Healthcare Survey Tools Market Outlook

The global healthcare survey tools market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% over the forecast period. This substantial growth is fueled by the increasing demand for real-time patient feedback, the necessity for healthcare organizations to stay compliant with regulatory standards, and the rising adoption of digital health solutions.

One of the most critical growth factors influencing the healthcare survey tools market is the heightened focus on patient-centric care. Healthcare providers are increasingly emphasizing patient feedback to ensure better care outcomes and enhance patient satisfaction. The shift towards value-based care models, which prioritize patient experiences and outcomes over service volume, necessitates the use of efficient survey tools. Additionally, regulatory bodies like the Centers for Medicare & Medicaid Services (CMS) have mandated patient experience surveys, further propelling market growth.

Another significant factor driving the market is the technological advancements in survey tools. The integration of Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) has revolutionized healthcare survey tools, making them more intuitive, scalable, and capable of providing in-depth analysis. These technologies enable real-time feedback collection and analysis, allowing healthcare organizations to promptly address issues and improve their services. Furthermore, the increasing penetration of smartphones and the internet facilitates easier access to survey tools, thereby boosting their adoption.

The COVID-19 pandemic has also significantly accelerated the growth of this market. The pandemic highlighted the need for robust healthcare feedback mechanisms to quickly adapt to evolving challenges. Organizations have had to rapidly gather and analyze patient and employee feedback to manage crisis situations effectively. This urgency has led to an increased reliance on digital survey tools, which provide quick and accurate insights, thereby contributing to market growth.

From a regional perspective, North America is anticipated to hold the largest market share, driven by the regionÂ’s advanced healthcare infrastructure, high adoption of digital health technologies, and stringent regulatory requirements. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by increasing healthcare investments, a growing focus on patient care quality, and the rising prevalence of chronic diseases.

The rise of Online Survey Software and Tools has been pivotal in transforming how healthcare organizations collect and analyze feedback. These tools offer a versatile platform for designing, distributing, and analyzing surveys, making it easier for healthcare providers to gather insights from patients and staff. With the ability to customize surveys and integrate them with existing healthcare systems, these tools enhance the efficiency of feedback collection processes. Moreover, the real-time analytics capabilities of these tools enable healthcare organizations to swiftly address issues and improve service quality, aligning with the industry's shift towards patient-centered care.

Product Type Analysis

The healthcare survey tools market by product type is segmented into Software and Services. Software solutions dominate this segment, offering various functionalities, including design, distribution, and analysis of surveys. The ease of customization and the ability to integrate with existing healthcare systems make software solutions particularly appealing. Software tools often come equipped with advanced analytics features, enabling healthcare providers to convert raw data into actionable insights swiftly. This capability is crucial for organizations aiming to improve patient satisfaction and care quality continuously.

Services, though a smaller segment compared to software, play a vital role in the market. These services typically include consulting, customization, and support, helping organizations maximize the utility of their survey tools. Vendors offer specialized services, such as training healthcare staff on effectively using the tools and interpreting the data. This ensures that organizations can fully leverage the technology to

The National Health Interview Survey (NHIS) is the principal source of information on the health of the civilian noninstitutionalized population of the United States and is one of the major data collection programs of the National Center for Health Statistics (NCHS) which is part of the Centers for Disease Control and Prevention (CDC). The National Health Survey Act of 1956 provided for a continuing survey and special studies to secure accurate and current statistical information on the amount, distribution, and effects of illness and disability in the United States and the services rendered for or because of such conditions. The survey referred to in the Act, now called the National Health Interview Survey, was initiated in July 1957. Since 1960, the survey has been conducted by NCHS, which was formed when the National Health Survey and the National Vital Statistics Division were combined. NHIS data are used widely throughout the Department of Health and Human Services (DHHS) to monitor trends in illness and disability and to track progress toward achieving national health objectives. The data are also used by the public health research community for epidemiologic and policy analysis of such timely issues as characterizing those with various health problems, determining barriers to accessing and using appropriate health care, and evaluating Federal health programs. The NHIS also has a central role in the ongoing integration of household surveys in DHHS. The designs of two major DHHS national household surveys have been or are linked to the NHIS. The National Survey of Family Growth used the NHIS sampling frame in its first five cycles and the Medical Expenditure Panel Survey currently uses half of the NHIS sampling frame. Other linkage includes linking NHIS data to death certificates in the National Death Index (NDI). While the NHIS has been conducted continuously since 1957, the content of the survey has been updated about every 10-15 years. In 1996, a substantially revised NHIS questionnaire began field testing. This revised questionnaire, described in detail below, was implemented in 1997 and has improved the ability of the NHIS to provide important health information.

The Washington State Department of Health presents this information as a service to the public. This includes information on the work status, practice characteristics, education, and demographics of healthcare providers, provided in response to the Washington Health Workforce Survey. This is a complete set of data across all of the responding professions. The data dictionary identifies questions that are specific to an individual profession and aren't common to all surveys. The dataset is provided without identifying information for the responding providers. More information on the Washington Health Workforce Survey can be found at www.doh.wa.gov/workforcesurvey This dataset has been federated from https://data.wa.gov/Health/Washington-Health-Workforce-Survey-Data/cvrw-ujje.

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Sierra Leone SDI Health survey team visited a sample of 536 health facilities across Sierra Leone between January and April 2018. The survey team collected rosters covering 5,055 workers for absenteeism and assessed 829 health workers for competence using patient case simulations.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Facility finances – Information on facility revenue and expenditures is collected from the health facility manager.

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

The global healthcare survey tools market is experiencing robust growth, driven by increasing demand for patient-centric care, the need for improved healthcare quality, and the rising adoption of digital health technologies. The market is segmented by application (patient feedback, hospital feedback) and type (cloud-based, on-premises), with cloud-based solutions witnessing faster adoption due to their scalability, accessibility, and cost-effectiveness. The market's Compound Annual Growth Rate (CAGR) is projected to be in the range of 15-20% from 2025-2033, indicating a significant expansion. This growth is fueled by several factors including the need for real-time feedback mechanisms, regulatory pressures for improved patient experience, and the ability of survey tools to track key performance indicators (KPIs) related to patient satisfaction and healthcare outcomes. North America and Europe currently hold significant market share, attributed to the higher adoption of advanced technologies and robust healthcare infrastructure. However, the Asia-Pacific region is expected to witness substantial growth in the coming years due to increasing healthcare expenditure and improving digital literacy. While the market demonstrates significant potential, several restraining factors exist. These include concerns regarding data privacy and security, the high initial investment costs for implementing comprehensive survey systems, and the need for trained personnel to effectively manage and interpret the collected data. The competitive landscape is fragmented, with both established players and emerging vendors vying for market share. Success hinges on offering innovative features, robust data analytics capabilities, and ensuring compliance with evolving data protection regulations. The market is projected to reach a value significantly exceeding $1 billion by 2033, making it an attractive investment opportunity for both established and new market entrants. Companies are constantly innovating to offer tailored solutions that meet the unique requirements of various healthcare settings, driving further market growth.

The global market for healthcare survey tools is experiencing robust growth, driven by the increasing need for patient feedback, improved healthcare quality, and the rising adoption of digital health technologies. The market size in 2025 is estimated at $2.5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033. This significant growth is fueled by several key factors. Firstly, healthcare providers are increasingly recognizing the value of patient experience data in enhancing service delivery and improving patient outcomes. Secondly, the proliferation of digital health solutions and the rising adoption of electronic health records (EHRs) are creating opportunities for seamless integration of survey tools into existing workflows. Furthermore, regulatory pressures and the focus on value-based care are incentivizing the use of data-driven approaches, including patient surveys, to optimize resource allocation and demonstrate quality improvement. Several trends are shaping the future of this market. The increasing demand for real-time data analytics capabilities within survey tools is pushing vendors to develop sophisticated platforms capable of providing actionable insights immediately. The integration of artificial intelligence (AI) and machine learning (ML) is streamlining data analysis and enabling predictive modeling to anticipate patient needs and improve healthcare planning. However, challenges remain, including concerns regarding data privacy and security, the need for interoperability between different systems, and the potential for survey fatigue among patients. Despite these restraints, the long-term outlook for the healthcare survey tools market remains highly positive, with continued growth expected throughout the forecast period. The market is fragmented, with major players like Qualtrics, SurveyMonkey, and others competing alongside smaller, niche providers. The competitive landscape is dynamic, characterized by continuous innovation and the emergence of new technologies.

The global healthcare survey software market is experiencing robust growth, driven by increasing demand for patient satisfaction data, the need for efficient clinical trial management, and a growing emphasis on data-driven decision-making within healthcare organizations. The market's expansion is fueled by advancements in technology, such as mobile-first survey platforms and AI-powered analytics, which enable healthcare providers to gather comprehensive insights from diverse populations more efficiently. Furthermore, regulatory compliance requirements and the rise of value-based care models are compelling healthcare providers to leverage sophisticated survey tools for quality improvement and patient engagement initiatives. While challenges remain, such as data security concerns and the need for user-friendly interfaces to encourage wider adoption, the market's trajectory points towards significant expansion over the next decade. We estimate the market size in 2025 to be approximately $2.5 billion, with a Compound Annual Growth Rate (CAGR) of 12% projected through 2033, resulting in a market value exceeding $7 billion by the end of the forecast period. This growth is expected to be driven by increasing adoption in emerging markets and continued innovation within the sector. The competitive landscape is characterized by a mix of established players and emerging companies. Key players like Qualtrics, SurveyMonkey (Momentive), and QuestionPro are leveraging their brand recognition and comprehensive feature sets to maintain market share. However, agile startups and specialized providers are offering innovative solutions tailored to specific healthcare niches, such as patient experience surveys, clinical trial feedback collection, and employee satisfaction assessments within the medical sector. The market's segmentation includes software-as-a-service (SaaS) offerings, on-premise solutions, and various pricing models catering to different organizational needs and budgets. Geographical expansion will be key for future market growth, with substantial opportunities in developing regions seeking to improve healthcare quality and efficiency through data-driven strategies.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

The World Health Survey was implemented by WHO in 2002–2004 in partnership with 70 countries to generate information on the health of adult populations and health systems. The total sample size in these cross-sectional studies includes over 300,000 individuals. Survey materials and data are available through the WHO World Health Survey Data Archive accessible from the WHS webpage. (From the WHO World Health Survey webpage).

Abstract

The Service Delivery Indicators (SDI) are a set of health and education indicators that examine the effort and ability of staff and the availability of key inputs and resources that contribute to a functioning school or health facility. The indicators are standardized, allowing comparison between and within countries over time.

The Health SDIs include healthcare provider effort, knowledge and ability, and the availability of key inputs (for example, basic equipment, medicines and infrastructure, such as toilets and electricity). The indicators provide a snapshot of the health facility and assess the availability of key resources for providing high quality care.

The Kenya SDI Health survey team visited a sample of 3,098 health facilities across Kenya between March and July 2018. The 2018 Kenya SDI is the largest to date. The survey team collected rosters covering 24,098 workers for absenteeism and assessed 4,499 health workers for competence using patient case simulation.

Geographic coverage

National

Analysis unit

Health facilities and healthcare providers

Universe

All health facilities providing primary-level care

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling strategy for SDI surveys is designed towards attaining indicators that are accurate and representative at the national level, as this allows for proper cross-country (i.e. international benchmarking) and across time comparisons, when applicable. In addition, other levels of representativeness are sought to allow for further disaggregation (rural/urban areas, public/private facilities, subregions, etc.) during the analysis stage.

The sampling strategy for SDI surveys follows a multistage sampling approach. The main units of analysis are facilities (schools and health centers) and providers (health and education workers: teachers, doctors, nurses, facility managers, etc.). The multi-stage sampling approach makes sampling procedures more practical by dividing the selection of large populations of sampling units in a step-by-step fashion. After defining the sampling frame and categorizing it by stratum, a first stage selection of sampling units is carried out independently within each stratum. Often, the primary sampling units (PSU) for this stage are cluster locations (e.g. districts, communities, counties, neighborhoods, etc.) which are randomly drawn within each stratum with a probability proportional to the size (PPS) of the cluster (measured by the location’s number of facilities, providers or pupils). Once locations are selected, a second stage takes place by randomly selecting facilities within location (either with equal probability or with PPS) as secondary sampling units. At a third stage, a fixed number of health and education workers and pupils are randomly selected within facilities to provide information for the different questionnaire modules.

Detailed information about the specific sampling process is available in the associated SDI Country Report included as part of the documentation that accompany these datasets.

Mode of data collection

Face-to-face [f2f]

Research instrument

The SDI Health Survey Questionnaire consists of four modules, plus weights:

Module 1: General Information - Administered to the health facility manager to collect information on equipment, medicines, infrastructure and other facets of the health facility.

Module 2: Provider Absence - A roster of healthcare providers is collected and absence measured.

Module 3: Clinical Vignettes – A selection of providers are given clinical vignettes to measure knowledge of common medical conditions.

Module 4: Public expenditure tracking - Information on facility finances

Weights: Weights for facilities, absentee-related analyses and clinical vignette analyses.

Cleaning operations

Quality control was performed in Stata.

Datasets dating from 1986 to the present are available for 93 countries in which data were collect through Household questionnaires, Women's questionnaires, Men's questionnaires, Biomarker's questionnaires, and Fieldworker's questionnaires. The following data types are produced from the collected data : Household Recode, Household Member Recode, Individual Women's Recode, Births Recode, Children's Recode, Men's Recode, Couple's Recode, Geographic Data, Geospatial Covariates. To view surveys and available datasets go to https://dhsprogram.com/data/available-datasets.cfm. Access to datasets for DHS surveys and their supporting documents may be granted to individuals who register at https://dhsprogram.com/data/new-user-registration.cfm and create a new research project request.

The New York City Community Health Survey (CHS) is a telephone survey conducted annually by the DOHMH, Division of Epidemiology, Bureau of Epidemiology Services. CHS provides robust data on the health of New Yorkers, including neighborhood, borough, and citywide estimates on a broad range of chronic diseases and behavioral risk factors. The data are analyzed and disseminated to influence health program decisions, and increase the understanding of the relationship between health behavior and health status. For more information see EpiQuery, https://a816-health.nyc.gov/hdi/epiquery/visualizations?PageType=ps&PopulationSource=CHS

The National Health Survey of Spain 2017 (ENSE 2017), carried out by the Ministry of Health, Consumption and Social Welfare with the collaboration of the National Institute of Statistics, collects health information related to the population residing in Spain in 23,860 households. It is a five-yearly survey that allows knowing numerous aspects of the health of citizens at a national and regional level, and planning and evaluating actions in health matters. It consists of 3 questionnaires, household, adult and minor, which address 4 large areas: sociodemographic, health status, use of health services and health determinants.

These data are the part of the two National Health Surveys in the Republic of Serbia, conducted in 2006 and 2013, funded by the Ministry of Health. The survey was conducted in accordance with the methodology and instruments of the European Health Interview Survey wave 2. Both surveys were conducted as cross sectional studies. Population presented in the research included adults, aged 19 and more. The researches excluded people living on the territory of Kosovo and Metohija, as well as people with residence addresses in Special institutions (retirement homes, prisons, psychiatric clinics). Data on basic characteristics of the interviewees, health condition of the interviewees, using hospital and non-hospital health care services and prevention check-ups and unachieved need for health care was obtained through a face-to-face interview carried out at home, while information at the level of the household was obtained by means of a household questionnaire. The questions were validated instruments based on the standard questionnaires from similar types of surveys.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which

The Public Health Agency of Sweden annually conducts a national public health survey, Health on Equal Terms, including a sample of 20 000 people aged 16-84 years. The survey, which was conducted for the first time in 2004, is an on going collaboration between the The Public Health Agency of Sweden and county councils/regions in Sweden and is carried out with help from Statistics Sweden (SCB). All studies, since 2004, can be found under the tab Related studies.

The survey is voluntary and done with the purpose to investigate the health in the population and to show changes in the population's health over time as a follow up of the national health politics.

The sample is randomly drawn from the Statistics Sweden's population register and includes 20 000 people aged 16-84 years. The personal data is confidential and protected by law and those working with this survey are obliged to practice professional secrecy. Individual answers can not be identified in the results.

The study participants are since 2007 given the opportunity to answer the survey on the web. Since 2012, the web survey is also in English, and since 2014 also in Finnish.

The questionnaire includes about 85 questions. Each county council has its own introduction letter and the questions has been prepared in collaboration with representatives from a number of different community medicine units. The origin and quality of the questions are described in the report "Objective and background of the questions in the national public health survey". Most questions recur each year, but questions can in particular cases be replaced by other questions of good quality and national relevance.

The questions in the national public health survey cover physical and mental health, consumption of pharmaceuticals, contact with healthcare services, dental health, living habits, financial conditions, work and occupation, work environment, safety and social relationships. Data regarding education is collected from the education register, and data of income, economic support, sickness benefits and pensions from the income an taxation register.

Purpose:

The aim is to investigate the health in the population and to show changes in the population's health over time as a follow up of the national health politics.

Healthcare Survey Software Market Outlook

The global healthcare survey software market size was valued at USD 1.5 billion in 2023 and is projected to reach USD 5.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 16.2% during the forecast period. The key growth factor propelling the healthcare survey software market includes the increasing importance of patient feedback and data analytics in improving healthcare services and outcomes.

Healthcare organizations are increasingly recognizing the value of patient feedback in enhancing the quality of care. As healthcare becomes more patient-centric, the demand for efficient tools to gather, analyze, and act on patient feedback has surged. Survey software provides a streamlined method for collecting patient opinions on various aspects of their care, including satisfaction with treatment, interaction with healthcare staff, and overall experience. This feedback is invaluable for healthcare providers aiming to improve service delivery, patient satisfaction, and clinical outcomes.

Another significant growth factor is the advancement in data analytics and integration capabilities. Modern healthcare survey software solutions are equipped with powerful analytics tools that allow organizations to derive actionable insights from collected data. These insights can be used to identify trends, pinpoint areas for improvement, and make informed decisions. The ability to integrate survey data with electronic health records (EHRs) and other healthcare systems further enhances the utility of these platforms, providing a comprehensive view of patient health and experiences.

The shift towards digitalization in healthcare is also driving market growth. The adoption of digital tools for various administrative and clinical tasks has increased efficiency and accuracy, and survey software is no exception. The convenience of deploying surveys through digital platforms, including mobile and web applications, ensures higher response rates and real-time data collection. Additionally, the cloud-based deployment of survey software solutions offers scalability, remote accessibility, and reduced IT overheads, which are particularly beneficial for large healthcare organizations.

Survey Software plays a pivotal role in the healthcare industry by providing comprehensive tools for collecting and analyzing patient feedback. These platforms enable healthcare providers to design customized surveys that capture detailed patient experiences, leading to more personalized care. The integration of survey software with existing healthcare systems allows for seamless data collection and analysis, offering insights that drive improvements in patient care and operational efficiency. As the demand for precise and actionable patient feedback grows, survey software becomes an indispensable asset in the healthcare sector, facilitating better decision-making and enhancing patient satisfaction.

Regionally, North America holds the largest market share due to the advanced healthcare infrastructure, high adoption rate of digital technologies, and the presence of major market players. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. Factors contributing to this growth include increasing investments in healthcare infrastructure, rising awareness about the importance of patient feedback, and the burgeoning use of digital healthcare solutions. Europe also shows significant potential, driven by regulatory support for patient-centric care and the adoption of advanced healthcare technologies.

Component Analysis

The healthcare survey software market is segmented by component into software and services. The software segment includes various types of survey software solutions that facilitate the creation, distribution, and analysis of surveys. These solutions come with features like customizable templates, automated survey distribution, and advanced analytics. The growing need for real-time feedback and data-driven decision-making is driving the adoption of sophisticated software solutions in the healthcare sector.

Within the software segment, the demand for advanced analytics tools is particularly high. These tools enable healthcare providers to analyze survey data comprehensively and derive actionable insights. The integration capabilities of software solutions with other healthcare systems, such as EHRs and patient management systems, further enh

The global healthcare survey software market is experiencing robust growth, driven by increasing demand for improved patient experience, enhanced healthcare quality, and the need for efficient data collection and analysis within healthcare organizations. The market's compound annual growth rate (CAGR) of 5% from 2019 to 2024 suggests a steadily expanding market. Considering the ongoing digital transformation within the healthcare sector and the increasing adoption of cloud-based solutions, this growth trajectory is expected to continue. The cloud-based segment dominates the market due to its scalability, accessibility, and cost-effectiveness compared to on-premises solutions. Patient feedback applications are particularly prevalent, reflecting the growing emphasis on patient-centric care and the use of feedback for service improvement. Key players such as Qualtrics, SurveyMonkey, and others are actively innovating, offering advanced features like real-time data analysis, automated reporting, and integration with Electronic Health Records (EHR) systems. This enhances the value proposition of these solutions, attracting a broader range of healthcare providers and researchers. The market's expansion is further propelled by government initiatives promoting patient engagement and the adoption of value-based care models that require robust data-driven insights. Despite the positive outlook, certain restraints exist. These include concerns related to data privacy and security, the cost of implementation and maintenance of software, and the need for comprehensive staff training on the use of such systems. However, ongoing technological advancements in data encryption and security, along with the increasing affordability of cloud-based solutions, are mitigating these challenges. The market is segmented by deployment type (cloud-based and on-premises) and application (patient feedback, hospital feedback, and others). While North America currently holds a significant market share due to early adoption and advanced technological infrastructure, growth is anticipated in regions like Asia Pacific, driven by increasing healthcare investments and digital health initiatives in developing economies. The continued focus on patient satisfaction, coupled with the increasing adoption of data analytics in healthcare, will fuel the market's expansion in the coming years. Future growth will depend on the continued development of user-friendly, secure, and cost-effective healthcare survey software solutions that meet the specific needs of various stakeholders within the healthcare ecosystem.

The Health Survey provides the most complete picture possible of developments in the health, medical contacts, lifestyle and preventive behaviour of the Dutch population.

Statistics Netherlands has been conducting an annual Health Survey since 1981. In the period 1997-2009, the Health Survey was part of the Continuing Survey on Living Conditions (POLS). As of 2010, the Health Survey is being conducted as an independent survey again.

Abstract

Different countries have different health outcomes that are in part due to the way respective health systems perform. Regardless of the type of health system, individuals will have health and non-health expectations in terms of how the institution responds to their needs. In many countries, however, health systems do not perform effectively and this is in part due to lack of information on health system performance, and on the different service providers.

The aim of the WHO World Health Survey is to provide empirical data to the national health information systems so that there is a better monitoring of health of the people, responsiveness of health systems and measurement of health-related parameters.

The overall aims of the survey is to examine the way populations report their health, understand how people value health states, measure the performance of health systems in relation to responsiveness and gather information on modes and extents of payment for health encounters through a nationally representative population based community survey. In addition, it addresses various areas such as health care expenditures, adult mortality, birth history, various risk factors, assessment of main chronic health conditions and the coverage of health interventions, in specific additional modules.

The objectives of the survey programme are to: 1. develop a means of providing valid, reliable and comparable information, at low cost, to supplement the information provided by routine health information systems. 2. build the evidence base necessary for policy-makers to monitor if health systems are achieving the desired goals, and to assess if additional investment in health is achieving the desired outcomes. 3. provide policy-makers with the evidence they need to adjust their policies, strategies and programmes as necessary.

Geographic coverage

The survey sampling frame must cover 100% of the country's eligible population, meaning that the entire national territory must be included. This does not mean that every province or territory need be represented in the survey sample but, rather, that all must have a chance (known probability) of being included in the survey sample.

There may be exceptional circumstances that preclude 100% national coverage. Certain areas in certain countries may be impossible to include due to reasons such as accessibility or conflict. All such exceptions must be discussed with WHO sampling experts. If any region must be excluded, it must constitute a coherent area, such as a particular province or region. For example if ¾ of region D in country X is not accessible due to war, the entire region D will be excluded from analysis.

Analysis unit

Households and individuals

Universe

The WHS will include all male and female adults (18 years of age and older) who are not out of the country during the survey period. It should be noted that this includes the population who may be institutionalized for health reasons at the time of the survey: all persons who would have fit the definition of household member at the time of their institutionalisation are included in the eligible population.

If the randomly selected individual is institutionalized short-term (e.g. a 3-day stay at a hospital) the interviewer must return to the household when the individual will have come back to interview him/her. If the randomly selected individual is institutionalized long term (e.g. has been in a nursing home the last 8 years), the interviewer must travel to that institution to interview him/her.

The target population includes any adult, male or female age 18 or over living in private households. Populations in group quarters, on military reservations, or in other non-household living arrangements will not be eligible for the study. People who are in an institution due to a health condition (such as a hospital, hospice, nursing home, home for the aged, etc.) at the time of the visit to the household are interviewed either in the institution or upon their return to their household if this is within a period of two weeks from the first visit to the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING GUIDELINES FOR WHS

Surveys in the WHS program must employ a probability sampling design. This means that every single individual in the sampling frame has a known and non-zero chance of being selected into the survey sample. While a Single Stage Random Sample is ideal if feasible, it is recognized that most sites will carry out Multi-stage Cluster Sampling.

The WHS sampling frame should cover 100% of the eligible population in the surveyed country. This means that every eligible person in the country has a chance of being included in the survey sample. It also means that particular ethnic groups or geographical areas may not be excluded from the sampling frame.

The sample size of the WHS in each country is 5000 persons (exceptions considered on a by-country basis). An adequate number of persons must be drawn from the sampling frame to account for an estimated amount of non-response (refusal to participate, empty houses etc.). The highest estimate of potential non-response and empty households should be used to ensure that the desired sample size is reached at the end of the survey period. This is very important because if, at the end of data collection, the required sample size of 5000 has not been reached additional persons must be selected randomly into the survey sample from the sampling frame. This is both costly and technically complicated (if this situation is to occur, consult WHO sampling experts for assistance), and best avoided by proper planning before data collection begins.

All steps of sampling, including justification for stratification, cluster sizes, probabilities of selection, weights at each stage of selection, and the computer program used for randomization must be communicated to WHO

STRATIFICATION

Stratification is the process by which the population is divided into subgroups. Sampling will then be conducted separately in each subgroup. Strata or subgroups are chosen because evidence is available that they are related to the outcome (e.g. health, responsiveness, mortality, coverage etc.). The strata chosen will vary by country and reflect local conditions. Some examples of factors that can be stratified on are geography (e.g. North, Central, South), level of urbanization (e.g. urban, rural), socio-economic zones, provinces (especially if health administration is primarily under the jurisdiction of provincial authorities), or presence of health facility in area. Strata to be used must be identified by each country and the reasons for selection explicitly justified.

Stratification is strongly recommended at the first stage of sampling. Once the strata have been chosen and justified, all stages of selection will be conducted separately in each stratum. We recommend stratifying on 3-5 factors. It is optimum to have half as many strata (note the difference between stratifying variables, which may be such variables as gender, socio-economic status, province/region etc. and strata, which are the combination of variable categories, for example Male, High socio-economic status, Xingtao Province would be a stratum).

Strata should be as homogenous as possible within and as heterogeneous as possible between. This means that strata should be formulated in such a way that individuals belonging to a stratum should be as similar to each other with respect to key variables as possible and as different as possible from individuals belonging to a different stratum. This maximises the efficiency of stratification in reducing sampling variance.

MULTI-STAGE CLUSTER SELECTION

A cluster is a naturally occurring unit or grouping within the population (e.g. enumeration areas, cities, universities, provinces, hospitals etc.); it is a unit for which the administrative level has clear, nonoverlapping boundaries. Cluster sampling is useful because it avoids having to compile exhaustive lists of every single person in the population. Clusters should be as heterogeneous as possible within and as homogenous as possible between (note that this is the opposite criterion as that for strata). Clusters should be as small as possible (i.e. large administrative units such as Provinces or States are not good clusters) but not so small as to be homogenous.

In cluster sampling, a number of clusters are randomly selected from a list of clusters. Then, either all members of the chosen cluster or a random selection from among them are included in the sample. Multistage sampling is an extension of cluster sampling where a hierarchy of clusters are chosen going from larger to smaller.

In order to carry out multi-stage sampling, one needs to know only the population sizes of the sampling units. For the smallest sampling unit above the elementary unit however, a complete list of all elementary units (households) is needed; in order to be able to randomly select among all households in the TSU, a list of all those households is required. This information may be available from the most recent population census. If the last census was >3 years ago or the information furnished by it was of poor quality or unreliable, the survey staff will have the task of enumerating all households in the smallest randomly selected sampling unit. It is very important to budget for this step if it is necessary and ensure that all households are properly enumerated in order that a representative sample is obtained.

It is always best to have as many clusters in the PSU as possible. The reason for this is that the fewer the number of respondents in each PSU, the lower will be the clustering effect which