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User-driven health care - answering multidimensional information needs in individual patients utilizing post-EBM approaches: a conceptual model

Biswas R, Martin CM, Sturmberg J, Shanker R, Umakanth S, Shanker S, et al.

J Eval Clin Pract, 2008 Oct;14(5):742-9.
PMID: 19018905 DOI: 10.1111/j.1365-2753.2008.00998.x

Evidence based on average patient data, which occupies most of our present day information databases, does not fulfil the needs of individual patient-centred health care. In spite of the unprecedented expansion in medical information we still do not have the types of information required to allow us to tailor optimal care for a given individual patient. As our current information is chiefly provided in disconnected silos, we need an information system that can seamlessly integrate different types of information to meet diverse user group needs. Groups of certain individual medical learners namely patients, medical students and health professionals share the patient's need to increasingly interact with and seek knowledge and solutions offered by others (individual medical learners) who have the lived experiences that they would benefit to access and learn from. A web-based user-driven learning solution may be a stepping-stone to address the present problem of information oversupply in medicine that mostly remains underutilized, as it doesn't meet the needs of the individual patient and health professional user. The key to its success would be to relax central control and make local trust and strategic health workers feel more engaged in the project such that it is truly user-driven.

Matched MeSH terms: Observation
Fulltext When to initiate combined antiretroviral therapy to reduce mortality and AIDS-defining illness in HIV-infected persons in developed countries: an observational study

HIV-CAUSAL Collaboration, Cain LE, Logan R, Robins JM, Sterne JA, Sabin C, et al.

Ann Intern Med, 2011 Apr 19;154(8):509-15.
PMID: 21502648 DOI: 10.7326/0003-4819-154-8-201104190-00001

BACKGROUND: Most clinical guidelines recommend that AIDS-free, HIV-infected persons with CD4 cell counts below 0.350 × 10(9) cells/L initiate combined antiretroviral therapy (cART), but the optimal CD4 cell count at which cART should be initiated remains a matter of debate.
OBJECTIVE: To identify the optimal CD4 cell count at which cART should be initiated.
DESIGN: Prospective observational data from the HIV-CAUSAL Collaboration and dynamic marginal structural models were used to compare cART initiation strategies for CD4 thresholds between 0.200 and 0.500 × 10(9) cells/L.
SETTING: HIV clinics in Europe and the Veterans Health Administration system in the United States.
PATIENTS: 20, 971 HIV-infected, therapy-naive persons with baseline CD4 cell counts at or above 0.500 × 10(9) cells/L and no previous AIDS-defining illnesses, of whom 8392 had a CD4 cell count that decreased into the range of 0.200 to 0.499 × 10(9) cells/L and were included in the analysis.
MEASUREMENTS: Hazard ratios and survival proportions for all-cause mortality and a combined end point of AIDS-defining illness or death.
RESULTS: Compared with initiating cART at the CD4 cell count threshold of 0.500 × 10(9) cells/L, the mortality hazard ratio was 1.01 (95% CI, 0.84 to 1.22) for the 0.350 threshold and 1.20 (CI, 0.97 to 1.48) for the 0.200 threshold. The corresponding hazard ratios were 1.38 (CI, 1.23 to 1.56) and 1.90 (CI, 1.67 to 2.15), respectively, for the combined end point of AIDS-defining illness or death.
LIMITATIONS: CD4 cell count at cART initiation was not randomized. Residual confounding may exist.
CONCLUSION: Initiation of cART at a threshold CD4 count of 0.500 × 10(9) cells/L increases AIDS-free survival. However, mortality did not vary substantially with the use of CD4 thresholds between 0.300 and 0.500 × 10(9) cells/L.

Matched MeSH terms: Observation

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