Monitoring patient dissatisfaction: a methodology based on SERVQUAL scale and statistical process control charts

The influence of service quality and anticipated emotions on donor loyalty: an empirical analysis in blood centres in Spain

Blood donation centres need to recruit and retain donors to ensure the effectiveness and efficiency of healthcare systems, as COVID-19 has recently evidenced. In such risky settings, blood donation services must increase donations. Service quality can increase donations but its evaluation only amounts to a cognitive evaluation, and not to an emotional appraisal. Consequently, both service quality and emotions should be considered when predicting donor behaviour. In fact, donating blood is an emotionally charged service, thus representing an ideal setting to investigate how emotions influence consumer behaviour. This research proposes a new method to predict blood donors' intentions by integrating a cognitive approach measuring perceived quality, and an emotional approach including anticipated emotions (both positive and negative) of 'donation' and 'non-donation'. Based on a sample of 30,621 active Spanish donors, it is concluded that service quality is an antecedent for anticipated emotions and that both service quality and anticipated emotions influence donor loyalty. Designing the donation process based on quality criteria would provoke encouraging emotions and diminish discouraging emotions, therefore improving donor loyalty.

Transitions between versions of the International Classification of Diseases and chronic disease prevalence estimates from administrative health data: a population-based study

Background

Diagnosis codes in administrative health data are routinely used to monitor trends in disease prevalence and incidence. The International Classification of Diseases (ICD), which is used to record these diagnoses, have been updated multiple times to reflect advances in health and medical research. Our objective was to examine the impact of transitions between ICD versions on the prevalence of chronic health conditions estimated from administrative health data.

Methods

Study data (i.e., physician billing claims, hospital records) were from the province of Manitoba, Canada, which has a universal healthcare system. ICDA-8 (with adaptations), ICD-9-CM (clinical modification), and ICD-10-CA (Canadian adaptation; hospital records only) codes are captured in the data. Annual study cohorts included all individuals 18 + years of age for 45 years from 1974 to 2018. Negative binomial regression was used to estimate annual age- and sex-adjusted prevalence and model parameters (i.e., slopes and intercepts) for 16 chronic health conditions. Statistical control charts were used to assess the impact of changes in ICD version on model parameter estimates. Hotelling’s T² statistic was used to combine the parameter estimates and provide an out-of-control signal when its value was above a pre-specified control limit.

Results

The annual cohort sizes ranged from 360,341 to 824,816. Hypertension and skin cancer were among the most and least diagnosed health conditions, respectively; their prevalence per 1,000 population increased from 40.5 to 223.6 and from 0.3 to 2.1, respectively, within the study period. The average annual rate of change in prevalence ranged from -1.6% (95% confidence interval [CI]: -1.8, -1.4) for acute myocardial infarction to 14.6% (95% CI: 13.9, 15.2) for hypertension. The control chart indicated out-of-control observations when transitioning from ICDA-8 to ICD-9-CM for 75% of the investigated chronic health conditions but no out-of-control observations when transitioning from ICD-9-CM to ICD-10-CA.

Conclusions

The prevalence of most of the investigated chronic health conditions changed significantly in the transition from ICDA-8 to ICD-9-CM. These results point to the importance of considering changes in ICD coding as a factor that may influence the interpretation of trend estimates for chronic health conditions derived from administrative health data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13118-8.

Re-evaluation of the healthcare service quality criteria for the Covid-19 pandemic: Z-number fuzzy cognitive map

Hospitals as healthcare centers have faced many challenges with the Covid-19 spread, which results in a decline in the quality of health care. Because the number of patients referred to hospitals increases dramatically during the pandemic, providing high-quality services and satisfying them is more important than ever to maintain community health and create loyal customers in the future. However, health care quality standards are generally designed for normal circumstances. The SERVPERF standard, which measures customer perceptions of service quality, has also been adjusted for hospital service quality measurement. In this study, the SERVPERF standard criteria for health services are evaluated in the Covid-19 pandemic. For this purpose, by considering the causal relationships between the criteria and using Z-Number theory and Fuzzy Cognitive Maps (FCMs), the importance of these criteria in the prevalence of infectious diseases was analyzed. According to the results, hospital reliability, hospital hygiene, and completeness of the hospital with ratios 0.9559, 0.9305, and 0.9268 are respectively the most influential criteria in improving the quality of health services in the spread of infectious diseases circumstances such as the Covid-19 pandemic. A review of the literature shows that in previous studies, comprehensive research has not been done on prioritizing the criteria for measuring the quality of health services in the context of the spread of infectious diseases.