Literature DB >> 28359191

The (in)stability of 21st century orthopedic patient contact information and its implications on clinical research: A cross-sectional study.

Daniel A London1,2, Jeffrey G Stepan2,3, Charles A Goldfarb2, Martin I Boyer2, Ryan P Calfee2.   

Abstract

BACKGROUND: In clinical research, minimizing patients lost to follow-up is essential for data validity. Researchers can employ better methodology to prevent patient loss. We examined how orthopedic surgery patients' contact information changes over time to optimize data collection for long-term outcomes research.
METHODS: Patients presenting to orthopedic outpatient clinics completed questionnaires regarding methods of contact: home phone, cell phone, mailing address, and e-mail address. They reported currently available methods of contact, if they changed in the past 5 and 10 years, and when they changed. Differences in the rates of change among methods were assessed via Fisher's exact tests. Whether participants changed any of their contact information in the past 5 and 10 years was determined via multivariate modeling, controlling for demographic variables.
RESULTS: Among 152 patients, 51% changed at least one form of contact information within 5 years, and 66% changed at least one form within 10 years. The rate of change for each contact method was similar over 5 (15%-28%) and 10 years (26%-41%). One patient changed all four methods of contact within the past 5 years and seven within the past 10 years. Females and younger patients were more likely to change some type of contact information.
CONCLUSION: The type of contact information least likely to change over 5-10 years is influenced by demographic factors such as sex and age, with females and younger participants more likely to change some aspect of their contact information. Collecting all contact methods appears necessary to minimize patients lost to follow-up, especially as technological norms evolve.

Entities:  

Keywords:  Clinical research; data collection; follow-up; longitudinal data; patient recruitment; research methods

Mesh:

Year:  2016        PMID: 28359191      PMCID: PMC5380166          DOI: 10.1177/1740774516677275

Source DB:  PubMed          Journal:  Clin Trials        ISSN: 1740-7745            Impact factor:   2.486


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