (feet/min)

8.00 (7)

9.00 (12)

0.19 9.52* (5.345)

13.63* (7.318)

0.02 16.56* (9.982)

16.85* (10.014)

0.91

Site - ACH

BT Range CFU per m3

(ISO)

SF Range CFU per m3

(ISO)

0.5µ Particles/

m3

(ISO)

OR A – 5 ACH 44-750* (>8)

76-747* (>8)

145887 (7)

OR A – 15 ACH 24-98 (8)

1-18 (7)

503269 (8)

OR B – 5 ACH 76-99* (8)

16-164* (8)

190492 (7)

OR B – 15 ACH 77-122 (>8)

28-104 (8)

299729 (7)

OR C – 5 ACH 38-69* (8)

4-18* (8)

310697 (7)

OR B – 15 ACH 39-62 (8)

2-15 (8)

991457 (8)

Microbial & Particulate Loading at 5 ACH vs. 15 ACH

* 6 data points in lieu of 24

• Recorded particle and microbial data at setback air change rate

• Did not perform mock procedure during setback

• Compared microbial for SF and BT

• Compared particulate counts for last 9 points during setback to first 9 points of mock procedure (non invasive period)

Velocity Contour at Along the Surgery Table OR C

47

Ft/min ≥

• ACH 25, Supply Temperature: 65 ºF, Return Temperature: 66 ºF

48

Lower Supply Velocity (ft/min) Back Table Velocity (ft/min)

CFD Results

Experiment Results

+/- % Variance

CFD Results

Experiment Results

+/- % Variance

ACH 15

11.19 12.07 7.9 8.7 8.5 2.3

ACH 20

8.01 13.38 67 17.5 9.42 46

ACH 25

16.42 16.62 1.2 18.67 16.88 9.6

CFD & Experiment Comparison OR C Only

Cost Factors for 5 OR ACH/Year Reduction Site A, B, and C

• 20 ACH ~ 2,000 CFM • Electrical Energy - Fans, Pumps, Cooling • Thermal Energy – Preheat and reheat • Steam - Humidification • Utilization Hours:

• Cooling • Heating • Economizer • Dehumidification/Sub Cooling

9%

14% 6%

21%

50%

Cooling/Subcooling Heating Humificiation Fans

OR A City Thermal Climate Zone 5

10,068 - 5.0 ACH

$

OR B Campus Thermal Climate Zone 4

$

OR C Self Generated Thermal Climate Zone 4

$ 7,052 5,218

Operating Cost Savings Summary

Notes: 1. Formulas were validated by third party for custom utility incentive and

national healthcare engineering firm 2. Does not include water costs for humidification

- 5.0 ACH - 5.0 ACH

Conclusions • There were differences between the cleanliness of the environment at the

sterile field versus the back table.

• Level of cleanliness was dependent upon air filtering and air distribution

• USP 797 ISO 14644-1 Classification may not be specific enough to benchmark higher environmental quality indicating (EQI) OR environments

• Data ‘points’ to greater ACH rates did not consistently and significantly produce a cleaner environment (statistically significant less particles), in some cases it was even less clean

Moving Forward…. • Would further testing of the relationship between the sterile field and back

table be beneficial?

• What is an acceptable level of cleanliness? Are EQIs a better benchmark than ACH?

• Is room air distribution and velocities at certain locations more important than the number of ACH?

• Additional research opportunities?

methodology for analyzing environmental quality indicators

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