Health IT Implications of Accountable Care Organizations

INTRODUCTION

One of the most talked about provisions of the Patient Protection and Affordable Care Act of 2010 is the development of Accountable Care Organizations (ACOs), which “create incentives for health care providers to work together to treat an individual patient across care settings – including doctor’s offices, hospitals, and long-term care facilities” (ACOs: Improving Care Coordination for People with Medicare, 2011). To succeed, an ACO must pay greater attention to prevention and chronic disease management, and information sharing among healthcare providers.

Almost universally, industry experts view health information technology (HIT) as a requirement for the establishment and effective operations of an ACO. Some of the technologies specifically identified as essential for the rise of ACOs include electronic health records (EHRs), data warehouses / Business Intelligence, disease registries, remote monitoring and telemedicine, health information exchanges, and robust health plan systems / actuarial analysis (Enders, Battani, & Zywiak, 2010).

This post will provide an overview of the key components of an Accountable Care Organization, including their organizational and financial structure, and explore how HIT serves as the foundation and the backbone of an ACO. It will briefly describe how each of the technology systems above serve as the ACO plumbing, and how each of these elements can come together to drive informed, high quality and cost-effective care.

BACKGROUND

There are many definitions of what an Accountable Care Organization is. Many have likened ACOs to the mythical unicorn in that although there is common knowledge as to what they should look like, no one has truly seen one (Vesely, 2010). According to the “Joint Principles for Accountable Care Organizations” (2010), a briefing from the nation’s top primary care medical associations, ACOs are defined as:

"A group of physicians, other healthcare professionals, hospitals and other healthcare providers that accept a shared responsibility to deliver a broad set of medical services to a defined set of patients across the age spectrum and who are held accountable for the quality and cost of care provided through alignment of incentives."

ACOs offer a major shift in the way health care is delivered, specifically going away from episodic- and provider-centered care towards patient-managed and outcome-focused health care. The proposed structure for ACOs also changes the financial incentives from that of a volume-over-value model to one of stewardship and “gain sharing” where bonuses or wage increases are linked to better outcomes as opposed to increased profits (Piper, 2010).

The concept of an Accountable Care Organization is not a new one. ACOs share some similarities to Health Maintenance Organizations (HMOs), which were introduced in the 1990’s, particularly the concept of improving health care delivery and provider reimbursement. However, ACOs go many steps beyond HMOs in that instead of allowing the insurance companies to set the standards, ACOs will allow providers to decide on what those standards should be as well as give them the opportunity to evaluate their own work (AHA Research Synthesis Report, 2010). ACOs also encourage collaboration, particularly through health information technology (HIT) resources, allowing timely access to all physicians treating a particular patient thus reducing the possibility of repeated testing and potential medical mistakes.

Some early leading models of Accountable Care Organizations include Geisinger Health System based in Pennsylvania, Advocate Healthcare based in Illinois, and Norton Healthcare based in Kentucky. Some common characteristics among these organizations include tight integration of physicians with hospitals, transparency, advanced clinical and analytical technologies, and a strong community/public health focus.

HEALTH INFORMATION TECHNOLOGY

Health information technology (HIT) is the information plumbing of an ACO. HIT is the enabler of coordination and information flow – by increasing the use of technology, coordination is increased – and its effective use will be critical in order for ACOs to succeed (Enders, Battani, & Zywiak, 2010). In this section, the key HIT components enabling the formation and success of an ACO are described.

Electronic Health Record (EHR)

EHRs, including/along with clinical decision support (CDS), and standards, are foundational technologies for Accountable Care Organizations. Inpatient and ambulatory EHRs are integral to the ACO, particularly because “inpatient, ambulatory, and ancillary care providers [assume] responsibility for the quality and cost of health care for a defined population of ACO members” (Enders, Battani, & Zywiak, 2010) and need access to rich clinical information to effectively manage care and cost. Integration of data between inpatient and ambulatory systems, which has historically been lacking in EHRs, is also critical for the success of ACOs. Integration of clinical data increases the ability for collaboration amongst providers and can aid providers in making informed medical decisions about a patient’s care.

Clinical decision support (CDS) prompts and alerts direct and guide safe and cost effective care and standards and are critical to the effectiveness of ACOs (Enders, Battani, & Zywiak, 2010). Standards, such as evidence based practices or organizational guidelines embedded in the build of the EMR, are also important.

Data Warehouse (DW) / Data Analytics

The aggregation and analysis of information from multiple systems – i.e. EHRs, financial systems, case management systems, and pharmacy systems – helps paint a broader picture of the care delivered, cost and outcomes. The adoption and use of data warehouses (DWs) on the provider side has been slow and is largely limited to academic centers and Integrated Delivery Systems (Finch, Murphy-Barron, & Mirkin, 2010). DWs are expensive and complex to build, and take a lot of “care feeding,” but without one in place ACO success is at risk, given the lack of integrated information to drive business decision-making. Finch, et al. (2010) explains that “for comprehensive risk, an ACO will need a data warehouse and provider profiling system to easily produce up-to-date reports on utilization, cost, physician report cards and comparisons to targets” (as cited in Moyer, R. & Leonardo, P., 2010; and Parke, R. & Fitch, K., 2009).

Business intelligence is the catch all terminology used for the systems and practices of combining/collating and analyzing the data. This is a newer field for providers and one necessary for ACOs. Payers have historically had advanced analytic capabilities, but they’ve been very utilization- and cost-centric. There has been a lot of buzz surrounding business intelligence but it can be challenging to implement these types of solutions within organizations, especially ACOs where there are many “owners” of the data and likely very little data normalization done up front (Enders, Battani, & Zywiak, 2010).

According to Enders, et al. (2010), feedback loops to providers are also very critical to ACOs. Providers still very much want comparative data and data from trusted sources, so timeliness and accuracy of data is crucial to success.

Disease Registry

Another key HIT tool for ACOs are disease registries, which are repositories of patient information surrounding a particular disease or diagnosis. Disease registries are used a lot in ambulatory care settings in order for providers to track and ensure all appropriate care is being delivered to large populations (Metzger, 2004). The challenge with disease registries is that they are not always integrated with EHRs, and if this is the case, another silo of data emerges. Providers like disease registries because they are easy to use and are focused on the provider’s needs, but there is a risk that it will become a “shadow” EHR (Amatayakul, 2003) and that key patient clinical data will not be accessible to others who seek it in the EHR. Another problem associated with disease registries is the risk of multiple disease registries for patients with multiple chronic diseases. This makes it difficult to aggregate the data if it is not known which one is the actual source of truth (Metzger, 2004). Large EHR vendors are starting to incorporate disease registry capabilities into their products making them more available and possibly more widely used.

Health Plan Data / Actuarial Analysis

Health plan data has historically been financially focused. This data will remain very important, but needs to be integrated with clinical data (i.e. Business Intelligence and analytics) to actually provide high value to ACOs in terms of showing cost effectiveness. Actuarial analysis will also be key for ACOs given the need to identify, stratify, and manage high-risk patient populations or sub-populations (Terry, 2011). Health plans recognize the need for greater data interoperability and exchange and in the past year, several large insurers, i.e. Aetna and Ingenix/United Healthcare have purchased data integrators/HIE vendors such as Medicity to give them internal capabilities to integrate data among providers, payers, and third parties (Goedert, 2011). This will be essential to contract and payment modeling in ACOs.

Patient Health Data Across The Continuum

ACOs need to address care beyond the inpatient ambulatory setting and integrate the data from these multiple sites of care, which include long-term care facilities, home health care, and home monitoring. From an IT evolution standpoint, these systems for these areas on the care continuum have not been fully developed or integrated with other systems. This poses challenges in the robustness of their functionality, their adoption and usage to date, and data interoperability (Andrews, 2011).

Telemedicine / Telehealth

Telemedicine / Telehealth can encompass services such as remote monitoring, e-visits, e-consults, etc. that are delivered virtually through technology. Telemedicine and telehealth have been slowly taking root. There has been a lag in adoption of telehealth because of network and technology capability, limited reimbursement (Boukus, Grossman, & O’Malley, 2010), and the “physicalness” of healthcare. However, these things are becoming less of an issue. Patient engagement and interaction via technology are instrumental to ACO success, particularly remote monitoring and data uploading, e-visits, and personal health records.

Health Information Exchanges (HIEs)

HIEs are envisioned as the plumbing of the ACO allowing data to be available to all parties in the ACO and used to drive clinical and financial decision-making. There is a proliferation of HIE planning and development across the country driven by the HITECH Act and merging standards. While many of these HIEs show great promise, sustainability has proven to be challenging. Keys to HIE success are strong governance, a stable funding model, value added services, and robust privacy and security of patient data (Deutsch & Turisco, 2009).

RISKS AND CHALLENGES TO ACOs

While the success of the ACO model and the individual ACO will be determined by many political, financial and competitive forces, technology will be a make or break factor.

One of the technology-centric risks to ACOs includes the high costs associated with acquiring the technology, which can be prohibitive. Adoption is another risk, posing the question of whether the technology will be used once it is purchased. Too often money is spent on technology adoption, but clinical workflow and utilization are factors not taken into consideration (Bowens, Frye, & Jones, 2010).

Integration of systems and data where standards are new or lacking also poses challenges to the success of ACOs. Lack of standards can lead to poor communication among providers, as well as duplication and inconsistency in providing care. Patient data security is another technology-centric risk to ACOs that must be considered. A recent audit conducted by the Department of Health and Human Services Office of the Inspector General (2011) found that “there were no HIT standards that included general IT security controls.” Another consideration is the current digital divide between those who are and those who are not able to afford the necessary technology for ACOs. Smaller hospitals and organizations as well as those with minimal funding, found mostly in rural and inner-city areas, are at a significant disadvantage in meeting the requirements to become an Accountable Care Organization.

CONCLUSION

The ACO “concept” that emerged from the Patient Protection and Affordable Care Act of 2010 will, regardless of the fate of healthcare reform, have a lasting impact on the healthcare industry. Many organizations have embraced a model of “Accountable Care” and view technology as a key facilitator in moving from their current siloed and volume-based practices to organizations focused on communication, collaboration, and value.

There is a rapid evolution of enabling technologies, driven in part by HITECH and Meaningful Use. Moreover, there is a widespread awareness that radical change into “the way we do business” is needed and that technology will be a key driver in helping providers deliver safe and effective care and share clinical information across the continuum.

REFERENCES

1. Accountable Care Organizations-AHA Research Synthesis Report (2010). American Hospital Association Committee on Research. Retrieved from http://www.hret.org/accountable/index.shtml

2. Amatayakul, M. (2003). HIPAA Reins in Shadow Charts, Independent Databases (HIPAA on the Job Series). Journal of AHIMA, 74(9), 16A-C.

3. Andrews, J. (2011). When will LTC get serious about IT? McKnight’s Long Term Care News, 32(1). Retrieved from http://www.mcknights.com/when-will-ltc-get-serious-about-it/article/193346/.

4. Audit of Information Technology Security Included in Health Information Technology Standards. (2011). Department of Health & Human Services Office of Inspector General. Retrieved from http://oig.hhs.gov/oas/reports/other/180930160.pdf

5. Boukus, E.R., Grossman, J.M., & O’Malley, A.S. (2010). Physicians Slow to E-mail Routinely with Patients. Center for Studying Health System Change, 134. Retrieved from http://hschange.org/CONTENT/1156/

6. Bowens, F.M., Frye, P.A., & Jones, W.A. (2010). Health Information Technology: Integration of Clinical Workflow into Meaningful Use of Electronic Health Records. Perspectives in Health Information Management, 1-18.

7. Deutsch, H. & Turisco, F. (2009). Accomplishing EHR/HIE (eHealth): Lessons From Europe. Computer Sciences Corporation. Retrieved from http://www.google.com/url?sa=t&source=web&cd=20&ved=0CGQQFjAJOAo&url=http%3A%2F%2Fncf.uschamber.com%2Fwp-content%2Fuploads%2FCSC_Accomplishing_EHR_HIE_eHealth_Lessons_from_Europe.pdf&rct=j&q=HIE%20strong%20governance&ei=GiHnTZzaOqfXiAKOsYzmCQ&usg=AFQjCNH3tOwCxs5D_6uaXmkB3SXqhiu5pg&sig2=dcLARuUuA3RvM2NyMBxNsg&cad=rja

8. Enders, T., Battani, J., & Zywiak, W. (2010). Health Information Requirements for Accountable Care. Computer Sciences Corporation. Retrieved from www.himss.org/ASP/ContentRedirector.asp?ContentID=75793

9. Finch, K., Murphy-Barron, C., & Mirkin, D. (2010). Nuts and Bolts of ACO Financial and Operational Success: Calculating and Managing to Actuarial Utilization Targets. Becker’s Hospital Review. Retrieved from http://www.beckershospitalreview.com/hospital-physician-relationships/nuts-and-bolts-of-aco-financial-and-operational-success-calculating-and-managing-to-actuarial-utilization-targets.html

10. Goedert, J. (2011). HIT Vendors Scramble for Positioning. Health Data Management. Retrieved from http://www.healthdatamanagement.com/issues/19_6/health-information-technology-vendor-acquisitions-42542-1.html?zkPrintable=true.

11. HealthCare.gov. Accountable Care Organizations: Improving Care Coordination for People with Medicare. (2011). Retrieved from http://www.healthcare.gov/news/factsheets/accountablecare03312011a.html

12. Metzger, J. (2004). Using Computerized Registries in Chronic Disease Care. First Consulting Group. Retrieved from http://www.chcf.org/resources/download.aspx?id=%7b8643F100-6E09-4E4F-9CD6-33AF8474A7BE%7d

13. Moyer, R. & Leonardo, P. (2010). Building an accountable care information system. Milliman Marketing Brief. Retrieved from http://www.milliman.com/expertise/healthcare/products-tools/medinsight/pdfs/building-an-accountable-care.pdf

14. Parke, R. & Fitch, K. (2009). Accountable care organizations: The new provider model? Milliman insight. Retrieved from http://insight.milliman.com/article.php?cntid=6056

15. Piper, K. (2010). The New Accountable Care Organizations and Medicare Gain-Sharing Program. American Health & Drug Benefits, 3(4), 261–262.

16. Terry, K. (2011). Health IT: The Glue for Accountable Care Organizations. Healthcare Informatics. Retrieved from http://www.healthcare-informatics.com/ME2/dirmod.asp?sid=&nm=&type=Publishing&mod=Publications%3A%3AArticle&mid=8F3A7027421841978F18BE895F87F791&tier=4&id=6E241A666E484896B82B43D8B209F200.

17. Vesely, R. (2010). Tests were inconclusive–California's experiment with ACOs raises questions about whether they'll save money. Modern Healthcare, 40(44), 6–7.

Submitted by Reesha Lopez