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Problem Statement and introduction
  
==Process and Prioritization==Improving Ambulatory Office Workflow, Efficiency and Reducing Prescribing Error Through the Use of E-Prescribing CPOE.
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===Scope of Problem ===
  
Background:  “The current system of prescribing and dispensing medications in the United States has widespread problems with safety and efficiency”.(3) Yet drug therapy is an integral component of many ambulatory treatment regimens recommended for chronic and acute medical conditions. Americans made 906.5 million outpatient visits in 2000(1) and half of the US population takes one prescription daily, with one in six taking three or more a day.(2) This includes 3.27 billion prescriptions and more than 10% of the national health spending.(2) In the Crossing the Quality Chasm article, The Institute of Medicine challenged us to create a new system that is safe, effective, patient-centered, timely, efficient and equitable. Our current ambulatory prescribing and dispensing systems do not meet those criteria. There appears to be one glaring weak link; inadequate implementation of ambulatory computerized patient ordering entry (ACPOE) systems for medications. i.e. electronic prescribing (eRx).  
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Published reports suggest that antibiotic susceptibility mismatch (ASM) is a significant problem. Buising and colleagues[1] noted that in a population of adult ICU patients, 14.3% of sterile and 30.8% of non-sterile isolates were treated inadequately initially, 4.0% of sterile and 21.3% of non-sterile isolates were treated inadequately after identification, and narrower-spectrum therapy was available for 30% of patients after microbe identification. In addition, Paterson et al[2] reported that 52% of mismatches occurred in patients who previously received a drug that was shown to be inadequate against the infecting organism, 30% of patients had a prior history of a drug’s ineffectiveness against an organism, and 62.5% of mismatches occurred in patients staying 14 days or longer (i.e., intensive care unit patients, cancer patients). These reports indicate that there are clear patterns and risk factors that describe ASM. Therefore, the process of identification and intervention for ASM is a particularly well-suited target for ongoing quality improvement efforts, which could identify workflow causes or process failures that promote ASM.
  
To the patient the prescriptive process seems quite simple. They are given a written prescription, take it to the pharmacy (or mail it in), pay the allotted amount due, receive and consume the medications. In all reality there is a complex and convoluted system that manages the drug industry’s transactions including the retail or mail order pharmacy, pharmacy benefit manager, payer, manufacture, wholesaler as well as technology venders for transaction networks, clinical information databases and software. This is further complicated by a serpentine economic trail of rebates and incentives. From the point a person turns in their prescription to when they pick it up, the processes are all electronic and have proven effective managing 3.27 billion prescriptions a year! Yet this process currently starts with a paper prescription process greater than 85% of the time.(1) This is the “weak link” where the majority of ambulatory medication errors occur. Converting the prescribing process from paper to an electronic process is often referred to as the “final mile” for ambulatory electronic medication management.(2).
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===Impact===
  
Because of the immense potential seen for ePrescibing to reduce errors and cost, Medicare Prescription Drug, Improvement, and Modernization Act (MMA) of 2003 was passed requiring the ePrescribing process adhere to specific standards.(3,4) Subsequently President Bush has called for linking reimbursement rendered for medical services covered by government sponsored plans to ePrescribing. A 2007 report issued by the Health and Human Services suggested that “electronic prescribing is still in its infancy” however the findings are encouraging. Although there is still work to be done implementing the remaining standards, the report encourages “interested stakeholders to fully adopt and implement electronic prescribing in order to reap its many potential benefits”.(3)
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Published research reviewed in developing the guideline reported various improvements in antimicrobial use and patient outcomes, among them: a) a 22% to 36% decrease in antimicrobial use through more efficient prescribing practice and use of less expensive alternatives; b) savings of $200,000 to $900,000 in direct drug costs (savings dependent on institution size); c) short-term susceptibilities among gram-negative pathogens (e.g., Klebsiella); d) reduced use of broad-spectrum antimicrobials by 34% to 84%; and e) modification of 25% of antimicrobial orders, with prescription of narrower-spectrum drugs in 47% of these cases.[3]
  
Errors in the medication process include prescribing, transcribing, dispensing, consuming and monitoring. Estimates suggest there are 8.8 million ambulatory adverse drug events (ADE) a year, of which 2.1 million are preventable and 130,000 are life threatening.(3) Preventable prescribing and transcribing errors include illegible written prescriptions, incorrect dosing, drug/allergy, drug/drug and drug/condition errors. Estimates vary on just how many of these ADE would be averted depending significantly on the software functionalities and human factors.(1)
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===Setting===
  
Unfortunately making a business case for implementation of health information technology in an independent primary care office has been difficult. The vast majority of the savings from ePrescribe go to the purchasers and payers of health services, not the physician.(1,3). Physicians will, however, migrate to eRx when they perceive the benefit to their practice outweigh the costs. The primary physician office benefits and costs are in the financial, productivity, service and hassle areas. It is anticipated that as eRx systems are able to meet these needs, adoption will increase.
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A large metropolitan children's hospital
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Aim: Our mission is to improve the office workflow efficiency and safety within the ambulatory prescription process of a primary care office within six months.
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Goals:
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===Aim===
• Reduce total telephone calls by 25%
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• Reduce drug/allergy prescribing errors to zero
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• Increase patient satisfaction to medication refill times by 50%
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• Develop and implement a staff satisfaction survey tool
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These address the efficiency, safety, and patient-centered goals of the IOM quality improvement initiative.
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==Intervention==
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To reduce the use of ineffective antibiotics for documented infections
PDSA 1
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Plan Flowcharting of current office workflow and proposed reengineering of rx refill protocol for improved safety and efficiency by initiating refill at the pharmacy, where electronic processing will pick up ADE's and formulary issues, moniter all phone calls for baseline using phone records
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===Specific Goal===
  
Do  Implement reengineered rx protocol
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To reduce the incidence of antibiotic susceptibility mismatches (ASM) for documented infections in urine and bloodstream through active surveillance of culture results and antibiotic use
  
Study Moniter phone calls with reengineered method and plot phone calls on p chart
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==Process and Prioritization==
  
Act Institute reengineered SOP for rx refills in preparation for e-prescribing by physicians
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===Process Affected===
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The process of selection of antibiotics at various stages of microbiology reporting will be affected.
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Measure(s):  ASMs per week and average length of stay during the 26 weeks before and the 26 weeks after implementation of an antibiotic audit and feedback intervention
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==Intervention==
  
PDSA 2
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=== Plan ===
Plan Reiterate above PDSA '''using e-prescribing''', and in addition, moniter cancelled rx using e-pharmacy software(assuming cancelled rx are due to averted ADE's or formulary issues)
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Do Implement e-prescribing
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Antimicrobial stewardship programs and guidelines for the appropriate use of antibiotics are reviewed and compared with the hospital's current ASM rate.
  
Study  Moniter phone call and cancelled rx and plot on p chart
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=== Do ===
  
Act Institute e-rx in practice, and expand, if successful, if not, repeat PDSA with a reengineered method.
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The ASM rate is monitored for 26 weeks without action. The hospital begins flagging ASMs in lab results for a second 26-week so physicians can change antibiotic orders. Average length of stay (LOS) in the hospital for patients receiving antibiotics is monitored through both 26-week periods.
  
==Reference==
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=== Study ===
  
Be sure to reference your work.
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The investigators study the ASM and LOS data to identify underlying cause(s) of failure to recognize and/or act on ASMs.
  
1. http://www.qualitytools.ahrq.gov/qualityreport/download/download_report.aspx
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=== Act ===
  
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The hospital implements additional intervention(s) such as electronic alerts and one-to-one physician counseling to further reduce the ASM rate and, potentially, the average LOS.
  
BIBLIOGRAPHY
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== References ==
The following websites were accessed for information and references:
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www.ahrg.gov
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www.ihi.gov
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www.mpro.org/doquit
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www.ncbi.nlm.nih.gov (pubmed)
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# Buising KL, Thursky KA, Bak N, Skull S, Street A, Presneill JJ, Cades JF, Brown GV. Antibiotic prescribing in response to bacterial isolates in the intensive care unit. Anaesth Intensive Care. 2005 Oct;33(5):571-7.
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# Paterson DL, McKinnon J, Ndirangu M, Capitano B, Potoski B, Linden PK. Why do doctors give microbiologically inadequate empiric therapy to critically ill patients? Abstr Intersci Conf Antimicrob Agents Chemother. 2003 Sep 14-17; 43:abstract no. K-1419.
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# Dellit TH, Owens RC, McGowan JE Jr, Gerding DN, Weinstein RA, Burke JP, Huskins WC, Paterson DL, Fishman NO, Carpenter CF, Brennan PJ, Billeter M, Hooton TM, Infectious Diseases Society of America; Society for Healthcare Epidemiology of America. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis. 2007 Jan 15;44(2):159-77. Epub 2006 Dec 13.
  
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Return to [[Quality Informatics]]
  
1. Johnston,DS,Pan,E,Walker,J,Bates,DW, Middleton,B, Patient Safety in the Physician’s Office: Assessing the Value of Ambulatory CPOE, I-Health Reports April,2004.
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[[category:BMI537-F-07]]
2. Sarasohn-Kahn, J., Holt, M, The Prescription Infrastructure: Are We Ready for ePrescribing? I-Health Reports, January,2006.
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3. Findings From The Evaluation of E-Prescribing Pilot Sites; AHQR Publication No. 07-0047-EF, April, 2007
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4. Johnson,KB,Fitzhenry,F, Case Report:Activity Diagrams for Integrating e_Prescribing Tools into Clinical Workflow, JAMIA 13(4) 2006: 391-96.
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5. Papshev,D,Peterson,AM, Electronic Prescribing in Ambulatory Practice:Promises,Pitfalls, and Potential Solutions, AmJManagCare 7(7)2001: 725-36.
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6. Bell,DS,Friedman,MA, E-Prescribing and the Medicare Modernization Act of 2003, Health Affairs 24(5) 2005: 1159-69.
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7. Wang,CJ,Marken,RS,Meili,RC,Straus,JB,Landman,AB,Bell,DS, Functional Characteristics of Commercial Ambulatory Prescribing Systems: A Field Study,
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JAMIA 12(3) 2005: 346-56.
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      8.  Tamblyn,R, et al, The Development and Evaluation of an Integrated Electronic                                         
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            Prescribing and Drug Management System for Primary Care, JAMIA  13(1):
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            148-59.
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9.  Gandhi,TK, Weingart,SN,Seger,AC, et al, Outpatient Prescribing Errors and the
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Impact of Computerized Prescribing, J Gen Int Med 20()  2005: 837-41.
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10. West,DR,Westfall,JM et al, Using Reported Primary Care Errors to Develop and
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Implement Patient Safety Interventions: A Report from the ASIPS Collaborative,
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Advances in Patient Safety Vol 3.
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11.  Feifer,RA,Nevins,LM,McGuigan,KA,Paul,L, Lee,J, Mail-Order Prescriptions   
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Requiring Clarification Contact with the Prescriber:Prevalence, Reasons, and Implications, JMCP 9(4) 2003: 346-52.
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Latest revision as of 18:59, 6 December 2011

Problem Statement and introduction

Scope of Problem

Published reports suggest that antibiotic susceptibility mismatch (ASM) is a significant problem. Buising and colleagues[1] noted that in a population of adult ICU patients, 14.3% of sterile and 30.8% of non-sterile isolates were treated inadequately initially, 4.0% of sterile and 21.3% of non-sterile isolates were treated inadequately after identification, and narrower-spectrum therapy was available for 30% of patients after microbe identification. In addition, Paterson et al[2] reported that 52% of mismatches occurred in patients who previously received a drug that was shown to be inadequate against the infecting organism, 30% of patients had a prior history of a drug’s ineffectiveness against an organism, and 62.5% of mismatches occurred in patients staying 14 days or longer (i.e., intensive care unit patients, cancer patients). These reports indicate that there are clear patterns and risk factors that describe ASM. Therefore, the process of identification and intervention for ASM is a particularly well-suited target for ongoing quality improvement efforts, which could identify workflow causes or process failures that promote ASM.

Impact

Published research reviewed in developing the guideline reported various improvements in antimicrobial use and patient outcomes, among them: a) a 22% to 36% decrease in antimicrobial use through more efficient prescribing practice and use of less expensive alternatives; b) savings of $200,000 to $900,000 in direct drug costs (savings dependent on institution size); c) short-term susceptibilities among gram-negative pathogens (e.g., Klebsiella); d) reduced use of broad-spectrum antimicrobials by 34% to 84%; and e) modification of 25% of antimicrobial orders, with prescription of narrower-spectrum drugs in 47% of these cases.[3]

Setting

A large metropolitan children's hospital

Aim

To reduce the use of ineffective antibiotics for documented infections

Specific Goal

To reduce the incidence of antibiotic susceptibility mismatches (ASM) for documented infections in urine and bloodstream through active surveillance of culture results and antibiotic use

Process and Prioritization

Process Affected

The process of selection of antibiotics at various stages of microbiology reporting will be affected.

Measure(s): ASMs per week and average length of stay during the 26 weeks before and the 26 weeks after implementation of an antibiotic audit and feedback intervention

Intervention

Plan

Antimicrobial stewardship programs and guidelines for the appropriate use of antibiotics are reviewed and compared with the hospital's current ASM rate.

Do

The ASM rate is monitored for 26 weeks without action. The hospital begins flagging ASMs in lab results for a second 26-week so physicians can change antibiotic orders. Average length of stay (LOS) in the hospital for patients receiving antibiotics is monitored through both 26-week periods.

Study

The investigators study the ASM and LOS data to identify underlying cause(s) of failure to recognize and/or act on ASMs.

Act

The hospital implements additional intervention(s) such as electronic alerts and one-to-one physician counseling to further reduce the ASM rate and, potentially, the average LOS.

References

  1. Buising KL, Thursky KA, Bak N, Skull S, Street A, Presneill JJ, Cades JF, Brown GV. Antibiotic prescribing in response to bacterial isolates in the intensive care unit. Anaesth Intensive Care. 2005 Oct;33(5):571-7.
  2. Paterson DL, McKinnon J, Ndirangu M, Capitano B, Potoski B, Linden PK. Why do doctors give microbiologically inadequate empiric therapy to critically ill patients? Abstr Intersci Conf Antimicrob Agents Chemother. 2003 Sep 14-17; 43:abstract no. K-1419.
  3. Dellit TH, Owens RC, McGowan JE Jr, Gerding DN, Weinstein RA, Burke JP, Huskins WC, Paterson DL, Fishman NO, Carpenter CF, Brennan PJ, Billeter M, Hooton TM, Infectious Diseases Society of America; Society for Healthcare Epidemiology of America. Infectious Diseases Society of America and the Society for Healthcare Epidemiology of America guidelines for developing an institutional program to enhance antimicrobial stewardship. Clin Infect Dis. 2007 Jan 15;44(2):159-77. Epub 2006 Dec 13.

Return to Quality Informatics