Intervention Protocol for Automated Point-of-Care Surveillance of Outpatient Delays in Cancer Diagnosis (PACT CREATE 3)
Automated Point-of-Care Surveillance of Outpatient Delays in Cancer Diagnosis
Many missed and delayed cancer diagnoses result from breakdowns in communication and coordination of abnormal findings suspicious for cancer, which often first emerge in the primary care setting. Delays in the follow-up of abnormal test results persist despite the reliable delivery of test results through the electronic health record.
This intervention is the final study in a three-phase project that will develop and test an innovative automated surveillance intervention to improve timely diagnosis and follow-up of five common cancers in primary care practice.
The investigators hypothesize that the median time in days from diagnostic clue to follow-up action (e.g. time to colonoscopy examination after am abnormal colon-related test) will be significantly less in the intervention arm than in usual care. The investigators also hypothesize that the proportion of patients receiving appropriate and timely follow-up care will be significantly higher in the intervention arm than in usual care.
調査の概要
状態
詳細な説明
The CREATE Project encompasses three phases, the first and second of which do not contain interventions. The first phase of the project determines the effectiveness of computerized queries the investigators develop to accurately identify which patients are at risk for delays in cancer diagnosis. Patients the investigators identify will have abnormal test results or symptoms that have not been followed up by their providers. In Phase 2 of the study, the research team will use interviewing and other participatory techniques to determine the best way to convey information about such at-risk patients to providers in an automated fashion. In Phase 3 of the project, the investigators will evaluate the effects of an automated surveillance intervention on the timeliness of the diagnostic process of five cancers.
This project will improve communication and coordination of cancer-related diagnostic information to improve quality and safety.
研究の種類
段階
- 適用できない
連絡先と場所
研究場所
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Illinois
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Chicago、Illinois、アメリカ、60612
- Jesse Brown VA Medical Center, Chicago, IL
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Hines、Illinois、アメリカ、60141-5000
- Edward Hines Jr. VA Hospital, Hines, IL
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Minnesota
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Minneapolis、Minnesota、アメリカ、55417
- Minneapolis VA Health Care System, Minneapolis, MN
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Texas
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Houston、Texas、アメリカ、77030
- Michael E. DeBakey VA Medical Center, Houston, TX
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Wisconsin
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Madison、Wisconsin、アメリカ、53705
- William S. Middleton Memorial Veterans Hospital, Madison, WI
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参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
- Patient charts: Medical charts of Veteran patients who receive care from participating VA facility (Madison VAH, Jesse Brown VAMC, Hines VAH, Michael E. DeBakey VAMC, and Minneapolis VAMC) providers during the one year study period (tentatively October 2016-October 2017) and who have potential delays in diagnostic evaluation for lung, colorectal, liver, bladder, or breast cancer will be reviewed as part of the study.
- Providers: Providers who have seen primary care outpatients in any of the participating facilities or their outpatient clinics within the year-long study period.
Exclusion Criteria:
- Patient Charts: Medical charts of patients who are not receiving care from participating facility providers or charts of patients who do not have potential follow-up delays for lung, colorectal, liver, bladder, or breast cancer in the time period of interest.
- Providers: Providers who have not seen primary care outpatients in any of the participating facilities or their outpatient clinics within the time period of interest.
研究計画
研究はどのように設計されていますか?
デザインの詳細
- 主な目的:ヘルスサービス研究
- 割り当て:ランダム化
- 介入モデル:並列代入
- マスキング:独身
武器と介入
参加者グループ / アーム |
介入・治療 |
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実験的:Communication of Patients Lost to Follow-up to Providers
This intervention will consist of two related, continuous steps over at least a 12-month period.
In the first step, the investigators will query the VA's Corporate Data Warehouse (CDW, a repository of near real-time patient data from all VA medical centers) weekly to identify possible lost to follow-up events in a pre-specified time period and for a random sample of about half of the providers at the investigators' study sites.
These identified patient charts will be reviewed by Facility Recipients/Cancer Trackers at each site who will then communicate patients truly found to be lost to follow-up to the appropriate provider/care team.
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The investigators will query the VA's database weekly to identify possible lost to follow-up events for a random sample of about half of the providers at our study sites.
The queries will use the trigger criteria developed in our previous work for colorectal cancer, lung cancer, hepatocellular carcinoma, breast cancer, and bladder cancer.
The list of trigger positive patients will be transmitted to a facility-level recipient who will either disseminate the information to existing facility individual cancer care coordinators/trackers or will review the charts of the "triggered" patients in order to determine whether these patients have been truly lost to follow-up or not.
If patients are found to be lost to follow-up, the Facility Recipient or cancer care coordinator/tracker will communicate the need for follow-up to the PACT or primary care provider, using secure emails, phone calls, or in person, depending on which method of communication they deem most appropriate and effective.
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介入なし:Usual Care
In the usual care group, providers will continue to use the existing notification system to receive abnormal test results in accordance with institutional norms, policies, and procedures.
There are no formal patient-tracking programs currently at our study sites for all abnormal test results.
The investigators will apply our computerized surveillance tools in the usual care arm only when the investigators are ready to conduct the final chart reviews on intervention patients and identify these patients in similar time periods as in the intervention arm.
If persistent delays are found, the investigators will inform the patients' primary care providers.
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この研究は何を測定していますか?
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
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Median Time from Initial Follow-up Delay to Follow-up Action
時間枠:1 year
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The investigators will conduct chart reviews of patients shown by our automated surveillance system to have not received appropriate follow-up care in both intervention and control groups at least 6 months after the first documentation of a diagnostic clue (e.g., initial abnormal chest X-ray).
Chart review will be used to quantify time in days from documentation of the clinical clue to the time when follow-up action on that clue was initiated.
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1 year
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協力者と研究者
捜査官
- 主任研究者:Hardeep Singh, MD MPH BS、Michael E. DeBakey VA Medical Center, Houston, TX
出版物と役立つリンク
一般刊行物
- Murphy DR, Meyer AN, Russo E, Sittig DF, Wei L, Singh H. The Burden of Inbox Notifications in Commercial Electronic Health Records. JAMA Intern Med. 2016 Apr;176(4):559-60. doi: 10.1001/jamainternmed.2016.0209. No abstract available.
- Bhise V, Meyer AND, Singh H, Wei L, Russo E, Al-Mutairi A, Murphy DR. Errors in Diagnosis of Spinal Epidural Abscesses in the Era of Electronic Health Records. Am J Med. 2017 Aug;130(8):975-981. doi: 10.1016/j.amjmed.2017.03.009. Epub 2017 Mar 31.
- Murphy DR, Meyer AN, Vaghani V, Russo E, Sittig DF, Richards KA, Wei L, Wu L, Singh H. Application of Electronic Algorithms to Improve Diagnostic Evaluation for Bladder Cancer. Appl Clin Inform. 2017 Mar 22;8(1):279-290. doi: 10.4338/ACI-2016-10-RA-0176.
- Meyer AND, Murphy DR, Al-Mutairi A, Sittig DF, Wei L, Russo E, Singh H. Electronic Detection of Delayed Test Result Follow-Up in Patients with Hypothyroidism. J Gen Intern Med. 2017 Jul;32(7):753-759. doi: 10.1007/s11606-017-3988-z. Epub 2017 Jan 30.
- Menon S, Singh H, Giardina TD, Rayburn WL, Davis BP, Russo EM, Sittig DF. Safety huddles to proactively identify and address electronic health record safety. J Am Med Inform Assoc. 2017 Mar 1;24(2):261-267. doi: 10.1093/jamia/ocw153.
- Baldwin JL, Singh H, Sittig DF, Giardina TD. Patient portals and health apps: Pitfalls, promises, and what one might learn from the other. Healthc (Amst). 2017 Sep;5(3):81-85. doi: 10.1016/j.hjdsi.2016.08.004. Epub 2016 Oct 3.
- Singh H, Graber ML, Hofer TP. Measures to Improve Diagnostic Safety in Clinical Practice. J Patient Saf. 2019 Dec;15(4):311-316. doi: 10.1097/PTS.0000000000000338.
- Singh H. Improving Diagnostic Safety in Primary Care by Unlocking Digital Data. Jt Comm J Qual Patient Saf. 2017 Jan;43(1):29-31. doi: 10.1016/j.jcjq.2016.10.007. Epub 2016 Oct 14. No abstract available.
- Giardina TD, Sarkar U, Gourley G, Modi V, Meyer AN, Singh H. Online public reactions to frequency of diagnostic errors in US outpatient care. Diagnosis (Berl). 2016 Mar;3(1):17-22. doi: 10.1515/dx-2015-0022. Epub 2016 Feb 19.
- Singh H, Schiff GD, Graber ML, Onakpoya I, Thompson MJ. The global burden of diagnostic errors in primary care. BMJ Qual Saf. 2017 Jun;26(6):484-494. doi: 10.1136/bmjqs-2016-005401. Epub 2016 Aug 16.
- Sittig DF, Wright A, Ash J, Singh H. New Unintended Adverse Consequences of Electronic Health Records. Yearb Med Inform. 2016 Nov 10;(1):7-12. doi: 10.15265/IY-2016-023.
- Pfoh ER, Engineer L, Singh H, Hall LL, Fried ED, Berger Z, Wu AW. Informing the Design of a New Pragmatic Registry to Stimulate Near Miss Reporting in Ambulatory Care. J Patient Saf. 2021 Apr 1;17(3):e121-e127. doi: 10.1097/PTS.0000000000000317.
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (実際)
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (見積もり)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
- CRE 12-033
- CIRB 15-07 (その他の識別子:VA Central IRB)
個々の参加者データ (IPD) の計画
個々の参加者データ (IPD) を共有する予定はありますか?
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
米国で製造され、米国から輸出された製品。
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