This randomized controlled trial of a telephone intervention in a hospital-based primary care clinic found that a reminder phone call reduced the no-show rate.1 This is timely and important because empirical evidence suggests that expanded health insurance coverage would potentially increase appointment wait time because of constraints on medical capacity, raising concern regarding efficient appointment coordination in health care services. For example, the average appointment wait time to see an internist increased from 33 days to 52 days when health care reform was initially implemented in Massachusetts.2
Medical practitioners and policymakers have recognized that delayed appointments could result in discontinuities of care and declines in health status and have performed various interventions such as same-day appointment.3 However, many interventions have emphasized the role of medical providers and have paid relatively less attention to the obstacles from patients although patient no-shows and last-minute cancellations also significantly interrupt medical providers’ productivity and other patients’ access to health care.4 This study implies that efficient appointment coordination would be critical to improve timely access to health care and that interventions would be more cost-effective if we identify patients at high risk to no-show and tailor interventions to them.
The soundness of a randomized controlled trial warrants careful discussion, as approximately a quarter of patients in the intervention group did not receive at least one reminder call and the differences in the baseline characteristics between the treatment and control groups were not examined statistically. Descriptions of the statistical analysis and estimation results also need further explanations. For example, the authors did not mention the core options (e.g., link function) of a generalized estimating equations model (GEE), even though a GEE yields a wide array of estimation models depending on these options.5 As a result, it is hard to understand exactly which estimation model was employed and how absolute risk reductions were defined and obtained after estimation.
Further studies investigating variations in appointment wait time and no-show (e.g., by physician specialty, patient employment status, and rurality) would provide valuable insights to facilitate efficient health care delivery in the Patient Protection Affordable Care Act era.
References
Shah SJ, Cronin P, Hong CS, Hwang AS, Ashburner JM, Bearnot BI, Richardson CA, Fosburgh BW, Kimball AB. Targeted reminder phone calls to patients at high risk to no-show for primary care appointment: a randomized trial. J Gen Intern Med. 2016. doi:10.1007/s11606-016-3813-0.
Massachusetts Medical Society. 2011 patient access to health care study: a survey of Massachusetts Physicians’ Offices. Waltham: Massachusetts Medical Society; 2011.
Murray M, Bodenheimer T, Rittenhouse D, Grumbach K. Improving timely access to primary care: case studies of the advanced access model. JAMA. 2003;289(8):1042–6.
Kheirkhah P, Feng Q, Travis LM, et al. Prevalence, predictors and economic consequences of no-shows. BMC Health Serv Res. 2016;16:13.
Hardin JW, Hilbe JM. Generalized estimating equations. 2nd ed. Boca Raton: Chapman and Hall/CRC; 2012.
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Tak, H.J. Capsule Commentary of Shah et al., Targeted Reminder Phone Calls to Patients at High Risk to No-Show for Primary Care Appointment: A Randomized Trial. J GEN INTERN MED 31, 1504 (2016). https://doi.org/10.1007/s11606-016-3835-7
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DOI: https://doi.org/10.1007/s11606-016-3835-7