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Accepted for/Published in: JMIR Formative Research

Date Submitted: Aug 5, 2021
Date Accepted: Aug 23, 2022

The final, peer-reviewed published version of this preprint can be found here:

Bolstering the Business Case for Adoption of Shared Decision-Making Systems in Primary Care: Randomized Controlled Trial

Sperl-Hillen JM, Anderson JP, Margolis KL, Rossom RC, Kopski KM, Averbeck BM, Rosner JA, Ekstrom HL, Dehmer SP, O’Connor PJ

Bolstering the Business Case for Adoption of Shared Decision-Making Systems in Primary Care: Randomized Controlled Trial

JMIR Form Res 2022;6(10):e32666

DOI: 10.2196/32666

PMID: 36201392

PMCID: 9585448

Bolstering the Business Case for Primary Care Adoption of Shared Decision Making Systems: Randomized Controlled Trial

  • JoAnn M. Sperl-Hillen; 
  • Jeffrey P. Anderson; 
  • Karen L. Margolis; 
  • Rebecca C. Rossom; 
  • Kristen M. Kopski; 
  • Beth M. Averbeck; 
  • Jeanine A. Rosner; 
  • Heidi L. Ekstrom; 
  • Steven P. Dehmer; 
  • Patrick J. O’Connor

ABSTRACT

Background:

Background:

Tight budgets can be a barrier for health systems to adopt clinical decision support (CDS) for some clinical conditions

Objective:

Objective:

To assess the effect of a CDS system previously shown to improve diabetes and cardiovascular outcomes on factors affecting revenue generation in primary care clinics.

Methods:

Methods:

As part of a large multisite clinic randomized controlled trial (RCT), we explored the differences at one care system between CDS system intervention clinics (n=8) and control clinics (n=9) on (a) likelihood of ICD-10 diagnostic coding for cardiometabolic conditions and (b) Current Procedural Terminology (CPT) billing codes documented by clinicians.

Results:

Results:

For all 24,138 encounters with care gaps targeted by the CDS, the proportion with high complexity CPT level of service 5 was increased at intervention clinics (6.1%) compared to control (2.9%), p < .001, adjusted OR1.64 (1.02, 2.61), and for specific care gaps as follows: diabetes with A1C > 8% (n=8,463), 7.2% vs. 3.4%, p<.001, adjusted OR 1.93 (1.01, 3.67); blood pressure above goal (n=8515), 6.5% vs. 3.7%, p<.001, adjusted OR 1.42 (.72-2.79); suboptimal statin management (n=17,765), 5.8% vs. 3.0%, p<.001, adjusted OR 1.41 (0.76, 2.61); tobacco dependency (n=7449), 7.5% vs. 3.4%, p<.001, adjusted OR 2.14 (1.31, 3.51); BMI >30 (n=19,838), 6.2% vs. 2.9%, p<.001, adjusted OR 1.45 (.75, 2.80). At intervention clinics compared to control, the likelihood of ICD-10 coding also trended higher for all the diabetes and cardiometabolic conditions targeted by the CDS.

Conclusions:

Conclusions:

The association of CDS use in intervention clinics with (a) a significantly higher proportion of all encounters with identified care gaps receiving a higher complexity CPT code (level 5) after adjusting for patient demographics and clustering at clinics and (b) an increase in appropriate ICD10 visit coding trends suggests that revenue generation related to CDS use may offset expenses related to CDS adoption and maintenance. Thus, CDS can align with incentives for both value-based and fee-for-service reimbursement of care delivery. Clinical Trial: clinicaltrials.gov identifier NCT 02451670, 10-23-2014


 Citation

Please cite as:

Sperl-Hillen JM, Anderson JP, Margolis KL, Rossom RC, Kopski KM, Averbeck BM, Rosner JA, Ekstrom HL, Dehmer SP, O’Connor PJ

Bolstering the Business Case for Adoption of Shared Decision-Making Systems in Primary Care: Randomized Controlled Trial

JMIR Form Res 2022;6(10):e32666

DOI: 10.2196/32666

PMID: 36201392

PMCID: 9585448

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