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1.
BMJ Open ; 14(1): e081158, 2024 01 24.
Article in English | MEDLINE | ID: mdl-38267242

ABSTRACT

OBJECTIVE: Reducing backlogs for elective care is a priority for healthcare systems. We conducted an interrupted time series analysis demonstrating the effect of an algorithm for placing automatic test order sets prior to first specialist appointment on avoidable follow-up appointments and attendance rates. DESIGN: Interrupted time series analysis. SETTING: 4 academic hospitals from Madrid, Spain. PARTICIPANTS: Patients referred from primary care attending 10 033 470 outpatient appointments from 16 clinical specialties during a 6-year period (1 January 2018 to 30 June 2023). INTERVENTION: An algorithm using natural language processing was launched in May 2021. Test order sets developed for 257 presenting complaints from 16 clinical specialties were placed automatically before first specialist appointments to increase rates of diagnosis and initiation of treatment with discharge back to primary care. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcomes included rate of diagnosis and discharge to primary care and follow-up to first appointment index. The secondary outcome was trend in 'did not attend' rates. RESULTS: Since May 2021, a total of 1 175 814 automatic test orders have been placed. Significant changes in trend of diagnosis and discharge to primary care at first appointment (p=0.005, 95% CI 0.5 to 2.9) and 'did not attend' rates (p=0.006, 95% CI -0.1 to -0.8) and an estimated attributable reduction of 11 306 avoidable follow-up appointments per month were observed. CONCLUSION: An algorithm for placing automatic standardised test order sets can reduce low-value follow-up appointments by allowing specialists to confirm diagnoses and initiate treatment at first appointment, also leading to early discharge to primary care and a reduction in 'did not attend' rates. This initiative points to an improved process for outpatient diagnosis and treatment, delivering healthcare more effectively and efficiently.


Subject(s)
Body Fluids , Hospitals, Teaching , Humans , Interrupted Time Series Analysis , Algorithms , Cognition
2.
Eur J Public Health ; 29(3): 413-418, 2019 06 01.
Article in English | MEDLINE | ID: mdl-30544169

ABSTRACT

BACKGROUND: There is little empirical research on the potential benefit that electronic patient portals (EPP) can have on the care quality and health outcomes of diverse multi-ethnic international populations. The purpose of this study is to determine the extent to which an EPP was associated with improvements in health service use. METHODS: Using a quasi-experimental interrupted time-series approach, we assessed health service use before (April 2012-September 2015) and after (October 2015-December 2016) the implementation of a comprehensive EPP at four hospitals in Madrid, Spain. Primary outcomes were number of outpatient visits, any hospital admission, any 30-day all-cause readmission and any emergency department visit. RESULTS: Implementation of the EPP was associated with a significant decline in readmissions. Among patients with chronic heart failure, EPP implementation was associated with a significant decline for all outcome measures, and among patients with COPD, a decline in all outcomes except readmissions. Among patients diagnosed with malignant hematological diseases, no significant changes were identified. CONCLUSIONS: EPPs hold promise for reducing hospital readmissions. Certain patient populations with chronic conditions may differentially benefit from portal use depending on their needs for communication with their providers.


Subject(s)
Patient Portals , Utilization Review , Ambulatory Care/statistics & numerical data , Chronic Disease , Emergency Service, Hospital/statistics & numerical data , Health Services Research , Hospitalization/statistics & numerical data , Humans , Interrupted Time Series Analysis , Patient Readmission/statistics & numerical data , Spain
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