Operational Waste Management Model Articulated Between Insurer Health and Pharmaceutical Benefit Manager

Author(s)

Hernández D1, Cardona JD1, Restrepo AM2, Tabares JE2, Abad JM1, Serna JA2, Estrada Acevedo JI3, Giraldo PA2, Madrigal Cadavid J4
1SURA EPS, Medellin, Colombia, 2+helPharma IPS, Medellin, Colombia, 3+helPharma IPS, Colombia, 4+helPharma IPS, Medellin, ANT, Colombia

Presentation Documents

OBJECTIVES: To describe the results of an operational waste management model articulated between the insurer health and the pharmaceutical benefit manager.

METHODS: a descriptive observational study, conducted between November 2020 - May 2021 in patients diagnosed with high-cost chronic pathologies. The pharmacists screened the patient prescriptions before dispensing their medications to identify and manage operational wasteful in an articulated way between the insurer health and the pharmaceutical benefit manager. A univariate analysis was performed, with summary measures of central tendency and relative and cumulative frequencies. R Core Team statistical package (2019) was used.

RESULTS: 2099 patients were managed with a mean age of 67 years (SD: 4) and 62.0% were women. Operational wasteful were identified and managed in 1.8% of the patients evaluated, representing 1103026.18 USD (157575.17 USD an average month). The main causes of operational waste were 41.4% authorizations of drugs that had already been previously suspended by the treating physician, 21.8% drug authorization error, 18.5%, prescriptions error, 10.2% redundant prescription, 5.7% deceased patient with prescription, 2.3% patient’s non-adherence. The acceptance rate of the interventions was 100%.

CONCLUSIONS: The articulation between the insurer health and the pharmaceutical benefit manager demonstrates that the identification and management of operational waste allow the optimization of the health system resources.

Conference/Value in Health Info

2021-11, ISPOR Europe 2021, Copenhagen, Denmark

Value in Health, Volume 24, Issue 12, S2 (December 2021)

Code

POSA395

Topic

Clinical Outcomes, Economic Evaluation, Health Service Delivery & Process of Care, Methodological & Statistical Research

Topic Subcategory

Artificial Intelligence, Machine Learning, Predictive Analytics, Clinical Outcomes Assessment, Pharmacist Interventions and Practices

Disease

Drugs, Multiple Diseases

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