Business Finance - Management APA assignment

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1 https://pubmed.ncbi.nlm.nih.… 67%

Web resultsNational Institutes of Health (NIH) |

(.gov)https://pubmed.ncbi.nlm.nih.govThe impact of chronic conditions on

emergency department length of stay

2 https://www.cliffsnotes.com/s… 33%

Web resultsCliffsNoteshttps://www.cliffsnotes.comAssignment 7 Case Study Analysis

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Content

Leveraging Technology to Address SDOH Challenges

Introduction

This report has been made for Mr. Alastair Bell, Chief Executive Of�cer,

Boston Medical Center (BMC). The issue considered in this report involves

how, as a safety net hospital in an urban setting, BMC can utilize disruptive

technology in a manner that addresses, in a fundamental way, the Social

Determinants of Health (SDOH) factors so crucial to its population, while at

the same time driving �nancial sustainability at the organization (Craig et

al., 2021). This report will de�ne SDOH, discuss SDOH in conjunction with

technology in a business setting, determine which SDOH factors are crucial

to an organization like BMC, and offer a plan on how a disruptive

technology can be factored into a viable business model.

Background of the Problem

BMC is ensconced in an intimate healthcare ecosystem, treating only part

of its patients’ healthcare. Most of their patients derive from a population

beset by deep-rooted socioeconomic adversities like poverty,

homelessness, lack of access to nutritious food, and lack of transportation.

These represent Social Determinants Of Health, namely: “the circumstances

in which people are born, live, grow, and everything in between.” The social

determinants in�uence health and healthcare, often resulting 1 . in adverse

health outcomes, higher rates of chronic diseases, and subsequently

unnecessary use of the Emergency Department, as well as Inpatient

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services (Gibbings & Wickramasinghe, 2021). BMC thus �nds itself facing

two challenges: its social mission to treat its underserved population, as

well as its unsustainable revenue streams because of its acute social

incentives’ costs.

Key Factors Supporting Recommendations

1 . There are many important considerations underlying the strategic

application of disruptive technology. Firstly, there is a clear �nancial

imperative and opportunity afforded by the movement towards value and

Medicaid 1115 waivers. Secondly, there is the application of leverage and

scalability afforded by technology that can integrate many more patients

simultaneously and automatically track data as opposed to individually

tracking and addressing patients' social needs manually (Sensmeier, 2020).

Thirdly, there is the fundamental importance of engaging and empowering

patients to manage their conditions on their own outside the four walls of

BMC hospitals because mobile technology can undoubtedly engage and

connect patients to support services and aids. Finally, there is a clear private

and public imperative to address SDOH problems that cannot and should

not be solved by BMC or other single entities; rather, there is a clear use and

application for technology platforms to integrate various community

organizations and services to form a single support ecosystem that BMC

can leverage and manage (Abbott et al., 2024).

Recommendations

BMC recommends exploring the possibility of designing and deploying a

well-integrated and patient-centric technology tool speci�cally made to

evaluate, treat, and lessen SDOH impact. This tool will function as an

integrated channel. It will be composed of three essential revolutionary

elements: To begin with, there will be an AI-based SDOH screening and risk

strati�cation mechanism placed right inside an electronic health record so

that the algorithm can locate patients with social needs through the

identi�cation process (He et al., 2023). Then, there will be a very considerate,

"closed-loop", patient relationship-building and engagement tool that is

very logically connected, linking patients to veri�ed social resources and, at

the same time, evaluating the levels of patient engagement.

Goal(s)

Its main aim is to minimize avoidable hospitalizations and visits to the

emergency department for high-risk patients by 15% in the third year when

their social needs are addressed in advance. Its secondary objectives are to

improve patient scores for food security/availability and housing

security/availability by 25%, patient engagement in preventive care by 20%,

and the development of new revenue streams based on success in risk

contracts (Craig et al., 2021).

Action Items

First, no more than six months into the project, form a cross-functional

‘Health Equity Technology’ team, with a team lead for each of the following

areas: clinical, IT, community partnerships, and �nance. Second, develop

and test the AI-driven patient screener and referral tool in two patient

populations with high needs: pediatric asthma sufferers and congestive

heart failure patients in nine months of project development (Gibbings &

Wickramasinghe, 2021). Third, develop and establish community

partnerships with at least �ve core providers of community resources in the

�rst year of development and include their offerings in the referral system.

Fourth, develop the patient-facing app in the patient advisory council in 12

months.

Action Plans

The action plan will include vendor development or internal development

of the platform’s core, based on guidance provided by the cross-functional

team. Phase II of the pilot will include training members of the clinical staff

in the new process, implementing the tool in the EHR, and determining

success metrics. Developing partnerships will include guidance from the

Community Partnerships team, who will manage all negotiations,

development of agreements, and validation of resource availability

(Sensmeier, 2020). Finally, the development of the mobile app will include

agile development methodology with feedback from patients.

2 . Metrics to Support Learning so That Continuous Improvement Is

Possible

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Continuous improvement will be made based on a known set of metrics.

Process metrics will measure the percentage of patients screened who are

identi�ed as needing SDOH and the completion rates of these referrals.

Outcomes will measure changes to the HbA1c values of diabetic patients or

the number of hospital visits related to asthma symptoms compared to

social service use. Cost metrics will measure the cost to care compared to

the control group (Abbott et al., 2024). Patient outcome metrics will come

from the app. Quarterly review of these metrics is required by the

leadership group to improve the functionality of the app and provide a

return on investment to continue to fund the project.

References

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