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Venous Thromboembolism (VTE) Prevention in the Hospital Greg Maynard MD, MSc Clinical Professor of Medicine and Chief, Division of Hospital Medicine University.

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Presentation on theme: "Venous Thromboembolism (VTE) Prevention in the Hospital Greg Maynard MD, MSc Clinical Professor of Medicine and Chief, Division of Hospital Medicine University."— Presentation transcript:

1 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

2 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, post- thrombotic syndrome, chronic PAH) Surgeon General’s Call to Action to Prevent DVT and PE 2008 DHHS

3 Risk Factors for VTE Stasis Age > 40 Immobility CHF Stroke Paralysis Spinal Cord injury Hyperviscosity Polycythemia Severe COPD Anesthesia Obesity Varicose Veins Hypercoagulability 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.

4 Risk Factors for VTE Stasis Age > 40 Immobility CHF Stroke Paralysis Spinal Cord injury Hyperviscosity Polycythemia Severe COPD Anesthesia Obesity Varicose Veins Hypercoagulability 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. Bick RL & Kaplan H. Med Clin North Am 1998;82:409. Most hospitalized patients have at least one risk factor for VTE

5 Failure to Do Simple Things Well Wash Hands – 60% Reliable Patients Understand Meds / Problems – 40% Reliable Central Lines Placed w/ Proper Technique – 60% Reliable Basal Insulin for Inpt Uncontrolled DM – 40% Reliable VTE Prophylaxis – 50% Reliable

6 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: Monreal M, et al. J Thromb Haemost 2004;2: Tapson V, et al. Blood 2004;104:11. Abstract #1762.

7 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.

8 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.

9 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

10 E-Alerts Can Increase Prophylaxis 2506 hospitalized patients VTE risk score ≥ 4 Randomized to intervention or control Intervention Treatment Received Mechanical, %Pharmacologic, % E-Alert Control1.513 P-value0.001 Kucher N, et al. N Engl J Med. 2005;352:

11 Intervention Control Time (days) % Freedom from DVT/ PE E-Alerts Decrease VTE Kucher N, et al. N Engl J Med. 2005;352: Intervention Control Number at risk % P = 0.001

12 Effectiveness can wane over time Lecumberri R, et al. Thromb Haemost. 2008;100: *P < 0.05 *

13 Human Alerts Increase Prophylaxis 2493 hospitalized patients VTE risk score ≥ 4 Randomized to intervention or control Intervention Treatment Received Mechanical, %Pharmacologic, % Hu-Alert2128 Control814 95% CI Piazza G, et al. Circulation. 2009;119:

14 % Freedom from DVT/ PE Human Alerts Decrease VTE Time After Initial Enrollment (days) P = 0.31 Piazza G, et al. Circulation. 2009;119:

15 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

16 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, DeCaire K, Friedrich Jan. Medical Admission Order Sets to Improve Deep Vein Thrombosis Prophylaxis Rates and Other Outcomes. J Hosp Med 2009

17 …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!

18 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

19 19 Baseline Consensus building Order Set Implementation & Adjustment Real time ID & intervention Baseline Consensus building Order Set Implementation & Adjustment Real time ID & intervention N = 2,944 mean 82 audits / month UCSD experience

20 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

21 21 Level 5 Oversights identified and addressed in real time 95+%

22 Dr. Maynard, the CIs are different here and in the proof. Which are correct? Maynard GA, et al. J Hosp Med. 2009; Hospital Acquired VTE by Year Patients at Risk9,7209,92311,207 Cases w/ any VTE Risk for HA VTE1 in 761 in 731 in 122 Unadjusted RR # (95% CI)( )( ) Cases with PE Risk for PE1 in 4631 in 4511 in 747 Unadjusted RR (95% CI)( )( ) Cases with DVT (and no PE) Risk for DVT1 in 881 in 851 in 146 Unadjusted RR * (95% CI)( )( ) Cases w/ Preventable VTE44217 Risk for Preventable VTE1 in 2211 in 4731 in 1,601 Unadjusted RR #0.14* (95% CI)( )( ) # p < 0.01 *p <

23 VTE Prevention Guides Modeling a Multifaceted Approach

24 VTE QI Resource Room

25 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

26 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

27 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

28 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):381S-453S

29 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)

30 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.

31 Hierarchy of Reliability No protocol* (“State of Nature”) 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) (by other QI / high reliability strategies) Oversights identified and addressed in real time Level Predicted Prophylaxis rate 40% 50% 65-85% 90% 95+% * Protocol = standardized decision support, nested within an order set, i.e. what/when

32 The Essential First Intervention 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 / efficiency 32 VTE Protocol

33 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

34 34 Is your order set in a competition?

35 Too Little Guidance Prompt ≠ Protocol DVT PROPHYLAXIS ORDERS  Anti thromboembolism Stockings  Sequential Compression Devices  UFH 5000 units SubQ q 12 hours  UFH 5000 units SubQ q 8 hours  LMWH (Enoxaparin) 40 mg SubQ q day  LMWH (Enoxaparin) 30 mg SubQ q 12 hours  No Prophylaxis, Ambulate

36 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

37 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 (5000 units q 12 h if > 75 or weight <50 kg) LMWH Enox 40 mg q day Other LMWH CONSIDER add IPC Enox 30 mg q 12 h or Enox 40 q day or Other LMWH or Fondaparinux 2.5 mg q day or Warfarin INR 2-3 AND MUST HAVE IPC 37 IPC needed if contraindication to AC exists Example from UCSD Keep it Simple – A “3 bucket” model

38 Paper Version – “3 Bucket” RAM DVT Prophylaxis Order Set Module See separate paper version demonstrating 3 bucket model

39 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

40 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

41 Hierarchy of Reliability No protocol* (“State of Nature”) 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) (by other QI / high reliability strategies) Oversights identified and addressed in real time Level Predicted Prophylaxis rate 40% 50% 65-85% 90% 95+% * Protocol = standardized decision support, nested within an order set, i.e. what/when

42 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 Measure-vention

43 Map to Reach Level % 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!

44 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”

45 45 Effect of Situational Awareness on Prevalence of VTE Prophylaxis by Nursing Unit Hospital A, 1 st Nursing Unit Baseline Post-Intervention UCL: 93% 104% Mean: 73% 99 % (p < 0.01) LCL: 53% 93% Hospital A, 2 nd Nursing Unit Baseline Post-Intervention UCL: 90% 102% Mean: 68% 87% (p < 0.01) LCL: 46% 72% Hospital B, 1 st Nursing Unit Baseline Post-Intervention UCL: 89% 108% Mean: 71% 98% (p < 0.01) LCL: 53% 88%_______________________ UCL = Upper Control Limit LCL = Lower Control Limit Hospital Days Intervention

46 Most Common Mistakes in Measurement of DVT Prophylaxis Not doing it at all Not doing it concurrently Failure to make measured poor performance actionable

47 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 VTE- risk 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

48 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: /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 Rockville, MD: Agency for Healthcare Research and Quality. August 2008, last accessed September 15, 2008 at 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) Maynard G, Stein J. Designing and Implementing Effective VTE Prevention Protocols: Lessons from Collaboratives. J Thromb Thrombolysis DOI /s published online Nov 10, 2009


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