Dan Zeltzer
Biographic Data
| ID | 5547209 |
|---|---|
| NAME | Dan Zeltzer |
| GIVEN NAMES | Dan |
| FAMILY NAME | Zeltzer |
| SIGNATURE | ZELTZER D |
| AFFILIATIONS | Tel Aviv University |
| ORCID | 0000-0002-4140-7531 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Challenging Encounters and Within-Physician Practice Variability
We examine how physician decisions are affected by difficult cases—encounters with newly diagnosed cancer patients. Using detailed administrative data, we compare primary care physicians’ decisions in visits that occurred before and after difficult cases and matched comparison cases by the same physicians on other dates. Immediately following a difficult case, physicians increase referrals for common tests, including diagnostic tests unrelated to…
Why Is End-of-Life Spending So High? Evidence from Cancer Patients
We study the sources of high end-of-life spending for cancer patients. Even among patients with similar initial prognoses, spending in the year postdiagnosis is over twice as high for those who die within the year than those who survive. Elevated spending on decedents is predominantly driven by higher inpatient spending, particularly low-intensity admissions. However, most such admissions do not result in death, making it difficult to target spen…
Prediction Accuracy With Electronic Medical Records Versus Administrative Claims
OBJECTIVE: The objective of this study was to evaluate the incremental predictive power of electronic medical record (EMR) data, relative to the information available in more easily accessible and standardized insurance claims data. DATA AND METHODS: Using both EMR and Claims data, we predicted outcomes for 118,510 patients with 144,966 hospitalizations in 8 hospitals, using widely used prediction models. We use cross-validation to prevent overfi…
No prominent works on this page.
Prediction Accuracy With Electronic Medical Records Versus Administrative Claims
OBJECTIVE: The objective of this study was to evaluate the incremental predictive power of electronic medical record (EMR) data, relative to the information available in more easily accessible and standardized insurance claims data. DATA AND METHODS: Using both EMR and Claims data, we predicted outcomes for 118,510 patients with 144,966 hospitalizations in 8 hospitals, using widely used prediction models. We use cross-validation to prevent overfi…
Why Is End-of-Life Spending So High? Evidence from Cancer Patients
We study the sources of high end-of-life spending for cancer patients. Even among patients with similar initial prognoses, spending in the year postdiagnosis is over twice as high for those who die within the year than those who survive. Elevated spending on decedents is predominantly driven by higher inpatient spending, particularly low-intensity admissions. However, most such admissions do not result in death, making it difficult to target spen…
Challenging Encounters and Within-Physician Practice Variability
We examine how physician decisions are affected by difficult cases—encounters with newly diagnosed cancer patients. Using detailed administrative data, we compare primary care physicians’ decisions in visits that occurred before and after difficult cases and matched comparison cases by the same physicians on other dates. Immediately following a difficult case, physicians increase referrals for common tests, including diagnostic tests unrelated to…
Medicine (3 works) · Computer Science (2 works) · Healthcare Policy and Management (2 works) · Internal Medicine (2 works) · Internal Medicine (2 works) · Cancer (1 work) · Data mining (1 work) · Demography (1 work) · Family medicine (1 work) · Gerontology (1 work)