The objectives of this study were to examine the association between patient perceived healthcare quality and self-reported medical, medication, and laboratory errors using cross-sectional and cross-national questionnaire data from eleven countries. In this research, quality of care was measured by a multi-faceted construct, which adopted the patient's perspectives. Five separated quality of care scales were assessed: Access to Care, Continuity of care, Communication of Care, Care Coordination, and Provider's Respect for Patients' Preferences. The findings from this investigation support a number of other published studies suggesting that Coordination of Care is an important predictor of perceived patient safety. After adjusting for potentially important confounding variables, an increase in peoples' perceptions of Coordination of Care decreased the likelihood of self-reporting medical errors (OR =0.605, 95% CI: 0.569 to 0.653), medication errors (OR =0.754, 95% CI: 0.691 to 0.830), and laboratory errors (OR =0.615, 95% CI: 0.555 to 0.681). Finally, results showed that the healthcare system type governing care processes modifies the effect of Coordination of Care on self-reported medication errors.

Darbo tikslas. Įvertinti klinikinės diagnostikos laboratorijos klaidas ir jų valdymo galimybes. Tyrimo metodika. Atlikta X ligoninės klinikinės diagnostikos laboratorijos klaidų registro 2007 – 2009 metų duomenų analizė ir susisteminti duomenys. Jais remiantis, identifikuotos klaidos, jų priežastys ir pasiskirstymas. Atlikta ligoninės skyrių, tiesiogiai susijusių su laboratoriniais tyrimais, darbuotojų (gydytojų ir slaugytojų) anketinė apklausa. Išdalinta 260, grąžinta 241 anketų (atsakas 92,7 proc.). Požymių ryšio reikšmingumui skaičiuotas χ2 kriterijus, dviejų proporcijų lyginimui - z kriterijus. Rezultatai. Iš visų klaidų (N=669) didžiausia dalis (80 proc.) identifikuota ikianaliziniame tarpsnyje. Dažniausios ikianalizinio tarpsnio klaidos - tyrimo užsakymo (22 proc.), ėminių ėmimo (23 proc.), užsakymo formos pildymo (21 proc.), įvykusios hemolizės (11 proc.). Kituose tarpsniuose klaidų pasiskirstymo dažnis ženkliai mažesnis: analiziniame. ir poanaliziniame po 10 proc. Analiziniame tarpsnyje didžiausią dalį užima klaidos, identifikuotos matavimo metu dėl ikianalizinių veiksnių poveikio (31 proc.), poanaliziniame - žmogiškojo faktoriaus ir elektroninių programų nesusidirbimo klaidos (41 proc.). Nustatyta, kad darbuotojų informuotumas apie laboratorijos klaidas ir jų valdymą yra nepakankamas. 55,9 proc. darbuotojų mano, kad apie galimas klaidas, lemiančias laboratorinių tyrimų patikimumą, bei jų išvengimo galimybes, žino tik iš dalies. Informacijos apie laboratorinio tyrimo... [toliau žr. visą tekstą] / Aim of the study: Evaluate clinical diagnostics laboratory errors and their management possibilities. Study methodology: Laboratory X error registry study performed (2007 – 2009 year). Survey among hospital staff related to laboratory test ordering conducted. Total responses: 241 (92.7% from 260 invitations). Criterions calculated: indication relation significance - χ2, couple proportions comparison - z. Results: Error distribution (total 669) by phase: 80% pre-analytical, 10% analytical, 10% post-analytical. Top errors in pre-analytical phase: specimen collection (23%), test ordering (22%), order form input (21%), hemolyzed sample (11%). Analytical phase most errors are influenced by pre-analytical variables (31%). Post-analytical phase most errors are caused by human factor and software malfunction (41%). Found, that hospital staff awareness about laboratory errors and their handling is insufficient. 55.9% staff responded they have only partial knowledge about errors influencing testing reliability and how to avoid errors. 51.3% staff has knowledge about test process organization. 33.3% staff knows about error classification by phase. 71.4% doctors and 42.6% nurses consider such information important and would like to learn more. 52% doctors and 33.8% nurses familiar with full set of available tests. More knowledge about available laboratory tests have staff of age >54y (58.1%), also, having employment history >24y (48.6%). Most of staff (expectation of 81.9% respondents... [to full text]

Abstract The aim of the study was to evaluate the usefulness of customer satisfaction surveys and spontaneous customer feedback procedure in a university hospital laboratory. Questionnaires containing closed-ended statements and an open-ended question were used in the customer satisfaction surveys targeted at the clinical units of the university hospital and regional health centres. Customer feedback documents including the subject matters of the reports, the investigations carried out and the actions taken were analysed using qualitative content analysis. The highest dissatisfaction rates in the clinical units were recorded for computerised test requesting and reporting, turnaround times of tests, missing test results and the schedule of phlebotomy rounds. In addition, additional instructions were needed. The most common causes of dissatisfaction among regional health centres were related to electronic data transfer of laboratory test requests and reports between health centres and the university hospital laboratory, need of additional instructions for handling of samples and preparation patients for laboratory tests, problems with decentralised phlebotomy services to hospital outpatients, and unawareness of the schedule of some less common laboratory tests. Further clarifications with selected customers were needed to specify the causes of dissatisfaction. Erroneous, delayed and lacking test results were the most common errors or defects revealed in the investigations of the spontaneous customer feedback reports from both the clinical units and the external customers. The most common underlying causes of errors were unintended errors and non-compliance with operating instructions. Systematic errors were found in one-sixth of the cases. Corrective actions were carried out in three-fourths of the cases. Satisfaction survey can be used as a screening tool to identify topics of dissatisfaction. However, further clarifications are often needed to find out the customer-specific causes of dissatisfaction and to undertake targeted corrective actions. Every reported case of customer feedback should be investigated to find out possible errors and their underlying causes so that appropriate corrective actions can be taken.