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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT02224417
Other study ID # NIHA-2013-1-005
Secondary ID
Status Completed
Phase N/A
First received
Last updated
Start date March 2015
Est. completion date October 31, 2018

Study information

Verified date January 2019
Source Duke-NUS Graduate Medical School
Contact n/a
Is FDA regulated No
Health authority
Study type Interventional

Clinical Trial Summary

Type II diabetes is associated with a host of adverse and costly complications, including heart attacks, strokes, blindness, kidney failure, and severe neuropathy that may result in amputations. For those with diabetes, glycemic control is essential to minimize complications but many fail at being sufficiently adherent to their treatment. The investigators propose to test two incentive-based intervention strategies aimed at improving diabetes outcomes amongst patients with uncontrolled glycemic levels. The incentives are tied either to processes aimed at improving blood sugar levels (glucose testing, physical activity and medication adherence) or directly to the intermediary outcome (blood glucose in the acceptable range). While process incentives are likely to provide more motivation for treatment adherence, as these goals may be comparably easier to meet, these incentives only reward intermediary outcomes and it might be more effective to reward successfully achieving a health outcome directly.


Description:

Type II diabetes is associated with a host of adverse and costly complications, including heart attacks, strokes, blindness, kidney failure, and severe neuropathy that may result in amputations. For those with diabetes, intensive glycemic control is essential to minimize complications. Medication adherence, weight loss, increased exercise and improved diet have all been shown to significantly improve glycemic control, resulting in improved health outcomes and lower medical costs, including a reduction in emergency department visits and hospitalizations. Yet, despite the significant health benefits associated with adherence to diet and exercise regimes and taking diabetes medications as prescribed, non-adherence to all three is a significant problem. One strategy to improve adherence and thus long term health outcomes is to provide a clearer short term benefit. For example, those with consistent evidence of adherence to an exercise or medication regimen could receive subsidies or incentives.

Therefore, the investigators propose to test three theory-based intervention strategies aimed at improving diabetes outcomes amongst a population of uncontrolled patients (Haemoglobin A1c, HbA1c, levels of 8.0 or greater at baseline). The proposed 6-month study will randomise 240 participants, 60 in the control arm and 90 in each incentivized arm from the Geylang Polyclinic. The first strategy does not involve incentives but includes a Diabetes Educational Program (DEP) to help the patient manage their condition. Included in the program are text messages to encourage participants to take their medications as prescribed and prompt good dietary and exercise practices. Subsequent strategies incorporate incentives as core components. The incentives are tied either to processes aimed at improving blood sugar levels (glucose testing, physical activity and medication adherence) or directly to the intermediary outcome (blood glucose in the acceptable range). While process incentives are likely to provide more motivation for treatment adherence, as these goals may be comparably easier to meet, these incentives only reward intermediary outcomes and it might be more effective to reward successfully achieving a health outcome directly. The investigators see this as an important empirical question that will be answered by our proposed trial. Another advantage of outcome incentives is that they are likely to be more cost-effective than process incentives as these incentives are only spent on results.

Aims and hypotheses that will be tested:

- Aim 1A: To determine if adding financial incentives for diabetes management to a Diabetes Educational Program (DEP), which comprises text messaging and use of study devices to encourage patient medical adherence and prompt good dietary as well as exercise practices, is more effective at improving diabetes health outcomes compared to the DEP alone.

- Hypothesis 1A: The average reduction in HbA1c levels at 6 months will be greater for participants in the incentive arms compared to participants in the DEP arm.

- Aim 1B: To determine whether incentivising health outcome (self-monitored blood sugar within acceptable range) is more effective at improving diabetes health outcomes than incentivising intermediate processes (blood glucose testing, physical activity and medical adherence) aimed at improving the primary outcome.

- Hypothesis 1B: The average reduction in HbA1c levels at 6 months will be greater for participants in the health outcome incentive arm compared to participants in the processes incentive arm.

- Aim 2: To determine which intervention (i.e. incentivising processes or outcome) is more cost effective (incrementally) at achieving reductions in HbA1c levels at 6 months.

- Hypothesis 2: The Incremental Cost-Effectiveness Ratio (ICER) of the intervention incentivising health outcome will be greater than that of the intervention incentivising processes.

- Aim 3A: To determine whether adding financial incentives for diabetes management is more effective at improving treatment adherence (assessed based on whether self-monitored blood sugar falls within acceptable range) than incentivizing intermediate processes aimed at improving the primary outcome.

- Hypothesis 3A: The average increase in the proportion of medications and blood tests taken as prescribed and average number of daily steps at 6 months will be greater for participants in the incentive arms compared to participants in the DEP arm.

- Aim 3B: To determine whether incentivising treatment adherence (through assessing if self-monitored blood sugar falls within acceptable range) is more effective at improving treatment adherence than incentivising intermediate processes aimed at improving the primary outcome.

- Hypothesis 3B: The average increase in the proportion of medications and blood tests taken as prescribed and average number of daily steps at 6 months will be greater for participants in the outcome incentive arms compared to participants in the processes incentive arms.


Recruitment information / eligibility

Status Completed
Enrollment 240
Est. completion date October 31, 2018
Est. primary completion date October 25, 2018
Accepts healthy volunteers No
Gender All
Age group 21 Years to 70 Years
Eligibility Inclusion Criteria:

- Participants need to be uncontrolled diabetics at Baseline. Uncontrolled diabetes is defined by a HbA1c level 8.0 or greater. Participants will be required to have at least 1 of 2 HbA1c readings 8.0 or greater in the past 6 months.

- Be prescribed at least one diabetic medication for at least three months and be willing to have this verified by a physician.

- Be Singaporean citizens or Permanent Residents.

- Be able to converse in English or Mandarin.

Exclusion Criteria:

- Individuals on inject-able insulin therapy.

- Individuals with significant co-morbid conditions such that they are unlikely to be able to take their medications without assistance from a third party.

- Individuals who are pregnant.

- Individuals who fail the PARQ and do not obtain doctor's consent.

Study Design


Intervention

Behavioral:
Diabetes Educational Program (DEP)
Participants in this Arm will receive the Diabetes Educational Program (DEP), as required, which is part of usual care at the Polyclinic. It is delivered by a Health Counsellor at the point of diagnosis and focused education is provided during doctor visits for medication. The program at the Polyclinic comprises information on a series of diabetes-related issues. The participant will receive the 2 or 3 study devices (patients will receive a glucometer if they do not already have one). The Site Study Coordinator will provide education on the use of the Fitbit Zip™ and the eCAP™. As part of usual care, patients who have difficulties with their glucometer will be referred to a Health Counsellor at the Polyclinic.
DEP + Process Incentive
Participants will receive the DEP as required. In addition, participants will have the opportunity to earn financial incentives (in vouchers) for meeting specified goals: SGD3.50 weekly for meeting Glucose testing goals: measuring blood glucose on three non-consecutive days each week. SGD0.50 daily for Medication adherence: taking medications daily as prescribed, monitored by eCAP device. Assessed based on medication-taking times within specified time windows. Participants should be adherent at all specified mealtimes to be fully adherent for the day. SGD1.00 daily for Regular Physical activity: taking 8,000 steps during the day as recorded by Fitbit.
DEP + Outcome Incentive
Participants will receive the DEP as required. In addition, participants will have the opportunity to earn financial incentives (in vouchers) for recording glucose readings within the normal range (i.e. between 4 to 7mmols/L two before a meal) on 3 non-consecutive days within the week using the glucometer. SGD 2 weekly if one glucose readings falls within the normal range, SGD 7 weekly if two glucose readings fall within the normal range, SGD 14 weekly if all three glucose readings fall within the normal range.

Locations

Country Name City State
Singapore SingHealth Polyclinic (Bedok) Singapore
Singapore SingHealth Polyclinics (Geylang) Singapore

Sponsors (1)

Lead Sponsor Collaborator
Duke-NUS Graduate Medical School

Country where clinical trial is conducted

Singapore, 

References & Publications (17)

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Chapman GB, Brewer NT, Coups EJ, Brownlee S, Leventhal H, Leventhal EA. Value for the future and preventive health behavior. J Exp Psychol Appl. 2001 Sep;7(3):235-50. — View Citation

Chernew ME, Juster IA, Shah M, Wegh A, Rosenberg S, Rosen AB, Sokol MC, Yu-Isenberg K, Fendrick AM. Evidence that value-based insurance can be effective. Health Aff (Millwood). 2010 Mar-Apr;29(3):530-6. doi: 10.1377/hlthaff.2009.0119. Epub 2010 Jan 21. — View Citation

Cohen ND, Dunstan DW, Robinson C, Vulikh E, Zimmet PZ, Shaw JE. Improved endothelial function following a 14-month resistance exercise training program in adults with type 2 diabetes. Diabetes Res Clin Pract. 2008 Mar;79(3):405-11. Epub 2007 Nov 19. — View Citation

DeFulio A, Silverman K. The use of incentives to reinforce medication adherence. Prev Med. 2012 Nov;55 Suppl:S86-94. doi: 10.1016/j.ypmed.2012.04.017. Epub 2012 May 2. Review. — View Citation

Doshi JA, Zhu J, Lee BY, Kimmel SE, Volpp KG. Impact of a prescription copayment increase on lipid-lowering medication adherence in veterans. Circulation. 2009 Jan 27;119(3):390-7. doi: 10.1161/CIRCULATIONAHA.108.783944. Epub 2009 Jan 12. — View Citation

Elliott RA, Shinogle JA, Peele P, Bhosle M, Hughes DA. Understanding medication compliance and persistence from an economics perspective. Value Health. 2008 Jul-Aug;11(4):600-10. doi: 10.1111/j.1524-4733.2007.00304.x. Epub 2008 Jan 8. — View Citation

Encinosa WE, Bernard D, Dor A. Does prescription drug adherence reduce hospitalizations and costs? The case of diabetes. Adv Health Econ Health Serv Res. 2010;22:151-73. — View Citation

Giuffrida A, Torgerson DJ. Should we pay the patient? Review of financial incentives to enhance patient compliance. BMJ. 1997 Sep 20;315(7110):703-7. Review. — View Citation

Johnston M, Sniehotta F. Financial incentives to change patient behaviour. J Health Serv Res Policy. 2010 Jul;15(3):131-2. doi: 10.1258/jhsrp.2010.010048. — View Citation

Maciejewski ML, Farley JF, Parker J, Wansink D. Copayment reductions generate greater medication adherence in targeted patients. Health Aff (Millwood). 2010 Nov;29(11):2002-8. doi: 10.1377/hlthaff.2010.0571. — View Citation

Parker B, Noakes M, Luscombe N, Clifton P. Effect of a high-protein, high-monounsaturated fat weight loss diet on glycemic control and lipid levels in type 2 diabetes. Diabetes Care. 2002 Mar;25(3):425-30. — View Citation

Sjöström CD, Lissner L, Wedel H, Sjöström L. Reduction in incidence of diabetes, hypertension and lipid disturbances after intentional weight loss induced by bariatric surgery: the SOS Intervention Study. Obes Res. 1999 Sep;7(5):477-84. — View Citation

Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care. 2005 Jun;43(6):521-30. — View Citation

Thomas DE, Elliott EJ, Naughton GA. Exercise for type 2 diabetes mellitus. Cochrane Database Syst Rev. 2006 Jul 19;(3):CD002968. Review. — View Citation

Umpierre D, Ribeiro PA, Kramer CK, Leitão CB, Zucatti AT, Azevedo MJ, Gross JL, Ribeiro JP, Schaan BD. Physical activity advice only or structured exercise training and association with HbA1c levels in type 2 diabetes: a systematic review and meta-analysis. JAMA. 2011 May 4;305(17):1790-9. doi: 10.1001/jama.2011.576. Review. — View Citation

Volpp KG, John LK, Troxel AB, Norton L, Fassbender J, Loewenstein G. Financial incentive-based approaches for weight loss: a randomized trial. JAMA. 2008 Dec 10;300(22):2631-7. doi: 10.1001/jama.2008.804. — View Citation

* Note: There are 17 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary HbA1c levels HbA1c levels will be the health outcome variable. HbA1c measures the metabolic control of diabetes, with normal values (well controlled blood glucose levels) below 7%. We hypothesise that participants with high adherence levels will have lower HbA1c levels and be more likely to have healthy (below 7%) HbA1c levels compared to less adherent participants, all being equal. Baseline, Week 12 and Week 24
Secondary Physical activity Fitbit data will be analysed to determine whether the average number of days that participants achieved the daily activity goal (8,000 or more steps per day) differs by intervention arm. Data will be reviewed for all time points, however the focus will be on physical activity in the final month of the study, which will provide the greatest evidence of potential long term behaviour change. Months 1 to 6
Secondary Medication Adherence Dose-rate adherence percentage for the last month of the study, as measured by the eCAP device. The dose-rate adherence percentage measures the proportion of times the participant took the medication within all specified pre-established dosing schedule. (Data will be reviewed for all time points, however the focus will be on the last month of the study). Months 1 to 6
Secondary Glucose testing rates Glucose testing rates measure the proportion of days within the month that the participant tested their blood glucose levels where the denominator is the level of testing recommended by the clinician. Months 1 to 6
Secondary Glucose testing within range The proportion of days within the month that the participant tested their blood glucose levels and the test results were within specified ranges. Months 1 to 6
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