- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06419725
Temporal Trends in Nonattendence Rate for Scheduled Outpatient Appointments.
May 14, 2024 updated by: LUCIA.PEREZ, Hospital Italiano de Buenos Aires
Ecological time-series study using secondary databases.
Study Overview
Status
Completed
Conditions
Detailed Description
A time-series study will be conducted to evaluate nonattendance over time.
The unit of analysis will be the appointment.
Study Type
Observational
Enrollment (Actual)
13823093
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Locations
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Ciudad Autonoma de Buenos Aire, Argentina, 1406
- Hospital Italiano de Buenos Aires
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Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
N/A
Sampling Method
Probability Sample
Study Population
The study population comprises individuals who requested at least one appointment for scheduled outpatient medical care at Hospital Italiano de Buenos Aires during the study period in any of its settings.
Description
Inclusion Criteria:
- Appointments scheduled for outpatient medical care across all settings and specialties from January 1, 2016, to December 31, 2023
Exclusion Criteria:
- Cancelled appointments, including cancellations made by the patient, medical team, and the appointment management system.
- Appointments that do not correspond to scheduled in-person care (Teleconsultations,
- Appointments for walk-in demand).
- Scheduled appointments that are not for medical care (Health coverage or specialties that do not correspond to scheduled medical care, Appointments for procedures,
- Appointments for complementary exams, Appointments for treatments such as speech therapy, physiotherapy, or other therapies).
- Spontaneous overflow appointments where the patient spontaneously presents for care at that moment. These appointments cannot be absent as the present and the appointment are assigned simultaneously.
- System errors that do not correspond to actual patient medical care appointments (Duplicate cancellations, Appointments where patient and physician coincide).
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Time Frame |
---|---|
Describe the behavior over time of the nonattendance proportion in scheduled outpatient medical appointments for in-person medical care over an 8-year period (globally and by subgroups: gender, age, medical specialty, and medical coverage).
Time Frame: 2016 to 2023
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2016 to 2023
|
Evaluate temporal trends and changes (joinpoints) in the absenteeism proportion in scheduled outpatient medical appointments for in-person medical care over the same period.
Time Frame: 2016 to 2023
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2016 to 2023
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Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- Colubi MM, Perez-Elias MJ, Elias L, Pumares M, Muriel A, Zamora AM, Casado JL, Dronda F, Lopez D, Moreno S; SEAD Study Group. Missing scheduled visits in the outpatient clinic as a marker of short-term admissions and death. HIV Clin Trials. 2012 Sep-Oct;13(5):289-95. doi: 10.1310/hct1305-289.
- Kheirkhah P, Feng Q, Travis LM, Tavakoli-Tabasi S, Sharafkhaneh A. Prevalence, predictors and economic consequences of no-shows. BMC Health Serv Res. 2016 Jan 14;16:13. doi: 10.1186/s12913-015-1243-z.
- Giunta DH, Alonso Serena M. Nonattendance rates of scheduled outpatient appointments in a university general hospital. Int J Health Plann Manage. 2019 Oct;34(4):1377-1385. doi: 10.1002/hpm.2797. Epub 2019 May 7.
- Giunta D, Briatore A, Baum A, Luna D, Waisman G, de Quiros FG. Factors associated with nonattendance at clinical medicine scheduled outpatient appointments in a university general hospital. Patient Prefer Adherence. 2013 Nov 8;7:1163-70. doi: 10.2147/PPA.S51841. eCollection 2013.
- Giunta DH, Alonso Serena M, Luna D, Peroni ML, Sanchez Thomas D, Binder F, Blugerman GA, Fuentes N, Elizondo CM, Gonzalez Bernaldo de Quiros F. Association between non-attendance to outpatient clinics and emergency department consultations, hospitalizations and mortality in a Health Maintenance Organization. Int J Health Plann Manage. 2020 Sep;35(5):1140-1156. doi: 10.1002/hpm.3021. Epub 2020 Jul 9.
- Carrillo GJS. Adhesión de los pacientes a las consultas de control ambulatorio. Investigación en Enfermería: Imagen y Desarrollo. 2011;9: 51-62.
- Berg BP, Murr M, Chermak D, Woodall J, Pignone M, Sandler RS, Denton BT. Estimating the cost of no-shows and evaluating the effects of mitigation strategies. Med Decis Making. 2013 Nov;33(8):976-85. doi: 10.1177/0272989X13478194. Epub 2013 Mar 20.
- Jabalera Mesa ML, Morales Asencio JM, Rivas Ruiz F, Porras Gonzalez MH. [Analysis of economic cost of missed outpatient appointments]. Rev Calid Asist. 2017 Jul-Aug;32(4):194-199. doi: 10.1016/j.cali.2017.01.004. Epub 2017 May 2. Spanish.
- George A, Rubin G. Non-attendance in general practice: a systematic review and its implications for access to primary health care. Fam Pract. 2003 Apr;20(2):178-84. doi: 10.1093/fampra/20.2.178.
- Wolff DL, Waldorff FB, von Plessen C, Mogensen CB, Sorensen TL, Houlind KC, Bogh SB, Rubin KH. Rate and predictors for non-attendance of patients undergoing hospital outpatient treatment for chronic diseases: a register-based cohort study. BMC Health Serv Res. 2019 Jun 14;19(1):386. doi: 10.1186/s12913-019-4208-9.
- Karter AJ, Parker MM, Moffet HH, Ahmed AT, Ferrara A, Liu JY, Selby JV. Missed appointments and poor glycemic control: an opportunity to identify high-risk diabetic patients. Med Care. 2004 Feb;42(2):110-5. doi: 10.1097/01.mlr.0000109023.64650.73.
- Lee RRS, Samsudin MI, Thirumoorthy T, Low LL, Kwan YH. Factors affecting follow-up non-attendance in patients with Type 2 diabetes mellitus and hypertension: a systematic review. Singapore Med J. 2019 May;60(5):216-223. doi: 10.11622/smedj.2019042.
- Srisaenpang S, Pinitsoontorn S, Singhasivanon P, Kitayaporn D, Kaewkungwal J, Tatsanavivat P, Patjanasoontorn B, Reechaipichitkul W, Thiratakulpisan J, Srinakarin J, Srisaenpang P, Thinkamrop B, Apinyanurak C, Chindawong BO. Missed appointments at a tuberculosis clinic increased the risk of clinical treatment failure. Southeast Asian J Trop Med Public Health. 2006 Mar;37(2):345-50.
- Ayten Turkcan & Lynn Nuti & Po-Ching DeLaurentis & Zhiyi Tian & Joanne Daggy & Lingsong Zhang & Mark Lawley & Laura Sands, 2013.
- Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications to cancer rates. Stat Med. 2000 Feb 15;19(3):335-51. doi: 10.1002/(sici)1097-0258(20000215)19:33.0.co;2-z. Erratum In: Stat Med 2001 Feb 28;20(4):655.
- Daniel L, Paula O, Alejandro LO, Eduardo R, Federico P, Adrián G, et al. Implementación de una Historia Clínica Electrónica Ambulatoria: El Proyecto Itálica. 6to Simposio de Informática en Salud - 32 JAIIO 2003. 2003.
- Plazzotta F, Luna D, Gonzalez Bernaldo de Quiros F. [Health information systems: integrating clinical data in different scenarios and users]. Rev Peru Med Exp Salud Publica. 2015 Apr-Jun;32(2):343-51. Spanish.
- Franco M, Giussi Bordoni MV, Otero C, Landoni MC, Benitez S, Borbolla D, Luna D. Problem Oriented Medical Record: Characterizing the Use of the Problem List at Hospital Italiano de Buenos Aires. Stud Health Technol Inform. 2015;216:877.
- Luna D, Franco M, Plaza C, Otero C, Wassermann S, Gambarte ML, Giunta D, Gonzalez Bernaldo de Quiros F. Accuracy of an electronic problem list from primary care providers and specialists. Stud Health Technol Inform. 2013;192:417-21.
- Plazzotta F, Otero C, Luna D, de Quiros FG. Natural language processing and inference rules as strategies for updating problem list in an electronic health record. Stud Health Technol Inform. 2013;192:1163.
- Torre LA, Siegel RL, Ward EM, Jemal A. International variation in lung cancer mortality rates and trends among women. Cancer Epidemiol Biomarkers Prev. 2014 Jun;23(6):1025-36. doi: 10.1158/1055-9965.EPI-13-1220. Epub 2014 May 16.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
January 1, 2016
Primary Completion (Actual)
December 31, 2023
Study Completion (Actual)
December 31, 2023
Study Registration Dates
First Submitted
May 14, 2024
First Submitted That Met QC Criteria
May 14, 2024
First Posted (Actual)
May 17, 2024
Study Record Updates
Last Update Posted (Actual)
May 17, 2024
Last Update Submitted That Met QC Criteria
May 14, 2024
Last Verified
May 1, 2024
More Information
Terms related to this study
Other Study ID Numbers
- 6922
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
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