Tumor registry versus physician medical record review: A head-to-head comparison of malignant pancreatic neuroendocrine tumor (mPNET) cases

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 6600-6600
Author(s):  
E. E. Manasanch ◽  
T. P. McDade ◽  
A. Bodnari ◽  
J. McKinney ◽  
M. E. Sullivan ◽  
...  

6600 Background: Researchers have underutilized single-institution tumor registry (TR) data, instead using researcher medical record review and/or personal, departmental or institutional databases to identify patients with particular malignancies. However, TR data is becoming increasingly prominent on a national level through broader use of the National Cancer Database (NCDB). We selected mPNETs as example to compare the accuracy of TR identification of these tumors with physician medical record review (MD Review). Methods: For MD Review, the health information services department of a single academic medical center was queried for all patients with pancreatic ICD9 codes (157.0–157.9; 211.6–211.7) January 2000-August 2008. A single physician reviewer analyzed computerized and paper medical records and identified mPNET cases. For TR data, mPNET patients were identified using the TR database with assistance of TR staff by two separate strategies. From January 2000-December 2006, patients were identified by using diagnosis codes from manual review of admission, discharge, clinic and pathology reports. From January 2007-August 2008 the TR used an automated case finding program (CAL by C/NET, California, USA) that downloaded cases with terms and codes related to malignancy. All MD Review- and TR-identified mPNET cases were reviewed by a second investigator blinded to identification strategy to assure consistency of mPNET definitions. Results: Using MD Review, 1194 pts with pancreatic ICD9 codes were identified. After MD Review, 42 mPNET patients were identified and confirmed. In comparison, TR identified 17 patients, of whom 5 were not identified by MD Review. Of the 47 patients identified by either strategy, TR identified 17/47 (32.6%) patients, whereas MD Review identified 42/47 (89.4%). TR identification rate in time periods 1 and 2 were 30% and 40%, respectively. Conclusions: Analysis of an academic tumor registry demonstrates that a substantial proportion of mPNET cases are missed when compared to ICD-9 identification and physician medical record review. Since MD review is imperfect, the TR may be even less effective at identifying PNETs than our data suggest. This may be applicable to other tumor registries and TR-based national studies. No significant financial relationships to disclose.

2018 ◽  
Vol 133 (3) ◽  
pp. 303-310 ◽  
Author(s):  
Jason L. Salemi ◽  
Rachel E. Rutkowski ◽  
Jean Paul Tanner ◽  
Jennifer L. Matas ◽  
Russell S. Kirby

Objectives: We identified algorithms to improve the accuracy of passive surveillance programs for birth defects that rely on administrative diagnosis codes for case ascertainment and in situations where case confirmation via medical record review is not possible or is resource prohibitive. Methods: We linked data from the 2009-2011 Florida Birth Defects Registry, a statewide, multisource, passive surveillance program, to an enhanced surveillance database with selected cases confirmed through medical record review. For each of 13 birth defects, we calculated the positive predictive value (PPV) to compare the accuracy of 4 algorithms that varied case definitions based on the number of diagnoses, medical encounters, and data sources in which the birth defect was identified. We also assessed the degree to which accuracy-improving algorithms would affect the Florida Birth Defects Registry’s completeness of ascertainment. Results: The PPV generated by using the original Florida Birth Defects Registry case definition (ie, suspected cases confirmed by medical record review) was 94.2%. More restrictive case definition algorithms increased the PPV to between 97.5% (identified by 1 or more codes/encounters in 1 data source) and 99.2% (identified in >1 data source). Although PPVs varied by birth defect, alternative algorithms increased accuracy for all birth defects; however, alternative algorithms also resulted in failing to ascertain 58.3% to 81.9% of cases. Conclusions: We found that surveillance programs that rely on unverified diagnosis codes can use algorithms to dramatically increase the accuracy of case finding, without having to review medical records. This can be important for etiologic studies. However, the use of increasingly restrictive case definition algorithms led to a decrease in completeness and the disproportionate exclusion of less severe cases, which could limit the widespread use of these approaches.


BMJ Open ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. e018576 ◽  
Author(s):  
Marije A van Melle ◽  
Dorien L M Zwart ◽  
Judith M Poldervaart ◽  
Otto Jan Verkerk ◽  
Maaike Langelaan ◽  
...  

ObjectiveInadequate information transfer during transitions in healthcare is a major patient safety issue. Aim of this study was to pilot a review of medical records to identify transitional safety incidents (TSIs) for use in a large intervention study and assess its reliability and validity.DesignA retrospective medical record review study.Settings and participantsCombined primary and secondary care medical records of 301 patients who had visited their general practitioner and the University Medical Center Utrecht, the Netherlands, in 2013 were randomly selected. Six trained reviewers assessed these medical records for presence of TSIs.OutcomesTo assess inter-rater reliability, 10% of medical records were independently reviewed twice. To assess validity, the identified TSIs were compared with a reference standard of three objectively identifiable TSIs.ResultsThe reviewers identified TSIs in 52 (17.3%) of all transitional medical records. Variation between reviewers was high (range: 3–28 per 50 medical records). Positive agreement for finding a TSI between reviewers was 0%, negative agreement 80% and the Cohen’s kappa −0.15. The reviewers identified 43 (22%) of 194 objectively identifiable TSIs.ConclusionThe reliability of our measurement tool for identifying TSIs in transitional medical record performed by clinicians was low. Although the TSIs that were identified by clinicians were valid, they missed 80% of them. Restructuring the record review procedure is necessary.


2019 ◽  
Vol 28 (2) ◽  
pp. 256-263 ◽  
Author(s):  
Nancy A. Brandenburg ◽  
Syd Phillips ◽  
Karen E. Wells ◽  
Kimberley J. Woodcroft ◽  
Kandace L. Amend ◽  
...  

2011 ◽  
Vol 7 (2) ◽  
pp. 111-116 ◽  
Author(s):  
Elisabet E. Manasanch ◽  
Jillian K. Smith ◽  
Andreea Bodnari ◽  
Jeannine McKinney ◽  
Catherine Gray ◽  
...  

Academic tumor registry analysis indicates many patients with pancreatic neuroendocrine tumors are not identified when compared with physician medical record review. Reasons include registry time lag and case-finding methodologies.


2021 ◽  
Vol 27 (Suppl 1) ◽  
pp. i9-i12
Author(s):  
Anna Hansen ◽  
Dana Quesinberry ◽  
Peter Akpunonu ◽  
Julia Martin ◽  
Svetla Slavova

IntroductionThe purpose of this study was to estimate the positive predictive value (PPV) of International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes for injury, poisoning, physical or sexual assault complicating pregnancy, childbirth and the puerperium (PCP) to capture injury encounters within both hospital and emergency department claims data.MethodsA medical record review was conducted on a sample (n=157) of inpatient and emergency department claims from one Kentucky healthcare system from 2015 to 2017, with any diagnosis in the ICD-10-CM range O9A.2-O9A.4. Study clinicians reviewed medical records for the sampled cases and used an abstraction form to collect information on documented presence of injury and PCP complications. The study estimated the PPVs and the 95% CIs of O9A.2-O9A.4 codes for (1) capturing injuries and (2) capturing injuries complicating PCP.ResultsThe estimated PPV for the codes O9A.2-O9A.4 to identify injury in the full sample was 79.6% (95% CI 73.3% to 85.9%) and the PPV for capturing injuries complicating PCP was 72.0% (95% CI 65.0% to 79.0%). The estimated PPV for an inpatient principal diagnosis O9A.2-O9A.4 to capture injuries was 90.7% (95% CI 82.0% to 99.4%) and the PPV for capturing injuries complicating PCP was 88.4% (95% CI 78.4% to 98.4%). The estimated PPV for any mention of O9A.2-O9A.4 in emergency department data to capture injuries was 95.2% (95% CI 90.6% to 99.9%) and the PPV for capturing injuries complicating PCP was 81.0% (95% CI 72.4% to 89.5%).DiscussionThe O9A.2-O9A.4 codes captured high percentage true injury cases among pregnant and puerperal women.


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