A study of malaria care provider choice in Ghana

Dzator, Janet; Asafu‐Adjaye, John

doi:10.1016/j.healthpol.2004.01.005

Cited by 41 publications

(48 citation statements)

References 29 publications

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“…The choice of multinomial logistic regression stems from the multicategory (dissimilar) nature of the options available to the enrolee, and it is consistent with studies modelling choice behaviour. [16][17][18] Since an enrolee chooses a PPP irrespective of sickness, this study excludes disease specific features of the individual. Thus, we make use of individual characteristics such as gender, education, age, income, residence, and facility features such as drug availability, waiting time and other factors such as distance between the individual's residence and the facility and travel time.…”

Section: Setting and Populationmentioning

confidence: 99%

“…Indeed, some studies on patient hospital (provider) choice and/or utilisation of healthcare services have been conducted in developing countries [16][17][18][19][20] and developed countries. 1,6,8,9,[21][22][23][24] However, most of these studies, eg, Dzator and Asafu-Adjaye, 17 examined patient hospital choice under conditions where price (user fees) existed and/ or for a particular disease. Similar to Varkevisser et al, 9 the present study focuses on factors that affect the choice of PPP in the absence of user fees for insured persons.…”

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confidence: 99%

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Preferred Primary Healthcare Provider Choice Among Insured Persons in Ashanti Region, Ghana

Boachie

2015

Int J Health Policy Manag

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Background: In early 2012, National Health Insurance Scheme (NHIS) members in Ashanti Region were allowed to choose their own primary healthcare providers. This paper investigates the factors that enrolees in the Ashanti Region considered in choosing preferred primary healthcare providers (PPPs) and direction of association of such factors with the choice of PPP. Methods: Using a cross-sectional study design, the study sampled 600 NHIS enrolees in Kumasi Metro area and Kwabre East district. The sampling methods were a combination of simple random and systematic sampling techniques at different stages. Descriptive statistics were used to analyse demographic information and the criteria for selecting PPP. Multinomial logistic regression technique was used to ascertain the direction of association of the factors and the choice of PPP using mission PPPs as the base outcome. Results: Out of the 600 questionnaires administered, 496 were retained for further analysis. The results show that availability of essential drugs (53.63%) and doctors (39.92%), distance or proximity (49.60%), provider reputation (39.52%), waiting time (39.92), additional charges (37.10%), and recommendations (48.79%) were the main criteria adopted by enrolees in selecting PPPs. In the regression, income (-0.0027), availability of doctors (-1.82), additional charges (-2.14) and reputation (-2.09) were statistically significant at 1% in influencing the choice of government PPPs. On the part of private PPPs, availability of drugs (2.59), waiting time (1.45), residence (-2.62), gender (-2.89), and reputation (-2.69) were statistically significant at 1% level. Presence of additional charges (-1.29) was statistically significant at 5% level. Conclusion: Enrolees select their PPPs based on such factors as availability of doctors and essential drugs, reputation, waiting time, income, and their residence. Based on these findings, there is the need for healthcare providers to improve on their quality levels by ensuring constant availability of essential drugs, doctors, and shorter waiting time. However, individual enrolees may value each criterion differently. Thus, not all enrolees may be motivated by same concerns. This requires providers to be circumspect regarding the factors that may attract enrolees. The National Health Insurance Authority (NHIA) should also ensure timely release of funds to help providers procure the necessary medical supplies to ensure quality service.

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Section: Setting and Populationmentioning

confidence: 99%

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confidence: 99%

Preferred Primary Healthcare Provider Choice Among Insured Persons in Ashanti Region, Ghana

Boachie

2015

Int J Health Policy Manag

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“…KA treatment and diagnosis services are available at the (public) district hospitals. A recent national representative survey suggested that more than 50% of rural people had access to district hospitals within a one-hour travel time, whereas more than 80% of rural people have access to below the district level primary care within a one-hour travel time [7]. There is a referral system from bottom to top level health care.…”

Section: Resultsmentioning

confidence: 99%

Decision-making process of Kala Azar care: results from a qualitative study carried out in disease endemic areas of Nepal

2013

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BackgroundAnalysis of consumer decision making in the health sector is a complex process of comparing feasible alternatives and evaluating the levels of satisfaction associated with the relevant options. This paper makes an attempt to understand how and why consumers make specific decisions, what motivates them to adopt a specific health intervention, and what features they find attractive in each of the options.MethodThe study used a descriptive-explanatory design to analyze the factors determining the choices of healthcare providers. Information was collected through focus group discussions and in-depth interviews.ResultsThe results suggest that the decision making related to seeking healthcare for Kala Azar (KA) treatment is a complex, interactive process. Patients and family members follow a well-defined road map for decision making. The process of decision making starts from the recognition of healthcare needs and is then modified by a number of other factors, such as indigenous knowledge, healthcare alternatives, and available resources. Household and individual characteristics also play important roles in facilitating the process of decision making. The results from the group discussions and in-depth interviews are consistent with the idea that KA patients and family members follow the rational approach of weighing the costs against the benefits of using specific types of medical care.ConclusionThe process of decision making related to seeking healthcare follows a complex set of steps and many of the potential factors affect the decision making in a non-linear fashion. Our analysis suggests that it is possible to derive a generalized road map of the decision-making process starting from the recognition of healthcare needs, and then modifying it to show the influences of indigenous knowledge, healthcare alternatives, and available resources.

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“…These different categories have to be combined into an overall measure of the number of practitioners. Third, rural areas have greater difficulties of access to medical practitioners; this has been noted in Perry and Gesler (2000), Wagstaff (2002), Buor (2003), Leonard (2003) and also Dzator and Asafu-Adjaya (2004). Rural populations tend to be spread over a larger area and so have to travel longer distances to reach a medical practitioner and may also have to face longer 'waiting times'.…”

Section: Introductionmentioning

confidence: 99%

Measuring the shortage of medical practitioners in rural and urban areas in developing countries: a simple framework and simulation exercises with data from India

Katrak

2007

Health Planning & Management

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This paper suggests a simple framework to estimate the shortage of medical practitioners in rural and urban areas in developing countries. Shortages are defined with respect to four main considerations. The overall numbers and also the different categories of practitioners in the rural and urban areas, the relatively greater difficulties of access in the rural areas (which reduce the number of accessible practitioners) and the greater health hazards in those areas (which lead to greater need for medical treatment). The quantitative effect of these factors is examined by undertaking simulation exercises with data for the Ujjain district in Madhya Pradesh state, India and also data for that state. The simulations turned up the following results. The un-weighted total number of practitioners, per head of population, is relatively greater in the rural areas; this is because of the relatively large numbers of the unqualified doctors in those areas. On the other hand, a 'quality adjusted' total, with lower weights for the unqualified doctors, found little overall difference between the rural and urban areas. Third, allowance for rural-urban differences in the difficulties of access showed that the number of accessible practitioners is much lower in the rural areas. Fourth, rural-urban differences in the incidence of health hazards and estimates of the need for medical treatment also showed a marked shortage of practitioners in the rural areas. The main implication of the results is that developmental efforts in the rural areas, including improvements in transport facilities and reduction of health hazards, would help to greatly reduce the shortage of practitioners in those areas. Training programmes to improve the quality of practitioners in the rural areas are also required.

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A study of malaria care provider choice in Ghana

Cited by 41 publications

References 29 publications

Preferred Primary Healthcare Provider Choice Among Insured Persons in Ashanti Region, Ghana

Preferred Primary Healthcare Provider Choice Among Insured Persons in Ashanti Region, Ghana

Decision-making process of Kala Azar care: results from a qualitative study carried out in disease endemic areas of Nepal

Measuring the shortage of medical practitioners in rural and urban areas in developing countries: a simple framework and simulation exercises with data from India

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