Artificial Intelligence Needs Clinical Intelligence to Succeed

Hospitalization for Heart Failure in the United States, UK, Taiwan, and Japan: An International Comparison of Administrative Health Records on 413,385 Individual Patients

“…Previous reports evaluating international differences in characteristics and outcomes for patients hospitalised with HF (HFH) have been based on those enrolled in clinical trials and registries. 2,13,14,17,[22][23][24][25][26][27][28] Research is usually conducted by investigators who are specialists working in academic centres; only the patients they care for have the possibility of being enrolled. 26 Patients are often further selected because of protocol inclusion and exclusion criteria.…”

“…2,13,14,17,[22][23][24][25][26][27][28] Research is usually conducted by investigators who are specialists working in academic centres; only the patients they care for have the possibility of being enrolled. 26 Patients are often further selected because of protocol inclusion and exclusion criteria. Investigators will often avoid enrolling elderly, frail patients with multiple comorbidities who are less likely to be able to comply with procedures.…”

Heart failure: age is no excuse for complacency

“…Assuming an incidence of three cases of heart failure per thousand population per year 1 with half of new cases being HFrEF, then 15 000 new cases of HFrEF per year would be expected in Sweden and about 300 000 new cases over the lifetime of the registry. It is likely that patients enrolled in the Swedish registry received more attention and better care than the majority of patients with HFrEF in Sweden 8 …”

“…It is likely that patients enrolled in the Swedish registry received more attention and better care than the majority of patients with HFrEF in Sweden. 8 Keeping this limitation in mind, how should we interpret these observational registry data?…”

Clinical Decision Support to Prevent Acute Kidney Injury After Cardiac Catheterization

“…Electronic health records offer the possibility of aggregating myriad discrete clinical data to inform real-time practice in the form of clinical decision support. However, for numerous reasons (including a focus on process as opposed to outcome metrics, disruption of established clinical workflows, and inadequate resourcing), clinical decision support has largely fallen short …”