Managing prior approval for site-of-service referrals: an algorithmic approach
Abstract Objectives Many 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 f...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2022-02-01
|
| Series: | BMC Health Services Research |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12913-022-07523-3 |
| _version_ | 1819277890935586816 |
|---|---|
| author | Maqbool Dada Vishal Mundly Chester G. Chambers Mohammad Ali Alamdar Yazdi Changhun Ha Sonia E. Toporcer Yi Zhou Yunong Gan Zhihua Xing Mark Mooney Ernest Smith Edward Kumian Kayode A. Williams |
| author_facet | Maqbool Dada Vishal Mundly Chester G. Chambers Mohammad Ali Alamdar Yazdi Changhun Ha Sonia E. Toporcer Yi Zhou Yunong Gan Zhihua Xing Mark Mooney Ernest Smith Edward Kumian Kayode A. Williams |
| author_sort | Maqbool Dada |
| collection | DOAJ |
| description | Abstract Objectives Many 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 Design We 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. Methods We 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. Results Data 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. Conclusions Instituting 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. |
| first_indexed | 2024-12-24T00:03:18Z |
| format | Article |
| id | doaj.art-2cb33a1ff3484ae882e73517e329236d |
| institution | Directory Open Access Journal |
| issn | 1472-6963 |
| language | English |
| last_indexed | 2024-12-24T00:03:18Z |
| publishDate | 2022-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Health Services Research |
| spelling | doaj.art-2cb33a1ff3484ae882e73517e329236d2022-12-21T17:25:04ZengBMCBMC Health Services Research1472-69632022-02-012211710.1186/s12913-022-07523-3Managing prior approval for site-of-service referrals: an algorithmic approachMaqbool Dada0Vishal Mundly1Chester G. Chambers2Mohammad Ali Alamdar Yazdi3Changhun Ha4Sonia E. Toporcer5Yi Zhou6Yunong Gan7Zhihua Xing8Mark Mooney9Ernest Smith10Edward Kumian11Kayode A. Williams12Johns Hopkins Carey Business SchoolJohns Hopkins Healthcare LLCJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Carey Business SchoolJohns Hopkins Healthcare LLCJohns Hopkins Healthcare LLCJohns Hopkins Healthcare LLCJohns Hopkins Carey Business SchoolAbstract Objectives Many 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 Design We 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. Methods We 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. Results Data 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. Conclusions Instituting 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.https://doi.org/10.1186/s12913-022-07523-3Site of service referralsManaged careMedicaid managed care organizations |
| spellingShingle | Maqbool Dada Vishal Mundly Chester G. Chambers Mohammad Ali Alamdar Yazdi Changhun Ha Sonia E. Toporcer Yi Zhou Yunong Gan Zhihua Xing Mark Mooney Ernest Smith Edward Kumian Kayode A. Williams Managing prior approval for site-of-service referrals: an algorithmic approach BMC Health Services Research Site of service referrals Managed care Medicaid managed care organizations |
| title | Managing prior approval for site-of-service referrals: an algorithmic approach |
| title_full | Managing prior approval for site-of-service referrals: an algorithmic approach |
| title_fullStr | Managing prior approval for site-of-service referrals: an algorithmic approach |
| title_full_unstemmed | Managing prior approval for site-of-service referrals: an algorithmic approach |
| title_short | Managing prior approval for site-of-service referrals: an algorithmic approach |
| title_sort | managing prior approval for site of service referrals an algorithmic approach |
| topic | Site of service referrals Managed care Medicaid managed care organizations |
| url | https://doi.org/10.1186/s12913-022-07523-3 |
| work_keys_str_mv | AT maqbooldada managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT vishalmundly managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT chestergchambers managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT mohammadalialamdaryazdi managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT changhunha managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT soniaetoporcer managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT yizhou managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT yunonggan managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT zhihuaxing managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT markmooney managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT ernestsmith managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT edwardkumian managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach AT kayodeawilliams managingpriorapprovalforsiteofservicereferralsanalgorithmicapproach |