Dataset Information

Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process.

ABSTRACT: CONTEXT.—:The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization. Cross-department, multidisciplinary collaboration to address gaps and improve patient and system outcomes is beneficial. OBJECTIVE.—:To demonstrate medical data warehouse utility for characterizing laboratory-associated quality gaps amenable to preanalytic or postanalytic interventions. DESIGN.—:A multidisciplinary team identified quality gaps. Medical data warehouse data were queried to characterize gaps. Organizational leaders were interviewed about quality improvement priorities. A decision aid with elements including national guidelines, local and national importance, and measurable outcomes was completed for each gap. RESULTS.—:Gaps identified included (1) test ordering; (2) diagnosis, detection, and documentation, and (3) high-risk medication monitoring. After examination of medical data warehouse data including enrollment, diagnoses, laboratory, pharmacy, and procedures for baseline performance, high-risk medication monitoring was selected, specifically alanine aminotransferase, aspartate aminotransferase, complete blood count, and creatinine testing among patients receiving disease-modifying antirheumatic drugs. The test utilization gap was in monitoring timeliness (eg, >60% of patients had a monitoring gap exceeding the guideline recommended frequency). Other contributors to selecting this gap were organizational enthusiasm, regulatory labeling, and feasibility of a significant laboratory role in addressing the gap. CONCLUSIONS.—:A multidisciplinary process facilitated identification and selection of a laboratory medicine quality gap. Medical data warehouse data were instrumental in characterizing gaps.

SUBMITTER: Raebel MA

PROVIDER: S-EPMC6941735 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process.

Raebel Marsha A MA Quintana LeeAnn M LM Schroeder Emily B EB Shetterly Susan M SM Pieper Lisa E LE Epner Paul L PL Bechtel Laura K LK Smith David H DH Sterrett Andrew T AT Chorny Joseph A JA Lubin Ira M IM

Archives of pathology & laboratory medicine 20181210 4

<h4>Context.—</h4>The laboratory total testing process includes preanalytic, analytic, and postanalytic phases, but most laboratory quality improvement efforts address the analytic phase. Expanding quality improvement to preanalytic and postanalytic phases via use of medical data warehouses, repositories that include clinical, utilization, and administrative data, can improve patient care by ensuring appropriate test utilization. Cross-department, multidisciplinary collaboration to address gaps ...[more]

PMID: 30525932

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Project description:BackgroundThe quality of decision-making in multidisciplinary team meetings (MDTMs) depends on the quality of information presented and the quality of team processes. Few studies have examined these factors using a standardized approach. The aim of this study was to objectively document the processes involved in decision-making in MDTMs, document the outcomes in terms of whether a treatment recommendation was given (none vs. singular vs. multiple), and to identify factors related to type of treatment recommendation.MethodsAn adaptation of the observer rating scale Multidisciplinary Tumor Board Metric for the Observation of Decision-Making (MDT-MODe) was used to assess the quality of the presented information and team processes in MDTMs. Data was analyzed using descriptive statistics and mixed logistic regression analysis.ResultsN?=?249 cases were observed in N?=?29 MDTMs. While cancer-specific medical information was judged to be of high quality, psychosocial information and information regarding patient views were considered to be of low quality. In 25% of the cases no, in 64% one, and in 10% more than one treatment recommendations were given (1% missing data). Giving no treatment recommendation was associated with duration of case discussion, duration of the MDTM session, quality of case history, quality of radiological information, and specialization of the MDTM. Higher levels of medical and treatment uncertainty during discussions were found to be associated with a higher probability for more than one treatment recommendation.ConclusionsThe quality of different aspects of information was observed to differ greatly. In general, we did not find MDTMs to be in line with the principles of patient-centered care. Recommendation outcome varied substantially between different specializations of MDTMs. The quality of certain information was associated with the recommendation outcome. Uncertainty during discussions was related to more than one recommendation being considered. Time constraints were found to play an important role. Some of those aspects seem modifiable, which offers possibilities for the reorganization of MDTMs.

Project description:BackgroundSouth Africa's National Health Laboratory Service (NHLS), the only clinical laboratory service in the country's public health sector, is an important resource for monitoring public health programmes.ObjectivesWe describe NHLS data quality, particularly patient demographics among infants, and the effect this has on linking multiple test results to a single patient.MethodsRetrospective descriptive analysis of NHLS data from 1st January 2017-1st September 2020 was performed. A validated probabilistic record-linking algorithm linked multiple results to individual patients in lieu of a unique patient identifier. Paediatric HIV PCR data was used to illustrate the effect on monitoring and evaluating a public health programme. Descriptive statistics including medians, proportions and inter quartile ranges are reported, with Chi-square univariate tests for independence used to determine association between variables.ResultsDuring the period analysed, 485 300 007 tests, 98 217 642 encounters and 35 771 846 patients met criteria for analysis. Overall, 15.80% (n = 15 515 380) of all encounters had a registered national identity (ID) number, 2.11% (n = 2 069 785) were registered without a given name, 63.15% (n = 62 020 107) were registered to women and 32.89% (n = 32 304 329) of all folder numbers were listed as either the patient's date of birth or unknown. For infants tested at < 7 days of age (n = 2 565 329), 0.099% (n = 2 534) had an associated ID number and 48.87% (n = 1 253 620) were registered without a given name. Encounters with a given name were linked to a subsequent encounter 40.78% (n = 14 180 409 of 34 775 617) of the time, significantly more often than the 21.85% (n = 217 660 of 996 229) of encounters registered with a baby-derivative name (p-value < 0.001).ConclusionUnavailability and poor capturing of patient demographics, especially among infants and children, affects the ability to accurately monitor routine health programmes. A unique national patient identifier, other than the national ID number, is urgently required and must be available at birth if South Africa is to accurately monitor programmes such as the Prevention of Mother-to-Child Transmission of HIV.

Dataset Information

Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process.

Publications

Identifying Preanalytic and Postanalytic Laboratory Quality Gaps Using a Data Warehouse and Structured Multidisciplinary Process.

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