Skip to main content
Download PDF

Quality of care and associated factors among patients with epilepsy at public hospitals in Arba Minch Town: a facility-based cross-sectional study

BMC Neurology volume 24, Article number: 485 (2024) Cite this article

Abstract

Background

Epilepsy is one of the most common neurologic disorders affecting approximately 51 million people globally and is associated with significant cases of age-standardized DALYs (182.6 per 100 000 people). The quality of health care services offered to people suffering from epilepsy often fails to meet standards in Ethiopia or internationally. This study was designed to assess the quality of care and associated factors among patients with epilepsy at public hospitals in Arba Minch Town, 2024.

Method

A facility-based cross-sectional study was conducted among 392 adult epileptic patients attending public hospitals in Arba Minch Town. Data entry was performed via Epi-data 3.1 software, and the data were analyzed via SPSS version 24 software. Binary logistic regression analysis was used to evaluate the associations between quality of care and sociodemographic, disease-related, and treatment-related factors. Multivariate logistic regression analysis was applied to identify factors independently associated with quality of care.

Results

Three hundred ninety-two adults with epilepsy participated in this study, for a response rate of 92.7%. More than one-half of the 237 (60.5%) patients were males, with a median age of 31 ± 12 years (interquartile range). Fewer than one-half (44.1%) of the patients adhered to antiepileptic medicines. The overall proportion of patients receiving quality care was 213 (54.3%). The seizure control rate was also low, at 130 (33.2%). Patients aged 18–29 years [AOR = 30.8 (95% CI, 8.22–35.616, p < 0.000)] and aged 30–39 years [AOR = 18.4 (95% CI, 5.016–67.613, p < 0.000)], and a seizure frequency of less than three [AOR = 2.318 (95% CI, 1.028–5.225, p < 0.043)] were positively associated with quality of care. Whereas, having poor knowledge about epilepsy [AOR = 0.107 (95% CI, 0.0.057–0.202, p < 0.000)] was negatively associated with quality care.

Conclusion

The quality of care provided to adult epilepsy patients at Arba Minch was low. In addition, patient knowledge, medication adherence, and the seizure control rate were also suboptimal. Therefore, addressing identified factors by involving all relevant stakeholders (health professionals, hospitals, zonal health departments, regional health bureaus, and patients) is critical for improving the quality of care. In addition, researchers willing to study this topic should use strong designs that can determine causal determinants of quality care.

Peer Review reports

Background

The quality of healthcare is the application of medical science and technology in a manner that maximizes its benefit to health without correspondingly increasing risk [1, 2]. Institute of medicine defines quality care as safe, effective, patient-centered, timely, efficient, and equitable care. From the context of epilepsy, quality epilepsy care can be defined as early detection and identification of types of seizures, and any associated conditions, providing evidence-based treatment for seizure control and consulting specialist in case of uncontrolled seizures and engaging the patient during diagnosis, treatment and follow-up [3]. It can also be defined as consistently discerning the patient by providing efficacious, effective, and efficient healthcare services according to the latest clinical guidelines and standards, which meet the patient’s needs and satisfy providers [4].

Epilepsy is a disease of the brain characterized by at least two unprovoked (or reflex) seizures occurring > 24 h apart; one unprovoked (or reflex) seizure and a probability of further seizure recurrence (at least 60%) occurring over the next 10 years; and a diagnosis of epilepsy syndrome [5]. An epileptic seizure can also be classified as unilateral (retained consciousness or impaired consciousness), bilateral (motor with all motor components or nonmotor with all of its components), or unilateral to bilateral (motor or nonmotor) [6].

Epilepsy is one of the most common neurologic disorders affecting approximately 51 million people globally and is associated with a significant number of age-standardized DALYs (182.6 per 100 000 people) [7]. A strategy for performance measurement and quality improvement in epilepsy care should involve people with epilepsy and their families, relevant professionals, researchers, health and human services professionals, and experts in terms of performance metrics and healthcare quality improvement [8]. The World Health Assembly also recommended coordinated action against epilepsy and its consequences [9].

Ongoing efforts are made to improve the lives of people with epilepsy and their families through sustained and coordinated care, ranging from increasing the understanding of the biomedical mechanisms of the disorder to enhancing clinical treatment and community services [10, 11]. People with epilepsy have relatively high rates of psychiatric comorbidities and may experience adverse psychosocial outcomes. Compared with people who do not have seizures, those who do have seizures have an approximately threefold increase in mortality [12].

Despite the importance of accessing timely coordinated care and early and accurate diagnosis, studies have indicated many gaps and unmet needs in the care and treatment of people with epilepsy (PWE) [13]. The treatment gap (the proportion of people with active epilepsy who are not receiving appropriate therapy). This is a significant issue in low- and middle-income countries, such as Ethiopia, where lack of healthcare resources compounds the problem and requires urgent action [14].

The quality of health care services offered to people suffering from epilepsy often fails to meet standards in Ethiopia or internationally. Studies have indicated that health professionals do not comprehensively address essential elements of care with PWE. A recent systematic review of unmet needs identified challenges that PWE experience in the availability, accessibility, and acceptability of services. Regarding availability, a lack of specialist services, long waiting times, and insufficient consultation time were reported [15]. In response, the American Academy of Neurology (AAN) identified eight performance metrics that could be used for quality improvement. The eight metrics include documentation in the medical records of “seizure type and current seizure frequency”; documentation of the etiology of epilepsy or epilepsy syndrome; EEG or computed tomography scan results reviewed, requested, or test ordered; querying and counseling about side effects of [seizure medication]; surgical therapy referral consideration for [refractory] epilepsy; counseling about epilepsy-specific safety issues; counseling for women of childbearing potential with epilepsy; and comorbidity management [16] (Fig. 1).

Fig. 1
figure 1

Conceptual framework indicating quality of care-associated factors on the basis of evidence-based guidelines and eight metrics and contributing factors adapted from a review of the literature. AAN = American Academy of Neurology; AEDs = Antiepileptic Drugs

Full size image

Despite efforts made to improve the quality of epilepsy care through different strategies including physician performance metrics [17], the gap in epilepsy care is still an important issue contributing to morbidity and mortality in low and middle-income countries like Ethiopia [7, 18]. This calls for efforts to ensure affordable access to quality care for patients with epilepsy [19], and identifying country-specific efficient methods to improve the quality of care [20].

An evidence-based recommendations and performance metrics are provided to improve the quality of epilepsy care [21]. However, very little is known about epilepsy in Ethiopia, and evidence concerning the quality of care provided to patients with epilepsy is lacking. This study determined the quality of care provided to patients with epilepsy and the determinants of good-quality care at public hospitals in Arba Minch Town. The findings of this study could provide relevant information to government offices and stakeholders for future planning and interventions to promote and maintain appropriate knowledge and quality care for patients with epilepsy in Arba Minch Town.

Methods and materials

Study area and period

The study was conducted in two hospitals in Arba Minch Town, Ethiopia. The southern Ethiopian region is one of the largest regions in Ethiopia, accounting for more than 10% of the country’s land area and an estimated population of 20,768,000 (May 2018), almost one-fifth of the country’s population. In 2008, less than one-tenth of its population (8.9%) lived in urban areas in the region. The southern Ethiopian region has twelve administrative zones. Wolaita Sodo is the region’s political and administrative center. Six regional bureaus were established in Wolaita Sodo, Dilla, Arba Minch, Sawla, Karati, and Jinka [22]. One general hospital and one district hospital with experience in providing epilepsy care were included. The selected public hospitals included Arba Minch General Hospital and Dile Fana Primary Hospital. The study was conducted from October 1, 2023, to November 30, 2023.

Study design

A facility-based cross-sectional study was conducted among adult epileptic patients at public hospitals in Arba Minch Town.

Population

Source populations

The source populations for this study were all adult epileptic patients who were followed up at public hospitals in Arba Minch Town and whose follow-up records were available.

Study populations

The study population included epileptic patients who were followed up at public hospitals in Arba Minch Town and whose follow-up records in two public hospitals fulfilled the inclusion criteria.

Eligibility criteria

Inclusion criteria

All adults (18 years and older) with epilepsy had at least 4 months of follow-up visits before data collection (to ensure adequate time for adherence) and received care during the study period from the selected hospitals and their respective follow-up records.

Exclusion criteria

Patients who were unwilling to participate, patients who had less than 4 months of follow-up, patients with incomplete patient records (those without diagnostic imaging records and refill medications, laboratory requests, and results), and those who were illegible were excluded. Finally, patients with provoked seizures (metabolic disturbances, drug intoxication, withdrawal, stroke, intracerebral hemorrhage, trauma, or malignancy) were also excluded from the study. This is because the management of provoked seizures is different from unproved seizures. For example, seizures in patients with newly diagnosed brain tumors do not respond to anticonvulsant medications. Prevention of seizures from alcohol withdrawal syndrome requires thiamine and anticonvulsant medications (diazepam or lorazepam). Similarly, a seizure in renal failure is provoked by metabolic disturbances or drugs that require correction of the triggering factors. In addition to this, for patients with tuberculosis meningitis long-term antiepileptic drug treatment is not needed.

Study variables

Dependent variables

  • Quality of care.

Independent variables

Patient-related variables included sociodemographic characteristics, treatment adherence, and knowledge. Disease-related variables included duration of epilepsy, type of epilepsy, cases of epilepsy, and presence of comorbidities. Drug-related variables (type of antiepileptic medication, regimen, dose, and medications for commodities). Health system-related variables(availability of diagnostic tests, availability of evidence-based guidelines, and access to antiepileptic medicines) were also included.

Sample size and sampling technique

Sample size determination

The sample size was determined by using a single population proportion formula and taking the level of quality of care provided as 50%, since there are no studies on the quality of care for patients with epilepsy in Ethiopia, and the Z value was 1.96, with a 95% confidence interval. We calculated the sample size by using 50% quality of care provided to epileptic patients to obtain the maximum sample size. After a 5% nonresponse rate was reached, 403 adults with epilepsy who were receiving follow-up care were included

$$\eqalign{ n& ={{{{(Z\alpha /2)}^2}P\left( {1 - P} \right)} \over {{d^2}}} = {\rm{ }}384 \cr & = 384 + (384*10\% ) = 423 \cr}$$

Where: n = is the sample size.

  • Z2= standard normal deviation, set at 1.96, corresponds to the 95% confidence interval.

  • d = is the desired level of precision/margin of error (0.05).

  • p= Estimated level of quality of care (p=50%), and q is 1-p.

The sample size for the second objective was determined by using the proportion of factors affecting the quality of care, taking the prevalence of patient knowledge about epilepsy from a study conducted at Jimma University Specialized Hospital as 25.5% and 60% of the respondents knew the cause and treatment of epilepsy, respectively [23]. Using a 60% proportion, the estimated sample size was 368, and treatment adherence was 32% according to a study conducted at Yigalem General Hospital [24]. Similarly, when a 32% proportion was used, the estimated sample size was 335. Therefore, the sample size based on the first objective [43] was selected for this study.

Sampling techniques

Two hundred fourteen and 178 adult epilepsy patients from Arba Minch General Hospital and Dil Fana Hospital, respectively included. Consecutive sampling was employed, where every eligible patient presenting during the study period was recruited.

Data collection tools and procedures

The data collection tools used were developed through a rigorous review of the scientific evidence and evidence-based clinical guidelines for epilepsy management. Concerning measuring performance and improving quality in epilepsy care, the American Academy of Neurology (AAN) identified eight performance metrics [16, 25]. Based on these eight metrics and the QUIET (QUality Indicators in Epilepsy Treatment), we developed a tool containing 22 questions. The contextualized tool contains information on epilepsy diagnosis, treatment and follow-up, and aspects of care for women with epilepsy and managing comorbidities. We adapted the Donabedian model for quality care from another study [26]. We assessed the quality of care from the structure-process and outcome perspectives for each domain. The overall quality is reported as good if all the domains are rated as quality otherwise poor [27]. Patient knowledge was assessed via questionnaires designed for this purpose. Patients who answered 75% or above correctly were considered to have good knowledge and were otherwise considered poor [28]. Adherence to treatment was evaluated via modified Hill-bone self-reports for measuring adherence to medication [29]. The scale has 14 items with a four-point response format: [4] all the time [3], most of the time [2], some of the time, and [1] never (Table 1). The items are assumed to be additive, and when summed, the total score ranges from 14 (minimum) to 56 (maximum). Patients who had a mean score of 28 or above on the questions were considered adherent to treatment and were otherwise considered nonadherent. We modified the bone-Hill medication compliance scale to address our disease context. The tool was originally developed for assessing medication adherence in patients with CVD. It contains questions related to salt consumption. This approach is used to address salt consumption-related blood pressure increases. In patients with epilepsy, salt consumption has no significant effect, and we replaced these questions with questions about alcohol consumption and drug use since they affect the treatment outcome of patients with epilepsy, including seizure control. Health system-related variables, mainly the availability of diagnostic tests, availability of evidence-based guidelines, and access to antiepileptic medicines, were assessed via interviews with health professionals treating epilepsy patients via a questionnaire.

Data quality control, processing, and analysis

Data quality control

The questionnaires were prepared in English, and the patient interview part of the questionnaire was translated into Amharic and translated back into English to check its consistency. The Amharic version of the patient interview questionnaire and the English version of the data abstraction form were used for data collection. The questionnaire was pretested on 30 adults with epilepsy in Chencha District Hospital to ensure that the respondents could understand the questions and to check for consistency, and possible amendments were made based on the findings. Three professional nurses (BSc.) for data collection and one senior professional working in the respective health facilities for supervision were oriented before data collection about principles to follow during data collection and the contents of the data collection format for one day by the principal investigator. The principal investigator throughout the data collection period conducted continuous follow-up and supervision. The collected data were checked daily for completeness and consistency by the principal investigator.

Data processing and analysis

Data entry was performed via Epi-data 3.1 software. After data processing, the analysis was performed via SPSS version 24.0. A summary descriptive statistic was computed for most variables, such as sociodemographic factors, disease-related factors, and treatment-related factors. A multicollinearity test was performed, and all the variables had a variance inflation factor (VIF) of less than 10. Binary logistic regression analysis was used to evaluate the associations between quality of care and sociodemographic factors, disease-related factors, and treatment-related factors. To avoid many variables and unstable estimates in the subsequent model, only variables that reached a p-value less than 0.25 in the binary analysis were used in the multivariate logistic analysis. Multiple logistic regression analysis was applied to identify predictors of quality of care. A point estimate of the odds ratio (OR) with a 95% confidence interval (CI) was determined to assess the strength of the association between the independent and dependent variables. For all the statistically significant tests, a p value < 0.05 was used as the cutoff point.

Operational definition

Medication adherence was determined via modified Hill-bone self-reports for measuring adherence to medication [29]. Patients who had a mean score of 28 or above on the questions were considered adherent to treatment and were otherwise considered nonadherent.

Quality care

If diagnosed, treated, or followed up, aspects of care for women with epilepsy and comorbidity management are per evidence-based guidelines (i.e., structure-process and outcome) [26, 30]; otherwise, they are considered poor.

Results

Sociodemographic characteristics

Three hundred ninety-two adults with epilepsy participated in this study, with a response rate of 92.7%. More than one-half of the 237 (60.5%) were males, and 155 (39.5%) were females, with a median age of 31 ± 12 (interquartile range) years ranging from 18 to 76 years. The majority (184, 46.9%) of patients were 18–29 years old, and 134 (34.2%) were 30–39 years old. More than one-half of patients (212, 54.1%) were of Gamo ethnicity, and 171 (43.6%) were protestant. One-half (50.8%) of the patients were illiterate, followed by 115 primary school-aged patients (29.3%). More than six out of the ten (62.8%) were merchants (Table 1).

Table 1 Sociodemographic characteristics of adult patients with epilepsy admitted to public hospitals in Arba Minch Town, January 2024
Full size table

Patient knowledge

Approximately two-thirds (67.9%) of the patients had good knowledge about epilepsy, and 126 (32.1%) had poor knowledge. The mean knowledge score of the patients was 10.25 ± 1.88, ranging from five to 14. Among the 14 questions, 374 (95.4%) address the impact of epilepsy on quality of life and academic performance. Similarly, 325 (82.9%) patients reported that epilepsy was not caused by an ancestor’s sin, 278 (70.9%) said that the disease was not contagious, and 177 (45.2%) knew it was a mental illness. However, very few people have adequate knowledge of the role of allopathic and Ayurveda/traditional treatments for epilepsy. Fewer than one-third of the 114 (29.1%) patients did not know the conditions that increase seizure risk. Patients’ knowledge of what to do when they see a person experiencing an epileptic attack was also low, at 177 (45.2%) (Table 2; Fig. 3).

Table 2 Knowledge of adult epilepsy patients attending public hospitals in Arba Minch Town, January 2024
Full size table

Medication adherence

We assessed medication adherence via a bone-Hill medication compliance scale modified for our disease context. Fewer than one-half (44.1%) of the patients adhered to antiepileptic treatment, and 219 (55.9%) were nonadherent. The mean patient adherence score was 26.4 ± 5.98, ranging from 15 to 42. Among the questions, 101 (25.8%) patients did not forget their medication when they were sick, and 71 (18.1%) patients did not stock out for medicine. However, 15 (3.8%) missing appointments and 31 (7.9%) not using recreational drugs were the least common practices requiring due attention (Table 3).

Table 3 Patient adherence to antiepileptic medications at public hospitals in Arba Minch Town, January 2024
Full size table

Quality of epilepsy care

We evaluated the quality of care via the Quality Indicators in Epilepsy Treatment (QUIET) tool. The overall quality of care (quality of diagnosis, quality of treatment and follow-up, quality of care, and comorbidity management) was 213 (54.3%). The seizure control rate was low (130 (33.2%)), as evidenced by the documented presence of seizures after the initiation of AEDs (262 (66.8%)). Just above one-half of 215 (54.8%) of the patients had a detailed history taken during the evaluation, and 293 (74.7%) received information on driving restrictions. Concerning the eight-quality metrics of the American Academy of Neurology (AAN), 238 (85.6%) had seizure types documented, and 335 (85.4%) had seizure frequency documented. Similarly, 178 (45.4%) had an etiology of epilepsy or an epilepsy syndrome documented, and 78 (19.9%) had EEG, MRI, or CT results or tests requested. Counseling about antiepileptic drug side effects was given to 343 patients (87.5%), and surgical therapy referral for intractable epilepsy was performed for 38 patients (80.9%). In addition, 87 (58.4%) of the women were receiving counseling during their childbearing years, and 109 (76.2%) had managed their comorbidities (Table 4). The quality of care for the diagnosis of epilepsy and for women’s care was lower than that for the other components of care (226 (57.6%) and 86 (58.0%), respectively). However, 308 patients were treated and followed up (78.6%), followed by comorbidity management, and 109 (76.2%) were comparably good (Table 4; Fig. 2).

Table 4 Quality of care provided to people with epilepsy at public hospitals in Arba Minch Town, January 2024 (n = 392)
Full size table
Fig. 2
figure 2

Quality of care provided to people with epilepsy at public hospitals in Arba Minch Town based on the American Academy of Neurology (AAN) in January 2024 (n = 392)

Full size image

Concerning physician response to uncontrolled seizures or seizures after initiating antiepileptic treatment, 59 (30.7%) compliance assessment, Patient education on lifestyle modification 52 (27.1%), followed by increase in AED dose 36 (18.8%), referral to higher level facility 25 (13.3%) and changing AED 20 (10.4%) (Fig. 3).

Fig. 3
figure 3

Physician interventions for uncontrolled seizures in Arba Minch town, January 2024. AED = Antiepileptic drugs

Full size image

Health system for epilepsy care

Concerning the health system for epilepsy care, we interviewed 16 professionals working in epilepsy clinics at public hospitals in Arba Minch Town. Nine (56.3%) professionals reported a shortage of diagnostic facilities and a lack of access to evidence-based medicines. However, 10 (75.0%) professionals reported that general treatment guidelines were available. However, there are no epilepsy-specific guidelines in either facility (Table 5).

Table 5 Health system variables for epilepsy care at public hospitals in Arba Minch Town, January 2024
Full size table

Factors associated with quality of care

According to our bivariate analysis, age 18–29 years [COR = 0.043 (95% CI = 0.013–0.144, p = < 0.000)], age 30–39 years [COR = 0.048 (95% CI = 0.014–0.160, p < 0.000)], age 40–49 years [COR = 0.03 (95% CI = 0.007–0.127, p< 0.000)], and seizure frequency less than three [COR = 2.431 (95% CI = 1.199–4.929, p < 0.014)] were associated with the quality of epilepsy care. Similarly, poor knowledge [COR = 9.988 (95% CI, 5.663–17.614; p < 0.000)] and treatment adherence [COR = 1.458 (95% CI, 1.075–2.182; p < 0.047)] were associated with the quality of epilepsy care. After these variables were subjected to multivariate logistic regression via the backward elimination method to control for confounding variables, patients aged 18–29 years [AOR = 30.8 (95%, CI, 8.22-35.616, p < 0.000)], aged 30–39 years [AOR = 18.4 (95%, CI, 5.016–67.613, p < 0.000)] were more likely to have good-quality care than were those aged 50 years and above. Patients with a seizure frequency less than three were two times (AOR = 2.318; 95% CI, 1.028–5.225; p < 0.043) more likely to have quality care than patients with five or more seizures. Patients with poor knowledge about epilepsy were 10% less likely [AOR = 0.107 (95%, CI, 0.0.057–0.202; p < 0.000)] to have quality care than were those with poor knowledge (Table 6).

Table 6 Factors affecting the quality of epilepsy care among adults at public hospitals in Arba Minch Town, January 2024
Full size table

Discussion

General description of the study

In this study, we evaluated the quality of care provided to 392 adults with epilepsy at public hospitals in Arba Minch Town. The majority of patients were young (18–29 years; 46.9%), followed by those aged 30–39 years (134; 34.2%). This finding is in line with a study conducted at Mettu Karl Specialized Hospital, which revealed that a majority were in the age range 18–30 years [31]. This population is productive, and addressing epilepsy and its determinants in the study areas as well as the country is critical to improving the mental health of the young population.

In this study, 266 (67.9%) patients had good knowledge of epilepsy. Among the 14 questions, 177 (45.2%) and 374 (95.4%) concerned the cause (mental illness) and treatment of epilepsy, respectively. Fewer than one-third of 114 patients (29.1%) did not know the conditions that can increase seizure risk. Patients’ knowledge of what to do when they see a person experiencing an epileptic attack was also low at 177 (45.2%). This percentage is relatively higher than that reported in a community-based study conducted to evaluate public and patient knowledge about epilepsy in different settings, which revealed that 56.4% [32] and 25.8% of the participants had good knowledge about epilepsy [33]. A similar systematic review and meta-analysis involving 12 studies revealed that 47.37% of the public has good epilepsy knowledge [34]. A similar study conducted at Jimma University Specialized Hospital among 180 epileptic patients revealed that 46 (25.5%) and 108 (60%) of the respondents knew the cause and treatment of epilepsy, respectively [23]. This could be due to differences in the study population. Our study evaluated knowledge about the disease among patients, and the claimed study evaluated public knowledge about epilepsy. In addition to this, variations in counseling practices, and healthcare infrastructure like diagnostic facilities could contribute to variation.

With respect to adherence to antiepileptic medications, 173 (44.1%) patients had good adherence to treatment. This is less than the findings from studies conducted in Jimma Medical Center, 212 (63.5% [35], Sudan, 62 (65.0%) [36], and India, 49.9% [37] of adults with epilepsy were adherent to antiepileptic drugs. This variation could be due to socioeconomic factors like monthly income, educational status, and attitude toward medication effectiveness. However, these findings are greater than those from Amanuel Mental Specialized Hospital which reported 16.38% adherence to epilepsy treatment [38], and among epileptic patients at Yirgalem General Hospital, 62 (32%) were treatment adherent [24]. The type of patients included in the studies and the variation in sociodemographic conditions can explain the variation. Amanuel Hospital is a mental illness-specialized hospital; patients with severe disease and comorbid mental illnesses such as depression are more likely to participate. However, in our study, patients with less severe conditions participated. Even though the reported adherence is comparable, it is still less than one-half. Therefore, it is important to design and implement strategies (education, counseling, and behavioral interventions [use of intensive reminders]) to improve medication adherence in this population [39].

Generally, about 70% of patients are estimated to have controlled seizures when they are properly diagnosed and treated [10]. In this study, about one-third of 130 (33.2%) of patients had controlled seizures. This is greater than findings from a study conducted in Zambia, which reported 52 (23.6%) seizure control rate [40]. This could be due to the difference in the definition of seizure control (i.e. 3 months) used in this study. Most studies use achieving a 1–2 years seizure-free stay on follow-up to define remission (seizure control) [41]. On the other hand, the finding is lower than evidence from systematic review, 49% [42], Mettu Karl Hospital, 43.96% [31], Gondar University Hospital, 138 (43.1%) [43], and South West Ethiopia, 165 (52.5%) [44]. This low level of seizure control could be explained by personal and socioeconomic factors like occupational status, poor sleep quality, Insomnia, number of medications, presence of comorbidity, and medication adherence [45]. This requires due attention from healthcare providers and all relevant stakeholders. Improving patient knowledge, treatment adherence and access to diagnostic facilities and medicines can improve the reported rate of low seizure control. In addition, integrating epilepsy treatment into primary healthcare systems could further improve the seizure control rate [14].

Quality of epilepsy care

The overall quality of care (quality of diagnosis, quality of treatment and follow-up, quality of care, and comorbidity management) was 213 (54.3%). This finding is almost comparable with findings that the quality of care for adults with epilepsy was 55.6% [27]. Just above one-half 215 (54.8%) of the patients had a detailed history taken during the evaluation, and 293 (74.7%) received information on driving restrictions. The majority 343 (87.5%) patients had counseling about the adverse effects of antiepileptic drugs. A similar study revealed that 66% of the patients received counseling about the side effects of AEDs during every visit. Almost all patients with intractable epilepsy were referred for surgical therapy. Safety issues were explained to 37% of the patients, and less than half of the women of childbearing age with epilepsy had received counseling regarding contraception and pregnancy at least once a year [46]. Evidence of counseling about antiepileptic drug side effects was present in 54 (34%) records. Counseling for women of childbearing potential was documented in 18 (33%) relevant records [47]. This highlighted that the quality of care provided to patients with epilepsy was below standard and needed attention from professionals, the health care system, patients, and the general public.

More than eight out of the ten 238 (85.6%) and 335 (85.4%) patients had seizure types and seizure frequencies documented. Similarly, 178 (45.4%) patients had documented etiology of epilepsy or epilepsy syndrome. Findings from a similar study revealed that 142 (88%) patients had documented seizure type and seizure frequency at each visit. Similarly, the etiology of seizure or epilepsy syndrome was documented in 93 (58%) patients [47].

In this study, less than one-fourth of the 78 (19.9%) patients had EEG, MRI, or CT results or tests requested. Surgical therapy referral for intractable epilepsy was performed for 38 patients (80.9%). These findings are lower than those of a similar study conducted in the USA, which reported that > 70% of new-onset epilepsy patients underwent diagnostic procedures (such as EEG and neuroimaging) [3]. Improving access to imaging studies could contribute to diagnostic quality since the classification of seizure types requires this approach.

In addition, 87 (58.4%) of the women were receiving counseling during their childbearing years, and 109 (76.2%) had managed comorbidities. These findings are greater than those from a similar study based on eight epilepsy care quality measures, which revealed that less than half (37%) of the women of childbearing age with epilepsy had received counseling regarding contraception and pregnancy at least once a year [46]. A study conducted in the USA reported that educational and counseling measures were provided or documented to < 50% of patients [3]. Counseling provided for women of childbearing potential was documented in 18 (33%) relevant records [47], and counseling for women of childbearing potential was documented in 18 (33%) relevant records [47]. The quality of care for adults with epilepsy assessed using the Quality Indicators in Epilepsy Treatment (QUIET) measure showed that care specific to women had the lowest concordance, 45%, with chronic care [27]. This better performance could be explained by differences in the study period, tools used, and sociodemographic characteristics of the patients.

Younger age is associated with better quality of care. Patients aged 18–29 years [AOR = 30.8 (95% CI, 8.22–35.616; p < 0.000)] and 30–39 years [AOR = 18.4 (95% CI, 5.016–67.613; p < 0.000)] were more likely to have good-quality care than were those aged 50 years and above. The improved awareness of the young population and resistance to antiepileptic medication among long-term users could explain these findings. In addition, age-related factors, such as polypharmacy, affect medication adherence [48].

In this study, patients with a seizure frequency less than three were two times more likely to have quality care [AOR = 2.318 (95%, CI, 1.028–5.225; p < 0.043)] than patients with five or more seizures. This could be explained by a seizure frequency-related reduction in the self-care of patients with epilepsy [48]. In addition, a higher seizure frequency is associated with uncontrolled seizures and could affect treatment adherence [43].

Patients with poor knowledge of epilepsy were 10% less likely [AOR = 0.107 (95% CI, 0.0.057–0.202; p < 0.000)] to have quality care than those with poor knowledge. This is because patients with epilepsy need to know about the diagnosis, treatment, and maintenance of psychosocial and comorbidity-related problems. Therefore, enhancing overall self-management knowledge through public education, media, digital technology, and peer education can improve quality care and treatment outcomes. Patients and public awareness of the disease and its management principles should support this. This is because knowledge is relevant only when patients and communities have the awareness and desire to engage first, and only then will knowledge lead to successful change [49].

Strengths and limitations of this study

The strength of the study relies on its methodology. Adequate and representative sample size was used to answer the question under study, and the Donabedian model integrated with the American Academy of Neurology quality metrics was used. However, no temporal relationship was identified due to the nature of the study. The use of patient records might contribute to the under- or overestimation of quality of care.

Conclusion

The quality of care provided to adults at selected public hospitals was low. In addition, patient knowledge, medication adherence, and the seizure control rate were also suboptimal. Age 18–29 years, age 30–39 years, and low seizure frequency were positively associated with quality of care. However, poor knowledge about epilepsy was negatively associated with quality care. Therefore, health professionals providing care should educate patients about epilepsy and its management including medication adherence and lifestyle management. Respective hospitals should provide evidence-based guidelines for the management of epilepsy. The regional health bureau should ensure access to diagnostic facilities and medicines. Patients should be discussed with their care providers before taking any other drugs, including traditional medicines. Patients should adhere to their treatment schedule and communicate any modifications needed with their providers. Finally, researchers willing to study this topic should use strong designs that can determine causal determinants of quality care.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

AED:

Antiepileptic Drug

ASM:

Anti-Seizure Medicine

ILAE:

International League Against Epilepsy

NICE:

National Institute for Health and Care Excellence

OPD:

Outpatient Department

PWE:

People with Epilepsy

QALYs:

Quality-Adjusted Life Years

QOL:

Quality of Life

WHO:

World Health Organization

References

  1. Mosadeghrad AM. Factors affecting Medical Service Quality. Iran J Public Health. 2014;43(2):210–20.

    PubMed  PubMed Central  Google Scholar 

  2. Mosadeghrad AM. A conceptual framework for quality of care. Mater Sociomed. 2012;24(4):251–61.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Altalib H, McMillan KK, Padilla S, Pugh MJ. Epilepsy quality performance in a national sample of neurologists and primary care providers: characterizing trends in acute and chronic care management. Epilepsy Behav. 2021;123:108218.

    Article  PubMed  Google Scholar 

  4. Mosadeghrad AM. Healthcare service quality: towards a broad definition. Int J Health Care Qual Assur. 2013;26(3):203–19.

    Article  PubMed  Google Scholar 

  5. Mathern GW, Beninsig L, Nehlig A. From the editors: Epilepsia’s 2014 operational definition of Epilepsy survey. Epilepsia. 2014;55(11):1683–7.

    Article  PubMed  Google Scholar 

  6. Sarmast ST, Abdullahi AM, Jahan N. Current classification of seizures and epilepsies: scope, limitations and recommendations for Future Action. Cureus. 2020;12(9):e10549.

    PubMed  PubMed Central  Google Scholar 

  7. Beghi E, Giussani G, Nichols E, Abd-Allah F, Abdela J, Abdelalim A, et al. Global, regional, and national burden of epilepsy, 1990–2016: a systematic analysis for the global burden of Disease Study 2016. Lancet Neurol. 2019;18(4):357–75.

    Article  Google Scholar 

  8. Reid AY, Metcalfe A, Patten SB, Wiebe S, Macrodimitris S, Jetté N. Epilepsy is associated with unmet health care needs compared to the general population despite higher health resource utilization–a Canadian population-based study. Epilepsia. 2012;53(2):291–300.

    Article  PubMed  Google Scholar 

  9. Covanis A, Guekht A, Li S, Secco M, Shakir R, Perucca E. From global campaign to global commitment: the World Health Assembly’s resolution on epilepsy. Epilepsia. 2015;56(11):1651–7.

    Article  PubMed  Google Scholar 

  10. Organization WH. Epilepsy: a public health imperative. World Health Organization; 2019.

  11. Hesdorffer DC, Beck V, Begley CE, Bishop ML, Cushner-Weinstein S, Holmes GL, et al. Research implications of the Institute of Medicine Report, Epilepsy across the spectrum: promoting health and understanding. Epilepsia. 2013;54(2):207–16.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Fisher RS, Acevedo C, Arzimanoglou A, Bogacz A, Cross JH, Elger CE, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia. 2014;55(4):475–82.

    Article  PubMed  Google Scholar 

  13. Higgins A, Downes C, Varley J, Tyrell E, Normand C, Doherty CP, et al. Patients with epilepsy care experiences: comparison between services with and without an epilepsy specialist nurse. Epilepsy Behav. 2018;85:85–94.

    Article  PubMed  Google Scholar 

  14. The Lancet Regional Health –, Western P. Addressing the epilepsy treatment gap in low resource settings. Lancet Reg Health – Western Pac. 2024;45.

  15. Mahendran M, Speechley KN, Widjaja E. Systematic review of unmet healthcare needs in patients with epilepsy. Epilepsy Behav. 2017;75:102–9.

    Article  PubMed  Google Scholar 

  16. Fountain NB, Ness PCV, Swain-Eng R, Tonn S, Bever CT Jr., For the American Academy of Neurology Epilepsy Measure Development P. Quality improvement in neurology: AAN epilepsy quality measures. Neurology. 2011;76(1):94.

  17. England MJ, Liverman CT, Schultz AM, Strawbridge LM. Epilepsy across the spectrum: promoting health and understanding.: a summary of the Institute of Medicine report. Epilepsy Behav. 2012;25(2):266–76.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Singh G, Singh MB, Ding D, Maulik P, Sander JW. Implementing WHO’s Intersectoral Global Action Plan for Epilepsy and other neurological disorders in Southeast Asia: a proposal. Lancet Reg Health Southeast Asia. 2023;10:100135.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Singh G, Sander JW. The global burden of epilepsy report: implications for low- and middle-income countries. Epilepsy Behav. 2020;105:106949.

    Article  PubMed  Google Scholar 

  20. Frølich A. Identifying organisational principles and management practices important to the quality of health care services for chronic conditions. Dan Med J. 2012;59(2):B4387.

    PubMed  Google Scholar 

  21. Singh SP, Sankaraneni R, Antony AR. Evidence-based guidelines for the management of epilepsy. Neurol India. 2017;65(Supplement):S6–11.

    Article  PubMed  Google Scholar 

  22. (ENA) ENA. House Orders Holding of Referendum for Establishment of New Region in SNNP. 2022.

  23. Kassie GM, Kebede TM, Duguma BK. Knowledge, attitude, and practice of epileptic patients towards their illness and treatment in jimma university specialized hospital, southwest Ethiopia. N Am J Med Sci. 2014;6(8):383–90.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hasiso TY, Desse TA. Adherence to treatment and factors affecting adherence of epileptic patients at Yirgalem General Hospital, Southern Ethiopia: a prospective cross-sectional study. PLoS ONE. 2016;11(9):e0163040.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ma X, Li Y, Li J, Zhou D, Yang R. Construction of nursing-sensitive quality indicators for epilepsy in China: a Delphi consensus study. Seizure - Eur J Epilepsy. 2023;107:71–80.

    Article  Google Scholar 

  26. Russo TT, Sorato MM, Mesfin AA, Hailu T, Tanga AT, Bussa Z, Endocrinology. Diabetes Metab. 2022;5(5):e355.

    Google Scholar 

  27. Pugh MJ, Berlowitz DR, Rao JK, Shapiro G, Avetisyan R, Hanchate A, et al. The quality of care for adults with epilepsy: an initial glimpse using the QUIET measure. BMC Health Serv Res. 2011;11(1):1.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Long L, Reeves AL, Moore JL, Roach J, Pickering CT. An assessment of epilepsy patients’ knowledge of their disorder. Epilepsia. 2000;41(6):727–31.

    Article  CAS  PubMed  Google Scholar 

  29. Culig J, Leppée M. From Morisky to Hill-bone; self-reports scales for measuring adherence to medication. Coll Antropol. 2014;38(1):55–62.

    PubMed  Google Scholar 

  30. Jackson MJ. Concise guidance: diagnosis and management of the epilepsies in adults. Clin Med (Lond). 2014;14(4):422–7.

    Article  PubMed  Google Scholar 

  31. Bekele F, Gezimu W. Treatment outcome and associated factors among epileptic patients at ambulatory clinic of Mettu Karl Comprehensive Specialized Hospital: a cross-sectional study. SAGE Open Med. 2022;10:20503121221125149.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Wubetu AD, Admasu Basha E, Alemnew Engidaw N. Public knowledge and attitude towards Epilepsy and its Associated factors: community-based cross-sectional study, Ethiopia, 2019. J Environ Public Health. 2020;2020:6801979.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Krishnaiah B, Alwar SP, Ranganathan LN. Knowledge, attitude, and practice of people toward epilepsy in a south Indian village. J Neurosci Rural Pract. 2016;7(3):374–80.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Woldegeorgis BZ, Anjajo EA, Korga TI, Yigezu BL, Bogino EA, Tema HT, et al. Ethiopians’ knowledge of and attitudes toward epilepsy: a systematic review and meta-analysis. Front Neurol. 2023;14:1086622.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Bayane YB, Senbeta BS. Pattern of anti-epileptic medications nonadherence and associated factors at ambulatory clinic of Jimma Medical Center, Southwestern Ethiopia: a prospective observational study. SAGE Open Med. 2023;11:20503121231160817.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Elsayed MA, El-Sayed NM, Badi S, Ahmed MH. Factors affecting adherence to antiepileptic medications among Sudanese individuals with epilepsy: a cross-sectional survey. J Family Med Prim Care. 2019;8(7):2312–7.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Singh AP, Chaudhary V, Kumari S, Dhir D, Devi V, Pal B. Nonadherence to antiepileptic medication and associated factors among persons with epilepsy in India: a systematic review and meta-analysis. Epilepsy Res. 2024;202:107358.

    Article  CAS  PubMed  Google Scholar 

  38. Shumet S, Wondie M, Ayano G, Asfaw H, Kassew T, Mesafint G. Antiepileptic drug adherence and its Associated factors among Epilepsy patients on follow-ups at Amanuel Mental Specialized Hospital, Ethiopia. Ethiop J Health Sci. 2022;32(5):913–22.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Al-aqeel S, Gershuni O, Al-sabhan J, Hiligsmann M. Strategies for improving adherence to antiepileptic drug treatment in people with epilepsy. Cochrane Database Syst Reviews. 2020(10).

  40. Mwansa NJ, Daka V, Mulenga D, Mfune RL, Mukanga B, Nyirenda C et al. Correlates of Seizure Control among patients with Epilepsy at two Referral hospitals in Zambia. Int J Translational Med Res Public Health.4.

  41. Kwan P, Arzimanoglou A, Berg AT, Brodie MJ, Allen Hauser W, Mathern G, et al. Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on therapeutic strategies. Epilepsia. 2010;51(6):1069–77.

    Article  CAS  PubMed  Google Scholar 

  42. Yazie TS, Kefale B, Molla M. Treatment outcome of epileptic patients receiving antiepileptic drugs in Ethiopia: a systematic review and Meta-analysis. Behav Neurol. 2021;2021:5586041.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Zena D, Tadesse A, Bekele N, Yaregal S, Sualih N, Worku E. Seizure control and its associated factors among epileptic patients at Neurology Clinic, University of Gondar hospital, Northwest Ethiopia. SAGE Open Med. 2022;10:20503121221100612.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Babu Y, Sheleme T, Sefera B, Bekele F, Olika W. Magnitude of uncontrolled seizures and associated factors among people with epilepsy. Data from a major teaching hospital in Southwest Ethiopia. Epilepsy Behav. 2023;140:109089.

    Article  PubMed  Google Scholar 

  45. Adal HD, Alemu K, Muche EA. Seizure control status and associated factors among pediatric epileptic patients at a neurologic outpatient clinic in Ethiopia. PLoS ONE. 2021;16(11):e0259079.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. de la Morena Vicente MA, Ballesteros Plaza L, Martín García H, Vidal Díaz B, Anaya Caravaca B. Pérez Martínez DA. Quality measures in neurology consult care for epileptic patients. Neurología (English Edition). 2014;29(5):267–70.

    Article  Google Scholar 

  47. Fitzsimons M, Dunleavy B, O’Byrne P, Dunne M, Grimson J, Kalra D, et al. Assessing the quality of epilepsy care with an electronic patient record. Seizure - Eur J Epilepsy. 2013;22(8):604–10.

    Article  Google Scholar 

  48. Ahmed I, Abera A, Demeke T, Terefe G, Shemsi S, Awol A. Self-care practice and associated factors among epileptic patients: a cross-sectional study, Ethiopia. Pan Afr Med J. 2023;44:36.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Ozuna J, Kelly P, Towne A, Hixson J. Self-management in Epilepsy Care: Untapped opportunities. Fed Pract. 2018;35(Suppl 3):S10–6.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

First, we would like to thank Arba Minch University, the College of Medicine and Health Sciences, and the School of Nursing for giving us this excellent opportunity. We would also like to thank the participants of this study; without their willingness, it would be impossible to conduct this research. Finally, we would like to thank all the staff of Komar University of Sciences and Technology, the College of Medicine, and the Department of Pharmacy for their technical and material support during manuscript development, including access to the internet.

Funding

None.

Author information

Authors and Affiliations

  1. Arba Minch General Hospital, Arba Minch, Ethiopia

    Melkenesh Nigatu

  2. College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia

    Gesila Endashaw & Tiwabwork Tekalign

  3. Department of Pharmacy, School of Medicine, Komar University of Science and Technology, Qularaisi, Sulaimaniyah, KRI, Iraq

    Mende Mensa Sorato & Trefa Mohammed

Authors
  1. Melkenesh Nigatu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Gesila Endashaw
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Mende Mensa Sorato
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Tiwabwork Tekalign
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Trefa Mohammed
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

All the authors read and approved the manuscript. MB conceived the research, framed the formatted the design, and conducted the data analysis; GE and TT participated in the data analysis, reviewed the manuscript writing process, and polished the manuscript. MS participated in the data analysis, reviewed the manuscript writing process, polished the manuscript, and developed the manuscript for publication.The guarantor of the study is MS. The authors accepts full responsibility for the finished work and/or the conduct of the study, has access to the data, and controls the decision to publish.

Corresponding author

Correspondence to Mende Mensa Sorato.

Ethics declarations

Ethical approval

Ethical clearance was obtained from Arba Minch University, the College of Medicine, and the Health Sciences Institutional Review Board with the following reference number: IRB/T13/2016. After the study objective and confidentiality of the information were clarified, verbal informed consent to participate was obtained from obtained from participants, or the parents or legal guardians of illiterate participants.

Consent for publication

All authors read the full version of this manuscript and agreed to publish.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nigatu, M., Endashaw, G., Sorato, M.M. et al. Quality of care and associated factors among patients with epilepsy at public hospitals in Arba Minch Town: a facility-based cross-sectional study. BMC Neurol 24, 485 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-024-03946-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12883-024-03946-z

Keywords

BMC Neurology

ISSN: 1471-2377

Contact us