Evidence map›Paper›PMID 35164749›Full record

ArticleBMC health services research2022

Managing prior approval for site-of-service referrals: an algorithmic approach.

Maqbool Dada, Vishal Mundly, Chester G Chambers, Mohammad Ali Alamdar Yazdi, Changhun Ha, Sonia E Toporcer, Yi Zhou, Yunong Gan, Zhihua Xing, Mark Mooney and 3 more

Abstract read
In one paragraph

Article in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Maqbool DadaJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA. dada@jhu.edu.
Vishal MundlyJohns Hopkins Healthcare LLC, 7231 Parkway Drivr Suite 100, Hanover, MD, 21076, USA.
Chester G ChambersJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Mohammad Ali Alamdar YazdiJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Changhun HaJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Sonia E ToporcerJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Yi ZhouJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Yunong GanJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Zhihua XingJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.
Mark MooneyJohns Hopkins Healthcare LLC, 7231 Parkway Drivr Suite 100, Hanover, MD, 21076, USA.
Ernest SmithJohns Hopkins Healthcare LLC, 7231 Parkway Drivr Suite 100, Hanover, MD, 21076, USA.
Edward KumianJohns Hopkins Healthcare LLC, 7231 Parkway Drivr Suite 100, Hanover, MD, 21076, USA.
Kayode A WilliamsJohns Hopkins Carey Business School, 100 International Drive, Baltimore, MD, 21202, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesMany payers and health care providers are either currently using or considering use of prior authorization schemes to redirect patient care away from hospital outpatient departments toward free-standing ambulatory surgical centers owing to the payment differential between these facilities. In this work we work with a medium size payer to develop and lay out a process for analysis of claims data that allows payers to conservatively estimate potential savings from such policies based on their specific case mix and provider network. STUDY

designWe analyzed payment information for a medium-sized managed care organization to identify movable cases that can reduce costs, estimate potential savings, and recommend implementation policy alternatives.

methodsWe analyze payment data, including all professional and institutional fees over a 15-month period. A rules-based algorithm was developed to identify episodes of care with at least one alternate site for each episode, and potential savings from a site-of-service policy.

resultsData on 64,884 episodes of care were identified as possible instances that could be subject to the policy. Of those, 7,679 were found to be attractive candidates for movement. Total projected savings was approximately $8.2 million, or over $1,000 per case.

conclusionsInstituting a site-of-service policy can produce meaningful savings for small and medium payers. Tailoring the policy to the specific patient and provider population can increase the efficacy of such policies in comparison to policies previously established by other payers.

Indexed as

Ambulatory Care FacilitiesPrior AuthorizationCosts and Cost AnalysisHealth PersonnelHumansReferral and ConsultationUnited StatesManaged careMedicaid managed care organizationsSite of service referrals

Identifiers

PMID35164749
PMCPMC8845286

What OpenQuestion holds

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LicenceCC BY
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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.