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

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

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT01346839
Enrollment
1256
Registered
2011-05-03
Start date
2011-02-28
Completion date
2012-08-31
Last updated
2016-02-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Colon Cancer, Lung Cancer, Prostate Cancer

Keywords

Diagnostic delay, Prevention, Diagnostic errors

Brief summary

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.

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.

Interventions

BEHAVIORALContact 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.

Sponsors

Scott and White Hospital & Clinic
CollaboratorOTHER
Baylor College of Medicine
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
SINGLE (Caregiver)

Eligibility

Sex/Gender
ALL
Age
18 Years to 65 Years
Healthy volunteers
No

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.

Design outcomes

Primary

MeasureTime frameDescription
Differences in Time to Documented Follow-up of a Red Flag Suggestive of Cancer15 monthsDifferences 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.

Secondary

MeasureTime frameDescription
Percentage of Patients Receiving Timely Follow-up of a Red Flag Suggestive of Cancer15 monthsThe 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.
Percentage of Cases With no Documented Justification for no Follow-up15 monthsThis 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.
Number of Participants Diagnosed With Cancer After Delay in Diagnostic Evaluation15 monthsSubsequent diagnosis of nonmalignant neoplasia, cancer, or death, and treatments required as a result of new cancer diagnoses after a pre-specified interval.
Trigger Positive Predictive Value15 monthsPositive 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.

Countries

United States

Participant flow

Participants by arm

ArmCount
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. 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.
369
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.
364
Total733

Baseline characteristics

CharacteristicUsual Care ControlContact InterventionTotal
Age, Continuous60.3 years
STANDARD_DEVIATION 8.5
60.4 years
STANDARD_DEVIATION 7.4
60.3 years
STANDARD_DEVIATION 7.9
Ethnicity (NIH/OMB)
Hispanic or Latino
33 Participants35 Participants68 Participants
Ethnicity (NIH/OMB)
Not Hispanic or Latino
331 Participants334 Participants665 Participants
Ethnicity (NIH/OMB)
Unknown or Not Reported
0 Participants0 Participants0 Participants
Number of Comorbidities2.1 Comorbidities
STANDARD_DEVIATION 1.4
2.2 Comorbidities
STANDARD_DEVIATION 1.3
2.2 Comorbidities
STANDARD_DEVIATION 1.4
Race (NIH/OMB)
American Indian or Alaska Native
1 Participants0 Participants1 Participants
Race (NIH/OMB)
Asian
13 Participants5 Participants18 Participants
Race (NIH/OMB)
Black or African American
154 Participants141 Participants295 Participants
Race (NIH/OMB)
More than one race
0 Participants0 Participants0 Participants
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
0 Participants0 Participants0 Participants
Race (NIH/OMB)
Unknown or Not Reported
17 Participants10 Participants27 Participants
Race (NIH/OMB)
White
179 Participants213 Participants392 Participants
Region of Enrollment
United States
364 participants369 participants733 participants
Sex: Female, Male
Female
66 Participants38 Participants104 Participants
Sex: Female, Male
Male
298 Participants331 Participants629 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
— / —— / —
other
Total, other adverse events
0 / 3690 / 364
serious
Total, serious adverse events
0 / 3690 / 364

Outcome results

Primary

Differences in Time to Documented Follow-up of a Red Flag Suggestive of Cancer

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.

Time frame: 15 months

ArmMeasureGroupValue (MEDIAN)
Contact InterventionDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Colorectal Trigger104 Days
Contact InterventionDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Prostate Trigger144 Days
Contact InterventionDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Lung Trigger65 Days
Usual Care ControlDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Colorectal Trigger200 Days
Usual Care ControlDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Prostate Trigger192 Days
Usual Care ControlDifferences in Time to Documented Follow-up of a Red Flag Suggestive of CancerTime to Follow-up of Lung Trigger93 Days
p-value: <0.05Regression, Cox
Secondary

Number of Participants Diagnosed With Cancer After Delay in Diagnostic Evaluation

Subsequent diagnosis of nonmalignant neoplasia, cancer, or death, and treatments required as a result of new cancer diagnoses after a pre-specified interval.

Time frame: 15 months

ArmMeasureValue (NUMBER)
Contact InterventionNumber of Participants Diagnosed With Cancer After Delay in Diagnostic Evaluation13 Number of patients diagnosed with cancer
Usual Care ControlNumber of Participants Diagnosed With Cancer After Delay in Diagnostic Evaluation10 Number of patients diagnosed with cancer
Secondary

Percentage of Cases With no Documented Justification for no Follow-up

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.

Time frame: 15 months

ArmMeasureValue (NUMBER)
Contact InterventionPercentage of Cases With no Documented Justification for no Follow-up33.9 percentage with no documentation
Usual Care ControlPercentage of Cases With no Documented Justification for no Follow-up48.0 percentage with no documentation
Secondary

Percentage of Patients Receiving Timely Follow-up of a Red Flag Suggestive of Cancer

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.

Time frame: 15 months

ArmMeasureValue (NUMBER)
Contact InterventionPercentage of Patients Receiving Timely Follow-up of a Red Flag Suggestive of Cancer73.4 percentage of follow-up
Usual Care ControlPercentage of Patients Receiving Timely Follow-up of a Red Flag Suggestive of Cancer52.2 percentage of follow-up
Secondary

Trigger Positive Predictive Value

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.

Time frame: 15 months

ArmMeasureValue (NUMBER)
Contact InterventionTrigger Positive Predictive Value63.5 Percentage of participants
Usual Care ControlTrigger Positive Predictive Value55.3 Percentage of participants

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026