Access to Health Care in Brazil. Spatialization of Medical Care in Belo Horizonte


Master's Thesis, 2018
115 Pages, Grade: 3.0

Free online reading

TABLE OF CONTENT

1 INTRODUCTION
1.1 Context
1.2 Previous Studies
1.3 Rationale
1.4 Omission to be Explored
1.5 Problem Research
1.6 Contribution Research
1.7 Analysis of Object - The metropolitan region of Belo Horizonte
1.8 General Objective
1.9 Specific objectives

2 THEORETICAL FOUNDATION
2.1 Context
2.2 Health Geography
2.3 Supplementary Healh
2.4 Spatial Statistics
2.5 Spatial Analysis
2.6 Geographic Distribution of Physicians
2.7 Reason Doctors / Inhabitants
2.8 Projection New Doctors
2.9 Guests of Physicians
2.10 Medical Dedication
2.11 Business Sector
2.12 Interdisciplinarity of Constructs

3 METHODOLOGY
3.1 Methodological Categorization
3.2 Literature Review
3.3 Methodological procedure
3.4 Data Extraction
3.5 Data Treatment Routines
3.6 Geocoding Service Points
3.7 Spatial Statistics Application
3.8 Generation of Maps
3.9 Generation of Analytical Reports

4 RESULTS
4.1 Medical DemoGraphs of MRBH
4.2 General Analysis (All Specialties)
4.3 Pediatric Analysis
4.4 Basic Specialties Analysis
4.5 Geographic Analysis
4.5.1 Location
4.5.2 Composition
4.5.3 Distribution

5 CONCLUSIONS

REFERENCES

Everything has its season, and a time to every purpose under heaven: there is time to be born and a time to die; time to plant and a time to pluck what is planted; a time to kill and a time to heal; time to tear down and a time to build; A time to weep and a time to laugh; a time to mourn and a time to jump, time to throw stones and a time to gather stones; time and hold time move away from embracing; time to seek and a time to lose; A time to keep and a time to cast away; time to tear and a time to sew; time to be silent and a time to speak; time to love and a time to hate; wartime and peacetime.

(Ecc 3: 1-8).

THANKS

First, I thank God who gave me life, direction, and strength. Without him, nothing would be done. My companion and Lord, my very present help in trouble. He gave me a wonderful family that I love deeply.

My father Miguel Carlos da Silva to has always charged my best and my mother Marlene Freire da Silva for having encouraged me since childhood.

Especially my wife Heloisa at your beautiful love without limits, for trusting me, believing that it would be possible, and for being the great woman she is. I love you!

When Peter, our son during this Masters was conceived, came into the world grew. Every day brings pride and joy to their parents for being the sweetest child of this universe. I love you!

The highly esteemed professor Leonidas Conception Barroso my advisor, I leave my supreme gratitude for being much more than I could expect from a true educator.

ABSTRACT

The present research AIMS to describe and present the medical demography in the metropolitan area of Belo Horizonte from the date of the general profile of physicians. Presenting the spatial distribution of professionals and their concentration in the private sector of supplementary health, through maps and cartograms. Spatial statistics and spatial analysis Were applied to elaborate the temporal cartograph diagnosis. Besides, the possible trends of the phenomenon are estimated. The mapping of the specific region was done using spatial data processing and observation techniques. The products generated Were temporally organized maps and attached to the analytical reports. They made explicit events. This work is expected to collaborate with the United Nations' (BU) Goal Sustainable Development (ODS) defined in its third objective. Which says: "Ensuring Promoting a healthy life and well-being for all, in all the ages." The study serves the informational support and support for the decision-making of supplementary health managers, the focus of the case study. For the academy, it Contributes to the production of a new bibliography on the proposed theme. This creation presents new questions about the subject. The spatial analysis allowed us to observe the patterns of the distribution of medical care as well as its dynamics over the years. For the academy, it Contributes to the production of a new bibliography on the proposed theme. This creation presents new questions about the subject. The spatial analysis allowed us to observe the patterns of the distribution of medical care as well as its dynamics over the years. For the academy, it Contributes to the production of a new bibliography on the proposed theme. This creation presents new questions about the subject. The spatial analysis allowed us to observe the patterns of the distribution of medical care as well as its dynamics over the years.

Keywords: Health Geography. Supplementary Health. Spatial statistics. Spatial Analysis. GeoGraph Distribution of Physicians. Metropolitan Region of Belo Horizonte.

LIST OF ABBREVIATIONS

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LIST OF TABLES

Table 1 - Population, area, and population density of the Municipalities MRBH.

Table 2- Comparison of the focuses of the previous studies and current research

Table 3 - Distribution of doctors working in the private sector, according to the workplace - Brazil, 2014

Table 4 - Result information processing calls with the geocoding

Table 5 - Analysis of selected within targeting medical specialties

Table 6 - Average Centers of Basic Specialties

Table 7 - Standard Distance and Centers of Basic Medium Specialties

Table 8 - Standard Distance from General Calls

Table 9 - Standard Distance from Pediatric Care

Table 10- Standard Distance from Basic Specialties

Table 11 - Weighted Standard Distance from General Calls

Table 12 - Weighted Standard Distance from Pediatric Care

Table 13 - Weighted Standard Distance from Attendances in Basic Specialties

GRAPHS LIST

Graph 1 - Percentage share of beneficiaries of supplementary health plans, between the municipalities of MRBH, 2017

Graph 2 - Evolution of the population of the metropolitan region of Belo Horizonte between 1940 and 2000

Graph 4 - Evolution of the number of doctors between 1910 and 2015 - Brazil, 2015, based on the registration of medical

Graph 5 - Doctors per 1,000 inhabitants, according to selected countries.

Graph 6- Evolution of the number of new doctors, according to new records and projection of new graduate vacancies - Brazil, 2015. Between 2000 and 2014 - new doctors registered in CRMs. Between 2015 and 2020 - Forecast of the number of vacancies (MEC) in new medical courses

Graph 7 - Distribution of doctors according exclusive or partial dedication to medicine - Brazil, 2014

Graph 8 - Distribution of doctors according to the number of work contracts - Brazil, 2014.

Graph 9 - Distribution of doctors, according to the weekly schedule - Brazil, 2014.

Graph 10 - Distribution of doctors, according to acting in the public and private sectors of health - Brazil, 2014

Graph 11 - Evolution of the total number of supplementary health physicians from 2007 to 2016 at MRBH

Graph 12 - Growth rate between subsequent years of the total number of supplementary health physicians between 2007 and 2016 at MRBH

Graph 13 - Evolution of the average age of supplementary health physicians between 2007 and 2016 at MRBH

Graph 14 - Percentage evolution of gender of doctors between 2007 and 2016 at MRBH

Graph 15 - Evolution of the gender of doctors between 2007 and 2016 (with trend line until 2043) in MRBH

Graph 16 - Evolution of the number of health care points in supplementary private health between 2007 and 2016 at MRBH..

Graph 17 - Comparative evolution of the number of healthcare points between the capital and the interior, from 2007 to 2016, at MRBH

Graph 18 - Evolution of the percentage difference between the number of health care points between the capital of the interior, from 2007 to 2016, in MRBH

Graph 19 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Capim Branco, Confins, Ibirité, Jaboticatubas, Juatuba, Raposos, Sao Joaquim de Bicas, Sao Jose da Lapa and Sarzedo

Graph 20 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Brumadinho, Caeté, Esmeraldas, Igarapé, and Matozinhos

Graph 21 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Lagoa Santa, Ribeirão das Neves, Sabará, Santa Luzia and Vespasiano

Graph 22 - Evolution in the number of health care points between 2007 and 2016 in the municipalities of Betim, Contagem, Nova Lima and Pedro Leopoldo

Graph 23 - Ratio of the number of points of service to the number of doctors between 2007 and 2016 at MRBH

Graph 24 - Total amount of health care between 2007 and 2016 at MRBH

Graph 25 - Average amount of health care services by location between 2007 and 2016 at MRBH

Graph 26 - Number of health care venues by location between 2007 and 2016 in medical specialties: Acupuncture, Allergy and Immunology, Cardiovascular Surgery, Hand Surgery and Head and Neck Surgery at MRBH

Graph 27 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Pediatric Surgery, Thoracic Surgery, Coloproctology, Endoscopy and Gastroenterology at MRBH

Graph 28 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Genetics, Geriatrics, Hematology, Homeopathy and Infectious Diseases at MRBH

Graph 29 - Number of health care locations by location between 2007 and 2016 in medical specialties: Occupational Medicine, Physical Medicine, Intensive Care Medicine, Nuclear Medicine and Clinical Neurophysiology at MRBH

Graph 30 - Number of health care locations per care location between 2007 and 2016 in medical specialties: Angiology, Neurology, Ophthalmology, Orthopedics and Otorhinolaryngology at MRBH

Graph 31 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Pathology, Clinical Pathology, Pulmonology, Psychiatry and Radiology at MRBH

Graph 32 - Number of health care venues by location between 2007 and 2016 in medical specialties: Anesthesiology, Cardiology, General Surgery, Medical Clinic and Dermatology at MRBH

Graph 33 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Endocrinology, Gynecology, Pediatrics and Urology at MRBH

Graph 34 - Number of health care venues by location between 2007 and 2016 in medical specialties: Plastic Surgery, Mastology, Nephrology, Neurosurgery and Rheumatology at MRBH

Graph 35 - Number of health care venues by location between 2007 and 2016 in medical specialties: Cancerology, Family Medicine, Nutrology and Radiotherapy at MRBH

Graph 36 - Evolution of the number of pediatric doctors between 2007 and 2016 at MRBH

Graph 37 - The growth rate of pediatric doctors between 2007 and 2016 at MRBH

Graph 38 - Evolution of the number of health care points for the pediatric specialty between 2007 and 2016 at MRBH

Graph 39 - Ratio of the number of points of service to the number of pediatric doctors between 2007 and 2016 at MRBH

Graph 40 - Comparative evolution of the number of pediatric healthcare points between the capital and the interior, from 2007 to 2016, at MRBH

Graph 41 - Relationship between the number of pediatric care points of Capital and Interior, from 2007 to 2016, at MRBH

Graph 42 - Total number of health appointments in the Pediatrics area between 2007 and 2016 at MRBH

Graph 43 - Average amount of health care provided by Pediatrics by place of care between 2007 and 2016 at MRBH

Graph 44 - Evolution of the number of doctors in basic specialties between 2007 and 2016 at MRBH

Graph 45 - Rate of growth of the number of doctors of basic specialties between 2007 and 2016 at MRBH

Graph 46 - Evolution of the number of health care points for basic specialties between 2007 and 2016 at MRBH

Graph 47 - Ratio of the number of points of service to the number of doctors of basic specialties, between 2007 and 2016 at MRBH

Graph 48 - Comparative evolution of the number of pediatric healthcare points between the capital and the interior, from 2007 to 2016 at MRBH

Graph 49 - Relationship between the number of service points in the basic specialties in Capital and Interior, from 2007 to 2016 at MRBH

Graph 50 - Total amount of health care in basic specialties between 2007 and 2016 at MRBH

Graph 51 - Average amount of health care in basic specialties by location between 2007 and 2016 at MRBH

LIST OF MAPS

Map 1 - CartoGraph location MRBH from the state of Minas Gerais and concerning Brazil

Map 2 - Municipalities in the Greater Belo Horizonte

Map 3 - metropolitan areas according to IBGE - 2009

Map 4 - Location of the Belo Horizonte Metropolitan Region, 2017

Map 5 - MRBH Municipalities, 2017

Map 6 - SociodemoGraph classifications (area and population)

Map 7 - SociodemoGraph classifications (Density and GDP)

Map 8 - SociodemoGraph classifications (Inhabitants x Point Service and% Population)

Map 9 - Population growth rate between 2010 and 2016

Map 10 - Distribution of General Service Points between 2007 and 2016

Map 11 - Distribution of Pediatric Service Points between 2007 and 2016

Map 12 - Distribution of Service Points of Basic Specialties between 2007 and 2016

Map 13 - Medium Centers between 2007 and 2016 (General, Basic Specialties, Non-Basic Specialties, and Pediatrics)

Map 14 - Overall Standard Distance between 2007 and 2016

Map 15 - Standard Distance in Pediatrics between 2007 and 2016

Map 16 - Standard Distance in Basic Specialties between 2007 and 2016

Map 17 - Overall Weighted Standard Distance between 2007 and 2016

Map 18 - Weighted Standard Distance in Pediatrics between 2007 and 2016

Map 19 - Standard Distance Weighted on Basic Specialties 2007-2016

Map 20 – 2007 and 2016 General Care Heat Map

Map 21 - Heat map of general care between 2007 and 2016

Map 22 - Heat Map of Pediatric Care between 2007 and 2016

Map 23 - Heat map of attendances of basic specialties between 2007 and 2016

LIST OF FIGURES

Figure 1 - Interdisciplinarity of the constructs

Figure 2 - methodological research Steps

Figure 3 - Example Request of the Google Maps API for geocoding address

Figure 4 - Return of the Google Maps API request in JSON format

Figure 5 - Formula midfielder

Figure 6 - Formula Center Weighted Average

Figure 7 - Formula Distance Standard

Figure 8 - Formula Standard Distance Weighted

1 INTRODUCTION

The reader will find in this chapter the subject of context, previous studies related an account of justification and the gap to be explored in the survey.

1.1.1 Context

The geoGraphal distribution of doctors is a factor, which is related to the welfare of the population in any location since they are the main providers of health services.

The United Nations (UN), being a global body of high representation of society, promotes the improvement of the living conditions of all humankind. Therefore, I developed the Sustainable Development Goals (SDGs), containing 17 actual goals. One of these, the third, preaches "Ensuring a healthy life and promote well-being for all, at all ages." This objective meets the basic needs of the population concerning access to health. This access can be explained as being the factor that unites the provision of health services to the demand for health care, from the perception of a need of the individual. (TRAVASSOS, 2008).

It is a challenge to ensure universal access to health services. Therefore, the contribution of this work will carry out the study within the metropolitan area of ​​Belo Horizonte (MRBH), focused on health insurance.

The reason for the definition of MRBH as a study the cutout is not limited to its representative since it is a region inhabited by about five million people is the third-largest metropolitan area in Brazil (Metropolis Observatory, 2010, p.4 ). However, since it houses one of the leading health insurance providers in Brazil, both in terms of beneficiaries and in revenue, this provides a mass of only representative data at the national level. It stands out so that the subject matter will be referred to as the doctors associated with the health insurance provider.

1.1.2 Previous Studies

As a result of the literature review, there is a limited number of studies that address the problem of the geoGraphal distribution of doctors, from the perspective of the Brazilian situation, focusing on the evidence of inequalities and not the causes. (Rigatto 1966; Melo, 1971; AX 1996)

Studies were developed in Canada, USA, Norway, Mexico, Chile, and Japan, to understand what are the determinants of the geoGraphal distribution of doctors. (Pitblado, 1999; Rimlinger, 1963; Kristiansen 1992; NIGENDA, 1997; GOIC, 1995; Kobayashi, 1992).

The literature points out that the two main determinants of the choice are: in the foreground locations with job opportunities for the spouse (KAZANJIAN, 1996; Holmes, 1986; Dussault, 2006; Leonardson, 1985), and in the background the nearby locations where the professional attended graduation or where he performed his residency (NIGENDA, 1997; Burfield, 1986; Watson, 1980; PINTO & MACHADO, 2000). Thus, it is possible to highlight those market mechanisms are not sufficient to ensure a geoGraphal distribution that meets all access needs.

The literature relates the distribution of physicians to the economic development of the region, as can be seen in the book of Rosko (1988). Studies also associate the per capita income of the population of a settlement with the rate of doctors per capita, suggesting that equity income would cause a fair distribution of physicians. (ESIS 1954; Rimlinger, 1963; BENHAM, 1968).

1.1.3 Rationale

The purpose of the study is to collaborate to minimize the impact of the medical distribution imbalance in the metropolitan region of Belo Horizonte, in its 34 municipalities. In this context, it is important to note the representation of information that will be worked on research, compared to the general quantitative data.

Thus, it is the primary object of study MRBH, an area located in the state of Minas Gerais - Brazil. The region has 34 municipalities, according to the legislature of Minas Gerais (MGSL). It has a total population of about 5,300,000 inhabitants according to the Brazilian Institute of Geography and Statistics (IBGE), representing 26% of the population of the state of Minas Gerais and about 3% of Brazil's population. In this region, there are around 19,500 doctors, according to data of the Regional Council of Medicine of Minas Gerais (MG-CRM). Map 1 shows the geoGraphal location of MRBH about the state of Minas Gerais and Brazil.

Map 1 - CartoGraph location MRBH from the state of Minas Gerais and concerning Brazil

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Source: Giro720 - Own work, based on Image: MinasGerais_MesoMicroMunicip.svg by Raphael Lorenzeto de Abreu, CC BY 2.5.

In Brazil, there are around 48 million health plan beneficiaries, representing 23% of the population, according to the National Health Agency (ANS). In MRBH there are close to 2 million beneficiaries, representing around 37% of the population of the region.

Within the primary object of the MRBH will be worked a portion of the information, which cover almost 1.2 million people (23% of the population MRBH), distributed in 34 counties in the region being served by 5600 representing 28% of physicians practicing physicians in MRBH, according to the Federal Council of Medicine (CFM).

Table 1 are listed the municipalities that make up the metropolitan area and its population, area, and population density.

Table 1 - Population, area, and population density of the Municipalities MRBH.

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Source: IBGE

Thus, it is possible to realize the importance of information that will be addressed here, justifying attention and study.

Another important factor is the participation of municipalities concerning the amount of health insurance beneficiaries. As can be seen from Figure 1, the capital has lost about 5% of its interest concerning other municipalities, which had its percentage share increased by 5%.

Graph 1 - Percentage share of beneficiaries of supplementary health plans, between the municipalities of MRBH, 2017

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Source: ANS data - TabNet, adapted by the author (2017)

The geoGraph location of all municipalities participating in the MRBH and the municipalities that are part of the metropolitan necklace on map 2 is presented; and the metropolitan necklace made up of municipalities around the metropolitan area of ​​Belo Horizonte affected by metropolization process to integrate the planning, organization, and execution of public functions of common interest.

Map 2 - Municipalities in the Greater Belo Horizonte

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Source: IBGE, 2007

1.1.4 Omission to be Explored

After a literature review, the following weaknesses in the studies that precede this research was highlighted: earlier work focused on public health. On the other hand, it will be the subject of this study, health insurance; once the studies were focused on the spatial distribution of disease or endemic diseases. Now the object is the spatial distribution of doctors; previous research had the essence of the use of tables and charts as visual aids to present the information. In this study will be used as presentation mapping technique of spatial information; before the nuclei were municipalities or countries, now being the focus in the metropolitan area. Finally, this research highlights the temporal view, while the other works are based on the current situation of the subject.

Table 2 shows a comparison between the existing studies and opportunities envisioned by this research.

Table 2- Comparison of the focuses of the previous studies and current research

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author.

1.1.5 Problem Research

This research aims to answer the following research question: What are the dynamics of the spatial distribution of supplementary private health doctors in the last ten years within the metropolitan region of Belo Horizonte?

1.1.6 Contribution Research

Provide temporal mapping information about the distribution of doctors in the metropolitan region of Belo Horizonte.

Provide managers with analytical work that will reveal the reality of the distribution of physicians in the region where they operate, enabling decision making for the benefit of interested beneficiaries, focusing on an equal and fair distribution of their services across the characteristics of their area.

Provide society with information that will meet the third objective of the ODS (Goal of Sustainable Development, UN), who preaches: "Ensuring a healthy life and promote well-being for all, at all ages."

Munir academia of new literature that is: teaching, the way the information is presented; Current, the recent study period; relevant, the importance of their subject in everyday life of people.

1.1.7 Analysis of Object - The metropolitan region of Belo Horizonte

The metropolitan areas were established in 1973 by the Federal Supplementary Law No. 14, which created nine metropolitan areas: São Paulo, Rio de Janeiro, Belo Horizonte, Salvador, Curitiba, Porto Alegre, Recife, Fortaleza, and Belem This creation was proposed with order to solve problems that went beyond the scope of municipal powers. The Federal Constitution, in paragraph 3 of the article. 25, adopted the term "civil service of common interest," which delegates to states the possibility to establish metropolitan regions, urban agglomerations and micro-regions, "to integrate the organization, planning, and execution of public functions of common interest."

The concept of the metropolitan area expanded from the 1990s and in 2012 already amounted to 51, which added about 28% of all municipalities (IBGE, 2008). Map 3 shows the geoGraphal location of the metropolitan regions of Brazil.

Also, they have defined areas called Metropolitan necklace, composed of neighboring municipalities to metropolitan regions, i.e., municipalities affected by the process of becoming cities. The Necklace of the Metropolitan Belo Horizonte metropolitan area was institutionalized in 1993 with 20 municipalities, through the State Complementary Law No. 26.

The composition of MRBH has undergone several changes since its implementation in 1973, and it was initially composed of 14 municipalities, reaching, in 2012, to 34.

In the case of the Metropolitan Necklace MRBH, it comprises 16 municipalities, defined by the Complementary State Law No. 124 of October 17, 2012, with an estimated population of 545,999 inhabitants, according to IBGE.

Map 3 - metropolitan areas according to IBGE - 2009

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Source: IBGE, 2009

According to Wolf and Matos (2016), one of the prominent themes in the context of population studies is the spatial deconcentration process of the population. In Brazil, which has relatively recent urbanization, there was a tendency to the dispersion of the population, even with the steady growth of the population contingent in the metropolitan centers.

Even as Wolf and Matos (2016), this trend also occurs in MRBH in which the Ribeirão das Neves municipalities, Sabara, Santa Luzia, Igarapé and Vespasian, on the periphery, have steady population growth due to migration of the metropolitan core.

According to Costa and Flowers (2003), the Municipality of Belo Horizonte has been the target of a daily commute, for reasons of work, much of the economically active population of MRBH of municipalities with few career opportunities like Ibirité and Ribeirão das Neves, where 45.17% and 49.52% of its economically active population moves daily to Belo Horizonte, respectively. These, in turn, are called municipalities dormitories. Ibirité, for example, increased its population by about 40 times in the last 30 years.

In another case, the municipality of Nova Lima shows a strong connection to Belo Horizonte, for 32.93% of the resident labor force in that municipality works in the capital. This strengthens the evidence of a periphery of the process MRBH. Graph 2 shows the evolution of the population of the region concerning the capital, where you can highlight a growing population balance.

How would the distribution of physicians serving health plans to allow the service of the population of the municipalities? It is expected that the capital to be a reference polo has a diversified service network to serve its population. However, when looking at MRBH in its diversity of municipalities, we need to evaluate the distribution of physicians with more discretion and attention.

About 83% of health insurance plans are marketed business, according to ANS data. Workers receive it as one of the key benefits offered by the companies where they work. Typically, this benefit is also extended to their dependents, and as the worker, the plan holder and their dependent family members.

According to Varzim and Andrade (2006), you need to check the distribution of physicians because its location influences the community's well-being. This diagnosis must be carried out under the reality of MRBH.

You can highlight some examples of analysis: Under the employee's perspective (holder), such an individual needs health care available close to your workplace. From the perspective of his family (dependents), these people need the availability of medical care close to home.

Thus, the health insurance provider manager need to note that the distribution of doctors must meet both workers in the capital when his family, thinking of the daily population displacement. Without naming the workers who live and work in the municipalities of MRBH except for the capital. For children, they mostly lack pediatricians. The distribution of such health professionals needs to observe such nuances. All these are important variables present in the dynamics of the population that can directly affect the decision-making process of the location of doctors.

The information elucidated above shows the relevance of the chosen object of study for this research.

Graph 2 - Evolution of the population of the metropolitan region of Belo Horizonte between 1940 and 2000

Abbildung in dieser Leseprobe nicht enthalten

Source: IBGE. DemoGraph Census from 1940 to 2000. (1) metropolitan municipalities least Belo Horizonte.

1.1.8 General Objective

To analyze the spatial distribution of doctors for health care of the additional private network over the past ten years in the metropolitan region of Belo Horizonte.

1.1.9 Specific objectives

It is of fundamental importance to define the path of research, treading the following specific objectives:

- Identify the spatial distribution of doctors over the years 2007 to 2016;
- Considering the spatial distribution of doctors for care;
- spatially analyze the results and raising the causes of the observed distribution;

2 THEORETICAL FOUNDATION

2.1.1 Context

Throughout this chapter, we will present the selected constructs for research and serve as a nucleus for the present work. Each theme will be contextualized for a complete explanation of the terms. It will also be elucidated its relationship with the proposal of this study. At the end of the chapter will be discussed interdisciplinarity between the constructs.

2.1.2 Health Geography

Historically, Health Geography starts from the first records of health variations in populations of different places made by doctors, when they began to travel. These doctors described the places and peoples in ancient Greece in the fifth century BC (Armstrong, 1983). The relationship between health and the "local" was first addressed in the Hippocratic treaty" Of Ares, Waters, and Places," in about 480 BC, and also in the writings on medicine in Egypt by Herodotus around 500 BC (THOUEZ, 1993).

Traditionally, descriptions of cities, regions and even whole countries, have been documented by doctors as medical-geoGraphal surveys, highlighting people and places. Wich diseases that afflicted them, local treatment wisdom, and knowledge about their causes. These surveys have become more diversified in that Europeans colonized Asia, the Americas, and Africa, serving as a guide for settlers and armies disputed regions of the potential diseases in unknown lands. That is the sixteenth and seventeenth (Armstrong, 1983).

Between the eighteenth and nineteenth centuries begins the systematization of information on the location of disease in studies called Medical Topographies, which are the precursors of the modern Medical Geography. These comprised information about cities, treating health conditions, meteorology, hydrology, plants, animals and especially the way of life of the locals (Armstrong, 1983; THOUEZ, 1993; OLIVERA, 1993).

One of the most important works, by its scope, content, and influence (the first to be established in the strict sense "Medical Geography") was written by Ludwig Leonard Finke in Leipzig (1792), with followers throughout the nineteenth century. However, the first paper entitled Medical Geography was Bourdin J. (1843). The latter is considered the first work on Medical Geography and not to Finke, which is earlier in terms of date (PESSÔA, 1978).

Pessôa (1978) says that the Medical Geography was treated vigorously in Brazil even before Pasteur (second half of the nineteenth century), meeting reports describing the distribution of disease in Brazil, carried out by naturalists and foreign travelers.

The geoGraphal approach opens a wide horizon for the establishment of new lines of study, planning, and management, created by the union of Human Geography and Health, giving the term Geography Health.

According to Abreu (2010), every event or phenomenon occurs at some time, somewhere, or space. Space can be analyzed in various ways, depending only on the issue to be studied. Spatial analysis is no longer retained in the hands of geographers. The maps have become indispensable resources for research, making the geoGraph knowledge and the location of these events are valued, not only in geography.

The population's access to health services is critical for health care quality. The geoGraphal location of offices is a critical factor that interferes with this access.

The literary theme of March came with Josué de Castro, who, through his "Geography of Hunger," succeeded for the first time in the history of the country, integrating geoGraph and health knowledge (Castro, 1957).

Studies on the events of the health scope, the scenario of urban or regional space, are growing every day, especially after the advent of GeoGraph Information Systems, which allowed the generation of geo-referenced information to help companies and the government itself in developing spatial strategies.

Although not located in highly privileged areas, with marked technical density, certain health services will choose areas for their location to be marked by certain technical equipment, such as bus terminals, bus lanes, the sidewalks, the major access roads and "devalued and damaged buildings," thereby revealing, as pointed out Montenegro (2006, p. 125), "the active role of space in conditioning the location and carrying out the activities."

To understand the spatial selectivity by private healthcare companies, or even the doctors, and the role played by the conditions offered by places, it is necessary to understand the geoGraphal space as synonymous with used territory; a social level, which imposes on everyone and everything. At this point, it is important to check and analyze the use of the territory by the company and by companies (SANTOS, 2008).

Every moment of a historical period, it appears the differentiated use of the territory, which requires the taking of decisions that enable the creation of some geoGraph objects. These will set the spatial forms to meet the objectives of capitalist reproduction in a given historical moment, and the new shares conditioned by pre-existing object systems in the territory (Ramalho, 2003).

The facilities or difficulties in land use for certain activities, actually due to its heterogeneity regarding the dissemination of technical objects and present spatial organization resulting phenomena that "left roots previously" (SANTOS, 2007, p. 56). Therefore, the spatial selectivity, it surpasses itself as a device that constantly guides the new space organization of social activities, given that the spatial selectivity is the "local election that society begins assembling its geoGraphal structure," permanently. (MOREIRA, 2007, p. 82).

From this perspective, it is understood that the installation of a private health project, while activity guided by the capitalist logic dominated by the issue of spatial selectivity, considering that this type of service, according to the specialties presented and technologies, seeks to locate in certain areas of the city (MOREIRA, 2007).

The Health Geography is still a domain little-explored among geographers. At different times and places they have been made attempts to institutionalize spaces for dissemination and debate of ideas. Also, they have been conducted Health Geography symposia periodically. A whole experience of theoretical and methodological on the distribution of damage to health is realized and strengthened in the field of public health, especially in Epidemiology and Social Medicine (Peiter, 2007).

2.1.3 Supplementary Healh

Health is a right of all Brazilians. It is what ensures the Federal Constitution of 1988. Thus, the State has to provide access to health for all Brazilians, through the provision of medical and hospital care, through social and economic policies; and that the health system can be divided into two: public and private (BRAZIL, 2007).

The public subsystem is represented by the Unified Health System (SUS), which is a universal system, with public funds and participation of all levels of the federation; with integration and coordination between the different spheres and the provision of assistance by own network of services of municipalities, states and Union, public services in other areas of government and private contracted services or agreement (BRAZIL, 2007). The SUS is free directly, though the payment of taxes supports it, or is paid indirectly.

The private subsystem is also divided into two: the health insurance sub-sector and the classical liberal subsector. The classical liberal is composed of the autonomous private practice with its clientele, not fixed and captured without formalization, with free costs and not tabulated. Already the health insurance, according to Pietrobon (2008), is established for services funded plans and health insurance. It is the most common in the private subsystem. It has private management and regulation by the National Health Agency (ANS). Health care providers are private and accredited by the plans and health insurance or the medical cooperatives.

Sub-sector health insurance is defined as supplementary. In Brazil, there is a compulsory charge for social security, which supports public health in the country and gives the right to access to public service. On the other hand, there is the option to hire and pay private insurance to have access to health care and to further free. You can even classify it as complementary because it supplies the limitation of the official system (BAHIA, 2002).

SUS should guarantee equality and universality of health but, contradictorily, such a system exposes its inefficiency, reviews, and inequity, which strengthens further the health supplement subsystem, allowing its expansion in the domestic market (SILVA, 2003 ).

The increasing failure of the public health system, which often does not support the amount of care required by the population, has allowed the strengthening of a market that is growing every day; private health. This market, in turn, represented by health insurance carriers, works as an escape valve for health in Brazil (Silva 2003).

The supplementary health insurance companies manage, following rules and regulations, their providers, i.e., the accredited doctors. The fact that a company following this accredits a doctor means that it can carry out health care for clients who contract the health plans (SILVA, 2003).

The ANS mandatorily regulates such companies. However, the regulation, which is defined by Law 9,656 / 98, does not cover the validation or even defining the location of private services (SILVA, 2003).

On the other hand, it is not the practice of health insurance carriers set or enforce locations of care hospitals and clinics accredited, and even the offices of their insured doctors/members, which leaves this point adrift and beneficiaries to the mercy of personal decisions (SILVA, 2003).

2.1.4 Spatial Statistics

According to Wong and Lee (2005), the concept of statistics is linked to quantitative measures derived from a set of numerical data that present various information about said set. The statistics can be divided into classical and spatial statistics.

The classical statistics can be further subdivided into descriptive statistics and inferential statistics. The specification is calculated from a set of data for describing how values ​​are distributed within the set. Already the inferential mode seeks to conclude a population, based on data derived from sample information in this same population (WONG; Lee, 2005).

The Spatial Statistics is closely based on classical statistics; however, labors essentially spatially referenced data. Wong and Lee (2005) state that certain spatial statistics are called geostatistics emanated end of geosciences entry.

Also, according to Wong and Lee (2005), spatial data is composed of map data and attribute data. The first describes the location and geometric characteristics of objects, and the attribute data answer descriptive information of the data.

The processing of geoGraph data traditionally employs well-defined techniques statistics (theories, assumptions, variance, and linear models), but does not allow consistent consideration of the geoGraphal space. To address these limitations of the data analysis, such elements are related to cartoGraph and georeferenced components to improve the construction of knowledge from the space element (DRUCK et al., 2004).

As Andriotti (2003) and Galvani (2005), the statistical analysis may be performed from the central tendency (maximum value, minimum value, amplitude arithmetic mean) measures of dispersion (coefficient of variation and deviation from the mean ) and measures correlation (correlation coefficient).

The organization of the data was drawn to the proposal to carry out statistical analysis of information concerning the MRBH, to identify discrepancies in the use of space on the location of service points in the health insurance.

2.1.5 Spatial Analysis

The spatial data analysis techniques are essential for spatial statistical modeling, which is usually sensitive to the type of distribution, the presence of extreme values.

The spatially distributed data analysis is being increasingly considered in health management; it presents new information for planning and evaluation of actions based on analysis of the spatial distribution.

The mapping techniques allow describing Graphally diverse phenomena in health, including the allocation of services, and even the accessibility studies. In this research, these techniques will be used as tools of exploratory analysis and results representation. Below are outlined the main types of maps that will be used in this work.

The first type of map to be used in this research is the "location points." It is of simple construction, in which points are noted on a cartoGraph base. In this work the points where they are located health care facilities will be marked. In general, each point represents a local call and may represent different urban facilities through the use of symbols or color codes (Gesler, 1986).

The second type of map is called "Standard." It is usually used to compare areas in health services. The most common territorial division is geopolitics: municipalities, states, districts, administrative regions or districts. The indicators are calculated for each map subdivision, allowing the division of the region into classes, according to statistical criteria or not. Each class will be associated with a pattern (hatch) or color that will fill the map subdivision (Marshall, 1991). This research will use this type of map to represent the comparison between the municipalities, on criteria such as population density, percentage of physicians, etc.

The provision of health services is made up of basic services, frequent use and which have lower costs, and complex services using higher technology and lower spatial density of demand; the latter are subject to economies of scale in its bid (SILVA, 2003).

The differentiation and complexity in offering services allow you to use a valuable theoretical framework entitled "Central Place Theory (TLC)" to analyze the spatial distribution of health services in MRBH. According to Christaller (1933), who developed this theory, it is based on the principle of centrality, in which there is a major urban center called the central place and the complementary region, or surroundings. This principle preaches the dependency relationship between the main core and its surroundings because this is the place of offering goods and services urban nature.

This study will assess the application of the TLC for the distribution of service points within the MRBH, i.e., verify the existence of the relationship between the central point (Belo Horizonte) and its surroundings.

2.1.6 Geographic Distribution of Physicians

Health is considered as an essential support to communities in general. Nasiripour (2013) states that the human resources employed in this sector are vital to the smooth operation of the delivery of health services. Moreover, he claims that the health system should determine the organization of human resources to meet the needs of society to achieve a level of service to ensure people's health and their ability to have useful and productive lives.

The study on the location of medical operations and their geoGraphal distribution has been based on both the economic literature as health in recent years (Carpenter, 1999). Healthcare accessibility for impasses is present in various contexts, highlighting the geoGraphal factors, socioeconomic inequalities, and factors related to the organization of supply and demand (Vieira da Silva, 2007).

Among the geoGraph features are the natural barriers or generated from the transformation of space by human activity, and certain travel time by distance, which are the main obstacles to the access of citizens to health care, as they represent the imposed resistance the geoGraphal space to users' displacement trajectories towards the services or to the places where they develop health actions (TRAVASSOS, 2008).

The study "Medical Demography in Brazil" (DMB) held by Scheffer et al. (2015), researchers from the Faculty of Medicine, University of São Paulo (USP), with the support of the Federal Council of Medicine (CFM), provide general information and analytical doctors. This work provides evidence issue of the distribution of physicians in Brazil and will serve as support and foundation of this research.

2.1.7 Reason Doctors / Inhabitants

According to the Medical Demography study in 2015, Brazil, the doctor ratio per 1,000 population grows straight and steadily, from 1.15 doctors per 1,000 inhabitants in 1980 to a ratio of 2.11 in 2015. However, the growth rate population decreased from 13.5% in 1985 to 5.4% in 2014, considering periods of five years. The growth rate of the number of doctors, in turn, initiates 30.4% in 1985, declining to 10.5% in 2010 and up to 14.9% in 2015 (Scheffer et al., 2015). In all five-year periods, the growth rate in the number of doctors is about twice that of the population. In 2014, for example, while the growth rate of medical reaches 14.9% of the population is 5.4%.

According to Scheffer et al. (2015), the difference in growth rates clarifies the continuous increase in the ratio physician/person. It should be noted that between 1980 and 2010, there was a decrease in the population growth rate, due to declining fertility and increasing life expectancy.

The year of 2015 provides the DMB Figure 4 on which it is perceived that there are periods of greater and lesser growth in the number of doctors. In the decades between 1940 and 1970, while the population increased by 129.18%, the number of doctors rose 184.38%, from 20,745 to 58,994. In the thirty years that followed, from 1970 to 2000, the total number of doctors reached 291,926, a jump of 394.84%, against population growth of 79.44%. From 2000 to 2010 the medical contingent reached 364 757, which represents an increase of 24.95%, against a population increase of 12.48% (Scheffer et al., 2015).

According to Scheffer et al. (2015), the clear increase in the number of doctors in Brazil results essentially from the opening of new medical schools and the expansion of undergraduate places in Medicine, aspects related to the evolution of demand and increasing health needs, and offering more medical work positions due to the expansion of the health system.

Graph 3 - Evolution of the number of doctors between 1910 and 2015 - Brazil, 2015, based on the registration of medical

Abbildung in dieser Leseprobe nicht enthaltenSource: M. Scheffer et al., 2015 Medical Demography in Brazil., P. 37.

Abbildung in dieser Leseprobe nicht enthalten

Source: M. Scheffer et al., 2015 Medical Demography in Brazil., P. 37.

With 2.1 doctors per 1,000 inhabitants, Brazil is the eighth country with the lowest rate among the 40 selected for the study (Figure 5), below the average of 3.2 doctors per 1,000 inhabitants. Below are just Brazil: South Korea, Turkey, Chile, China, South Africa, India, and Indonesia. The country with the highest rate in Greece, with 6.1 workers per 1,000 inhabitants, followed by Russia, with 5; Austria, 4.8; Italy, with 4.1; Portugal, 4.0; Sweden, 3.9; and Germany, with 3.8. Of the 40 countries surveyed, twenty have more than 3 doctors per 1,000 inhabitants. Below this rate is also developed countries like the UK, Ireland and New Zealand. Brazil has a rate close to countries like the United States, with 2.5 doctors per 1,000 inhabitants; Canada, 2.4; Poland, with 2.2; and Japan, with a rate of 2.2.

Graph 4 - Doctors per 1,000 inhabitants, according to selected countries.

Abbildung in dieser Leseprobe nicht enthalten

Source: Scheffer M. et al., Medical Demography in Brazil, 2015, p.79.

2.1.8 Projection New Doctors

Following the 2015 DMB, the projection of new medical points to 32,476 new physicians in 2020, as can be seen in Figure 6. These doctors represent 11,677 more than the 20,799 who formed and entered the profession in 2014. Brazil had in October 2015, with 257 medical schools, and 69 of them open after the year 2010, formed not by doctors have less than six years of existence. If the number of authorized spaces is maintained, protrudes from 2015, significant and cumulative increase in the market medical input, as the new schools will form the first groups (Scheffer et al., 2015).

Graph 5- Evolution of the number of new doctors, according to new records and projection of new graduate vacancies - Brazil, 2015. Between 2000 and 2014 - new doctors registered in CRMs. Between 2015 and 2020 - Forecast of the number of vacancies (MEC) in new medical courses

Abbildung in dieser Leseprobe nicht enthalten

Source: Scheffer M. et al., Medical Demography in Brazil, 2015, p. 39.

2.1.9 Guests of Physicians

As Scheffer et al. (2015) suggest, medical mobility between cities, states and regions, whether temporary or permanent, is a variant that needs to be examined in an unequal distribution of medical approaches.

According to DMB data in 2015, 7% of the country's doctors work in different municipalities of those where they reside, and 29% meet in the city where they live and also moving to work in another municipality (Scheffer et al., 2015).

Thus, the authors conclude that regional, state or local mobility of doctors, is the temporary displacement, definite or caused by professional practice in more than one location, it is a relevant factor that should be considered in the distribution studies of doctors (Scheffer et al ., 2015).

The study reveals that in Brazil, there are two distinct scenarios concentration of doctors. On the one hand, the capitals of the 27 states meet 55.24% of medical records, although its population represents only 23.80% of the national total. On the other hand, the entire interior (5,543 municipalities, excluding the capital) concentrated 44.76% of physicians while its population amounts to 76.2% of the national total. This difference directly reflects the ratio of doctors per 1,000 inhabitants: the capital has 4.84 ratios, while inside there are 1.23 doctors per 1,000 residents, four hundred percent difference between the two.

2.1.10 Medical Dedication

The study reveals that medicine is a profession with considerable membership, since the percentage of professionals who are dedicated exclusively to medicine is high, whether in care, management, service management, teaching, research or other function performed by the doctor. Doctors with full dedication represent 83.7% (Chart 7). The remaining 16.3% have a partial dedication to medicine, also exerting a second activity or craft; whether as a businessman, lawyer, parliamentarian, journalist, etc. (Scheffer et al., 2015).

Graph 6 - Distribution of doctors according exclusive or partial dedication to medicine - Brazil, 2014

Abbildung in dieser Leseprobe nicht enthalten

Source: Scheffer M. et al., Medical Demography in Brazil, 2015, p. 99.

According to the 2015 study DMB, Brazilian doctors have, in general, multiple labor bonds (Chart 8), of which 48.5% of professionals have three or more links. Link work here is equivalent to every occupation, employment, position, position, function or doctor paid employment. The study concludes that the accumulation and coexistence of work characterize the medical profession, and 78% of doctors working for more than one employer and has, throughout his working day, over a link (Scheffer et al., 2015 ).

As in Figure 8, only 22% of doctors have a single work bond, while 5.4% have six or more, 29.5% and 24.3% have two to three links accumulate. Together, these last two groups represent the largest contingent of Brazilian physicians, representing 53.8%.

Graph 7 - Distribution of doctors according to the number of work contracts - Brazil, 2014

Abbildung in dieser Leseprobe nicht enthalten

Source: M. Scheffer et al., Medical Demography in Brazil, 2015, p 101.

As Scheffer et al. (2015), working time is the time that the doctor is available to their professional practice. In the study, this time is measured by the number of hours worked in a typical week, summing their working links. Approximately one-third of physicians (32.4%) work more than 60 hours per week, and 75.5% work more than 40 hours, as shown in Figure 9.

Graph 8 - Distribution of doctors, according to the weekly schedule - Brazil, 2014

Abbildung in dieser Leseprobe nicht enthalten

Source: Scheffer M. et al., Medical Demography in Brazil, 2015, p. 104.

2.1.11 Business Sector

According to the DMB 2015, 21.6% of physicians work exclusively in the public sector, and 26.9% work exclusively in the private sector. The rest, 51.5% work in two spheres, public and private. Considering the most exclusive co-operation in both sectors, we can attest that 78.4% of doctors work in the private sector and 73.1% work in the public sector, as can be seen in Figure 10 (Scheffer et al., 2015 ).

Graph 9 - Distribution of doctors, according to acting in the public and private sectors of health - Brazil, 2014

Abbildung in dieser Leseprobe nicht enthalten

Source: Scheffer M. et al., Medical Demography in Brazil, 2015, p. 111.

According to the study, with respect to 78.4% of the doctors working in the private sector (26.9% of them exclusively), the most common workplaces are private practice (40.1%), the private hospital (38, 1%) and clinical or private clinic (31.1%); followed by private university (5.3%), medical service company (4.8%) and laboratories and diagnosis and therapy (1.8%). This can be seen in Table 3 (Scheffer et al., 2015).

Table 3 - Distribution of doctors working in the private sector, according to the workplace - Brazil, 2014

Abbildung in dieser Leseprobe nicht enthalten

Grades:

(1) The doctor owns or shares the private practice in partnership with one or more doctors.
(2) This refers to the nature of private care (hospital serving private patients and health plans).
(3) The doctor does not own but works or provides services in a public clinic or private clinics.
(4) Teaching and research activities.
Source: Prepared by the author, adapted from M. Scheffer et al., Medical Demography in Brazil, 2015.

The study found the concentration of medical services, activities and private health system structures that serve narrow populations and clienteles, formed by private consumers or licensed health plans, the focus of this research (Scheffer et al., 2015).

The presumed numerical balance of doctors working in the public sector and the private sector need to be considered. About 75% of the population uses the SUS exclusively. On the other hand, a portion of 25% of the population uses additional medical care, in addition to the right to SUS. This demonstrates inequality between the public and private sectors (Scheffer et al., 2015).

Inequality is this distribution. In 2014, according to IBGE estimates, the country had 201 032 714 inhabitants. In June 2015, according to figures from the National Health Agency (ANS), customers of health plans were 50,516,992. The remaining 150 515 722 Brazilian resort exclusively to the SUS. In short, the population served by the additional medical care is about three times more doctors at their disposal that the population served by the public. According to Scheffer et al. (2015), public-private discrepancies can be significantly more alarming in different Brazilian regions and between different medical specialties.

2.1.12 Interdisciplinarity of Constructs

Regarding the theoretical framework presented here, it is essential to refer to the relationship between all selected constructs for this research.

Based on the reading of selected texts can describe their importance and actual use in this research

Briefly, the GeoGraph Distribution of Physicians axis with the metropolitan area of ​​Belo Horizonte, working in the Health Insurance will be addressed, following the approach of the Health Geography, using the tools of Spatial Statistics with the perspective of spatial analysis. Such constructs are shown in Figure 1.

Figure 1 - Interdisciplinarity of the constructs

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

3 METHODOLOGY

This chapter initially depicts the classification of research to position the reader as to the type of work. Subsequently, the methodology used in this research consistently and gradually appears.

3.1.1 Methodological Categorization

This research has naturally interdisciplinary content, mainly involving the disciplines of geoGraph information systems, cartography, statistics, and health.

The study approach is quantitative since orders of magnitude will be presented statistics, grouped or scattered. The mensuration helps to clear up the phenomenon under study.

According to Richardson (1989), a quantitative approach is characterized by using the measurement from the collection until the processing of information, using statistical tools, and generating accurate results. In turn, it is applied research, which, according to Schwartzman (1979), is one that generates a practical result, whether economic or not, provided it is not knowledge itself.

Also, the objective of this research is exploratory. According to Theodorson and Theodorson (1970), exploratory research is a preliminary study, in which the primary goal is to acclimate to a phenomenon that wants to investigate, allowing the researcher to choose the most appropriate techniques for your search.

As for the procedure, it is a case study. As Ventura (2007), the case study analysis the investigation of a specific case, marked, contextualized in time and place, for the execution of the search for information. Faithfully presented concept, this work is focused on a health segment of the company, for ten years, in a specific region of Brazil.

The collection of data of this work comprises the search for information through consultations in secondary banks, specifically in corporate databases. As Smith (2005), secondary data are data previously collected, tabulated, and sorted for other purposes, different results for meet current analysis needs.

For the analysis of the spatial distribution of health care, we used statistical and spatial data processing. Thus research employs quantification in data collection, the data analysis, and also the presentation of the results, which benefits from the use of thematic maps to better highlight the phenomena. The thematic mapping allows obtaining knowledge from pattern recognition and spatial relations, stimulated by viewing (Martinelli, 2003).

3.1.2 Literature Review

A literature review is a secondary analysis study to identify and elucidate the available evidence in the literature regarding a survey question (PETERSEN, 2008).

According to Yin (2015), the route begins with a detailed review of the literature with the idea focused on the issues or research objectives. Then sets up the "case," the problem question is promoted, we analyze the relevant data to be collected in the context of the study, research is delimited and is elaborated constructs to be analyzed. Finally settles the type of case study to be adopted.

In this research, we have followed the comments made by Yin (2015, p.3), so that the literature review was carried out in parallel to the database work, statistical and cartoGraph data, with the aim of a better understanding of the constructs and issues involved.

3.1.3 Methodological procedure

Six methodological steps were implemented to meet the objectives proposed in this research: (1) data extraction tabulated in relational database, (2) building and running routines for the treatment of the extracted data, (3) geocoding of service points, (4) processing of data with spatial statistics, (5) generation of maps for visualization of information and (6) generation of analytical reports from the information collected. Figure 2 indicates each of the steps.

Figure 2 - methodological research Steps

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

3.1.4 Data Extraction

Note that this database contains historical information of doctors accredited a highlight health plan operator in the mining market. The principle of this research is with data extraction. It conducted access to the relational database, Oracle 11g in the case where the information is stored. Then they were raised and set the data entities that hold the records needed for consultation. Following the extraction of the data was performed using SQL routines (Structured Query Language). This was achieved with the aid of Programming Language tool / Structured Query Language (PL / SQL).

3.1.5 Data Treatment Routines

Given the quality and consistency of the data, this research conducted their treatment. Thus, in the second step, the purpose was to perform an audit for ratification data extracted from the secondary database. Absences, inaccuracies or incompleteness of the data has been cleared. The search for data validation is a process of paramount importance for the veracity and credibility to the results. Routines were created in PL / SQL that conducted verification tests on the extracted information. Only the data passed all the tests is to be utilized in the study.

The first test assessed the completeness of medical production, i.e., only doctors who have had some medical attention in the study year are to be used. The second test evaluated the municipality of emergence of these calls, restricting only to doctors who conducted consultations within the metropolitan area (the operator's business rule exists the concept of exchange, where a customer is serviced by another carrier, outside the area of ​​operation of health plan contracted, which is often the case of emergency care). The third test checked the type of care. They have only availed consultation calls and revoked the appointments of surgical types, outpatient, or even hospitalization. The fourth test removed the records of doctors who have not completed registration,

Finally, a care conference was held only made the operator's customers, being removed from the attendance records to other operators or even individuals. It is also important to note that the selected data respected the address of the health care site as the realization address at the time they occurred.

Certainly, it was important to quantify these calls because of the granularity of the search to enable the display of information on maps. With this, it can be noted that the selection quantified the average annual medical consultation calls made by place of care by a physician, in the year of implementation of health care.

When choosing a doctor, it would be possible to establish your expertise and your age and gender profile. To distinguish the point of care, it would be feasible to geo-reference the address. This process was made for each of the years spanning research, from 2007 to 2016, enabling the creation of a historical relationship of phenomena.

3.1.6 Geocoding Service Points

It is defined here as the point of care as the physical location where any health service runs, which can be an office, clinic, hospital, etc. Thus, the third methodological step of geocoding treated, which is the process of converting addresses (such as street name and house number) in geoGraph coordinates (latitude and longitude); which allow the inclusion of location markers on a map, or the map placement. In this case, an Application Programming Interface was used (API) available for free by Google.

The operation of this API part of creating free key usage. Based on this key, concatenate to Uniform Resource Locator (URL) standard with the address of which you want to get the latitude and longitude. Figure 3 shows an example of the API call, and then Figure 4 shows the result returned in response to the request, the JavaScript Object Notation (JSON).

Each record of the base selected in the previous step was processed using this API. The address of the records served as the input parameter to the API, and return the attributes latitude and longitude were extracted subsequently related to the input record.

Figure 3 - Example Request of the Google Maps API for geocoding address

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2007

Figure 4 - Return of the Google Maps API request in JSON format

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Table 4 illustrates the result of the extraction and processing of information, along with the coordinate information, API implementation of the result to each of the addresses. The API returns the latitude and longitude for the main study. In this step, the textual information on the street was discarded. The average production attribute quantified had been obtained from the secondary database.

Table 4 - Result information processing calls with the geocoding

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

3.1.7 Spatial Statistics Application

The fourth methodological step included the processing of data with spatial statistics.

According to the Ministry of Health (1987), basic medical specialties are considered: internal medicine, general surgery, gynecology, and pediatrics. All measurements and spatial statistical applications take into account the four directions and are applied to each of them.

The dynamic of the study was built following three focuses, as the direction of the medical specialties: 1) basic medical specialties, 2) only pediatrics and 3) all specialties. These directions were set as targets according to Table 5.

Table 5 - Analysis of selected within targeting medical specialties

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

According to Andriotti (2003) and Galvani (2005), the statistical analysis may be performed from measures of central tendency, measures of dispersion and correlation measures.

The first calculation executed is the average center. It is a measure of central tendency, similar to the average. It is defined as the point of a plan that minimizes the sum of squared distances to all other points in the plane. It can be pointed out as the balance point of a given plane. It is calculated by the equation shown in Figure 5, where Xi and Yi are the coordinates existing in decimal degrees.

Figure 5 - Formula midfielder

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

The X and Y components resulting from the application of the formula correspond to a pair of coordinates representing a point in the plane, respectively the latitude and longitude in decimal degrees.

In the dynamic proposal, it was obtained a mean center for each year of research for each direction. Table 6 shows examples of the mean centers obtained.

Table 6 - Average Centers of Basic Specialties

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

The second calculation was performed at the weighted average center. While the average center is the gravitational center of a set of points, regardless of the occurrence of the intensity of points, the weighted average center takes into account the weights of the associated phenomena.

In this work, the weight will be determined by the medical production medium at a point of service (average number of calls at a given point of care). Thus, not enough to know the location of a health care point is also relevant to take into account the volume of calls.

The locations of the midpoint of both the weighted average point are sensitized by positioning each particular point, as well as the weight of each location. Points with remote locations or with high weights, they magnetize to the distribution center. The average center is calculated by the equation shown in Figure 6, where Wi is the value to consider, in case the medical production.

Figure 6 - Formula Center Weighted Average

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

The third calculation was carried standard distance. Knowing the average center is not enough, because different distributions can have the same central point. Thus, it becomes beneficial measures of variability or dispersion. The standard distance, but is the dynamic radius, or distance standard, which represents the variability of a set of points around a central mean value. Along the way, it attains a circle centered on the central midfielder, whose radius is called the standard distance.

The default distance is corresponding to the standard deviation concept. However, the standard deviation is to support dimensional differences or distances squared for each value of X the mean of the set. The standard distance will have the same reasons. However, about two axes X and Y. The distance is expressed in standard units of measurement X and Y (m, kilometers, miles, degrees, etc.). Very different amounts of data analyzed may influence the value of the standard distance because their distances are squared. Figure 7 shows the pattern distance calculating formula.

Figure 7 - Formula Distance Standard

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

Table 7 shows an example of the medium centers obtained.

Table 7 - Standard Distance and Centers of Basic Medium Specialties

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017

The fourth and final calculation performed was the weighted standard distance. The calculation of the standard distance does not take into account the relevance or weight in existing care facilities. Previously, it used only the location of the points. This distance should be used when the significance of a phenomenon located on the points relevant.

For this work, the weighting is determined by the average number of visits to a particular point of care. Its formula is shown in Figure 8.

Figure 8 - Formula Standard Distance Weighted

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

3.1.8 Generation of Maps

For the manufacture of cartograms and maps were used various cartoGraph databases, together with alphanumeric data. The GIS was chosen QGIS (Quantum GIS) version 12.8. It is a geoGraphal information system open-source (GIS) friendly, licensed under the GNU General Public License.

QGIS is an official project of the Open Source Geospatial Foundation (OSGeo). It runs on Linux, Unix, Mac OSX, Windows and Android and supports multiple formats and features vector, raster and database. The reasons that led to the choice of QGIS were: (a) ease of learning, (b) gratuity and (c) robustness. In a way, the good money of this application led to the decision to use it for this search.

The location map of the metropolitan region of Belo Horizonte was built from a query to the 34 municipalities that are part of it. Thus, the union of the area of ​​all, it established the region, which has its seat in the city of Belo Horizonte. The main cartoGraph bases were obtained from the website of the Brazilian Institute of Geography and Statistics (IBGE) and the State Spatial Data Infrastructure of Minas Gerais (IEDE).

3.1.9 Generation of Analytical Reports

The information obtained was analyzed and worked. From these analyzes were generated analytical reports being grouped into the following areas: (1) sociodemoGraph data and (2) Atlas of GeoGraph Distribution in medical MRBH.

4 RESULTS

Next, we will present the results obtained from the analysis of the data generated by the secondary databases, after processing the information, as explained in the section “Methodological Procedure.”

In the first part of this chapter, the temporal sociodemoGraph data will be portrayed. In the second part of this chapter the georeferenced information will be presented through cartograms and maps, offering a view not only temporal but also spatial. All information will be treated with the temporal vector, within the scope of research of the last ten years.

4.1.1 Medical DemoGraphs of MRBH

The cross-sectional demoGraph study with secondary data includes sociodemoGraph characteristics, geoGraphal distribution, medical specialties, and comparisons with some groupings. For this, it employs indicator measures cited in the literature (BERENYI, 2010) and demonstrated in the form of absolute or effective frequency (e.g., number of doctors), relative frequency (e.g. percentage distribution of doctors by sex), density (e.g., number of doctors per inhabitant), among others.

4.1.2 General Analysis (All Specialties)

Analyzing the number of doctors, according to Graph 11, the time series presents the growth in the number of doctors.

In 2007 there were about 4,400 doctors, reaching around 6400 in 2016, representing an increase of more than 2000 doctors in the region. This corresponds to a growth of about 46%.

According to Scheffer et al. (2015), the growth in the number of doctors in Brazil was around 25% in the period between 2000 and 2010. In a way, the national trend is also reflected in the region of study of this research.

Graph 10 - Evolution of the total number of supplementary health physicians from 2007 to 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Although each year the number of doctors increases, the growth rate is not homogeneous; on the contrary, it fluctuates as can be seen in Graph 12.

Graph 11 - Growth rate between subsequent years of the total number of supplementary health physicians between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Exploiting now the age attribute, it can be seen from Graph 13 that the population of active doctors aged on average 2 years, starting from 49.4 years in 2007 and reaching 51.4 years in 2016.

These values contradict the national trend of rejuvenation in the medical profession, which the DMB points to concerning the year of birth; although there were years when the average age decreased.

Graph 12 - Evolution of the average age of supplementary health physicians between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Regarding gender, in general, the number of women is growing each year proportionally, as can be seen in Graph 14.

Feminization has become a trend, as Scheffer et al. (2015). If this propensity for growth remains at the same pace, the number of women working in medicine will be higher than men from the year 2040.

Graph 13 - Percentage evolution of gender of doctors between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 15 below shows the trend line for the future, where the year 2040 would be the break-even point in this hypothesis.

Graph 14 - Evolution of the gender of doctors between 2007 and 2016 (with trend line until 2043) in MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The number of points of care is an important aspect of this study, due to its relevance, because they are places where there is medical care, and this is the main theme of this research.

Graph 16 shows the number of attendances over the years.

Graph 15 - Evolution of the number of health care points in supplementary private health between 2007 and 2016 at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

It was considered in this topic the “capital” being Belo Horizonte and the “interior” being the municipalities that are part of MRBH except for the capital.

By comparing the number of service points in the capital and the interior, in Graph 17, it was possible to notice two aspects. The first would be the numerical supremacy of service points in the capital over the interior, over each year. The second is relevant, albeit modest, an increase in the number of service points in the interior from 2011.

In the capital, we have a ratio of 303 inhabitants by place of service. Inland, the proportion is 1140 inhabitants per place of care. Thus, it is possible to affirm a more than 3.8 times greater availability of service points in the capital compared to the interior of MRBH. However, the interior has 5% more inhabitants than the capital of that region. This is important since the surroundings of Belo Horizonte have more inhabitants than the capital.

Graph 16 - Comparative evolution of the number of healthcare points between the capital and the interior, from 2007 to 2016, at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 18 shows the percentage difference in the capital x interior ratio. Looking at the graph, it is possible to notice a constant decrease in this ratio, which can be considered as an indication of the decentralization of the service places.

Graph 17 - Evolution of the percentage difference between the number of health care points between the capital of the interior, from 2007 to 2016, in MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

To better understand the dynamics of the interior, it was necessary to broaden the view, showing the information on the clipping level of the municipalities, as can be seen in the following graphs. The separation of municipalities in the various graphs sought to respect the volume of care. Thus, the municipalities with approximate volumes were grouped.

In Graph 19, the selected municipalities have at most 2 points of service, some even having none. With a total population of almost 340 thousand inhabitants, representing approximately 6.4% of the population of MRBH, and a total of 6 points of service in 2016, these municipalities reach an average ratio of 56,666 inhabitants per point of service. It is not possible to observe growth in this quantity, and on the contrary, there was a decrease from 11 points in 2007 to 6 points in 2016.

Graph 18 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Capim Branco, Confins, Ibirité, Jaboticatubas, Juatuba, Raposos, Sao Joaquim de Bicas, Sao Jose da Lapa and Sarzedo

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Looking at Graph 20, we can see considerable growth in the supply of service points in the municipalities covered, especially after 2011; and there is no decline compared to 2007. The total population of these municipalities is around 230 thousand inhabitants, representing 4.3% of the population of MRBH, in a total of 127 points of service, generating a ratio of 1810 inhabitants by place of service.

Graph 19 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Brumadinho, Caeté, Esmeraldas, Igarapé, and Matozinhos

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The third grouping is depicted in Graph 21, in which it is possible to notice two scenarios: the first group of municipalities where the number of health care points grows over time and a second where this amount decreases. The total population of these municipalities is around 860 thousand inhabitants, representing 16.3% of the population of MRBH, out of 256 points of service, making an average of 3359 inhabitants per point of service in 2016.

Graph 20 - Evolution of the number of health care points between 2007 and 2016 in the municipalities of Lagoa Santa, Ribeirão das Neves, Sabará, Santa Luzia and Vespasiano

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The last grouping is shown in Graph 22, where it is possible to notice growth in all municipalities of the court. The total population of these municipalities is about 1.230 thousand inhabitants, representing 23.3% of the population of MRBH, out of a total of 2037 points of service, making an average of 603 inhabitants per point of service in 2016.

Graph 21 - Evolution in the number of health care points between 2007 and 2016 in the municipalities of Betim, Contagem, Nova Lima and Pedro Leopoldo

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The municipalities that were not represented in the graphs did not have medical production services registered during the research period. These are Baldim, Forestry, Itaguara, Itatiaiuçu, Mario Campos, Mateus Leme, Nova União, Upstream, Manso River, and Taquaraçu de Minas. Together they amount to 110 thousand inhabitants, representing around 2% of the population of MRBH.

As shown in Graph 23, the ratio between the number of points of care and the number of doctors decreases continuously. This portrays the fact that physicians, in general, are attending in fewer places than before, ie, staying in the same place during working time; this in the case of consultations, which are the clipping of this work.

Graph 22 - Ratio of the number of points of service to the number of doctors between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 24 expresses a steady increase in the number of calls, i.e., regardless of distribution, there is more “medical production” each year.

Graph 23 - Total amount of health care between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Although calls are increasing in volume, the places where calls are made have remained at a low rate since 2011, as shown in Figure 25. If the volume of calls increases but the average number of calls per location remains stable, it is possible increasing the number of service locations.

Graph 24 - Average amount of health care services by location between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

A grouping of information focusing on the medical specialty now begins, specifically the number of care locations for each specialty.

The medical specialties depicted in Graph 26 show little variation, except for Acupuncture, which has significant annual growth.

Graph 25 - Number of health care venues by location between 2007 and 2016 in medical specialties: Acupuncture, Allergy and Immunology, Cardiovascular Surgery, Hand Surgery and Head and Neck Surgery at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties reported in Graph 27 show little occurrence, except for Gastroenterology, which had considerable growth, although there was a retraction in 2016.

Graph 26 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Pediatric Surgery, Thoracic Surgery, Coloproctology, Endoscopy and Gastroenterology at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties reported in Graph 28 show little variation in the period.

Graph 27 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Genetics, Geriatrics, Hematology, Homeopathy and Infectious Diseases at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 29 reports growth in the Intensive Care specialty, mainly because this specialty has been in greater demand in recent years, with the growth of Intensive Care Units (ICU) and Intensive Care Centers (ICU).

Graph 28 - Number of health care locations by location between 2007 and 2016 in medical specialties: Occupational Medicine, Physical Medicine, Intensive Care Medicine, Nuclear Medicine and Clinical Neurophysiology at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties depicted in Graph 30 show little variation.

Graph 29 - Number of health care locations per care location between 2007 and 2016 in medical specialties: Angiology, Neurology, Ophthalmology, Orthopedics and Otorhinolaryngology at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties depicted in Graph 31 likewise show little variation.

Graph 30 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Pathology, Clinical Pathology, Pulmonology, Psychiatry and Radiology at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

In Chart 32, it is possible to observe considerable growth in the Medical Clinic's attendance places, of approximately 50%. Possibly due to the growing demand from new clients, and also by the behavioral change of the population, which generally seeks more health services. It should be noted that all these data refer to supplementary private health.

Graph 31 - Number of health care venues by location between 2007 and 2016 in medical specialties: Anesthesiology, Cardiology, General Surgery, Medical Clinic and Dermatology at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties depicted in Graph 33 show little variation.

Graph 32 - Number of health care facilities per care location between 2007 and 2016 in medical specialties: Endocrinology, Gynecology, Pediatrics and Urology at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties depicted in Graph 34 show little variation.

Graph 33 - Number of health care venues by location between 2007 and 2016 in medical specialties: Plastic Surgery, Mastology, Nephrology, Neurosurgery and Rheumatology at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical specialties depicted in Graph 35, in turn, are relatively new specialties, which joined the role of the Federal Council of Medicine (CFM) around 2011 and would naturally have noticeable growth as they did not exist previously.

Graph 34 - Number of health care venues by location between 2007 and 2016 in medical specialties: Cancerology, Family Medicine, Nutrology and Radiotherapy at MRBH

Abbildung in dieser Leseprobe nicht enthaltenSource: Prepared by the author, 2017.

4.1.3 Pediatric Analysis

This study cut the specialty Pediatrics, isolating it due to its uniqueness, by dealing with children.

It is important to report that in 2011, the company incorporated a large health insurance operator, located in Betim. Thus, in addition to the client portfolio, doctors who attended there belonged to this company from which the data were obtained.

Graph 36 shows an almost constant growth in the number of pediatricians, although the growth rate shifted by almost 11% in 2011, as shown in Graph 37. 2011 corresponds to the incorporation as mentioned above. . Its biggest reflexes are noticeable only in the following year, as the process ended in the last quarter of 2011.

Graph 35 - Evolution of the number of pediatric doctors between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 36 - The growth rate of pediatric doctors between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Regarding the number of pediatric points of care, there were consecutive reductions in 2008, 2009, 2010, and 2011. Only in 2012 began a recovery of this variable, when in 2013 the level of 2007 was recovered. Growth was continuous until the last survey year, as shown in Graph 38.

This behavior is contradictory to what occurred with the number of doctors but can be explained by the phenomenon of proportionality between the number of doctors and the number of points of care, shown in Graph 39. It is possible to observe that there is a successive reduction until 2011, maintaining balanced until the last year of the study.

Graph 37 - Evolution of the number of health care points for the pediatric specialty between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 38 - Ratio of the number of points of service to the number of pediatric doctors between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The behavior of the Capital versus Interior relationship follows the general pattern, as can be seen in Charts 40 and 41. In 2007, pediatric service points represented about 20% of the total. Already in 2016, this percentage reaches 29%.

Graph 39 - Comparative evolution of the number of pediatric healthcare points between the capital and the interior, from 2007 to 2016, at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 40 - Relationship between the number of pediatric care points of Capital and Interior, from 2007 to 2016, at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The annual attendance volume grows successively. From 2007 to 2016 there was a growth of over 100%, that is, more than doubled. Probably this fact may be related to population growth as well as the growing number of health insurance beneficiaries occurred in this decade, as can be seen in Graph 42.

Graph 41 - Total number of health appointments in the Pediatrics area between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

In addition to the growth in medical production mass, there was a growth in the average number of calls at each location, as shown in Graph 43. This event can also be observed in the general quantities (Graph 25), noting a general, unassociated behavior. To a particular specialty.

Graph 42 - Average amount of health care provided by Pediatrics by place of care between 2007 and 2016 at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

4.1.4 Basic Specialties Analysis

According to CFM, the specialties considered basic are Medical Clinic, General Surgery, Gynecology, and Pediatrics. Similar to introduced specifically in the Pediatrics specialty, this specialty group gains focus in this session.

The quantitative increase in the number of doctors is equivalent to general and pediatric studies. Since 2007, this category has had a 65% growth in the number of doctors, as shown in Chart 44. Also, the annual growth rate is presented. Similar to what was presented in the other sessions, the impact of the incorporation of the Betim operator is also noted here, as shown in Chart 45.

Graph 43 - Evolution of the number of doctors in basic specialties between 2007 and 2016 at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 44 - Rate of growth of the number of doctors of basic specialties between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Similar to what was observed in the general data, the quantitative occurrence of service points decreased until 2010, resuming growth from 2011, as shown in Chart 46. However, in the general analysis, the beginning of growth occurs only in 2012.

Graph 45 - Evolution of the number of health care points for basic specialties between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The medical relationship versus points of care presented in Graph 47 indicates a balance in this bond. After a reduction by 2011, slight growth or even stability can be observed in subsequent years. This phenomenon is similar to what happens in general and pediatric data.

Graph 46 - Ratio of the number of points of service to the number of doctors of basic specialties, between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The correspondence between the Capital and the Interior follows the general pattern, as can be seen in Charts 48 and 49. In 2007 the points of service of the basic specialties represented approximately 19% of the total. Already in 2016, this percentage reaches 27%. The representativeness of the “Interior” increased by 8 percentage points.

Graph 47 - Comparative evolution of the number of pediatric healthcare points between the capital and the interior, from 2007 to 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Graph 48 - Relationship between the number of service points in the basic specialties in Capital and Interior, from 2007 to 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The volume of care has grown over the years, as expected. This number almost doubled between 2007 and 2016, according to Graph 50. At this moment it is possible to identify the representativeness of pediatrics concerning basic specialties. In 2007, it represented 29%, and in 2016 it now corresponds to 31% of attendance.

Graph 49 - Total amount of health care in basic specialties between 2007 and 2016 at MRBH

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

The positioning of the average attendance is similar to that of Pediatrics, as well as the general, as can be seen in Graph 51.

Graph 50 - Average amount of health care in basic specialties by location between 2007 and 2016 at MRBHAbbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

4.1.5 Geographic Analysis

This chapter is intended to expose the results from a geoGraphal perspective, making progress in the exploration of information, this time using spatial analysis and cartography techniques.

4.1.6 Location

In this section, we will present the cartoGraph views of the results obtained after analyzing the data generated according to the methodology presented.

The metropolitan region of Belo Horizonte was already presented in the “Justification” session; however the purpose here is to show its location in the world, as can be seen in Map 4. It is located in the state of Minas Gerais, around the state capital, whose location is Latitude: -19.8157, Longitude: - 43.9542 (19 ° 48 ′ 57 ″ South, 43 ° 57 ′ 15 ″ West).

Map 4 - Location of the Belo Horizonte Metropolitan Region, 2017

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

4.1.7 Composition

The Belo Horizonte Metropolitan Region consists of 34 municipalities, as can be seen in Map 5.

Map 5 - MRBH Municipalities, 2017

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Map 6 aims to identify municipalities and their geoGraphal area measured in km2. The total area of MRBH is close to 9,500 km2. The average is around 280km2. The map highlights 4 municipalities under 65 km2 and 4 municipalities over 552 km2.

Map 6 - SociodemoGraph classifications (area and population)

Abbildung in dieser Leseprobe nicht enthalten

Still, about Map 6, it also highlights the population of the municipalities. There are 4 municipalities with more than 290,000 inhabitants, all close to each other, including the capital itself. It is also noted that the municipalities with the smallest population are furthest from the capital.

Map 7 shows the demoGraph density variable. Analyzing it, it is possible to verify that the 4 municipalities of higher density (Belo Horizonte, Betim, Contagem, and Nova Lima), are also those that have the largest absolute populations of MRBH.

Regarding Gross Domestic Product (GDP), it is important to highlight that the most populous municipalities have a higher GDP. The exceptions are Ribeirão das Neves, which although has one of the largest populations, has a lower GDP than the others. Also, there is the case of Nova Lima, which does not have many inhabitants; however, it has one of the largest GDP in the region.

Map 8 shows the relationship between the number of inhabitants and the number of points of service. Only 2 municipalities (Belo Horizonte and Nova Lima) have a higher proportion. Besides, it is possible to verify the population representativeness of each of the municipalities. Individually, the interior municipalities have little representation, but together their populations equal those of the capital.

Map 7 - SociodemoGraph classifications (Density and GDP)

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Map 8 - SociodemoGraph classifications (Inhabitants x Point Service and% Population)Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Map 9 - Population growth rate between 2010 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

4.1.8 Distribution

Next, the geoGraphal distribution of the service points will be presented in each of the years under study in this research.

Maps 10, 11, and 12 depict the evolution of care locations year by year, providing a temporal view of information in geoGraph spaces. The first points to the general distribution, the second to the organization of pediatrics and the last to the general specialties.

There is a strong concentration of points around the limits of Belo Horizonte (capital), which confirms the sociodemoGraph information presented in the previous session.

It is possible to identify that some municipalities do not have service points during the ten years of research, such as Baldim, Forestry, Itaguara, Itatiaiuçu, Mateus Leme, Nova União, Rio UP and Rio Manso.

Map 13 presents the results of the Mid-Center calculations for each year across all focuses of study. By observing this map, it is possible to infer a minimum displacement of the middle center over the years in a northwest direction, slightly to the west in the case of pediatrics. This movement is not constant. In some years it even goes back to the East, but when comparing the years 2007 and 2016, the sense is Northwest. This can be evidenced by measuring the distance between the average center of 2007 and 2016, which was around 1.4 km in a region with 9,471 km2.

Maps 14, 15, and 16 show the average center and standard distance in the three views: general, pediatric, and basic specialties. In all three scenarios, year-on-year growth in the standard distance is noted, as well as a slightly mid-west shift from the mid-west. The standard distance, shown on the maps, is the first indication of improvement in distribution over the years, as its radius increases gradually, with a slight retraction in 2013 and 2015, as can be seen in tables 8, 9 and 10. The increased radius in kilometers implies a larger area of ​​distribution of the studied phenomenon.

Table 8 - Standard Distance from General Calls

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Table 9 - Standard Distance from Pediatric Care

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Table 10- Standard Distance from Basic Specialties

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Maps 17, 18, and 19 show the weighted mean center and weighted standard distance in the three views as well: general, pediatrics, and basic specialties. In all three scenarios, year-on-year growth in the standard distance is noted, as well as a slightly mid-west shift from the mid-west. The standard distance, shown on the maps, is the first indication of improvement in distribution over the years, as its radius increases gradually, with retractions in 2015 and 2016, as can be seen in tables 11, 12 and 13. The increase in radius It implies a larger area of coverage of the distribution of the studied phenomenon.

Table 11 - Weighted Standard Distance from General Calls

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Table 12 - Weighted Standard Distance from Pediatric Care

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Table 13 - Weighted Standard Distance from Attendances in Basic Specialties

Abbildung in dieser Leseprobe nicht enthalten

Source: Prepared by the author, 2017.

Map 10 - Distribution of General Service Points between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 11 - Distribution of Pediatric Service Points between 2007 and 2016Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 12 - Distribution of Service Points of Basic Specialties between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 13 - Medium Centers between 2007 and 2016 (General, Basic Specialties, Non-Basic Specialties, and Pediatrics)

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 14 - Overall Standard Distance between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 15 - Standard Distance in Pediatrics between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 16 - Standard Distance in Basic Specialties between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 17 - Overall Weighted Standard Distance between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 18 - Weighted Standard Distance in Pediatrics between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 19 - Standard Distance Weighted on Basic Specialties 2007-2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 20 shows the heat maps of the general distribution of care at MRBH in a comparison between 2007 and 2016. The high granularity of this map in this view allows a broad view of the intensity of care in these two years of study. It is noteworthy to highlight slight deconcentration in 2016 compared to 2007 — besides, a North and West displacement in the region.

Map 20 – 2007 and 2016 General Care Heat MapAbbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017.

Maps 21, 22 and 23 show the heat maps in the three strands of study, the first of the general, the second of pediatrics and the third of the basic ones. These maps were created with a smaller granularity to identify the details more accurately. Thus, it is possible to find a certain level of attendance dispersion in the three outbreaks; however these decentralized occurrences are not significant enough to infer a better distribution.

Map 21 - Heat map of general care between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 22 - Heat Map of Pediatric Care between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

Map 23 - Heat map of attendances of basic specialties between 2007 and 2016

Abbildung in dieser Leseprobe nicht enthalten

Source: Data from MRBH Supplementary Health Operator, 2017. CartoGraph base: IBHE 2016. Prepared by the author, 2017

5 CONCLUSIONS

The present study allowed us to verify the distribution of supplementary private health care in the Metropolitan Region of Belo Horizonte over the last 10 years.

Several techniques were used as described in the methodology section. The fact that this study is quantitative allowed to effectively reach the answer to the research question, combined with the fact that the use of cartoGraph elements, allowed to improve the understanding of the “where” in the research theme.

The work exposed here generated important artifacts for the analysis of information and can be considered an atlas of the geoGraphal distribution of doctors. The diversity of Graph resources offers managers of private health organizations, as well as public managers, a rich and distinguished material to support the strategic decision making of health equipment allocation. This documentary tool allows a better understanding of the dynamics of this distribution over the years.

The distribution of care has a significant concentration in the capital and this does not change significantly over the years under study. Although the municipalities of the interior, over the years, have been gaining ever larger population contingents, reaching even or surpassing (added) the population of the capital, this phenomenon is not reflected in the distribution of points of care. Certainly such a distribution has changed over the years, but the momentum has not reached the necessary balance.

The representativeness of the "interior" vis-à-vis "capital" is in the direction of equilibrium, but not in the short term. The medical ratio versus point of care tends to a balance as well as the average attendance by location. The proportion of female doctors follows a trend in overcoming women compared to the male number.

The use of cartography was the differential in this work, as it allows us to understand the dynamics of care, which is extremely concentrated, but gently directed towards the West. This means that there was a movement of doctors to the west, approaching the counties of Contagem and Betim. Such scenario has not had sudden changes, however this scenario may change in the future, depending on some action of adding new doctors or even care measures directed to the suburban population, such as health centers in the municipalities or even on the expansion of the concept of family doctor. The spatial distribution applied to the obtained data allowed to visualize the current situation and also a retroactive analysis of the behavior of such indicators.

The general objective of this research was achieved, being possible to analyze the distribution of the attendances in the last ten years, using the cartoGraph tools.

The spatial distribution of physicians was identified over the years, as shown by the maps presented.

All studies were weighted, especially in the maps presented, using the average number of calls as a weighting variable.

The results were spatially analyzed, so that spatial statistics such as mean center and standard distance were generated, as well as the maps themselves.

Future studies suggest the creation of geoGraph trend metrics, as well as an analysis of the displacement of the economically active population and also a study among public health facilities in relation to supplementary ones. Finally, a study focused only on the most complex care in the care network would be of great value.

REFERENCES

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115 of 115 pages

Details

Title
Access to Health Care in Brazil. Spatialization of Medical Care in Belo Horizonte
Course
Postgraduate Program in Information Systems and Knowledge Management
Grade
3.0
Author
Year
2018
Pages
115
Catalog Number
V501408
ISBN (Book)
9783346042743
Language
English
Tags
Health Geography. Supplementary Health. Spatial statistics. Spatial Analysis. GeoGraph Distribution of Physicians. Metropolitan Region of Belo Horizonte
Quote paper
Carlos Miguel Freire Silva Viegas (Author), 2018, Access to Health Care in Brazil. Spatialization of Medical Care in Belo Horizonte, Munich, GRIN Verlag, https://www.grin.com/document/501408

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