Определение интервалов квазистационарности экономических систем

В работе рассмотрен вопрос определения оптимального интервала адаптации алгоритма динамического управления капиталом для нестационарного случая методами расчета показателя Херста и построения автокорреляционной функции для анализа временных рядов. Проведен анализ влияния выбора интервала адаптации на эффективность алгоритма. Из анализа полученных результатов следует, что метод расчета показателя Херста позволяет более эффективно, чем метод построения автокорреляционной функции, определить интервал стационарности модели функционирования экономической системы.Робота присвячена питанню визначення оптимального інтервалу адаптації алгоритму динамічного керування капіталом для нестаціонарного випадку за допомогою методів розрахунку показника Херста і побудови автокореляційної функції задля аналізу часових рядів. Проведено аналіз впливу вибору інтервалу адаптації на ефективність алгоритму. Порівняння результатів проведеного аналізу дозволяє стверджувати, що метод розрахунку показника Херста дозволяє більш ефективно, ніж метод побудови автокореляційної функції, визначити інтервал стаціонарності моделі функціонування економічної системи

Non-dispensing pharmacist integrated in the primary care team:Effect on the quality of physician's prescribing, a non-randomised comparative study

BackgroundEspecially in elderly with polypharmacy, medication can do harm. Clinical pharmacists integrated in primary care teams might improve quality of pharmaceutical care.ObjectiveTo assess the effect of non-dispensing clinical pharmacists integrated in primary care teams on general practitioners' prescribing quality.SettingThis study was conducted in 25 primary care practices in the Netherlands.MethodsNon-randomised, controlled, multi-centre, complex intervention study with pre-post comparison. First, we identified potential prescribing quality indicators from the literature and assessed their feasibility, validity, acceptability, reliability and sensitivity to change. Also, an expert panel assessed the indicators' health impact. Next, using the final set of indicators, we measured the quality of prescribing in practices where non-dispensing pharmacists were integrated in the team (intervention group) compared to usual care (two control groups). Data were extracted anonymously from the healthcare records. Comparisons were made using mixed models correcting for potential confounders.Main outcome measureQuality of prescribing, measured with prescribing quality indicators.ResultsOf 388 eligible indicators reported in the literature we selected 8. In addition, two more indicators relevant for Dutch general practice were formulated by an expert panel. Scores on all 10 indicators improved in the intervention group after introduction of the non-dispensing pharmacist. However, when compared to control groups, prescribing quality improved solely on the indicator measuring monitoring of the renal function in patients using antihypertensive medication: relative risk of a monitored renal function in the intervention group compared to usual care: 1.03 (95% CI 1.01-1.05, p-value 0.010) and compared to usual care plus: 1.04 (1.01-1.06, p-value 0.004).ConclusionThis study did not demonstrate a consistent effect of the introduction of non-dispensing clinical pharmacists in the primary care team on the quality of physician's prescribing. This study is part of the POINT-study, which was registered at The Netherlands National Trial Register with trial registration number NTR-4389

Validity and reliability of a medical record review method identifying transitional patient safety incidents in merged primary and secondary care patients' records.

OBJECTIVE: Inadequate 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. DESIGN: A retrospective medical record review study. SETTINGS AND PARTICIPANTS: Combined 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. OUTCOMES: To 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. RESULTS: The 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. CONCLUSION: The 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.This work was supported by the Dutch Ministry of Health, Welfare and Sports (VWS; grant number 320698), and Achmea Healthcare (grant number Z415)

Missed Acute Coronary Syndrome During Telephone Triage at Out-of-Hours Primary Care: Lessons From A Case-Control Study

OBJECTIVES: Serious adverse events at out-of-hours services in primary care (OHS-PC) are rare, and the most often concern is missed acute coronary syndrome (ACS). Previous studies on serious adverse events mainly concern root cause analyses, which highlighted errors in the telephone triage process but are hampered by hindsight bias. This study compared the recorded triage calls of patients with chest discomfort contacting the OHS-PC in whom an ACS was missed (cases), with triage calls involving matched controls with chest discomfort but without a missed ACS (controls), with the aim to assess the predictors of missed ACS. METHODS: A case-control study with data from 2013 to 2017 of 9 OHS-PC in the Netherlands. The cases were matched 1:8 with controls based on age and sex. Clinical, patient, and call characteristics were univariably assessed, and general practitioner experts evaluated the triage while blinded to the final diagnosis or the case-control status. RESULTS: Fifteen missed ACS calls and 120 matched control calls were included. Cases used less cardiovascular medication (38.5% versus 64.1%, P = 0.05) and more often experienced pain other than retrosternal chest pain (63.3% versus 24.7%, P = 0.02) compared with controls. Consultation of the supervising general practitioner (86.7% versus 49.2%, P = 0.02) occurred more often in cases than in controls. Experts rated the triage of cases more often as "poor" (33.3% versus 10.9%, P = 0.001) and "unsafe" (73.3% versus 22.5%, P < 0.001) compared with controls. CONCLUSIONS: To facilitate learning from serious adverse events in the future, these should also be bundled and carefully assessed without hindsight bias and within the context of "normal" clinical practice

Secondary analysis of frequency, circumstances and consequences of calculation errors of the HEART (history, ECG, age, risk factors and troponin) score at the emergency departments of nine hospitals in the Netherlands

OBJECTIVE: The HEART score can accurately stratify the risk of major adverse cardiac events (MACE) in patients with chest pain. We investigated the frequency, circumstances and potential consequences of errors in its calculation. METHODS: We performed a secondary analysis of a stepped wedge trial of patients with chest pain presenting to nine Dutch emergency departments. We recalculated HEART scores for all patients by re-evaluating the elements age (A), risk factors (R) and troponin (T) and compared these new scores with those given by physicians in daily practice. We investigated which circumstances increased the probability of incorrect scoring and explored the potential consequences. RESULTS: The HEART score was incorrectly scored in 266 out of 1752 patients (15.2%; 95% CI 13.5% to 16.9%). Most errors occurred in the R ('Risk factors') element (61%). Time of admission, and patient's age or gender did not contribute to errors, but more errors were made in patients with higher scores. In 102 patients (5.8%, 95% CI 4.7% to 6.9%) the incorrect HEART score resulted in incorrect risk categorisation (too low or too high). Patients with an incorrectly calculated HEART score had a higher risk of MACE (OR 1.85; 95% CI 1.37 to 2.50), which was largely related to more errors being made in patients with higher HEART scores. CONCLUSIONS: Our results show that the HEART score was incorrectly calculated in 15% of patients, leading to inappropriate risk categorisation in 5.8% which may have led to suboptimal clinical decision-making and management. Actions should be taken to improve the score's use in daily practice

Secondary analysis of frequency, circumstances and consequences of calculation errors of the HEART (history, ECG, age, risk factors and troponin) score at the emergency departments of nine hospitals in the Netherlands

OBJECTIVE: The HEART score can accurately stratify the risk of major adverse cardiac events (MACE) in patients with chest pain. We investigated the frequency, circumstances and potential consequences of errors in its calculation. METHODS: We performed a secondary analysis of a stepped wedge trial of patients with chest pain presenting to nine Dutch emergency departments. We recalculated HEART scores for all patients by re-evaluating the elements age (A), risk factors (R) and troponin (T) and compared these new scores with those given by physicians in daily practice. We investigated which circumstances increased the probability of incorrect scoring and explored the potential consequences. RESULTS: The HEART score was incorrectly scored in 266 out of 1752 patients (15.2%; 95% CI 13.5% to 16.9%). Most errors occurred in the R ('Risk factors') element (61%). Time of admission, and patient's age or gender did not contribute to errors, but more errors were made in patients with higher scores. In 102 patients (5.8%, 95% CI 4.7% to 6.9%) the incorrect HEART score resulted in incorrect risk categorisation (too low or too high). Patients with an incorrectly calculated HEART score had a higher risk of MACE (OR 1.85; 95% CI 1.37 to 2.50), which was largely related to more errors being made in patients with higher HEART scores. CONCLUSIONS: Our results show that the HEART score was incorrectly calculated in 15% of patients, leading to inappropriate risk categorisation in 5.8% which may have led to suboptimal clinical decision-making and management. Actions should be taken to improve the score's use in daily practice

In-hospital prescription changes and documentation in the medical records of the primary care provider : results from a medical record review study

Background An increasing number of transitions due to substitution of care of more complex patients urges insight in and improvement of transitional medication safety. While lack of documentation of prescription changes and/or lack of information exchange between settings likely cause adverse drug events, frequency of occurrence of these causes is not clear. Therefore, we aimed at determining the frequency of in-hospital patients’ prescription changes that are not or incorrectly documented in their primary care provider’s (PCP) medical record. Methods A medical record review study was performed in a database linking patients’ medical records of hospital and PCP. A random sample (n = 600) was drawn from all 1399 patients who were registered at a participating primary care practice as well as the gastroenterology or cardiology department in 2013 of the University Medical Center Utrecht, the Netherlands. Outcomes were the number of in-hospital prescription changes that was not or incorrectly documented in the medical record of the PCP, and timeliness of documentation. Results Records of 390 patients included one or more primary-secondary care transitions; in total we identified 1511 transitions. During these transitions, 408 in-hospital prescription changes were made, of which 31% was not or incorrectly documented in the medical record of the PCP within the next 3 months. In case changes were documented, the median number of days between hospital visit and documentation was 3 (IQR 0–18). Conclusions One third of in-hospital prescription changes was not or incorrectly documented in the PCP’s record, which likely puts patients at risk of adverse drug events after hospital visits. Such flawed reliability of a routine care process is unacceptable and warrants improvement and close monitoring

In-hospital prescription changes and documentation in the medical records of the primary care provider : results from a medical record review study

Background An increasing number of transitions due to substitution of care of more complex patients urges insight in and improvement of transitional medication safety. While lack of documentation of prescription changes and/or lack of information exchange between settings likely cause adverse drug events, frequency of occurrence of these causes is not clear. Therefore, we aimed at determining the frequency of in-hospital patients’ prescription changes that are not or incorrectly documented in their primary care provider’s (PCP) medical record. Methods A medical record review study was performed in a database linking patients’ medical records of hospital and PCP. A random sample (n = 600) was drawn from all 1399 patients who were registered at a participating primary care practice as well as the gastroenterology or cardiology department in 2013 of the University Medical Center Utrecht, the Netherlands. Outcomes were the number of in-hospital prescription changes that was not or incorrectly documented in the medical record of the PCP, and timeliness of documentation. Results Records of 390 patients included one or more primary-secondary care transitions; in total we identified 1511 transitions. During these transitions, 408 in-hospital prescription changes were made, of which 31% was not or incorrectly documented in the medical record of the PCP within the next 3 months. In case changes were documented, the median number of days between hospital visit and documentation was 3 (IQR 0–18). Conclusions One third of in-hospital prescription changes was not or incorrectly documented in the PCP’s record, which likely puts patients at risk of adverse drug events after hospital visits. Such flawed reliability of a routine care process is unacceptable and warrants improvement and close monitoring