Shedding Light on the Roots of Dissatisfaction with Health Care Services in the State of Qatar: An Exploratory Study
Bibliographic record
Abstract
Introduction Dissatisfaction with health care performance is an important source of information about health care reforms as perceived by the public as it is associated with negative beliefs about health system. Previous studies have shown that dissatisfaction with health care has a long-term negative impact on the health care users' relationship with healthcare providers, health related behaviors, and health outcomes. In addition, a recent study conducted in Qatar, showed that approximately 24% of the studied population who used health care in the past 12 months prior to the study were dissatisfied with health care services provided in the country. Given that dissatisfaction with care can negatively impact on help-seeking behaviors, this finding could have grave public health implications. This has been witnessed in the context of high prevalence of chronic health conditions in Qatar where long-term relations with healthcare professionals are necessary for better chronic disease management, reduced disease-related complications, and mortality. This study aims to identify the sources of dissatisfaction with medical care among adults, Qataris and white collar migrants aged eighteen years or older. Methods This study is based on secondary data from a larger national survey, which was conducted during the fall of 2012 for the purpose of collecting household-based information on health services utilization and health-related expenditures. Disproportionate stratified probability sampling was employed to select a representative sample of households. A final sample of 3,080 completed face-to-face interviews (1,528 Qataris and 1,552 White Collar Migrants) using computer assisted personal interviewing (CAPI) method for a raw response rate of 78.1%. The sample included individuals who may or may not have used Qatar's health care system during the 12 months prior to survey administration. Respondents were asked to discuss the reasons for their discontent with healthcare services in Qatar by selecting pre-coded categories of dissatisfaction including: Waiting time to see the provider, language used to communicate, clarity of how things are explained to the patient, poor services provided (such as cleanliness, reception, respect, and parking), inability to choose provider or doctor, high costs and other reasons to be specified by respondents. A total of 711 open-ended responses to the “Other” category were translated, coded and analyzed qualitatively. “Crowdedness”, “staff and physicians' incompetence”, “medical errors”, “discrimination”, “disrespect”, and “lack of staff and services” are all themes that emerged as reasons for dissatisfaction. Analysis Arabic responses were translated into English and researchers discussed any dissimilar results until an agreement was reached on all translated responses. Upon reviewing the responses, themes, which were different from the pre-specified answer choices of the questionnaire, emerged. The researchers then coded the responses by assigning codes to each response, then compared against each other. Coding discrepancy was discussed until an agreement was reached. The codes of the open-ended responses were later merged with those of the pre-specified categories and the corresponding frequency for each coding category was calculated using STATA. The Alberta Quality Matrix for Health was used to guide the analysis of the themes based on the six dimensions of health system quality. Results The analysis of the open-ended responses that probed into reasons for respondents' dissatisfaction revealed thirteen categories of dissatisfaction that were related to four different dimensions of quality of healthcare, based on the Alberta Quality Matrix for Health. The most common dimension of dissatisfaction with health care in Qatar was accessibility, which refers to the provision of health service in the most optimum setting and within “reasonable time and distance”. Safety was the second most common dimension reported by the respondents. This construct relates to minimizing any threats that could cause harm. Acceptability, such as the provision of respectful and patient-centered health services was the third dimension identified, followed by efficiency, which is mainly related to the optimal use of resources, to achieve the best desired health outcomes. Conclusion Identifying the roots of dissatisfaction with health care services among distinct social groups can be achieved by analyzing responses to simple open-ended questions in routinely administered population health surveys. This is important for monitoring the quality of care in heterogeneous population contexts as well as engaging the public in the process of developing a world-class health care system as per Qatar's national vision of 2030. This research highlights priority needs to be addressed by the Qatari government in order to increase health care satisfaction as part of the quest for better health care in the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".