Evidence map›Paper›PMID 39187724›Full record

ArticleJournal of community health2025

Digital Reimbursement Systems in a Student-Run Clinic.

Parsa Nilchian, Subhanik Purkayastha, Gianni Thomas, Kaya L Curtis, Natalia Roszkowska, Elizabeth K Benitez, Tiffany Merlinsky, Michael Farid, Cecilia E W Nicol, Ashita S Batavia and 1 more

Abstract read
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Article in Journal of community health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Parsa NilchianWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA. pan4004@med.cornell.edu.ORCID 0000-0002-1460-5946
Subhanik PurkayasthaWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0003-3067-2070
Gianni ThomasWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.
Kaya L CurtisWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0001-6207-5989
Natalia RoszkowskaWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0002-7365-3956
Elizabeth K BenitezWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0001-5797-922X
Tiffany MerlinskyWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0001-8983-2425
Michael FaridWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0002-6734-9931
Cecilia E W NicolWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.
Ashita S BataviaWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.ORCID 0000-0002-4209-8654
Pamela CharneyWeill Cornell Community Clinic, Weill Cornell Medical College, 1300 York Avenue, New York, NY, 10021, USA.

Funding

Weill Cornell/Rockefeller/Sloan Kettering MST ProgramT32GM152349 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI KATHARINE C HSU · 2024 to 2026
$6.6M
6 · The paper itself

Abstract

The increasing reliance on digital tools for standard healthcare practices in uninsured populations is poorly understood. This study aims to assess the impacts of a newly implemented digital reimbursement system at a student-run primary care clinic associated with an academic medical institution serving uninsured New York City residents. Pharmacy records of 94 unique patients receiving a total of 2770 reimbursements between October 17th, 2016, and May 18th, 2023, were analyzed. Patients were divided into two groups (in-person vs. digital) based on their reimbursement preferences type. Demographic analyses were performed in addition to assessing reimbursement volumes, number of refunds, and duration until receipt of payment for each group. The clinic's total monthly reimbursement volume, number of prescriptions, and number of patients for the period before introduction of digital refunds was compared to the period after. The mean age (in-person = 52.7 ± 14.7 years, digital = 54.9 ± 12.9 years) was not statistically different between the groups. Patients in the digital group requested on average more refunds (digital = 47 refunds, in-person = 14 refunds), received higher total reimbursement amount (digital = $1131.24, in-person = $289.36), and they were reimbursed faster (digital = 56 days, in-person = 62 days). Since the introduction of the digital reimbursement option, our three-month reimbursement volume more than doubled from $481 to $1298. The average number of monthly reimbursements increased from 27 to 45 refunds, and the number of monthly patients increased from 6 to 9 patients. In summary, digital reimbursement options can facilitate medication reimbursement among uninsured patients. These results suggest that digital reimbursement systems result in higher utilization, faster refunds, and larger total reimbursements amount for uninsured and underserved patients.

Indexed as

Primary Health CareReimbursement MechanismsStudent Run ClinicAdultAgedFemaleHumansMaleMedically UninsuredMiddle AgedNew York CityDigital reimbursement systemsDigital transformationStudent-run primary care clinicUninsured patients

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Registered trials

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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.