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1.
Am J Clin Pathol ; 158(3): 409-415, 2022 09 02.
Article in English | MEDLINE | ID: mdl-35713605

ABSTRACT

OBJECTIVES: Surprisingly, laboratory results, the principal output of clinical laboratories, are not standardized. Thus, laboratories frequently report results with identical meaning in different formats. For example, laboratories report a positive pregnancy test as "+," "P," or "Positive." To assess the feasibility of a widespread implementation of a result standard, we (1) developed a standard result format for common laboratory tests and (2) implemented a feedback system for clinical laboratories to view their unstandardized results. METHODS: In the largest integrated health care system in America, 130 facilities had the opportunity to collaboratively develop the standard. For 15 weeks, clinical laboratories received a weekly report of their unstandardized results. At the study's conclusion, laboratories were compared with themselves and their peers by metrics that reflected their unstandardized results. RESULTS: We rereviewed 156 million test results and observed a 51% decline in the rate of unstandardized results. The number of facilities with fewer than 23 unstandardized results per 100,000 (Six Sigma σ > 5) increased by 58% (52 to 82 facilities; ß = 1.79; P < .001). CONCLUSIONS: This study demonstrated significant improvement in the standardization of clinical laboratory results in a relatively short time. The laboratory community should create and promulgate a standardized result format.


Subject(s)
Clinical Laboratory Services , Laboratories, Clinical , Clinical Laboratory Techniques , Female , Humans , Laboratories , Pregnancy
2.
Headache ; 61(2): 318-328, 2021 02.
Article in English | MEDLINE | ID: mdl-33502769

ABSTRACT

OBJECTIVE: To characterize patient-reported ideas and concerns about cluster headache, treatment options, and management strategies. BACKGROUND: Cluster headache patients experience severe pain and often suffer additional consequences from their disease. Patients have identified methods to cope with and combat cluster headache that are not widely known. METHODS: Secondary analysis was performed using deidentified data from the online Clusterbusters Medication Use survey, wherein 10 questions allowed for freely written comments. Using mixed-methods techniques, neurologists with expertise in headache medicine identified themes from these comments. Subgroup analysis sought to identify variables associated with specific themes. RESULTS: Among 2274 free-text responses from 493 adult participants, 23 themes were identified. Themes commonly discussed in the literature included such topics as "nothing worked" (24.7%, 122/493), "side effects" (12.8%, 63/493), and difficulties with "access/cost" (2.4%, 12/493). Less widely recognized themes included the use of "illicit substances" (35.5%, 175/493) and "vitamins/supplements" (12.2%, 60/493) in disease management. Lesser-known themes included "coffee" (5.3%, 26/493) and "exercise/physical activity" (4.7%, 23/493). Using strict significance criteria, no subgroup was associated with any theme. Several poignant quotes highlighted patient thoughts and experiences. CONCLUSIONS: This mixed-methods analysis identified challenges endured by cluster headache patients, as well as a variety of patient-directed disease management approaches. The volunteered information spotlights pharmacological, physiological, and psychological aspects of cluster headache that warrant further exploratory and interventional investigation.


Subject(s)
Cluster Headache/therapy , Disease Management , Health Knowledge, Attitudes, Practice , Adult , Health Surveys , Humans , Qualitative Research
3.
Arch Pathol Lab Med ; 144(4): 478-484, 2020 04.
Article in English | MEDLINE | ID: mdl-31469586

ABSTRACT

CONTEXT.­: Clinical laboratories are obligated to implement Logical Observation Identifier Names and Codes (LOINC), an informatics standard used to uniquely identify laboratory tests. The historical progress of laboratories in achieving this goal is unknown. OBJECTIVE.­: To evaluate the implementation of LOINC by clinical laboratories with attention to LOINC's adoption, diversity, and correctness over time. DESIGN.­: We aggregated data from 130 facilities within the Veterans Health Administration (VA), an early adopter of LOINC, during a 20-year period (1999-2018). To assess the adoption of LOINC, we calculated the annual proportion of tests and results without a LOINC. To assess the diversity of LOINC, we counted the yearly number of distinct LOINCs in active use. To assess the correctness of LOINC over time, we compared the assigned LOINCs to a manually reviewed gold standard for each year. RESULTS.­: We reviewed a total of 586 000 tests and 9.162 billion results. LOINC adoption, measured as a proportion of both tests and results, improved over time (P < .001). In the final year reviewed, 85% (172 142 of 202 125) of laboratory tests and 99% (547 229 066 of 551 205 087) of results had LOINCs. The number of distinct LOINCs in active use from 1999 to 2018 increased 2.78-fold from 4502 to 12 503 (P < .001). Correctness generally improved but varied considerably by test and across time. CONCLUSIONS.­: The adoption of LOINC has improved during the past 2 decades. More diverse LOINCs were associated with increased adoption and were a challenge to keep up-to-date. The correctness of LOINCs has improved but remains an issue that likely necessitates supplemental review for most applications.


Subject(s)
Clinical Laboratory Services , Logical Observation Identifiers Names and Codes , Veterans Health Services , Humans , United States
4.
J Am Med Inform Assoc ; 25(2): 121-126, 2018 02 01.
Article in English | MEDLINE | ID: mdl-28505339

ABSTRACT

Objective: Clinical laboratories in the United States do not have an explicit result standard to report the 7 billion laboratory tests results they produce each year. The absence of standardized test results creates inefficiencies and ambiguities for secondary data users. We developed and tested a tool to standardize the results of laboratory tests in a large, multicenter clinical data warehouse. Methods: Laboratory records, each of which consisted of a laboratory result and a test identifier, from 27 diverse facilities were captured from 2000 through 2015. Each record underwent a standardization process to convert the original result into a format amenable to secondary data analysis. The standardization process included the correction of typos, normalization of categorical results, separation of inequalities from numbers, and conversion of numbers represented by words (eg, "million") to numerals. Quality control included expert review. Results: We obtained 1.266 × 109 laboratory records and standardized 1.252 × 109 records (98.9%). Of the unique unstandardized records (78.887 × 103), most appeared <5 times (96%, eg, typos), did not have a test identifier (47%), or belonged to an esoteric test with <100 results (2%). Overall, these 3 reasons accounted for nearly all unstandardized results (98%). Conclusion: Current results suggest that the tool is both scalable and generalizable among diverse clinical laboratories. Based on observed trends, the tool will require ongoing maintenance to stay current with new tests and result formats. Future work to develop and implement an explicit standard for test results would reduce the need to retrospectively standardize test results.


Subject(s)
Clinical Laboratory Information Systems/standards , Clinical Laboratory Techniques/standards , Vocabulary, Controlled , Algorithms , Data Analysis , Databases, Factual/standards , Electronic Health Records/standards , Humans , Logical Observation Identifiers Names and Codes , Quality Control , United States
5.
J Am Med Inform Assoc ; 25(2): 192-196, 2018 02 01.
Article in English | MEDLINE | ID: mdl-28637208

ABSTRACT

Logical Observation Identifiers Names and Codes (LOINC) is the most widely used controlled vocabulary to identify laboratory tests. A given laboratory test can often be reported in more than 1 unit of measure (eg, grams or moles), and LOINC defines unique codes for each unit. Consequently, an identical laboratory test performed by 2 different clinical laboratories may have different LOINC codes. The absence of unit conversions between compatible LOINC codes impedes data aggregation and analysis of laboratory results. To develop such conversions, a computational process was developed to review the LOINC standard for potential conversions, and multiple expert reviewers oversaw and finalized the conversion list. In all, 285 bidirectional conversions were identified, including conversions for routine clinical tests such as sodium, magnesium, and human immunodeficiency virus (HIV). Unit conversions were applied to the aggregation of laboratory test results to demonstrate their usefulness. Diverse informatics projects may benefit from the ability to interconvert compatible results.


Subject(s)
Clinical Laboratory Information Systems , Logical Observation Identifiers Names and Codes , Mathematical Concepts , Laboratories
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