Procedures and Forms

Investigators who wish to request support must fill out a BCCC Request Support form to provide a brief summary of the objectives and study design for the project. An initial meeting to ascertain the scope of work will then be scheduled, usually within 10 business days, depending upon BCCC resource availability. Principal Investigators and Senior mentors, when applicable, are required to attend the initial meeting.

• The initial meeting with a Biostatistician to discuss needs/project scope is free of charge. The purpose of the meeting will be to review the research needs and study design issues, to estimate workload, and to plan a realistic timetable. If BCCC support is desired by the Investigator, an Agreement for Support Form will be developed by the BCCC, and presented to the Principal Investigator with estimated workload and associated fees.
• After the initial meeting, upon a signed Agreement between the BCCC and Principal Investigator, all subsequent support will be charged according to our rate structure, unless investigator's home department is enrolled in our collaboration plan.
• No work can begin until a project agreement form has been completed; this includes our fees based on the estimated workload, a University of Miami account number to be billed, and the signature of a person authorized to expend funds from the account. (Projects external to the University of Miami (non- UM) must provide other acceptable billing information, and paid in advance, prior to the start of the work.) Initial fees established after the initial meeting will not be exceeded without prior notification and approval.

Advance contact is necessary to allow sufficient time to address your needs before deadline. Below are minimum times required:

Protocol Development/ Grant application – two months. It is most advantageous that biostatistical expertise be obtained as early as possible in the proposal development. At least six weeks. If it is a first submission and we don't have enough time, our contribution will demonstrate statistical involvement but will likely be criticized for being incomplete. If it is a re-submission, we may at least two months to provide quality input.

Protocol review (completed) – 2 weeks. We may find statistical issues, and if it is desired the BCCC support the protocol from that point, more time will be required.

Statistical analysis – 3 weeks, depending on the type of analysis and study design.

Abstracts – 1 month, depending on statistical analysis. At least one month. If it is less than a month before the deadline, we may be able to help you with some simple summary statistics. There may not be enough time to do anything more complex.

Manuscript preparation-3-4 weeks, after statistical analysis is complete.

As the deadline approaches, the likelihood that we can provide helpful statistical support diminishes.

On a case-by-case basis, we may be able to accommodate requests that are closer to the deadlines than described in the timelines above. In order to provide anything of real quality, appropriate planning for adequate time is essential.

Prioritization

In general, the priorities for BCCC support resource allocation (from highest to lowest) are:

• Grant preparation
• Abstracts for national meetings, and other reports with fixed deadlines
• Protocol design and review
• Laboratory, animal, and epidemiology study design and review
• Short term consults
• Study monitoring, analysis, manuscript preparation, and replies to manuscript reviews
• Education of users

• Co-authorship on scientific journal articles is generally expected on studies where substantive input on design and/or analysis is provided. The contribution of each person needs to be evaluated as a manuscript is prepared. Consideration for authorship should be based on the accepted criteria for most medical journals. These criteria generally cite both study design and statistical analysis as intellectual input sufficient for authorship. It is impossible to define every situation in advance; however, it should be clear that reimbursement for time does not preclude or replace authorship. For more information, please refer to the edicts set forth in the Uniform Requirements for Manuscripts Submitted to Biomedical Journals.
• The biostatistician performing the analysis will be a co-author on the publication to acknowledge the intellectual contribution to the work. Statistician co-authors will use their primary appointment affiliation on manuscripts and abstracts.
• To maintain study and statistical integrity, statistical analysis for publication and abstracts will only be analyzed after study completion.
• The BCCC biostatistician performs the analysis, collaborates in the structuring of the presentation of the results and writes the “statistical methods” section of the paper.
• The BCCC biostatistician reviews the final publication prior to submission.
• The biostatistician assists with revisions and reviews the publication prior to resubmission.
• All publications resulting from the utilization of CTSI resources are required to credit the CTSI grant by including the NIH Funding Acknowledgment and must comply with NIH Public Access Policy. Please reference your PMID Number and PMCID Number on all publications the benefited from any resources supported by the UM CTSI.

"The project described was supported by Grant Number 1UL1TR000460, University of Miami Clinical and Translational Science Institute, from the National Center for Advancing Translational Sciences and the National Institute on Minority Health and Health Disparities. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH."

General Policy

Information pertaining to specific individuals is protected by Health Insurance Portability and Accountability Act (HIPAA). Data that is protected in this context should be treated carefully. If data has any of the identifying characteristics elaborated on below, special issues may arise with transferring data and the permissions of the analyst to view and/or store the data. Please discuss de-identification options with your biostatistician to mitigate these issues.

PHI Definitions (COMIRB Guidelines)

Protected health information (PHI) is any data which, when combined with one or more data elements or commonly available information, could be used to identify a person. PHI does not include de-identified information which does not identify an individual and for which there is no reasonable basis to believe that information could be used to identify an individual.

Information Which May Be Protected Includes, but is Certainly Not Limited To:

• Name
• Postal address (to a location smaller than state)
• All elements of dates, except year (For dates directly related to an individual including birth date, admission date, discharge date, and date of death. As well as ages greater than 89 aggregated to 90 and older.)
• Phone/Fax Number
• Email addresses
• Social Security Number Medical Record Number
• Health plan number
• Account numbers
• Certificate/license numbers
• URL addresses
• IP addresses
• Vehicle identifiers
• Device ID
• Biometric ID
• Full face (or other identifying photo)
• Any other unique identifying number, characteristic, or code
• It should be noted that HIPAA regulations also apply to deceased individuals

Data Security

• All data should be securely stored, and access should be restricted to those individuals entering data.
• Properly dispose of paper and electronic files, keep paper copies in locked cabinet, and store electronic files on a secure-access central server.
• Keep in mind the Health Insurance Portability and Accountability Act (HIPAA)’s Minimum Necessary Principle when listing what variables to include in your database.
• Use or disclose only information necessary to the task. It is important to exclude unnecessary items that make information identifiable to ensure privacy, security and patient confidentiality.
• If identifiable information is necessary for research (e.g. birth date, visit date, physical address), take necessary precautions to protect the database: strong passwords, anti-virus software, data backup, possibly encryption, and being very cautious with email.
• Refer to HIPAA for additional stipulations.
• Subject identifiers such as name and social security number, and medical record locator must be removed from the dataset before it is given to the BCCC.
• It is the responsibility of the Principal Investigator to ensure that databases, analysis datasets and other aspects of the study are HIPAA compliant. Datasets received by the BCCC with Protected Health Information (PHI) will be returned to the study investigator for removal of non-compliant fields.
• All projects must have IRB approval for human subject studies and IACUC approval for animal studies. Investigators must be willing to provide approval documents when requested by the BCCC.

The time and effort involved in performing statistical analyses can be greatly reduced if the data are entered in the proper format. It is the responsibility of the investigator or research team to provide data sets that are clean and in proper format. If the BCCC needs to invest time in cleaning and formatting data, this will be charged for according to our rate structure. It is best to consult with BCCC personnel before you begin to collect the data if possible, to ensure that proper construction and formatting is used. We recommend the use of the REDCap, Velos or UChart database systems when it is feasible.

Best Practice for Improving Readability of Data

We are unable to address data format issues and may need to ask you to reformat improperly formatted datasets. Please be sure to follow these guidelines when you format your dataset:

• Single row for headings/column names. No repeated headings.
• Headings not too long—use short (1 or 2 words) column headings, then use a data dictionary to elaborate the short heading. We’ll be sure the long version from the data dictionary makes its way onto figures, etc.
• Include a separate document that defines values – a “data dictionary.” See below for an example.
• We cannot analyze “free form” or “text string” columns (such as “other,” “explain,” or “notes”), although you can leave them in the dataset for reference.
• The computer ignores color, so don’t color-code data or the information that you color-coded will be lost.
• Stick to a coding convention. Entering “F” for one woman’s sex, “f” for another’s, and “Female” for another’s results in three types of females. Pick one convention and be consistent throughout a column. Capitalization matters!
• No “special” characters, such as text accents.
• File types that end with .xls, .xlsx, .csv, and .sas7bdat are good.
• Include patient IDs, provider IDs, etc.
• Do not include any Protected Health Information (PHI).
• Missing data should be left blank, rather than coded as “99,” “-99,” “.,” etc.
• No characters in a numeric column/variable. If there are characters anywhere in a column (aside from the column name), the computer will treat the whole column as characters. Putting the word “missing” or “unknown” or the character “-“ for missing values in a column will convert any numbers in that column to character expressions, which would be treated as categories, not numbers, in an analysis.
• For numeric variables, don’t include units in the cell values, as they are characters. Include the units in the data dictionary instead, and we’ll put them on figures, tables, etc.

NOTE: This list is not exhaustive

Data Dictionary Example

For a Ventricular Tachycardia Study

• PtID: patient ID
• Inst: institution ID
• Gender: gender of patient
• M=Male
• F=Female
• AblNum: ablation number:
  • Numeric count
• Fascic: tachycardia type:
  • 1=Fascicular VT
  • 0=Other VT
• Recur: tachycardia recurrence:
  • 1=VT recurrent
  • 0=VT not recurrent
• Follow_Up: Follow up time after this ablation
  • Time started with a successful ablation and ended when VT recurred (1 above) or when follow up time ended without recurrent VT (0 above)
• Status: Final Patient Status:
  • 0=off meds, no VT
  • 1=off meds, intermittent VT
  • 2=on meds, no VT
  • 3=on meds, intermittent VT
  • 4=other

Organize Your Data for Statistical Analysis - Best Practices for Data Transfer

It is important for you to organize your data in a way that facilitates transfer to our biostatisticians, or other investigators or computers. Well-defined and organized data minimizes confusion and incorrect data. You are encouraged to use REDCap for data collection to minimize data entry errors or risks to patient confidentiality, and ease data transfer for statistical analysis.

Recommendations for Organizing Data

These recommendations have demonstrated to be effective for moving data from point to point in a structured manner. A reasonable data organization scheme should minimize the amount of editing needed at the receiving side of your data transfer.

Table 1 illustrates three types of variables in a structure that lends itself to simple data transfer and minimal data editing.

• Identification (PatID) variables: uniquely identify aspects of an individual record (row of data), for instance, subject #, clinic #, or PatID.
• Time-stable variables: include characteristics that remain constant for individual subject if observed over time, for instance, baseline demographics (age, sex, race) or study group (A, B).
• Longitudinal variables: potentially change over time, for instance, weight, adolescent height, muscle tone, lab values (cholesterol, blood sugar, etc.).

In this example, the structure has one column available for identifying an individual (Subject), two columns for time-stable characteristics (Trt, Sex) and two columns for longitudinal characteristics (time, weight). Note the values of subject and time uniquely identify each row.

Other experimental designs will require different data structures, but each measured response must be uniquely associated with only one subject, visit or test.

Most statistical software packages (e.g. SAS, SPSS, Splus, R and Stata) require data represented in a rectangular format where each row is a unique observation and each column is a separate variable. When organizing data into a rectangular format: first each row contains one (and only one) unique observation. In the example each row contains a unique combination of subject, time, and treatment. Second, each column contains one (and only one) variable or response.

Codebook (in a separate worksheet):

Trt: Treatment, 0=Placebo, 1=Drug
Sex: 0=Woman, 1=Men
Time: Time in Study in weeks
Weight: Body weight in pounds

• Data table is rectangular, rows represent observations, and columns represent variables. Some columns identify observation and others contain a measured response. All data contained in one rectangular area.
• Only Patient ID numbers are used, Protected Health Information (PHI) is not included. Names should not be included in your database for analysis to avoid unnecessary risks to patient confidentiality (see Table 2).
• Unique key to each row consists of two variables (columns) PatID and Time.
• Characters (A, AB, O) and numeric values (0, 1, 2) are not mixed within one column. Where possible, a number has been chosen in place of a character. Definition of numbers, units for continuous data, and explanation for abbreviated variable titles should be provided separately in a codebook.
• Missing data: Note that none of the variable values uniquely identify the subject and conditions where measurements taken are missing (ID, trt, time). A character value (e.g. "missing", "dk", "x") or numeric value zero (i.e., 0) should not be used to indicate missingness for a continuous variable (ex: variable "Weight" in Table 1).
• Before data collection begins, your should give special attention to how an assay value below detection will be indicated in the data, and how it should be treated in the statistical analysis. Similarly, for left- censored or right-censored values.
• Column headers are variable names, not a description. Variable descriptions can be provided separately in a "codebook" (or a separate worksheet in same workbook). In general, variable names must:
  1. Be 8 characters or less in length
  2. Consist of one word (i.e. no spaces)
  3. Be unique (not duplicated across multiple columns)
  4. Begin with a letter, not a number
  5. Contain no special characters: commas, quotes, apostrophes, period, underscore.
• Avoid using punctuation or spaces (e.g. commas, quotes, <,>).
• Avoid using special formatting like colored text, highlighted columns, italics, bolding, super or sub scripting, and the "comment" feature.
• Store notes about patients in separate column from data used in analysis (e.g. "scheduled to come in again for repeat lab"). If information in text of notes needs to be analyzed, it should be coded into one (or more) variable column(s).

If considered in enough detail before your data collection process begins, the organization of the experimental data is relatively simple. Whether or not there are questions or confusion about how to efficiently organize and manage your data, consulting with a statistician before your experiment begins is a good idea. These matters can usually be resolved in a short time with satisfactory results for all concerned. Biostatisticians often oversee the data collection, storage, and retrieval systems for clinical studies. The study biostatistician is able to distinguish between essential and non-essential data and can therefore limit the data collection systems to relevant information.

Limiting the amount of data collected means it is easier to assure data quality, minimize missing data, and pre- define the analysis data sets so that, upon study completion, data analysis is straightforward. Developing an effective data collection and management system is a key step in assuring the ultimate integrity of your study. Dataset planning can be iterative, involving meetings between the Statistician, Investigator, and Informatics Manager.

Specific examples of instances in your planning phase where obtaining a statistician’s input would be beneficial:

• Design data collection forms
• Outline data collection/management systems (include variable name, specify variable type, e.g. date, numeric, open text)
• Design, implement, and conduct of data quality monitoring system for a study
• Outline how and when data abstraction should occur for interim analyses
• Provide input on parameters that would help to ensure data quality control

BCCC offers support for your REDCap implementation, as part of the Miami CTSI. This includes:

• Going over your project and helping you to design a database that will ensure all important data has a field and is uniformly coded.
• Setting up field validation and required fields to ensure all important items are filled out when populating.
• Setting up reports to determine state of data population.
• Programming branching logic to ensure that only fields relevant to an instance are displayed and filled out.
• Teaching you how to use other features such as the data exportation tool.
• REDCap is accessible to all UM Faculty, Staff, and Students. External users can also access REDCap if they have a CaneID. No access request form is required to log into this application. REDCap is an application that allows users to build and manage online surveys and databases quickly and securely.

All Fees are based on UM policy B020 for Recharge or Cost Centers (see page 28):

• An hourly rate of $105.00, for all support activities for University of Miami, and affiliated organizations and institutions;
• An hourly rate of $152.00, for all support activities for Non-University of Miami, and external non- affiliated organizations and institutions.

For example, the BCCC may be approached by a University of Miami Investigator to provide statistical support for a proposal development/grant application that the BCCC estimates to require 40 hours of work. Thus, we would charge 40*$105=$4200 for this support.

Billing & Procedure

User departments and/or sponsored accounts will be billed via Workday. The BCCC’s policy and procedure must be adhered to in order to receive core support. Outstanding bills (past one quarter) will lead to project termination and or denial of future support.

Forms of payment

The invoice will be created once a signed agreement has been sent to the BCCC Administrator. Invoice and billing will be submitted via Workday.

• BCCC Request Support Form (Common Intake Form)
  All required fields should be completed, and submitted. If the department has a collaboration plan, please select it in the intake form for approval, in order to receive support under their collaboration plan. Once the BCCC Administrator receives it, the initial meeting will be scheduled.
• BCCC Office Hours Support Form
  Complete the form to schedule an office meeting. Ensuring all required fields are filled, and then email the completed form to the BCCC Administrator at mjrodriguez@med.miami.edu.
• BCCC Agreement Support Form
  The form will be e-mailed to the investigator, by the BCCC Administrator, after the initial meeting. This will include a description of the proposed work; the corresponding BCCC time commitment estimated based on the initial meeting, and associated fees. The BCCC Support Agreement should include an account number, and authorized signature of the client(s), before any type of work can begin.
• BCCC Grant Submission Agreement Form (Non CTSI support and CTSI support)
  The form will be e-mailed, to the investigator, by the BCCC Administrator after the initial support has been completed, and when the investigator is ready to submit the grant.
• BCCC Collaboration Plan Agreement Form
  The form will be e-mailed to the investigator or the person responsible for the collaboration plan, once an agreement of the hours for the fiscal year has been established. This agreement should include a department account number, and the authorized signature of the account holder, before any type of work can begin.
• BCCC Authorization for Use of Existing Collaboration Plan Agreement Form
  The form will be received by the person responsible for the plan, upon request from the investigator on the intake form. This applies for anyone in their department that would like biostatistics support. Once the approval of the person responsible for the plan is submitted then the support will begin.