[{"innerBlocks":[],"name":"core\/freeform","postId":126264,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"Clinical documentation integrity is becoming increasingly important in the healthcare field. Under both fee-for-service and value-based reimbursement, accurate and complete clinical documentation is the foundation for correct medical record coding and quality measures reporting.

While clinical documentation improvement (CDI) programs have primarily been deployed in the inpatient setting, hospitals and health systems recognize that clinical documentation across all care settings is a key component to financial health.

With the majority of inpatient CDI programs having reached a level of success, maturity and sustainability, many hospital-based CDI programs are expanding beyond inpatient encounters and into outpatient settings including physician practices, clinics, rehabilitation and more. Before investing in outpatient CDI expansion, however, many executive teams require that outpatient programs demonstrate a positive return on investment during a pilot testing phase.

There are three common hurdles to overcome when planning an expansion of your inpatient CDI program. All three challenges stem from unique differences between inpatient and outpatient physician documentation goals, workflow, and technology.

Diverse goals<\/b>
Inpatient CDI programs have traditionally focused on capturing complications and comorbidities during the admission. This is in response to DRG-based reimbursement payment systems in place since the early 1990s. Both outpatient and inpatient CDI share the common goals of accurate, complete, and consistent documentation. However, outpatient CDI is more focused on capturing the chronic conditions being managed over time and becoming familiar with documentation and codes that factor into risk adjustment, beyond the CC and MCC lists.

Now outpatient CDI specialists must understand hierarchical condition categories (HCCs), MACRA, MIPS and a wide variety of value-based reimbursement programs they may be unfamiliar with if their prior focus was based on the Inpatient Prospective Payment System. Case identification, prioritization, and review processes must shift with these new elements in mind.

Longitudinal focus vs. single admission focus<\/b>
The longitudinal nature of outpatient care and chronic disease management by a primary care physician or specialist is vastly different from the single-encounter approach currently used for inpatient hospital CDI programs. The focus of most inpatient CDI programs is on a single hospital episode of care, with a national average length of stay of approximately five days. Payment for outpatient care, however, may encompass a reporting period of 12 months or longer.

The duration of outpatient treatment, and number of associated encounters, magnifies all the various data integrity issues already experienced in inpatient documentation programs. Outpatient CDI specialists are looking at the entirety of the patients\u2019 care, not just one encounter.

Data<\/b>
The effort required to manually comb through the vast data generated on the outpatient side is daunting. Multiple source systems are usually involved, and clinical documentation is captured in a variety of formats. This can make it difficult for outpatient CDI specialists to create a complete patient picture and meet the goal of timely reviews. If concurrent or pre-bill CDI reviews are expected, the time frame for CDI specialist intervention becomes even shorter.

Technology is one solution to address these challenges. Inpatient CDI technology in use today varies from program to program. Some organizations have dedicated best of breed CDI software; some have coding or other revenue cycle applications that have been adapted for CDI use; some use home-grown databases or spreadsheets; and some are using integrated modules within the EHR as more vendors strive to create a true \u201cone stop shop.\u201d

Most robust tools today have incorporated some level of artificial intelligence (AI) or machine learning. One of the most common types of AI is natural language processing (NLP). These systems sort through information that is input, dictated, or transcribed, and, when combined with discrete clinical data, quickly identify and flag undocumented, unsupported, or unspecified clinical documentation terms automatically. CDI specialists are notified of cases where documentation can or should be clarified. If a system isn\u2019t leveraging this type of technology then they are often at the mercy of what can be gathered from discrete data elements collected and entered by end users.

Regardless of the system used, many organizations recognize that CDI technology created and designed to support inpatient CDI needs does not automatically meet the emerging needs of outpatient CDI programs.

Most hospitals and health systems attempt to leverage the inpatient CDI technology, people, and processes they already have in place to support their outpatient program expansion. We believe the best option is to create a cohesive CDI program that focuses on the entire patient journey, not just a single encounter. The documentation should be consistent whether the patient is receiving services as an inpatient or outpatient. Communication should be transparent across care settings. This can be accomplished by ensuring your software is analyzing all the pertinent data.

Investing in business intelligence or data analytics software that can be utilized across the organization is a much more practical use of scarce resources. All the organization\u2019s key data from the EHR and other systems can be funneled to this software, and the data can be used to identify and monitor key indicators across the organization.

Data analytics can assist with the following functions to better support an outpatient CDI program.
Case Finding\/Identification:<\/b> Identification of all outpatient cases that need to be reviewed based on provided inclusions, exclusions, and other custom parameters. With analytics, case identification expands beyond a single payer or physician to find all patients where HCC capture can be improved or risk adjustment factors better defined. <\/li>
Case Prioritization:<\/b> Identification of outpatient cases that have an opportunity. If cases that don\u2019t need to be reviewed by the CDI specialist are filtered out or de-prioritized, this maximizes efficiency and ensures that reviewers are spending their productive time on encounters that make a difference. We often know which patients are \u201chigh risk\u201d for documentation integrity issues but analytics can help us to identify, or predict, the factors that may put them at risk for documentation integrity. If we proactively identify these priority cases, then we can proactively notify physicians and care coordinators in advance or at the time of service. <\/li>
Workflows:<\/b> Once cases have been prioritized, the system automatically sends them to CDI specialist work lists\/pools\/queues for review and action. CDI specialists, physicians, coders, auditors, quality personnel, and care coordinators should all be able to communicate and route work to one another. <\/li>
Messaging\/Alerts:<\/b> Messages can be routed directly to the EHR when patients are analyzed by the software or reviewed by a user so physicians and care coordinators are apprised of clinical actions or interventions that are required during the patient visit. <\/li>
Templates:<\/b> Inpatient CDI specialists traditionally use retrospective queries, after the provider has documented, to communicate documentation gaps. Unfortunately, in the outpatient world where patient visits average somewhere around 20 minutes or less, retrospective queries aren\u2019t typically welcomed. Instead, we\u2019ve seen success with customized EHR templates. Condition specific mini-templates can be built within the EHR to substantiate the HCC condition, resulting in optimal payment for that visit. Pre-visit review and analysis by the clinical documentation specialist (CDS) can help the CDS route the needed templates to the physician so they are available at the time of service. <\/li><\/ul>
Finally, even technology that supports outpatient CDI must be supplemented by staff with the right skills and capabilities. CDI specialists with deep knowledge of Medicare Part B, HCCs and quality measures reporting are essential.

Health information management professionals have a unique opportunity to continue to demonstrate their value to CDI programs. An industry poll recently caused a stir when it reported that 47 percent of respondents do not consider HIM professionals when hiring for CDI roles.

HIM pros with data analytics skills should be engaged to support the technology infrastructure for outpatient CDI programs. They can analyze the data to identify proper patients for outpatient CDI review, as they have the unique ability to decode EHR downloads and output. HIM professionals have been trained to understand the subtle nuances that appear in the data, while many clinicians, unfamiliar with data science concepts, may miss the elusive significance.

Clinical documentation improvement programs are no longer inpatient vs. outpatient CDI. They are evolving into whole patient CDI and encompassing every step of the patient\u2019s journey. A longitudinal look at clinical documentation integrity supported by new technology approaches and upgraded staff skills have become the new normal.","saveContent":"Clinical documentation integrity is becoming increasingly important in the healthcare field. Under both fee-for-service and value-based reimbursement, accurate and complete clinical documentation is the foundation for correct medical record coding and quality measures reporting.

While clinical documentation improvement (CDI) programs have primarily been deployed in the inpatient setting, hospitals and health systems recognize that clinical documentation across all care settings is a key component to financial health.

With the majority of inpatient CDI programs having reached a level of success, maturity and sustainability, many hospital-based CDI programs are expanding beyond inpatient encounters and into outpatient settings including physician practices, clinics, rehabilitation and more. Before investing in outpatient CDI expansion, however, many executive teams require that outpatient programs demonstrate a positive return on investment during a pilot testing phase.

There are three common hurdles to overcome when planning an expansion of your inpatient CDI program. All three challenges stem from unique differences between inpatient and outpatient physician documentation goals, workflow, and technology.

Diverse goals<\/b>
Inpatient CDI programs have traditionally focused on capturing complications and comorbidities during the admission. This is in response to DRG-based reimbursement payment systems in place since the early 1990s. Both outpatient and inpatient CDI share the common goals of accurate, complete, and consistent documentation. However, outpatient CDI is more focused on capturing the chronic conditions being managed over time and becoming familiar with documentation and codes that factor into risk adjustment, beyond the CC and MCC lists.

Now outpatient CDI specialists must understand hierarchical condition categories (HCCs), MACRA, MIPS and a wide variety of value-based reimbursement programs they may be unfamiliar with if their prior focus was based on the Inpatient Prospective Payment System. Case identification, prioritization, and review processes must shift with these new elements in mind.

Longitudinal focus vs. single admission focus<\/b>
The longitudinal nature of outpatient care and chronic disease management by a primary care physician or specialist is vastly different from the single-encounter approach currently used for inpatient hospital CDI programs. The focus of most inpatient CDI programs is on a single hospital episode of care, with a national average length of stay of approximately five days. Payment for outpatient care, however, may encompass a reporting period of 12 months or longer.

The duration of outpatient treatment, and number of associated encounters, magnifies all the various data integrity issues already experienced in inpatient documentation programs. Outpatient CDI specialists are looking at the entirety of the patients\u2019 care, not just one encounter.

Data<\/b>
The effort required to manually comb through the vast data generated on the outpatient side is daunting. Multiple source systems are usually involved, and clinical documentation is captured in a variety of formats. This can make it difficult for outpatient CDI specialists to create a complete patient picture and meet the goal of timely reviews. If concurrent or pre-bill CDI reviews are expected, the time frame for CDI specialist intervention becomes even shorter.

Technology is one solution to address these challenges. Inpatient CDI technology in use today varies from program to program. Some organizations have dedicated best of breed CDI software; some have coding or other revenue cycle applications that have been adapted for CDI use; some use home-grown databases or spreadsheets; and some are using integrated modules within the EHR as more vendors strive to create a true \u201cone stop shop.\u201d

Most robust tools today have incorporated some level of artificial intelligence (AI) or machine learning. One of the most common types of AI is natural language processing (NLP). These systems sort through information that is input, dictated, or transcribed, and, when combined with discrete clinical data, quickly identify and flag undocumented, unsupported, or unspecified clinical documentation terms automatically. CDI specialists are notified of cases where documentation can or should be clarified. If a system isn\u2019t leveraging this type of technology then they are often at the mercy of what can be gathered from discrete data elements collected and entered by end users.

Regardless of the system used, many organizations recognize that CDI technology created and designed to support inpatient CDI needs does not automatically meet the emerging needs of outpatient CDI programs.

Most hospitals and health systems attempt to leverage the inpatient CDI technology, people, and processes they already have in place to support their outpatient program expansion. We believe the best option is to create a cohesive CDI program that focuses on the entire patient journey, not just a single encounter. The documentation should be consistent whether the patient is receiving services as an inpatient or outpatient. Communication should be transparent across care settings. This can be accomplished by ensuring your software is analyzing all the pertinent data.

Investing in business intelligence or data analytics software that can be utilized across the organization is a much more practical use of scarce resources. All the organization\u2019s key data from the EHR and other systems can be funneled to this software, and the data can be used to identify and monitor key indicators across the organization.

Data analytics can assist with the following functions to better support an outpatient CDI program.
Case Finding\/Identification:<\/b> Identification of all outpatient cases that need to be reviewed based on provided inclusions, exclusions, and other custom parameters. With analytics, case identification expands beyond a single payer or physician to find all patients where HCC capture can be improved or risk adjustment factors better defined. <\/li>
Case Prioritization:<\/b> Identification of outpatient cases that have an opportunity. If cases that don\u2019t need to be reviewed by the CDI specialist are filtered out or de-prioritized, this maximizes efficiency and ensures that reviewers are spending their productive time on encounters that make a difference. We often know which patients are \u201chigh risk\u201d for documentation integrity issues but analytics can help us to identify, or predict, the factors that may put them at risk for documentation integrity. If we proactively identify these priority cases, then we can proactively notify physicians and care coordinators in advance or at the time of service. <\/li>
Workflows:<\/b> Once cases have been prioritized, the system automatically sends them to CDI specialist work lists\/pools\/queues for review and action. CDI specialists, physicians, coders, auditors, quality personnel, and care coordinators should all be able to communicate and route work to one another. <\/li>
Messaging\/Alerts:<\/b> Messages can be routed directly to the EHR when patients are analyzed by the software or reviewed by a user so physicians and care coordinators are apprised of clinical actions or interventions that are required during the patient visit. <\/li>
Templates:<\/b> Inpatient CDI specialists traditionally use retrospective queries, after the provider has documented, to communicate documentation gaps. Unfortunately, in the outpatient world where patient visits average somewhere around 20 minutes or less, retrospective queries aren\u2019t typically welcomed. Instead, we\u2019ve seen success with customized EHR templates. Condition specific mini-templates can be built within the EHR to substantiate the HCC condition, resulting in optimal payment for that visit. Pre-visit review and analysis by the clinical documentation specialist (CDS) can help the CDS route the needed templates to the physician so they are available at the time of service. <\/li><\/ul>
Finally, even technology that supports outpatient CDI must be supplemented by staff with the right skills and capabilities. CDI specialists with deep knowledge of Medicare Part B, HCCs and quality measures reporting are essential.

Health information management professionals have a unique opportunity to continue to demonstrate their value to CDI programs. An industry poll recently caused a stir when it reported that 47 percent of respondents do not consider HIM professionals when hiring for CDI roles.

HIM pros with data analytics skills should be engaged to support the technology infrastructure for outpatient CDI programs. They can analyze the data to identify proper patients for outpatient CDI review, as they have the unique ability to decode EHR downloads and output. HIM professionals have been trained to understand the subtle nuances that appear in the data, while many clinicians, unfamiliar with data science concepts, may miss the elusive significance.

Clinical documentation improvement programs are no longer inpatient vs. outpatient CDI. They are evolving into whole patient CDI and encompassing every step of the patient\u2019s journey. A longitudinal look at clinical documentation integrity supported by new technology approaches and upgraded staff skills have become the new normal.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

How to expand CDI programs into outpatient settings

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