Study design, Area and period
An institution based cross-sectional study was conducted from April 09 to 16, 2019 at Debre Markos Referral Hospital. The average number of patients treated in the hospital as an outpatient monthly was 5,658 from the three wards internal medicine (2100), surgery (1800) and Gynecology / Obstetrics (1758) respectively[10].
Population and eligibility criteria
The source population was all adult patients (>18years) visiting laboratories in internal medicine, surgery, Gynecology /Obstetrics departments at Debre Markos Referral Hospital. The study population was all adult patients (>18years) visiting laboratories in internal medicine, surgery and Gynecology /Obstetrics departments at Debre Markos Referral Hospital during the data collection period. All adult patients at the internal medicine, surgery and Gynecology /Obstetrics outpatient departments who were requested for clinical chemistry, hematology, parasitological and urine analysis tests were included in the study. However, patients who had mental illness and hearing impairments were excluded from the study.
Sample Size Determination and Sampling procedure
The required sample size was calculated using a single population proportion formula;
Assumptions: n = required sample size, Z = critical value for normal distribution at 95% confidence level (1.96), d = 0.05 (5% margin of error), P=63.3% (proportion of patients satisfied with laboratory service) [11] and an estimated non-response rate of 10%. The final calculated sample size for this study was 391. Systematic random sampling technique was used to select study participants. Proportional allocation to population size (170 from Internal medicine, 112 from Surgery, and 109 from Gynecology / Obstetrics outpatient departments) was employed.
Data collection procedure
Data were collected using a pretested and structured interviewer administered questionnaire. The questionnaire was prepared in English and translated to Amharic, then back to English to check for its consistency. The questionnaire contains satisfaction indicators which are related to socio-demographic characteristics of the patients and different dimensions of laboratory services such as waiting time (turnaround time), availability of requested laboratory tests, convenience of service hours, and type of laboratory visit, privacy, respect, courtesy and confidentiality. The study participants were asked to rate each aspects of the laboratory service on five point liker scale (1=Very Dissatisfied, 2=Dissatisfied, 3=Neutral, 4=Satisfied, 5=Very satisfied).
To assure the data quality, two diploma laboratory technicians and one BSc laboratory professional were recruited as data collectors and supervisor, respectively. In addition, training regarding the study objectives and data collection process was given for data collectors and supervisor for two days. Moreover, the questionnaire was pretested among 5% of the sample size at Finoteselam hospital. Furthermore, intensive supervision was done by supervisor and principal investigators throughout the data collection period.
Study variables
The dependent variable of this study was patient satisfaction. Patient satisfaction with laboratory services is defined as the patient’s opinion of the care received from the institution and is acknowledged as an outcome indicator of the quality of health care. i.e. ≥ mean value=Satisfied and < mean value=Dissatisfied[7].
The independent variables were: Socio demographic characteristics (age, gender, level of education, marital status, occupation, income and residence),waiting time to get service, availability of requested lab tests, convenience of service hours, confidentiality of lab results, improvement of service from time to time, queue process to get service, availability of service providers at their job, missing results, cost of laboratory service, location of laboratory, hospitality of laboratory professionals to patient, cleanness of latrine, needle stick attempted, and availability of equipment.
Data processing and Analysis
Data were cleaned, coded and entered using Epi data software Version 4.2 and analyzed using SPSS Version 23. Binary logistic regression was employed. In the bivariable analysis, variables with p-value < 0.25 were fitted into the multivariable model. Finally, adjusted odds ratios with their 95% confidence intervals were estimated to assess the strength of association, and variables with p-value <0.05 were considered statistically significant factors.