ArticleApplied clinical informatics2016
Appointment Lead Time Policy Development to Improve Patient Access to Care.
Article in Applied clinical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Neurology Access Clinic: A Model to Improve Access to Neurologic Care in an Academic Medical Center.Neurology. Clinical practice · 2022Article
- Patient scheduling based on a service-time prediction model: a data-driven study for a radiotherapy center.Health care management science · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPatient access to care has been a known and continuing struggle for many health care providers. In spite of appointment lead time policies set by government or clinics, the problem persists. Justification for how lead time policies are determined is lacking.
objectivesThis paper proposed a data-driven approach for how to best set feasible appointment target lead times given a clinic's capacity and appointment requests.
methodsThe proposed approach reallocates patient visits to minimize the deviation between actual appointment lead time and a feasible target lead time. A step-by-step algorithm was presented and demonstrated for return visit (RV) and new patient (NP) types from a Pediatric clinic excluding planned visits such as well-child exam and the same day urgent appointments. The steps are: 1. Obtain appointment requests; 2. Initialize a target lead time; 3. Set up an initial schedule; 4. Check the feasibility based on appointment availability; 5. Adjust schedule backward to fill appointment slots earlier than the target; 6. Adjust schedule forward for appointments not able to be scheduled earlier or on target to the later slots; 7. Trial different target lead times until the difference between earlier and later lead time is minimized.
resultsThe results indicated a 59% lead time reduction for RVs and a 45% reduction for NPs. The lead time variation was reduced by 75% for both patient types. Additionally, the opportunity for the participating clinic to achieve their organization's goal of a two-week lead time for RVs and a two-day lead time for NPs is discussed by adjusting capacity to increase one slot for NP and reduce one slot for RV.
conclusionsThe proposed approach and study findings may help clinics identify feasible appointment lead times.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.