The success of value-based healthcare is dependent on data. It is impossible to measure the “value” achieved without having a solid framework to measure the desired outcome and associated costs and ensuring that quality data are collected and managed. Embracing value-based healthcare inevitably requires measuring health outcomes and costs. Progress is well underway in developing methodologies and approaches for tracking and better making use of the data.
Digital infrastructure and data management
In chapter 1, we covered the essential components for creating a value-based healthcare service system. One of the key enablers is “being able to measure meaningful outcomes and associated costs”.
Depending on the specific case, the ability to measure the value (or impact) of therapies and interventions requires data and analytics. In most cases, data collected from a single organization or care setting is not sufficient, in which case organizations need to either integrate other data sources with their solutions or to contribute their own data to an information exchange system.
The ability to measure meaningful outcomes and costs requires both horizontal and vertical data integration. Horizontal integration refers to sharing data between providers, for example between public primary care, private occupational healthcare, and third-sector service providers. Vertical integration refers, for example, to data sharing between primary and specialty care. To measure the efficacy of services, one needs to add outcomes data from public or private sources, such as a health information exchange (HIE) or private insurers claims data.
Types of data
Many types and sources of data are used in healthcare today. The most important data in clinical work is patient records. Patient records are typically inputted into electronic health record (EHR) systems by clinicians and include data such as lab results, patient medication lists, discharge summaries, and referral letters. The primary use case for patient records is clinical work by clinicians. Other use cases include using aggregated data for population health management (for example risk stratification) and to analyze the effectiveness of therapies.
Electronic health record example: Apotti, a modern fully integrated system
The Apotti system is currently being rolled out across several municipalities in Southern Finland. Apotti is based on Epic systems’ technology and after the system is fully implemented it promises to integrate data and care pathways across all care settings – from primary care to tertiary care. An additional unique feature of Apotti is that it includes social and healthcare integration.
The Apotti system handles both vertical and horizontal integration needs, meaning integration across care settings and across administrative silos of health and social care. Horizontal integration of social and health data should lead to a better understanding of the social determinants of health, such as health risks posed by living environment, socio-economic status, or lifestyle choices. Vertical integration of primary and specialty care improves patient safety and outcomes as clinicians have access to comprehensive patient data.
Epic systems’ electronic health record features structured input of data, which means that instead of free text, clinicians input patient data using sophisticated structured tools based on, for example, diagnostic decision-making trees. A well-structured dataset is more reliable and enables the use of the data for powerful population health solutions and AI-powered diagnostics.
Outcome data is typically stored in many systems. These include insurers’ claims data systems and national census bureau data on causes of death or reasons for disability pensions.
Personal health records (PHRs) are increasingly important. Personal health records store data that individuals collect and contribute themselves. This data may include such things as self-measured blood glucose levels and wellbeing data collected by wearable devices (activity trackers). The role of personal data is increasing as wearable devices are becoming more affordable, which supports widespread adoption. At the same time, computing power is increasing exponentially, which enables new types of data analytics that can offer a much better picture of patients’ lifestyle-related health risks.
Data storage and integration
There are many strategies for data integration. On a technical level, the main strategies are point-to-point integrations that are used when a sender has to send a message to a single receiver, and health information exchanges, which are platforms where many organizations share their data.
Point-to-point integrations are necessary to share data between separate information systems within a hospital system where each clinic or medical specialty group often has their own separate solutions in use. An example of this is picture archiving and communication systems (PACS) that are used in radiology to store images. For those images to be easily accessible by clinicians, a picture archiving and communication system is typically integrated into an electronic health record system.
Insights from data
Combined data from various sources can be used in clinical decision making, population health management, research, development, and innovation.
Clinical decision making is the most common use case for patient records. Clinicians use patient data, or insights that are derived from that data, to decide the optimal care for patients. The most advanced solutions use artificial intelligence (AI) to derive insights from vast amounts of data. An AI solution can effortlessly compare thousands of patients and detect anomalies in longitudinal data (tracking the same customer across time) – a feat that is impossible for any human to achieve.
Population health management uses aggregate data to identify at-risk populations or a thin slice of individual level data to infer individual health risks. Population health management does not typically require all of the data stored in an electronic health record or health information exchange system. Most use cases, like risk stratification in its basic form, require data on diagnoses.
Why measuring outcomes is essential
A key goal for every doctor/healthcare professional is to help their patients by curing diseases, relieving pain, and helping them to manage their health over time. In order to be able to do this even more effectively, information on treatment outcomes is needed. By measuring treatment outcomes, medical professionals learn about and thus improve patients’ lives. When internationally accepted indicators are used, the information obtained from them is comparable and can be used to learn more widely. Measuring outcomes also helps to motivate physicians to compare their performance and learn from each other.
For value-based healthcare to be successful it’s important to measure the most relevant outcomes for patients. Instead of only comparing certain clinical indicators such as infection rates and mortality, the patient experience should also be measured. Patient-reported outcome measures (PROMs) are, for example, a good way to measure overall quality of life.
Examples of outcome metrics
ICHOM standard sets: Inflammatory bowel disease
A multidisciplinary 25-member working committee developed the evidence-based Standard Set of Patient-Centered Outcome Measures for Patients with Inflammatory Bowel Disease (IBD) for use in a variety of healthcare settings. Patients, patient associations, gastroenterologists, surgeons, specialist nurses, IBD registries, and PROM methodologists were involved in the development work. Minimum standards were developed for people over 16 years of age regarding for example survival, disease management factors, remission, quality of life, nutritional status, and fistulas. The IBD standard set provides an international model for relevant, easy-to-understand, and comparable results for implementing value-based healthcare for IBD.
Patient-reported outcome measures (PROMs)
What are patient-reported outcome measures?
Patient-reported outcome measures are defined by the NHS as “standardized, validated questionnaires (which are called instruments) completed by patients to measure their perception of their functional well-being and health status” (National Health Service, 2009). Patients rate their health by scoring the severity of symptoms or their difficulty in completing certain tasks or routine activities.
In terms of best practices, it is useful to compare patient-reported outcome measures because practices can be systematically improved and harmonized. By comparing results and improving procedures, the quality of care improves and can be reflected in the patient’s wellbeing and quality of life. From the patient’s point of view, the systematic measurement of patient-reported outcome measures and the easy availability of results (transparency) leads to better autonomy, because the patient can, for example, choose their treatment site based on the actual results.
The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials
The mission of the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) is to develop consensus reviews and recommendations for improving the design, execution, and interpretation of clinical trials of treatments for pain. The first IMMPACT meeting was held in November 2002, and there have been a total of twenty-three consensus meetings on clinical trials of treatments for acute and chronic pain in adults and children.
For example, the initial 2003 IMMPACT recommendations for “core domains for clinical trials of chronic pain treatment efficacy and effectiveness” are now routinely reported in acute pain trials. These domains include: pain, physical functioning, emotional functioning, participant ratings of global improvement, symptoms and adverse events, and participant disposition (including adherence to the treatment regimen and reasons for premature withdrawal from the trial).
Oral healthcare measures
At present, treatment outcomes are not generally measured in oral healthcare, although patient needs and expectations have increased as opportunities to treat and prevent a variety of dental problems have increased. Value-based healthcare, or in this case value-based oral healthcare, offers increased transparency on oral healthcare outcomes relative to the cost of dentistry. This is an opportunity for oral healthcare to improve treatment outcomes, focus on preventing oral healthcare diseases and problems, and help improve public health. The continuous improvement in healthcare is much about patient selection and patient competition.
Measuring oral health outcomes
Outcomes can be measured at both an individual and a population level. The data is usable for the following:
• Improving dental care
• Medical-dental integration
• Value-based payments
• Public health programming
• Monitoring and needs planning
It’s important to collect data relevant to patients, which typically means using dental patient-reported outcome measures (dPROMs). This can be divided into two broad categories of data: 1) oral health-related quality of life (OHRQoL) and 2) actual physical oral health. Oral health-related quality of life covers a patient’s own perception of their oral health including oral function, orofacial pain, orofacial appearance, and psychosocial impact. For physical oral health, dental caries, periodontitis, and tooth loss are prioritized, with tooth loss being the most eligible for replacing clinical assessment with self reporting.
Source: Science Direct
In Finland, patients already have the right to choose in which hospital district they want their illness that requires specialized medical care to be treated. It would be important for patients to see comparable results for the treatment in question, but at present such information is generally not openly available, except for example of treatment access times and post-operative infection statistics.
When a patient chooses a dental practice/dentist in the private sector that specializes in artificial roots/dental implants, they should be able to make that choice by comparing treatment outcomes such as patient-reported outcome measures (for aesthetics or chewing ability), as well as outcomes such as recovery time and complications.
Clinical quality registries
Clinical quality registries are organizations that monitor the quality (appropriateness and effectiveness) of healthcare within specific clinical domains. They do this by routinely collecting, analyzing, and reporting health-related information to create a self-improving health system.
There is evidence for the ability of registry information to drive continuous improvements in patient outcomes and adherence to guideline-recommended care. Systematic and ongoing collection of standardized data on medical and surgical interventions allows the identification and analysis of clinical practice variation and its effect on patient outcomes. Registry data has credibility with clinicians, which leads to increased use of evidence-based clinical management, decreased variation in care, and improved patient outcomes.
Source: Australian government
Case: National quality registries in Sweden
National quality registries in Sweden contain individualized data concerning patient problems, medical interventions, and outcomes after treatment within all healthcare provision. There are currently more than 100 national quality registries (NQRs) plus further candidates, all initiated and led by healthcare professionals. They are used in an integrated and active way for continuous learning, improvement, research, and management to create the best possible health and care together with the individual. The accumulating body of data has allowed Swedish clinicians to identify which providers deliver the best outcomes, codify their clinical best practices, and share them with other providers – thus improving average health outcomes over time.
How it works
Registries contain data on:
- Patient demographics
- Provider organization characteristics
- The structure of care
- The process of care including patient-reported experience measures (PREMs)
- The outcomes of care including patient-reported outcome measures (PROMs)
National quality registries cover many areas of healthcare, from common to rare conditions and from nursing and primary to tertiary care. Examples include stroke, ischemic heart disease, heart failure, most forms of cancer, bipolar disorder, eating disorders, end-of-life care, neurology with MS, Parkinson’s, dementia care, HIV-AIDS, diabetes mellitus, and orthopedics.
Financing and governance:
- The Ministry of Health and Welfare (70%); Swedish county councils and regions (30%)
- Funding is provided according to specified criteria; $50,000 to $800,000 annually per registry
- The more mature the NQR, the greater the expectations and the potential funding
- Each NQR is governed by a multi-professional group of national experts and often includes patients
National registries were initiated before the emergence of electronic health records and most registries operate in parallel with them. Integration is desired and ongoing.
Example 1: Pediatric diabetes
Good metabolic control is important for children and adolescents with type 1 diabetes. There are usually large differences in mean haemoglobin A1c (HbA1c) in different hospitals and difficulties implementing national guidelines in everyday practice. The Swedish pediatric diabetes quality registry, SWEDIABKIDS, was used as a tool and resource for feedback and outcome measures. It facilitated improvements in the quality of care by pediatric diabetes teams. By involving pediatric diabetes teams in a quality improvement collaborative together with access to a quality register, the quality of pediatric diabetes care can improve, thereby contributing to a reduced risk of late complications for children and adolescents with diabetes.
Example 2: Acute myocardial infarction (heart attack):
NQRs not only allow comparisons within a country across the various regions and facilities, they also allow international comparison on quality of care.
A study demonstrated that 30-day mortality after acute myocardial infarction was 37% higher in the United Kingdom than in Sweden (Chung et al, 2014). Differences in mortality were not explained by differences in casemix, but were partly attributable to recorded differences in clinical care.
International comparisons of care and outcome registries may generate important, actionable insights to guide healthcare policy and clinical practice to improve the quality of health systems and prevent avoidable deaths from acute myocardial infarction.
Researchers are leveraging the provider networks affiliated with Sweden’s quality registries to conduct clinical trials evaluating the effectiveness of treatments and procedures, at roughly 10% of the cost of traditional clinical trials.
Patient assessment and their role in shaping value-based healthcare
Routine use of patient-reported outcome measures has the potential to help transform healthcare and improve healthcare quality. Patient-reported outcome measures allow the efficacy of a clinical intervention to be measured from the patient’s perspective. Questionnaires are given to patients both pre and post-operatively to allow comparison of outcomes before and after a procedure. In addition to outcomes relating to interventions, patient-reported outcome measures measure patients’ perceptions of their general health or their health in relation to a specific disease. Patient-reported outcome measures are a means of measuring clinical effectiveness and safety.
Patient-reported outcome measures can be classified as either generic or disease specific. Generic measures cover a variety of aspects of a broad range of medical conditions, allowing for the overall evaluation of care, quality of life, and the cost effectiveness of interventions. Disease-specific patient-reported outcome measures allow individual aspects of a condition and their impact on outcome to be examined. A combination of the two types is often used.
The purpose of generic health status instruments is to measure the wellbeing of an individual within certain dimensions, generally consisting of measures of physical function, social function, pain, and depression or anxiety. Generic instruments have the advantage of being able to make comparisons between and within interventions.
No single instrument has established itself as the gold standard for measuring patient status. Each instrument measures different dimensions of health, uses different levels of scoring, and references different time periods. Some generic health status instruments provide a single value or utility score for a given health state, while other instruments provide an assessment of a given health state in multiple dimensions.
Examples of generic instruments that have been developed and validated in different populations:
- Quality of life measures (EQ-5D)
- Health Utilities Index
- Quality of wellbeing
- Symptoms such as pain, fatigue, etc.
- Distress, for example depression (K10, PHQ-2) or anxiety (GAD7)
- Functional ability (WHODAS 2.0, ODI)
- Self-reported health status (SF-36)
- Self-efficacy (GSE)
Condition-specific measures ask questions about changes in health status related to a given disease, disability, or surgery. These instruments have the advantage of being able to detect small changes in health or functional status.
Case: NHS patient-reported outcome measures in England for hip and knee replacements
Arthritis damage is the most common reason to need hip replacement while the most common reason for knee replacement surgery is to relieve severe pain caused by osteoarthritis. If the pain interferes with daily activities and nonsurgical treatments haven’t helped or are no longer effective, hip or knee replacement surgeries are considered.
From April 2009 onwards, patients undergoing elective inpatient surgical procedures for hip or knee replacement by the English NHS have been invited to complete pre and post-operative questionnaires on their general and condition-specific health. Patient participation in PROMs is on a voluntary basis.
Improvements in health as perceived by the patients themselves are assessed using condition-specific measures (Oxford Hip Score (OHS) and Oxford Knee Score (OKS)) and general health measures (EQ-5DTM Index and the EQ VAS).
The data is analysed and published online by patient profile, success and satisfaction, health gain for hip replacements, health gain for knee replacements, data quality statement, and patient engagement.
Publications and data showing patient-reported outcome measures can be used by patients to inform their choice of hospital provider and are used by hospital clinicians to inform decisions about individual patients’ direct care. The data has also been used in medical research studies to improve outcomes by comparing scores across different types of treatments. National quality registries are an integral part of healthcare, and they need to be constantly developed and updated. The hospitals and regions should be benchmarked to ensure quality of care.
Below are the key results from 01 Apr 2018 to 31 Mar 2019, published in Feb 2020 on NHS Digital:
- For hip replacements, 97% of patients reported improvements, with an average health gain on the Oxford Hip Score of 22.0
- For knee replacements, 94% of patients reported improvements, with an average health gain on the Oxford Knee Score of 17.0
- 95% of hip replacement patients and 90% of knee replacement patients felt better after the operation
- 93.2% of hip replacement patients and 87% of knee replacement patients thought the results of their operation were excellent, very good, or good
For more on NHS´s national patient-reported outcome measures program, read here
What are patient-reported experience measures (PREMs)?
Patient-reported experience measures are measures of a patient's perception of their personal experience of the healthcare they received.
Difference between PROMs and PREMs
Patient-reported outcome measures and patient-reported experience measures measure different aspects of quality of care (Chapter 1).
For example, patient-reported outcome measures can measure effectiveness of care (does it reduce symptoms, improve function, improve quality of life?) and safety (does it cause harm in terms of mortality/morbidity, are there any complications?).
Patient-reported experience measures on the other hand can measure how people-centered the healthcare is – what do patients think of the healthcare process, e.g. dignity, information, trust in staff, cleanliness, timeliness?
In contrast to patient-reported outcome measures, which have been utilized widely for elective surgical procedures, there has been limited research or practical application of patient-reported experience measures. While generic patient-reported experience measures are important, they risk losing elements of a patient's experience that are specific or weighted towards a particular disease or illness that is the dominant reason for a patient to seek healthcare assistance. This is why both generic and condition-specific patient-reported experience measures would be ideal.
To measure patient-reported experience measures, various indicators are included in validated surveys and questionnaires. For example, in the US, the Consumer Assessment of Healthcare Providers and Systems (CAHPS) program is a multi-year initiative of the Agency for Healthcare Research and Quality (AHRQ). Newer attempts to measure integrated care are driven by organizations such as Picker Institute Europe.
Examples of patient-reported experience measures are as follows:
- Time spent waiting
- Access to and ability to navigate services
- Involvement (consumer and carer) in decision-making
- Knowledge of care plan and pathways
- Quality of communication
- Support to manage long-term condition
- Would they recommend the service to family and friends
Outcome metrics across disease categories
Outcomes that reflect what matter most to patients are infrequently measured in clinical practice. Even when they are captured, the definitions used often vary between countries, making global comparisons and learning unfeasible.
The International Consortium for Health Outcomes Measurement (ICHOM) was founded in 2012 to address the above challenges. ICHOM brings together working groups, organized around a medical condition, consisting of patients, health professionals, researchers, outcomes measurement experts, and policy makers, from major regions of the world. The end result is a globally agreed set of outcomes that reflects what matters most to most patients, organized by disease categories. ICHOM sets are designed to be used in both routine clinical practice and as an endpoint in clinical studies.
The international standards for outcome metrics across key disease categories that ICHOM has so far developed are available online.
The key unit of analysis here is the population of individuals suffering from the same disease or condition, or sharing similar risk profiles. By focusing on distinct population segments, providers can meaningfully compare health outcomes, identify the causes of unnecessary variations in those outcomes, and improve overall outcomes over time.
Source: Harvard Business Review
Example: Cancer cost in Europe
In Europe (EU-27 plus Iceland, Norway, Switzerland, and the United Kingdom), health expenditure on cancer care has almost doubled from €52 billion to €103 billion between 1995 and 2018, whereas the number of newly diagnosed cancer cases has increased by about 50%. The rapid growth in cancer drug expenditure is linked to increased usage (e.g., increased number of cancer patients and new cancer drugs, new patient groups eligible for treatment, use in an adjuvant setting, longer duration of therapy) and to higher (list) prices of new drugs. Health expenditure on cancer care was of a similar magnitude as the sum of non-healthcare costs (informal care costs and loss of productivity) in 2018. Over the last two decades, health spending on cancer has increased faster than the increase in cancer incidence. The productivity loss from premature mortality has decreased because of reductions in mortality in the working-age population.
Source: Hofmarcher et al. 2020
Case: The ICHOM standard set for localized prostate cancer
Prostate cancer is cancer that occurs in the prostate — a small gland in men that produces the seminal fluid that nourishes and transports sperm.
Cancer is the second leading cause of death globally and prostate cancer is the second most frequent cancer diagnosis made in men. Usually prostate cancer grows slowly and is initially confined to the prostate gland, where it may not cause serious harm. However, while some types of prostate cancer grow slowly and may need minimal or even no treatment, other types are aggressive and can spread quickly.
Prostate cancer that's detected early — when it's still confined to the prostate gland — has a better chance of successful treatment.
Doctors and hospitals may approach and diagnose prostate cancer through the prostate-specific antigen (PSA) test, but of greater immediate concern to the average patient may be urinary incontinence or erectile dysfunction. This is why there is a need to change how diseases are evaluated and how health providers and patients talk and work together to improve patient health. The ICHOM standard set for localized prostate cancer is one example of how this works in practice. The objectives of ICHOM standard set development are to promote informed decision making, to enhance quality care, and to reduce costs. By focusing on the health outcomes, the results that matter most to patients, patients can demand meaningful outcomes from their health providers and providers can respond with data-driven answers.
The standard set defines 10 to 15 key outcomes and related risk factors that should be tracked for all patients with localized prostate cancer in any country. The purpose is to track, compare, and improve the value of localized prostate cancer treatment. The resulting transparency makes it easier for doctors to choose treatments based on actual outcomes and for patients to make decisions about their treatments.
The standard set for localized prostate cancer is the result of work by an international group of leading urologists and radiation oncologists, measurement experts, and patients. This group was convened and organized by ICHOM.
The standard set was designed around men with clinical American Joint Committee of Cancer (AJCC) stages T1–T4 (how far the tumor has progressed, see note below) localized prostate cancer treated with curative intent or followed with active surveillance. This scope covers >90% of men with newly diagnosed prostate cancer (based on screening studies in the United States and Europe).
The standard set represents who should be tracked, what should be measured and when, and what data is necessary to make meaningful comparisons. Standardized outcomes measurement means physicians can compare performance globally, allowing them to learn from each other and rapidly improve the care provided to patients.
Examples of what is measured and why
- Selected measures of cancer eradication for the standard set include overall survival, cause-specific survival, metastasis-free survival, and biochemical recurrence-free survival (prostate-specific antigen recurrence are intermediate end points, they correlate highly with patient anxiety and initiation of additional therapy, warranting their inclusion in the set).
- Treatments are classified as accurately as deemed necessary – for example, radical prostatectomy (an operation to remove the prostate gland and tissues surrounding it) alone or combined with adjuvant treatment and frequent post-operation check-ups. Another example is classification of radiation therapy by radiation dose and fraction size, where the goal is to establish common standards to make outcomes comparable to enable continuous improvement.
- Possible treatment complications are a matter of concern to patients and can have a significant impact on long-term outcomes. Common terminology for adverse events was chosen for non-surgically treated patients. A comprehensive grading system for the adverse effects of cancer treatment was designed and is commonly used in clinical trials. For surgically treated patients the Clavien-Dindo classification is suggested.
- Patient-reported health status is needed because physicians tend to underestimate health-related quality of life in prostate cancer patients. Patient-reported outcome measures have been widely implemented, but using only a single recommended patient-reported outcome measure covering all relevant areas makes it easier to evaluate the results.
- Baseline clinical and pathologic factors are associated with both disease control and quality of life outcomes in prostate cancer patients. The baseline data necessary to make meaningful comparisons between patients has been identified. Numerous factors are associated with clinical outcomes following treatment for prostate carcinoma.
Benefits for patients
By measuring the outcomes, the quality of care improves through the use of best practices. Transparency is also helpful for patients as it’s crucial for most to know about treatment efficacy and possible side effects when making decisions.
For example, in some treatments the side effects can be inconvenient while their benefit can be correspondingly quite moderate. Some patients may want all possible treatment regardless of the side effects, which may in the case of prostate cancer include impotence. Others may want to invest more in their quality of life and thus take a slightly increased risk. When the doctor and the patient have all the possible data at their disposal, it’s easier to make the decision that suits them best, based on the doctor's recommendation.
While it’s true that the cost of cancer treatments has doubled since 1995, the outcomes are far better. As mentioned before, productivity loss has decreased because of reductions in mortality in the working-age population. Similarly, new therapies can for example cause less side effects, which is good for the quality of life and work ability. These health benefits also generate savings and higher tax-revenues to the society.
A well-known example of an unsuccessful value-based healthcare implementation is from Karolinska in Stockholm, Sweden. Karolinska is regarded as one of the leading hospitals globally, which is why the chaos resulting from poorly implemented value-based healthcare concepts made headlines across the world.
Anna Gustafsson and Lisa Röstlund, two journalists working for a major Swedish daily newspaper, Dagens Nyheter, published a book in May 2019 on the experiences at Karolinska titled “Kampen om Karolinska: Konsulterna”. In the book, they detail the problems caused by new management concepts based on value-based healthcare. Those concepts emphasize the cost of treatments in addition to clinical outcomes. While there is nothing inherently wrong with the idea of considering costs, or prioritization, the implementation at Karolinska had major shortcomings.
The building of the new Karolinska hospital had already proven difficult with massive budget overruns and poor planning (for example, the architects wrongly assumed patient flow would be so effective that no waiting rooms would be needed). In addition to this, problems with the new model materialized.
In retrospect, many of these problems were rooted in poor understanding of the realities of working in a hospital setting – in other words, they came from a lack of real-world experience. For instance, the developers of the new model failed to recognize that many of the patients were suffering from multiple chronic conditions, which was not properly included in the models which administrators used to prioritize patients.
This oversight led to prolonged waiting times. When moving into New Karolinska, 350 children had been in the queue for surgery for more than 90 days. Almost a year later, the queue had grown to 800 children. Pancreatic cancer patients in Germany and Denmark are typically operated on within 14 days, but in Sweden the limit was raised to 36 days, within which Stockholm county (where New Karolinska is located) could only deal with a third of cases in 2017.
The key lesson to be learned from Karolinska is that when re-designing the management practices of a healthcare organization – whether value-based healthcare related or not – those practices need to be grounded in both best practice and proven clinical practices.
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After completing Chapter 2, you should be able to:
- Understand the concept of value vs volume in healthcare
- Explain four approaches to value-based healthcare being pursued by healthcare providers today
- Understand how data is the key enabler for making value-based healthcare work in practice