Effectiveness of Electronic Health Record-Based Interventions for Improving Follow-Up in Primary Care

January 12, 2016 updated by: Hardeep, Baylor College of Medicine

Diagnostic delays in ambulatory care are often due to breakdowns of related care processes. Electronic systems can improve follow-up and reduce delays by detecting missed appointments or incomplete procedures so that patients are called back to conduct timely investigations when appropriate. To achieve high standards of patient safety in cancer diagnosis, the investigators not only need to use information technology appropriately but also improve the processes, policies, and procedures of monitoring, communication, and coordination of care.

Given the importance of cancer-related diagnostic delays in ambulatory care, the investigators need effective methods to detect them, understand their causes, and intervene to reduce them. Manual techniques to detect these delays, such as spontaneous reporting and random chart reviews, have limited effectiveness. Our proposed study focuses on testing methods to proactively identify delays using certain "triggers" as they occur and intervene in a timely manner.

Study Overview

Status

Completed

Intervention / Treatment

Detailed Description

The goal of this proposal is to demonstrate and test methods by which large health care systems can efficiently identify cancer patients who are more likely to experience diagnostic delays and pre-emptively rectify these delays. This study will build upon tools developed in our recent work (Aim1, prior IRB Protocol Number: H-23801) and test their effectiveness to identify patients at risk of experiencing delays in cancer diagnosis followed by an intervention that the investigators hypothesize will reduce these delays.

This is Aim 2 (for which the investigators are seeking approval) is the final Aim of this proposal. Aim 1 was approved under Protocol Number: H-23801.

In Aim 2 the investigators will determine the effectiveness of an IT-based intervention (consisting of data mining using triggers tested in Aim 1 followed by targeted electronic communication and surveillance techniques) to facilitate cancer diagnosis as compared with usual care (no use of trigger or electronic communication and surveillance). Hypothesis 1: The time from first appearance of a diagnostic clue to follow-up action (e.g. colonoscopy performance after a positive FOBT) will be significantly less in the intervention arm than in usual care. Hypothesis 2: The percentage of patients receiving timely follow-up care will be significantly more in the intervention arm than in usual care. To improve the generalizability of our findings to multiple ambulatory care environments, the investigators will conduct our research in two settings: an urban Veterans Affairs facility in Houston, Texas and a large primary care network in central Texas. These settings include internal medicine and family medicine, academic and nonacademic practices, and significant racial, gender, ethnic, age, urban/rural, and socioeconomic diversity. Our study addresses coordination and timeliness of care, both of which are priorities to achieve high quality care.

Hypothesis 3: Overall, the trigger will achieve a positive predictive value (PPV) of at least 50% in identifying delays in care. PPV is defined as the number of charts correctly identified with a delay in diagnostic evaluation, divided by the total number of charts identified by the trigger, and was deemed to be the approximately level necessary to avoid substantial contribution to provider alert fatigue.

Study Type

Interventional

Enrollment (Actual)

1256

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Texas
      • Houston, Texas, United States, 77030
        • Michael E. DeBakey VA Medical Center
      • Temple, Texas, United States, 76508
        • Scott and White Memorial Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years to 65 years (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

All primary care providers at both study sites who agree to be in the study. Intervention will be performed on those whose patients are electronically identified to have suspected cancer defined as presence of any predefined clue for cancer that is not followed-up in a timely manner. Three cancers are included; colorectal, lung and prostate and their clues include • chest x-imaging suspicious for malignancy • suspected or confirmed iron deficiency anemia • positive FOBT • hematochezia • abnormal PSA Patients will be selected from the data warehouse .

Exclusion Criteria:

Primary care providers who do not wish to be in the study.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Contact Intervention
The intervention will include activities such as electronic communication and surveillance that facilitate the care of patients experiencing delays. A trained chart reviewer will conduct chart reviews on trigger-positive patients to confirm they are at risk for care delays and this will be followed by an electronic and/or verbal communication to the provider. The intervention will be compared to usual care at both sites.
The intervention will include activities such as electronic communication and surveillance that facilitate the care of patients experiencing delays. A trained chart reviewer will conduct chart reviews on trigger-positive patients to confirm they are at risk for care delays and this will be followed by an electronic and/or verbal communication to the provider. The intervention will be compared to usual care at both sites.
No Intervention: Usual Care Control
The usual care at MEDVAMC consists of providers using an advanced EHR and its notification system (the View Alert system) that immediately alerts providers about clinically significant events. The system relies primarily on computerized notification (alerts) displayed prominently through a "View Alert" window that is displayed in the EHR every time a provider signs on or switches between patient records. The system does not require providers to read alerts, and providers do have an option of ignoring the View Alert window to bypass it. At SWHS there is a navigation program for patients who have received a cancer diagnosis by tissue biopsy. However, currently there is no routine tracking of patients if they do not show for their scheduled appointments and tests at SWHS.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Differences in Time to Documented Follow-up of a Red Flag Suggestive of Cancer
Time Frame: 15 months
Differences between the intervention and control groups (based on a Cox Proportional Hazards Survival Analysis) in median time to documented follow-up of a red flag (e.g., colonoscopy performance after positive FOBT) or of a deliberate decision by the treating provider not to take follow-up action. When less than 50% of patients in either group received diagnostic evaluation (ie, medians were not reached), the point at which 40% received diagnostic evaluation was compared instead.
15 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Percentage of Patients Receiving Timely Follow-up of a Red Flag Suggestive of Cancer
Time Frame: 15 months
The percentage of patients receiving timely follow-up care, as defined by action taken by provider within appropriate pre-defined time intervals for each diagnostic clue, in both intervention and control groups.
15 months
Percentage of Cases With no Documented Justification for no Follow-up
Time Frame: 15 months
This is a descriptive sub-analysis looking only at cases with no follow-up at the end of the follow-up period. Specifically, out of the cases that never got follow-up, this represents the percent of that subsample that had no justification in the medical record for the lack of follow-up. This is based on manual chart reviews.
15 months
Number of Participants Diagnosed With Cancer After Delay in Diagnostic Evaluation
Time Frame: 15 months
Subsequent diagnosis of nonmalignant neoplasia, cancer, or death, and treatments required as a result of new cancer diagnoses after a pre-specified interval.
15 months
Trigger Positive Predictive Value
Time Frame: 15 months
Positive Predictive Values of each of the triggers in identifying patients with a true delay in diagnostic evaluation. Calculated as: percentage of patients identified as trigger positive that actually had a delay.
15 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Hardeep Singh, MD MPH, Baylor College of Medicine

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start

February 1, 2011

Primary Completion (Actual)

August 1, 2012

Study Completion (Actual)

August 1, 2012

Study Registration Dates

First Submitted

February 23, 2011

First Submitted That Met QC Criteria

May 2, 2011

First Posted (Estimate)

May 3, 2011

Study Record Updates

Last Update Posted (Estimate)

February 9, 2016

Last Update Submitted That Met QC Criteria

January 12, 2016

Last Verified

January 1, 2016

More Information

Terms related to this study

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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