Hospital Services for Ill Patients in the Middle-Belt Geopolitical Zone,Nigeria: Patient’s Waiting Time and Level of Satisfaction

Abstract

An important parameter in the assessment of quality health care lies on patient satisfaction. Despite concerted efforts to improve health-care services, patient satisfaction coupled with the quality of hospital care at disposal remain a significant challenge in Nigeria. The purpose of the study was to determine the perception on factors associated with prolonged waiting time and patient satisfaction at the outpatient department of Ibrahim Badamasi Babangida Specialist Hospital in Nigeria. A mixed-method research was utilized. Questionnaire was administered on 95 outpatients, and a focus group discussion (FGD) was held with eight participants. Statistical analysis was utilized to determine the association between dependent and independent variables. Data from FGD were analyzed with NVivo 10. The overall hospital satisfaction was found to be 75.8% among the study population. There was a significant inverse relationship between the level of satisfaction with the doctor and employment status and educational level and a significant direct relationship between the level of satisfaction with the doctor and appointment status and type of visits. The results of FGD show that patients were satisfied with the neatness of the hospital, doctor’s professionalism, and patient–doctor relationship. Dissatisfaction was with extended patient waiting time and the small size infrastructure of the hospital, inefficient handling of patient files by nurse aids, and thoroughness of the physicians. The results showed that majority of the patients were dissatisfied with the waiting time for consultation in the hospital. In other words, consultation time positively correlated with the level of patient satisfaction. To improve the overall patient satisfaction, the waiting time for consultation should be reduced significantly.

Keywords

illness patients satisfaction waiting time

Introduction

Prolonged waiting time by the patient resulting to overcrowding of the hospitals and vice versa is a well-known recurring phenomenon that impedes patient satisfaction (Carrus, Corbett, & Khandelwal, 2010; Derlet & Richards, 2000; Sinclair, 2007; Tiwari, Goel, & Singh, 2014). This recurrence is still a huge problem in the third world nations where appointment system is not resourcefully implemented (Idowu, Adeosun, & Williams, 2014). Patient’s satisfaction is one indicator used to measure the quality of care and how long they have to wait for medical attention (Anderson, Camacho, & Balkrishnan, 2007; Billing, Newland, & Selva, 2007).

According to Lambe et al. (2003) and Rauf, Blitz, Geyser, and Rauf (2009), patient waiting time is the time the patient spent in the hospital before receiving medical care. Whereas patient waiting time among outpatient is referred to as the length of time the patient spent between entering and leaving the outpatient department (Dinesh, Singh, Nair, & Remya, 2013). Studies over the years had shown that prolonged patient waiting time in the outpatient department occurred from diverse scenarios. Liptak, Super, Baker, and Roghmann (1985) found that patient waiting time was prolonged as a result of the absence of medical personnel, unavailability of examination rooms, and contemporaneous registering of patients. This is in line with findings in Canada by Brian (2002) that ailing planned services, deficiency in health-care workers, inability of physicians to work as a team, and inadequate health facilities can significantly cause or lead to long waiting in public hospitals. Furthermore, Thatcher (2005) found that patient waiting time was caused by shortage of staff, inappropriate filing of cards, delays arising from doctor’s first consultation, and inconsistent break in times. Likewise, Datuk et al. (2011) observed that lengthy waiting time stems from employees attitude, work processes, an excessive work load, feeble management and supervision, and inadequate facilities among others. Hall (2013) in his study discovered that factors associated with prolonged waiting time are multifactorial which include inadequate bed capacity, severe nursing shortage, challenges in accessing the specialist on call, high acuity patient, and patient lacking insurance cover. Likewise, Ho (2014) observed that the interplay of appointment scheduling, registration processes, retrieval of medical records, patient load, overall patient and doctor’s punctuality, and synergy between service providers are responsible for prolonged patient waiting time.

However, Murray and Berwick (2003) disagreed with the widespread belief that delay is unavoidable and connected to limitation in resources, and they suggested that prolonged waiting time is a result of unplanned and irrational scheduling as well as poor resource apportionment. This was bolstered by Haraden and Resar (2004) who stated that prolonged waiting time cannot be resolved by adding resources but can be effectively reduced by addressing problems related to the patient flow. This is because patient flows (uninterrupted movement of the patient) represent a guide in the health-care system that monitors and evaluates the quality of services rendered to the patient (Conrad, 2013). Zhang et al. (2014) stated that patient flow represents both the progression of a patient’s health status and the transferring of the patient through multiple hospital units within a hospital or among other hospitals. In addition, Yeboah and Thomas (2014) pointed out that prolonged consultation can also be influenced by the patient diagnosis that can have a logjam effect on the patient waiting time. Furthermore, similar factors were associated with prolonged waiting time in Nigeria. For example, Oche and Adamu (2014) observed that long waiting time is mostly caused by large turnover of the patient to be handled by insufficient health workers. As stated in O’Neill, Edim, and Obarein (2014) studies, the main problem of prolonged waiting time among health-care seekers in public health-care facilities to include among others are poor human resources development, the absence of professional independence, poor control, and support.

Long waiting time is perceived by the patients in different ways, and it generates different reactions and consequences. Johnson, Myers, Wineholt, Pollack, and Kusmiesz (2009) stated that reduction in patient waiting time will inadvertently reduce patient leaving hospital without medical care. And protracted waiting time promotes decline and discontent with health care and reduces agreement with provider’s recommendation (Liptak et al., 1985). Prolonged waiting by the patient does not only affect the service satisfaction bond but also depend on the perceived waiting time, satisfaction with the waiting environment, and satisfaction with the information giving for the delay to be the determinant of waiting time satisfaction (Bielen & Demoulin, 2007). This was buttressed by Becker and Douglass (2008) who noted that the attractiveness of the physical environment of the health-care facilities can have an impact on the patient perception of waiting time. Furthermore, the patient medical condition can deteriorate following anxiety and stress from unexplained lengthy waiting (Hall, Belson, Murali, & Dessouky, 2006). According to Paul and Moser (2009), when it comes to psychosocial theory, stress is involved in its pathway to ill health. Again, in a model of stress management, waiting time is perceived to be longer than usual time as a consequence of either physical or emotional stress (Cox, 1993). This is closely related to findings of Naumann and Miles (2001) who stated that patients who occupied their time while waiting enjoy a higher level of satisfaction compared with those that are idle. One of the negative consequences of prolonged waiting is the hospital losing its teeming patients. The loss relating to waiting time is tagged by Barlow (2002) as lose–lose strategy because patients lose valuable time and hospital lose patient and reputation and staff experience tension and stress. Patient who experienced shorter waiting time are willing to recommend the hospital to others (Thompson, Yarnold, Williams, & Adams, 1996) and are also willing to return to the facility themselves (Taylor, Kennedy, Virtue, & Mcdonald, 2006). On numerous occasions, verbal aggression by patients toward hospital staff was due to prolonged waiting time (Bolton, 2002). In the extreme cases, O’Neill et al. (2014) stated that the system sometimes witnesses sudden collapse or death of health-care seekers while waiting.

Time spent waiting by the patient is seen as resource investment for the craving objective of been seen by the physician and hence may be moderated by the outcome (Anderson et al., 2007). They further stated that in a typical setting, some degree of counter control exists between the patient waiting time and the time spent with the physician. The more time an individual gets from a particular physician, the longer the other patients would have to wait to see that physician. Finally, while gearing effort toward reducing patient waiting time, Ajayi (2002) stated that for the benefit of the waiting patient, the period could be sufficiently used as a medium for health information dissemination and thus improve the quality of care provided in the clinics. According to Barua, Esmail, and Jackson (2014) and Meier-Kriesche et al. (2000), waiting for health-care services results in poorer medical outcomes.

It is recommended by the Institute of Medicine that 90% of the patients should be seen within 30 minutes of their scheduled appointment (O’Malley, Fletcher, Fletcher, & Earp, 1983). In Nigeria and indeed most developing countries, this is far from achievable. For example, the mean patient waiting time in an outpatient department from entry to exit point in two teaching hospitals in north-western Nigeria are about 120 minutes in Zaria (Ameh, Sabo, & Oyefabi, 2013), 168 minute in a teaching hospital in Sokoto (Oche & Adamu, 2014), and 73 minutes in a university college hospital in Ibadan Southwest, Nigeria (Bamgboye, Erinoso, & Ogunlesi, 1992). In a national study in Malaysia done in public hospitals by Datuk et al. (2011), patients were found to wait for an average of up to 2 hours in the outpatient department from registration to getting the prescription slip and spent an average of 15 minutes with the medical personnel. However, studies in more developed countries have shown the waiting time to be shorter; for instance, the medium waiting time in California is 38 minutes (Lambe et al., 2003) and 60 minutes in Atlanta (Dos Santos, Stewart, & Rosenberg, 1994).

Patient satisfaction over the years has been used as a tool for the quality assessment and improvement in the health-care services (Bowers, Swan, & Koehler, 1994; Cleary & McNeil, 1988; Fenton, Jerant, Bertakis, & Franks, 2012). Patient satisfaction is directly linked to the degree of completion of their expectation. Moreover, satisfaction consists of communally a cognitive evaluation and emotional reaction to the components of care delivery and services (Urden, 2002). Also, Shirley and Sanders (2013) pointed out that patient satisfaction arises as a result of flexible factors such as setting the appropriate expectation, minimization of waiting time, and provision of continuity of care and physician–patient communication. Michael, Schaffer, Egan, Little, and Pritchard (2013) stated that in an outpatient care, there is a strong and inverse relationship between patient satisfaction and waiting times. Therefore, patient waiting time is an essential component of patient satisfaction.

Patients usually visit the hospital when they have challenges or compromised health state. It is not uncommon that a patient who deserves immediate health care, so as to reduce the negative consequences found themselves waiting for hours before being seen by the doctor. To keep patient waiting longer than necessary is clearly undesirable based on humanitarian ground because excessive waiting means loss of working time that most country can hardly afford, as a result of shortage of manpower (Derlet & Richards, 2000, 2002; Lowry, 2009; Welch & Bailey, 1952). Prolonged waiting time does not only lead to poor medical outcomes and patient leaving without medical care but also result in patient dissatisfaction. Also, to improve patient satisfaction, there is need to identify patient waiting time and related factors responsible for its protraction. Besides, in many settings, patient satisfaction serves as a perceptible feature of practice that patient will use to evaluate health personnel without paying much attention to their knowledge and skills (Oche & Adamu, 2014).

The study was aimed to determine the perceptive factors associated with prolonged waiting time and patient satisfaction at the outpatient department of Ibrahim Badamasi Babangida (IBB) Specialist Hospital in Nigeria. The objectives are (a) to determine the relationship between sociodemographic variables (gender, age, marital status, educational level, employment status, appointment status, and type of visits), level of satisfaction in the card room, nursing unit, and consultation room; (b) to determine the relationship between sociodemographic variables and patient time (consultation time and patient waiting time); (c) to determine the relationship between patient time (consultation time and patient waiting time) and level of patient satisfaction; and (d) to understand the in-depth level of satisfaction with services of the patient at the outpatient department of IBB specialist hospital.

Methods

Research Design

This study is a cross-sectional descriptive study carried out at the outpatient department of IBB Specialist Hospital in Minna, capital city of Niger State in the north central geopolitical zone of Nigeria. Mixed-method convergent parallel design was adopted for the study as conferred in earlier studies (Creswell & Plano Clark, 2007; Creswell, Plano Clark, Gutmann, & Hanson, 2003; Johnson, Onwuegbuzie, & Turner, 2007).

The quantitative approach adopted validated self-administered questionnaires in English language which was administered at exit point to collect information on sociodemographic features of the patient, waiting time, and questions on the general satisfaction with health-care services. Satisfaction was assessed using 5-point Likert rating scale (very satisfied, somewhat satisfied, undecided, somewhat dissatisfied, and very dissatisfied). In this study, patient waiting time was conveyed as the time spent before registration, before vital signs are taken, and before consultation. Moreover, scheduling data collection was done only on outpatient clinic days, through the month of September 2015. Two medical personnel were trained to assist respondents who cannot read or write to complete the questionnaire. On the other hand, an open-ended questionnaire was used for the FGD to determine an in-depth knowledge of patient’s perceptions on causes of prolonged waiting time and general satisfaction of the health-care services at the outpatient department. This part of the study is a thematic approach.

All patients who were seeking medical attention at the general outpatient department of the hospital were included in the survey. Patients aged 15 years and older who consented to participate in the study were included for the survey (inclusion criteria); patient who often bypass the hospital protocol and the critically ill patients were excluded from the survey. The required sample size of 96 was calculated using Gregg (2008) formula for calculating the sample size in a population less than 10,000. Value of n was calculated using the formula n = Z₂pq/d₂. Snowball sampling technique was used for the qualitative study. The quantitative aspect of the study was analyzed with Statistical Package for Social Science (SPSS). This includes descriptive analysis and bivariate and multivariate logistic regressions to determine the association between the covariate and dependent variables. Association between variable was based on Spearman Rho correlation. Multiple regressions were used to test the strength of prediction of independent variables on outcome variables. Similarly, the open-ended questions used in the focus group discussion were analyzed with NVivo.

The scales used in this study have already been used in other studies, and pretests of the contextually adopted tools were carried out before the actual data collection. Multiple items were used to establish appropriate measurement properties of the selected constructs. Trustworthiness of a research is significant in evaluating its worth, and it was used to determine the quality assurance for the qualitative strand.

Institutional approval

Accurate information regarding the research was made available to the institution. A written research proposal along with completed ethical form was submitted to the institution. The dissertation was approved by the Natural Science Ethics Subcommittee of the Middlesex University.

Hospital approval

The researcher obtained approval from the hospital research, ethics, and publication committee before the commencement of the study.

Confidentiality

Assurance was given to the respondents that all their responses will be kept confidential.

Results

The sociodemographic characteristics of the respondents for this study include age, sex, educational level, employment, marital status, appointment status, and types of visit. More than half (53.7%) of the respondents were female (Table 1). The age range of the respondents was between 15 and 85 years, of which about 70% of them are young adults between the age of 15 and 45 years, and the remaining 30% were 45 years and older. The mean age and standard deviation were 38.98 and 15.65 years, respectively. A higher percentage of those who responded are educated, 56.8% were educated to tertiary level, and 31.6% were educated below tertiary level while 11.6% did not have any form of education. More than half (61%) of the respondents were either formally or informally employed; this was followed by 22.1% students and 16.8% who are not gainfully employed. About 80% are married and made up the majority of the respondents, 19% were not married, and only 1% of the respondent was found to be divorced.

Table 1.

Sociodemographic Characteristics of the Respondents (n = 95).

Characteristics of respondents	n	Percent
Gender
Male	44	46.3
Female	51	53.7
Age (years) *38.98 (15.65)
15–30	33	34.7
31–45	33	34.7
46–60	22	23.2
61–85	7	7.4
Educational level
None	11	11.6
Primary	7	7.4
Secondary	23	24.2
Tertiary	54	56.8
Employment status
No gainful employed	16	16.8
Student	21	22.1
Informal employment	17	17.9
Formal part time	4	4.2
Formal full time	37	38.9
Marital status
Single	18	19.4
Married	74	79.4
Divorce	1	1.2

However, in the qualitative phase, the lowest age of the participants is 36 years, and the highest is 65 years. Half of the participants were between 36 and 45 years. The remaining 37.5% and 12.5% of the participants were aged between 49–55 and 56–65 years, respectively. More than half of the participants (62.5%) were females and majority of the participants (75%) were both educated up to tertiary education level and were in formal employment. All the participants were married.

Table 2 shows that about two thirds of the respondents (75.8%) were follow-up patients, out of which overwhelming majority came to the facility on appointment while the remaining one third (24.2%) were using the facility for the first time only and 12.6% of the total respondents were there on appointment.

Table 2.

Facility Related Characteristics of the Patient (n = 95).

Appointment status	Type of visit		Total
Appointment status	New n (%)	Follow-up n (%)	Total
On appointment	12 (12.6)	62 (65.2)	74 (77.8)
Not on appointment	11 (11.6)	10 (10.5)	21 (22.1)
Total	23 (24.2)	72 (75.8)	95 (100)

In the qualitative phase, the thematic analysis was used to code the transcript into broad themes based on the research objectives and the interview questions. The themes was further reviewed and modified. Each broad theme was then analyzed, and some child nodes were identified.

Majority of the patients perceived prolonged waiting in the outpatient department most especially while waiting for consultation. And the perceived cause of the prolonged waiting was long queue and shortage of manpower, which is consistent with the findings of the quantitative survey. However, undue interference of the clinics, thoroughness of the doctors, misplacements of cards at the card room, and preferential treatment given to some patients (whereby the cards of those who came late were swapped with the cards of those who were early) by the nurses were also highlighted in the FGD as reasons for prolonged patient waiting time. This was similar to the findings in quantitative phase, where about 38% of respondents waited greater than 2 hours before consultation (Figure 1), and the average individual waiting time increases when you add this to the time spent waiting in the card room and nursing station. Although the mean waiting time was not calculated for this study, but quantitatively more than half of them believed they experienced often delays while waiting for consultation, reasons not farfetched from long queues (46%), late commencement of clinics (10.6%), poor communication (7.5%), and shortage of manpower (7.5%); see Figure 2.

Figure 1.

Number of persons waiting at the outpatient department by duration of waiting time (n = 95).

Figure 2.

Causes of prolonged waiting time at the outpatient department.

High satisfaction level was observed quantitatively (>90%) in all the sections of the outpatient department under study (card room, nursing station, and consultation room); see Table 3. Majority of the participants in the focus group discussion were satisfied with neatness of the hospital, exceptional professionalism by the doctor, good patient–providers interaction, and hierarchy system of operation. For example, a comment made by a 36-year-old patient of the hospital is as follows:

And then what I like about the hospital is the neatness, no oozing, there is cleanliness, very okay. The expertise the way I looked at it, I am not a doctor, the professional aspect, the doctor always listen carefully, advice well and I think administers well too.

Table 3.

Percentage of the Level of Satisfaction at the Outpatient Department.

	Strongly satisfied	Satisfied	Undecided	Dissatisfied	Strongly dissatisfied
At the card room	62.8	33.0	0	2.1	2.1
At the nursing unit	46.8	47.9	0	3.2	2.1
At the examination room	59.6	33.0	3.2	2.1	2.1
Time spent with the doctor	61.7	34.0	1.1	1.1	2.1
Time spent waiting for doctor	16.0	20.2	3.2	22.3	38.3
Overall satisfaction	20	55.8	3.2	14.7	6.3

Perhaps the aforementioned factors could be responsible for the high level of overall satisfaction of 75.8% obtained from the quantitative phase (see Table 3). However, quantitatively 23.2% of the respondents were dissatisfied with the hospital (Table 3). Factors such as prolonged patient waiting time, the small size of the hospital, poor attention to National Health Insurance Scheme (NHIS) patients, poor schedules of clinic days and the high cost of medical bills for NHIS patients, and lack of adequate education of patient medical condition by the providers were identified in the qualitative phase to be responsible for dissatisfaction.

From the quantitative phase (Table 4), no significant correlation was observed between age, gender, marital status, and level of satisfaction with service delivery at the outpatient department unit. This was in line with findings in the qualitative phase were mixed feelings toward satisfaction level were displayed without clear dichotomy preference for any age and gender. However, the results showed the presence of a significant weak negative correlation between the level of satisfaction with the doctor and employment status (r = −.204, p = .047) and educational level (r = −.259, p = .011) (see Table 4). The unemployed and the least educated were more satisfied with the services they received from the doctors. Although this was an interesting finding from the survey, comments from the focus group participants on satisfaction with the doctor were homogenous across the educational level and employment status. Similarly, there was a significant weak positive correlation between appointment status and level of satisfaction with the doctor (r = .218, p = .034) (Table 4). This denotes that patients on appointment are more satisfied with the doctor than those who came without an appointment.

Table 4.

Association Between Sociodemographic Characteristics and Satisfaction Level.

Variables	Card room (p)	Nursing unit (p)	Consultation room (p)	Overall clinic satisfaction (p)
Age	−.064 (.543)	−.079 (.448)	−.184 (.075)	.029 (.779)
Gender	.138 (.183)	−.047 (.649)	−.049 (.638)	−.061 (.554)
Employment status	−.98 (.346)	−.082 (.427)	−.204 (.047*)	.128 (.216)
Educational level	−.122 (.242)	.028 (.786)	−.259 (.011*)	.123 (.235)
Marital status	−.195 (.600)	.114 (.270)	−.141 (.174)	.083 (.423)
Type of visit	.094 (.366)	.113 (.275)	.326 (.001**)	.175 (.095)
Appointment status	.132 (.205)	−.183 (.076)	.218 (.034*)	−.156 (.132)

Note. *Significant at p < .05, **Significant at p < .01.

A significant positive weak correlation was also observed between type of visits and level of satisfaction with the doctor (r = .326, p = .001) Table 4. Follow-up patients are more satisfied with the services they get from the doctor than those using the facility for the first time. This observation was not completely in line with the findings from the qualitative phase. For example, see the comments from two participants. A male participant who had been using the facility for about 10 years commented: “Since I started coming to this hospital I have not seen changes in the outpatient rather the hospital is living on past glory.” Another comment coming from a female respondent using the facility for the first time: “They are trying, this is not my first hospital, and they are trying compare to other hospital.”

There was a significant negative moderate correlation between the type of visit and satisfaction with time spent in the examination room (consultation time) (r = −.437, p = <.001) see Table 5. Those using the facility for the first time were more satisfied with the consultation time than the follow-up cases. Although in the qualitative phase, satisfaction with the consultation was homogenous. Also from quantitative phase, findings from Table 6 shows a significant positive moderate correlation between satisfaction with the time spent with the doctor and the level of satisfaction with the doctor (r = .651, p = .00). Those who spent more time with the doctor were more generally satisfied with the doctor. A significant positive but weak correlation was observed between satisfaction with the services of the doctor and the overall hospital satisfaction (pleasant experienced) (r = .243, p = .018) see Table 6. Those who were more satisfied with the physician tend to have more overall hospital satisfaction. This can casually be related to the findings from qualitative phase, which revealed that despite dissatisfaction with the long waiting time, high cost of NHIS drugs, poor handling of NHIS patients, and unpleasant schedules of clinic days, overall clinic experience was pleasant by most participants, perhaps this could be as a result of high satisfaction with the doctor. A counter-measure was observed in both quantitative and qualitative phases. For example, despite having waited for long before the consultation, most of the patients were still satisfied with the services at the examination room because of satisfaction with the consultation time. It was revealed in the quantitative phase (see Table 3) that 95.7% of the respondents were satisfied with the consultation time, and nearly all the participants in the focus group were also satisfied with the time they get during the consultation. For example, here is one of the comments in FGD:

yesterday I had problem and coming to see doctor I was delayed, and I was not satisfied at that point but when I was able to see a doctor, and I think the doctor was able to attend to me thoroughly unlike other places when you visit a doctor, and the doctor will be in haste or some of them don’t have manners to accommodate patients. That doctor-patient relationship yesterday I think I was satisfied a bit because the man was able to attend to me, despite the fact that I delay a bit, and that was based on the fact that there were people there before me. So they have to attend to people before me and I consider it a normal thing.

Table 5.

Association Between Sociodemographic Variables and Satisfaction With Patient Waiting Time.

Variables	Satisfaction level with
Variables	Consultation time rho (p)	Time waiting for consultation rho (p)
Age	−.098 (.343)	−.014 (.894)
Gender	−.075 (.472)	−.010 (.023)
Employment status	−.111 (.282)	−.144 (.163)
Education level	.155 (.133)	−.137 (.185)
Marital status	−.185 (.072)	.015 (.887)
Type of visit	−.437 (.000**)	.106 (.307)
Appointment status	.193 (.061)	.086 (.409)

Note. **Significant at p < .01.

Table 6.

Association Between Patient Satisfaction and Patient Waiting Time.

Variable	Level of satisfaction with
Variable	Consultation time rho (p)	Time spent waiting to see doctor rho (p)	Overall hospital satisfaction rho (p)
Level of satisfaction with the doctor	.651 (.000**)	.048 (.643)	.243 (.018*)

Note. *Significant at p < .05, ** Significant at p < .01.

Lastly, in the quantitative phase, consultation time was found to be a strong predictor of the level of satisfaction with the physician. Moreover, the level of satisfaction with the doctor was also found to be a predictor of overall clinic satisfaction (Table 7). This could also be a reflection of the findings from the qualitative phase where emphasis was continuously made at different stages of the discussion by the participants on the high level of satisfaction with the doctors.

Table 7.

Multiple Regression Analysis for Patient Satisfaction With Doctor.

Selected variable	Unadjusted coefficient (b)	p	Adjusted coefficient (b)	p
Consultation time	.859	.001**	.846	.001**
Doctor’s waiting time	.084	.132	−.03	.928
Overall Clinic satisfaction	.154	.040*	.60	.212

Note. *Significant at p < .05, **Significant at p < .01.

Discussion

Prolonged waiting time was perceived as a source of dissatisfaction in most public health facilities. This was not an exception in this study, and the overall causes of prolonged waiting time are long queues, late commencement of clinics, poor communication, shortage of manpower, undue interference of the clinics, thoroughness of the doctors, misplacements of cards at the card room, and not handling cards on a first-come-first-served basis. Similar reasons were also observed to be the cause of prolonged waiting when you combine the findings of studies of Thatcher (2005) in Jos University Teaching Hospital and Megbelayin, Ibeinmo, Kurawa, and Babalola (2013) in Uyo all in Nigeria. The findings from this study were in line with this assertion that 63.8% of the patients were dissatisfied with the time they waited for consultation. This finding was much higher than the value obtained in a study in Aminu Kano Teaching Hospital by Iliyasu, Abubakar, Abubakar, Lawan, and Gajida (2010) where only 30% of the patients were dissatisfied with the waiting time. The low level of satisfaction with the waiting time may be attributed to the fact that, as the hospital transform from specialized hospital to specialist hospital and still evolving, there was a significant increase in the influx of patients seeking for various specialist care without corresponding increase in manpower or improvement in appointment system to match the new status of the hospital. This mismatch in doctor–patient ratio will continue to contribute to prolonged patient waiting time.

The overall level of satisfaction with the services at the outpatient department was 75.8%. This level of satisfaction is similar to that obtained in Ibadan, Nigeria (75%) by Olusina, Ohaeri, and Olatawura (2002), in Bida, Nigeria (78.5%) by Adekanye et al. (2013) but lower than the values obtained in Kano, Nigeria (83%) by Iliyasu et al. (2010) and Ethiopia (80.1) by Asefa, Kassa, and Dessalegn (2014). The dissimilarities in the study population and perhaps patient expectation and the difference in the way services are delivered could affect the satisfaction level. Neatness of the hospital, exceptional professionalism of the doctors, and good patients–providers interaction were some of the factors responsible for satisfaction. Similar reasons were also found to be determinants of patient satisfaction in a study by Net, Sermsri, and Chompikul (2007) in Thailand.

In this study, no significant correlation was observed between age, gender, marital status, and level of satisfaction with service delivery at the outpatient department unit. These outcomes are in agreement with the findings of a study in Ethiopia by Asefa et al. (2014). However, a significant negative correlation was observed between educational level, employment status, and level of satisfaction with the doctor. The findings of the association between sociodemographic characteristics of the patient and the level of satisfaction in this study were similar with those obtained in Iran by Kelarijani, Jamshidi, Heidarian, and Khorshidi (2014). In their study, no association was found between age, gender, and patient satisfaction, but a significant negative correlation was found between educational level, employment status, and patient satisfaction. They further reiterated that less satisfaction is observed with patients with higher level of education, mainly because they have higher education, higher income and social status, and perhaps their expectations are higher. Moreover, this is a reflection of the meaning of quality health services which is based on the growing public awareness.

High satisfaction level was recorded in this study ( > 90%) in all the sections of the outpatient department under study (card room, nursing station, and consultation room). These findings are similar to those obtained in a study in Cambodia by Vadhana (2012) where 81.5% to 96% of the respondents were satisfied with the services at the nursing units and consultation room. Although unlike the finding in the present study, the satisfaction level at card room in the study at Cambodia is low. This higher level of satisfaction in the card room in this study could be as a result of the differences in the operation settings in the centers and also because the card room recently benefitted from additional manpower as the hospital transformed from a specialized to a specialist hospital and also because the section periodically has students on posting who usually contribute to their workforce.

The findings from this study show a significant positive moderate correlation between satisfaction with the consultation time and the general satisfaction with the doctor. This was similar to findings of Anderson et al. (2007) who found that the time spent with the physician was a stronger predictor of the patient satisfaction than with the time spent in the waiting room. This could also be explained by findings in a study in London, the United Kingdom by Ogden et al. (2004). Results from their study show that irrespective of the real or perceived consultation span, greater desire for more time was associated with a lower satisfaction with the emotional content of the consultation and a lower intention to comply with the doctor’s recommendations. Similarly, a significant positive but weak correlation was observed between satisfaction with the services of the doctor and the overall hospital satisfaction. Moreover, consultation time was found to be a strong predictor of the level of satisfaction with the doctor, while the level of satisfaction with the doctor was also found to be a predictor of overall clinic satisfaction. This is in line with findings from a study in Makurdi, Nigeria by Onwujekwe, Etiaba, and Oche (2015). The study identified consultation time as an influencing factor on the level of patient satisfaction with health-care services. Moreover, time spent with the doctors during consultation was the most powerful determinant of the overall patient satisfaction.

Conclusion

The study demonstrated that patients are dissatisfied with prolonged waiting in the outpatient departments, especially when waiting for consultation. However, high satisfaction of more 90% was recorded with services in all the units under study, and this contributed to the overall level of satisfaction (75.8%). Also, overall clinic satisfaction was strongly predicted by level of satisfaction with the doctor which in turn depends on the consultation time. What this means for the hospital administrators is that, since level of satisfaction appears to increase with the time spent with a doctor, they may want to design appropriate strategies that will reduce waiting time significantly thereby maintaining or even increasing the consultation time.

The government and policy makers could also benefit from the study by hiring more hands so that patients could take more benefits from the health-care centers.

Limitations

The average mean waiting time was not calculated in this study because the individual average waiting time was not entered as a continuous variable.

Some level of bias may exist because the questionnaires were self-reported by the patient and this depend on their character, receptivity, and overall frame of mind.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Ahmed Abdulsalam is currently the deputy state immunisation officer at the primary healthcare development agency Minna, Niger state of Nigeria. He received MSc in applied public health at Middlesex University London, MSc in disaster risk management and development study at Federal University of technology Minna, Nigeria and bachelor of medicine and bachelor of surgery (MBBS) at Usman Danfodiyo University Sokoto, Nigeria. Previously Dr Ahmed has worked as a senior medical officer at Ibrahim Badamasi Babangida (IBB) specialist hospital Minna, Nigeria and medical officer at Federal Medical officer katsina Nigeria. His area of research interests lie in the areas of improvements of healthcare system and individual health.

Hafiz T. A. Khan is currently a reader in Statistics at Birmingham City University in the UK. He received PhD in applied statistics from Edinburgh Napier University in 1996. Previously Dr. Khan worked as a senior lecturer at Middlesex University in London (2009 -2016) and is also a research fellow at the Oxford Institute of Population Ageing, the University of Oxford, UK (2006 - 2008). Dr. Khan trained as a statistical demographer and has particular research interests in modelling ageing in Asia and its long-term care and support provisions. Most recently, he has conducted research on The Global Ageing Surveys (GLAS) at the University of Oxford and has published articles on various issues of global ageing and health. He has coauthored two books on Research Methods for Business and Social Science, 2007 & 2014, Sage.

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