SPI Analysis

Case Overview:

This network consists of the city patients with obra social (OS) who also were in upper income classes. In this research study, this accounts for an sample of ten interviews across three sites: Tandil, Mar del Plata, and Bahía Blanca. This network gives insights into the how these patients conceptualize the good and negative aspects of their care experiences.

Signal Landscape:

As noted in the TSCM section, the smaller sample size implies a lighter relational pull than in larger matrices, so interface signals need to be read with this in mind. As with all matrices, barriers outweigh enablers at the component level, so there is a meaningful burden on the system. Within the relational term, interfaces lean enabler-signaled, indicating the way elements connect tend to help the system. The topology term is reasonably quite small, given the lower sample size on this graph. Moving to the TSCM +/-, the local relational densities are modest compared to the overall. Thus, net barriers burden the system, improvements can flow through enablers to improve the system, though the limited interfaces and topology limit these from being system-wide waves.

In the CSCM metrics, the shortlist gives us a good sense of where we can target interventions balancing lower node complexity with higher relational scores. Leading items tend to align within a few key groups. These include going to private and out of town facilities, financial frictions with insurance issues, and capacity issues influencing a lack of trust in local facilities.

Overall, from these signals, systems administrators should anticipate seeking targeted wins rather than broad cascades. Focused improvements on financial pathways, trimming wait times, and increasing trust in local options are some overall emphases. Because interfaces lean enabler-signed while C3 is low, well-aimed operational moves should be felt by this group, but cascading waves will be limited.

Node-Level Synthesis:

For City, OS, Upper, routing and speed of care sit at the center of patient choice. When local care looks to take to long or there are uncertainties in scheduling, going to Buenos Aires or other regional cities* or shifting to out of pocket paid care become preferred routes for faster care (*this is most prominent in discussion in Tandil, where patients discussed going to either La Plata or Mar del Plata). Further, when stakes for care feel high, many families in this subgroup default to going to Buenos Aires to see ‘super-specialists,’ even as far away as Bahía Blanca. As a number of patients described in examples, they have access to a “back specialist,” but in Buenos Aires, they have access to a “L3 lumbar specialist.” This access to top-tier professionals, deep set trust in Buenos Aires, and the financial means to travel means that patients in this group see this as a viable approach to seeking healthcare services. These nodes sit low on interface quintiles, matching how ingrained some behaviors have become. Administrators should understand this cultural uncurrent conditioning care choices.

Financial pressures run alongside routing. The creep of increasing bonos and uncovered services has decreased the utility of patients’ OS insurance. Increasing medications and services are denied, leaving patients stuck with bills that were covered just months before. This required some patients to change care providers or dedicate more financial resources towards healthcare. Due to their position in upper income classes, these costs could often be covered, but large surgeries, chronic medications, and other expensive medical services could still destabilize normal care routines. Coverage friction from worsening insurance commonly manifested to administrative uncertainty then paying out of pocket.

Capacity issues and long wait times were still a feature in city OS care, though to a lesser extent than in other settings. Wait times still heavily influenced the ingrained use of services in other locations and decreased trust in local care capacity. Due to public wait times, most city OS patients sought to avoid using the public system, favoring faster care at clinics, paying out of pocket outside of network, or going to other cities for improved care and insurance functionality. Many viewed the public system as overburdened already and unable to take further increased patient loads. Some patients tied this to the lack of auxiliary professionals, where private and clinic doctors act in all roles from receptionist to negotiating insurance contracts in addition to clinical care. This extenuates insurance and reimbursement issues for patients, while also decreasing care time and increasing burnout for providers.

A large comparative node was present in both the centrality and clustering of the network, Private versus Public. This is an interesting node as it gives us direct insights into care choice behavior. It sits between triangulated nodes, such as “distrust in local care” and “BA or city complexity trust,” while being amplified by “boca a boca” when friends signal positive and negative experiences. These triangular relationships, where “misdiagnosis,” “poor quality care,” and “lack of trust in the public system” help to reconstruct patterns of experience and provide insights for why the private system is so much more trusted than the private system in this network. The the public/private comparison, public appointment waits and long waits for care are influential nodes, though they are difficult to intervene directly on. The private system is not free from barriers, however. Paying out of pocket, bonos, worsening insurance and high costs also degrade the private system’s reliability.

Good care experience counterweights the financial and routing barriers. Patients discussed simple things local providers did that increased trust and anchored them in town for primary care at a minimum: being listened to, clean facilities, and continuity with care teams. Personalized or relationship-based care was a key facet in quality care alongside holistic care and continuity. These directly related to the “staying local for care” node pointing to the importance of quality care to stop leaks to other locales. Administrators should understand the critical role that these play in retaining patients and protect appointment times, strive for continuity in teams, and facilitate the system to be seen as trustworthy.

Key Take Aways and Intervention Opportunities:

Patients in this insurance and social class do not often use the public system except for vaccinations or emergencies. Many utilize local clinical services but travel to Buenos Aires is also a relatively common practice. This choice is motivated by higher trust and specialist availability. While being in upper income groups, they are not fully insulated from the worsening insurance market and general economy. These changes have put a greater financial strain on patients, changing some behaviors and use to decrease out of pocket expenses. Perceived and experienced long wait times in public facilities stabilize these patients use of private care options. Trust and, particularly, a lack of trust in the public system also condition this behavior, with word-of-mouth amplifying both trust and lack of trust signals in social groups. The structure of the network lends itself to targeted interventions to both reduce and capitalize on system characteristics, but the structure does not lend itself to broad sweeping impacts from any one change.

For interventions, administrators can look towards a handful of bundled areas, where bundled implantation can compound wins. A key difficulty of this subsystem is that OS is not controlled or sometimes even administered locally and there could be hundreds of OS plans present in a given city. Nonetheless, as shown in some localities in the Province of Buenos Aires, public-private partnerships are possible and help to centralize some aspects of private insurance markets to improve administrability. Within the OS system, helping clinics and single providers negotiate OS service contracts will likely push more patients to these providers by alleviating surprise and large out of pocket fees. In the same vein, maintaining an up-to-date database of specialists and insurance alignment can help better direct patients to in-network providers, reducing public system or travel reliance to keep patients local. Providers should seek to make competence and professionalism visible through clean facilities, stability in care teams, and an emphasis on relational acquisition and retention.