Effectiveness of Electronic Health Record-Based Interventions for Improving Follow-Up in Primary Care
| Status: | Completed |
|---|---|
| Conditions: | Lung Cancer, Prostate Cancer, Colorectal Cancer, Cancer, Cancer, Cancer |
| Therapuetic Areas: | Oncology |
| Healthy: | No |
| Age Range: | 18 - 65 |
| Updated: | 4/21/2016 |
| Start Date: | February 2011 |
| End Date: | August 2012 |
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.
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.
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.
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.
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.
We found this trial at
2
sites
Michael E. Debakey VA Medical Center The Michael E. DeBakey VA Medical Center serves as...
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Scott & White Memorial Hospital When Arthur C. Scott, MD, and Raleigh R. White Jr.,...
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