Why hospital performance cannot be understood without population, capacity, and context. Aurelian’s Casebook Casebook #3 The dashboard was green. Surgical backlog: 0%. No patients were waiting beyond the hospital’s defined backlog threshold. Then the hospital director received a question from regional leadership: Why is your operating room performing so few surgeries? It was a reasonable … Read more
Agent. Host. Environment. All three may be present—and the outcome can still be different. Three people live in the same community. The same infectious agent is circulating. They experience similar environmental conditions and opportunities for exposure. One never becomes infected. Another becomes infected but develops no apparent illness. A third develops clinical disease. Why? At … Read more
Aurelian’s Casebook Casebook #2 A performance indicator can tell us something about a system. That does not make improving the indicator the purpose of the system. Healthcare organizations measure utilization for good reasons. Admissions, bed-days, occupancy, outpatient activity, and referrals help leaders understand demand, capacity, access, and how healthcare resources are being used. But an … Read more
Aurelian’s Surveillance Files Field Note #8 The case definition asks whether the patient belongs in the surveillance net. Clinical reasoning asks whether the disease actually explains the patient. Imagine a clinician working in a region where dengue is endemic. A patient arrives with fever, thrombocytopenia, and other compatible clinical findings. The surveillance criteria are reviewed. … Read more
Aurelian’s Casebook Casebook #1 Case Presentation An executive committee is reviewing its monthly hospital performance dashboard. Among the quality indicators, one measure immediately draws attention: overall hospital mortality. The dashboard reports the following: Hospital Moratality Rate Hospital A 8% Hospital B 13% Based on these figures, the conclusion seems obvious. Hospital A has the lower … Read more
Aurelian’s Surveillance Files Field Note #7 Surveillance systems rarely fail because a single link breaks. They fail because, over time, we allow the chain to rust Last week, we explored sentinel surveillance and why effective surveillance is less about watching everything than about watching the right things. This week, I want to step back from … Read more
Aurelian’s Surveillance Files Field Note #6 — Sentinel Surveillance Good surveillance is not measured by how much data we collect, but by whether we collect the right data at the right time to support better decisions. In recent Field Notes, we have looked at how surveillance systems classify disease, recognize patterns before diagnoses are confirmed, … Read more
Aurelian’s Surveillance Files Field Note #5 — Active vs. Passive Surveillance Surveillance does not always come to the epidemiologist. Sometimes the epidemiologist has to go looking for it. In recent Field Notes, we have looked at how surveillance systems use case definitions to classify disease and how syndromic surveillance can reveal a pattern before a … Read more
Every outbreak begins with individual patients. Syndromic surveillance helps us recognize when their separate stories are becoming one larger story. In the previous Field Note, we considered why surveillance case definitions must change as the evidence changes. Good surveillance is not rigid. It adapts as diseases emerge, knowledge improves, and public health priorities shift. This … Read more
Aurelian’s Surveillance Files Field Note #3 — Case Definitions Evolve A case definition is not a diagnosis. It is a surveillance tool used to recognize, classify, and monitor disease consistently. Like science itself, it must evolve as the evidence changes. In the previous Field Note, we examined epidemiologic silence and why an absence of reports … Read more