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CalRedi collects data rapidly to look out for disease outbreaks. They collect data from state and local levels in California. 

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CalRedi collects data rapidly to look out for disease outbreaks. They collect data from state and local levels in California. 

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Centers for Disease Control and Prevention (CDC)

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Modernizing disease surveillance in California

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Goal of HIE to promote readiness in the medical community

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Goal of HIE to promote readiness in the medical community

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How interoperability & data sharing can improve patient safety

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CDC tools for Patient Health Information Network Vocabulary Access and Distribution System (PHIN VADS) is a directory of standard vocabulary use to better share data. This would help greatly in providing quick feedback. 

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CDC tools for Patient Health Information Network Vocabulary Access and Distribution System (PHIN VADS) is a directory of standard vocabulary use to better share data. This would help greatly in providing quick feedback. 

# data[].attributes.attachment_link.readable_text
PHIN VADS provides standard vocabularies to CDC and its public health partners in one place. PHIN VADS is a web-based enterprise vocabulary system for accessing, searching, and distributing vocabularies used in public health and clinical care practice. It promotes the use of standards-based vocabulary to support the exchange of consistent information among public health partners. Currently, there are 206 code systems, 1,506 value sets, 77 views and more than 5 million concepts in PHIN VADS based on the code system/domain recommendations and value set recommendations from Health Information Technology Standards Panel (HITSP) C80 specificationexternal icon . Users can access and view vocabularies in the context of public health with file download options for Value Sets, Value Set Concepts, Views and Groups available in a tab-delimited text format and also in Microsoft Excel format (additional download file formats are scheduled for a future release of PHIN VADS). The main purpose of PHIN VADS is to distribute the value sets associated with HL7 message implementation guides.

To access PHIN VADS, go to: http://phinvads.cdc.gov.

Release notes detailing changes of content and/or application updates in the current PHIN VADS release can be found in the PHIN VADS application via the 'Release Notes' link in the left navigation pane.

PHIN VADS Content and Resources

PHIN VADS provides all the vocabulary metadata needed for HL7 Messaging or Clinical Document Architecture (CDA). Users can navigate and download value sets based on HL7 Implementation Guides or PHIN Vocabulary Groups (Domains).

Frequently Used PHIN VADS Content (Hot Topics)

PHIN VADS provides quick access to commonly and frequently used value sets and messaging guide vocabulary views in the home page ( http://phinvads.cdc.gov) under "Hot Topics." Some of the hot topics are listed below:

1. RCMT - Reportable Condition Mapping Table (RCMT) provides mapping between conditions and its associated lab test and results.

2. Public Health Meaningful Use vocabulary (Electronic Laboratory Reporting [ELR], Immunization and Syndromic Surveillance)

1. ELR HL7 2.5.1 - Value sets associated with Electronic Laboratory Reporting HL7 2.5.1 Implementation Guide.

2. Immunization HL7 2.5.1 - Value sets associated with Immunization HL7 2.5.1 implementation guide.

3. Syndromic Surveillance for Emergency Department (ED) and Urgent Care (UC) - Value sets associated with Syndromic Surveillance PHIN messaging guide.

4. Reporting to Central Cancer Registries - Value sets associated with Implementation Guide for Healthcare Provider Reporting to Central Cancer Registries (Release 1.0).

3. NHSN Healthcare Associated Infection (HAI) - All the value sets associated with National Healthcare Safety Network (NHSN) - Healthcare Associated Infection (HAI) - Release 5.

4. PHLIP Flu Lab Report Vocabulary - All the value sets associated with PHLIP Flu lab report HL7 message implementation guide.

PHIN VADS Web Service

The PHIN VADS web site is powered by an open web service that can be directly consumed by third party applications. These web services are public and built upon open standards such as HL7 Common Terminology Services (CTS) and IHE Sharing Value Set (SVS).

The VADS Web Service consists of an interface that defines the web methods that are available, the domain objects that represent vocabulary information, and data transfer objects (DTOs) to transfer data to and from the web service. Custom programs, applications, or data extraction scripts can be written to directly use PHIN VADS Web Services.

A sample web service code and a detailed application program interface (API) are available in the PHIN VADS Developer's Toolkit at the following PHIN VADS site: http://phinvads.cdc.gov/vads/developersGuide.action.

Contacting Us

To report issues or questions contact the VADS team at phinvs@cdc.gov. Enhancement Requests/Defect Reports can also be submitted to the PHIN VADS team using this same email address with the subject header: Enhancement or Defect.

# data[].attributes.attachment_link.description
PHIN VADS provides standard vocabularies to CDC and its public health partners in one place. PHIN VADS is a web-based enterprise vocabulary system for accessing, searching, and distributing vocabularies used in public health and clinical care practice. It promotes the use of standards-based vocabulary to support the exchange of consistent information among public health partners.

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And article on employee risk assessment with feedback. 

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And article on employee risk assessment with feedback. 

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The Guide to Community Preventive Services (The Community Guide)

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Welcome to The Community Guide! Let us know what you think of the website by completing this quick survey.

Tabs

Snapshot

Summary of CPSTF Finding

The Community Preventive Services Task Force (CPSTF) recommends the use of assessments of health risks with feedback when combined with health education programs, with or without additional interventions, on the basis of strong evidence of effectiveness in improving one or more health behaviors or conditions in populations of workers. Additionally, the CPSTF recommends the use of assessments of health risks with feedback when combined with health education programs to improve the following outcomes among participants:

Tobacco use (strong evidence of effectiveness)

Excessive alcohol use (sufficient evidence of effectiveness)

Seat belt use (sufficient evidence of effectiveness)

Dietary fat intake (strong evidence of effectiveness)

Blood pressure (strong evidence of effectiveness)

Cholesterol (strong evidence of effectiveness)

Number of days lost from work due to illness or disability (strong evidence of effectiveness)

Healthcare services use (sufficient evidence of effectiveness)

Summary health risk estimates (sufficient evidence of effectiveness)

The CPSTF finds insufficient evidence for

Body composition

Consumption of fruit and vegetables

Fitness

The CPSTF has related findings for assessments of health risks with feedback when implemented alone (insufficient evidence).

Intervention

This intervention includes:

An assessment of personal health habits and risk factors (that may be used in combination with biomedical measurements of physiologic health)

A quantitative estimation or qualitative assessment of future risk of death and other adverse health outcomes

Provision of feedback in the form of educational messages and counseling that describes how changing one or more behavioral risk factors might change the risk of disease or death

Worksite interventions may use an assessment of health risks with feedback (AHRF) alone or as part of a broader worksite health promotion program that includes health education and other health promotion components offered as follow-up to the assessment.

CPSTF Finding and Rationale Statement

Read the full CPSTF Finding and Rationale Statement [PDF - 144 kB] for details including implementation issues, possible added benefits, potential harms, and evidence gaps.

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What the CPSTF Found

About The Systematic Review

The CPSTF finding is based on evidence from a systematic review of 51 studies (search period through June 2005). The review was conducted on behalf of the CPSTF by a team of specialists in systematic review methods, and in research, practice, and policy related to worksite health promotion.

Context

There is no information for this section.

Summary of Results

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement [PDF - 144 kB].

Fifty-one studies qualified for the review.

This review considered a range of outcome measures for each outcome category. Conclusions for each of these outcomes are based on a review of both quantified and qualitatively described results.

Health Behavior Outcomes

Dietary Behavior
Fourteen studies qualified for the review.

With the exception of one study that showed no change in intake of fruits and vegetables, changes in dietary behaviors were in favor of the intervention.

Intake of fruits and vegetables: median increase of 0.09 servings per day (6 studies)

Percent of employees with high risk fat intake: median relative decrease of 5.4% (interquartile interval: -21.9% to -1.8%; 13 studies)

Physical Activity
Eighteen studies qualified for the review.

The majority of results were in favor of the intervention.

Percent of employees who were physically active: median relative increase of 15.3% (interquartile interval: 8.3% to 37.2%; 16 study arms)

Tobacco Use
Twenty-nine studies qualified for the review.

All results were in favor of the intervention.

Prevalence rates (percent of employees who smoke): median relative decrease of 13.3% (interquartile interval: -24.0% to -3.3%; 27 study arms)

Cessation rates (percent of employees who quit):17.8% (interquartile interval: 12.0% to 22.6%; 21 study arms)

Physiologic Indicators

Blood Pressure
Thirty-one studies qualified for the review.

Results were in favor of the intervention.

Diastolic blood pressure: median decrease of 1.8 mm Hg (interquartile interval: -4.4 to -0.3 mm Hg; 22 study arms)

Systolic blood pressure: median decrease of 2.6 mm Hg (interquartile interval: -4.8 to -0.3 mm Hg; 24 study arms)

Change in prevalence rate of employees with high risk blood pressure reading: median decrease of 4.5 percentage points (interquartile interval: -8.7 to -0.4 percentage points; 16 study arms)

Body Composition (weight, body mass index [BMI] or percent body fat)
Twenty-seven studies qualified for the review.

Some of the results were in favor of the intervention and some were not.

Change in body weight: median decrease of 0.56 pounds (interquartile interval: -5.1 to +1.5 pounds; 17 study arms)

Change in BMI: median decrease of 0.50 points (interquartile interval: -1.1 to -0.3 points BMI)

Cholesterol
Twenty-seven studies qualified for the review

Results were in favor of the intervention.

Total cholesterol: median decrease of 4.8 mg/dL (interquartile interval: -10.4 to 0.0 mg/dL; 23 study arms)

HDL cholesterol: median increase of 0.94 mg/dL (interquartile interval: -0.9 to 2.3 mg/dL; 10 study arms)

Percent of employees with high risk readings: decrease of 6.6 percentage points (interquartile interval: -14.8 to -2.4 percentage points; 12 study arms)

Other Variables

Summary of Economic Evidence

Detailed results from the systematic review are available in the CPSTF Finding and Rationale Statement [PDF - 144 kB].

Nine studies qualified for the economic review. All monetary values are reported in 2005 U.S. dollars.

Program costs

Costs per participant per year ranged from $65 to $285 (7 studies).

Costs for per employee per year ranged from $40 to $234 (2 studies).

Program benefits

Benefits per participant per year ranged from $93 to $695 (7 studies).

Benefits per employee per year ranged from $160 to $272 (2 studies).

The benefit-to-cost ratio-defined as averted medical costs, productivity losses due to the program as both, divided by program costs-ranged from 1.4:1 to 4.6:1. This means that every dollar invested into the intervention yielded an annual gain between $1.40 and $4.60 (8 studies).

Applicability

Results from this review should be applicable to programs implemented in small, medium, or large companies in a range of settings.

Whites and African Americans were well represented among studies reporting information on race; however, there was not enough information available to determine if the intervention had differential effects for different racial or ethnic groups.

Evidence Gaps

Each Community Preventive Services Task Force (CPSTF) review identifies critical evidence gaps-areas where information is lacking. Evidence gaps can exist whether or not a recommendation is made. In cases when the CPSTF finds insufficient evidence to determine whether an intervention strategy works, evidence gaps encourage researchers and program evaluators to conduct more effectiveness studies. When the CPSTF recommends an intervention, evidence gaps highlight missing information that would help users determine if the intervention could meet their particular needs. For example, evidence may be needed to determine where the intervention will work, with which populations, how much it will cost to implement, whether it will provide adequate return on investment, or how users should structure or deliver the intervention to ensure effectiveness. Finally, evidence may be missing for outcomes different from those on which the CPSTF recommendation is based.
Identified Research Gaps The following outlines evidence gaps for assessment of health risks with feedback when used alone, and when combined with health education programs, with or without additional interventions.
This review of the use of assessments of health risks with feedback in worksite settings addressed important questions that earlier reviews were unable to address, such as:

Does AHRF, when used alone, lead to behavior change or change in health outcomes among employees?

Does this type of assessment, when used with other worksite-based intervention components result in change?

And finally, what types of behaviors or health outcomes are affected by these interventions?

The structure of this review, however, leaves two additional questions about worksite health promotion programs unanswered:

Are worksite health promotion programs with a health education component effective in the absence of AHRF and

Does AHRF add value to worksite health promotion programs with regards to behavior change and improvement in health outcomes?

The field will also likely be interested in addressing questions related to implementation of the intervention: what components are necessary and for whom are they most effective? How many times must AHRF occur and for how long must employees be exposed to additional intervention components? What qualifications of staff or health educators are needed? How long do the effects last? With regards to the assessment: Are there key assessment questions or aspects of the assessment (like biometric screening) that provide information resulting in a more effective intervention? Does the format of the questionnaire or the feedback make a difference? Is employee participation in creation of the program important and what role does organizational support play in participation rates and overall effectiveness?

Finally, questions regarding economic efficiency will be of interest to most in the field and should be addressed more systematically. A first step would be to clearly delineate the aspects of program costs and benefits that should be assessed in program evaluation. How many employees need to be reached for a positive ROI? What should the GRP (gross rating product) be for the ROI? Is there a "break even point" or a certain amount of time for which costs will outweigh benefits before there are actual savings from program implementation? Although the questions above stem from this review of assessments of health risk with feedback, many of them pertain to the broader field of worksite health promotion and can be used to inform future evaluation of these programs.

Study Characteristics

Of the 51 studies included in the AHRF Plus review:

Twenty studies included an untreated or lesser treated comparison group.

Five studies used a retrospective cohort.

Four studies were a time series study.

Twenty-two studies were included as before-after study designs.

Evaluated interventions were conducted in a variety of worksites including manufacturing plants, healthcare facilities, health insurance companies, government offices, field settings, banks, schools, and in an ambulance service workforce.

Most studies were conducted in companies or worksites with more than 500 employees and in urban or suburban settings.

Six studies were conducted in medium-sized companies (50 -499 employees) and one in a small company (50 employees).

Forty studies were conducted in the U.S., two in a group of European countries, two each in Australia and Finland, and one study was conducted in each of the following countries: Canada, Japan, the Netherlands, Sweden, and Switzerland.

Whites and African Americans were well represented among studies reporting information on race.

The average age of participants was 40 years, and a range of educational levels and job positions was represented.

Almost all of the evaluated interventions included health education lasting more than 1 hour or occurring at more than one time during the course of the intervention.

Health education was provided in group settings, one-on-one, or both.

Some of the evaluated interventions also provided enhanced access to physical activity (17 programs), nutrition (6 programs), and medical care (3 programs).

About one-third of the interventions offered some form of incentive or competition for participating or for meeting a program goal.

Publications

Supporting Materials

Analytic Framework

Analytic Framework [PDF - 324 kB] - see Figure 1 on page S241

Summary Evidence Table

Included Studies

The number of studies and publications do not always correspond (e.g., a publication may include several studies or one study may be explained in several publications).
Aldana SG, Greenlaw R, Diehl HA, Englert H, Jackson R. Impact of the Coronary Health Improvement Project (CHIP) on several employee populations. Journal of Occupational and Environmental Medicine 2002;44:831-9.

Aldana SG, Jacobson BH, Harris CJ, Kelley PL. Mobile work site health promotion programs can reduce selected employee health risks. Journal of Occupational Medicine 1993;35:922-8.

Aldana SG, Jacobson BH, Kelley PL, Quirk M. The effectiveness of a mobile worksite health promotion program in lowering employee health risk. American Journal of Health Promotion 1994;8:254-6.

Anderson J, Dusenbury L. Worksite cholesterol and nutrition: An intervention project in Colorado. American Association of Occupational Health Nurses Journal 1999;47: 99-106.

Anderson RC, Anderson KE. Positive changes and worksite health education. Psychological Reports 1994;74:607-10.

Baier CA, Grodzin CJ, Port JD, Leksas L, Tancredi DJ. Coronary risk factor behavior change in hospital personnel following a screening program. American Journal of Preventive Medicine 1992;8:115-22.

Bertera RL. Behavioral risk factor and illness day changes with workplace health promotion: two-year results. American Journal of Health Promotion 1993;7:365-73.

Blair SN, Piserchia PV, Wilbur CS, Crowder JH. A public health intervention model for work-site health promotion. Impact on exercise and physical fitness in a health promotion plan after 24 months. JAMA 1986;255:921-6.

Bly JL, Jones RC, Richardson JE, Bly JL, Jones RC, Richardson JE. Impact of worksite health promotion on health care costs and utilization. Evaluation of Johnson & Johnson's Live for Life program. JAMA 1986;256:3235-40.

Breslow L, Fielding J, Herrman AA, Wilbur CS. Worksite health promotion: its evolution and the Johnson & Johnson experience. Preventive Medicine 1990;19:13-21.

Brill PA, Kohl HW, Rogers T, Collingwood TR, Sterling CL, Blair SN. Relationship between sociodemographic characteristics and recruitment, retention, and health improvements in a worksite health promotion program. American Journal of Health Promotion 1991;5:215-21.

Donnelly IW. Using health promotion to improve workers' health. Managing Employee Health Benefits 1996:74-7.

Dunton S, Perkins DD, Zopf KJ. The impact of worksite-based health risk appraisal programs on observed safety belt use. Health Education Research 1990;5:207-16.

Edington M, Karjalainen T, Hirschland D, Edington D. The UAW-GM Health Promotion Program: Successful Outcomes. American Association of Occupational Health Nurses Journal 2002;50:26-31.

Edye BV, Mandryk JA, Frommer MS, Healey S, Ferguson DA. Evaluation of a worksite programme for the modification of cardiovascular risk factors. Medical Journal of Australia 1989;150:574-81.

Erfurt JC, Foote A, Heirich MA. Worksite wellness programs: incremental comparison of screening and referral alone, health education, follow-up counseling, and plant organization. American Journal of Health Promotion 1991;5:438-48.

Erfurt JC, Holtyn K. Health promotion in small business: What works and what doesn't work. Journal of Occupational Medicine 1991;33:66-73.

Fielding JE, Knight K, Mason T, Klesges RC, Pelletier KR. Evaluation of the IMPACT blood pressure program. Journal of Occupational Medicine 1994;36:743-6.

Fitzgerald ST, Gibbens S, Agnew J. Evaluation of referral completion after a workplace cholesterol screening program. American Journal of Preventive Medicine 1991;7:335-40.

Frommer MS, Mandryk JA, Edye BV, Healey S, Berry G, Ferguson DA. A randomised controlled trial of counseling in a workplace setting for coronary heart disease risk factor modification: effects on blood pressure. Asia Pacific Journal of Public Health 1990;4:25-33.

Goetzel RZ, Dunn RL, Ozminkowski RJ, Satin K, Whitehead DA, Cahill K. Differences between descriptive and multivariate estimates of the impact of Chevron Corporation's Health Quest program on medical expenditures. Journal of Occupational & Environmental Medicine 1998:40(6):538-45.

Goetzel RZ, Kahr TY, Aldana SG, Kenny GM. An evaluation of Duke University's live for life health promotion program and its impact on employee health. American Journal of Health Promotion 1996;10.

Goetzel RZ, Ozminkowski RJ, Bruno JA, RutterKR, Isaac F, Wang S. The long-term impact of Johnson & Johnson's Health & Wellness Program on employee health risks. Journal of Occupational & Environmental Medicine 2002;44:417-24.

Goetzel RZ, Sepulveda M, Knight K, Eisen M, Wade S, et al. Association of IBM's "A Plan for Life" health promotion program with changes in employees' health risk status. Journal of Occupational Medicine 1994;36:1005-9.

Gomel M, Oldenburg B, Simpson JM. Work-site cardiovascular risk reduction: a randomized trial of health risk assessment, education, counseling, and incentives. American Journal of Public Health 1993;83:1231-8.

Gomel MK, Oldenburg B, Simpson JM, Chilvers M, Owen N. Composite cardiovascular risk outcomes of a work-site intervention trial. American Journal of Public Health 1997;87:673-6.

Gregg W, Foote A, Erfurt JC, Heirich MA. Worksite follow-up and engagement strategies for initiating health risk behavior changes. Health Education Quarterly 1990;17:455-78.

Guico-Pabia CJ, Cioffi L, Shoner LG. The Lucent-Takes-Heart cardiovascular health management program. Successful workplace screening. AAOHN Journal 2002;50: 365-72.

Hartman TJ, Himes JH, McCarthy PR, Kushi LH. Effects of a low-fat, worksite intervention on blood lipids and lipoproteins. Journal of Occupational & Environmental Medicine 1995;37:690-6.

Hartman TJ, McCarthy PR, Himes JH. Use of eating-pattern messages to evaluate changes in eating behaviors in a worksite cholesterol education program. Journal of the American Dietary Association 1993;93:1119-23.

Heirich MA, Foote A, Erfurt JC, Konopka B. Work-site physical fitness programs. Comparing the impact of different program designs on cardiovascular risks. Journal of Occupational Medicine 1993;35:510-7.

Holt MC, McCauley M, Paul D. Health impacts of AT&T's Total Life Concept (TLC) program after five years. American Journal of Health Promotion 1995;9:421-5.

Knight KK, Goetzel RZ, Fielding JE, Eisen M, Jackson GW, et al. An evaluation of Duke University's LIVE FOR LIFE health promotion program on changes in worker absenteeism. Journal of Occupational Medicine 1994;36:533-6.

Kronenfeld JJ, Jackson K, Blair SN, Davis K, Gimarc JD, et al. Evaluating health promotion: a longitudinal quasi-experimental design. Health Education Quarterly 1987;14:123-39.

Maes S, Verhoeven C, Kittel F, Scholten H. Effects of a Dutch work-site wellness-health program: the Brabantia Project. American Journal of Public Health 1998;88: 1037-41.

McCarthy PR, Lansing D, Hartman TJ, Himes JH. What works best for worksite cholesterol education? Answers from targeted focus groups. Journal of the American Dietary Association 1992;92:978-81.

Merrill BE, Sleet DA. Safety belt use and related health variables in a worksite health promotion program. Health Education Quarterly 1984;11:171-9.

Musich S, McDonald T, Hirschland D, Edington D. Examination of risk status transitions among active employees in a comprehensive worksite health promotion program. Journal of Occupational & Environmental Medicine 2003;45:393-9.

Nilsson PM, Klasson EB, Nyberg P. Life-style intervention at the worksite - reduction of cardiovascular risk factors in a randomized study. Scandinavian Journal of Work, Environment & Health 2001;27:57-62.

Oldenburg B, Owen N, Parle M, Gomel M. An economic evaluation of four work site based cardiovascular risk factor interventions. Health Education Quarterly 1995;22: 9-19.

Ostwald SK. Changing employees' dietary and exercise practices: an experimental study in a small company. American Journal of Health Promotion 1989;4:141-2.

Ozminkowski RJ. Long-term impact of Johnson & Johnson's Health & Wellness Program on health care utilization and expenditures. Journal of Occupational & Environmental Medicine 2002;44:21-9.

Ozminkowski RJ, Goetzel RZ, Smith MW, Cantor RI, Shaughnessy A, Harrison M. The Impact of the Citibank, NA, Health Management Program on Changes in Employee Health Risks Over Time. Journal of Occupational & Environmental Medicine 2000;42: 502-11.

Ozminkowski RJ, Dunn RL, Goetzel RZ, Cantor RI, Murnane J, Harrison M. Return on investment evaluation of the Citibank, NA, Health Management Program. American Journal of Health Promotion 1999;14:31-43.

Pelletier B, Boles M, Lynch W. Change in health risks and work productivity over time. Journal of Occupational & Environmental Medicine 2004;46.

Pilon BA, Renfroe D. Evaluation of an employee health risk appraisal program. AAOHN Journal 1990;38:230-5.

Pilon BA, Renfroe D. Evaluation of an employee health risk appraisal program. American Association of Occupational Health Nurses Journal 1990;38:230-5.

Poole K, Kumpfer K, Pett M. The impact of an incentive-based worksite health promotion program on modifiable health risk factors. American Journal of Health Promotion 2001;16:21-6, ii.

Purath J, Miller AM, McCabe G, Wilbur J. A brief intervention to increase physical activity in sedentary working women. Canadian Journal of Nursing Research 2004;36:76-91.

Puska P, Niemensivu H, Puhakka P, Alhainen L, Koskela K, et al. Results of a one-year worksite and mass media based intervention on health behaviour and chronic disease risk factors. Scandinavian Journal of Work, Environment & Health 1988;16: 241-50.

Schultz AB, Lu C, Barnett TE, Yen LT, McDonald T, et al. Influence of participation in a worksite health-promotion program on disability days. Journal of Occupational & Environmental Medicine 2002;44:776-80.

Sepulveda M, Goetz A, Grana J. Measuring second-order selection bias in a work site health program. Journal of Occupational & Environmental Medicine 1994;36:326-33.

Serxner S, Gold D, Anderson D, Williams D. The impact of a worksite health promotion program on short-term disability usage. Journal of Occupational & Environmental Medicine 2001;43:25-9.

Serxner SA, Gold DB, Bultman KK. The impact of behavioral health risks on worker absenteeism. Journal of Occupational & Environmental Medicine 2001;43:347-54.

Shi L. Impact of increasing intensity of health promotion intervention on risk reduction. Evaluation & the Health Professions 1992;15:3-25.

Shi L. Health promotion, medical care use, and costs in a sample of worksite employees. Evaluation Review 1993;17:475-87.

Shimizu T, Nagashima S, Mizoue T, Higashi T, Nagata S. A psychosocial-approached health promotion program at a Japanese worksite. Journal of the University of Occupational & Environmental Health 2003;25:23-34.

Shipley RH, Orleans T, Wilbur CS, Piserchia PV, McFadden DW. Effect of the Johnson & Johnson Live for Life Program on Employee Smoking. Preventive Medicine 1988; 12:25-34.

Sloan RP, Gruman J. Participation in workplace health promotion programs: the contribution of health and organizational factors. Health Education Quarterly 1988;15:269-88.

Sorensen G, Stoddard A, Hunt MK, Hebert JR, Ockene JK, et al. The effects of a health promotion-health protection intervention on behavior change: the WellWorks Study. American Journal of Public Health 1998;88:1685-90.

Sorensen G, Stoddard AM, LaMontagne AD, Emmons K, Hunt MK, et al. A comprehensive worksite cancer prevention intervention: behavior change results from a randomized controlled trial (United States). Cancer Causes Control 2002;13: 493-502.

Sorensen G, Thompson B, Glanz K, Feng Z, Kinne S, et al. Work site-based cancer prevention: primary results from the Working Well Trial. American Journal of Public Health 1996;86:939-47.

Sorensen G, Himmelstein JS, Hunt MK, Youngstrom R, Hebert JR, et al. A model for worksite cancer prevention: integration of health protection and health promotion in the WellWorks Project. American Journal of Public Health 1995;10:55-62.

Spilman MA, Goetz A, Schultz J, Bellingham R, Johnson D. Effects of a corporate health promotion program. Journal of Occupational Medicine 1986;28:285-9.

Stevens MM, Paine-Andrews A, Francisco VT. Improving employee health and wellness: a pilot study of the employee-driven Perfect Health Program. American Journal of Health Promotion 1996;11:12-14.

Strychar IM, Champagne F, Ghadirian P, Bonin A, Jenicek M, Lasater TM. Impact of receiving blood cholesterol test results on dietary change. American Journal of Preventive Medicine 1998;14:103-10.

Tilley BC, Glanz K, Kristal AR, Hirst K, Li S, Vernon SW et al. (1999). Nutrition intervention for high-risk auto workers: Results of the Next Step Trial. Preventive Medicine, 28, 284-292.

Tilley BC, Vernon SW, Glanz K, Myers R, Sanders K, et al. Worksite cancer screening and nutrition intervention for high-risk auto workers: design and baseline findings of the Next Step Trial. Preventive Medicine 1997;26:227-35.

Tilley BC, Vernon SW, Myers R, Glanz K, Lu M, et al. The Next Step Trial: impact of a worksite colorectal cancer screening promotion program. Preventive Medicine 1999; 27:276-83.

Walton C, Timms J. Providing worksite health promotion through university-community partnerships: the South Carolina DOT project. American Association of Occupational Health Nurses Journal 1999;47:449-55.

Weinstein ND, Grubb PD, Vautier JS. Increasing automobile seat belt use: an intervention emphasizing risk susceptibility. Journal of Applied Psychology 1986;71: 285-90.

Williams A, Wold J, Dunkin J, Idleman L, Jackson C. CVD prevention strategies with urban and rural African American women. Applied Nursing Research 2004;17:187-94.

Wood EA. Lifestyle risk factors and absenteeism trends - a six-year corporate study. AWHP'S Worksite Health 1997;4:32-5.

Wood EA, Olmstead GW, Craig JL. An evaluation of lifestyle risk factors and absenteeism after two years in a worksite health promotion program. American Journal of Health Promotion 1989;4:128-33.

World Health Organisation European Collaborative Group. European collaborative trial of multifactorial prevention of coronary heart disease: final report on the 6-year results. Lancet 1986;1:869-72.

World Health Organization. An international controlled trial in the mulitfactorial prevention of coronary heart disease. International Journal of Epidemiology 1974;3: 219-24.

World Health Organization European Collaborative Group. Multifactorial trial in the prevention of coronary heart disease: 2. Risk factor changes at two and four years. European Heart Journal 1982;3:184-90.

World Health Organization European Collaborative Group. Multifactorial trial in the prevention of coronary heart disease: 3. Incidence and mortality results. European Heart Journal 1983;4:141-7.

Yen L, Edington MP, McDonald T, Hirschland D, Edington DW. Changes in health risks among the participants in the United Auto Workers - General Motors LifeSteps Health Promotion Program. American Journal of Health Promotion 2001;16:7-15.
Economic Review
Aldana SG, Jacobson BH, Harris CJ, Kelley PL. Mobile work site health promotion programs can reduce selected employee health risks. J Occup Med 1993;35(9):922-8.

Bertera RL. The effects of workplace health promotion on absenteeism and employment costs in a large industrial population. Am J Public Health 1990; 80(9):1101-5.

Burton W, Conti D. Disability management: corporate medical department management of employee health and productivity. J Occup Environ Med 2000;42:1006 -12.

Erfurt JC, Foote A, Heirich MA. The cost effectiveness of worksite wellness programs for hypertension control, weight loss, and smoking cessation. J Occup Med 1991;33(9):962-70.

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Shi L. Health promotion, medical care use, and costs in a sample of worksite employees. Eval Rev 1993;17(5):475-87.

Search Strategies

The following outlines the search strategy used for reviews of assessment of health risks with feedback when used alone, and when combined with health education programs, with or without additional interventions.
The articles to be reviewed were obtained from systematic searches of multiple databases, reviews of bibliographic reference lists, and consultations with experts in the field. The following databases were searched: Medline, Employee Benefits, NTIS, Sports Information Resource Center, Cambridge Scientific Abstracts, Inc., Business Week, ABI Inform, Health Promotion and Education, Cumulative Index to Nursing & Allied Health Literature, Office of Smoking and Health, AIDSLine, PsycInfo, and Sociological Abstracts.

Database: Ovid MEDLINE(R) [1966 to June Week 4 2005]

1. exp health behavior/ or exp health education/ or health promotion/ or exp primary prevention/ (218287)

2. exp work/ or workplace/ or occupational health/ (22008)

3. risk assessment/ or risk factors/ or health status indicators/ or mass screening/ (357682)

4. (health risk assessment$ or health risk appraisal$ or health screening$ or health status assessment$ or health assessment$ or screening$).mp. [mp=title, original title, abstract, name of substance word, subject heading word] (189292)

5. (risk awareness or risk profile$ or lifestyle check$ or health quiz or health measur$ or health report$ or risk identification).mp. [mp=title, original title, abstract, name of substance word, subject heading word] (5429)

6. 3 or 4 or 5 (490335)

7. (health maintenance organization$ or health clinic$ or insurance compan$).mp. [mp=title, original title, abstract, name of substance word, subject heading word] (18831)

8. 2 or 7 (40777)

9. 1 and 6 and 8 (607)

10. limit 9 to english language (559)

Database: Employee Benefits_1986-2005/Jun (c) 2005

Sets selected:

Set Items Description

1. 831 HEALTH()BEHAVIOR OR HEALTH()EDUCATION OR HEALTH()PROMOTION OR PRIMARY()PREVENTION

2. 1291 HEALTH()RISK()ASSESSMENT? OR HEALTH()RISK()APPRAISAL?
OR HEALTH()SCREENING? OR HEALTH()STATUS()ASSESSMENT?
OR HEALTH()ASSESSMENT? OR SCREENING?

3. 554 RISK()AWARENESS OR RISK()PROFILE?
OR LIFESTYLE()CHECK? OR HEALTH()QUIZ
OR HEALTH()MEASUR? OR HEALTH()REPORT?
OR RISK()IDENTIFICATION

4. 1360 S2 OR S3

5. 310 S1 AND S4

Databases:BAMP_2005/Jul W2 (c) 2005 and PAIS Int._1976-2005/Jun (c) 2005

Sets selected:

Set Items Description

Database: TGG Management Contents(R)_86-2005/Jul W2 (c) 2005 and Business Week_1985-2005/Jul 21 (c) 2005

Sets selected:

Set Items Description

Database: ABI Inform(R)_1971-2005/Jul 22 (c)

Sets selected:

Set Items Description

1. 6388 HEALTH()BEHAVIOR OR HEALTH()PROMOTION OR HEALTH()EDUCATION OR PRIMARY()PREVENTION

2. 6342 (HEALTH()RISK()ASSESSMENT? OR HEALTH()RISK()APPRAISAL? OR HEALTH()SCREENING? OR HEALTH()STATUS()ASSESSMENT? OR HEALTH()ASSESSMENT? OR SCREENING?)/TI,AB

3. 1039 (RISK()AWARENESS OR RISK()PROFILE? OR LIFESTYLE()CHECK? OR HEALTH()QUIZ? OR HEALTH()MEASUR? OR HEALTH()REPORT? OR RISK()IDENTIFICATION)/TI,AB

4. 7371 S2 OR S3

5. 252 S1 AND S4

6. 517172 WORKSITE? OR WORKPLACE? OR EMPLOYER? OR EMPLOYEE? OR WORKER?

7. 184 S5 AND S6

8. 184 S9/ENG

Database: CDP File (Health Promotion and Education Database)

Descriptors: "WORKSITE" and "HEALTH RISK APPRAISAL" and
Form: "JOURNAL ARTICLE" OR
Descriptors: "worksite" not "health risk appraisal" and
Textwords: HEALTH ADJ1 RISK ADJ1 ASSESSMENT* OR HEALTH ADJ1 SCREEN* OR RISK ADJ1 ASSESSMENT* OR HEALTH ADJ1 ASSESSMENT* OR *RISK ADJ1 (AWARENESS* OR PROFILE* OR IDENTIFICATION) OR HEALTH ADJ1 (MEASURING OR REPORT* OR QUIZ*) OR LIFESTYLE ADJ1 CHECK* and Form: "JOURNAL ARTICLE"
TOTAL = 212

Database: CINHAL

Descriptors: "WORKSITE" and "HEALTH RISK APPRAISAL" and
Form: "JOURNAL ARTICLE" OR
Descriptors: "worksite" not "health risk appraisal" and
Textwords: HEALTH ADJ1 RISK ADJ1 ASSESSMENT* OR HEALTH ADJ1 SCREEN* OR RISK ADJ1 ASSESSMENT* OR HEALTH ADJ1 ASSESSMENT* OR *RISK ADJ1 (AWARENESS* OR PROFILE* OR IDENTIFICATION) OR HEALTH ADJ1 (MEASURING OR REPORT* OR QUIZ*) OR LIFESTYLE ADJ1 CHECK* and Form: "JOURNAL ARTICLE"
TOTAL = 212

Database: NTIS, Intl Cpyrght All Rights Res

Sets selected:

Set Items Description

1. 9285 HEALTH()BEHAVIOR OR HEALTH()EDUCATION OR HEALTH()PROMOTION OR PRIMARY()PREVENTION

2. 4804 WORKSITE OR WORKPLACE OR WORK-SITE OR OCCUPATIONAL()HEALTH

3. 289 S1 AND S2

4. 17896 HEALTH()RISK()ASSESSMENT? OR HEALTH()RISK()APPRAISAL? OR HEALTH()SCREENING? OR HEALTH()STATUS()ASSESSMENT? OR HEALTH()ASSESSMENT? OR SCREENING?

5. 477 RISK()AWARENESS OR RISK()PROFILE? OR LIFESTYLE()CHECK? OR HEALTH()QUIZ OR HEALTH()MEASUR? OR HEALTH()REPORT? OR RISK()IDENTIFICATION

6. 18332 S4 OR S5

7. 47 S3 AND S6

Database: SportDiscuss

Sets selected:

Set Items Description

1. 9166 HEALTH()BEHAVIOR OR HEALTH()EDUCATION OR HEALTH()PROMOTION OR PRIMARY()PREVENTION

2. 1589 WORKSITE OR WORKPLACE OR WORK-SITE OR OCCUPATIONAL()HEALTH

3. 479 S1 AND S2

4. 2169 HEALTH()RISK()ASSESSMENT? OR HEALTH()RISK()APPRAISAL? OR HEALTH()SCREENING? OR HEALTH()STATUS()ASSESSMENT? OR HEALTH()ASSESSMENT? OR SCREENING?

5. 176 RISK()AWARENESS OR RISK()PROFILE? OR LIFESTYLE()CHECK? OR HEALTH()QUIZ OR HEALTH()MEASUR? OR HEALTH()REPORT? OR RISK()IDENTIFICATION

6. 2341 S4 OR S5

7. 22 S3 AND S6

8. 22 S7/ENG

Database: OSH (Office of Smoking and Health)

Descriptors: ("WORKERS" OR "WORKPLACE*" OR "WORKSITE CESSATION PROGRAMS") AND ("HEALTH EDUCATION*" OR "HEALTH PROMOTION*" OR
"PREVENTION*" OR "INTERVENTION*") and
Textwords: RISK* OR SCREEN* OR ASSESSMENT* OR LIFESTYLE ADJ1 CHECK OR HEALTH ADJ1 QUIZ* OR HEALTH ADJ1 MEASUR* OR HEALTH ADJ1 REPORT*
Total - 20

Database: Sociological Abstracts [1963 to April 2005]

Database: PsycINFO [1967 to June Week 4 2005]

Database: AIDSLINE [1980 to December 2000] CLOSED FILE

1. exp health behavior/ or exp health education/ or health promotion/ or exp primary prevention/ (14069)

2. exp work/ or workplace/ or occupational health/ (347)

3. risk assessment/ or risk factors/ or health status indicators/ or mass screening/ (18933)

4. (health risk assessment$ or health risk appraisal$ or health screening$ or health status assessment$ or health assessment$ or screening$).mp. [mp=title, abstract, mesh subject heading] (6055)

5. (risk awareness or risk profile$ or lifestyle check$ or health quiz or health measur$ or health report$ or risk identification).mp. [mp=title, abstract, mesh subject heading] (239)

6. 3 or 4 or 5 (23204)

7. (health maintenance organization$ or health clinic$ or insurance compan$).mp. [mp=title, abstract, mesh subject heading] (488)

8. 2 or 7 (831)

9. 1 and 6 and 8 (36)

10. limit 9 to english language (36)

11. limit 10 to nonmedline (23)

12. from 11 keep 1-23 (23)

Review References

There is no information for this section.

Considerations for Implementation

Considerations for Implementation

The following considerations are drawn from studies included in the evidence review, the broader literature, and expert opinion.

Employers may be reluctant to implement interventions involving AHRF due to employee concerns over breach of confıdentiality of health records to other employees or to health insurance providers. Programs that offer incentives for completion of HRA tools or require that employees meet specifıc health standards (for example, they must fall within a particular BMI range) may exacerbate concerns.

Engaging employees can be challenging. Those who think or know that they have important health risks may be least likely to participate.

Even if there is broad participation in AHRF, there may be low participation in intervention components offered in addition to AHRF. In such cases, employers may be inclined to reduce the scope of or cancel these components.

While not evaluated in the included studies, interventions may lead to increased employee satisfaction.

The review team noted potential harms, including increased anxiety for workers during the feedback portion; false positives; and overestimates of risk status.

Crosswalks

Healthy People 2020

Healthy People 2020 includes the following objectives related to this CPSTF recommendation.

# data[].attributes.attachment_link.title
Worksite: Assessment of Health Risks with Feedback (AHRF) to Change Employees' Health - AHRF Plus Health Education With or Without Other Interventions

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Welcome to The Community Guide! Let us know what you think of the website by completing this quick survey. Snapshot The Community Preventive Services Task Force (CPSTF) recommends the use of assessments of health risks with feedback when combined with health education programs, with or without additional interventions, on the basis of strong evidence of effectiveness in improving one or more health behaviors or conditions in populations of workers.

# data[].attributes.body
Data mining from internet searches related to illness and even social media posts from the population can be extremely helpful in predicting an outbreak or emergency situation at real time. As McGonigle & Mastrian (2018) state, great care and discernment must be used because not internet searches or social media is accurate.

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Importance of Population Health data in Regional HIE and Future National HIN.

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Importance of Population Health data in Regional HIE and Future National HIN.

# data[].attributes.body
Seamless shared data from not only health data, but also all hospitals, pharmacies, laboratories, clinics, poison control, and environmental agencies are imperative to effectively and swiftly identify and implement action plans when assessing needs and emergencies. For this to happen, it has to start at the regional health information exchanges and eventually national health information network (McGonigle & Mastrian 2018).

# data[].attributes.body
Community Health Risk Assessments are evaluations of a community to find out what health risks they are prone to. They are used in public health programs (McGonigle& Mastrian 2018). Data can be collected about communities either from existing data, focus groups, statistics, health records, and making observations just from driving around the community.

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Goals of community health risk assessments. 

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Goals of community health risk assessments. 

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1. What are  needs or issues in the community?

2. Collaborations with multiple agencies in the community are vital.

3. get resources

4. get community to have increased awareness of the identified issues

5. take a proactive approach.

# data[].attributes.headline
Nursing and Community Health Risk Assessments 

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Nursing and Community Health Risk Assessments 

# data[].attributes.attachment_link.title
Community Health Nursing - Community Assessment and Community Health Plan

# data[].attributes.headline
Role of nursing in relation to community health risk assessments. 

# data[].attributes.subject
Role of nursing in relation to community health risk assessments. 

# data[].attributes.body
As nurses, we are always assessing our patients. We are constantly documenting risk assessments such fall and suicide risks. Nurses play a vital role in community health risk assessments also. Nurses can help identify certain needs of the community or risks that the community. At the very least, nursing documentation will help when data is being collected to identify risks and needs. When a plan is in place to provide education or share resources, nurses can help in implementing that plan. Nurses also can collaborate with other community agencies to provide input and feedback.

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Effective ways to identify community needs or risks. 

# data[].attributes.subject
Effective ways to identify community needs or risks. 

# data[].attributes.body
Just driving around the community can help bring better understanding of needs.

demographics

close proximity to health facilities

grocery stores (how close and what kind)

transportation

violence

mental health

housing

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Action plan and implementation for Blue Island Community through collaboration between community and agencies in the community. 

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Action plan and implementation for Blue Island Community through collaboration between community and agencies in the community. 

# data[].attributes.attachment_link.authors[].name
Centers for Disease Control and Prevention (CDC)

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Be Healthy Blue Island: A Roadmap to a Healthier Community

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Here is an article on population health and an action plan for nursing. 

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Here is an article on population health and an action plan for nursing. 

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Abstract

The passage of the Affordable Care Act shifted the focus of health care from individual, patient specific, episodic care, towards health management of groups of people with an emphasis on primary and preventive care. Population health management assists to attain and maintain health while improving quality and lowering costs. The recent Catalyst for Change report creates an urgent call for harnessing the power of nurses-in our communities, schools, businesses, homes and hospitals-to build capacity for population health. Informatics Nurse Specialists are prepared to bridge roles across practice, research, education, and policy to support this call. Each year, the AMIA Nursing Informatics Working Group convenes an expert panel to reflect on the "hot topics" of interest to nursing. Not surprisingly, the 2017 topic was on the current state and challenges of population health. The following summary reflects the panel's perspectives and recommendations for action.

INTRODUCTION

Population health is defined as the "health outcomes of a group of individuals, including the distribution of such outcomes within the group." The passage of the Affordable Care Act (ACA) shifted the focus of health care from individual, patient specific, episodic care, towards health management of groups of people with an emphasis on primary and preventive care. Population health management assists these groups to attain and maintain health with an increased focus on shared accountability for the upstream environment, social, and community factors that contribute to chronic disease and cost. With more than 3 million nurses in the United States, in all sectors of health care, nurses, because of their role, their education, and the respect they have earned, are well positioned to help shape and improve our nation's health status and care infrastructure. The recent Catalyst for Change report (RWJF, 2017) creates an urgent call for harnessing the power of nurses-in our communities, schools, businesses, homes, and hospitals-to build capacity for population health. Informatics Nurse Specialists (INSs) are prepared and well positioned to bridge roles across practice, research, education, and policy to support this call.

Each year, the AMIA Nursing Informatics Working Group (NIWG) convenes an expert panel to focus on a "hot topic" of interest to nursing. Not surprisingly, the 2017 topic was on the current state and challenges of population health. The following summary reflects the panel's perspectives and recommendations for action.

POPULATION HEALTH IN PRACTICE

Nursing practice is experiencing a paradigm shift from siloed health information technology (HIT) designed to collect data at points-of-care within organizations, to data collected along a patient's health trajectory, co-ordinated across where they live, work, and play. However, the health care data collected today is largely designed, maintained, and groomed for transactions between providers and payers and for managing point-of-care contacts with patients. The information, communication, and technology infrastructure must: integrate data, creating robust analytic environments designed to assemble and assess populations; identify and predict adverse outcomes; support programs and interventions to address inter-professional work flow needs across all care venues; and measure success.

Nurse leaders, nurses, and INSs are active and innovative in addressing the move from transactional systems to a robust data warehouse environment with an operational analytic infrastructure. Basic capabilities start with patient identity management (PIM) and patient/primary care provider attribution. Health Information Exchanges (HIE) deal with complex PIM issues and where no HIE exists, PIM may not be possible., Successful population health management requires primary care at its core; however; attribution is, at its best, a compromise among a complex set of methodological choices and, at its worst, fraught with errors in the data collection and workflow management process.

While organizations accountable for care can demonstrate analytic expertise using risk prediction and prescription models, these capabilities come at high cost when manually executed, lacking in scale and efficiency. These challenges make it near impossible for organizations to make informed, strategic decisions for managing the health outcomes of patients, risk contracting, and gaining overall competitive advantage.

Recommendations for practice include:

Assemble a workforce of INS's prepared to manage the complexities of population health.

Incorporate robust analytic tools that provide near real-time knowledge that bridge patient-centered care across the continuum.

Test translational models for moving population health methods and findings from research into practice.

Inform HIT policymakers on practice challenges and barriers to achieving population health knowledge.

POPULATION HEALTH IN EDUCATION

Population health is not a new concept for nursing education. As far back as Florence Nightingale, nurses have fostered a philosophy of care that focuses on the assessment and management of physical, biological, social, psychological, and environmental influences on patients and populations. This population focus, however, has diminished over time with a push towards education and competency development to prepare nurses for acute and critical care. Today, there is a resurgence of interest in population health-based nursing education, encouraging nurses to reclaim their history and take on key roles in a health care system responsive to the needs of populations.

Nurses must be competent in: near real-time assessment and identification of issues negatively affecting health and well-being; discernment of patterns from data and populations; creating linkages among community resources and services; developing population-focused interventions; and evaluating the impact of the efforts., Next generation INSs must elevate their support of population health efforts through: training and competency in data capture from disparate systems; validation and maintenance of data; transformation and analysis of data; inclusion of social determinants of health (SDOH) to address disparities; predictive and prescriptive analysis; risk stratification; and evaluation of education programs.

Accreditation and certification bodies as well as licensing boards for the graduates of programs must ensure that all nursing students from entry to practice to graduate level, including INS students are provided learning opportunities to attain these competencies and advance graduates who demonstrate these skills. As we move our emphasis from an acute care focus to population health model, it will require rethinking and a shift in focus for many nursing and informatics programs.

Recommendations for education:

Nursing education programs must prepare nurses to:

Tackle the impact of SDOH on improving health and reducing health inequalities

Consider community resources and provide learning opportunities to build engagement

Assess process and outcomes of community-based interventions

Nursing informatics graduate programs must prepare the INSs to:

Manage data capture from disparate systems, beyond the electronic health record (EHR)

Understand data validation, transformation, and maintenance

Develop skills in data science and analytics to assess the health status and risk levels of populations

Evaluate the use of risk stratification, as well as predictive and prescriptive analytics

POPULATION HEALTH IN RESEARCH

Population health research investigates various determinants of health, including health care services, individuals' genetics and health behaviors, physical and social environments. Funding agencies have increased their support for population health research in response to rapidly growing chronic illness populations and skyrocketing medical costs. For example, the strategic plan of the National Institute of Nursing Research (NINR) focuses on 4 scientific themes: symptom science, wellness, self-management of chronic conditions, and end-of-life and palliative care. The Agency for Healthcare Research and Quality (AHRQ) supports research initiatives to improve health care quality and make health care safer, more accessible, affordable, and efficient.

Health information technology (HIT) is a vital component that supports population health research. Some of examples HIT areas includes: meaningful use of EHRs, HIE, interoperability, Big Data, and health care analytics. Many studies have demonstrated the important roles of HIT components in knowledge discovery and the development and implementation of new health interventions while engaging patients in their care.

Informatics Nurse Specialists including both researchers and practitioners, have an in-depth understanding of the associations among the data, clinical practices and workflow, and track records of using HIT in health-related research. They can also significantly contribute to the advancement of population health research by using robust HIT tools that improve quality of care and patient outcomes and contributing to the development of efficient and interoperable health care systems.

Recommendations for research:

Enhance nurses' knowledge about big data and population health knowledge

Develop new systems and tools that engage and empower patients to improve quality of care, outcomes, and wellness activities.

Map data to standardized terminologies and protocols for interoperability and outcome measurement

Contribute to the science of the associations among the data, clinical practices, and workflow.

Research health information systems that can contribute to reducing health disparities.

POPULATION HEALTH IN POLICY

The AMIA NIWG panel concluded with an update on public policy and invited continued engagement in population health efforts supported by AMIA and The Alliance for Nursing Informatics (ANI). Multiple policy issues impact population health, with only a few highlighted during this event. For example, AMIA's Policy Invitational (API 2017) explored "redefining our picture of health," through the lens of how patients experience care, research, wellness, and community-rather than those of provider institutions, payers, and health IT vendors. Policy recommendations focused on the development of an integrated, socio-technical ecosystem that enables an individual (the "n-of-1") to improve the health of populations (the "n-of-many"), and vice versa.

Implementation of the 21st Century Cures Act and testimony to the Senate Health, Education, Labor & Pensions committee reports progress on: interoperability; secure and trusted bi-directional exchange; Trusted Exchange Framework and Common Agreement (TEFCA); clinician burden; and information blocking. The new Centers for Medicare and Medicaid Services "Meaningful Measures" Initiative was launched to reduce regulatory burden and promote innovation in the transition value-based payment.

The fields of public, population, and community health informatics offer overlapping perspectives to policy considerations, recognizing social, economic, and environmental risk factors as predictors of health disparities at the individual and community level. Nurse-led population health improvement efforts need to consider policies which address SDOH, health inequities, access to affordable care, and healthy behaviors. Although early in development, infrastructure is needed across nursing practice, education, and research settings to develop and test population-based care and payment accountability models. Alternate Payment Models (APM) and payment reforms that seek to deliver better care at lower cost achieved 29% in 2016, with expected progress toward the goal of 50% by 2018. Policy will continue to evolve to find ways to significantly improve affordability and value for both consumers and the health care system.

Policy recommendations:

Promote health policy that encourages person-centered, integrated health care, research, preventive care, and wellness in the context of a community ecosystem

Monitor progress on the Office of the National Coordinator's Shared Nationwide Interoperability Roadmap and the 21st Century Cures Act

Incentivize data transparency and bi-directional health data exchange bridging institution-centric and person-centric approaches

Advocate funding for population-focused nursing education and research, including support of the recommendations laid out in the Institute of Medicine's 2010 report, The Future of Nursing and the RWJF 2017 Catalyst for Change: Harnessing the Power of Nurses to Build Population Health for the 21st Century

CONCLUSION

In conclusion, the AMIA NIWG Population Health panel acclaims that INSs are in integral roles to actively support capacity building for nurses to build population health in the 21st century, aligned with the Catalyst for Change white paper. Informatics Nurse Specialists are critical partners to lead population health, care coordination across settings of care, and inter-professional and community stakeholder collaboration. Informatics Nurse Specialists are well positioned to influence practice, education, research, and health care policy. Preparing nurses for robust roles to improve population health will require clear articulation of nursing's value proposition to impact health, cost, and outcomes for both the individual and populations; and active engagement in redesigning health data infrastructures to address current gaps. The AMIA NIWG panel of opinion leaders have provided background, identified recommendations, and perspectives to meet the demands of an evolving health care system, including the application of new knowledge and skills.

FUNDING

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Conflict of interest statement. None declared.

CONTRIBUTORS

All authors contributed to overall intellectual content and sections of writing.

ACKNOWLEDGMENTS

The authors thank our colleagues in the AMIA Nursing Informatics Working Group (NIWG) who helped inspire and shape this work: Juliana Brixey, Sarah Collins, Kandace Kelly, Laura Heerman-Langford, Judy Murphy, Marisa Wilson, and Ron Piscotty.

References

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

# data[].attributes.attachment_link.title
Population health: a nursing action plan

# data[].attributes.attachment_link.description
The passage of the Affordable Care Act shifted the focus of health care from individual, patient specific, episodic care, towards health management of groups of people with an emphasis on primary and preventive care. Population health management assists to attain and maintain health while improving quality and lowering costs.