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The Hackensack Meridian Health Universal Observational COVID-19, a descriptive observational database, is a multi-center initiative collecting data throughout the Hackensack Meridian Health Network (HMH). HMH utilizes the EPIC system at most of the facilities, which will serve as the primary data source. The database will be designed within the REDCap system. A de-identified dataset will be sent to COTA for primary statistical analysis as requested by the research teams.
The principle objective of this observational database is to build research-grade real world data that will serve as platform to advance the scientific understanding and clinical care of patients with COVID-19.
1. Demographic, diagnostic, treatment and outcome data from centers throughout the Hackensack Meridian Health Network will be abstracted from the electronic health records of patients with confirmed or suspected COVID-19. This will be purely observational and no direction as to the care of the patient will be performed as part of this effort.
1a. Data points to be collected will include, but are not limited to: age, gender, zip code, prior evaluation for COVID-19, tobacco history, race, site of care, healthcare worker, nursing home care, visits to ER, presenting features of fever/ cough/ dyspnea/ gastrointestinal/ mental status changes, days of symptoms, comorbidities, uses of antihypertensives, duration of hospitalization/ icu care, presenting laboratory functions, presenting vital signs, need for oxygen support, dialysis/ ecmo use, treatment with hydroxychloroquine/ azithromycin/ remdesevir/ tociluzimab/ anti-inflammatory agents, arrhythmias/ QTc prolongation, enrollment on clinical trial, positive cultures, survival and cause of death. Additional data points will be added as needed.
2. The data will be entered into a central "Universal" database hosted within the REDCap system (HIPAA compliant, secure, access only per HMH research approval)
3. A de-identified dataset will be sent to COTA for primary statistical analysis as requested by the research teams. COTA will also make available a data/analytic visualization tool (hosted on Tableau) for analysis by primary investigators.
4. Additional data points and analysis may be added to the Universal database as requested by HMH investigators with IRB approval. De-identified data may also be sent directly to HMH investigators for their own analysis with IRB approval of their projects 5. Data will be made available to governmental agencies as requested.
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| Measure | Description | Time Frame |
|---|---|---|
| Need for Hospitalization | Number of Participants needing hospitalization | 1 Year |
| Duration of Hospitalization | The duration of hospitalization is defined as the time in days from the first day of hospitalized to the date of discharge or death. Patients who are not discharged, are alive and still in the hospital on the date of closing follow-up, or lost follow-up on the date of closing follow-up will be considered censored on that date. | 1 Year |
| Need for ICU/Ventilator Support | Rate of ICU/Ventilator Support | 1 Year |
| Duration of Ventilator Support | The duration of Ventilator Support is defined as the time in days from the first day of using mechanical ventilation to the last day of using mechanical ventilation. All evaluable patients will be included and no censoring for this analysis. | 1 Year |
| Overall Survival Rate | Overall survival will be defined as rate of patients alive at end of follow up | 1 Year |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with confirmed or suspected COVID-19
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| Name | Affiliation | Role |
|---|---|---|
| Andrew Ip, MD | Hackensack Meridian Health | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hackensack Meridian Health - John Theurer Cancer Center | Hackensack | New Jersey | 07601 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32091533 | Background | Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648. No abstract available. | |
| 34329317 | Derived |
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| ID | Title | Description |
|---|---|---|
| FG000 | Patients With Confirmed or Suspected COVID-19 | Confirmed or suspected COVID-19 with data available via the EPIC system. There are no age restrictions or pregnancy restrictions |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
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| ID | Title | Description |
|---|---|---|
| BG000 | Patients With Confirmed or Suspected COVID-19 | Confirmed or suspected COVID-19 Data available via the EPIC system |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Due to the nature of the retrospective study, not all baseline measures were available in the electronic medical record for all participants. |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Need for Hospitalization | Number of Participants needing hospitalization | Posted | Count of Participants | Participants | 1 Year |
|
|
Adverse events were collected for 1 year but this is an observational study and there was no intervention introduced for research purposes.
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Patients With Confirmed or Suspected COVID-19 | Confirmed or suspected COVID-19 included in the COVID-19 Database Data available via the EPIC system |
| Term | Organ System | Source Vocabulary | Assessment Type | Notes | Statistical Information |
|---|---|---|---|---|---|
| Death | Investigations | Systematic Assessment |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Joshua Zenreich | Hackensack Meridian Health | 5519965900 | joshua.zenreich@hmhn.org |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Oct 2, 2020 | Oct 11, 2022 | Prot_SAP_000.pdf |
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| ID | Term |
|---|---|
| D000086382 | COVID-19 |
| D018352 | Coronavirus Infections |
| ID | Term |
|---|---|
| D011024 | Pneumonia, Viral |
| D011014 | Pneumonia |
| D012141 | Respiratory Tract Infections |
| D007239 | Infections |
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| Berry DA, Ip A, Lewis BE, Berry SM, Berry NS, MrKulic M, Gadalla V, Sat B, Wright K, Serna M, Unawane R, Trpeski K, Koropsak M, Kaur P, Sica Z, McConnell A, Bednarz U, Marafelias M, Goy AH, Pecora AL, Sawczuk IS, Goldberg SL. Development and validation of a prognostic 40-day mortality risk model among hospitalized patients with COVID-19. PLoS One. 2021 Jul 30;16(7):e0255228. doi: 10.1371/journal.pone.0255228. eCollection 2021. |
| 32838323 | Derived | Biran N, Ip A, Ahn J, Go RC, Wang S, Mathura S, Sinclaire BA, Bednarz U, Marafelias M, Hansen E, Siegel DS, Goy AH, Pecora AL, Sawczuk IS, Koniaris LS, Simwenyi M, Varga DW, Tank LK, Stein AA, Allusson V, Lin GS, Oser WF, Tuma RA, Reichman J, Brusco L Jr, Carpenter KL, Costanzo EJ, Vivona V, Goldberg SL. Tocilizumab among patients with COVID-19 in the intensive care unit: a multicentre observational study. Lancet Rheumatol. 2020 Oct;2(10):e603-e612. doi: 10.1016/S2665-9913(20)30277-0. Epub 2020 Aug 14. |
| 32790733 | Derived | Ip A, Berry DA, Hansen E, Goy AH, Pecora AL, Sinclaire BA, Bednarz U, Marafelias M, Berry SM, Berry NS, Mathura S, Sawczuk IS, Biran N, Go RC, Sperber S, Piwoz JA, Balani B, Cicogna C, Sebti R, Zuckerman J, Rose KM, Tank L, Jacobs LG, Korcak J, Timmapuri SL, Underwood JP, Sugalski G, Barsky C, Varga DW, Asif A, Landolfi JC, Goldberg SL. Hydroxychloroquine and tocilizumab therapy in COVID-19 patients-An observational study. PLoS One. 2020 Aug 13;15(8):e0237693. doi: 10.1371/journal.pone.0237693. eCollection 2020. |
| Mean |
| Standard Deviation |
| years |
|
| Sex: Female, Male | Due to the nature of the retrospective study, not all baseline measures were available in the electronic medical record for all participants. | Count of Participants | Participants |
|
| Ethnicity (NIH/OMB) | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
|
| Primary | Duration of Hospitalization | The duration of hospitalization is defined as the time in days from the first day of hospitalized to the date of discharge or death. Patients who are not discharged, are alive and still in the hospital on the date of closing follow-up, or lost follow-up on the date of closing follow-up will be considered censored on that date. | Hospitalized Patients | Posted | Mean | Standard Deviation | Days | 1 Year |
|
|
|
| Primary | Need for ICU/Ventilator Support | Rate of ICU/Ventilator Support | Posted | Count of Participants | Participants | 1 Year |
|
|
|
| Primary | Duration of Ventilator Support | The duration of Ventilator Support is defined as the time in days from the first day of using mechanical ventilation to the last day of using mechanical ventilation. All evaluable patients will be included and no censoring for this analysis. | Posted | Mean | Standard Deviation | Days | 1 Year |
|
|
|
| Primary | Overall Survival Rate | Overall survival will be defined as rate of patients alive at end of follow up | Posted | Count of Participants | Participants | 1 Year |
|
|
|
| 933 |
| 4,588 |
| 933 |
| 4,588 |
| 0 |
| 4,588 |
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| D014777 |
| Virus Diseases |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012327 | RNA Virus Infections |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |