期刊
CANCER
卷 121, 期 10, 页码 1662-1670出版社
WILEY
DOI: 10.1002/cncr.29236
关键词
patient navigation; cancer care; predictive modeling; no-show; disparities
类别
资金
- Lazarex Cancer Foundation
BACKGROUNDPatient adherence to appointments is key to improving outcomes in health care. No-show appointments contribute to suboptimal resource use. Patient navigation and telephone reminders have been shown to improve cancer care and adherence, particularly in disadvantaged populations, but may not be cost-effective if not targeted at the appropriate patients. METHODSIn 5 clinics within a large academic cancer center, patients who were considered to be likely (the top 20th percentile) to miss a scheduled appointment without contacting the clinic ahead of time (no-shows) were identified using a predictive model and then randomized to an intervention versus a usual-care group. The intervention group received telephone calls from a bilingual patient navigator 7 days before and 1 day before the appointment. RESULTSOver a 5-month period, of the 40,075 appointments scheduled, 4425 patient appointments were deemed to be at high risk of a no-show event. After the patient navigation intervention, the no-show rate in the intervention group was 10.2% (167 of 1631), compared with 17.5% in the control group (280 of 1603) (P<.001). Reaching a patient or family member was associated with a significantly lower no-show rate (5.9% and 3.0%, respectively; P<.001 and .006, respectively) compared with leaving a message (14.7%: P=.117) or no contact (no-show rate, 21.6%: P=.857). CONCLUSIONSTelephone navigation targeted at those patients predicted to be at high risk of visit nonadherence was found to effectively and substantially improve patient adherence to cancer clinic appointments. Further studies are needed to determine the long-term impact on patient outcomes, but short-term gains in the optimization of resources can be recognized immediately. Cancer 2015;121:1662-1670. (c) 2015 American Cancer Society. Targeted patient navigation over the telephone to patients determined by predictive modeling to be at high risk of being no-shows for appointments can effectively and substantially increase patient adherence to cancer clinic appointments and improve adherence to cancer care.
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