GP assessment of unmet need in a complex multimorbid population using a data-driven and clinical triage system: a prospective cohort study

利用数据驱动的临床分诊系统对复杂多病人群中未满足的医疗需求进行全科医生评估:一项前瞻性队列研究

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Abstract

BACKGROUND: Patients with unmet healthcare needs are more likely to access unscheduled care. Identifying these patients through data-driven and clinical risk stratification for active case management in primary care can help address patient need and reduce demand on acute services. AIM: To determine how a proactive digital healthcare system can be used to undertake comprehensive needs analysis of patients at risk of unplanned admission and mortality. DESIGN & SETTING: Prospective cohort study of six general practices in a deprived UK city. METHOD: To identify those with unmet needs, the study's population underwent digitally-driven risk stratification into Escalated and Non-escalated groups using seven risk factors. The Escalated group underwent further stratification using GP clinical assessment into Concern and No concern groups. The Concern group underwent Unmet Needs Analysis (UNA). RESULTS: From 24 746 patients, 516 (2.1%) were triaged into the Concern group and 164 (0.7%) underwent UNA. These patients were more likely to be older (t = 4.69, P<0.001), female (X(2) = 4.46, P<0.05), have a Patients At Risk of Re-hospitalisation (PARR) score ≥80 (X(2) = 4.31, P<0.05), be a nursing home resident (X(2) = 6.75, P<0.01), or on an end-of-life (EOL) register (X(2) = 14.55, P<0.001). Following UNA, 143 (87.2%) patients had further review planned or were referred for further input. The majority of patients had four domains of need. In those who GPs would not be surprised if they died within the next few months, n = 69 (42.1%) were not on an EOL register. CONCLUSION: This study showed how an integrated, patient-centred, digital care system working with GPs can highlight and implement resources to address the escalating care needs of complex individuals.

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