Universal healthcare: key behavioural factors affecting providers’ and recipients’ value ...

Int. J. Behavioural and Healthcare Research, Vol. 3, No. 1, 2012 25

Copyright © 2012 Inderscience Enterprises Ltd.

Universal healthcare: key behavioural factors affecting providers’ and recipients’ value propositions: a structural causal model of the Puerto Rico experience

Valerie Quiñones-Avila* International Service Systems Engineering Research Lab, ISSER, University of Puerto Rico at Mayaguez, MSC 308 Suite 112, 100 Grand BLVD Paseos, San Juan, 00926-4262, Puerto Rico E-mail: [email protected] *Corresponding author

Alexandra Medina-Borja International Service Systems Engineering Research Lab, ISSER, Industrial Engineering Department, University of Puerto Rico at Mayaguez, II-205 Industrial Engineering Building, Mayaguez, PR 00680, Puerto Rico E-mail: [email protected]

Abstract: In 1993, Puerto Rico became a pioneer amongst the USA and its territories for instituting a public health insurance funded by the state and provided by private insurance companies. This health reform plan was aimed at providing coverage particularly to the medically indigent sector of society and ensuring universal access to healthcare. However, today this system is still struggling with sustaining the goals that originated it. Thus, the purpose of this study is to understand how universal access affects physicians’ and patients’ attitudes, in turn affecting the effectiveness of health reform implementation. A causal model was created to depict the structural form of the physician and patient value system influenced by different actors as a result of the implementation of the Government Health Reform from 1993–2010 in Puerto Rico.

Keywords: causal model; healthcare systems engineering; service effectiveness; qualitative research; behavioural factors; Puerto Rico.

Reference to this paper should be made as follows: Quiñones-Avila, V. and Medina-Borja, A. (2012) ‘Universal healthcare: key behavioural factors affecting providers’ and recipients’ value propositions: a structural causal model of the Puerto Rico experience’, Int. J. Behavioural and Healthcare Research, Vol. 3, No. 1, pp.25–45.

Biographical notes: Valerie Quiñones-Avila is an Industrial Engineering graduate from the University of Puerto Rico at Mayaguez. Her previous research work under Dr. Medina-Borja in the International Service Systems Engineering Research Lab, ISSER, involves a research study on inter-cultural service encounters with call canters. She also worked as a summer

26 V. Quiñones-Avila and A. Medina-Borja

undergraduate research student at Dr. P. Brennan’s Health System’s Lab at the University of Wisconsin-Madison, where she took a patient-focus approach for evaluating non-use of a consumer health information technology.

Alexandra Medina-Borja earned her PhD and Master’s from the Grado Department of Industrial and Systems Engineering at Virginia Tech and her undergraduate degree in Production Engineering from the Federal University of Sao Carlos in Sao Paulo, Brazil. She has concentrated her research efforts in areas related to the effective design and analysis of service delivery systems. In 2006, she co-founded the International Service Systems Engineering Research Lab (ISSER) at the University of Puerto Rico-Mayaguez. She won the IE Distinguished Faculty Award in 2007 and 2008 and the prestigious Goodeve Medal from the British Operational Research Society in 2008.

1 Introduction

The public healthcare system of the Government of Puerto Rico dates as far back to the beginning of the island’s status as a Commonwealth of the United States in 1952. During the 1950s, health services were provided exclusively by the local government (Garcia-Ariz et al., 2010). However, as the Commonwealth experienced economic growth, a private health sector grew alongside the public sector (Hulme and Rios, 1998). A new health insurance system was developed in which premiums were paid, either by federal programmes or private capital, for the provision of health services by contracted providers (PAHO, 2007).

Until 1993, general claims of inequality and discrimination of health services between the public and private sectors, disparity in distribution of resources, as well as the excessive increase in government expenditures in health services worked as catalysts for a transformation in Puerto Rico. Through the privatisation of health services by contracting private health insurance companies, combined with the leasing of obsolete public hospital facilities to private corporations, elimination of direct subsidies to publicly operated health clinics, and the use of federal funds, the Commonwealth was able to implement the Government Health Insurance Plan (GHIP) in 1993 (Gibson, 2009; PAHO, 2007; Ramírez-García, 2008; Vanderbilt Centre for Better Health, 2007). This would be the island’s most influencing healthcare reform for the next seventeen years. The government no longer would be the main provider of health services, but rather would contract with private companies to provide services to the poor and uninsured (Commission for Evaluation of the Health System of the Commonwealth of Puerto Rico, 2005; Torres and Alegría, 2010). Puerto Rico became a pioneer amongst the USA and its territories for instituting a health reform with an emphasis on primary care, providing access to health services to all the population, facilitating the integration of all levels of health delivery, improving efficiency and equality of health service delivery, and providing a coverage that would be publicly funded but provided by private services.

Puerto Rico’s current model for health service delivery is a product of the transformation that began with the Government Health Reform (GHR) in 1993 and has culminated in a managed care model. This new model has turned private almost the

Universal healthcare 27

totality of the government’s health service sector. Although this process resulted in a system that is mostly privatised, the responsibility of monitoring the population’s health still resides in the Department of Health, as the assigned agency for these purposes for the Commonwealth of Puerto Rico. Also, 18 years after the implementation, the Commonwealth is still struggling with the same economical and service access problems as it was facing previously. The GHIP was aimed at responding to an urgent need to fix a system that was failing the population by neglecting access to the medically indigent. Ironically, the non-insured sector has continued to increase over the years, escalating to approximately 8% of the population (2005), indicating that the universal access to healthcare is not being completely achieved by the reform implementation. Although studies from 2005 to 2009 have been performed to evaluate the health system’s successes and shortcomings, none of them has considered the causality in value propositions of healthcare provider and recipients influenced by the implementation of a GHR trying to achieve universal access to healthcare.

2 Research objective

The research objective of this study is to understand how universal access to healthcare affects physicians’ and patients’ attitudes, as well as causality for the different factors influencing their value propositions. Behavioural factors are key components in the evaluation of service delivery systems, such as in measuring quality, efficiency, interactions, and outcomes. The uniqueness of this study relies in its empirical approach to examine how a behavioural factors, such as satisfaction, is affected by different actors, which in turn can influence the success of healthcare reform implementation.

This study is aimed at creating a causal framework for further research based on both quantitative and qualitative data collection methods. This framework includes the structural form of a value system of both healthcare providers and recipients when faced with a GHR aimed at providing universal access to healthcare. Thus, this study aims to answer the following research questions:

• Is patient satisfaction influenced by different levels of universal access to healthcare, such as doctor/patient relationship, access to medical services, availability of medical services, ease of access to tangibles and financial protection?

• Does the type of health insurance (private, public, or none) matter with respect to:

• neglecting medical service

• overall evaluation of the health system

• access to medical services

• frequency of medical assistance.

• What levels of universal access to healthcare influence physician satisfaction?

• Do these value systems (physicians’ and patients’) converge?


3 Mixed methodology

The first step taken to build the causal model was to identify the variables for the analysis and decide on how to measure them. We chose doctors as the healthcare providers and patients as the healthcare recipients. The study was divided into two phases:

1 survey development and structural equation modelling (SEM) for the patient value system

2 interview and qualitative analysis for the doctor value system.

Behavioural factors are key components in the evaluation of service delivery systems because perceptions have a crucial role for service recipient’s evaluation of the service. A survey was created consisting of 33 questions on direct evaluation of patients’ experiences with the health services received since the GHIP implementation, from 1993–2010. The survey measured patient satisfaction and dissatisfaction with the quality of the health services received. Since the main dependent variable, patient satisfaction, was measured in a five-point Likert scale, we wanted to see how the selected factors (representing universal access to healthcare) interact to produce each of the five levels of measured satisfaction (from extremely dissatisfied to extremely satisfied). Ultimately, we did not want to necessarily model patients’ individual reactions to items in the survey, but instead we wanted to model the interactions of patient satisfaction as a latent concept when influenced by access to a universal healthcare.

Predictive methodologies, such as bivariate correlations, factor and reliability analysis, and decision trees using chi-square automatic interaction detection (CHAID) were first used in order to validate survey consistency and extract significant variable relationships (i.e., whether a relationship exists and the direction of the relationship). However, even when the existence of the relationship is known, identification itself does not provide enough information to determine how the variables included in the survey interact to affect patient satisfaction. For such reason, this exploratory method was then used as a basis to feed the equations to the causal model using SEM. A more inclusive modelling behaviour was accomplished by using SEM in order to establish and quantify complex dependencies amongst variables in a causal framework (Medina-Borja and Pasupathy, 2007). Using SEM, we could calculate the contribution to patient satisfaction of each one of its dimensions and then come up with a mathematical formula that relates, not survey items or relations, but the concepts of universal access to care with satisfaction.

In order to integrate the physician value propositions into the causal framework, we were able to interview doctors on their experiences with the success and shortcomings of the GHIP in Puerto Rico. A qualitative analysis was used to identify similarities and differences between the answers to the open-ended questions. This method was consequently employed for identifying and proposing the latent variables of universal access to care that influence physician satisfaction. The latent variables were then included in a conceptual model for understanding how universal access to healthcare influences doctors’ and patients’ satisfaction. The interviews and statistical analysis of survey results has helped us elicit key satisfiers and dissatisfiers, hurdles and enablers of healthcare reform implementation in order to depict a causal model for further research.


4 Patient survey

4.1 Data collection

The survey was administered to 100 patients in the Río Piedras Medical Centre. This is the largest medical centre in Puerto Rico and receives patients from all parts of the island, regardless of their insurance plans, and in many occasions the most severe cases. There was no success in administering the survey to patients in Independent Practitioner Associations (IPAs) and private hospitals, because no authorisation from their administrations was received. Thus, the convenient sample taken from the Rio Piedras Medical Centre cannot be extrapolated to represent the whole Puerto Rican population, but it is a group within the population. The captive audience consisted of people that were waiting in line for a medical service and agreed to participate in the study. As this is an exploratory study, this convenient sample was considered appropriate. From the 100 patients surveyed, 48% had the GHIP, 51% had private health insurance, and 1% did not have any kind of health insurance. This is consistent with the proportions of insurance types in Puerto Rico (approximately 38% public, 54% private, and 8% uninsured) (Gibson, 2009; Vanderbilt Centre for Better Health, 2007).

4.2 Data analysis

4.2.1 Factor and reliability analyses

A factor analysis was used to identify the abstract concepts, known as latent variables, which could explain the pattern of correlations within a set of observed variables (survey questions). Afterwards, a reliability analysis was performed for each resulting construct in order to demonstrate that the pertaining observed data would consistently reflect the construct it was measuring. Internal consistency reliability was chosen for this study, since it is an estimation based on the correlations between the variables compromising the construct (Field, 2005). This enabled us to validate consistency of the results and have a degree of assurance for naming each construct. The bivariate correlations, factor and reliability analysis were useful to test hypothesis about the latent variables underlying the different sets of observed variables. We were able to identify constructs that explained different levels of patient value propositions with universal access to healthcare.

Figure 1 represents the resulting constructs from the factor and reliability analyses. We have included the names of each construct, each pertaining Cronbach alpha from the reliability analysis, and the set of observed variables. The KMO and Bartlett’s Test indicated that the overall measure of sampling adequacy for this set of variables was 0.801, which exceeds the minimum requirement of 0.50 for overall MSA. Also, a p-value of < 0.05 indicated that the model from the factor analysis was significant. Originally, the cumulative proportion of variance criteria indicated that a total of seven components from the factor analysis were needed to satisfy the criterion of explaining 76% of the total variance. After evaluating these constructs with the reliability analysis, and eliminating variables to increase the pertaining logic and Cronbach alpha, we were left with five constructs and a set of variables that did not belong to any construct, as demonstrated above. The observed variables within these five constructs and the last two variables in Figure 1 were measured using a five-point Likert scale of patient satisfaction (ranging from extremely dissatisfied to extremely satisfied).


Figure 1 Resulting constructs from factor and reliability analyses


The main target for subsequent analyses was patient satisfaction in regards to different levels of universal access to healthcare, which was represented by the constructs of relationship with doctor, access to medical services, availability of medical services, ease of access to tangibles, and financial protection under insurer. We also used additional questions in order to study if the type of health insurance the patient has would matter with respect to neglecting medical service, overall evaluation of the health system, access to medical services, and frequency of medical assistance.

4.2.2 Bivariate correlations and decision trees

The questions pertaining to the Additional Variables Column in Figure 1 were used to evaluate if the patient’s type of health insurance would matter with respect to having been denied of a medical service, overall evaluation of the health system, access to medical services, and frequency of medical assistance. Bivariate correlations were used to explore the inter-correlations among variables while decision trees were used to identify the most important predictors of the target variable. The exhaustive CHAID algorithm was selected to create the decision trees. This algorithm explores data while building profiles with respect to a desired outcome. It does so by selecting a set of predictors and their interactions that optimally predict the dependent measure (Medina and Pasupathy, 2007). The statistical software package SPSS™ was used for both techniques. The significant results would then be used as a basis for depicting the causal model and testing it using SEM.

The patient’s type of health insurance was classified into three groups: private insurance (paid by employer, out of pocket, Medicare HMO’s), public insurance (GHIP), or none. As demonstrated in Table 1, this variable resulted in a negative correlation with age, overall evaluation of the health system, and evaluation of access to health services if the GHR did not exist. The negative correlation between health insurance type and age represents that the older the patient, the more likely was he/she to have a private health insurance. This makes sense, since private plans such as Medicare and Medicare HMO’s are targeted towards an older population ( > 65 years). Table 1 Bivariate correlation matrix for type of health insurance

Age

If you had received medical service(s) before the GHR, please evaluate

the change…

If GHR did not exist, I would

have access to...

Correlation coefficient

–.260* –0.278** –0.763**

Sig. (two-tailed) 0.011 0.007 0.000

Big classification of insurance type

N 96 94 94

Notes: **Correlation is significant at the 0.01 level (two-tailed). *Correlation is significant at the 0.05 level (two-tailed).

The negative correlation (–0.278) between the type of health insurance and the overall evaluation of the health system indicates that those with the GHIP or no medical insurance were more likely to evaluate the change of the Puerto Rico health system as worse after the GHR implementation. Those with private insurance were more likely to evaluate the change as better. The negative correlation (–.0763) between health insurance


type and evaluation of access to health services if the GHR did not exist indicates that those with the GHIP were more likely to perceive they would have access to some or none of the currently available health services if the GHR did not exist while those with private health insurance were more likely to perceive that they would still have access to all of the currently available health services if the GHR did not exist.

In other words, despite those patients that had the GHIP would tend to have a low overall evaluation of the health system, they would still perceive the GHR as a high necessity for access to health services. This might be because without it they would tend to perceive they would lose access to some or all services. However, one may hypothesise that those that perceive a worsening of health system after the GHR implementation perhaps would perceive better access to health services without it. Those patients that had private plans would tend to perceive the health system as being slightly better than others and considered that they would have access to health services even if the GHR did not exist. Again, one might have expected that perhaps those with private health insurance would have perceived the change in the health system as worse due to the fact that all services have to be shared between those with private and government plans, thus restricting the availability of services whose access level was once completely divided before the GHR. Perhaps, this finding could be furthered explained by a common perception that with or without a GHR, there will always be access to healthcare because health services are a necessity of the population.

Figure 2 Decision tree (see online version for colours)


Figure 2 demonstrates the result from the decision tree exploration using exhaustive CHAID algorithm. The most significant predictors for their perception of access are represented as insurance type, satisfaction in regards to physician’s time dedicated to the patient’s visit, and overall evaluation of the service received. If the patient had the GHIP, felt neutral or less about the physician’s time dedicated to the medical appointment, and dissatisfied or less with the overall evaluation of the medical service received, then the patient would have an 83% probability of perceiving he or she would have access to some but not all of the currently available services if the GHR would not exist. For those who had a private health insurance, they would have a 98% likelihood of perceiving access to all of the currently available health services regardless of their answers to other questions. This further demonstrates the gap in perceptions of the different types of health insurance. Basically we used CHAID to elicit those factors that were better predictors of the patient’s perception of access.

4.2.3 Structural equation modelling

In order to depict a causal model that includes the structural form of a value system influenced by the behaviour of both health providers and recipients, SEM was used with the statistical software package AMOS™. SEM is a methodology used to model interactions and non-linearities amongst multiple latent independents measured by multiple observed variables (Medina-Borja and Pasupathy, 2007). A causal model based on theory is first proposed and then tested to determine how well it fits the data. Several proposed models can be compared against each other and based on the goodness-of-fit measures, the best model is chosen.

The hypothesised causal loop incorporates the latent variables and their respective indicators, which were derived from the factor and reliability analysis. The directions of the interactions were based on the previous results described by the correlations and decision tree. That is, if we were to combine the same type of statements describing the relationship of patient satisfaction with universal access to healthcare expressed in the previous section (4.2.b.) we would conceive the hypothesised model in Figure 3.

For our theoretical model, we wanted to find out if patient satisfaction could be approximated by a linear combination of value propositions with access to medical services, access to tangibles, availability of medical services, doctor-patient relationship, financial protection under the insurance plan, type of health insurance, evaluation of access to medical services if the GHR did not exist, overall evaluation of the health system, having been denied access to medical services, and frequency of medical assistance. Each variable has an error term associated with it and is explicitly modelled in SEM to capture the measurement error.

Our initial hypothesised model did not run properly, due to the large amounts of constructs and ambiguity specification of covariance. However, an advantage that SEM has is that it allows the researcher to explore variations to the model and see which seems to be more appropriate. Thus, we explored different alternative models by inputting all possible variance and covariance between the latent variables and the target in order to select the most significant model. The final model resulted in Figure 4. Each single headed arrow represents regression weights and the double headed lines indicate the correlations among the variables (Arbuckle and Worthke, 1995). Tables 2 and 3 show the equations for the resulting causal framework demonstrated in Figure 4.


Figure 3 Hypothesised causal diagram for patient satisfaction


Figure 4 SEM output: causal model for patient satisfaction

The results demonstrate that our main constructs: relationship with doctor, access to medical services, access to tangibles and financial protection under the insurer, are correlated amongst each other (correlations ranging from 0.463 to 0.727). The highest correlation (0.727) is between availability of medical services and the doctor-patient relationship. In other words, the causal model depicting the structural form of a value system of the patient, represented by patient satisfaction, is in fact being influenced by universal access to health services through a GHR implementation. The major components of this system are the satisfaction in regards to the constructs previously discussed which are also correlated among each other.


Table 2 Standardised regression estimates (single headed lines)

Relationship Equation (standardised regression estimates)

Access to medical services

0.945 * access to medical care + 0.907 * access to primary care + 0.791 * access to auxiliary services + 0.729 * access to mental service + 0.226 * waiting time in primary care doctor’s office

Access to tangibles

0.957 * ease of obtaining necessary medications + 0.929 * ease of obtaining prescriptions + 0.756 * ease of obtaining referrals + 0.338 * having been neglected or denied of a medical service due to inability of payment

Financial protection

0.917 * protection against excessive or unnecessary medical costs + 0.850 * protection against unnecessary medical treatments + 0.813 * received medical care without mayor financial problems

Type of medical insurance

–0.310 * evaluation of change in health system after the GHIP implementation – 0.736 * evaluation of access to medical services if GHIP did not exist

Age 0.230 * frequency of medical assistance

Relationship with doctor

0.896 * overall evaluation of the service received + 0.869 * politeness, respect, and consideration + 0.863 * time dedicated to the visit + 0.862 * attention + 0.854 * receptive attitude and willingness to help you + 0.838 * technical competence and clinical skills + 0.835 * follow-up with the same doctor + 0.705 * access to health care information + 0.687 * waiting time for an appointment + 0.468 * waiting time in primary care doctor’s office

Availability of medical services

–0.145 * evaluation of access to medical services if the GHIP did not exist + 0.752 * convenience of office hours + 0.907 * ease of choosing primary care doctor + 0.846 * number of primary care doctors to choose from + 0.724 * ease of contact

Table 3 Correlations (double-headed lines)

Correlations Estimate

Access to medical services ↔ access to tangibles 0.631

Access to tangibles ↔ finance 0.463

Access to medical services ↔ finance 0.440

Availability of medical services ↔ relationship with doctor 0.727

Access to medical services ↔ relationship with doctor 0.684

Availability of medical services ↔ finance 0.552

Availability of medical services ↔ access to medical services 0.623

Access to tangibles ↔ relationship with doctor 0.612

Availability of medical services ↔ access to tangibles 0.590

Finance ↔ relationship with doctor 0.561

Satisfaction with waiting time in the doctor’s office is being influenced by the satisfaction with both the relationship with the doctor and with access to medical services. This means that those who were satisfied with their doctor-patient relationship and with the level of access to medical services, were more likely to be


satisfied with the waiting time in the primary care doctor’s office. In other words, no matter how long they wait in line, patients will be more likely to be satisfied with the waiting if they are satisfied with both the doctor-patient relationship and access to medical services.

The same applies vice versa; patients will be more likely to be dissatisfied with the waiting in time, if they are dissatisfied with the doctor-patient relationship and with the level of access to medical services. Thus, satisfaction with the waiting time in primary care doctor’s office is not measured by patients’ perception of the actual time they waited, but as a variable that is being influenced by other variables. This could have a cultural component that we have not measured as people in the Caribbean tend to have a more relaxed perception of time.

The positive relationship between access to tangibles and having been denied a medical service indicates that those who were satisfied with their access to medical prescriptions, medications, and referrals were more likely to not have been denied of a medical service. Since the same applies vice versa, perhaps those that were dissatisfied with their access to tangibles had also been denied of a medical service before.

The type of health insurance influences the evaluation of the change in health system after the GHR implementation and the evaluation of access to medical services if the GHR did not exist. For those survey respondents with private health insurance, the negative regression weights indicate that they evaluate universal access as a positive impact on the health system, but seem to also consider that they would always have access to medical services even if the GHR did not exist. The latter can be explained by perhaps that as long as private insurance exists, and they have the means to pay it (either by their own means, or qualifying for Medicare HMO’s, or paid by the employer) these patients perceive that access to medical services will always be available for them.

On the other hand, those with the GHR as their medical insurance are more likely to evaluate the current health system as worse than the previous one before the GHR, yet consider they would have access to only some or even none of the currently available medical services if the GHR did not exist. In other words, even though the medical indigent patients are dissatisfied with the change in access to health services brought upon by the GHIP, they are likely to still consider universal access as important because without it they perceive they would have access to only some or none of the currently available medical services. This phenomenon could be further explained with the inference that perhaps this sector agrees with and needs the universal access to medical services, but tend to be dissatisfied with the way it has been implemented in the island.

Evaluation of access to medical services if the GHR did not exist is also being influenced by availability of medical services. The negative regression weight indicates that those who were satisfied with availability of medical services were more likely to perceive they would not have access to medical services if the GHR did not exist, thus implying the importance perceived on the GHR.

Age was directly related to frequency of looking for medical assistance, indicating that the older patients were more likely to have a higher frequency of use of medical services. Satisfaction with transportation for those who did not have a car to get to the medical appointments and gender did not result in a significant relationship with any other variable. Perhaps satisfaction with transportation did not result in any significant relationship with any other variable because most of the patients had their own transportation, and thus, could not answer this question because it did not apply for them.


5 Interviews with doctors

The causal model in Figure 4 depicts the important variables from the patient standpoint, and highlights the importance of the physician in the whole scenario. The patient relationship with the physician is one of crucial importance, yet physician’s practices regarding time dedicated to each patient and waiting time for appointments have been perceived as deteriorating in the island. To have the complete picture of the patient-physician system we performed a qualitative analysis.

We present the results of interviews with five physicians that witnessed the move to a universal healthcare in Puerto Rico and currently have their medical practices. The doctors were asked about their frustrations and successes with the provision of medical services under the GHIP, their perspective on the capitation system, their experiences with programmes of health promotion and illness prevention, and their perspective on the non-insured sector of the population.

Under the Puerto Rico health system, primary care physicians with private offices have the choice of either engaging into the capitation system and providing services to all types of patients (those with private plans, GHIP, or no insurance) or providing services to only patients who have private health insurance. Under the capitation system, primary care doctors are assigned a fixed amount of payment per month, which is determined by the Puerto Rico Health Insurance Administration for the potential population of patients. When the primary doctor refers a patient to a specialist, orders a medicine or laboratory tests, the costs of these services are debited to the assigned amount and subtracted from the amount that the primary care doctor will receive. Interviews were made to five doctors from different backgrounds: one board member from the College of Doctors and Surgeons of Puerto Rico, one primary care doctor from a correctional facility, one primary care doctor and medical director of a Federal Qualified Health Care Centre, one primary care doctor from an IPA in Rio Piedras, Puerto Rico, and one paediatrician from an IPA in Rio Piedras, Puerto Rico.

6 Results from interviews with physicians

Table 4 summarises the questions asked to each of the doctors and the concepts answered. The first two doctors do not give services to patients under the GHIP, while the other three are part of IPAs and do give services to patients under the GHIP. The first doctor does not attend patients with GHIP because of the perception that under capitation, patient care becomes a cost to the primary care doctor, rather than the primary goal. The second doctor does not provide services to patients because of the nature of the place where that person works in: a correctional facility. Correctional Health provides medical services funded directly by the government, without having insurers as intermediaries. The primary doctors working in correctional facilities do not receive payment through capitation, rather they have fixed salaries. Although two of the doctors did not provide services to patients with GHIP, while the other three did, all of them had similar and consistent perceptions on most of the questions regarding the attempt for universal healthcare access with the implementation of the GHIP. The following presents an explanation for the concepts present in the previous table:


Table 4 Qualitative analysis: physician interviews

Type

of d

octo

r W

hy d

o yo

u no

t ac

cept

the

GH

IP?

Frus

trat

ions

with

the

prov

isio

n of

med

ical

se

rvic

es u

nder

the

GH

IP?

Succ

esse

s with

the

prov

isio

n of

m

edic

al se

rvic

es

unde

r the

GH

IP?

Dis

cuss

you

r per

spec

tive

on th

e ca

pita

tion

syst

em.

Hav

e yo

u ha

d an

y pr

oble

ms?

Wha

t has

bee

n yo

ur

expe

rienc

e w

ith h

ealth

pr

omot

ion

and

dise

ase

prev

entio

n pr

ogra

mm

es?

Wha

t is y

our

pers

pect

ive

on w

hy

ther

e is

still

a g

roup

of

non-

insu

red

peop

le?

Col

lege

of

Doc

tors

and

Su

rgeo

ns o

f PR

Und

er th

is sy

stem

, the

pr

ovis

ion

of m

edic

al

serv

ice

to th

e pa

tient

be

com

es a

cos

t to

the

doct

or. T

his i

s unf

air,

sinc

e pa

tient

car

e sh

ould

be

the

phys

icia

n’s p

rimar

y go

al, r

athe

r tha

n a

cost.

Cap

itatio

n, ri

sk

dist

ribut

ion,

eth

ical

di

lem

mas

, Med

icai

re c

ap,

insu

ffic

ient

fund

ing,

lack

of

mon

itorin

g IP

As a

nd

insu

rers

R

isk

dist

ribut

ion,

eth

ical

pr

oble

ms,

insu

ffic

ient

fu

ndin

g

Posi

tive

impa

ct in

pub

lic

heal

th, p

reve

ntiv

e m

edic

ine

shou

ld b

e th

e co

re o

f hea

lth re

form

GH

IP e

valu

ates

in

com

e, d

ual e

ligib

le

Cor

rect

iona

l H

ealth

C

orre

ctio

nal H

ealth

doe

s no

t use

GH

IP, t

he

gove

rnm

ent i

s res

pons

ible

fo

r pro

vidi

ng th

e se

rvic

es

dire

ctly

to th

e pr

ison

ers,

rath

er th

an h

avin

g in

sure

rs

as in

term

edia

ries.

Unf

air p

rofit

and

risk

di

strib

utio

n, M

edic

aire

ca

p

Orig

inal

idea

was

go

od: s

uppl

y a

heal

th in

sura

nce

to

thos

e th

at n

eede

d it

the

mos

t, G

HIP

is

the

mos

t com

plet

e pl

an, c

over

s ev

eryt

hing

Ethi

cal p

robl

ems,

de

lay

in re

ferr

als,

unfa

ir as

sign

men

t of p

opul

atio

n to

prim

ary

care

doc

tors

Goo

d N

on-in

sure

d:

min

imum

inco

me,

pr

oper

ties,

cann

ot

affo

rd p

rivat

e pl

ans

IPA

– c

omm

unity

he

alth

cen

tre

Ec

onom

ical

rest

rictio

ns,

capi

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1 Frustrations with the provision of medical services under the GHIP: • Unfair risk distribution and profits between primary care doctors and insurers –

The way risk transfer works in the island was the following way: primary care doctors are assigned a fixed amount of payment per month, which is determined by ASES by the potential population of patients. This amount is about $20 per patient per month and is funded by Federal Medicaid (2007). When the primary doctor refers a patient to a specialist, orders a medicine or laboratory tests, the costs of these services are debited to the assigned amount and subtracted from the amount that the primary care doctor will receive. Thus, the primary doctor that gives more care is the one who receives less payment. Having insurers as intermediaries for the provision of health services, the risk distribution is settled by ASES and the insurer according to the population demographics and health status. The risk transfer was managed under the GHIP from 1993–2010 by shifting 100% financial responsibility of external services such as pharmacy, emergency, hospitalisation, gynaecology, paediatrics, family and internal medicine to the primary care doctor. Risk transfer improperly penalises primary care physicians by imposing on them financial risk for services provided by other providers to beneficiaries registered with their primary care centres, while insurers are not affected by the government’s inability to cover the beneficiaries medical costs (Ramirez-Garcia, 2008). With the new GHR in Puerto Rico, called My Health, which was effective by the end of 2010, the risk transfer has been redistributed as pharmacy – 100% for the insurer, emergency – 50% primary care doctor and 50% insurer. Hospitalisation and the rest of the external services are still being imposed 100% on the primary care doctor. Although this government initiative is a beginning step to share the risk between the doctor and the insurer, all the interviewed doctors agreed that this risk transfer is not enough, since for example emergency cots and hospitalisation costs are still very high, and in many cases the risk redistribution has not been implemented completely. Also, having insurers as intermediaries has brought upon an antagonist relationship between the doctor and the patient, due to the limitation of resources. There have been a lot of internal problems between the insurers and the primary doctors, such as errors in bills and administrative responsibilities. All of the interviewed doctors agreed that there are few or even none audits to account for the inefficiencies brought by the insurers.

• Economic restrictions – These includes insurer limitations when providing medicines, treatments, referrals, and prescriptions; all of which bring about rationing of services.

• Ethical dilemmas brought by capitation – Specialists and external services such as dentistry, labs, radiology, are not funded by capitation, but rather by “fee for service”. This unequal form of payments between primary care doctors and external services along with the financial risk imposed on the primary care doctor have lead ethical dilemmas of denying needed services and even delaying clinically necessary tests.

• Inaccessibility of specialists brought upon fee for service charges.


• Lack of services for health promotion and illness prevention – Most of the doctors agreed that there have been very few or even none incentives for health promotion and illness preventions. One of the consequences has been the overcrowded emergency rooms of unnecessary patient visits.

• Medicaid cap: All of the doctors compared healthcare funding in PR vs. in the USA. Due to the cap of Medicaid in Puerto Rico, the federal government contributes about $20 per low-income beneficiary per month, while federal Medicaid support in the USA is approximately $330 per participant per month. As a result, numerous issues in the quality of healthcare delivery have emerged over the years, like infrastructure problems, number of workforce reducing over the years, eligibility criteria being more restrictive than in other states, and rationing of services.

2 Success with the provision of medical services under the GHIP • Coverage – All of the doctors agreed that the GHIP is the most complete health

plan for its beneficiaries, sometimes even better than many private plans. They also expressed the necessity of this plan since the medical indigent population comprises almost half of the island’s population.

• Primary care doctor as gatekeeper – This system requires the physician to maximise his/her potential. The primary care doctor is considered the gatekeeper of the health system because the medical indigent patient chooses a primary doctor that determines if the patient’s condition needs the referral to a specialist, diagnostic tests, and/or medicines. The primary care doctor is challenged to be educated and keep up with medical advances to provide the best possible medical service at less cost. Also, by having a ‘gatekeeper’ many unnecessary treatments and referrals are avoided. Therefore, the primary care doctor integrates health services by functioning as the gatekeeper of the health system.

3 Discuss your perspective on the capitation system. Have you had any problems or difficulties? What difficulties you believe that this will bring to the success of the reform? • All of the doctors agreed on the difficulties that capitation brings on the success

of the GHR, which are risk distribution, insufficient funding, less payment to the primary care physician vs. the increased profits gained from insurers. They also agreed on an unfair assignment of population to primary care doctors, brought upon by the capitation. That is, depending on the population that the primary care doctor is assigned, there will be patients that do not have mayor medical complications and thus, the capitation amount is retained almost completely by the primary care doctor as the payment for their service. However, in many cases, patients have medical complications and incur in additional medical costs that take up all capitation amount, which is frequently not enough. Thus, in many cases, the primary care doctor is being left with no payment from the service to the medically indigent patient. This brings about the ethical dilemmas previously discussed.

4 What has been your experience with the programmes of health promotion and disease prevention with the GHIP?


Two of the doctors agreed on the lack of health promotion and disease prevention programmes, as well as insufficient funding for screening tests. Two doctors expressed the positive impact these programmes have had in the public health, since public health has improved in terms of the cases of polio, tuberculosis, tetanus, encephalitis and vaccines. Curiously, doctors that worked in IPAs were dissatisfied with these programmes.

5 What is your perspective on why is there still a group of non-insured people?

All the doctors agreed that the non-insured population in Puerto Rico is characterised by the following economical limitations: • minimum income and properties disqualifies them from being eligible for the

GHIP Plan, yet this population does not have the economical capacity of paying a private health insurance

• do not have a minimum of five years of residency in Puerto Rico, which is a common case for people from other countries, like those immigrants coming from the Dominican Republic.

One of the doctors also expressed that there are people who have the GHIP as their insurance and also have private insurance plans, indicating that the government distribution of health insurance is not always consistent or fair.

7 Conclusions

The causal model created with the combination of techniques such as factor and reliability analysis, bivariate correlations, decision trees, and structure equation modelling depicts a structural form of the patient value system influenced by different actors as a result of the implementation of the GHR from 1993–2010 in Puerto Rico. Major findings resulted in that universal access to healthcare affects patient value propositions in terms of relationship with doctor, access to medical services and tangibles, and financial protection under the insurer. Satisfaction with these variables also influences value propositions with other variables as well. For example, satisfaction with waiting time in the doctor’s office is also being influenced by the satisfaction with both the doctor-patient relationship and access to medical services. Additional relationships resulted between type of health insurance, evaluation of the change in access to medical services brought by the GHIP, and the evaluation of access to medical services if the GHIP did not exist. This latter finding is parallel to doctors’ value propositions. It can be concluded that health providers and beneficiaries of GHIP may be dissatisfied with the implementation; yet recognise the importance and benefits of the concept of a universal healthcare.

Figure 5 depicts the conceptual model that includes the constructs and causal arrows that were hypothesised as being the links between variables where both value systems converge. The latent variables for the physician satisfaction were chosen from the pilot interview experiences. We hypothesise that these variables influence doctors into making difficult decisions when dealing with patient care, thus affecting access to services for patients. Furthermore, physician satisfaction could influence the doctor-patient relationship, which in turn is correlated with access to medical services and influences patient satisfaction.


Figure 5 Conceptual model: patient and physician value system


Our findings are useful to advance fundamental knowledge about factors influencing value propositions in regards to the effectiveness of universal access from both the healthcare provider’ and healthcare recipients’ point of view. Just as in the case of the 1993 Puerto Rico GHR, President Obama’s recent federal plan for healthcare in the USA is aimed at responding to an urgent need of fixing a system that has been failing the population by neglecting access to the medically indigent. Many parallels and lessons could be drawn from the early implementation of the Puerto Rico GHR in order to contribute to a successful universal access to healthcare in the USA. This parallel is relevant as many insurance companies operate equally in the island as in the mainland; billing, medical practices, and procedures are virtually the same. The key success factors elicited in the causal model provide a basis for further research on developing a causal framework for effective health reform implementation aimed at universal access to healthcare.

8 Future work

We have elicited factors to be considered from both patients’ and physicians’ points of view in healthcare reform. Our intent is to propose a framework for future study of what constitutes health reform success from both points of view and from the intersection where the patient value system (the factors that matter to the patient) converge with the physician’s (the factors that affect their satisfaction, involvement and perceptions). To the best of our knowledge, this had not been done before for any region of the USA and we hope it initiates research in this direction.

After doing statistical analysis to validate the physician value system, augmenting the sample size, and creating a survey to elicit doctor’s perceptions that could be statistically verified, we plan to work with the causal model with the purpose of finding the parameters for the relationships between variables that would allow us to develop a simulation with system dynamics. The objective of the simulation is to hypothesise on structural changes in this complex system, testing them in order to find optimal levels for key variables through experimentation. Other complex systems paradigms could also be used to simulate behavioural factors of the interaction between patients and doctors in a bottom up approach, such as with complex adaptive systems technologies, mainly agent-based modelling, To do that we would need go back to the patients and ask them what interactions with the doctors would make them re-consider their selection with the insurance constraints and to the doctors what would it take for them to make changes in the way their services are provided.

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