key: cord-0858742-uot1fqhx
authors: Tanniru, Mohan R.
title: Transforming public health using value lens and extended partner networks
date: 2020-07-04
journal: Learn Health Syst
DOI: 10.1002/lrh2.10234
sha: cf0b423187bf0369b5c3073cd866a8b69480d013
doc_id: 858742
cord_uid: uot1fqhx

INTRODUCTION: Organizational transformations have focused on creating and fulfilling value for customers, leveraging advanced technologies. Transforming public health (PH) faces an interesting challenge. The value created (preventive practices) to fulfill policy makers’ desire to reduce healthcare costs is realized by several external partners with varying goals and is practiced by the public (value in use), which often places low priority on prevention. METHODS: This paper uses value lens to argue that PH transformation strategy must align the goals of all stakeholders involved. This may include allowing partners and the public to contextualize the preventive practices to see the value in near term and as relevant. It also means extending the number of partners PH uses and helping them connect with the public to seek shared alignment in shared goals of value fulfillment and value‐in‐use. RESULTS: Using lessons from Covid‐19 and PH experience with partners in four different sectors: business, healthcare, public and community, the paper illustrates how PH transformation strategy can be implemented going forward. CONCLUSIONS: We conclude the paper with five distinct directions for future research to create and sustain value using the framework of learning health systems.

those of their partners, that is, share in the benefits of revenues generated. Similarly, when hospitals co-create value with patients, they seek to align the patients' goal to self-manage their health and the hospital's goal to provide quality care at reduced costs. Similarly, when hospitals use external partners, they both seek to align their goals of sharing reimbursement dollars and reducing readmission costs. 12 In both business and healthcare, the alignment in goals with partners leads to gaining access to information on value-in-use, so that new value can be created.

Public health (PH) (refers to departments, organizations, agencies, etc.) has a distinct challenge in aligning goals with customers and partners. Creating value by developing practices to prevent the spread of an infection or a disease condition calls for allocating funds by policy makers and investment in behavioral change by the public today, with value-in-use realized later. Similarly, PH uses several media and community partners to fulfill the value, and they as well as PH see valuein-use feedback for their effort from yet a different set of partners (state and federal agencies) later. In other words, PH, its customers, and its partners are all investing in value creation or value fulfillment, with no immediate feedback on their efforts with information on value-in-use. This makes it difficult to seek commitment in aligning goals that today are mostly implicit. This is in fact counter to the use of frequent value cycles (value creation, fulfillment, and value-in-use) needed to create and sustain value, 13 and learning health systems research that advocates continual learning loops of data to knowledge, knowledge to performance and performance to data to tailor personalized care. 14 All these time delays and lack of explicit goal alignment disappear when there is a health emergency such as Covid-19. PH is creating value with goal alignment with the public in preventing the spread of infections and with policy makers by gaining access to needed monetary or staffing resources. It can summon partnerships in supporting value fulfillment with many non-traditional partners, including hospitals, businesses, schools, and community and social organizations, etc.

It is also able to gain feedback from these partners and the public to assess the effectiveness of preventive measures (ie, value-in-use) so they can adjust the value created (new value created). In some cases, it is even allowing partners to tailor the public health practices to suit their context. For example, staying under quarantine, maintaining social distancing, wearing a mask, washing hands, etc. have been adapted by partners based on their situation (eg, allowing knowledge workers to work from home, developing partitions for those who need to work in close quarters, staggering hours to reduce the number of workers in a plant at any given time, etc.).

In summary, PH is able to extend its partner network and allow partners and the population segment with whom they work to customize practices within their context so that they can help fulfill the value and provide value-in-use information for it to create new practices or value quickly, because there is an alignment in the goals of all stakeholders: policy makers, the public, and partners. While such alignment is developing in response to a health emergency, how can PH transform its operations going forward so it can sustain some of this goal alignment and partnership in normal times? Hence, the research question: Can public health build a broader network of partners whose goals are aligned with it as they serve select population segments?

Secondly, can partner engagement in customizing and fulfilling the value created lead to improved surveillance needed to analyze values gaps and create new value cycles?

The paper is organized as follows. The next section looks at prior research on pandemics and the current Covid-19 experience to understand the extended partner network that public health can leverage to support its transformation. The third section provides a strategy to aligns the goals of partners involved to tailor and fulfill the Information from the mortality surveillance system was used to track deaths due to influenza outbreaks, 15 and real time health insurance claims data including outpatient and emergency department visits can provide patient condition information post discharge. 16 Inpatient data was used to capture information on patients' age and the presence of certain comorbidities and co-diagnoses, 17 as well as the breadth and depth of heterosubtypic immunity (ie, the immunity one gains with "seasonal" influenza) among certain population groups. 18 Some of this clinical data is adjusted with other non-clinical information, such as information on travel intensity, 19 types of school closures that vary with grade levels and across regions after an infection outbreak occurs, 20 quality of days or years (QALDs and QALYs) lost in work and school, 21 and global travel characteristics of populations. 22 In summary, surveillance methods used to gather intelligence phase of PH decision process includes both clinical and non-clinical data. This data is generated from several nodes, as shown in Figure 1 .

Diverse models are designed to analyze the data gathered during surveillance to identify factors that have contributed to the viral spread. The viral behavior within a human immune system and its various perturbations is complex, and non-linear dynamic models are often used to determine factors contributing to the viral transmissibility. 23 Other models were used to analyze data from the public: social media interactions to assess the pandemic spread 24 and classification of Twitter messages to understand public trust on the practice message communicated. 25 Models used within the clinical sector included those that analyzed the testing data to improve surveillance accuracy, 26 resource utilization data in hospitals to assess the spread of an outbreak, 27 the number of hospitalizations of children, 28 and the impact of co-morbidity on projected hospital length of stay, time to ventilation, and ventilation time. 29 Other models in public and community sectors were used to assess the impact of community practices in schools and other regional institutions 30 and the role of health inequities 31 on the viral spread. The key for all these models is access to surveillance data in real time from several partner institutions, so that PH can assess value gaps or the effectiveness of its practice interventions.

Viral infections impact populations disproportionately (eg, pregnant women, children, or older populations during prior pandemics such as H1N1, SARS, Ebola, etc.) and can be transmitted differently (eg, exchange of bodily fluids as in HIV/AIDS or airborne and through human contact as in . Therefore, the policy and practice options selected should lead to specific guidance to different population segments based on their susceptibility to get sick such as pregnant women 32 or those with respiratory infectious diseases. 33 The guidance can be tailored to help institutions such as schools decide how to operationalize closures to reduce the intensity of viral spread. 34 In addition, broader regional and national factors as well as community level factors must be considered before practice interventions are chosen for implementation. 35 For example, New York City may have a different exposure to risk based on the density of its population and its movement using public transportation compared to regions like Montana where the population is spread out and use of personal cars for transportation is predominant. In summary, evidence-based community level, assessment 36 is needed to tailor practices before they are implemented.

From the above discussion, each node in Figure 1 is both an input for capturing the data needed for value creation and an output for practice implementation, with an opportunity to tailor the practice to its context. This is key for PH as it looks to learn from its pandemic experience to transform its operations. PH by itself cannot develop customized practices to each partner node. It can communicate the practice and let the partner node tailor this to align with its goals and that of the public it serves. For example, the business node can take the practice information and align it further to meet the business and employee goals by customizing the practice. Businesses may provide the option to employees to work from home, come on different dates, stay at a safe distance when they meet, etc. This is one of the reasons that the nodes in Figure 1 are shown as a double circle, representing both the partner and the population segment it serves. The public node is also shown separately, as some segments of the population are not directly connected with any single partner node. We will return to this in the next section.

Revisiting the research question, PH can rely on a several partners connected to various population segments to help fulfill the practices recommended, if it views the public as a collection of population groups that play various roles and some of these roles directly connect these population groups to specific partners (eg, employers when they work, patients when they go to hospitals, citizens when they see other public services, etc.). This leaves the second question: How will the partner's value creation and fulfillment help with the surveillance F I G U R E 1 Public health extended network needed to analyze gaps and create new value cycles? This is address in the next section.

Service science research argues that in a service driven knowledge economy, organizations need to co-create value propositions with their customers and fulfill these value propositions by leveraging internal resources and the resources of partners. 37 Also, engaging consumers during value-in-use (ie, during consumers' use of the product purchased) can help discover gaps in value, leading to creating the next value cycle. 13 In other words, organizations need to use successive value cycles to align their goals with the goals of their customers.

Similarly, to fulfill the value crated, organizations and partners need to align their goals through shared resources. For PH to leverage its partners in value fulfillment and value-in-use, it needs to seek alignment with these partners. This is discussed in this section. For simplifying the discussion, Figure 2 

Keeping employees healthy by having them engage in preventive practices such as eating healthy food, walking when feasible while at work, and reducing family stress by having day care centers at work facilities are becoming a good business practice to improve employee morale, reduce absenteeism, improve productivity, and reduce healthcare costs. PH has many preventive practices to improve healthy behavior among population segments like the practices discussed above. However, there is limited effort to align the goals of employers and PH, even though there is significant effort in aligning the goals of hospitals, employers, and insurers for obvious reasons such as healthcare cost containment. In fact, the pandemic has highlighted the disadvantages of not sharing information when it came to employees working in meat processing plants, rural farms, and even urban cities where the public must use public transportation to get to their work.

While PH, hospitals, and businesses are not all going to be a part of the same enterprise creating and fulfilling value for employees, what is needed is an alignment in goals so PH can develop practices tailored to address the needs of seniors, women who are pregnant, children and youth, etc. and let businesses who serve these population groups fulfill the value created. For example, businesses that provide products or services to seniors, mothers who are pregnant, customers who use gyms, or schools that service young students can help fulfill the practice intervention and build customer loyalty. Similarly, businesses that employ similar population segments can tailor such practices to improve employee productivity, reduce absenteeism, and improve retention, even if it has no immediate impact on healthcare costs. 

The public sector incudes other public services besides PH, PH agencies/departments in other regions and countries, as well as policy makers. We will look at the first two here.

Public sector services: When the Centers for Disease Control (CDC) 41 developed specific guidelines after the 2009 H1N1 pandemic, it included many PH partners such as state and local public health officials, schools, patients who are supported by community organizations besides hospitals, daycare centers, and public transportation companies. Each of the partners within the government can help fulfill the value created by PH in normal times. For example, agencies that supervise schools that want to improve the quality of lunches served, transport agencies that seek to provide accessibility to seniors, community organizations that seek to address food and home insecurities, etc. can help fulfill value created by PH on eating healthy food to reduce obesity in children, reducing social isolation among seniors, improve infection control using flu shots and immunizations, etc. While some of these occur today, a lack of real time information sharing often contributes to the inability to tailor practices (eg, leveraging influential members of the society to impress upon measles vaccination).

PH agencies: While the long-term ecological and epidemiological dynamics of viral infections globally may follow very simple rules even for highly mobile populations, 23 the spread of viral infections is often dictated by contextual factors associated with the community in which policy makers operate. The key decisions PH policy makers must make during pandemics relate to how large a response to mount, which control/intervention measures to implement, and for whom and when. 42 In addition to historical data gathered from prior pandemics or epidemics at various levels of granularity, real time data that comes from various community and regional nodes is critical for community level response. For example, this data may include confirmed cases, syndromic surveillance, outbreak investigations, serological data, and clinical cases, as well as data for customer surveys and hospitalizations from a regional level and viral surveillance data from around the globe. PH agencies need a shared repository for real time 

Using prior research and experience from recent pandemics, the paper articulates how PH transformation can begin by reaching out to several partners that touch distinct population groups. By seeking alignment of PH goals with partner goals, PH can let the partners support value fulfillment, potentially by tailoring the value created to their specific context. The data gathered in real time from these partners, combined with other aggregated public health data, can then be used for analysis of the value gaps before new value is created. and intangible (eg, lost experience, disruption to work-flow, depression, anxiety, isolation, etc.). Also, risks vary depending on partner-population segment cohesion. If the segment is cohesive and distinct as in people working in meat packing or manufacturing firms, these partners may be given an opportunity to tailor practices to address these trade-offs at their local context. On the other hand, airlines, and population segment that travels are not cohesive, and PH may set the guidelines based on the need for value fulfillment by all that travel. Use of multi-criteria decisionmaking and a mix of quantitative and qualitative decision models may be needed in selecting partners allowed to tailor practices.

• Empower partners and public to fulfill practices. Inverse care law 46 may apply here, as practices may never reach the population segment the partner is trying to reach. This is often attributed to the partner not knowing how to reach the population group they are asked to support or have trust related challenges with the group.

For example, perceptions that the data may be used for surveillance, performance evaluation or assessing penalties, shared with insurers or peers, etc. can lead to distrust. Research is needed on how to incentivize the partners and population groups using incentives or gamification to work together and develop privacy and security protocols to address information sharing.

• Gather information in as close to a real time as feasible from partners on population adherence to practices developed in value fulfillment. Besides addressing the privacy and security issues in sharing some of this information, PH and partners need to recognize that diverse technologies are used by these population groups to share the value-in-use information for analysis. An external third party may be used to reduce distrust and provide the information in anonymized and in aggregate form for partners and PH. Information architectures specific to such data collection 47 or distributed architectures such as blockchain may be explored to support some of this communication and collaboration.

• Analyze data collected from each partner node and consolidate this with other regional and national data to assess health trends or infection spread. Since the timing, accuracy, and security/privacy of information shared can vary for clinical and non-clinical data shared, new approaches are needed to combine this data. There is need for data cleansing and normalization prior to analysis. Advances in data science may be relevant in support of some of this analysis. Some of the data collected here may be contextualized for use in developing policies as well as storing them for future use. 45 • Develop policies and practices to address the spread of infections or improve health conditions. The learning from previous value fulfillment effort should become a part of the shared knowledge for future use by all PH agencies. CDC 41 guidelines post H1N1 is one example of sharing prior learning using a WHO 48 pandemic framework, 49 but how well these are available in real time for today's pandemic is unclear. Also, learning from prior explorations (eg, heuristics, use cases, expert opinions, etc.) developed possibly by autonomous population agents 50 can help PH tailor prior policy or practice options to current context quickly. AI and machine leaning methods as well as intelligent agent technology may be useful here.

In summary, this paper suggests that PH take a broader value creation and fulfillment lens to support its transformation. The breadth seen through such a lens includes the use of multiple partners who align their goals and the population groups they support and the goals of PH to tailor health practices and support their implementation. The broader lens allows gathering of diverse data from these partners and the health conditions of the population groups to assess gaps between value created and value in use (customer adherence) to create new policies/practices. Similarly, the broader lens helps PH to view public as multiple population groups, each needing a more narrowly focused approach to improve their adherence to health behavior and reduce healthcare costs. As stated at the beginning, PH needs to transform citizen's perspective on prevention as personal for their immediate engagement.

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Society for Modeling & Simulation International, CA. How to cite this article: Tanniru MR. Transforming public health using value lens and extended partner networks