All IRB applications require a Principal Investigator (PI) who will be responsible for conducting and/or managing the research (or data request). Principal Investigators must have an account with IAMOnline to submit their application to the IRB. Information on how to create an IAMOnline account is available on the IRB website.

Provide the PI's institution in the organization field and organizational division. A division may be a program or unit within a company or a college within a university. If the PI does not have a division within their organization then provide the organization name.

All institutions listed on the IRB application (PI and research team) will be required to have an executed Memorandum of Understanding before any data are released by the Texas Department of State Health Services.

A student researcher is an individual enrolled in a university program where a research project is required for graduation. The student will be listed as the research project’s Principal Investigator.

Student projects must have a faculty advisor included on the study team as a co-investigator and an Academic Letter of Support. Include the Letter of Support as an attachment to the application (in the attachments section).

The DSHS IRB must ensure that all principal investigators maintain continuing knowledge of, and comply with, relevant Federal regulations, Office of Human Research Protections (OHRP) guidance, other applicable guidance, State and local law, and IRB determinations and policies for the protection of human subjects. The DSHS IRB must have documentation of such training for the Principal Investigator as a condition for conducting human subject research. This requirement can be met by completing a computer-based training program, or a seminar or class on human subjects protections and regulations. Information about training can be found on the DSHS IRB FAQ page.

The IRB will not accept training certificates that exceed three years from the issuance date.

Provide an appropriate title that reflects the study goals and subject matter.

The ‘project start date’ is the expected date when all project activities will start.

The ‘project end date’ is the expected date of completion of all project activities. This should not include data retention periods. In the protocol an estimated data destruction date is required, and this will cover any applicable data retention period.

Provide a brief (no more than 100 word) overview of the study design and purpose of the study.

Example:

1. This research is an analysis of mortality in 2020 and 2021, compared to a baseline of five prior years, to estimate excess mortality and economic impact from premature death among various Texas sub-populations. Statistical tests and data visualizations of state-level aggregate data will be used to understand mortality disparity trends among Texas populations, as well as to determine excess mortality in 2020 among different Texas geographic areas and for different demographic groups. In addition, differences in mortality numbers/rates for broad cause of death categories and by place of death in 2020 and 2021 will be ascertained.
    
2. Cancer remains the leading cause of death by disease among children. Therefore, new efforts are needed to improve outcomes in these individuals. It has been estimated  that approximately 10% of children diagnosed with cancer have a cancer predisposition syndrome (CPS). However, there are no population-based estimates to confirm this, which limits screening and surveillance strategies and ultimately impacts outcomes. We propose leveraging newborn screening (NBS) blood spots in Texas, linked to the Texas Cancer Registry (TCR), to estimate the proportion of children diagnosed with cancer who also have a CPS.
    
3. While a suspected component for most birth defects, the genetic contribution to risk is unknown in the majority of affected individuals. Despite technological advances that have reduced the cost of genome sequencing, there have been few population-based efforts to confirm these estimates. This is especially true for children born with multiple congenital anomalies (MCAs) and less common birth defects. In this study, we would like to identify families of children with birth defects through the Texas Birth Defects Registry (TBDR) for the purpose of contacting and enrolling these subjects to better characterize the causes underlying these conditions.
    
4. The study will use the existing THCIC hospital discharge and outpatient research data files to identify unduplicated, age specific, and disease specific discharges for the uninsured population by targeted diseases. Identifying these data will assist with understanding the size and disease burden of the uninsured population in Texas. These data are necessary to support planning for the ABC Program transition process and to assist with further delivery system reform after the ABC Program ends.

Provide the complete name for your primary funder. Please do not include acronyms. For example, “NIH” should be written as “National Institutes of Health”. Please enter “N/A” if not applicable.

Please provide the names of any programs and program staff that have helped you develop this application. This information will help IRB administration staff identify the appropriate program reviewers for your application.

Provide information on other IRBs that have reviewed your application and their determination. Please provide determination letters along with any other attachments. If your study has not been reviewed by any other IRBs, then enter “No other reviews.”

You can submit an IRB application to be reviewed by HHS programs while waiting for other IRB determinations, but the DSHS IRB will not review an application until all other IRBs determinations are complete.

Include information on the background, study rationale, and information on why this issue is important. Reviewers should be able to understand the “who, what, and why” for this study. The background should include summary information on the health topic (“who and what”). The rationale of a study should include information on a gap in current knowledge or a problem (the “why”).

You do not need to avoid technical terms, but IRB members may be unfamiliar with the topic, so the summary should provide reviewers with enough information to provide a general understanding.

Example:

1. This research hopes to improve on the growing body of COVID-19 knowledge by applying excess mortality analysis to various Texas populations. As public health programs work to understand the impact of COVID-19, a measure employed by the CDC and other agencies is estimation of excess death. Excess deaths are the difference between the observed and expected number of total deaths. However, these efforts typically report excess mortality for the total population in the United States and are not generalizable to sub-populations in Texas. We also plan to  examine two factors that could better explain any excess mortality observed: changes in mortality by cause of death and by place of death. These can help to determine whether increases in mortality were caused by COVID-19 directly (e.g., an increase in deaths due to respiratory illness) or indirectly (e.g., by delayed/lack of access to appropriate care or emergency services). Lastly, we hope to gain a better understanding of the long-term economic impacts of COVID-19 from productivity loss due to excess premature deaths.

Provide all study research questions. A research question should be a question that you seek to answer with your research. Try to avoid questions that can be answered with a simple statistic or a yes/no answer. Research questions should be not be too general.

DSHS does not typically approve protocol amendments for additional questions which change the intention of a protocol. Researcher are asked to submit a new protocol application in these situations.

If your activity is not research, then please indicate if there are no research questions.

Examples:

1. 1) How have mortality rates among different Texas demographic groups (by sex, age, race/ethnicity, education) and geographic areas changed in 2020 and 2021 compared to mortality rates during 2015-2019? 
   
   2) How have mortality numbers/rates for different broad causes of death changed in 2020 compared to prior years (2015-2019)? 
   
   3) How have mortality numbers/rates by place of death (e.g., in the hospital, at home, other facilities) changed in 2020 and 2021 compared to prior years (2015-2019)?
    
2. Do genomic and related variations contribute to the development of isolated birth defects and/or multiple congenital anomalies? 
   
   Are there other phenotypic features that were not captured in the Texas Birth Defects Registry among children with birth defects and multiple congenital anomalies?
    
3. 1) What are the size and geographic spread of Texas’ uninsured population? 
   
   2) What is the extent of the disease burden for the uninsured population; in particular for a diagnosis of a chronic or behavioral disease? 
   
   3) How does this compare to the population covered by Medicaid or other insurance?

A hypothesis should be a testable statement related to your study purpose. A hypothesis proposes a relationship between an independent and dependent variable that will be tested. Some research is considered hypothesis generating and does not provide a hypothesis. In this case, provide information on what the work intends to investigate.

The DSHS IRB also reviews the release of personally identifiable data for non-research activities. If your activity is not research, then please provide information on what the work intends to investigate (if anything).

Example:

1. We hypothesize that mortality rates among Texas populations were higher in 2020 and 2021 compared to baseline 2015-2019 mortality rates. Increases in mortality are expected to be attributable to the COVID-19 pandemic, both directly (COVID-19 as cause of death) and indirectly (e.g., long-term health repercussions from the disease, lack of access to health care and emergency services, increase in domestic violence). Further, we hypothesize that differences in 2020 and 2021 mortality rates will likely be observed among Texas sub-populations (e.g., among different age and race/ethnic groups) and/or geographic areas (e.g., by health service region or urban vs. rural locations).
    
2. Our underlying hypothesis is that the development of birth defects is influenced by certain genetic factors. 

Please provide no more than five studies that support the background and premise of the research

The objective of the study is the purpose of your research. The objective should align with the study rationale provided in the study background (the “why"). The purpose of the study should address the gap in knowledge or problem identified in the background. The objective should identify your expected outcome (ie. benefit) of doing the research.

Each aim should align with a specific research question and provide an action that will be used to test the questions. Some researchers start every aim with “To…” to ensure that they write an action. Try to write aims that are independent and not require specific results of any other aim.

Examples:

1. Overall Objective: To assess potential changes in mortality among Texas populations and subpopulations in 2020 and 2021 compared with mortality during 2015-2019.
   
   Specific Aims: 
   a) To estimate excess deaths attributable to the COVID-19 pandemic in 2020 and 2021 among different sex, age, education level, and racial/ethnic populations, as well as among populations in different geographic areas in Texas; 
   
   b) To examine differences in mortality by broad causes of death in 2020 and 2021, compared with prior non-pandemic years (2015-2019); 
   
   c) To examine differences in mortality by place of death in 2020 and 2021, compared with prior non-pandemic years (2015-2019).
    
2. Our objective is to assess if screening for CPSs in NBS blood spots will help identify infants who are at risk for developing pediatric cancer. Currently, NBS blood spots are not used to determine cancer risk. Our specific aim is to use a CPS panel to sequence stored NBS blood spots (collected between 5/27/2009 to 12/31/2020) linked to the TCR to determine the frequency of CPSs among children diagnosed with cancer. We will focus on genes with surveillance recommendations: RET, RB1, TP53, DICER1, SUFU, PTCH1, SMARCB1, WT1, APC, ALK, and PHOX2B.
   
   Our primary aim is to identify genomic and related variation underlying isolated birth defects and multiple congenital anomalies and our secondary aim is to characterize phenotypic features not captured in the TBDR among children with birth defects and MCAs.

Provide any goals for this work.

Example:

1. To determine the impact of changes in mortality and economic impact from premature death in 2020 and 2021 in the context of the novel COVID-19 virus, and to examine factors that could better explain excess mortality observed.
    
2. Our goal is to determine the frequency of cancer predisposition syndromes among children with cancer in the state of Texas.

Please provide the information on the potential public health benefit of this work or how this work aligns with public health priorities.

Examples:

1. Results of the study will broaden knowledge of changes in mortality during 2020 and 2021 that are specific to Texas and Texas subpopulations, as well as knowledge of corresponding economic impacts. These data will help inform programmatic efforts to reduce impacts of COVID-19 among these populations. Data will also be used as part of a needs assessment and used to prioritize community activities.
    
2. Currently no newborn screening test for cancer risk exists in the United States. This study will estimate the proportion of children diagnosed with cancer who have a cancer predisposition syndrome and explore the feasibility of using newborn screening blood spots to screen infants for cancer predisposition syndrome in the future. If this were eventually implemented, cancer may be detected earlier in children, which could lead to improved outcomes within this population.

Risk is the probability of harm or injury (physical, psychological, social, or economic) occurring as a result of participation in a research study. Both the probability and magnitude of possible harm may vary from minimal to significant. Federal regulations define only "minimal risk."

The release of potentially identifiable information can always result in a loss of confidentiality.

Ways that risk can be minimized include controlled access to information (or patients), secure data storage, proper training, proper destruction of data, the release of datasets with the minimal amount of information necessary to conduct research, and following medically approved procedures.

Example:

1. This research will utilize a minimal individual-level Texas death dataset; only variables that are needed to answer our research questions are requested. If compromised, this information could potentially be used to personally identify Texas residents. However, this risk will be minimized by 1) storing these data on Company ABC network servers and accessing them using secure VPN, with data access restricted to only those individuals listed on the Research Team Log, 2) requesting no other personal identifiers except address information (needed for geocoding, obtaining census tract information, and double-checking county information for provisional data); and 3) reporting aggregate analysis results. In addition, all participants have taken Company ABC IT cybersecurity training and human subjects protection training.

2. This study will use already collected blood spot samples; therefore, no new samples will be obtained. All blood spots will be de-identified prior to sending to the research staff at University of ABC and no personally identifiable information (PII) or protected health information (PHI) will be provided. All electronic data will be securely stored on password and firewall protected Network-Attached Storage servers within University ABC. All newborn screening blood spots will be kept and managed based on unique subject ID numbers.

3. There are no physical risks to participate in this study. Breach of confidentiality is a possible risk. Every reasonable precaution will be taken to reduce this risk to a minimum. The research data will not be added to the subjects' medical records. Paper files will be kept locked in secured Baylor College of Medicine (BCM) facilities in Houston, TX. Computer files containing research data will be maintained in the computer system of BCM, and will be password protected. Access to the research data will be strictly limited to the PI and his designees only. The samples accrued in the study, and the information obtained from the questionnaire will be kept and managed based on unique subject ID numbers. Study results that may be published will remain anonymous. 

   Other risk relates to possible psychological distress of the subject's parent(s) in participating in the questionnaire which asks questions regarding the use of assisted reproductive therapy and information on personal or family history of birth defects. These types of questions may be unpleasant for some participants. Participants will be given the opportunity to decline answering any questions that they are uncomfortable answering on the questionnaire.

A benefit is a valued or desired outcome; an advantage. Benefits may include new scientific knowledge, development of improved public health processes, and new medical procedures.

Example:

1. The expected outcome of this research is to provide a greater understanding of excess deaths in 2020 and 2021 in Texas as a whole, as well as among several different Texas subpopulations. This information will be used by Company ABC to inform the development of organizational programming to address disparity and need.
    
2. This study will not provide any direct benefits to individuals. However, if screening for cancer predisposition syndromes in newborn screening blood spots is deemed feasible and implemented in the future, childhood cancer cases may be diagnosed earlier, which could lead to improved outcomes. 
    
3. There will be no direct benefit to the individual subject. The identification of genetic contributions to birth defects will add significantly to our knowledge about the etiology of these conditions. This work could ultimately inform genetic testing, counseling strategies, and treatment decisions. We believe the potential benefits from this study measurably outweigh any physical or emotional harm.

Please include detail in this section, such as what types of data you will be requesting from the Texas Department of State Health Services (DSHS) or Health and Human Services Commission (HHSC). If your study has multiple research questions, please provide information on which population will be studied for each question.

Examples:

1. We are requesting death records for all Texas residents from 2015-2021, regardless of age, sex, race/ethnicity, and geography. Below is information on key demographic characteristics by research question:
   
   Research Question 1: Texas resident deaths among males and females aged 0-18 and females aged 15-45. 
   
   Research Questions 2-5: All Texas resident deaths, regardless of age, sex, race/ethnicity, education level attained, and geographic location. We will stratify deaths by these characteristics, as well as by broad causes of death and place of death, but we will examine all Texas resident deaths for these analyses.
    
2. We are requesting newborn screening blood spots collected from infants born in Texas between 5/27/2009-12/31/2020, which are stored as part of the Texas Department of State Health Services (DSHS) Newborn Screening Program with their parents’ consent (through the Parent Decision Form for Storage and Use of Newborn Screening Blood Spot Card). Additionally, the DSHS Newborn Screening Program will only release records that have a match with Texas Cancer Registry (TCR) records and the TCR will only release records that have a match with the Newborn Screening Program records. Information on cancers diagnosed between 5/27/2009-12/31/2020 will also be obtained from the TCR. There will be no restriction based on gender, race, ethnicity, or geography.
    
3. The subject population is inpatient and outpatient discharges by targeted conditions for the most recent three years of data available for the entire state of Texas. To the extent possible, these data will be differentiated by age, gender, race/ethnicity, county, and health coverage (Medicaid, other insured, and uninsured). Data for subjects with the targeted conditions will be compared with data for subjects without the targeted conditions.

Control groups can mean different things depending on the type of research that you are conducting. Generally speaking, a control group is comparable to the individuals being studied or is the population that doesn’t have an intervention or exposure.

If your study does not have a control group, you can enter “Not applicable- no control group will be used.”

Example:

1. No control group will be used, but 2020 and 2021 mortality data will be compared separately with mortality data during 2015-2019. Comparison groups will include mortalities in Texas as a whole in 2015-2019, as well as mortalities among corresponding age, sex, geographic, education level, and race/ethnic populations during those years. Population estimates for 2015-2021 (used in calculating mortality rates) will be obtained from the Texas Demographic Center.
    
2. There will be no control group included. We are evaluating the frequency of CPSs among children born and diagnosed with cancer in Texas.

Inclusion criteria define who will be included in your study. This is often determined by demographic characteristics, but may also be defined by characteristics such as disease status or disease stage. These criteria are established by researchers to ensure that the study population is relevant to the research question and that the results can be meaningfully applied to the intended population.

Example:

1. Inclusion criteria by research question are below: 
   
   Research Question 1: All Texas residents who died in 2015-2021 and were either a) 0 - 18 years of age at time of death (males and females) or b) females ages 15-45 at time of death will be included in analyses. 
   
   Research Questions 2-5: All Texas residents who died in 2015-2021 will be included in analyses.
    
2. All children born in Texas between 5/27/2009 and 12/31/2020 who were diagnosed with cancer and have available stored Newborn Screening blood spots. 
    
3. All birth, fetal death, and linked birth-infant death (BID) records of Texas residents collected by the DSHS Bureau of Vital Statistics for CY 2011 and 2012 are required for this study. 
    
4. The subject population will include individuals with a diagnosis of one or more of the following conditions: diabetes type 1 or 2; chronic heart disease: CHF, angina, hypertension, ASCVD, hypercholesterolemia; asthma; one or more of any chronic disease: diabetes, heart disease, asthma, COPD; and one or more chronic disease; and chronic hepatitis C.

Exclusion criteria define who will be removed from your study population. Individuals may be excluded based on demographic characteristics, disease status, death, or other reasons.

Example:

1. Overall, Texas residents who did not die between January 1, 2015 and December 31, 2021 are excluded from this request and study analyses, as are all non-Texas residents.
   
   Further information regarding exclusion criteria by research question is below: 
   
   Research Question 1: Deaths not occurring in Texas and deaths to non-Texas residents will be excluded, as well as deaths occurring among males 19+ years of age and among females over 45 years of age. 
   
   Research Questions 2-5: Deaths not occurring in Texas and deaths to non-Texas residents will be excluded.
    
2. All infants born in Texas between 5/27/2009 to 12/31/2020 without stored NBS blood spot samples and/or not diagnosed with cancer.

Provide your best estimate of the total number of individuals’ records that are requested as part of this application. If you are requesting multiple records for each individual, then provide that information in the next question. If no Texas HHS data are requested then enter 0.

You can provide more detailed information in the next question.

Please provide specific information on specific datasets that will be requested from HHS. For each dataset provide information on the years (or dates) requested and generally which data are requested (demographic, disease stage, disease characteristics, geospatial, etc). Programs may require forms in which you will indicate the specific variables you are requesting. If a program has a data request form you must include it with the IRB submission.

If your study requires linkage between datasets please indicate which data will be requested for the linkage, which variables will be used for linking from the datasets, and who is linking the data. Indicate if programs are destroying the linking variable or if you are requesting that the linking variable be included with data submissions. Information on the data linking plan can be provided in the question “Describe the statistical analysis plan.” Some projects have complex data linking plans. Researchers can include an attachment with specific details (including variable information, diagrams, etc.) with their application.

Some HHS-managed data cannot be released to researchers due to federal or state law. Please contact DSHS programs to ensure that the data are releasable.

Example:

1. We request data on an estimated 1,342,000 deaths among Texas residents from 2015-2021.
   
   Below are the estimated number of deaths requested by research question: 
   
   Research Question 1: 100,000 
   
   Research Questions 2-5: 1,342,000 
   
   CHS finalized and provisional mortality data for 2015-2021 are requested for this study. For years where finalized datasets are available, only finalized data are requested. If finalized datasets are not available (e.g., 2020), provisional death datasets are requested instead. Data requested are one record per person. Death data requested include demographic data (age, sex, race/ethnicity, education), cause of death information, geographic identifiers (resident address, location of death), and information on the date of death. Specific requested data elements are indicated on the attached Checklist for Death Data.
    
2. We will sequence available stored NBS blood spots (using a CPS panel described in Section IX (Design and Methodology) from children born in Texas between 5/27/2009-12/31/2020. Based on the current number of pediatric cancer cases diagnosed per year in Texas who were also born in the state (~1,500), the proportion of individuals who consent for blood spot storage (~40% since 2012), and the proposed time period (2009-2020), we estimate we will receive NBS blood spots on 6,000 children diagnosed with cancer.
    
3. We estimate that there will be between 60 to 70 million inpatient and outpatient records for the three-year time frame but are uncertain how many distinct subjects will be included.

Specify the years of data requested and which years of data correspond to which datasets (if not specified above). Consult with the programs to determine if data are available.

Researchers can request data that are not yet available, but should be aware of analysis limitations.

Provide information on the proposed study design. Studies maybe classified as descriptive, analytic, cohort, case-control, cross-sectional, ecologic, intervention/experiment, retrospective, or another design type. Many studies that utilize data from the Texas Department of State Health Services that analyze registry data are retrospective studies (case-control, longitudinal, or cross-sectional) studies. However, some studies may use registry data to contact participants and are prospective cohort or cross-sectional studies.

Example:

1. This is a population-based retrospective epidemiologic and economic study to examine differences in mortality and economic cost of premature death in 2020 and 2021 compared to prior years.

Provide general information about the intervention or experiment (if applicable). If your study uses DSHS or HSHC data for recruitment, then additional recruitment details will be requested later in the application. If your application does not include an intervention or any experimental procedures, then indicate “Not applicable. There are no intervention or experimental procedures.”

Provide information about data used for this protocol for each research question unless all data are used for all questions. Provide specific variables unless that information is listed in a data request checklist. Provide detail if your analysis utilizes data from multiple sources (ex. air quality data, Census data, interview responses).

Some datasets contain similar information (ex. race and ethnicity is available in Census data products, vital event files, hospital discharge records, etc.). Please provide details on which datasets provide the information used in analysis.

Example:

1. Death records data are requested from the DSHS Center for Health Statistics. Requested vital event death data elements are indicated on the attached Checklist for Death Data. The Texas Demographic Center webpage will provide all Texas population estimates used in analyses Population-level employment data used for economic analyses (county-level average annual wages, labor force participation, unemployment rates, etc.) will come from the U.S. Bureau of Labor Statistics.
   
   Death data elements to be utilized in specific research questions include: 
   
   Research Question 1: Age, sex, race/ethnicity, residence location, date of death 
   
   Research Question 2: Age, sex, race/ethnicity, education, residence location, date of death 
   
   Research Question 3: Age, sex, race/ethnicity, residence location, cause of death, date of death. For this research question, we will use information on cause of death from death records to examine mortality numbers and rates for several cause-of-death categories, including: malignant neoplasms, heart disease, cerebrovascular disease, COVID-19, flu & pneumonia, chronic lower respiratory diseases, other respiratory diseases, sepsis (septicemia), Alzheimer’s, diabetes, kidney diseases, and others. We will also examine mortality numbers and rates for all natural causes together (illness, medical causes) and all external causes together (injuries, homicide, suicide). 
   
   Research Question 4: Age, sex, race/ethnicity, residence location, cause of death, location of death, date of death 
   
   Research Question 5: Age, sex, race/ethnicity, education, residence location, date of death 

All DSHS data, except for suppressed publicly available aggregate data, is considered identifiable. In certain presentations of data, the combination of values can pinpoint just one or a few cases (e.g. a rare cancer in a small town). Even if the personal identifiable information (PII) is removed from the data set, the data are potentially identifiable. Therefore, all DSHS data are considered identifiable and should be treated as such. All identifiable data requires an IRB submission. Suppressed aggregate data are available to the public and does not require an IRB determination.

Provide a justification for the release of PII or confidential data and how the research could not be conducted with aggregate or non-deidentified data.

Example:

1. The 2020 and 2021 vital event data are not finalized, so address information is required to geocode the data to obtain geographic indicators comparable to stat-locked death files. Individual-level characteristics (race/ethnicity, educational attainment, etc.) are necessary to understand how Covid-19 may have disparate impacts on Texas populations. Additionally, the Farrington methods to calculate excess mortality utilize weekly counts. These counts are likely to be smaller than standard suppression guidelines for some sub-groups analyzed in these research questions. Suppression of these data would result in less accurate estimates of excess mortality and possible errors in software algorithms; this is one reason we are requesting individual-level records rather than aggregate numbers.
    
2. To be able to deduplicate discharges and provide distinct counts of clients by diagnoses.  This information will be used to determine key populations that would benefit from additional and/or enhanced state services related to the ABC Program transition.

Provide sufficient information so that the IRB can review the protocol and determine if the research can be conducted with the requested data elements in the proposed timeline. Researchers should provide information on all relevant methods used in the protocol including: descriptive analysis, data linking, data cleaning, statistical analysis, data visualization, software, missing data analysis, and any relevant information.

Example:

1. Descriptive analysis will be conducted to assess mortality trends in each year by the individual characteristics described previously. Counts, rates, means, standard deviations, and/or medians will be presented. Statistical tests for excess mortality will utilize Farrington methods to calculate excess mortality by calculating the difference between the number of expected deaths and the observed number of deaths in 2020 and 2021 (separately). Confidence intervals will be calculated and presented in the results. A p-score will be calculated to measure excess mortality. The P-score gives the percentage difference between deaths that occurred in 2020 and 2021 and the average number of deaths in 2015-2019.
   
   Counts will be aggregated by week and characteristics relevant to the research question. Deaths and mortality rates will be presented for populations by week and/or year. If weekly death numbers/rates are too small for publication, then data will be aggregated by month or by year. Results will be interpreted to identify individual characteristics and time periods (weeks or months) when deaths exceeded expected mortality. 
   
   The R “surveillance” package contains the Farrington methods to calculate excess mortality and will be utilized. 
   
   Statistical adjustments may be performed for annual population increases in Texas. Estimation of the lifetime productivity loss due to premature death will be estimated for individuals under 65 years of age, the assumed age of retirement, following standard procedures. Age-specific estimates of lifetime productivity loss discounted back to the year of death will be estimated using publicly available data on average annual wages, labor participation, and unemployment rates at the county level from the U.S. Bureau of Labor Statistics. 
   
   Results will be presented in charts and maps. Charts will display weekly, monthly, and/or yearly deaths and excess deaths; however, counts will not be presented on maps and graphs if the values do not meet minimum size requirements. Maps will present rates from all counties, but will be categorized into intervals that best represent the shape of the distribution of excess deaths.
    
2. Frequency tables (counts) of targeted conditions for the most recent three years of data available for the entire state of Texas will be developed. To the extent possible, these data will be differentiated by diagnosis, age, gender, race/ethnicity, county, and health coverage (Medicaid, other insured, and uninsured). Targeted conditions include: diabetes type 1 or 2; chronic heart disease: CHF, angina, hypertension, ASCVD, hypercholesterolemia; asthma; one or more of any chronic disease: diabetes, heart disease, asthma, COPD; and one or more chronic disease; and chronic hepatitis C.

Provide any power calculations (if applicable). The data request should be sufficient per the provided power-test results. If no power test was run, then indicate if no power analysis was conducted and provide a justification.

Example:

1. The complete cohort of deaths in Texas is requested to understand true changes in mortality in the state. Since this study uses the complete population, differences are the true difference and not subject to sampling error or level of significance.

Provide information on the statistical tests that will be utilized in the study. Please do not copy and paste your analysis plan from the previous question.

Example:

1. Farrington methods implemented in the R surveillance package will be utilized to calculate excess mortality. For some research questions, excess mortality may also be measured using P-scores. Data will be screened to assess completeness by checking for mortality data from all requested time intervals. Statistical tests assume completeness of the data and comparability among years used to calculate baseline mortality.
    
2. We do not anticipate running any statistical tests.  Frequency tables (counts) of targeted conditions for the most recent three years of data available for the entire state of Texas will be developed.

Provide a brief description of the expected results. The results should be aligned with study research questions.

Example:

1. We expect that mortality rates in 2020 and 2021, and thus the economic impact of premature death, will be higher than baseline mortality rates for many age/sex, geographic, education level, and race/ethnicity cohorts; we also expect that there will be demographic and geographic disparities among mortality rates in 2020 and 2021. We expect difference in causes of mortality consistent with conditions associated with Covid-19. Additionally, we expect locations of death to differ between 2020 and 2021 and prior years, with higher mortality hypothesized in nursing homes and hospitals.

Programs can provide information on how data or biospecimens can be transferred to your organization. Some programs have established methods for transferring data or biospecimens. Data will be transferred with encrypted, secure methods.

Example:

1. Data will be transferred via HHS GlobalScape EDTS SFTP or another data transmission mechanism approved by DSHS. The principal investigator will download the data to a secure location on the university network.
2. Blood spots, which will be mailed to the PI, will be stored at -80 degrees Celsius and labeled with a code that does not include personally identifiable information (PII) or protected health information (PHI). Electronic data will be transferred through the HHS Gateway Portal, which is a Secure File Transfer Protocol (SFTP).

HHS data and biospecimens are expected to be securely stored in a restricted-access environment. Please provide as much information on where data or biospecimens are stored.

If data are stored on cloud-based servers please provide information on the system and whether servers are US-based or data can be stored in multiple countries. Data are expected to be stored on US-based servers, unless study specifics require data to be stored outside the US.

Example:

1. The data files will be stored on Company ABC’s restricted-access file server located in Winters Building C. Company ABC IT will create the secure network folder when the IRB application is approved. Only individuals identified in these IRB documents will have access to this folder. All research team members listed on HRP 306 Research Team Log will use password-protected computers to access data files via VPN.
    
2. Blood spots, which will be mailed to the PI, will be stored at -80 degrees Celsius and labeled with a code that does not include any PII or PHI. Electronic data will be stored in password-protected files, on password-protected Baylor College of Medicine computer servers.

Researchers must provide information on data security and how individuals securely access data or biospecimens. 

Researchers are encouraged to provide information on:

• Encryption standards
• Any security training
• Any NIST protocols utilized by your organization

Examples:

1. All research team members will follow all Company ABC confidentiality and data security requirements.
   
   The data files will be stored on a Company ABC restricted-access file server, and research team members will use password-protected computers to access data files via secure VPN. 
   
   Only research team members will have access to the requested data files.
    
2. The NBS blood spots, which will be mailed to the PI, will be stored at -80 degrees Celsius and labeled with a unique subject identifier that is both randomly assigned and does not include any PII or PHI. Additionally, all unused blood spot samples will be discarded by 12/31/2025. 
    
3. Only select members of Organization ABC will have access to the birth and fetal death data.  Data will be stored and run on a secure network and stand-alone server - each of which has multilevel password and firewall protection.  Once linked, a statistical/research file will be created and personal identifiers will be redacted.  These identifiers include any names, addresses, certificate numbers, plan identifiers, etc. that have been requested and are listed as confidential on the Electronic Birth and Fetal Death Records Field Forms as well as the BID files.  These data will be redacted from the working file once all necessary file linkages are made.  Identifiers will be retained on an original unaltered electronic file and stored in a secure and restricted environment as a backup to the working file and used only in the event that additional linkages must be made or original files are corrupted. 

Provide information on how your program will allocate resources to the study project to ensure that the study will complete in the estimated time frame, has the necessary management and staff, review processes, and any advisory committees.

Example:

1. The researchers will be allotted up to 10 hours of work a week. We hope to complete final drafts of manuscripts by February 2024. Drafts will be reviewed by all applicable Unit, Section, and Division leadership before journal submission.
   
   In addition to publishing results in peer-reviewed scientific journals, selected findings are expected to be included in Company ABC reports/publications, and may also be included in other organization publications.

All DSHS data, except for suppressed publicly available aggregate data, are considered identifiable. Research results from PII data are expected to be suppressed such that individuals cannot be identified. DSHS does not have a standard suppression policy, but programs can provide guidance on appropriate suppression such that individual information is protected.

Explicitly state a specific number that you will use as a cutoff for suppression. If producing maps, provide specific detail on how you will protect the privacy of individuals in your maps, such as through suppression of cell counts (provide the threshold used for suppression) and/or mapping techniques (aggregation, blurring, perturbation, coarsening geographic scale).

Example:

1. Only aggregate results will be published. No counts will be reported if the cell size is less than 10.
    
2. No personally identifiable information will be published. Research data will be identified through study identification numbers only, and results will be reported only in aggregate. Additionally, no cells with <5 observations will be reported.

Provide information on your programs plans for publishing results including whether you intend to present at conferences, publish in journals, use data for legislative reports, white papers, present at community meetings, or through other means.

Publications are expected to be included when submitting renewal or study closure applications.

Example:

1. Findings from these studies will be published in scientific journals, presented at academic conferences, and in Company ABC reports and presentations.
    
2. After the analyses are completed, we will submit a manuscript detailing our findings to a peer-reviewed journal. Aggregate study results may also be shared orally or in print at scientific conferences.

Provide a plan for when you will destroy data. Some studies require all data for the duration of a study while others do not. Please provide information on any federal law, state law, or institutional requirements that require data to be retained.

Example:

1. The requested vital events data will be retained for the duration of the project. Once individual addresses have been geocoded and appropriate census tract and county information identified, address information will be deleted from the file. At the termination of the project all electronic copies of the data will be securely deleted using agency-approved file deletion software.

All HHS data are expected to be securely destroyed before study closure. Please provide specific software that will be used (or expected to be used) to securely destroy the data. If your IT does not provide tools to securely destroy the data, then you will need to provide information on how the data will be destroyed and made unrecoverable. If data are stored in cloud-based systems please provide information on how destroyed data are unrecoverable. Your IT department may have documentation that can describe how data are destroyed.

Example:

1. C Cleaner or other approved software will be used to securely delete all data following Company ABC IT policies and procedures.
    
2. The dataset received from the TCR will be destroyed using DOD Wipe, which is software that overwrites the data multiple times using zeros.

Hard copies or magnetic media are expected to be destroyed or unrecoverable before study closure. Please describe any methods utilized to make information unrecoverable. Please indicate if no hard copies or magnetic media will be utilized.

Example:

1. This study does not expect to utilize any hard copies. Any paper products will be destroyed using a cross-cut shredder.

Biospecimens provided by HHS are expected to be destroyed before study closure. Please describe any methods utilized to destroy biospecimens. Please indicate if your study will not include any biospecimens.

Example:

1. Not applicable- this study will not utilize any biospecimens.
    
2. All unused blood spots will be stripped of labels and discarded in biohazard waste.

Please provide an estimated data destruction date.

The ‘data destruction date’ is when the investigator no longer needs to hold the data. The data is destroyed, and the IRB is closed. The ‘project end date’ is when all project activities have been completed, but the researcher needs to retain the data for retention purposes.

HHS expects all data to be destroyed before study closure. If your program incorporates HHS data into databases or other files, the study will need to remain renewed until the database or files are destroyed.

Provide a summary of the informed consent process (if applicable).

Example:

1. No study subjects will be contacted, and a waiver of informed consent is included in this application.

Generally, researchers choose only one of the following:

• Written Informed Consent Document(s) to be Signed by Subjects
• Waiver of Informed Consent
• Waiver of Documentation of Informed Consent
• Alteration of Informed Consent

It is uncommon, but some multi-stage research activities that involve recruitment and secondary data analysis may choose more than one. Generally, these researchers request a Waiver of Informed Consent for secondary data analysis and provide an Informed Consent documentation or request an Alternation of Informed Consent.

Unless waived by the IRB, researchers are expected to obtain informed consent from all study participants. Please select “Written Informed Consent Document(s) to be Signed by Subjects” or the appropriate waiver request.

Selecting “Waiver of Informed Consent” requests the IRB to approve participant inclusion in the research without first obtaining approval by each study participant. Not every study can qualify for a waiver of informed consent and these studies typically involve the use of secondary datasets (ie. registry or administrative data).

Unless waived by the IRB, all researchers are required to keep documentation that an individual signed their consent form. Federal regulations (46.CFR.117(c)) provide three reasons when a researcher can waiver documentation of informed consent: 1) there is potential harm in maintaining the documentation, 2) the research is no more than minimal harm and involves activities that normally wouldn’t require consent, and 3) when signing a document is against cultural norms. Selecting “Waiver of Documentation of Informed Consent” indicates that one of the following reasons would apply to your research.

Selecting Alteration of Informed Consent indicates that you are obtaining and documenting informed consent, but are requesting to omit or alter some required elements of the informed consent documents.

Select “Yes” or “No” as appropriate. Selecting “Yes” will require you to provide additional detail on the recruitment protocol.

Individuals who meet any of the following criteria should be in the Personnel Table:

• Participate in the protocol design
• Interact with any human subject for research purposes
• Obtain the informed consent of human subjects for research purposes
• Obtain identifiable information and biospecimens for research purposes
• Access, use, study, and analyze identifiable information and biospecimens

 The Start Date is when the member is added to the team.

Per DSHS IRB rules, the IRB will not accept training certificates that exceed three years from the issuance date. If you have any questions about the appropriateness of a training certificate, please refer to the IRB FAQ page or contact the IRB administrator.

The following documents are required if applicable to the study and/or investigators.

• DSHS/HHSC Program Data Checklist (if required by DSHS/HHSC program)
• Other IRB Determination Letters (most recent date)
• Conflicts of Interest Disclosure Letter
• Academic Letter of Support (if principal investigator is a student)
• Principal Institution Protocol (most recent version)
• Vendor Information Form (if an initial application)
• Consent Forms
• Translation Certification Form

Please provide a Vendor Information Form for each institution represented in the personnel table.

HHS expects researchers to acknowledge and agree to all IRB requirements. Please contact the DSHS IRB administrator if there are questions or concerns about any IRB requirement.

If a conflict of interest is reported then the PI is expected to include a Conflict of Interest Letter as an attachment in this submission.

Choose one of the three reasons: Research on Public Health Benefit or Service Programs, Minimal Risk Research, or Screening, Recruiting or Determining Eligibility.

Research on Public Health Benefit or Service Programs:

The research or demonstration project is to be conducted by or is subject to the approval of state or local government officials and is designed to study, evaluate or otherwise examine (a) public benefit or service programs; (b) procedures for obtaining benefits or services under those programs; (c) possible changes in methods or levels of payment for benefits or services under those programs or procedures; or (d) possible changes in methods or levels of payment for benefits or services under those programs; and the research could not be carried out without the waiver or alteration.

Minimal Risk Research:

1. The research involves no more than minimal risk to the subjects.
2. The waiver or alteration will not adversely affect the rights and welfare of subjects.
3. The research could not practicably be carried out without the waiver or alteration.
4. If the research involves using identifiable private information or identifiable biospecimens, the research could not practicably be carried out without using such information or biospecimens in an identifiable format.
5. Whenever appropriate, subjects or legally authorized representatives will be provided with additional pertinent information after participation.

Screening, Recruiting or Determining Eligibility:

The investigator will obtain information or biospecimens for the purpose of screening, recruiting, or determining the eligibility of prospective subjects if either of the following are met:

1. The investigator will obtain information through oral or written communication with the prospective subject or legally authorized representative, or
2. The investigator will obtain identifiable private information or identifiable biospecimens by accessing records or stored biospecimens.

If selecting Research on Public Health Benefit or Service Programs provide justification for at least one of the four eligible study focuses and addresses how the research could not be carried out without the waiver or alteration. The four eligible study focuses are mentioned under “Research on Public Health Benefit or Service Programs” above.

If selecting Minimal Risk Research provide a justification for minimal risk research that addresses each of the 5 bullet points. The 5 bullet points are mentioned under “Minimal Risk Research” above.

If selecting Screening, Recruiting or Determining Eligibility provide a justification that addresses the two bullet points. The two bullet points are mentioned under “Screening, Recruiting or Determining Eligibility” above.

Example Justifications Waiving Informed Consent:

1. The research involves no more than minimal risk to the subjects and could not practicably be carried out without the waiver or alteration. Requested data are only provided in aggregate. Depending on the size of cells, the data may not be considered confidential per standard DSHS Center for Health Statistics suppression standards. Risk of individual identification is minimal.
    
2. The receipt and use of newborn screening blood spots involves no more than minimal risk. No PHI or PII will be provided to the University ABC research staff and therefore, subjects will not be directly contacted for this study. Additionally, the research could not practicably carried out without the waiver or alteration as this would require obtaining information on all children born in Texas with stored NBS blood spots during the period of 5/27/2009-12/31/2020, whom were also diagnosed with cancer. Therefore, it is not feasible to conduct this research without the waiver of consent.
   
   This waiver will not adversely affect the rights and welfare of the subjects. All electronic data will be securely stored electronically on password and firewall protected Network-Attached Storage servers at University ABC. The computer files will be password-protected to ensure database security, and access will be limited to authorized individuals. Blood spots will be mailed to the PI and labeled with a code that does not include any PII or PHI.

Informed consent documents need to be submitted as attachments with this application.

Select Yes or No depending on whether the statement is included in the informed consent document. Provide a justification for each statement not included in the informed consent document.

The IRB determines if a study is considered minimal risk, but please indicate if you anticipate that your study is more than minimal risk.

“Minimal risk means that the probability and magnitude of harm or discomfort anticipated in the research are not greater in and of themselves than those ordinarily encountered in daily life or during the performance of routine physical or psychological examinations or tests.” 45.CFR.46.102(j)

Please select the appropriate option as indicated in your consent form.

Please select the appropriate choice. You will be asked about inclusion of FDA required consent form statements if you indicate that your research is FDA regulated.

Federal regulations identify additional elements of informed consent to be included for a Food and Drug Administration (FDA) regulated study, when appropriate. Select “Included” if the statement is appropriate and included in the consent form. Selecting “Not Appropriate” indicates that the statement is not appropriate and was not included in the form.

The following statements must be added to the Basic Elements of Informed Consent, if applicable. Choose “Included” if the statement was included. Click ”Not Applicable” if the statement is not applicable.

Provide information on how subjects will be identified.

Provide information on which HHS datasets will be utilized for recruiting. For each dataset include information on which variables will be utilized for recruiting.

Please provide information on whether information will be utilized in letters, telephone calls, postcards, or other communication.

Please provide information on the number of individuals that are expected to be recruited for this study. Please provide information on the overall recruitment goals (for all sites) and how many are expected from HHS information.

Please provide detailed information on any phone calls, mailings, or other interactions to recruit individuals to the study. Please provide the number of attempted contacts and intervals between attempted contacts. Please detail any pre-screening processes.

Please provide all compensation information.

‘“[F]ollow-back” refers to the process of contacting a physician, abstractor, or reporting facility to obtain missing information or to resolve inconsistencies in data.’ SEER Guidance

Please provide any information on any follow-back process.

Please provide any information on how risk associated with the disclosure of PII will be minimized. Also include methods to minimize PII risk including controlled access to PII, proper training, following approved protocols, and other relevant materials.