1236_asli

Received 2018-05-29

Revised 2018-06-16

Accepted 2018-07-22

Effective Factors of Utilization of Inpatient,

Outpatient, Diagnostic, and Pharmaceutical

Health Services: A Systematic Review

Solmaz Azimzadeh1, Jafar Sadegh Tabrizi2, Shirin Nosratnejad3, Mostafa Farahbakhsh2, Saber Azami Aghdash4, Hossein Mashhadi Abdolahi2

1 Iranian Center of Excellence in Health Management and Department of Health Service Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran

2 Tabriz Health Services Management Research Center, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran

3 Department of Health Services Management, Faculty of Management and Medical Informatic, Tabriz University of Medical Sciences, Tabriz, Iran

4 Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran

Abstract

Utilization is one of the dimensions of equity in health systems. Identifying the factors affecting utilization of health services can be helpful for interventional purposes. This study systematically reviewed the factors affecting the utilization of inpatient, outpatient, diagnostic, and pharmaceutical services. This systematic review was conducted between 2016 and 2017. The search was performed using keywords based on MeSH in valid databases such as Scopus, Embase, ProQuest, ScienceDirect, PubMed, and Web of Science in the fields of title, abstract, and keyword. Related papers published from 2000 to 2017 were searched. First, the retrieved studies were screened and checked for quality; then, the useful data were extracted and analyzed. Out of the 1178 retrieved publications, 20 studies were included in the final analysis. The identified factors were categorized into 5 areas, including demographic (4 items), socioeconomic (13 items), health services–related (13 items), health status–related (7 items), and health insurance–related factors (2 items), and reported. The findings of this study can be a useful source and a comprehensive body of evidence on the utilization of health services. The results can be used by the policy makers and managers in designing interventions for changing the utilization patterns of health services. [GMJ.2019;8:e1236] DOI:10.22086/gmj.v8i0.1236

Keywords:  Utilization; Health Services; Inpatient; Outpatient; Diagnostics; Pharmaceuticals

Introduction

Health is a matter of importance in today’s modern societies in such a way that we might conclude that improvements of health indicators lead to human and social development and then elevate the development status of the country [1]. Management of the health system requires evidence-informed decisions and some deep knowledge on the utilization of health services [2]. Today, health-related views have expanded and nonmedical determinants of health have gained special attention. These determinants,

Correspondence to:

Hossein Mashhadi Abdolahi, Building No. 3 Tabriz University of Medical Sciences, Tabriz Health

Services Management Research Center

Telephone Number: +989144000823

Email Address: hm_abdolahi@yahoo.com

GMJ.2019;8:e1236

www.gmj.ir

individually or by affecting others, seriously influence the health of people. Although health care results in the prevention of diseases, improvement of health, and treatment of illnesses, the socioeconomic status and the social determinants of health are highly influencing the health, illness, and need for medical care [3]. Reducing the inequalities in gender, races, and age groups is one of the main goals of the health policy makers [4]. Moreover, one dimension of equity is the utilization of health services [5]. The equitable access of all members of the society to health services leads to the improvement of health status in the whole population, and it prepares the requirements of growth and development [6]. As the effective factors on the utilization of health services are among the key determinants of community health, many researchers and health policy makers are interested in them [7]. Evidence shows that socioeconomic differences, by influencing the utilization rate of health services, lead to inequality in access to health care and thus an increase in the burden of diseases. Access is the first step for health services utilization and plays a main role in it [8]. Studies have shown that the utilization of health services is affected by many factors such as demographic factors, socioeconomic and cultural factors, health needs of the individuals, and access to the health facilities. On the other hand, poor socioeconomic conditions and lifestyle factors increase the burden of diseases, and resultantly, the need for health services [9-11]. Various models have been developed for understanding the pattern of health services utilization up to now. The model proposed by Andersen (2005) describes the health care utilization as a model of behavior. It considers the utilization of health services as a dependent factor of ability to use, barriers to use, and the need for the services. Furthermore, some people tend to use more health services than others, which can be predicted by some characteristics. Individuals with such characteristics of demographic factors, social factors, incentives, and beliefs are more likely to use the health services. In addition to the predictive factors of utilization, some other factors such as income, health insurance, availability, and access are necessary, without which the utilization would not occur [12]. The research on utilization of health services enables us to identify its facilitators and barriers and also to investigate the appropriateness of the volume and quality of the services [13]. The health services include a wide range of services, each of which is influenced by a number of other factors. Therefore, this study was conducted with the aim of identifying the effective factors on the utilization of inpatient, outpatient, diagnostic, and pharmaceutical health services.

Materials and Methods

This systematic review was conducted between 2016 and 2017, and it was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

Data Sources

The existing scientific papers in English and Persian published between January 2000 and September 2017 were retrieved through searching English databases such as Scopus, Embase, ProQuest, ScienceDirect, PubMed, and Web of Science and also Persian databases such as SID and Magiran. Furthermore, the Google Scholar search engine was used for additional search of the related literature. The search keywords were “healthcare utilization,” “healthcare utilization,” “health service utilization” and “factors affect*,” “factors influenc*,” “affect* factors,” “influenc* factors,” “clinic/outpatient,” “hospitalization/inpatient,” “drug/medicine,” and “paraclinic/diagnos*.” The references of the related papers were also checked by hand for additional studies.

Inclusion and Exclusion Criteria

There were 2 main inclusion criteria: (1) papers published between January 2000 and September 2017 and (2) papers investigating the effective factors of the utilization of inpatient, outpatient, diagnostics, and pharmaceutical health services. Meanwhile, there were 4 major exclusion criteria: (1) studies conducted before January 2000, (2) studies without a published full text, (3) studies published in languages other than Persian and English, and (4) papers studying specific populations such as immigrants or a specific disease such as AIDS or any other specific diseases.

Screening

The retrieved corpus was pooled in EndNote X7 software produced by Thomson Reuters Company, and the duplicates were identified and removed. Then, the irrelevant papers were identified and excluded first by title screening and then by abstract screening. Finally, the full texts of the remaining papers were reviewed for eligibility according to the inclusion and exclusion criteria.

Quality Appraisal

To assess the quality of the included papers, the Strengthening the Reporting of Observational Studies in Epidemiology checklist was used [14]. This checklist includes 22 items. The assessment was performed by 2 independent researchers. Each item had 1 score, and if the item had not passed, it got 0 score. In case of disagreement between the assessors about the score of the paper on a specific item, the case was discussed and resolved. Finally, those papers that gained 50% and more of the total possible score were included in the final analysis.

Data Extraction

The required data were determined based on the study purpose and then extracted by one researcher and rechecked by another. The collected data were entered into an MS Excel spreadsheet in a table. The extraction table included information such as names of the authors, publication year, country, study type, sample size, data collection method, related findings, and the result of the quality assessment of the paper. To develop the table, the data related to 5 studies were extracted as pilot, and then the table was reviewed and revised.

Data Analysis

Content analysis, which is a widely used qualitative research technique, was used in this study to analyze the extracted data. First, the influencing factors were identified from the content of the included papers. Then, the findings were coded and categorized as similar and related factors to be in the same category. The categories were named to describe the contents. Finally, the frequency of the codes was counted, and the results were presented in tables.

Results

Out of the total 1178 retrieved papers, 350 were duplicates that were excluded from the study. The remaining 828 records were first screened by title and then by abstract. Finally, after finishing the screening phase, 20 studies were included in the analysis. Figure-1 shows the search and selection process of the studies. The data were extracted from the final 20 included studies, and the affecting factors on the utilization of services were identified. The factors were divided into 2 groups of positive effect and negative effect. Table-1 shows the characteristics of the included studies and the main findings of each study as the factors affecting the utilization of health services. Out of the total 20 included studies, 12 were conducted in Asia and 8 were cross-sectional. The data used in 6 studies were secondary data. The health services were arranged in 4 groups of inpatient services, outpatient services, diagnostic procedures, and pharmaceutical services. Four studies had investigated the pharmaceutical services, 6 studies the diagnostic services, 8 studies the inpatient services, and 10 studies the outpatient services. A total of 45 factors were identified as having a positive effect on the utilization of health services and 8 factors as having a negative effect. The identified factors were classified into the following 5 categories:

  1. Demographic factors (n=4), which included age, sex, marital status, and family size.
  2. Socioeconomic factors (n=12), which included education, income level, employment, race, household expenditures, urban area, living place, using social media, health literacy, regular study, rented house, and the characteristics of family members.
  3. Health service–related factors (n=13), which included physician visit, use of preventive care, medical technology growth, medical regulations,
  4. hospitalization, length of hospital stay, grade of hospital, use of traditional medicine, physician’s qualifications, provider experience, access to health facilities, distance to health facilities, and regular care.
  5. Factors related to the health status of individuals (n=8), which included chronic diseases, poor health condition, stressful life event, smoking, alcohol consumption, regular physical activity, days with disability, and inactivity.
  6. Health insurance–related factors (n=2), which included insurance status and the insurance type.

Table-2 shows the summary of the identified effective factors on the utilization of health services.

Discussion

This study reviewed the effective factors on the utilization of health services worldwide in the following 4 categories: pharmaceutical services, diagnostic procedures, inpatient services, and outpatient services. The identified factors were organized into 5 groups: demographic factors (4 factors), socioeconomic factors (13 factors), factors related to health services (13 factors), factors related to health status of the individuals (7 factors), and factors related to health insurance (2 factors). The determinants of health services utilization were vast and included a variety of factors that were related to the people and health care providers. The factors had been studied differently in various studies. Some studies had categorized the factors by the type of services, whereas other studies had categorized them by the type of clients. In this study, we tried to summarize the determinant factors of health services utilization in a simple and understandable way. Numerous studies have assessed the utilization of health services in different countries and in various populations to depict the demand for the services. Thus, the health system would be able to provide the services in a responsible manner to meet the health needs of the population. Findings of the studies on individual, social, and economic determinants of health services utilization

Figure 1. Search and selection process of the studies

Table 1. Characteristics of the Included Studies and Their Main Findings as the Affecting Factors On the Utilization of Health Services

Author/year

Country

Scope

Study Population and Sample Size

Study Design

Data Collection Method

Factors

Quality Score (out of 22)

Positive Effect

Negative Effect

Cifaldi (2001)

Canada

Pharmaceuticals

9 articles

Review

Paper review

Medical care utilization, health status, insurance coverage, income

-

16

Pappa et al. (2011)

Greece

Pharmaceuticals

968 patients

Cross-sectional

Interview

Increased age, education, visits to physician (4 times or more), poor physical and mental health, having at least one chronic disease, gender, married, living in urban area, employment status

-

18

Sistrom et al. (2012)

Massachusetts (USA)

Diagnostics

85277 patients,

148 physicians

Retrospective cohort study

Secondary data

Patient factors: race, health problem, visits to the linked PCP (preventive care physician), visits to specialists

physician factors: years of experience, physician degree, clinic size

Provider experience, gender (male)

19

Quaas et al. (2014)

New York (USA)

Diagnostics

584 patients

Prospective observational study

Interview

Medicolegal liability

Physician reassurance, Patient reassurance,

Cost

18

Lee et al. (2013)

Taiwan

Diagnostics

142123 patients

Survey

Secondary data

Physician visited, major illnesses, chronic disease, occupational diseases/injuries

-

15

Lee et al. (2011)

Taiwan

Diagnostics

241843

patients

Survey

Secondary data

Specialists visit, severe diseases, disabled subjects, chronic illnesses, length of stay

Income,

urbanized

17

Siti Fatimah et al. (2015)

MALAYSIA

Diagnostics

234

patients

Cross-sectional

Questionnaire

Health knowledge, personal interest, marital status, general health problems

-

17

Tian et al. (2010)

Taiwan

Inpatient

1478

patients

Survey

Interview

Gender (males), health condition, specific chronic illnesses

Utilization of preventive care, economic hardship

20

Abenhai et al. (2008)

USA

Inpatient

45 630

patients

Retrospective cohort study

Secondary data

Median household income, insurance status (private insurance), race (Caucasians)

-

19

Ohta and

Kronenfeld (2011)

USA

Inpatient

3409

patients

Survey

Secondary data

Age, race/ethnicity (Hispanic), insurance type, hospital-level variables

-

18

Mendoza-Sassi et a.l (2003)

Brazil

Outpatient

1260

patients

Cross-sectional study

Interview

Age groups (25-44 years and 65 years or over), marital status, stressful life events, regular source of care, health insurance, inactivity, potential serious symptom, chronic health problem, income

Education, gender (male)

19

Dunlop et al. (2000)

Canada

Outpatient

17, 626

patients

Survey

Interview

Number of health problems, perceived health status (poorer health status), regular care, marital status, income, education, physical inactivity, smoking, alcohol drinking

Gender (male)

19

Miltiades and Wu (2008)

China

Boston (USA)

Outpatient

420 patients

177 family

Survey

Questionnaire

Chronic conditions, married, use of traditional Chinese medicine, poorer health status

chronic conditions, health status, age, and social network, insurance status

-

18

Nain et al. (2013)

Malaysia

Outpatient

183 patients

Cross-sectional study

Interview

Higher education level, good quality of services, short distances between their residences and the health clinics

-

17

Gholami et al. (2015)

Iran

Outpatient

400 households

Cross-sectional

Interview

Gender of the head of household (male), marital status of the head of household, household size, education level of the head of household, job of the head of household, economic status of the household, regular study

Regular exercise

13

Wong et al. (2012)

Netherlands

Pharmaceuticals

10000 patients

Cross-sectional

Secondary data

Age +65

20

Inpatient

Age (0-4 (newborn) and ages 80-84 in both and 30-34 years in women), growth in medical technology

Outpatient

Age +65

-

Gong et al. (2016)

China

Inpatient

18246

patients

Longitudinal Study

Interview

Age +65, marital status, ethnicity, residents in urban areas, people with healthy lifestyles (such as not smoking or drinking, and having regular physical exercises), higher household expenditure, health insurance type, poor health conditions, physical disability, ADL (activities of daily living) limitations commercial insurance, education, gender (male)

20

Outpatient

Age, marital statuses, ethnicity, people with healthy lifestyles (such as not smoking or drinking, with regular physical exercises), higher household expenditure, insurance type, poorer health status (physical & mental)

Ebadifard Azar et al. (2011)

Iran

Pharmaceuticals

390 individuals, 130 households

Cross-sectional

Interview

Age of father, job of father, age of mother, education of father, education of mother, income, living area, number of children, health insurance type

-

-

Diagnostics

Age of father, job of father, age of mother, job of mother, education of father, education of mother, household income, living area, number of children, health insurance type

-

Inpatient

Age of father, job of father, job of mother, education of father, education of mother, household income, living area, number of children, health insurance type

-

Outpatient

Age of father, job of father, age of mother, job of mother, education of father, education of mother, household income, living area, number of children, health insurance type

-

Nooraiee Motlagh et al. (2014)

Iran

Inpatient

33000 households

Retrospective

Questionnaire

Households that have a member with chronic disease or elderly over 65 years or children under 5 years, households of higher income

Female head of the household, higher education of head of the household, rented house

15

Outpatient

Households that have a member with chronic disease or elderly over 65 years or children under 5 years, households of higher income, female head of household, bigger family size, insurance coverage

-

Borhani nejad et al. (2015)

Iran

Inpatient

600 individuals

Cross-sectional

Questionnaire

Age (age group 74 to 90 years), health insurance coverage, poor self-estimation of health condition

Gender (male)

15

Outpatient

Age (age group 60 to 74), education (illiterates), married, health insurance coverage, poor self-estimation of health condition

-

Table 2. Factors Affecting the Utilization of Health Services

Health Services

Categories

Demographic Factors

Socioeconomic Factors

Factors Related to Health Status

Health Services-Related Factors

Health Insurance-Related factors

Pharmaceuticals

Age, sex, marital status, household size

Education, income, employment, urban area, characteristics of household members

Poor health condition, chronic diseases

Physician visit, hospitalization

Having health insurance coverage, having private health insurance

Diagnostics

Age, sex, marital status

Education, income, employment, race, household expenditure, urban area, health literacy, characteristics of household members

Health status of the individual, having chronic disease

Physician visit, hospitalization, hospital length of stay, academic degree of physician, experience of the provider, access to providers, regulations

-

Inpatient

Age, sex, marital status

Education, income, employment, race, household expenditure, urban area, rented house, characteristics of household members

Health status of the individual, chronic disease, smoking, alcohol, regular physical activity

Using preventive care, medical technology growth, hospital grade

Insurance coverage, private insurance

Outpatient

Age, sex, marital status, household size

Education, income, employment, household expenditure, urban area, rented house, characteristics of household members

Health status of the individual, chronic disease, smoking, alcohol, regular physical activity, stressful life events

Use of traditional medicine, regular care, distance to clinic

Insurance coverage, private insurance

indicate the needs of the societies for the health services. These findings can be used by the health system policy makers at the regional and national levels. For instance, studies that performed in China and Britain by the survey data found that similar socioeconomic groups have a similar utilization rate of the health services. Hence, based on these findings, they were looking for approaches to decrease the inequalities between the socioeconomic groups [15]. The results of the study showed that the demographic and socioeconomic factors were investigated more than other factors and were reported by more studies to have an effect on utilization of health services, in a way such that the demographic factors had been investigated in 15 studies and the socioeconomic factors in 16 studies out of the 20 included studies. Yet, some factors that correlate with health service utilization in a particular population on a particular group of health services may show no correlation in another population or another group of services. Even the effect of the factor might differ in different situations, for example, a particular factor may have a positive effect on the utilization of some services and simultaneously a negative effect on other services or in other regions or populations. Examples of this statement are discussed below. To conclude, the determinant factors of health services utilization are, to some extent, region-specific, and it is difficult to generalize them to all populations. In spite of this, findings of this review provided a basic understanding of the effective factors on the utilization of health services around the world. They can also be used as a list of potential factors for future studies. Some studies have mentioned education as a positive influencing factor on the utilization of health services [3, 12, 16, 17]. This means that more the education level of the individual, more the use of health services. However, 2 studies reported that by increasing the education level, the utilization rate of health services decreases [11, 18]. This might be justified by the assumption that people with more education have a better health status and they need health services less than others. A similar conflict exists about sex. Pappa et al. (2011) reported that women use more pharmaceuticals than men [18]. Sistrom et al. (2012) reported that women use more diagnostic services than men [19]. Tian et al. (2010) and Borhaninejad et al. (2015) reported that men use more inpatient services than women [20], whereas the study by Gong et al. (2016) found women using more inpatient services than men [21]. Such differences might be justified by cultural, social, and genetic differences of the studied populations. Moreover, Mendoza-Sassi (2003) and Nain (2013) reported a relatively higher use of outpatient services by women [11, 17]. Yet, the studies by Dunlop (2000) and Miltiades (2008) found that men use more outpatient services [10, 22]. It seems that the higher rate of utilization of health services by women is due to their higher sensitivity and attention to the health issues and preventive measures. Although household income was reported in some studies to have a positive effect on the utilization of health services [3, 9, 11, 12, 15, 23, 24], it was reported to have a negative effect in one study [25]. The study by Lee et al. (2011) indicated that the low-income people used more health services when they were covered by a type of health insurance. Moreover, some studies reported that those households that had high expenditures also had a high rate of utilizing inpatient services [21, 26]. However, the study by Nooraiee Motlagh et al. (2014) showed that those families who had high expenditures, such as a rented house, had a low rate of utilizing inpatient services [27]. It seems that it depends on other factors such as out-of-pocket payment and the insurance coverage. The nature of the household expenditure as an indicator is that the high expenditure in some cases means a high income; but in other cases, it may mean the low ability of the families to spend on health services, especially when they are not covered by any type of health insurance or the out-of-pocket payment is high. There was also a conflict regarding the role of smoking and alcohol consumption. Although the study by Dunlop et al. found smoking and alcohol to have a positive effect on utilizing outpatient services [12], Gong et al. reported that less smoking and alcohol consumption results in a higher use of inpatient and outpatient services [21]. This might be due to an incorrect identification of smokers and alcoholics in the conducted studies or the assumption that those people who had risky behaviors in the past had started to care more about their health. As smoking and alcohol are risk factors for many noncommunicable diseases, it can be assumed that many consumers have cardiovascular diseases, blood pressure, or other related diseases that oblige them to use more health services. Another possible reason might be that the smokers and alcoholics, due to concerns about their health, use more physician visits, screening, and diagnostic services. Regarding the people with chronic diseases, there was a unanimous agreement between almost all studies that these people had reported to have a higher utilization of all categories of health services [12, 16, 18, 19, 20, 22, 25, 26, 28, 29]. This is probably due to their higher need for health services. As expected, the health insurance coverage and having private health insurance were reported to have a positive effect on the utilization of health services [15, 17, 21, 23, 24, 30]. As health insurance provides better financial access to health services, those covered by a type of health insurance tend to use health services more than uninsured ones. The main limitation of this study was that it merely included the studies published in Persian and English. There might be some studies in other languages that would add to the findings of the study. However, the authors of this study used English as it is the formal language of most international scientific journals and Persian as it is the formal language of Iran.

Conclusion

This study systematically reviewed the literature on utilization of pharmaceutical, diagnostic, inpatient, and outpatient health services. The identified factors that affect the utilization of health services were categorized as demographic, socioeconomic, health services–related, health status–related, and health insurance–related factors. Identifying the effective factors of utilizing health services can, first, depict the health needs of the population, and then, help the policy makers decide the best options to satisfy the needs. Such results can also help the policy makers in rational and evidence-informed decision making on planning the health services provision.

Conflict of Interest

None declared.

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