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Statistical process monitoring to improve quality assurance of inpatient care.

ABSTRACT: BACKGROUND:Statistical Process Monitoring (SPM) is not typically used in traditional quality assurance of inpatient care. While SPM allows a rapid detection of performance deficits, SPM results strongly depend on characteristics of the evaluated process. When using SPM to monitor inpatient care, in particular the hospital risk profile, hospital volume and properties of each monitored performance indicator (e.g. baseline failure probability) influence the results and must be taken into account to ensure a fair process evaluation. Here we study the use of CUSUM charts constructed for a predefined false alarm probability within a single process, i.e. a given hospital and performance indicator. We furthermore assess different monitoring schemes based on the resulting CUSUM chart and their dependence on the process characteristics. METHODS:We conduct simulation studies in order to investigate alarm characteristics of the Bernoulli log-likelihood CUSUM chart for crude and risk-adjusted performance indicators, and illustrate CUSUM charts on performance data from the external quality assurance of hospitals in Bavaria, Germany. RESULTS:Simulating CUSUM control limits for a false alarm probability allows to control the number of false alarms across different conditions and monitoring schemes. We gained better understanding of the effect of different factors on the alarm rates of CUSUM charts. We propose using simulations to assess the performance of implemented CUSUM charts. CONCLUSIONS:The presented results and example demonstrate the application of CUSUM charts for fair performance evaluation of inpatient care. We propose the simulation of CUSUM control limits while taking into account hospital and process characteristics.

SUBMITTER: Hubig L

PROVIDER: S-EPMC6947979 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundDespite more than a decade of research on hospitalists and their performance, disagreement still exists regarding whether and how hospital-based physicians improve the quality of inpatient care delivery. This systematic review summarizes the findings from 65 comparative evaluations to determine whether hospitalists provide a higher quality of inpatient care relative to traditional inpatient physicians who maintain hospital privileges with concurrent outpatient practices.MethodsArticles on hospitalist performance published between January 1996 and December 2010 were identified through MEDLINE, Embase, Science Citation Index, CINAHL, NHS Economic Evaluation Database and a hand-search of reference lists, key journals and editorials. Comparative evaluations presenting original, quantitative data on processes, efficiency or clinical outcome measures of care between hospitalists, community-based physicians and traditional academic attending physicians were included (n = 65). After proposing a conceptual framework for evaluating inpatient physician performance, major findings on quality are summarized according to their percentage change, direction and statistical significance.ResultsThe majority of reviewed articles demonstrated that hospitalists are efficient providers of inpatient care on the basis of reductions in their patients' average length of stay (69%) and total hospital costs (70%); however, the clinical quality of hospitalist care appears to be comparable to that provided by their colleagues. The methodological quality of hospitalist evaluations remains a concern and has not improved over time. Persistent issues include insufficient reporting of source or sample populations (n = 30), patients lost to follow-up (n = 42) and estimates of effect or random variability (n = 35); inappropriate use of statistical tests (n = 55); and failure to adjust for established confounders (n = 37).ConclusionsFuture research should include an expanded focus on the specific structures of care that differentiate hospitalists from other inpatient physician groups as well as the development of better conceptual and statistical models that identify and measure underlying mechanisms driving provider-outcome associations in quality.

Project description:This study utilizes process control techniques to identify action limits for TomoTherapy couch positioning quality assurance tests. A test was introduced to monitor accuracy of the applied couch offset detection in the TomoTherapy Hi-Art treatment system using the TQA "Step-Wedge Helical" module and MVCT detector. Individual X-charts, process capability (cp), probability (P), and acceptability (cpk) indices were used to monitor a 4-year couch IEC offset data to detect systematic and random errors in the couch positional accuracy for different action levels. Process capability tests were also performed on the retrospective data to define tolerances based on user-specified levels. A second study was carried out whereby physical couch offsets were applied using the TQA module and the MVCT detector was used to detect the observed variations. Random and systematic variations were observed for the SPC-based upper and lower control limits, and investigations were carried out to maintain the ongoing stability of the process for a 4-year and a three-monthly period. Local trend analysis showed mean variations up to ±0.5 mm in the three-monthly analysis period for all IEC offset measurements. Variations were also observed in the detected versus applied offsets using the MVCT detector in the second study largely in the vertical direction, and actions were taken to remediate this error. Based on the results, it was recommended that imaging shifts in each coordinate direction be only applied after assessing the machine for applied versus detected test results using the step helical module. User-specified tolerance levels of at least ±2 mm were recommended for a test frequency of once every 3 months to improve couch positional accuracy. SPC enables detection of systematic variations prior to reaching machine tolerance levels. Couch encoding system recalibrations reduced variations to user-specified levels and a monitoring period of 3 months using SPC facilitated in detecting systematic and random variations. SPC analysis for couch positional accuracy enabled greater control in the identification of errors, thereby increasing confidence levels in daily treatment setups.

Project description:OBJECTIVE:To assess hospital practices in obstetric quality management activities and identify institutional characteristics associated with utilization of evidence-supported practices. METHODS:Data for this study came from a statewide survey of obstetric hospitals in California regarding their organization and delivery of perinatal care. We analyzed responses from 185 hospitals that completed quality assurance sections of the survey to assess their practices in a broad spectrum of quality enhancement activities. The association between institutional characteristics and adoption of evidence-supported practices (ie, those supported by prior literature or recommended by professional organizations as beneficial for improving birth outcome or patient safety) was examined using bivariate analysis and appropriate statistical tests. RESULTS:Most hospitals regularly audited adherence to written protocols regarding critical areas of care; however, 77.7% and 16.8% reported not having written guidelines on diagnosis of labor arrest and management of abnormal fetal heart rate, respectively. Private nonprofit hospitals were more likely to have a written protocol for management of abnormal fetal heart rate (P=.002). One in 10 hospitals (9.7%) did not regularly review cases with significant morbidity or mortality, and only 69.0% regularly tracked indications for cesarean delivery. Moreover, 26.3%, 14.3%, and 8.7% of the hospitals reported never performing interprofessional simulations for eclampsia, shoulder dystocia, or postpartum hemorrhage, respectively. Teaching status was associated with more frequent simulations in these three areas (P?.04 for all), while larger volume was associated with more frequent simulations for eclampsia (P=.04). CONCLUSION:Hospitals in California engage in a wide range of practices to assure or improve quality of obstetric care, but substantial variation in practice exists among hospitals. There is opportunity for improvement in adoption of evidence-supported practices.

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Statistical process monitoring to improve quality assurance of inpatient care.

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