Modeling Outcomes of Earlier ART Initiation in the U.S.
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Modeling outcomes in HIV care can provide insight into future trends and costs relating to various care strategies. Now, researchers have used a Monte Carlo health-state transition simulation to predict long-term outcomes for a hypothetical 10,000 patients in each of four CD4-count categories on care entry: ≤200, 201–350, 351–500, and 501–900 cells/mm3. They assumed that a patient entering care at a CD4 count >500 cells/mm3 would …Context: The transition to population health management has changed the healthcare landscape to identify high risk, high cost patients. Various measures of patient risk have attempted to identify likely candidates for care management programs. Pre-screening patients for outreach has often required several years of data. Intermountain Healthcare relied on cost-ranking algorithms which had limited predictive ability. A new risk-adjusted algorithm shows improvements in predicting patients’ future cost status to facilitate identifying patient eligibility for care management.Case Description: A retrospective cohort study design was used to evaluate high-cost patient status for two of the next three years. Modeling was developed using logistic regression and tested against other decision tree methods. Key variables included those readily available in electronic health records supplemented by additional clinical data and estimates of socio-economic status.Findings: The risk-adjusted modeling correctly identified 79.0% of patients ranking among the top 15% of costs in one of the next three years. In addition, it correctly estimated 48.1% of the patients in the top 15% cost group in two of the next three years. This method identified patients with higher medical costs and more comorbid conditions than previous cost-ranking methods.Major Themes: This approach improves the predictive accuracy of identifying high cost patients in the future and increases the sensitivity of identifying at-risk patients. It also shortened data requirements to identify eligibility criteria for case management interventions.Conclusion: Risk-adjustment modeling may improve management programs’ interface with patients thus decreasing costs. This method may be generalized to other healthcare settings.
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The International Journal of Integrated Care (IJIC) is an online, open-access, peer-reviewed scientific journal that publishes original articles in the field of integrated care on a continuous basis.IJIC has an Impact Factor of 5.120 (2020 JCR, received in June 2021)
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Given that many hospitalized patients return within 30 days, identifying those at greatest risk for rehospitalization would aid in targeting care-transition interventions and limiting readmissions. To assess how well validated readmission risk-prediction models work, researchers performed a systematic review of 30 studies (26 unique models) involving a variety of patient populations and clinical settings. …
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Abstract Introduction Differentiated service delivery (DSD) models for antiretroviral treatment (ART) for HIV are being scaled up in the expectation that they will better meet the needs of patients, improve the quality and efficiency of treatment delivery and reduce costs while maintaining at least equivalent clinical outcomes. We reviewed the recent literature on DSD models to describe what is known about clinical outcomes. Methods We conducted a rapid systematic review of peer‐reviewed publications in PubMed, Embase and the Web of Science and major international conference abstracts that reported outcomes of DSD models for the provision of ART in sub‐Saharan Africa from January 1, 2016 to September 12, 2019. Sources reporting standard clinical HIV treatment metrics, primarily retention in care and viral load suppression, were reviewed and categorized by DSD model and source quality assessed. Results and discussion Twenty‐nine papers and abstracts describing 37 DSD models and reporting 52 discrete outcomes met search inclusion criteria. Of the 37 models, 7 (19%) were facility‐based individual models, 12 (32%) out‐of‐facility‐based individual models, 5 (14%) client‐led groups and 13 (35%) healthcare worker‐led groups. Retention was reported for 29 (78%) of the models and viral suppression for 22 (59%). Where a comparison with conventional care was provided, retention in most DSD models was within 5% of that for conventional care; where no comparison was provided, retention generally exceeded 80% (range 47% to 100%). For viral suppression, all those with a comparison to conventional care reported a small increase in suppression in the DSD model; reported suppression exceeded 90% (range 77% to 98%) in 11/21 models. Analysis was limited by the extensive heterogeneity of study designs, outcomes, models and populations. Most sources did not provide comparisons with conventional care, and metrics for assessing outcomes varied widely and were in many cases poorly defined. Conclusions Existing evidence on the clinical outcomes of DSD models for HIV treatment in sub‐Saharan Africa is limited in both quantity and quality but suggests that retention in care and viral suppression are roughly equivalent to those in conventional models of care.
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