Estimating the hospital costs of care for people living with HIV in England using routinely collected data

Author:

Miners Alec1ORCID,Lampe Fiona C.2ORCID,Cambiano Valentina2ORCID,Schwenk Achim3,Rodger Alison2ORCID,Sadique Zia1ORCID,Rein Sophia2ORCID,Delpech Valerie4ORCID,Phillips Andrew N.2ORCID

Affiliation:

1. Department of Public Health and Policy London School of Hygiene and Tropical Medicine London UK

2. Institute for Global Health University College London London UK

3. North London Partners in Health and Care London UK

4. UK Health Security Agency London UK

Abstract

AbstractBackgroundUnderstanding the health care activity and associated hospital costs of caring for people living with HIV is an important component of assessing the cost effectiveness of new technologies and for budget planning.MethodsData collected between 2010 and 2017 from an English HIV treatment centre were combined with national reference costs to estimate the rate of hospital attendances and costs per quarter year, according to demographic and clinical factors. The final dataset included records for 1763 people living with HIV, which was analysed using negative binomial regression models and general estimating equations.ResultsPeople living with HIV experienced an unadjusted average of 0.028 (standard deviation [SD] 0.20) inpatient episodes per quarter, equivalent to one every 9 years, and 1.85 (SD 2.30) outpatient visits per quarter. The unadjusted mean quarterly cost per person with HIV (excluding antiretroviral drug costs) was £439 (SD 604). Outpatient appointments and inpatient episodes accounted for 88% and 6% of total costs, respectively. In adjusted models, low CD4 count was the strongest predictor of inpatient stays and outpatient visits. Low CD4 count and new patient status (having a first visit at the Trust in the last 6 months) were the factors that most increased estimated costs. Associations were weaker or less consistent for demographic factors (age, sex/sexual orientation/ethnicity). Sensitivity analyses suggest that the findings were generally robust to alternative parameter and modelling assumptions.ConclusionA number of factors predicted hospital activity and costs, but CD4 cell count and new patient status were the strongest. The study results can be incorporated into future economic evaluations and budget impact assessments of HIV‐related technologies.

Publisher

Wiley

Subject

Pharmacology (medical),Infectious Diseases,Health Policy

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