Comparing Treatment Options for Uterine Fibroids: An EHR-based Algorithm for Registry Recruitment [12H]. Issue 1 (May 2017)
- Record Type:
- Journal Article
- Title:
- Comparing Treatment Options for Uterine Fibroids: An EHR-based Algorithm for Registry Recruitment [12H]. Issue 1 (May 2017)
- Main Title:
- Comparing Treatment Options for Uterine Fibroids
- Authors:
- Hoffman, Sarah
Westreich, Daniel
Vines, Anissa
Halladay, Jacqueline
Pfaff, Emily
Nicholson, Wanda K. - Abstract:
- Abstract : INTRODUCTION: COMPARE-UF is a national registry of women with uterine fibroids (UF) that will examine the effectiveness of different fibroid treatments on patient-centered outcomes. Electronic health records (EHR) may be used for efficient identification of eligible women within healthcare systems. An EHR-based algorithm was developed to identify women with symptomatic UF for recruitment into the PCORI-supported COMPARE-UF registry. METHODS: An iterative process was undertaken with a goal to maximize the positive predictive value (PPV) of the final algorithm. For the first algorithm, women were required to be age 18-54, have imaging confirming UFs or a diagnosis code for UF and no history of hysterectomy. The second algorithm required both imaging and at least 2 diagnoses codes for UF. The third algorithm required at least 2 diagnosis codes for UF on separate dates, and excluded patients who had UF detected during a prenatal or emergency department visits. Randomly selected charts were reviewed for each algorithm. RESULTS: The first algorithm identified 4, 342 patients, with a PPV of 47% (95% CI: 39-56%) after 150 charts were reviewed with ultrasound evidence of UFs in 139 (93%). The second algorithm yielded 1, 174 patients, with a PPV of 65% (95% CI: 50-79%) after reviewing 51 charts. The third algorithm yielded 465 patients, with a PPV of 76% (95% CI: 71-81%) after 300 chart reviews. CONCLUSION: An EHR algorithm can identify patients with UFs. HoweverAbstract : INTRODUCTION: COMPARE-UF is a national registry of women with uterine fibroids (UF) that will examine the effectiveness of different fibroid treatments on patient-centered outcomes. Electronic health records (EHR) may be used for efficient identification of eligible women within healthcare systems. An EHR-based algorithm was developed to identify women with symptomatic UF for recruitment into the PCORI-supported COMPARE-UF registry. METHODS: An iterative process was undertaken with a goal to maximize the positive predictive value (PPV) of the final algorithm. For the first algorithm, women were required to be age 18-54, have imaging confirming UFs or a diagnosis code for UF and no history of hysterectomy. The second algorithm required both imaging and at least 2 diagnoses codes for UF. The third algorithm required at least 2 diagnosis codes for UF on separate dates, and excluded patients who had UF detected during a prenatal or emergency department visits. Randomly selected charts were reviewed for each algorithm. RESULTS: The first algorithm identified 4, 342 patients, with a PPV of 47% (95% CI: 39-56%) after 150 charts were reviewed with ultrasound evidence of UFs in 139 (93%). The second algorithm yielded 1, 174 patients, with a PPV of 65% (95% CI: 50-79%) after reviewing 51 charts. The third algorithm yielded 465 patients, with a PPV of 76% (95% CI: 71-81%) after 300 chart reviews. CONCLUSION: An EHR algorithm can identify patients with UFs. However symptomatic UF cases can be challenging to distinguish from asymptomatic cases and require additional steps to confirm eligibility. … (more)
- Is Part Of:
- Obstetrics and gynecology. Volume 129:Issue 1(2017)
- Journal:
- Obstetrics and gynecology
- Issue:
- Volume 129:Issue 1(2017)
- Issue Display:
- Volume 129, Issue 1 (2017)
- Year:
- 2017
- Volume:
- 129
- Issue:
- 1
- Issue Sort Value:
- 2017-0129-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-05
- Subjects:
- Obstetrics -- Periodicals
Gynecology -- Periodicals
618 - Journal URLs:
- http://journals.lww.com/greenjournal/pages/default.aspx ↗
http://journals.lww.com ↗ - DOI:
- 10.1097/01.AOG.0000514914.91178.bf ↗
- Languages:
- English
- ISSNs:
- 0029-7844
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6208.200000
British Library DSC - BLDSS-3PM
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- 4530.xml