CClinicalTrials.gg
CompletedNCT01221090P20-P2Updated Oct 14, 2013Results posted

Diabetes Self-Management Models to Reduce Health Disparities

A Phase 4 interventional study of PDA and CDSMP in Type 2 Diabetes, sponsored by Scott and White Hospital & Clinic. Completed at 1 site in United States. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2013-10-14.

Sponsored by Scott and White Hospital & Clinic · Phase 4, Interventional, and Prevention

Phase
Phase 4
Study type
Interventional
Enrollment
376
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study summary

To evaluate the effectiveness of two different diabetes self-management approaches (Personal Digital Assistant-based intervention \& Chronic Disease Self-Management Program) to reduce health disparities in minority, rural residents, and other underserved populations with type 2 diabetes in Central Texas. We hypothesise that: 1) Racial/ethnic minority patients with T2DM will be found to experience disparities in diabetes self-management treatment protocols and clinical outcomes, which persist even when controlling for age, gender, obesity, and insurance status; 2) Patients with T2DM who reside in more rural areas will be found to experience disparities in diabetes self-management treatment protocols and clinical outcomes as compared to more urban counterparts, controlling for age, gender, race/ethnicity, obesity, and insurance status; 3) The introduction of CSDMP and HIT protocols will improve diabetes-related self management behaviors, reduce HBA1c values, and increase quality of life in persons with T2DM as compared to controls. A combined intervention approach will result in the greatest reductions; 4) Health improvements following the introduction of CDSMP, HIT or CDSMP/HIT protocols in persons with T2DM compared to controls will be more marked in racial/ethnic minority patients and those patients residing in rural areas; 5) The introduction of self-management interventions will be cost-effective in reducing HbA1c values over time, and associated health care utilization including overall reduction in ER and acute care hospital admissions; 6) Although there is little prior research in this area to guide specific hypotheses, we hypothesize that, overall, there will be no significant cost-effective differential in CDSMP as compared to HIT approaches, although the cost-effective ratio may be stronger in particular subpopulations. The combined approach will have higher costs, but is also anticipated to have a higher cost-benefit ratio for minority populations; 7) The majority of clinicians will be willing to let their patients enroll in the study and will reinforce intervention protocols; and 8) These interventions can be embedded into existing health care structures. At the end of the study, Scott and White will institutionalize cost-effective treatment protocols.

Read the detailed description

Despite concerted federal and state attempts to reduce health disparities over the past decades substantial disparities in reported rates of chronic disease for minorities still exist. In particular, African Americans and Hispanics experience higher rates of Type 2 diabetes (T2DM), and cardiovascular disease (CVD) than do other segments of the U.S. population. The objectives of this proposed research project are to test two different diabetes self-management (DSM) programs in a large multi-site health care organization in Central Texas that serves large populations of minority and rural residents, comparing outcomes in order to evaluate their efficacy for reducing health disparities. Our specific aims are to: 1) document the nature and magnitude of extant health disparities in diabetes treatment processes and outcomes; 2) evaluate different DSM intervention approaches on behavioral and clinical outcomes, with attention to differential effects by patient and environmental characteristics; 3) examine the cost-effectiveness of these different approaches to DSM education in minority and rural populations; and 4) explore the reach of our intervention efforts and the broader organizational impacts of DSM education, including feedback loops to clinicians and organizational receptivity to self-management approaches. Our study will employ four different activities: 1) an initial electronic chart review of 1300 records of adults; 2) a 2 by 2 open 24 month randomized clinical trial of behaviorally and technologically based DSM interventions with 400 adults age 21 and older who have type 2 diabetes (T2DM); 3) a cost-effectiveness analysis of the different treatment approaches; and 4) surveys of primary care providers and health care administrators. While our primary outcome will be reductions in hemoglobin A1c (HbA1c), our conceptual model includes clinical, behavioral, economic and organizational outcomes. We will also assess the extent to which our interventions reduce health disparities by examining differential treatment success. This study is innovative in its comparison of both behavioral and technological intervention approaches, its attention to the public health impact and cost-effectiveness of different intervention approaches, and its concern with organizational responses to intervention sustainability. A noteworthy significance will be the strengthening of the linkages between clinical and community treatment approaches and the identification of successful treatment strategies in different settings and populations.

02

Conditions studied

  • Type 2 Diabetes

Keywords

  • Type 2 diabetes
  • Health disparities
  • Central Texas
  • PDA
  • CDSMP
03

In context

Diabetes Mellitus

10,925 studies on the registry are indexed under Diabetes Mellitus; 1,319 are open to participants now.

This study's enrollment of 376 is above the median of 80 across 8,367 interventional studies indexed under Diabetes Mellitus.

Browse Diabetes Mellitus studies →

Lead sponsor

Scott and White Hospital & Clinic is the lead sponsor of 13 studies on the registry; none are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  • Patients with T2DM, including those who require insulin therapy, aged >18 years (eliminates the need to obtain assent for minors who are also dependent on their parents).
  • Last measured HbA1c value of > 7.5% (this study hopes to show an improvement in the control of patient's diabetes, and not focused on patients who already show evidence of good disease control).
  • Willingness and ability to attend one initial research visit and semi-annual routine follow-up visits over a 24-month period. The follow-up visits include height, weight, and blood pressure measurement and a survey. Surveys may be conducted by phone interview or mail when a follow-up visit can not be scheduled.
  • Ability to read, write, and speak English at least at a grade 8 level so as to be able to engage in self-monitoring and use the commercial diabetes management software program (Diabetes Pilot), which is available only in English. For those with lower-literacy, assistance in filling out forms and understanding required intervention protocols will be provided, and use of a "buddy" will be recommended.

Exclusion criteria

Exclusion Criteria:

  • Not willing to sign an informed consent or be randomized to any of the four treatment/control groups, (we want to minimize any upfront treatment biases, while adhering to human subject protocols).
  • Currently, documented severe alcoholism or drug abuse that is \< 6 months ago (concerns that this problem is likely to significantly affect their ability and likelihood to comply with the study requirements over the course of the 24 months).
  • Female patients who are pregnant or planning to become pregnant within 12 months (in pregnancy, type 2 diabetes is managed in a completely different manner than in non-pregnant patients).
05

Study design

Phase
Phase 4
Primary purpose
Prevention
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
376 participants (actual)

Study arms

  • Experimental
    Personal Digital Assistant

    Individuals in this arm were taught to use a diabetes self-care software, Diabetes Pilot™ (Digital Altitudes, Arlington Heights, IL), developed for PalmOS® (Palm, Sunnyvale, CA) which was loaded on to compatible PDAs, the Tungsten™ E2 handheld device. The Diabetes Pilot allowed participants to monitor their blood glucose, blood pressure, medication usage, physical activity, and dietary intake by tracking these measures in an electronic diary.

    Behavioral: PDA

  • Active comparator
    CDSMP

    6-week, classroom-based program for diabetes self-management. The CDSMP, developed by Stanford University, equipped participants with the education and skill sets needed to take a more proactive approach in managing their chronic condition(s) and related symptoms.

    Behavioral: CDSMP

  • Active comparator
    PDA/CDSMP

    Combined intervention

    Behavioral: PDA/CDSMP

  • No intervention
    Control

    Usual Care

Interventions

  • BehavioralPDA

    Technological assistance

    Also known as: Personal digital assistant

  • BehavioralCDSMP

    6-week classes

    Also known as: Chronic disease self-management program

  • BehavioralPDA/CDSMP

    Combined technology and education

    Also known as: PDA + CDSMP

06

What researchers measure

Primary outcomes

  1. HbA1c

    Measures of HbA1c were collected from electronic health records dating back six months prior to orientation to the last day of study participation (45 days after the 12-month follow-up period). If a participant did not have any HbA1c value within the electronic health record for any particular follow-up visit, a lab test was scheduled to obtain a measure. Of the HbA1c collected six months prior to orientation, the value measured closest to the orientation date was considered as the baseline HbA1c value. HbA1c values that were measured on dates preceding the baseline HbA1c were not included; i.e., HbA1c values included in the analysis were those collected since the baseline HbA1c and until the last day of study participation.

    Time frame: 12 months

Secondary outcomes

  1. BMI

    Body mass index

    Time frame: 12 months

  2. Patient Self-reported Perceived Health Status

    Time frame: 12 months

  3. Diabetes-related Behaviors

    Participants were asked the number of days in the past 7 which they participated in various diabetes self-care activities on diet, exercise, home blood glucose monitoring, and foot care.

    Time frame: 12 months

  4. Quality of Life (QOL)

    Participants where asked the number of days in the past 30 days in which their physical (phys) and/or mental was not good, and whether their usual activity was affected by their physical/mental health.

    Time frame: 12 months

07

Results

Posted Oct 14, 2013
Limitations and caveats
Differential dropout across interventions. Failure to obtain 50% minority and 50% non-minority participants, preventing further analyses regarding race/ethnicity differences in outcome. Could only provide information in an exploratory manner.

Participant flow

Participant flow — Overall Study
MilestoneCDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
Started101819995
Completed86475773
Not completed15344222
Withdrew: Non-compliant or unable to contact15121520
Withdrew: Withdrawal by subject022272

Outcome measures

PrimaryHbA1c

Measures of HbA1c were collected from electronic health records dating back six months prior to orientation to the last day of study participation (45 days after the 12-month follow-up period). If a participant did not have any HbA1c value within the electronic health record for any particular follow-up visit, a lab test was scheduled to obtain a measure. Of the HbA1c collected six months prior to orientation, the value measured closest to the orientation date was considered as the baseline HbA1c value. HbA1c values that were measured on dates preceding the baseline HbA1c were not included; i.e., HbA1c values included in the analysis were those collected since the baseline HbA1c and until the last day of study participation.

Time frame:
12 months
Reported as:
Mean · percentage of gycosylated HbA1c
HbA1c
percentage of gycosylated HbA1cCDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
HbA1c8.7 ± 1.98.7 ± 1.78.6 ± 1.48.4 ± 1.6
Statistical analysis
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Likelihood Ratio Tests · p = 0.771 (A priori threshold for statistical significance is \<0.05)
SecondaryBMI

Body mass index

Time frame:
12 months
Reported as:
Mean · kg/m^2
BMI
kg/m^2CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
BMI34.9 ± 9.235.8 ± 7.632.8 ± 5.533.9 ± 8.4
Statistical analysis
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Regression, Linear · p = 0.2176 (A priori threshold for statistical significance is \<0.05)Robust variance estimates.
SecondaryPatient Self-reported Perceived Health Status
Time frame:
12 months
Reported as:
Number · participants
Patient Self-reported Perceived Health Status
participantsCDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
Excellent3011
Very Good13365
Good196414
Fair10298
Poor1002
Statistical analysis
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Fisher Exact · p = 0.572 (A priori threshold for statistical significance was \<0.05)
SecondaryDiabetes-related Behaviors

Participants were asked the number of days in the past 7 which they participated in various diabetes self-care activities on diet, exercise, home blood glucose monitoring, and foot care.

Time frame:
12 months
Reported as:
Mean · Days (e.g., Avg diff 12mo vs baseline)
Diabetes-related Behaviors
Days (e.g., Avg diff 12mo vs baseline)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
Test blood sugar0.26 ± 3.01-0.91 ± 2.120.10 ± 2.050.97 ± 2.76
Test blood sugar the recommended times0.55 ± 3.37-1.22 ± 2.280.11 ± 2.401.21 ± 3.28
Exercise at least 30 minutes0.80 ± 2.900.09 ± 2.39-0.16 ± 2.220.70 ± 2.44
Participate in a specific exercise session0 ± 2.39-1.00 ± 1.610.37 ± 1.890.72 ± 3.06
Check feet1.84 ± 2.990.36 ± 2.110.65 ± 2.660.63 ± 3.11
Wash feet0.52 ± 1.550.09 ± 1.70-0.05 ± 1.00-0.17 ± 1.37
Soak feet0.74 ± 2.291.00 ± 2.000.55 ± 2.500.32 ± 3.13
Dry between toes0.53 ± 2.520.36 ± 1.911.53 ± 3.040.76 ± 2.67
Inspect inside of shoes1.47 ± 3.530.82 ± 1.890.20 ± 3.160.11 ± 3.57
Follow healthful eating plan0.28 ± 2.05-0.36 ± 1.960.60 ± 2.440.93 ± 2.45
Space carbohydrates0.15 ± 3.00-0.36 ± 3.670.60 ± 2.580.64 ± 2.28
Eat 5+ servings of fruits and vegetables0.31 ± 2.920.64 ± 2.460.35 ± 2.061.10 ± 2.14
Eat high-fat foods-0.98 ± 2.171.45 ± 2.340.53 ± 2.29-0.72 ± 2.20
Eat packaged foods (e.g., sweets and desserts)-0.09 ± 2.260 ± 0.630 ± 2.68-0.66 ± 2.02
Followed a healthful eating plan0.32 ± 1.97-0.36 ± 1.630.50 ± 2.370.52 ± 2.34
Statistical analysis
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.26 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.21 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.53 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.24 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.18 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.19 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.87 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.53 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.32 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.37 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.72 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.59 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = <0.004 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.66 (A priori threshold for statistical significance is \<0.05)
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · ANOVA · p = 0.68 (A priori threshold for statistical significance is \<0.05)
SecondaryQuality of Life (QOL)

Participants where asked the number of days in the past 30 days in which their physical (phys) and/or mental was not good, and whether their usual activity was affected by their physical/mental health.

Time frame:
12 months
Reported as:
Mean · Number of days
Quality of Life (QOL)
Number of daysCDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControl
Physical health was not good in the past 30 days5.9 ± 8.79.0 ± 11.78.5 ± 10.27.3 ± 8.8
Mental health was not good in the past 30 days6.8 ± 9.67.2 ± 12.67.3 ± 11.06.6 ± 10.2
Poor phys/mental health prevented usual activities3.8 ± 7.27.3 ± 12.67.8 ± 9.15.4 ± 9.3
Statistical analysis
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Regression, Linear · p = 0.685 (A priori threshold for statistical significance is \<0.05)Robust Variance Estimation.
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Regression, Linear · p = 0.997 (A priori threshold for statistical significance is \<0.05)Robust variance estimation.
  • CDSMP vs Personal Digital Assistant (PDA) vs PDA/CDSMP vs Control · Regression, Linear · p = 0.3067 (A priori threshold for statistical significance is \<0.05)Robust variance estimation.

Adverse events

Non-serious events are listed at a 1% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
CDSMP—0/101 (0%)0/101 (0%)
Personal Digital Assistant (PDA)—0/81 (0%)0/81 (0%)
PDA/CDSMP—0/99 (0%)0/99 (0%)
Control—0/95 (0%)0/95 (0%)

Baseline characteristics

Age, Categorical
Age, Categorical(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
<=18 years00000
Between 18 and 65 years81567370280
>=65 years2025262596
Age Continuous
Age Continuous(years)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
Mean56.4 ± 10.857.7 ± 10.857.7 ± 10.358.5 ± 11.957.6 ± 10.9
Sex: Female, Male
Sex: Female, Male(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
Female54475353207
Male47344642169
Region of Enrollment
Region of Enrollment(participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
United States101819995376
Minority
Minority(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
No60516563239
Yes41303432137
Race-Ethnicity
Race-Ethnicity(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
Non-Hispanic White58496158226
Non-Hispanic Black2111121761
Hispanic2019221576
Other224513
Education
Education(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
Less than high school643316
Some high school438116
High school graduate1620172174
Some college/vocational school46343336149
College graduate1613242174
Graduate school137141347
Income
Income(Participants)CDSMPPersonal Digital Assistant (PDA)PDA/CDSMPControlTotal
< $15,00012117939
$15,000 - $24,9991114191660
$25,000 - $49,99941373230140
$50,000 - $75,0001212231764
> $75,000126141446
Prefer not to answer1314927

4 further baseline measures are reported on the registry.

08

Study locations

1 site
  • Scott & White Clinic
    Temple, Texas 76504, United States
09

References and documents

Publications

  • Vuong AM, Huber JC Jr, Bolin JN, Ory MG, Moudouni DM, Helduser J, Begaye D, Bonner TJ, Forjuoh SN. Factors affecting acceptability and usability of technological approaches to diabetes self-management: a case study. Diabetes Technol Ther. 2012 Dec;14(12):1178-82. doi: 10.1089/dia.2012.0139. Epub 2012 Sep 26. PubMed 23013155 ↗
  • Appiah B, Hong Y, Ory MG, Helduser JW, Begaye D, Bolin JN, Forjuoh SN. Challenges and opportunities for implementing diabetes self-management guidelines. J Am Board Fam Med. 2013 Jan-Feb;26(1):90-2. doi: 10.3122/jabfm.2013.01.120177. PubMed 23288286 ↗
  • Forjuoh SN, Huber C, Bolin JN, Patil SP, Gupta M, Helduser JW, Holleman S, Ory MG. Provision of counseling on diabetes self-management: are there any age disparities? Patient Educ Couns. 2011 Nov;85(2):133-9. doi: 10.1016/j.pec.2010.08.004. Epub 2010 Sep 21. PubMed 20863646 ↗
  • Forjuoh SN, Bolin JN, Gupta M, Huber C, Helduser JW, Holleman S, Robertson A, Ory MG. Disparities in diabetes management by race or ethnicity in a primary care clinic in central Texas. Tex Med. 2010 Nov 1;106(11):e1. PubMed 21104573 ↗
  • Adepoju OE, Bolin JN, Phillips CD, Zhao H, Ohsfeldt RL, McMaughan DK, Helduser JW, Forjuoh SN. Effects of diabetes self-management programs on time-to-hospitalization among patients with type 2 diabetes: a survival analysis model. Patient Educ Couns. 2014 Apr;95(1):111-7. doi: 10.1016/j.pec.2014.01.001. Epub 2014 Jan 13. PubMed 24468198 ↗
  • Forjuoh SN, Bolin JN, Huber JC Jr, Vuong AM, Adepoju OE, Helduser JW, Begaye DS, Robertson A, Moudouni DM, Bonner TJ, McLeroy KR, Ory MG. Behavioral and technological interventions targeting glycemic control in a racially/ethnically diverse population: a randomized controlled trial. BMC Public Health. 2014 Jan 23;14:71. doi: 10.1186/1471-2458-14-71. PubMed 24450992 ↗
  • Adepoju OE, Bolin JN, Ohsfeldt RL, Phillips CD, Zhao H, Ory MG, Forjuoh SN. Can chronic disease management programs for patients with type 2 diabetes reduce productivity-related indirect costs of the disease? Evidence from a randomized controlled trial. Popul Health Manag. 2014 Apr;17(2):112-20. doi: 10.1089/pop.2013.0029. Epub 2013 Oct 23. PubMed 24152055 ↗
10

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Oct 14, 2013, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT01221090
Lead sponsor
Scott and White Hospital & Clinic
Collaborators
Texas A&M University
Responsible party
Sam Forjuoh (Professor & Director of Research, Scott and White Hospital & Clinic) — Principal investigator
First posted
Oct 14, 2010
Start date
Jan 2009
Primary completion
May 2012
Completion
May 2012
Results posted
Oct 14, 2013
Last update
Oct 14, 2013

Study contacts

Samuel N Forjuoh, MD MPH DrPH
principal investigator · Scott & White

Oversight

Data monitoring committee
Yes
View the source record on ClinicalTrials.gov ↗

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