Henry Krakauer
Biographic Data
| ID | 5540710 |
|---|---|
| NAME | Henry Krakauer |
| GIVEN NAMES | Henry |
| FAMILY NAME | Krakauer |
| SIGNATURE | KRAKAUER H |
| AFFILIATIONS | Uniformed Services University of the Health Sciences |
| ORCID | 0000-0003-2517-0957 |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1989 |
| LATEST PUBLICATION YEAR | 1994 |
| H-INDEX | 0 |
The Relationship of Hospital Ownership and Teaching Status to 30- and 180-Day Adjusted Mortality Rates
Hospital characteristics have been shown previously to be associated with variations in the probability of death within 30 days of admission. In the current study, the authors extend the examination of the relationship between hospital type to both short-term and long-term adjusted mortality. Observed and predicted 1988 hospital mortality rates were obtained from the Health Care Financing Administration (HCFA). A total of 3,782 acute care hospita…
Severity of Illness Measures Derived From the Uniform Clinical Data Set (UCDSS)
The Health Care Financing Administration (HCFA) plans to use the Uniform Clinical Data Set System (UCDSS) to collect data on hospitalized Medicare patients. This study examined the value of UCDSS data for creating severity of illness measures. UCDSS data were obtained from a study hospital and from a national data set for patients with pneumonia (n = 528) and stroke (n = 565). Models to predict length of stay or an adverse event were derived for …
Hospital and Patient Characteristics Associated With Death After Surgery
We asked if the factors that predict overall mortality following two common surgical procedures are different from those that predict adverse occurrences (complications) during the hospitalization or death after an adverse occurrence, which we refer to as "failure to rescue." We examined 5,972 Medicare patients undergoing elective cholecystectomy or transurethral prostatectomy using three outcome measures: 1) the death rate (number of deaths/numb…
Using Clinical Variables to Estimate the Risk of Patient Mortality
The Health Care Financing Administration (HCFA) uses information from hospital bills, such as age, sex, and diagnoses, to estimate statistical models for the probability, or risk, of death during and after hospital stays. The average risk estimates (expected death rates) are compared with the actual death rates to identify potentially poor quality of care. However, the methods have been criticized as inadequate and an often cited reason is the fa…
Hospital Characteristics and Mortality Rates
The Health Care Financing Administration (HCFA) publishes hospital mortality rates each year. We undertook a study to identify characteristics of hospitals associated with variations in these rates. To do so, we obtained data on 3100 hospitals from the 1986 HCFA mortality study and the American Hospital Association's 1986 annual survey of hospitals. The mortality rates were adjusted for each hospital's case mix and other characteristics of its pa…
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Hospital Characteristics and Mortality Rates
The Health Care Financing Administration (HCFA) publishes hospital mortality rates each year. We undertook a study to identify characteristics of hospitals associated with variations in these rates. To do so, we obtained data on 3100 hospitals from the 1986 HCFA mortality study and the American Hospital Association's 1986 annual survey of hospitals. The mortality rates were adjusted for each hospital's case mix and other characteristics of its pa…
Using Clinical Variables to Estimate the Risk of Patient Mortality
The Health Care Financing Administration (HCFA) uses information from hospital bills, such as age, sex, and diagnoses, to estimate statistical models for the probability, or risk, of death during and after hospital stays. The average risk estimates (expected death rates) are compared with the actual death rates to identify potentially poor quality of care. However, the methods have been criticized as inadequate and an often cited reason is the fa…
Hospital and Patient Characteristics Associated With Death After Surgery
We asked if the factors that predict overall mortality following two common surgical procedures are different from those that predict adverse occurrences (complications) during the hospitalization or death after an adverse occurrence, which we refer to as "failure to rescue." We examined 5,972 Medicare patients undergoing elective cholecystectomy or transurethral prostatectomy using three outcome measures: 1) the death rate (number of deaths/numb…
The Relationship of Hospital Ownership and Teaching Status to 30- and 180-Day Adjusted Mortality Rates
Hospital characteristics have been shown previously to be associated with variations in the probability of death within 30 days of admission. In the current study, the authors extend the examination of the relationship between hospital type to both short-term and long-term adjusted mortality. Observed and predicted 1988 hospital mortality rates were obtained from the Health Care Financing Administration (HCFA). A total of 3,782 acute care hospita…
Severity of Illness Measures Derived From the Uniform Clinical Data Set (UCDSS)
The Health Care Financing Administration (HCFA) plans to use the Uniform Clinical Data Set System (UCDSS) to collect data on hospitalized Medicare patients. This study examined the value of UCDSS data for creating severity of illness measures. UCDSS data were obtained from a study hospital and from a national data set for patients with pneumonia (n = 528) and stroke (n = 565). Models to predict length of stay or an adverse event were derived for …
Emergency Medicine (5 works) · Internal Medicine (5 works) · Medicine (5 works) · Emergency Medicine (4 works) · Healthcare Policy and Management (4 works) · Internal Medicine (4 works) · Mortality rate (4 works) · Health care (3 works) · Acute care (2 works) · Adverse effect (2 works)