IMM: VA Integrated Medication Manager

• Sponsor: University of Utah (Other)
• Overall Status: Completed
• CT.gov ID: NCT01787175
• Collaborator: Agency for Healthcare Research and Quality (AHRQ) (U.S. Fed)
• Enrollment: 58
• Location: 1
• Arms: 2
• Duration (Months): 41
• Patients Per Site Per Month: 1.4

Study Details

Study Description

Brief 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).

Condition or Disease	Intervention/Treatment	Phase
Electronic Health Records	Other: Integrated Medication Manager	N/A

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

• Study Type: Interventional
• Actual Enrollment: 58 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Masking: None (Open Label)
• Primary Purpose: Health Services Research
• Official Title: Veterans Affairs Integrated Medication Manager
• Study Start Date: Oct 1, 2007
• Actual Primary Completion Date: Mar 1, 2011
• Actual Study Completion Date: Mar 1, 2011

Arms and Interventions

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.	Other: Integrated Medication Manager; 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: IMM
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.

Outcome Measures

Primary Outcome Measures

1. Amount of Time to Complete Assessment and Plan [10 minutes]

   Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan.

2. Accuracy of Written Assessment and Plan in Terms of Control and Status [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.

Secondary Outcome Measures

1. Identification of Planned Monitoring and Follow up Encounters in Assessment and Plan [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.

Eligibility Criteria

Criteria

• Ages Eligible for Study: 18 Years and Older
• Sexes Eligible for Study: All
• Accepts Healthy Volunteers: Yes

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

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	VA SLC Health Care System	Salt Lake City	Utah	United States	84148

Sponsors and Collaborators

• University of Utah
• Agency for Healthcare Research and Quality (AHRQ)

Investigators

• Principal Investigator: Jonathan Nebeker, MD, MS, University of Utah

Study Documents (Full-Text)

None provided.

More Information

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.
• 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.
• Bradley EH, Bogardus ST Jr, Tinetti ME, Inouye SK. Goal-setting in clinical medicine. Soc Sci Med. 1999 Jul;49(2):267-78.
• 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.
• 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.
• 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.
• 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. Review.
• 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.
• Miller RH, Sim I. Physicians' use of electronic medical records: barriers and solutions. Health Aff (Millwood). 2004 Mar-Apr;23(2):116-26.
• Morris AH. Developing and implementing computerized protocols for standardization of clinical decisions. Ann Intern Med. 2000 Mar 7;132(5):373-83.
• 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. Review.
• 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.
• 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. Review.
• 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.
• Taatz H. [The problem of the time factor in orthodontic treatment]. Stomatol DDR. 1976 Feb;26(2):102-5. German.
• 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.
• 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. Epub 2006 Oct 26.
• Weir CR. Linking information needs with evaluation: the role of task identification. Proc AMIA Symp. 1998:310-4.
• 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.

• Responsible Party: University of Utah
• ClinicalTrials.gov Identifier: NCT01787175
• Other Study ID Numbers: 5R18HS017186-03
• First Posted: Feb 8, 2013
• Last Update Posted: Jun 23, 2016
• Last Verified: May 1, 2016

• Keywords provided by University of Utah: Medication Therapy Management; Clinical Decision Support Systems; Medical Informatics; Patient Care Management; United States Department of Veterans Affairs

Study Results

Participant Flow

Recruitment Details	Recruitment 12/2010 to 3/2011 at the Salt Lake City VA and University of Utah health care systems. Simulations took place at either of these locations.

Arm/Group Title	Integrated Medication Manager	Standard EHR
Arm/Group Description	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.	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.
Period Title: Overall Study
STARTED	30	28
COMPLETED	30	28
NOT COMPLETED	0	0

Baseline Characteristics

Arm/Group Title	Integration Medication Manager	Standard EHR	Total
Arm/Group Description	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.	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.	Total of all reporting groups
Overall Participants	30	28	58
Age (Count of Participants)
<=18 years	0 0%	0 0%	0 0%
Between 18 and 65 years	30 100%	28 100%	58 100%
>=65 years	0 0%	0 0%	0 0%
Sex: Female, Male (Count of Participants)
Female	18 60%	15 53.6%	33 56.9%
Male	12 40%	13 46.4%	25 43.1%
Region of Enrollment (participants) [Number]
United States	30 100%	28 100%	58 100%

Outcome Measures

1. Primary Outcome

Title	Amount of Time to Complete Assessment and Plan
Description	Each participant had 10 minutes maximum to review the patient case and write an Assessment and Plan.
Time Frame	10 minutes

Outcome Measure Data

Analysis Population Description

58 providers were enrolled

Arm/Group Title	Integrated Medication Manager	Standard EHR
Arm/Group Description	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.	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.
Measure Participants	30	28
Mean (Standard Deviation) [minutes]	8.5 (1.9)	8.7 (1.6)

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Integrated Medication Manager
	Comments	Null hypothesis: Participants will require the same amount of time to complete assessments and plans using either IMM or CPRS. Power calculation: With 2 replications per subject, and assuming an ICC of 0.15, a two-sided alpha 0.05 comparison adjusted for 5 multiple comparisons (adjusted alpha = 0.01), and power of 80%, an N of 32 clinicians was required for each group (32 using IMM, and 32 using CPRS).
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value	0.047
	Comments
	Method	Mixed-effects linear model
	Comments
Method of Estimation	Estimation Parameter	Difference in time to complete A&P
	Estimated Value	-17.73
	Confidence Interval	(2-Sided) 95%; -35.24 to -0.23
	Parameter Dispersion	Type: Value:
	Estimation Comments

2. Primary Outcome

Title	Accuracy of Written Assessment and Plan in Terms of Control and Status
Description	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.
Time Frame	10 minutes

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Integrated Medication Manager	Standard EHR
Arm/Group Description	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.	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.
Measure Participants	30	28
Mean (95% Confidence Interval) [units on a scale]	0.609	0.569

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Integrated Medication Manager
	Comments	Null hypothesis: Participants will receive the same scores for assessments and plans completed using either IMM or CPRS. Power calculation: With 2 replications per subject, and assuming an ICC of 0.15, a two-sided alpha 0.05 comparison adjusted for 5 multiple comparisons (adjusted alpha = 0.01), and power of 80%, an N of 32 clinicians was required for each group (32 using IMM, and 32 using CPRS).
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value	0.15
	Comments
	Method	Mixed-effects linear model
	Comments
Method of Estimation	Estimation Parameter	Value of problem scores for A&P complete
	Estimated Value	0.04
	Confidence Interval	(2-Sided) 95%; -0.01 to 0.09
	Parameter Dispersion	Type: Value:
	Estimation Comments

3. Secondary Outcome

Title	Identification of Planned Monitoring and Follow up Encounters in Assessment and Plan
Description	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.
Time Frame	10 minutes

Outcome Measure Data

Analysis Population Description

[Not Specified]

Arm/Group Title	Integrated Medication Manager	Standard EHR
Arm/Group Description	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.	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.
Measure Participants	30	28
Mean (95% Confidence Interval) [proportion]	0.505	0.477

Statistical Analysis 1

Statistical Analysis Overview	Comparison Group Selection	Integrated Medication Manager
	Comments	Null hypothesis: Participants will receive the same proportion of acceptable scores for assessments and plans completed using either IMM or CPRS. Power calculation: With 2 replications per subject, and assuming an ICC of 0.15, a two-sided alpha 0.05 comparison adjusted for 5 multiple comparisons (adjusted alpha = 0.01), and power of 80%, an N of 32 clinicians was required for each group (32 using IMM, and 32 using CPRS).
	Type of Statistical Test	Superiority or Other
	Comments
Statistical Test of Hypothesis	p-Value	0.005
	Comments
	Method	Regression, Logistic
	Comments
Method of Estimation	Estimation Parameter	Odds Ratio (OR)
	Estimated Value	1.90
	Confidence Interval	(2-Sided) 95%; 1.22 to 2.98
	Parameter Dispersion	Type: Value:
	Estimation Comments

Adverse Events

Arm/Group Title	Integrated Medication Manager		Standard EHR
Arm/Group Description	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. Integrated Medication Manager: 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.		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. Integrated Medication Manager: 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.
All Cause Mortality
	Integrated Medication Manager		Standard EHR
	Affected / at Risk (%)	# Events	Affected / at Risk (%)	# Events
Total	/ (NaN)		/ (NaN)
Serious Adverse Events
	Integrated Medication Manager		Standard EHR
	Affected / at Risk (%)	# Events	Affected / at Risk (%)	# Events
Total	0/30 (0%)		0/28 (0%)
Other (Not Including Serious) Adverse Events
	Integrated Medication Manager		Standard EHR
	Affected / at Risk (%)	# Events	Affected / at Risk (%)	# Events
Total	0/30 (0%)		0/28 (0%)

Limitations/Caveats

We were not able to evaluate a system-wide deployment of the resulting graphical user interface (GUI) (IMM) in terms of patient outcomes (Aim 3). We were unable to conduct Aim 3, which would have evaluated IMM in a cluster-randomized trial.

More Information

Certain Agreements

All Principal Investigators ARE employed by the organization sponsoring the study.

There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed.