- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT01787175
VA Integrated Medication Manager (IMM)
Veterans Affairs Integrated Medication Manager
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
In an attempt to address problems patient non-compliance with quality goals barriers to access and integration of health information that impede achievement of treatment goals, the VA is developing a new approach to the electronic medical record. The VA is moving away from the paper-chart metaphor and towards an integrated representation of the patient's status and care process across time. One of the first steps in the development phase has been to explicitly relate patient conditions, therapies, and goals in the domain of pharmacotherapy. This is called Integrated Medication Management and draws on Hollnagel's Contextual Control Model. Providers will be able to plan care and create orders directly in the context of these explicit relationships. This application will be implemented nationwide through a web interface embedded within the existing Computerized Patient Record System (CPRS), the graphical user interface to VA Information Systems (VistA).
Aim 1: Identify cognitive components of providers' therapeutic decision making in the field.
Aim 2. Refine and evaluate the Integrated Medication Manager using simulation studies.
- Aim 2.a. Refine interfaces and logic of the Integrated Medication Manager.
- Aim 2.b. Compare the performance of the Integrated Medication Manager and usual CPRS.
All hypotheses (below) test the use of IMM versus usual electronic medical record (EMR).
- Speed of decision-making will be faster.
- Accuracy of data interpretation (clinical assessment) will be higher.
- Appropriateness of therapeutic plans will be higher.
- Efficiency of gathering information will be higher.
- Common ground measures will be higher.
- Appropriateness of therapeutic plans will be higher when relevant data is outside the usual time horizon.
- Appropriateness of therapeutic plans will be higher when complex associations among patient therapies and goals exist.
- Appropriateness of therapeutic plans will be no lower when relevant data is not captured by the displays of the IMM.
- Appropriateness of therapeutic plans will be higher when highly salient data is not germane to the most important problem.
- Appropriateness of therapeutic plans will be higher when cognitive load is high due to interruptions.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
Utah
-
Salt Lake City, Utah, United States, 84148
- VA SLC Health Care System
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Practiced in primary care for at least two years
- Third year residents with two years of residency in internal medicine or family practice
- Do not have to be currently practicing
Exclusion Criteria:
- None
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Health Services Research
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
---|---|
Experimental: Integrated Medication Manager
Experienced providers that participated in the EHR simulations.
Half of the providers were assigned to use the new Integrated Medication Manager (intervention) during the simulation.
The other half were assigned the VA's CPRS to use (standard EHR).
Providers were randomly assigned which system to use.
|
A theory based electronic health record.
Half of the provider participants were assigned the IMM to use.
The other half were assigned the VA's CPRS EHR to use for the simulation.
Providers were randomly assigned to a EHR to use.
Other Names:
|
No Intervention: Standard EHR
Experienced providers that participated in the EHR simulations.
Half of the providers were assigned to use the new Integrated Medication Manager (intervention) during the simulation.
The other half were assigned the VA's CPRS to use (standard EHR).
Providers were randomly assigned which system to use.
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Amount of Time to Complete Assessment and Plan
Time Frame: 10 minutes
|
Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan.
|
10 minutes
|
Accuracy of Written Assessment and Plan in Terms of Control and Status
Time Frame: 10 minutes
|
Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan.
The primary outcome evaluated participants' recommendations for treatment of patient conditions.
Participants reviewed a total of 10 patient cases and received a score between 0 and 3 points for each issue within each patient case.
The final score for each participant was a proportion between 0 and 1.
The proportion represented the sum of all points assigned to the participant, divided by the total number of points possible.
Higher values on the scale represent greater accuracy of the written assessment and plan.
|
10 minutes
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Identification of Planned Monitoring and Follow up Encounters in Assessment and Plan
Time Frame: 10 minutes
|
Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan. .
The secondary outcome evaluated participants' recommendation about future monitoring of patient conditions.
Participants reviewed a total of 10 patient cases and received a score of 0 or 1 point for each issue within each case.
The final score for each participant was a proportion between 0 and 1.
The proportion represented the sum of all points assigned to the participant, divided by the total number of points possible.
Higher values on the scale represent a greater proportion of appropriate monitoring recommendations made.
|
10 minutes
|
Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Principal Investigator: Jonathan Nebeker, MD, MS, University of Utah
Publications and helpful links
General Publications
- Phillips LS, Branch WT, Cook CB, Doyle JP, El-Kebbi IM, Gallina DL, Miller CD, Ziemer DC, Barnes CS. Clinical inertia. Ann Intern Med. 2001 Nov 6;135(9):825-34. doi: 10.7326/0003-4819-135-9-200111060-00012.
- Crosson JC, Stroebel C, Scott JG, Stello B, Crabtree BF. Implementing an electronic medical record in a family medicine practice: communication, decision making, and conflict. Ann Fam Med. 2005 Jul-Aug;3(4):307-11. doi: 10.1370/afm.326.
- Tinetti ME, Bogardus ST Jr, Agostini JV. Potential pitfalls of disease-specific guidelines for patients with multiple conditions. N Engl J Med. 2004 Dec 30;351(27):2870-4. doi: 10.1056/NEJMsb042458. No abstract available.
- Asch SM, McGlynn EA, Hogan MM, Hayward RA, Shekelle P, Rubenstein L, Keesey J, Adams J, Kerr EA. Comparison of quality of care for patients in the Veterans Health Administration and patients in a national sample. Ann Intern Med. 2004 Dec 21;141(12):938-45. doi: 10.7326/0003-4819-141-12-200412210-00010.
- Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005 Mar 9;293(10):1223-38. doi: 10.1001/jama.293.10.1223.
- Perlin JB, Pogach LM. Improving the outcomes of metabolic conditions: managing momentum to overcome clinical inertia. Ann Intern Med. 2006 Apr 4;144(7):525-7. doi: 10.7326/0003-4819-144-7-200604040-00012. No abstract available.
- Morris AH. Developing and implementing computerized protocols for standardization of clinical decisions. Ann Intern Med. 2000 Mar 7;132(5):373-83. doi: 10.7326/0003-4819-132-5-200003070-00007.
- Fox J, Alabassi A, Black E, Hurt C, Rose T. Modelling clinical goals: a corpus of examples and a tentative ontology. Stud Health Technol Inform. 2004;101:31-45.
- Xiao Y, Hunter WA, Mackenzie CF, Jefferies NJ, Horst RL. Task complexity in emergency medical care and its implications for team coordination. LOTAS Group. Level One Trauma Anesthesia Simulation. Hum Factors. 1996 Dec;38(4):636-45. doi: 10.1518/001872096778827206.
- Nebeker JR, Hurdle JF, Bair BD. Future history: medical informatics in geriatrics. J Gerontol A Biol Sci Med Sci. 2003 Sep;58(9):M820-5. doi: 10.1093/gerona/58.9.m820.
- Hayward RA, Asch SM, Hogan MM, Hofer TP, Kerr EA. Sins of omission: getting too little medical care may be the greatest threat to patient safety. J Gen Intern Med. 2005 Aug;20(8):686-91. doi: 10.1111/j.1525-1497.2005.0152.x.
- Shekelle PG. Invited commentary: Implementation of health information technology: an important but challenging field of inquiry. Proc (Bayl Univ Med Cent). 2006 Oct;19(4):313. doi: 10.1080/08998280.2006.11928190. No abstract available.
- Weir CR, Nebeker JJ, Hicken BL, Campo R, Drews F, Lebar B. A cognitive task analysis of information management strategies in a computerized provider order entry environment. J Am Med Inform Assoc. 2007 Jan-Feb;14(1):65-75. doi: 10.1197/jamia.M2231. Epub 2006 Oct 26.
- Berg CA, Strough JN, Calderone KS, Sansone C, Weir C. The role of problem definitions in understanding age and context effects on strategies for solving everyday problems. Psychol Aging. 1998 Mar;13(1):29-44. doi: 10.1037//0882-7974.13.1.29.
- Weir CR. Linking information needs with evaluation: the role of task identification. Proc AMIA Symp. 1998:310-4.
- Taatz H. [The problem of the time factor in orthodontic treatment]. Stomatol DDR. 1976 Feb;26(2):102-5. No abstract available. German.
- Campbell M, Grimshaw J, Steen N. Sample size calculations for cluster randomised trials. Changing Professional Practice in Europe Group (EU BIOMED II Concerted Action). J Health Serv Res Policy. 2000 Jan;5(1):12-6. doi: 10.1177/135581960000500105.
- Miller RH, Sim I. Physicians' use of electronic medical records: barriers and solutions. Health Aff (Millwood). 2004 Mar-Apr;23(2):116-26. doi: 10.1377/hlthaff.23.2.116.
- Bradley EH, Bogardus ST Jr, Tinetti ME, Inouye SK. Goal-setting in clinical medicine. Soc Sci Med. 1999 Jul;49(2):267-78. doi: 10.1016/s0277-9536(99)00107-0.
Study record dates
Study Major Dates
Study Start
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimate)
Study Record Updates
Last Update Posted (Estimate)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Other Study ID Numbers
- 5R18HS017186-03 (U.S. AHRQ Grant/Contract)
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Electronic Health Records
-
University Hospital, GrenobleUnknown
-
Weill Medical College of Cornell UniversityThe Commonwealth Fund; New York State Department of Health; Taconic Health Information... and other collaboratorsCompletedElectronic Health Records | Quality of Health CareUnited States
-
University of North Carolina, Chapel HillMayo Clinic; National Library of Medicine (NLM); University of Pittsburgh Medical... and other collaboratorsRecruitingCritical Care | Usability | Electronic Health Records | Information Seeking BehaviorUnited States
-
Parkview Hospital, IndianaAbbott Medical DevicesCompletedPatient Participation | Electronic Health Records | Implantable Cardioverter-Defibrillator | Health Information ExchangeUnited States
-
University of Toronto Practice Based Research NetworkUniversity of Manitoba; University of British Columbia; Canadian Institutes of... and other collaboratorsEnrolling by invitationAged | Primary Health Care | Polypharmacy | Quality Improvement | Inappropriate Prescribing | Electronic Health RecordsCanada
-
Ohio State UniversityCompletedOutpatient | Physician-Patient Relations | Inpatient Facility Diagnoses | Electronic Health RecordsUnited States
-
VA Office of Research and DevelopmentCompletedElectronic Medical RecordsUnited States
-
University of California, San FranciscoCompletedChronic Disease | Health Literacy | Electronic Health Records
-
St George Hospital, AustraliaNational Health and Medical Research Council, Australia; The University of... and other collaboratorsUnknownPersonal Health Records | Chronic Medical Conditions | Electronic Medical RecordAustralia
-
Columbia UniversityAgency for Healthcare Research and Quality (AHRQ)RecruitingMedical Errors | Electronic Medical RecordsUnited States
Clinical Trials on Integrated Medication Manager
-
Duke UniversityAgency for Healthcare Research and Quality (AHRQ); Northern Piedmont Carolina... and other collaboratorsCompletedMyocardial Ischemia | Heart Failure | Stroke | Hypertension | Diabetes Mellitus | AsthmaUnited States
-
University of UtahHitachi, Ltd.CompletedDiabetes Mellitus, Type 2 | Diabetes MellitusUnited States
-
US Department of Veterans AffairsCompleted
-
National Institute of Allergy and Infectious Diseases...CompletedHIV InfectionsUnited States
-
University Health Network, TorontoCanadian Institutes of Health Research (CIHR)CompletedHypertension | Renal Insufficiency, Chronic | Mobile Applications | Medication ReconciliationCanada
-
Brigham and Women's HospitalHarvard Risk Management FoundationCompletedHealthy | Medical Record Systems, ComputerizedUnited States
-
Children's Hospital Medical Center, CincinnatiRecruiting
-
Afyonkarahisar Health Sciences UniversityThe Scientific and Technological Research Council of Turkey; Afyonkarahisar...CompletedVentilator Associated Pneumonia | Mechanical Ventilation Complication | Nursing Caries | Aspiration, RespiratoryTurkey
-
University of WashingtonDuke University; University of New MexicoCompletedChronic PainUnited States
-
Johns Hopkins UniversityRobert Wood Johnson FoundationCompletedHypertension | Type 2 Diabetes | Preterm Delivery | Gestational DiabetesUnited States