| P50 | author | Salvador Peiró | Q42878326 |
| P2093 | author name string | J Librero | |
| | R Ordiñana | |
| P2860 | cites work | Hospital case-mix change: sicker patients or DRG creep? | Q48933506 |
| | Possible influence of the prospective payment system on the assignment of discharge diagnoses for coronary heart disease. | Q52390492 |
| | The effects of diagnostic criteria on trends in coronary heart disease morbidity: the Minnesota Heart Survey. | Q52544842 |
| | The accuracy of Medicare's hospital claims data: progress has been made, but problems remain. | Q55043677 |
| | [The agreement in the principal diagnosis at hospital discharge] | Q70266929 |
| | Reliability of reporting nosocomial infections in the discharge abstract and implications for receipt of revenues under prospective reimbursement | Q70334742 |
| | Accuracy of diagnostic coding for Medicare patients under the prospective-payment system | Q70374986 |
| | [How much and how are we using the Hospital Morbidity Survey?] | Q71150993 |
| | A new method of classifying prognostic comorbidity in longitudinal studies: development and validation | Q29547376 |
| | The impact of different coding systems on DRG assignment and data | Q30571462 |
| | A method for screening the quality of hospital care using administrative data: preliminary validation results | Q30885269 |
| | Risk adjusting health care outcomes: a methodologic review | Q33625086 |
| | Hospital case mix: its definition, measurement and use: Part I. The conceptual framework | Q33627908 |
| | Hospital case mix: its definition, measurement and use. Part II: Review of alternative measures. | Q33627957 |
| | Using administrative diagnostic data to assess the quality of hospital care. Pitfalls and potential of ICD-9-CM. | Q34061414 |
| | Medicaid data as a resource for epidemiologic studies: strengths and limitations | Q35905583 |
| | Medicare reimbursement accuracy under the prospective payment system, 1985 to 1988. | Q36365650 |
| | Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities | Q36428029 |
| | Flaws in mortality data. The hazards of ignoring comorbid disease | Q36436512 |
| | Using administrative data for longitudinal research: comparisons with primary data collection. | Q36482288 |
| | Using administrative data to describe casemix: a comparison with the medical record | Q36701884 |
| | How accurate are hospital discharge data for evaluating effectiveness of care? | Q36765531 |
| | Risk adjustment in claims-based research: the search for efficient approaches | Q38409582 |
| | Measurement of severity of illness and the Medicare prospective payment system: state of the art and future directions | Q39527818 |
| | Can Medicare prospective payment survive the ICD-9-CM disease classification system? | Q39587946 |
| | Coding of acute myocardial infarction. Clinical and policy implications | Q39607075 |
| | Reliability of Information Abstracted from Patients?? Medical Records | Q39778206 |
| | DRG creep: a new hospital-acquired disease | Q40306153 |
| | Physician and coding errors in patient records | Q41375266 |
| | The Risk-Adjusted Mortality Index. A new measure of hospital performance. | Q44155398 |
| | Accuracy in recorded diagnoses | Q44573737 |
| | The diagnostic coding of myocardial infarction | Q44702278 |
| P433 | issue | 1 | |
| P407 | language of work or name | Spanish | Q1321 |
| P304 | page(s) | 9-21 | |
| P577 | publication date | 1998-01-01 | |
| P1433 | published in | Gaceta Sanitaria | Q5873857 |
| P1476 | title | Automated analysis of the quality of the minimum set of basic data. Implications for risk-adjusting systems | |
| P478 | volume | 12 | |