Literature DB >> 26484851

Strategies to Maximize Data Collection Response Rates in a Randomized Control Trial Focused on Children with Medical Complexity.

Stanley M Finkelstein1, Margaret Celebrezze1,2, Rhonda Cady1,3, Scott Lunos4, Wendy S Looman2.   

Abstract

INTRODUCTION: Obtaining complete and timely subject data is key to the success of clinical trials, particularly for studies requiring data collected from subjects at home or other remote sites. A multifaceted strategy for data collection in a randomized controlled trial (RCT) focused on care coordination for children with medical complexity is described. The influences of data collection mode, incentives, and study group membership on subject response patterns are analyzed. Data collection included monthly healthcare service utilization (HCSU) calendars and annual surveys focused on care coordination outcomes.
MATERIALS AND METHODS: One hundred sixty-three families were enrolled in the 30-month TeleFamilies RCT. Subjects were 2-15 years of age at enrollment. HCSU data were collected by parent/guardian self-report using mail, e-mail, telephone, or texting. Surveys were collected by mail. Incentives were provided for completed surveys after 8 months to improve collection returns. Outcome measures were the number of HCSU calendars and surveys returned, the return interval, data collection mode, and incentive impact.
RESULTS: Return rates of 90% for HCSU calendars and 82% for annual surveys were achieved. Mean return intervals were 72 and 65 days for HCSU and surveys, respectively. Survey response increased from 55% to 95% after introduction of a gift card and added research staff.
CONCLUSIONS: High return rates for HCSU calendars and health-related surveys are attainable but required a flexible and personnel-intensive approach to collection methods. Family preference for data collection approach should be obtained at enrollment, should be modified as needed, and requires flexible options, training, intensive staff/family interaction, and patience.

Entities:  

Keywords:  home health monitoring; information management; telehealth; telenursing

Mesh:

Year:  2015        PMID: 26484851      PMCID: PMC4817571          DOI: 10.1089/tmj.2015.0069

Source DB:  PubMed          Journal:  Telemed J E Health        ISSN: 1530-5627            Impact factor:   3.536


  19 in total

1.  A questionnaire for the assessment of patients' impressions of the risks and benefits of home telecare.

Authors:  G Demiris; S Speedie; S Finkelstein
Journal:  J Telemed Telecare       Date:  2000       Impact factor: 6.184

2.  The CAHPS Hospital Survey: development, testing, and use.

Authors:  Christine Crofton; Charles Darby; Marybeth Farquhar; Carolyn M Clancy
Journal:  Jt Comm J Qual Patient Saf       Date:  2005-11

3.  Development and testing of the social capital scale for families of children with special health care needs.

Authors:  Wendy Sue Looman
Journal:  Res Nurs Health       Date:  2006-08       Impact factor: 2.228

4.  Assessing services, supports and costs for young families under stress.

Authors:  M Sleed; J Beecham; M Knapp; C McAuley; N McCurry
Journal:  Child Care Health Dev       Date:  2006-01       Impact factor: 2.508

5.  Clinical trials and treatment effects monitoring.

Authors:  C L Meinert
Journal:  Control Clin Trials       Date:  1998-12

6.  Functional status II(R). A measure of child health status.

Authors:  R E Stein; D J Jessop
Journal:  Med Care       Date:  1990-11       Impact factor: 2.983

7.  Differentiating subgroups of children with special health care needs by health status and complexity of health care needs.

Authors:  Matthew D Bramlett; Debra Read; Christina Bethell; Stephen J Blumberg
Journal:  Matern Child Health J       Date:  2008-04-02

8.  The PedsQL 4.0 as a pediatric population health measure: feasibility, reliability, and validity.

Authors:  James W Varni; Tasha M Burwinkle; Michael Seid; Douglas Skarr
Journal:  Ambul Pediatr       Date:  2003 Nov-Dec

Review 9.  Maximising response to postal questionnaires--a systematic review of randomised trials in health research.

Authors:  Rachel A Nakash; Jane L Hutton; Ellen C Jørstad-Stein; Simon Gates; Sarah E Lamb
Journal:  BMC Med Res Methodol       Date:  2006-02-23       Impact factor: 4.615

10.  The PedsQL Family Impact Module: preliminary reliability and validity.

Authors:  James W Varni; Sandra A Sherman; Tasha M Burwinkle; Paige E Dickinson; Pamela Dixon
Journal:  Health Qual Life Outcomes       Date:  2004-09-27       Impact factor: 3.186

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  2 in total

1.  The Impact of Telehealth and Care Coordination on the Number and Type of Clinical Visits for Children With Medical Complexity.

Authors:  Holly D McKissick; Rhonda G Cady; Wendy S Looman; Stanley M Finkelstein
Journal:  J Pediatr Health Care       Date:  2016-12-22       Impact factor: 1.812

2.  Help to Overcome Problems Effectively for Cancer Survivors: Development and Evaluation of a Digital Self-Management Program.

Authors:  Hayley Wright; Louise Moody; Becky Whiteman; Michael McGillion; Wendy Clyne; Gemma Pearce; Andy Turner; Faith Martin
Journal:  J Med Internet Res       Date:  2020-05-19       Impact factor: 5.428

  2 in total

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