| P50 | author | Niraj J Gusani | Q73189816 |
| P2093 | author name string | Christopher S Hollenbeak | |
| | Laura M Enomoto | |
| | Peter W Dillon | |
| | Neil H Bhayani | |
| P2860 | cites work | Using administrative databases to evaluate the quality of medical care: A conceptual framework | Q40474095 |
| | Successful implementation of the Department of Veterans Affairs' National Surgical Quality Improvement Program in the private sector: the Patient Safety in Surgery study | Q43489647 |
| | Accuracy in recorded diagnoses | Q44573737 |
| | The National Surgical Quality Improvement Program in non-veterans administration hospitals: initial demonstration of feasibility | Q45334016 |
| | Identifying patient preoperative risk factors and postoperative adverse events in administrative databases: results from the Department of Veterans Affairs National Surgical Quality Improvement Program | Q45334119 |
| | The Department of Veterans Affairs' NSQIP: the first national, validated, outcome-based, risk-adjusted, and peer-controlled program for the measurement and enhancement of the quality of surgical care. National VA Surgical Quality Improvement Program | Q45334952 |
| | How best to measure surgical quality? Comparison of the Agency for Healthcare Research and Quality Patient Safety Indicators (AHRQ-PSI) and the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) postoperative adve | Q45418143 |
| | The accuracy of Medicare's hospital claims data: progress has been made, but problems remain. | Q55043677 |
| | The International Classification of Diseases: Ninth Revision (ICD-9) | Q67283809 |
| | Accuracy of diagnostic coding for Medicare patients under the prospective-payment system | Q70374986 |
| | Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research | Q72030547 |
| | Validating risk-adjusted surgical outcomes: site visit assessment of process and structure. National VA Surgical Risk Study | Q73782173 |
| | Focus on quality: profiling physicians' practice patterns | Q77126502 |
| | Can administrative data be used to ascertain clinically significant postoperative complications? | Q28216654 |
| | A comparison of clinical registry versus administrative claims data for reporting of 30-day surgical complications | Q30574624 |
| | Monitoring adverse outcomes of surgery using administrative data | Q30576785 |
| | Identification of in-hospital complications from claims data. Is it valid? | Q30605833 |
| | Use of administrative data to find substandard care: validation of the complications screening program | Q30605837 |
| | Can administrative data be used to compare postoperative complication rates across hospitals? | Q30741805 |
| | Clinical versus administrative data bases for CABG surgery. Does it matter? | Q30861800 |
| | Administrative databases provide inaccurate data for surveillance of long-term central venous catheter-associated infections | Q30886951 |
| | Assessment of the reliability of data collected for the Department of Veterans Affairs national surgical quality improvement program | Q31106747 |
| | Rating health information on the Internet: navigating to knowledge or to Babel? | Q32106863 |
| | Validity of selected AHRQ patient safety indicators based on VA National Surgical Quality Improvement Program data | Q33372570 |
| | Assessing surgical quality using administrative and clinical data sets: a direct comparison of the University HealthSystem Consortium Clinical Database and the National Surgical Quality Improvement Program data set. | Q33479455 |
| | Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program | Q33528355 |
| | Using administrative diagnostic data to assess the quality of hospital care. Pitfalls and potential of ICD-9-CM. | Q34061414 |
| | What are the real rates of postoperative complications: elucidating inconsistencies between administrative and clinical data sources | Q34197239 |
| | Validating risk-adjusted surgical outcomes: chart review of process of care | Q34321036 |
| | Detecting adverse events in surgery: comparing events detected by the Veterans Health Administration Surgical Quality Improvement Program and the Patient Safety Indicators | Q36020028 |
| | Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities | Q36428029 |
| | Using administrative data for longitudinal research: comparisons with primary data collection. | Q36482288 |
| | Identifying complications and low provider adherence to normative practices using administrative data | Q36685256 |
| | Identifying complications of care using administrative data. | Q36733975 |
| | A comparison of administrative versus clinical data: coronary artery bypass surgery as an example. Ischemic Heart Disease Patient Outcomes Research Team | Q36745646 |
| | Using administrative data to screen hospitals for high complication rates | Q36748559 |
| | Bias in the coding of hospital discharge data and its implications for quality assessment | Q36759497 |
| | Registries and administrative data: organization and accuracy. | Q36777916 |
| | Assessing quality using administrative data | Q36893036 |
| | The classic: A study in hospital efficiency: as demonstrated by the case report of first five years of private hospital | Q36997489 |
| | Risk adjustment in claims-based research: the search for efficient approaches | Q38409582 |
| | Can Medicare prospective payment survive the ICD-9-CM disease classification system? | Q39587946 |
| P433 | issue | 8 | |
| P304 | page(s) | 1416-1422 | |
| P577 | publication date | 2014-06-14 | |
| P1433 | published in | Journal of Gastrointestinal Surgery | Q15764393 |
| P1476 | title | Measuring surgical quality: a national clinical registry versus administrative claims data | |
| P478 | volume | 18 | |