Showing Health Information Value in a Community Network (North Carolina)

Project Final Report (PDF, 569.07 KB) Disclaimer

Project Details - Ended

Project Categories

Summary:

This three-year project assessed the costs and benefits of health information technology (health IT) in an established community-wide network of academic, private and public health care facilities created to share clinical information for the purpose of population-based care management of over 17,000 Medicaid beneficiaries in Durham County, North Carolina. The area of interest for this project was the impact of information-driven interventions on care quality, patient safety and health care costs across the diverse stakeholders participating in this collaborative partnership.

In order to asses health IT value rigorously in the context of a production information system that is under continual development, we conducted a randomized controlled trial. Specifically, we randomly assign patients by family unit to either a control group or to an intervention group in which they initially receive one of 3 information-driven interventions. The interventions included clinical alerts sent to care providers, performance feedback reports presented to clinic managers, and care reminders sent directly to patients. The content of the interventions addressed "concerning" events (e.g., an emergency room encounter for asthma) and care deficiencies (e.g., delinquency on biannual mammogram) identified from the composite set of clinical data in our information system.

To assess the benefits and burdens of the interventions, combinations of the 3 interventions were sequentially introduced into the study groups over the course of the project. The analysis compared groups receiving various combinations of interventions as well as those receiving no interventions. At baseline and at six-month intervals throughout the course of the study, we measured emergency department encounter rates, hospitalization rates, HEDIS scores, missed appointment rates, glycated hemoglobin levels in diabetics, and patient satisfaction. Our assessment looked at the societal value of health IT as well as the value for individual stakeholders including patients, providers, payers, purchasers and policy makers. From these measures, we assessed the costs and benefits of this community-wide effort to promote interoperability of clinical data exchange in order to increase the understanding of health IT value in a community setting.

Showing Health Information Value in a Community Network - 2008

Summary Highlights

  • Principal Investigator: 
  • Organization: 
  • Funding Mechanism: 
    RFA: HS04-012: Demonstrating the Value of Health Information Technology (THQIT)
  • Grant Number: 
    R01 HS 015057
  • Project Period: 
    09/04 – 08/08, Including No-Cost Extension
  • AHRQ Funding Amount: 
    $1,487,072
  • PDF Version: 
    (PDF, 64.49 KB)


Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to support patient-centered care, the coordination of care across transitions in care settings, and the use of electronic exchange of health information to improve quality of care.

Business Goal: Knowledge Creation

Summary: Health information technology (IT) is a promising strategy for improving the quality of health care. However, little is known of the specific benefits of health IT to share information in a community setting using a population health management care model. The purpose of this project was to: 1) increase knowledge and understanding regarding the value of health IT at clinical, organizational, and financial levels within a community partnership focusing on care management of a vulnerable population, 2) determine its value to various stakeholders, and, 3) demonstrate a generalizable approach to health IT in a community setting that can be replicated at other sites. A study population of 20,108 Medicaid beneficiaries in Durham, North Carolina, was randomly assigned by family unit to receive either health IT-augmented or usual care. For the intervention group, sentinel health events were detected using a standards-based clinical decision support tool that conducted routine surveillance on a centralized regional health information exchange database. Events were grouped as:

  • Events of commission (i.e., reflecting an activity done by a patient) that were the target of Phase 1 of the study
  • Events of omission (i.e., reflecting activities neglected by a patient such as preventive health services), that were the focus of Phase 2
  • Events self-reported by patients through questionnaires on health risk and barriers-to-care-access completed by patients on free-standing public kiosks

Because fewer than 150 patient-reported events were detected out of all of the possible question responses from the four kiosks in Durham County, these findings were not included in the analysis. Notifications were sent to patients’ assigned care managers through weekly e-mails, to patients’ assigned clinical homes via quarterly feedback reports, and to patients directly through weekly postal letters. The impact of the three notification methods on emergency care use, hospitalizations, and care quality was compared to usual care and to each other using regression model techniques. Patient satisfaction and quality of life were assessed using the Computer Assessment of Healthcare Providers and Systems (CAHPS) and the EuroQoL survey instruments, respectively. Provider opinions were assessed using validated survey instruments for assessing usability.

Specific Aims

  • Evaluate from a societal perspective the clinical, organizational, and financial value of health IT in a community network. (Achieved)
  • Evaluate the value of health IT in a community network from the perspective of specific stakeholder groups, including patients, providers, hospitals, payers, and purchasers. ((Ongoing*)
  • Disseminate the design of the community-based health information network, the techniques of the intervention approaches, and the results of the evaluation to interested stakeholders. (Ongoing*)

2008 Activities: Data for the primary and secondary outcomes were obtained from claims data from the North Carolina Department of Health and Human Services. Analyses were delayed at least 6 months after the completion of each study phase to ensure that the claims dataset was complete and stable. As a consequence of these delays, preliminary analyses have not been performed for all phases. After further validation and subanalyses, the results from the subsequent phases will be submitted for peer-reviewed publication.

Impact and Findings: The primary finding from this investigation is that weekly e-mail notices sent to care managers regarding sentinel health events—a diagnosis for an individual that may indicate a broader need for preventive care—can lower emergency department (ED) use for low-severity issues. These notifications are well received by care managers and are reported to enhance productivity. In contrast, feedback reports sent quarterly to clinic managers did not impact ED use or hospitalizations, nor did letters sent to patients.

The net effect of the intervention was to decrease ED use and inpatient reimbursements (for ED and hospital care) for patients randomized to the group whose care managers received weekly e-mail notifications about sentinel events. There were no hospital effects for patients in the two other intervention groups. There was an increase in outpatient costs, but these were for mental health services that were not associated with the study interventions. The cost changes observed in this study were associated with reductions in copayments for study patients randomized to care manager-notice intervention, and with increases in payer reimbursements for patients randomized to receive patient letters. The net results on stakeholder groups are that patients may get more appropriate and perhaps higher quality care; providers may see patients in more appropriate settings and feel that they are delivering better care; hospitals (and their EDs) may save money by handling fewer Medicaid cases; and payers and purchasers experience no benefits or detriments because there were no net changes in total costs.

CAHPS-Medicaid patient surveys were completed by 146 adults and on behalf of 174 children by a parent or guardian. There were no statistically significant differences except that adult respondents in the control group indicated a greater need for specialists relative to the intervention group. The EuroQol quality-of-life survey was completed by 143 adults. When compared with the combined intervention groups, the control group had higher scores for pain/discomfort and for anxiety/depression. Several valuable lessons were learned through the development, implementation, and operational support of this population health management system. In the area of system development, resolving political issues related to the exchange of clinical information and identifying resources to implement the data exchange are often more challenging and time consuming than the technical aspects of information exchange. However, once the exchanged information was in use for proactive care management, clinical sites began to offer their information to the health information exchange so that they could reap the benefits of the proactive care notices.

Selected Outputs

Eisenstein EL, Anstrom KJ, Macri JM, et al. Assessing the potential economic value of health information technology interventions. AMIA Annu Symp Proc 2005;221-5.

Eisenstein EL, Lobach DF, Montgomery P, et al. Evaluating implementation fidelity in health information technology interventions. AMIA Annu Symp Proc 2007;211-5.

Eisenstein EL, Ortiz M, Anstrom KJ, et al. Assessment of the quality of medical information technology economic evaluations: room for improvement. AMIA Annu Symp Proc 2006;234-8.

Kawamoto K, Lobach DF. Design, implementation, use, and preliminary evaluation of SEBASTIAN, a standards-based Web service for clinical decision support. AMIA Annu Symp Proc 2005;380-4.

Lobach DF, Kawamoto K, Anstrom KJ, et al. Proactive population health management in the context of a regional health information exchange using standards-based decision support. AMIA Annu Symp Proc 2007;473-7.

Lobach DF, Silvey G, Willis J, et al. Coupling direct collection of health risk information from patients through kiosks with decision support for proactive care management. AMIA Annu Symp Proc 2008;429-33.

Grantee’s Most Recent Self-Reported Status (as of August 2008):Data collection and some preliminary analyses are complete, including all analysis of Phase 1. Further conclusions will be disseminated through peer-reviewed publication and other mechanisms as they are developed.

Milestones: Progress is mostly on track.

Budget: Spending is roughly on target.

* This aim was not completed prior to scheduled conclusion of the grant (August, 2008) however, research will continue through other funding sources.

Showing Health Information Value in a Community Network - Final Report

Citation:
Lobach D. Showing Health Information Value in a Community Network - Final Report. (Prepared by Duke University under Grant No. R01 HS015057). Rockville, MD: Agency for Healthcare Research and Quality, 2008. (PDF, 569.07 KB)

The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
Principal Investigator: 
Document Type: 
Medical Condition: 
This project does not have any related resource.
This project does not have any related survey.
This project does not have any related project spotlight.
This project does not have any related survey.

AHRQ-Funded Study Explores the Value of Health Information to Communities

David F. Lobach, M.D., Ph.D.What is the value of health information to a community?

Potentially, a great deal, in terms of both health care quality and costs.  The trick, though, is not to share too much too fast, because information overload can undermine the bestof intentions.

That's what David F. Lobach, M.D., Ph.D., of the Division of Clinical Informatics in the Department of Community and Family Medicine at Duke University Medical Center in Durham, N.C., is learning through a research project funded by the Agency for Healthcare Research and Quality (AHRQ).

Early lessons from the ongoing, 3-year project -- which involves providing clinical alerts, feedback reports, and reminders to clinicians and patients -- indicate that sometimes less is more when it comes to sharing health information technology (health IT).

Lobach's study, which involves 18,000 active Medicaid beneficiaries in Durham County, N.C., has already identified one important lesson:  Beware of information overload.  Lobach and his colleagues have found that health care providers can absorb only so much new information at once.  At the same time, the proprietary database used for the study was put under tremendous strain, and had to be migrated to a more robust database platform.

Lobach's project generates a lot of information, through three interventions:

  • Clinical alerts sent via email to care providers, informing them of specific actions or follow-up that a patient may need -- whether it's time for a woman to have a Pap smear or whether a patient has had multiple emergency room visits in the past 3 months.
  • Performance feedback reports to clinic managers on individual patients' care and follow-up needs.  The reports also address "concerning" events, such as an emergency room visit by an asthma patient, and care deficiencies, such as delinquency on a biannual mammogram.
  • Reminder letters mailed to patients, alerting them they are due for a check-up or cholesterol, blood-sugar, or other types of preventive care or disease monitoring tests.

The project's database contains administrative, clinical, care management, and communication data pulled from a variety of sources, including eight primary care clinics, two area hospitals and their emergency departments, and the state Medicaid program.  These data are used to generate the three interventions that are being tested.

Each patient in the study has been assigned to a home clinic so that the study researchers could determine which physicians and care managers should receive which patient reports.  Initially, each of the 18,000 study patients was randomized into one of three intervention groups:  alert, feedback report, or patient reminder; plus three groups that did not receive an intervention for the study's first phase, to provide a comparison.  Under the original study plan, each group would receive new information from an additional intervention every six months.

But that design proved difficult to implement.

First, clinicians were concerned that they would become bombarded with information that they didn't know how to use effectively.   Second, the volume of data required to generate the interventions overwhelmed the project database.  The core system database had to be migrated to a more robust database management system, requiring additional, planned time for the project.

As a result, the researchers redesigned the study in mid-stream -- essentially slowing it down and simplifying it so that providers could adjust and learn how to make the best use of their new information without being overwhelmed.

Lobach and his team decided to decrease the content of the initial interventions by focusing on the detection of health events "committed" by a patient, such as an emergency department visit.  During a second phase, health issues pertaining to aspects of care "omitted" from a patient's care management , such as missing a biennial mammogram, were added.  In addition, the first phase of the study was extended from six months to nine to allow more time for the interventions to be accepted and to have measurable impact.

To make up for time delays related to the database migration, Lobach and his colleagues collapsed the three comparison groups into one.  Consequently, the project phase in which clinicians were to receive only two interventions was dropped, and arrangements were made for clinicians, clinics, and patients to progress from receiving one intervention to receiving three interventions.

The researchers are reviewing a wide range of outcomes, including emergency department and hospital use; care quality as measured by HEDIS scores for preventive services and chronic disease management; care coordination; costs and revenues; and patient and provider satisfaction.

But Lobach says the researchers are already starting to see some impact from the interventions on the care management teams.  "Once the clinicians get used to the information, it becomes a driving force for finding patients with problems and improving quality," he says.

Each week, the care management teams receive email messages with a secure link to their clinical alerts reports.  "They use that report as a work list to figure out who to contact that week," Lobach says.  For example, frequent emergency department users are a red flag.

Lobach acknowledges that the project has been very labor-intensive:  from developing strong partnerships with participating hospitals and clinics, to cleaning and maintaining the data that are collected, to transforming data because of different data codes and standards used by providers.

But the potential payoff is more than academic.  Lobach hopes that this project will not only help quantify the value of health information to communities, but also shed light on the unique contributions of different methods for providing health information.  In that way, the project could provide valuableinsights for the development and implementation of future community-based health information exchanges.

This project does not have any related emerging lesson.