Venous Thromboembolism (VTE) Prevention in the Hospital Greg Maynard MD, MSc Clinical Professor of Medicine and Chief, Division of Hospital Medicine University of California, San Diego
VTE: A Major Source of Mortality and Morbidity • • 350, 000 to 650, 000 with VTE per year 100, 000 to > 200, 000 deaths per year Most are hospital related. VTE is primary cause of fatality in half– More than HIV, MVAs, Breast CA combined – Equals 1 jumbo jet crash / day • 10% of hospital deaths – May be the #1 preventable cause • Huge costs and morbidity (recurrence, postthrombotic syndrome, chronic PAH) Surgeon General’s Call to Action to Prevent DVT and PE 2008 DHHS
Risk Factors for VTE Stasis Hypercoagulability Age > 40 Immobility CHF Stroke Paralysis Spinal Cord injury Hyperviscosity Polycythemia Severe COPD Anesthesia Obesity Varicose Veins Cancer High estrogen states Inflammatory Bowel Nephrotic Syndrome Sepsis Smoking Pregnancy Thrombophilia Endothelial Damage Surgery Prior VTE Central lines Trauma Anderson FA Jr. & Wheeler HB. Clin Chest Med 1995; 16: 235. Anderson FA Jr. & Wheeler HB. Clin Med 1995; 16: 235.
Risk Factors for VTE ve ha E ts Endothelial Stasis Hypercoagulability VT ien r Damage at fo Age > 40 Cancer p Surgery Immobility High estrogen statestor ed ac Prior VTE liz f CHF Inflammatory Bowel a it isk Central lines p Stroke Nephrotic Syndrome Trauma os ne r Paralysis t h Sepsis to Spinal Cord s o a. Smoking s M le Pregnancy injury Hyperviscosity at Thrombophilia Polycythemia Severe COPD Anesthesia Obesity Varicose Veins Anderson FA Jr. & Wheeler HB. Clin Chest Med 1995; 16: 235. Anderson FA Jr. & Wheeler HB. Clin Med 1995; 16: 235. Bick RL & Kaplan H. Med Clin North Am 1998; 82: 409. Med 1998; 82: 409. Bick RL & Kaplan H. Am
Failure to Do Simple Things Well • Wash Hands – • Patients Understand Meds / Problems – • 40% Reliable Central Lines Placed w/ Proper Technique – • 60% Reliable Basal Insulin for Inpt Uncontrolled DM – • 60% Reliable 40% Reliable VTE Prophylaxis – 50% Reliable
Registry Data Highlight the Underuse of Thromboprophylaxis DVT-FREE RIETE IMPROVE BAD NEWS! Only a minority of hospitalized patients receive thromboprophylaxis Goldhaber SZ, Tapson VF. Am J Cardiol 2004; 93: 259 -62. Monreal M, et al. J Thromb Haemost 2004; 2: 1892 -8. Tapson V, et al. Blood 2004; 104: 11. Abstract #1762.
Endorse Results • Out of ~70, 000 patients in 358 hospitals, appropriate prophylaxis was administered in: – 58. 5% of surgical patients – 39. 5% of medical patients Cohen, Tapson, Bergmann, et al. Venous thromboembolism risk and prophylaxis in the acute hospital care setting (ENDORSE study): a multinational cross-sectional study. Lancet 2008; 371: 387– 94.
The “Stick” is coming…. NQF endorses measures already Public reporting and TJC measures coming soon: - Prophylaxis in place within 24 hours of admit or risk assessment / contraindication justifying it’s absence - Same for critical care unit admit / transfers - Track preventable VTE CMS – DVT or PE with knee or hip replacement reimbursed as though complication had not occurred.
Why don’t we do better? • Lack of awareness or buy in of guidelines • Underestimation of clot risk, overestimation of bleeding risk • Lack of validated risk assessment model • Translating complicated guidelines into everyday practice is difficult
E-Alerts Can Increase Prophylaxis • 2506 hospitalized patients • VTE risk score ≥ 4 • Randomized to intervention or control Intervention Treatment Received Mechanical, % Pharmacologic, % E-Alert 10 23. 6 Control 1. 5 13 P-value 0. 001 Kucher N, et al. N Engl J Med. 2005; 352: 969 -977.
E-Alerts Decrease VTE % Freedom from DVT/ PE 100 98 Intervention 96 94 92 Control 90 0 30 60 90 Time (days) Number at risk Intervention 1255 977 900 853 Control 1251 976 893 839 Kucher N, et al. N Engl J Med. 2005; 352: 969 -977. 41% P = 0. 001
Effectiveness can wane over time *P < 0. 05 * Lecumberri R, et al. Thromb Haemost. 2008; 100: 699 -704.
Human Alerts Increase Prophylaxis • 2493 hospitalized patients • VTE risk score ≥ 4 • Randomized to intervention or control Intervention Treatment Received Mechanical, % Pharmacologic, % Hu-Alert 21 28 Control 8 14 95% CI 10. 6 -16. 0 10. 5 -16. 8 Piazza G, et al. Circulation. 2009; 119: 2196 -2201.
% Freedom from DVT/ PE Human Alerts Decrease VTE P = 0. 31 Time After Initial Enrollment (days) Piazza G, et al. Circulation. 2009; 119: 2196 -2201.
Bottom Line - Alerts • • A Useful Strategy E – Alerts and Human Alerts can work Not a panacea Alert fatigue can be a problem • Need a multifaceted approach
Medical Admission Order Sets Can Improve DVT Prophylaxis……… Baseline- Only 11% of inpatients on any VTE prophylaxis Intervention – A simple prompt for UFH or Mechanical Prophylaxis placed into voluntary admission order sets. Post intervention: 44% on any prophylaxis 26% pharmacologic prophylaxis O'Connor C, Adhikari N, De. Caire K, Friedrich Jan. Medical Admission Order Sets to Improve Deep Vein Thrombosis Prophylaxis Rates and Other Outcomes. J Hosp Med 2009
…but not enough by themselves, and design of the order set matters • Best practice prophylaxis not defined Prompt ≠ Protocol • No protocol = No guidance at the point of care in order set, heparin, mechanical devices, and no prophylaxis presented as equal choices • Implementation / Reliability At 15 months, only about half of inpatient admissions utilized standardized order set. Other methods needed to enhance performance!
Education alone is not sufficient …. but it is essential to optimize other strategies that are effective • • • Standardized order sets Computerized decision support E-alerts Human alerts Raising situational awareness Audit and feedback
UCSD experience N = 2, 944 mean 82 audits / month Order Set Implementation & Adjustment Baseline Real time ID & intervention Consensus building 19
UCSD VTE Protocol Validated • Easy to use, on direct observation – a few seconds • Inter-observer agreement – – 150 patients, 5 observers- Kappa 0. 8 and 0. 9 • Predictive of VTE • Implementation = high levels of VTE prophylaxis – From 50% to sustained 98% adequate prophylaxis – Rates determined by over 2, 900 random sample audits • Safe – no discernible increase in HIT or bleeding • Effective – 40% reduction in HA VTE – 86% reduction in risk of preventable VTE
Level 5 Oversights identified and addressed in real time 95+% 21
Hospital Acquired VTE by Year 2005 2006 2007 2008 9, 720 9, 923 11, 207 Cases w/ any VTE Risk for HA VTE Unadjusted RR (95% CI) 131 1 in 76 1. 0 138 1 in 73 1. 03 (0. 81 -1. 31) 92 1 in 122 0. 61# (0. 47 - 0. 79) Cases with PE Risk for PE Unadjusted RR (95% CI) 21 1 in 463 1. 0 22 1 in 451 1. 02 (0. 54 -1. 86) 15 1 in 747 0. 62 (0. 32 -1. 20) 116 1 in 85 1. 03 (0. 80 -1. 33) 77 1 in 146 0. 61* (0. 45 -0. 81) 68 21 1 in 473 0. 47# (0. 28 -0. 79) 7 1 in 1, 601 0. 14* (0. 06 -0. 31) 6 Cases with DVT (and no PE) Risk for DVT Unadjusted RR (95% CI) 110 1 in 88 1. 0 Cases w/ Preventable VTE Risk for Preventable VTE Unadjusted RR (95% CI) 44 1 in 221 1. 0 Dr. Maynard, the CIs are different here and in the proof. Which are correct? Patients at Risk # p < 0. 01 *p < 0. 001 Maynard GA, et al. J Hosp Med. 2009; 80 12
VTE Prevention Guides Modeling a Multifaceted Approach http: //www. hospitalmedicine. org/Resource. Room. Redesign/RR_VTE/VTE_Home. cfm http: //ahrq. hhs. gov/qual/vtguide/
VTE QI Resource Room www. hospitalmedicine. org
Collaborative Efforts • • • SHM VTE Prevention Collaborative I - 25 sites SHM / VA Pilot Group - 6 sites SHM / Cerner Pilot Group – 6 sites AHRQ / QIO (NY, IL, IA) - 60 sites IHI Expedition for VTE Prevention – 60 sites • Effective across wide variety of settings – Paper and Computerized / Electronic – Small and large institutions – Academic and community
Basic Ingredients for Success • Institutional support, will to standardize the process • Designated multidisciplinary team with physician leadership • Specific goals and metrics • VTE Protocol guidance built into order sets • Education / consensus • Alerts / feedback to clinicians in real time
Enlist Key Groups / Leaders • Section Heads • Hospitalists – (most groups receive some direct support from the hospital) • Other high volume providers • Find some more physician champions
Educational Detailing - PR Quote ACCP 8 Guidelines Don’t use aspirin alone for DVT prophylaxis Mechanical prophylaxis is not first line prophylaxis in the absence of contraindications to pharmacologic prophylaxis Geerts WH et al. Chest. 2008; 133(6 Suppl): 381 S-453 S
Use the powerful anecdote and data • Look for VTE case that could have been prevented • Personalize the story • Enlist a patient / family to help you tell the story • Get data on VTE in your medical center – (it occurs more often than the doctors think it does)
Q and A Q. What is the best VTE risk assessment model? A. Simple, text based model with only 2 -3 layers of VTE Risk Q. Who should do the VTE risk assessment? A. Doctors (via admit transfer order sets), with back up risk assessment by front line nurses or pharmacists, focusing on those without prophylaxis.
Hierarchy of Reliability Predicted Prophylaxis rate Level 1 No protocol* (“State of Nature”) 40% 2 Decision support exists but not linked to order writing, or prompts within orders but no decision support Protocol well-integrated (into orders at point-of-care) Protocol enhanced (by other QI / high reliability strategies) Oversights identified and addressed in real time 50% 3 4 5 65 -85% 90% 95+% * Protocol = standardized decision support, nested within an order set, i. e. what/when
The Essential First Intervention VTE Protocol 1) a standardized VTE risk assessment, linked to… 2) a menu of appropriate prophylaxis options, plus… 3) a list of contraindications to pharmacologic VTE prophylaxis Challenges: Make it easy to use (“automatic”) Make sure it captures almost all patients Trade-off between guidance and ease of use /32 efficiency
Map to Reach Level 3 Implementing an Effective VTE Prevention Protocol • Examine existing admit, transfer, periop order sets with reference to VTE prophylaxis. • Design a protocol-driven DVT prophylaxis order set (w/ integrated risk assessment model [RAM]) • Vette / Pilot – PDSA • Educate / consensus building • Place new standardized DVT order set ‘module’ into all pertinent admit, transfer, periop order sets. • Monitor, tweak - PDSA
Is your order set in a competition? 34
Too Little Guidance Prompt ≠ Protocol DVT PROPHYLAXIS ORDERS q Anti thromboembolism Stockings q q q Sequential Compression Devices UFH 5000 units Sub. Q q 12 hours UFH 5000 units Sub. Q q 8 hours LMWH (Enoxaparin) 40 mg Sub. Q q day LMWH (Enoxaparin) 30 mg Sub. Q q 12 hours No Prophylaxis, Ambulate
No Math! Critiques of VTE Risk Assessment Model using point scoring techniques • Point based systems – low inter-observer agreement in real use – users stop adding up points – too large to be modular (collects dust) – point scoring is arbitrary – never validated
Example from UCSD Keep it Simple – A “ 3 bucket” model Low Medium High Ambulatory with no other risk factors. Same day or minor surgery CHF COPD / Pneumonia Most Medical Patients Most Gen Surg Patients Everybody Else Elective LE arthroplasty Hip/pelvic fx Acute SCI w/ paresis Multiple major trauma Abd / pelvic CA surgery Early ambulation UFH 5000 units q 8 h Enox 30 mg q 12 h or Enox 40 q day or Other LMWH or (5000 units q 12 h if > 75 or weight <50 kg) LMWH Enox 40 mg q day Other LMWH CONSIDER add IPC Fondaparinux 2. 5 mg q day or Warfarin INR 2 -3 AND MUST HAVE IPC 37 IPC needed if contraindication to AC exists
Paper Version – “ 3 Bucket” RAM DVT Prophylaxis Order Set Module See separate paper version demonstrating 3 bucket model
Integrate order set as a module • Make order set even more portable • Incorporate module into current heavily used order sets Or Strip out VTE orders from popular order sets and refer to the standardized orders Clip orders to all admit / transfer orders
Most Common Mistakes in VTE Prevention Orders • Point based risk assessment model • Improper Balance of guidance / ease of use – Too little guidance - prompt ≠ protocol – Too much guidance- collects dust, too long • • • Failure to revise old order sets Too many categories of risk Allowing non-pharm prophy too much Failure to pilot, revise, monitor Linkage between risk level and prophy choices are separated in time or space
Hierarchy of Reliability Predicted Prophylaxis rate Level 1 No protocol* (“State of Nature”) 40% 2 Decision support exists but not linked to order writing, or prompts within orders but no decision support Protocol well-integrated (into orders at point-of-care) Protocol enhanced (by other QI / high reliability strategies) Oversights identified and addressed in real time 50% 3 4 5 65 -85% 90% 95+% * Protocol = standardized decision support, nested within an order set, i. e. what/when
Measure-vention Daily measurement drives concurrent intervention (i. e. same as Level 5 in Hierarchy of Reliability) Identify patients not receiving VTE prophylaxis in real time 1) Suitable for ongoing assessment, reporting to governing body Archive-able data (!) 2) Can be used for real time intervention Actionable data (!) 42
Map to Reach Level 5 95+ % prophylaxis • Use MAR or Automated Reports to Classify all patients on the Unit as being in one of three zones: GREEN ZONE - on anticoagulation YELLOW ZONE - on mechanical prophylaxis only RED ZONE – on no prophylaxis Act to move patients out of the RED!
Situational Awareness and Measure-vention: Getting to Level 5 • Identify patients on no anticoagulation • Empower nurses to place SCDs in patients on no prophylaxis as standing order (if no contraindications) • Contact MD if no anticoagulant in place and no obvious contraindication – Templated note, text page, etc • Need Administration to back up these interventions and make it clear that docs can not “shoot the messenger”
Effect of Situational Awareness on Prevalence of VTE Prophylaxis by Nursing Unit Hospital A, 1 st Nursing Unit Intervention UCL: Baseline 93% Mean: 73% LCL: 53% Post-Intervention 104% 99% (p < 0. 01) 93% Hospital Days Hospital A, 2 nd Nursing Unit UCL: Baseline 90% Mean: 68% LCL: Intervention 46% Post-Intervention 102% 87% (p < 0. 01) 72% Hospital B, 1 st Nursing Unit UCL: Baseline 89% Mean: 71% LCL: 53% Post-Intervention 108% 98% (p < 0. 01) 88% Intervention ____________ UCL = Upper Control Limit LCL = Lower Control Limit 45
Most Common Mistakes in Measurement of DVT Prophylaxis • Not doing it at all • Not doing it concurrently • Failure to make measured poor performance actionable
Key Points - Recommendations • • QI building blocks should be used Multifaceted approach is needed VTE protocols embedded in order sets Simple risk stratification schema, based on VTErisk groups (3 levels of risk should do it) • Institution-wide if possible (a few carve outs ok) • Local modification is OK – Details in gray areas not that important • Use measure-vention to accelerate improvement 47
Maynard G, Morris T, Jenkins I, Stone S, Lee J, Renvall M, Fink E, Schoenhaus R (2009) Optimizing prevention of hospital acquired venous thromboembolism: prospective validation of a VTE risk assessment model. J Hosp Med 4(7). doi: 10. 1002/jhm. 562 Maynard G, Stein J. Preventing Hospital-Acquired Venous Thromboembolism: A Guide for Effective Quality Improvement. Prepared by the Society of Hospital Medicine. AHRQ Publication No. 08 -0075. Rockville, MD: Agency for Healthcare Research and Quality. August 2008, last accessed September 15, 2008 at http: //www. ahrq. gov/qual/vtguide/. Maynard G, Stein J. Preventing Hospital-Acquired Venous Thromboembolism: A Guide for Effective Quality Improvement, version 3. 3. Society of Hospital Medicine supplement The Hospitalist August 2008, Vol 12 (8) 1 -40. Maynard G, Stein J. Designing and Implementing Effective VTE Prevention Protocols: Lessons from Collaboratives. J Thrombolysis DOI 10. 1007/s 11239 -009 -0405 -4 published online Nov 10, 2009
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