Electronic Health RecordsIMMNCT01787175
VA Integrated Medication Manager
A study testing Integrated Medication Manager in people with Electronic Health Records, run by University of Utah at 1 site in United States.
Trial summary
The purpose of this study is to advance the science of healthcare informatics and to improve medication management through the development of a new approach to the electronic medical record called the Integrated Medication Manager (IMM). Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Electronic Health Records
- What is being tested?
- Integrated Medication Manager
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 58 participants
- Where
- 1 siteUnited States
- Study dates
- Oct 2007to Mar 2011
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- 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
Who cannot join
- None
Trial locations and contacts
1 site in 1 country.
United States1 site
VA SLC Health Care System
Salt Lake City, Utah, 84148
About this study
Official title: Veterans Affairs Integrated Medication Manager
The purpose of this study is to advance the science of healthcare informatics and to improve medication management through the development of a new approach to the electronic medical record called the Integrated Medication Manager (IMM).
Read the 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.
- Conditions
- Electronic Health Records
- Being tested
- Integrated Medication Manager
- Keywords
- Medication Therapy Management, Clinical Decision Support Systems, Medical Informatics, Patient Care Management, United States Department of Veterans Affairs
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Integrated Medication ManagerOther
Also called IMM
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.
| Study group | Role | What they receive |
|---|---|---|
| Integrated Medication Manager | Experimental | 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. Receives: Other: Integrated Medication Manager |
| Standard EHR | No intervention | 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 being measured
The primary outcome is the main question the study is designed to answer.
Amount of Time to Complete Assessment and Plan
Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan.
Measured: 10 minutes
Accuracy of Written Assessment and Plan in Terms of Control and Status
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.
Measured: 10 minutes
Secondary outcomes (1)
Identification of Planned Monitoring and Follow up Encounters in Assessment and Plan
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.
Measured: 10 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Feb 2013 (estimated)
- Study startOct 2007
- Primary completionMar 2011
- Study completionMar 2011
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (19)Papers the sponsor has linked to this study.
- Other trials for Electronic Health RecordsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 58 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Utah
- Sponsor type
- University, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Responsible party
- Sponsor
- Investigators
- Jonathan Nebeker, MD, MS, Principal investigator, University of Utah
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT01787175
- Sponsor's protocol ID
- 5R18HS017186-03
- Acronym
- IMM
- Status last verified
- May 2016
- First submitted
- 22 Jan 2013
- Last updated
- 23 Jun 2016
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
Publications
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.
PubMed 15611491Perlin 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.
PubMed 16585667Morris 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.
PubMed 10691588Fox 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.
PubMed 15537204Xiao 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.
PubMed 8976626Phillips 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.
PubMed 11694107Nebeker 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.
PubMed 14528038Crosson 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.
PubMed 16046562Hayward 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.
PubMed 16050875Tinetti 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.
PubMed 15625341Garg 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.
PubMed 15755945Shekelle 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.
PubMed 17106490Weir 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.
PubMed 17068345Berg 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.
PubMed 9533188Weir CR. Linking information needs with evaluation: the role of task identification. Proc AMIA Symp. 1998:310-4.
PubMed 9929232
Study at a glance
From the registry record, last updated by the sponsor on 23 Jun 2016. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Veterans Affairs Integrated Medication Manager
- ClinicalTrials.gov ID
- NCT01787175
- Acronym / sponsor ID
- IMM / 5R18HS017186-03
- Conditions
- Electronic Health Records
- Keywords
- Medication Therapy Management, Clinical Decision Support Systems, Medical Informatics, Patient Care Management, United States Department of Veterans Affairs
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 58 participants (actual)
- Lead sponsor
- University of UtahUniversity, hospital or other
- Collaborators
- Agency for Healthcare Research and Quality (AHRQ)
- Study start
- Oct 2007
- Primary completion
- Mar 2011 (actual)
- Study completion
- Mar 2011 (actual)
- First posted
- 8 Feb 2013 (estimated)
- Results
- Posted 23 Jun 2016
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this study is to advance the science of healthcare informatics and to improve medication management through the development of a new approach to the electronic medical record called the Integrated Medication Manager (IMM).
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 design
- Primary purpose
- Health services research
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Integrated Medication Manager | Experimental | Other: Integrated Medication ManagerExperienced 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. |
| Standard EHR | No intervention | –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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- 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
Key exclusion criteria (1 listed)
- None
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Integrated Medication ManagerAlso: IMMA 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 | Integrated Medication Manager |
Primary outcome
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.
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.
1 secondary outcome
Identification of Planned Monitoring and Follow up Encounters in Assessment and Plan
Time frame: 10 minutes
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Jun 2016.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Background: PubMed 15611491Asch 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.
- Background: PubMed 16585667Perlin 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.
- Background: PubMed 10691588Morris 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.
- Background: PubMed 15537204Fox 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.
- Background: PubMed 8976626Xiao 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.
- Background: PubMed 11694107Phillips 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.
- Background: PubMed 14528038Nebeker 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.
- Background: PubMed 16046562Crosson 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.
- Background: PubMed 16050875Hayward 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.
- Background: PubMed 15625341Tinetti 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.
- Background: PubMed 15755945Garg 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.
- Background: PubMed 17106490Shekelle 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Jonathan Nebeker, MD, MS principal investigator
University of Utah
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Integrated Medication Manager in people with Electronic Health Records, run by University of Utah at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Jun 2016. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 23 Jun 2016). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Amount of Time to Complete Assessment and Plan (time frame: 10 minutes). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT01787175, which also lists 19 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Jun 2016.